Sustainable Environmental Protection Technologies: Contaminant Biofiltration, Adsorption and Stabilization [1st ed.] 9783030477240, 9783030477257

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Pranas Baltrėnas Edita Baltrėnaitė

Sustainable Environmental Protection Technologies Contaminant Biofiltration, Adsorption and Stabilization

Sustainable Environmental Protection Technologies

Pranas Baltrėnas • Edita Baltrėnaitė

Sustainable Environmental Protection Technologies Contaminant Biofiltration, Adsorption and Stabilization

Pranas Baltrėnas Vilnius Gediminas Technical University Vilnius, Lithuania

Edita Baltrėnaitė Vilnius Gediminas Technical University Vilnius, Lithuania

ISBN 978-3-030-47724-0 ISBN 978-3-030-47725-7 https://doi.org/10.1007/978-3-030-47725-7

(eBook)

© Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

The global stability crisis of ecosystems manifests itself in the growth of a technogenic load and the deteriorated quality of life, particularly in the concentrated centres of urbanization and industry. Therefore, the need to discuss the importance of technogenesis and sustainable environmental protection technologies is essential. The concept of the contamination footprint and the methods of evaluating it are presented prior to the further discussion on biogeochemical and engineered barriers that have become the basis for sustainable environmental protection technologies. The study introduces and discusses the sustainability of environmental protection technologies at three levels, including natural technologies, the analysis of using natural materials in environmental engineering systems and the components ensuring the sustainability of environmental engineering systems. The book provides the classification of barriers and defines the position of natural and artificial biogeochemical barriers considering this classification as an example of the first level sustainability of environmental protection technologies. The use of sustainable natural materials (based on the examples of biochar) in environmental engineering systems is presented as the second level sustainability of environmental protection technologies. The following of the study proceeds with the discussion on the second sustainability level of environmental protection technologies and focuses on the use of natural materials for contaminant removal from the aqueous media, e.g. describes potentially toxic elements found in water streams and concentrates on the employment of biochar as a sustainable material for removing pollutants. The third level sustainability of environmental protection technologies is presented as an example of the biological treatment of the air thus discussing the major principles and applications of the biological air treatment method, the loads used, their characteristics and influence on air treatment effectiveness and the analysis of biological air treatment facilities, including their influence on air treatment effectiveness. The study analyses and evaluates the findings of the conducted research into the impact of the humidified packing material of air treatment biofilters on air treatment effectiveness and the distribution of temperature, acidity (ph) and oxygen in the packing material. The book describes the microorganisms oxidizing volatile compounds in air treatment biofilters, looks at the specificity of factors v

vi

Preface

determining the vital activity of microorganisms, introduces analytical equipment for investigating the physical properties of the packing material of air treatment biofilters and deals with similar types of the biofilter under laboratory conditions. The work assesses analytical equipment for aerodynamic parameters (air flow rates and aerodynamic resistance), examines air flow rates and aerodynamic resistance of air treatment biofilters as well as presents the results of experimental research. The study reports the findings of the cellulase and xylanase activity of the microorganisms in order to achieve the microorganisms present in the packing material should self-provide with nutrients and focuses on the selection and properties of the microorganisms (bacteria, microscopic fungi, yeast) capable of purifying biogas during the process of drying organic waste. Thus, the influence of temperature and pH parameters on the activity of the microorganisms found in the air treatment biofilter have been identified and filter odours have been considered applying the olfactometric method. The book analyses the theory of biological treatment principles, presents the models describing biofiltration processes and simulation programs and has the following distinctive features. The sustainability of environmental protection technologies is considered at three levels, including natural technologies (ecotechnologies), the analysis of using natural materials in environmental engineering systems and the components ensuring the sustainability of environmental engineering systems. The study discusses the application of biochar as a sustainable material used for decreasing the negative effect of climate change and documents the removal of contaminants from the air and water thus stabilizing them in the soil. The cases of biofiltration systems demonstrate that engineering solutions can be used for the most efficient performance of the components ensuring the sustainability of systems. The development of sustainable technologies from the laboratory to the pilot scale and simulating the cases of biofiltration systems are presented. The study is a valuable tool for scientists working in the field of environmental engineering and for environmental protection experts. The book, as a source of scientific knowledge, can be successfully applied for doctoral and post-graduate studies. Reviewed by: Dr. Ing. Oleksandr Sigal, Kiev, Ukraine Prof. Dr. Habil. Donatas Butkus, Vilnius Gediminas Technical University, Lithuania Prof. Dr. Dainius Steponavičius, Vytautas Magnus University, Kaunas, Lithuania Vilnius, Lithuania

Pranas Baltrėnas Edita Baltrėnaitė-Gedienė

Introduction

The global stability crisis of ecosystems manifests itself in the growth of their technogenic load and the deteriorated quality of life, particularly in the concentrated centres of urbanization and industry. The intensive industrial development and urbanization as well as the negligible return of hazardous components to the deeper layers of the Earth increase the contamination load on the noosphere. Along with a rise in both human population and gross domestic product by approximately 72 and 225%, respectively, the overall extraction of chemical elements has exceeded 75%. An upturn in the withdrawal of chemical elements causes a growth in the load of contaminants, which results in an increase of the urban contaminant footprint. The need for reducing the spread and mobility of contaminants is growing. If not avoided, contaminants can only be stabilized by reducing their migration flows by means of natural and engineered barriers. Moreover, for maintaining sustainable development, natural materials should be used as media in environmental protection technologies. The study begins with a description of technogenesis effect and the need for developing sustainable environmental protection technologies (Chaps. 1 and 2). The rising level of contamination is assessed with reference to the contamination footprint while offering the use of biogeochemical barriers (e.g. based on the bioaccumulation properties of plants alone or mixed with contaminant stabilizing amendments) that are commonly perceived as natural and therefore sustainable technologies known as ecotechnologies. The book discusses the major trends towards technogenesis, which resulted in the contamination footprint in the twenty-first century and presents the concept of the contamination footprint and methods for evaluating it. The classification of barriers provided and the position of natural and artificial biogeochemical barriers disclosed in this classification are defined as the example of the first level sustainability of environmental protection technologies. The second level sustainability of environmental protection technologies is related to the employment of sustainable natural materials in environmental engineering systems (Chaps. 3 and 4). The chapters focus on using such materials in waste management, on the stabilization of the polluted soil and contaminant removal vii

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Introduction

from the aqueous media. The study describes manufacturing biochar from various kinds of waste materials containing potentially toxic elements (e.g. sewage sludge and waste from paper manufacturing), conducts a comparative analysis of its properties, investigates the stability of potentially toxic elements in biochar, evaluates environmental risk and discusses the results of using biochar for the purpose of stabilizing metallic elements in the polluted soils, the removal of contaminants from the aqueous media and the effect of biochar on the bioavailability of elements in the soil. This book is the first work describing the use of biochar in environmental protection technologies from various perspectives. Biochar was included in the Intergovernmental Panel on Climate Change report in 2018 as negative emission technology but is introduced in this book as a material used for sustainable technological applications. The third sustainability level includes the components ensuring the environmental sustainability of engineering systems (Chap. 5) and portrays a biofiltration system as an example thus analysing the principles of system operation, structural solutions and criteria describing their effectiveness as well as variations in aerodynamic characteristics so as to ensure the most effective performance of sustainable materials (biofiltration substrate) (Chaps. 6 and 7) as well as the functioning of other system components (microorganisms) (Chap. 8) guaranteeing the sustainability of the systems. The operational characteristics are also discussed in terms of engineering and technological performance along with the above three sustainability levels of environmental protection technologies. The description of the developmental stages of technologies (sustainability in particular) is a very important point primarily referring to the stage of transition from the laboratory to the prototype. This technological development is shown in the light of analysing the structures of biofiltration systems on the lab and prototype scales (Chap. 9). In both cases, the properties (characteristics) of the components of the system as well as aerodynamic and temperature regimes are discussed thus emphasizing the sustainability of performance and the properties of various materials and components. For this purpose, mathematical models adapted for describing the above-considered systems are applied.

Contents

1

The Importance of Technogenesis and Sustainable Environmental Protection Technologies . . . . . . . . . . . . . . . . . . . . . . 1.1 Technogenesis and the Extent of the Chemical Elements Entering the Noosphere . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Technogenic Flows of Pollutants: An Example of Potentially Toxic Elements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.1 Sources of Potentially Toxic Elements . . . . . . . . . . . . . . . 1.2.2 PTE Transportation and Removal from the Atmosphere . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.3 PTEs in the Soil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.4 Soil–Plant Transfer of PTEs . . . . . . . . . . . . . . . . . . . . . . 1.2.5 PTEs Uptake and Accumulation in Trees . . . . . . . . . . . . . 1.2.6 Hazards and Exposure of PTEs Pollution . . . . . . . . . . . . . 1.2.7 Transport of PTEs Within Environmental Compartments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.8 Dispersion of Pollutants . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.9 Deposition of Pollutants . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Evaluating Pollution Level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.1 Pollution Assessment Parameters Describing Soil Contamination by PTEs . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.2 Dynamic Factor Method for Transferring Metallic Elements in the Soil–Plant System . . . . . . . . . . . . . . . . . 1.4 Footprints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4.1 Ecological Footprint . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4.2 Nutrient Footprint . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4.3 Chemical Footprint . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4.4 Urban Contamination Footprint . . . . . . . . . . . . . . . . . . . . 1.5 Geochemical Barriers Preventing from the Spread of Pollutants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6 Sustainable Environmental Protection Technologies . . . . . . . . . . .

1 1 5 5 6 8 10 12 14 17 19 21 22 22 23 28 28 30 30 32 33 34 ix

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3

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Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Natural and Semi-Natural Barriers . . . . . . . . . . . . . . . . . . . . . . . . 2.1.1 Snow Cap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.2 Soil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.3 Mosses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.4 Bark and Annual Tree Rings . . . . . . . . . . . . . . . . . . . . . . 2.1.5 Lichens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.6 Precipitation (Rain and Snow) . . . . . . . . . . . . . . . . . . . . 2.2 Natural Barriers as an Example of Retention for Aerogenic Contamination from the Oil Refinery . . . . . . . . . . . . . . . . . . . . . . 2.2.1 Oil Refineries and Typical Pollutants . . . . . . . . . . . . . . . . 2.2.2 Deposit Media in the Vicinity of the Oil Refinery . . . . . . . 2.3 Natural Biogeochemical Barriers as a Retention Example of Aerogenic Pollution Caused by Waste Incineration Plant . . . . . . 2.4 Artificial Biogeochemical Barriers as Phytoremediation Potential of Herbaceous Plants . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.1 Tolerance to PTEs in the Plants of the Brassicaceae Family . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.2 The Accumulation of Cu, Pb, Cd and Zn in the Above- and Under-Ground Parts of Plants . . . . . . . 2.4.3 Extractability or Bioavailability Changes in Time . . . . . . . 2.4.4 Seedling Preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.5 Acropetal and Basipetal Metal Translocation . . . . . . . . . . 2.4.6 The Accumulation of PTEs in Treated Plants . . . . . . . . . . 2.4.7 PTEs in the Soil and Sewage Sludge . . . . . . . . . . . . . . . . 2.4.8 Modelling the Removal of PTEs from Plants . . . . . . . . . . Sustainable Natural Materials and Their Importance for Waste Management and Stabilization of Soil Pollution . . . . . . . 3.1 The Second Sustainability Level of Environmental Protection Technologies. A Carbon Footprint of Wood as a Feedstock for Biochar . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.1 Carbon Footprint Assessment of Woody Products . . . . . 3.1.2 Life Cycle Assessment . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.3 The Potential for Production of Biochar from Wood Wastes . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Is Biochar a Sustainable Natural Material? . . . . . . . . . . . . . . . . . 3.2.1 The Properties and Use of Biochar for Soil Improvement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.2 Pollutants That May Be Contained in Biochar . . . . . . . . 3.2.3 European Policies and Regulations Related to Biochar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 The Stability of Chemical Elements in Biochar . . . . . . . . . . . . . .

39 40 44 48 48 49 51 51 52 52 55 67 75 76 78 80 81 84 85 87 87

.

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. . .

93 94 96

. 102 . 103 . 104 . 107 . 108 . 109

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3.3.1 3.3.2 3.3.3

3.4

3.5

4

Sewage Sludge as a Potential Biochar Feedstock . . . . . . Industrial Sewage Sludge and Its Composition . . . . . . . . The Process of Leaching Metals from Biochar Produced from Industrial Sludge . . . . . . . . . . . . . . . . . . 3.3.4 Comparison of the Physical–Chemical Properties of Biochar and PTE Concentrations with the European Biochar Certificate . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.5 Determining PTE Leaching from Biochar According to ‘Characterization of Waste: Leaching Behaviour Tests—Up-Flow Percolation Test’ . . . . . . . . . . . . . . . . 3.3.6 Determining PTE Leaching from Biochar According to ‘Characterization of the Two-Stage Batch Test at a Liquid-to-Solid Ratio of 2 and 8 L/kg’ . . Using Biochar for Stabilizing Metallic Elements in the Soil . . . . . 3.4.1 Biochar and Soil Restoration . . . . . . . . . . . . . . . . . . . . 3.4.2 Study into the Effects of Biochar on Potentially Toxic Elements Present in the Soil . . . . . . . . . . . . . . . . 3.4.3 Factors Regulating Leaching . . . . . . . . . . . . . . . . . . . . . 3.4.4 Characteristics of Soil Before PTE Immobilization . . . . . 3.4.5 Comparing the Properties of Biochar Taken from a Relatively Clean Environment and Rail Sleepers . . . . . . 3.4.6 Leaching Study of the Soil Mixed with Two Types of Biochar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Potentially Toxic Elements and Dissolved Organic Carbon in Biochar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5.1 The Leachability of PTEs from Biochar . . . . . . . . . . . . . 3.5.2 Leaching Dissolved Organic Carbon from Biochar . . . . .

Sustainable Natural Materials Used for Adsorbing Pollutants from the Aqueous Medium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Potentially Toxic Elements in the Aquatic Environment . . . . . . . 4.1.1 Potentially Toxic Elements in Surface Runoff . . . . . . . . 4.1.2 Factors Affecting the Load and Transport of Potentially Toxic Elements in Surface Runoff of Urban Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.3 Different Surfaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.4 The Influence of Storm Parameters on the Concentrations of Potentially Toxic Elements . . . 4.1.5 The Seasonality of the Concentrations of Potentially Toxic Elements . . . . . . . . . . . . . . . . . . . . 4.2 Adsorption and Desorption Processes of PTEs in the Aquatic Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.1 Adsorption Mechanisms . . . . . . . . . . . . . . . . . . . . . . . . 4.2.2 Theoretical Aspects of Adsorption . . . . . . . . . . . . . . . . 4.2.3 Isotherm Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. 109 . 110 . 111

. 113

. 116

. 118 . 120 . 120 . 121 . 123 . 123 . 125 . 131 . 135 . 137 . 138 . 143 . 143 . 144

. 146 . 147 . 148 . 149 . . . .

149 150 152 154

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4.3 4.4

4.5

4.6 5

4.2.4 Henry’s Law Isotherm . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.5 Two-Parameter Isotherms . . . . . . . . . . . . . . . . . . . . . . . 4.2.6 Three-Parameter Isotherms . . . . . . . . . . . . . . . . . . . . . . 4.2.7 Modelling the Multi-component Adsorption Process . . . Geochemical Models for Estimation of Bioavailability of PTEs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Biochar as the Potential Adsorption Medium for PTEs . . . . . . . . 4.4.1 Biochar Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4.2 The Characteristics of Biochar Properties Influencing Adsorption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4.3 The Major Mechanisms and Parameters for Controlling PTE Adsorption by Biochar . . . . . . . . . Adsorption Behaviour of PTEs on Biochar . . . . . . . . . . . . . . . . . 4.5.1 Freundlich Isotherms and Extended Adsorption Equilibrium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5.2 Redlich–Peterson Isotherms and Extended Adsorption Equilibrium . . . . . . . . . . . . . . . . . . . . . . . . 4.5.3 A Comparison of the Results of Freundlich and Redlich Peterson Isotherms . . . . . . . . . . . . . . . . . . The Sustainable Role of Biochar . . . . . . . . . . . . . . . . . . . . . . . .

Biotechnology as Sustainable Environmental Protection Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 The Principles and Application of the Biological Air Treatment Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 The Properties of the Packing Materials Used for Biological Air Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 The Analysis of the Structures of Biological Air Treatment Equipment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.1 Membrane Bioreactors . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.2 Droplet Biofilters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.3 Bioscrubbers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.4 Biofilters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 The Effect of the Packing Material and Structure on Air Treatment Effectiveness . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 Methods Applied for Investigating the Physical and Aerodynamic Properties of Packing Materials . . . . . . . . . . . . . . . 5.6 Microorganisms Oxidizing Volatile Compounds in Biofilters and the Properties of Factors in Determining Vital Activity of Microorganisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7 Theoretical Basis for the Biological Air Treatment Process . . . . . 5.7.1 Theoretical Basis for Pollutant Degradation in the Biofilter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7.2 Theoretical Calculations of the Durability of the Packing Material . . . . . . . . . . . . . . . . . . . . . . . .

. . . .

155 155 158 159

. 160 . 162 . 165 . 166 . 168 . 169 . 170 . 177 . 183 . 185 . 187 . 187 . 192 . . . . .

195 196 197 199 201

. 205 . 207

. 212 . 220 . 222 . 228

Contents

5.8

6

xiii

Mathematical Models and Simulation Programmes for Biofiltration Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.8.1 A Mathematical Model for Air Flow Between Vertical Lamellar Plates . . . . . . . . . . . . . . . . . . . . . . . . 5.8.2 A Mathematical Model for Air Flow Passing Between Wavy Lamellar Walls . . . . . . . . . . . . . . . . . . . 5.8.3 A Theoretical Model for Filtering Gas in the Porous Medium . . . . . . . . . . . . . . . . . . . . . . . . .

. 230 . 230 . 241 . 249

The Major Properties of Natural Materials in Biofiltration Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 Analytical Equipment for Investigating the Physical Properties of the Packing Material of Biological Air Treatment Filters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1.1 Basic Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1.2 Equipment Used for Research Purposes . . . . . . . . . . . . . . 6.1.3 Characteristics of the Device . . . . . . . . . . . . . . . . . . . . . . 6.1.4 General Technical Characteristics . . . . . . . . . . . . . . . . . . 6.1.5 Quantachrome Instruments Automatic Mercury Porosimeter PM-33-12 . . . . . . . . . . . . . . . . . . . 6.2 Air Treatment Biofilters Under Laboratory Conditions . . . . . . . . . 6.2.1 Operating Principle . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2.2 Determining the Humidity of the Packing Material . . . . . . 6.3 The Humidity of Packing Materials in the Inlet, Outlet and Between the Lamellar Plates of Biological Air Treatment Filters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.1 The Relative and Absolute Humidity of the Material . . . . 6.3.2 The Porosity of the Material . . . . . . . . . . . . . . . . . . . . . . 6.3.3 Capillary Humidification . . . . . . . . . . . . . . . . . . . . . . . . 6.3.4 The Density of the Material Surface . . . . . . . . . . . . . . . . 6.3.5 Sorption Parameters of the Packing Material (Diameter, Surface Area and Volume of Pores) . . . . . . . . 6.3.6 The Humidity of the Packing Material and Air Using Straight Lamellar Plates and Applying Natural Microorganisms and Separately Releasing Ammonia, Acetone and Xylene . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.7 The Humidity of the Packing Material and Air Using Straight Lamellar Plates and Applying the Selected Microorganisms and Separately Releasing Ammonia, Acetone and Xylene . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.8 The Humidity of the Packing Material and Air Using Wavy Lamellar Plates and Applying Natural Microorganisms and Separately Releasing Ammonia, Acetone and Xylene . . . . . . . . . . . . . . . . . . . . . . . . . . . .

259

259 262 263 269 270 275 277 277 281

283 283 284 286 288 291

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6.3.9

6.4

7

The Humidity of the Packing Material and Air Using Wavy Lamellar Plates and Applying Selected Microorganisms and Separately Releasing Ammonia, Acetone and Xylene . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.10 The Humidity of the Packing Material and Air Applying a Tubular Biofilter . . . . . . . . . . . . . . . . . . . . . The Distribution of Temperature, Acidity (pH) and Oxygen in the Packing Material of the Biological Air Treatment Filter . . . 6.4.1 The Scope of Research Elements: Assessed Parameters . 6.4.2 Determining the Temperature and pH of the Medium . . . 6.4.3 Determining Oxygen Content . . . . . . . . . . . . . . . . . . . . 6.4.4 Determining Biofilter Parameters . . . . . . . . . . . . . . . . . 6.4.5 The pH, Temperature and Content of Oxygen Dissolved in the Medium when Applying Straight Lamellar Plates and Natural Microorganisms . . . . . . . . . 6.4.6 The Distribution of Temperature, Acidity (pH) and Oxygen Throughout the Entire Volume of the Packing Material when Using the Selected Microorganisms . . . . . 6.4.7 The Distribution of Temperature, Acidity (pH) and Oxygen Throughout the Entire Volume of the Packing Material when Applying Wavy Lamellar Plates and Using Natural Microorganisms . . . . . . . . . . . . . . . . . . . 6.4.8 The Distribution of Temperature, Acidity (pH) and Oxygen Throughout the Entire Volume of the Packing Material when Applying the Selected Microorganisms . . 6.4.9 The Distribution of Temperature, Acidity (pH) and Oxygen Throughout the Entire Volume of the Packing Material when Applying the Biofilter with the Tubular Structure of the Plates . . . . . . . . . . . . . . . . . . . . . . . . . 6.4.10 The Physical Properties of Biochar when Applying the Biofilter with the Tubular Structure of the Plates . . . . . .

The Importance of Biofiltration System Performance Parameters for the Effective Functioning of Components and System Sustainability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1 The Aerodynamic Resistance of the Biological Air Treatment Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1.1 Aerodynamic Resistance Using Straight Lamellar Plates and Natural Microorganisms . . . . . . . . . . . . . . . . 7.1.2 Aerodynamic Resistance Using Straight Lamellar Plates and Selected Microorganisms . . . . . . . . . . . . . . . 7.1.3 Aerodynamic Resistance Using Wavy Lamellar Plates and Natural Microorganisms . . . . . . . . . . . . . . . . 7.1.4 Aerodynamic Resistance Using Wavy Lamellar Plates and Selected Microorganisms . . . . . . . . . . . . . . .

. 317 . 325 . . . . .

328 329 330 330 331

. 332

. 336

. 338

. 344

. 347 . 348

. 359 . 359 . 362 . 365 . 366 . 369

Contents

7.2

7.3

7.4

xv

Air Flow Rates in Biological Air Treatment Filters . . . . . . . . . . . . 7.2.1 Determining the Air Flow Permeability of the Packing Material . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.2 Air Flow Rates Using Straight Lamellar Plates, Natural Microorganisms and Separately Supplying Xylene, Ammonia and Acetone . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.3 Air Flow Rates Using Straight Lamellar Plates, Selected Microorganisms and Separately Supplying Xylene, Ammonia and Acetone . . . . . . . . . . . . . . . . . . . 7.2.4 Air Flow Rate Using Wavy Lamellar Plates, Natural Microorganisms and Separately Supplying Xylene, Ammonia and Acetone . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.5 Air Flow Rate Using Wavy Lamellar Plates, Selected Microorganisms and Separately Supplying Xylene, Ammonia and Acetone . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.6 Air Flow Rates Using a Tubular Biofilter . . . . . . . . . . . . . Air Treatment Effectiveness of Biological Filters . . . . . . . . . . . . . 7.3.1 Air Treatment Effectiveness Using Straight Lamellar Plates, Natural Microorganisms and Pollutants Such as Xylene, Ammonia and Acetone . . . . . . . . . . . . . 7.3.2 Air Treatment Effectiveness Using Straight Lamellar Plates, Selected Microorganisms and Pollutants Such as Ammonia, Xylene and Acetone . . . . . . . . . . . . . 7.3.3 Air Treatment Effectiveness Using Wavy Lamellar Plates, Natural Microorganisms and Pollutants Such as Ammonia, Xylene and Acetone . . . . . . . . . . . . . 7.3.4 Air Treatment Effectiveness Using Wavy Lamellar Plates, Selected Microorganisms and Pollutants Such as Ammonia, Xylene and Acetone . . . . . . . . . . . . . 7.3.5 Air Treatment Effectiveness Using Tubular Biofilters, Natural and Selected Microorganisms and Pollutants Such as Xylene and Acetone . . . . . . . . . . . . . . . . . . . . . . Odours Produced by Biological Air Treatment Filters . . . . . . . . . . 7.4.1 Odour Identification when Applying the Olfactometry Method . . . . . . . . . . . . . . . . . . . . . . . . 7.4.2 Odour Identification when Applying the Olfactometer and Using the Biofilter with Straight Lamellar Plates . . . . 7.4.3 Odour Identification when Applying the Olfactometer and Using the Biofilter with Wavy Lamellar Plates . . . . . . 7.4.4 Odour Identification when Applying the Olfactometer and the Tubular Biofilter . . . . . . . . . . . . . . . . . . . . . . . .

373 373

374

377

379

385 387 388

390

394

398

401

406 412 413 418 423 428

xvi

8

Contents

Natural and Inoculated Microorganisms as Important Component for Sustainability of Biofiltration System . . . . . . . . . . . 8.1 The Selection and Properties of Microorganisms (Bacteria, Microscopic Fungi, Yeast) Capable of Removing Organic and Inorganic Volatile Compounds from the Polluted Air in the Biofilters Under Laboratory Conditions . . . . . . . . . . . . . . . 8.1.1 Screening Micromycetes Capable of Growing Under the Effect of Volatile Compounds . . . . . . . . . . . . 8.2 Cellulase and Xylanase Activity of Microorganisms to Provide them with the Nutrients Contained in the Biopacking Material of the Biofilter Under Laboratory Conditions . . . . . . . . . . . . . . . 8.2.1 Quantitative Evaluation of Cellulase Complex Activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3 The Effect of Temperature and pH on the Activity of Microorganisms Present in the Biofilter Under Laboratory Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3.1 Micromycetes Ability to Grow at Different Temperatures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3.2 Yeast Ability to Grow at Different Temperatures . . . . . . 8.3.3 Bacteria Ability to Grow at Different Temperatures . . . . 8.3.4 pH Effect on the Activity of Biofilter Microorganisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4 Microorganisms Abundance and the Varying Species in the Diversely Structured Biofilters Under Varying Packing Materials and the Removal of Airborne Volatiles Under Laboratory Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4.1 The Development of Microorganisms and Varying Species in the Laboratory Biofilter with Straight Lamellar Plates Covered with the Packing Material of Non-woven Cork Under the Removal of Airborne Volatiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4.2 The Development of Microorganisms and Varying Species in the Laboratory Biofilter with Straight Lamellar Plates Covered with the Packing Material of Wood Fibre Under the Removal of Airborne Volatiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4.3 The Development of Microorganisms and Varying Species in the Laboratory Biofilter with Straight Lamellar Plates Covered with the Packing Material of Wood Fibre and Linen Fabric Under the Removal of Airborne Volatiles . . . . . . . . . . . . . . . . . . . . . . . . . .

. 433

. 434 . 434

. 437 . 442

. 444 . 444 . 444 . 444 . 445

. 451

. 451

. 454

. 456

Contents

xvii

8.4.4

8.4.5

8.4.6

8.4.7

8.4.8

8.4.9

8.4.10

8.4.11

9

The Abundance of Microorganisms and Varying Species in the Laboratory Biofilter with Wavy Lamellar Plates Covered with the Packing Material of Wood Fibre and Linen Fabric Under the Removal of Airborne Volatiles . The Abundance of Microorganisms and Varying Species in the Laboratory Biofilter with Wavy Lamellar Plates Covered with the Packing Material of Non-woven Cork and Wood Fibre Under the Removal of Airborne Volatiles . . . . . . . . . . . . . . . . The Abundance of Microorganisms and Variations in Dominating Species in the Laboratory Biofilter with Straight Lamellar Plates and Selected Microorganisms Under the Removal of Airborne Volatiles . . . . . . . . . . . The Abundance of Microorganisms and Variations in Dominating Species in the Laboratory Biofilter with Wavy Lamellar Plates and Selected Microorganisms Under the Removal of Airborne Volatiles . . . . . . . . . . . The Abundance of Natural Microorganisms and Variations in Species in the Tubular Air Treatment Laboratory Biofilter Containing Biochar Produced of Birch and Pine Wood Incinerated at Different Temperatures Under the Removal of Airborne Volatiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Abundance of Natural Microorganisms and Variations in Species in the Tubular Structure of the Plate of the Laboratory Biofilter Filled with Pine Wood Biochar (Pf6) and Wood Fibre Under the Removal of Airborne Volatiles . . . . . . . . . . . . . . . . The Abundance of Microorganisms and Variations in Species in the Tubular Air Treatment Biofilter Filled with Pine Biochar (Pf6), Wood Fibre and Selected Microorganisms Under the Removal of Airborne Volatiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Abundance of Microorganisms and Variations in Species in the Tubular Air Treatment Biofilter Filled with Birch Biochar (Pf6) and Fibre Under the Removal of Xylene from the Air . . . . . . . . . . . . . . .

. 459

. 461

. 463

. 466

. 471

. 473

. 476

. 479

Technological Development from the Model to the Prototype: An Example of the Biofiltration System . . . . . . . . . . . . . . . . . . . . . . . 9.1 Schemes for Operating Pilot Biofilter Structures . . . . . . . . . . . . . . 9.1.1 The Operational Principles of the Biofilters with Straight and Wavy Lamellar Plates . . . . . . . . . . . . . 9.1.2 The Operational Principle of the Tubular Biofilter . . . . . . 9.2 Applied Analytical Methods and Equipment . . . . . . . . . . . . . . . . . 9.2.1 Air Flow Permeability in the Biofiltration System . . . . . .

483 483 483 486 486 493

xviii

9.3

9.4

9.5

9.6 9.7

Contents

9.2.2 Aerodynamic Resistance of the Biofiltration System . . . . . Aerodynamic Parameters for the Packing Materials of Pilot Biofilters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.3.1 The Porous Structures of Biochar Samples Obtained by Testing a Tubular Pilot Biofilter Supplied with Different Types of Pollutants . . . . . . . . . . . . . . . . . . 9.3.2 Microscopic Structures of Non-woven Cork (NWC) Samples Obtained when Testing Pilot Biofilters with Straight and Wavy Lamellar Plates Supplied with Different Types of Pollutants . . . . . . . . . . . . . . . . . . 9.3.3 Aerodynamic Resistance and Air Pressure in the Inlet and Outlet Ducts of Pilot Biofilters . . . . . . . . . . . . . . . . . Microbiological Properties of the Packing Materials of Pilot Biofilters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.4.1 Activity of the Selected Microorganisms Considering Temperature and Other Physical-Chemical Parameters in Pilot Biofilters with Straight and Wavy Lamellar Plates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.4.2 Activity of the Selected Microorganisms Considering the Temperature and Other Physical-Chemical Parameters for Pilot Tubular Biofilters . . . . . . . . . . . . . . . Air Treatment Effectiveness of Pilot Biofilters . . . . . . . . . . . . . . . 9.5.1 Air Treatment Effectiveness of the Pilot Biofilter with Straight Lamellar Plates . . . . . . . . . . . . . . . . . . . . . 9.5.2 Air Treatment Effectiveness of the Pilot Biofilter with Wavy Lamellar Plates . . . . . . . . . . . . . . . . . . . . . . . 9.5.3 Air Treatment Effectiveness of the Pilot Tubular Biofilter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Assessing Odours in Pilot Biofilters . . . . . . . . . . . . . . . . . . . . . . . Created and Manufactured Lamellar-Plate-Structure Pilot Biofilters Equipped with the Capillary Humidification System of the Packing Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

493 494

494

498 503 505

505

514 519 519 521 524 527

531

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 541 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 551 Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 639

About the Authors

Habil Pranas Baltrėnas senior researcher at the Institute of Environmental Protection, founder of the Institute of Environmental Protection and the Department of Environmental Protection of Vilnius Gediminas Technical University, a member of three international Academies of Sciences, chief editor of the international Journal of Environmental Engineering and Landscape Management, ISSN 1648-6897, a member of the editorial boards of five international journals, chief editor of Proceedings of Conference for Junior Researchers based on the material of the yearly conference Science— Future of Lithuania, head of the conference Environmental Engineering Organization Committee, head of Committee of Doctoral Studies in the Scientific Field of Environmental Engineering, head of the Public Environmental Protection Commission in the Vilnius City Council, a member of the Council of the Union of Lithuanian Scientists, chairman of the Environmental Protection Committee No. 36 of the Lithuanian Standardization Department. Research areas: complex theoretical and experimental studies of the environmental technosphere, process modelling and the development of the environment protection technologies, including the control over stationary and mobile air and soil pollution sources as well as waste and effluents, investigation of noise sources and electromagnetic fields, and development of pollution reducing technologies and equipment. He established the Department of Environmental Protection, the Institute of Environmental Protection, and the laboratory of the Environmental Protection and Work Conditions in VGTU and was the founder of environmental protection engineering field in Lithuania. P. Baltrėnas made research visits to Weimar and Mikkeli higher schools as well as to Rostock (Germany), Dresden (Germany), Hamburg–Harburg (Germany), Lulea (Sweden), Illinois (USA) and Ancona (Italy) universities and is a Lithuanian representative (coordinator) of the international programs, such as COST, INTERREG, 7th Framework, BPD, MUNDUS and TEMPUS. xix

xx

About the Authors

Under the supervision of Prof. Baltrėnas, 19 theses for Doctor’s degree were defended. In 1994, P. Baltrėnas was the winner of the Lithuanian Republic prize for the achievements in research, while in 2000 he was awarded the medal of M. Lomonosov, and in 2003 conferred an Honorary Doctor’s title at Saint Petersburg Academy of Sciences. In 2007, he was awarded the World Intellectual Property Organization (Geneva, Switzerland) Award Certificate in recognition of his outstanding achievements as an author for inventions. For the merits in environmental protection in the Lithuanian capital city (Vilnius), he was awarded with the Saint Christopher statue. He was elected as foreign member for active cooperation at the Ukrainian Academy of Civil Engineering. For the merits to Vilnius and Lithuanians, he was awarded with the second class medal. Prof. Baltrėnas is the author and co-author of 680 publications, including 19 monographs, 3 textbooks, 27 analytical and review methodical works, as well as 365 research papers, including 97 papers published abroad, and 104 certificates and patents.

Edita Baltrėnaitė-Gedienė Doctor of Sciences in the Scientific Field of Environmental Engineering and Landscape Management, is Professor in Vilnius Gediminas Technical University of the Department of Environmental Protection and Water Engineering, senior researcher at the Institute of Environmental Protection in Vilnius Gediminas Technical University, scientific leader of the Laboratory of Biochar Environmental Technologies and obtained the diploma of Bachelor and international (in English) Master of Sciences in Vilnius Gediminas Technical University. In 2007, she defended a thesis named Investigation and Evaluation of the Transfer of Heavy metals from Soil to the Tree. Since 2007, she has been a scientific secretary of the international Journal of Environmental Engineering and Ecological Science, a member of the Editorial Board of the Journal published by Romanian Academy of Science, Annals—Series on Chemistry Sciences, a member of EISN-Institute, NJF, in 2017 appointed to the Agricultural and Biological Science Editorial Advisory Group at Cambridge Scholars Publishing; Senior member of Hong Kong Chemical, Biological and Environmental Engineering Society (HKCBEES); member of Vilnius International Rotary Club; Chair of selection committee for Dr. Arūnas ir Irena Draugeliai grant for environmental engineering students at Vilnius Gediminas Technical University. Edita delivers lectures to master’s degree students about the environmental protection technologies, anthropogenic impact on the environment, waste utilization, soil recovery technologies, clean technologies, soil remediation technologies and supervises doctoral students. She is also a member of the Committee for the research area of Environmental Engineering and a head/member of the committees for seven defended theses.

About the Authors

xxi

She was a supervisor of studies of 1 doctoral student from Italy, 24 bachelor’s and 12 master’s degree students as well as 2 post-doctoral and 9 student trainees from Lithuania, Belgium, Finland and Italy, supervise 3 doctoral students. She also delivers lectures in Helsinki University (Finland), Norwegian University of Life Sciences, Valencia Polytechnic University (Spain), Aalto University (Finland) and Southern Denmark University. She paid research visits to Norwegian University of Life Sciences, Slovenian Research Institute after Joseph Stephan and Latvian State Wood Chemistry Institute. She maintains close contacts and cooperates with other high schools in Europe and other countries of the world, such as Chinese Academy of Science (Institute of Urban Environment), Hyderabad University (India), KU Leuven University (Belgium), UNESCO-IHE (the Netherlands), the State Montclair University (USA), Swiss Federal Technological Institute in Zurich, Illinois Institute of Technology (USA), Helsinki University (Finland), the State Tomsk University (Russia), Barcelona University (Spain) and Ancona University (Italy). The author of 100 papers (47 of which are published in the Web of Science refereed journals having the citation index), scientific committee member of 3 international conferences in Australia, Poland and Turkey, chairperson of 5 international conferences, participant of more than 20 international conferences; 3 oral presentations in international conferences in the USA, China and Poland; the author/coauthor of the monographs Small Bioreactors for Management of Biodegradable Waste (Springer, 2018), The Sustainable Role of the Tree in Environmental Protection Technologies (Springer, 2016), Tvarus medžio vaidmuo aplinkos apsaugos technologijose (in Lithuanian) (Vilnius: Technika, 2016); 1 EU patent, 5 Lithuanian patents; the textbook Manufacturing Industries and Environmental Impact, 3 chapters in the books: Phytoremediation: Management of Environmental Contaminants; Plants, Pollutants and Remediation published by Springer. One of the editors of the special issue on Biochar as an option for sustainable resource management (EU COST Action TD1107 final publication 2017) in the Journal of Environmental Engineering and Landscape Management; board member of 11 PgD student defences, 1 graduated doctor in cooperation with Italian delle Marche University; supervisor of 2 PhD students, 2 post-doctoral students and 9 trainees from Finland, Italy, Belgium and Lithuania; member of 2 VGTU competence centres. Edita with two co-authors—Arvydas Lietuvninkas and Pranas Baltrėnas—were awarded the third prize for the monograph The Sustainable Role of the Tree in Environmental Protection Technologies in the monograph contest organized by Vilnius Gediminas Technical University, March 2018. In 2013–2014, Edita Baltrėnaitė was granted a young researcher grant for the work The Evaluation of heavy metals’ stability in biochar and, in 2007, a prize for the work Investigation and Evaluation of the Transfer of Heavy Metals from Soil to the Tree by the Lithuanian Academy of Sciences. Areas of interests: application of biogeochemical processes to the environmental protection technologies, evaluation of metals’ transportation in the ecosphere and thermal processing and application of lignocellulosic products in the environmental protection engineering.

Chapter 1

The Importance of Technogenesis and Sustainable Environmental Protection Technologies

The chapter discusses the major trends in technogenesis that caused the contamination footprint in the twenty-first century, defines the concept of the contamination footprint and the methods for evaluating it as well as formulates the concept and role of biogeochemical and engineered barriers forming a part of sustainable natural and engineering environmental protection technologies for decreasing the contamination footprint caused by technogenesis. The fundamental framework comprising the classification of biogeochemical and engineered barriers and their description is provided. The chapter explores the sustainability of environmental protection technologies at three levels, including natural technologies, the analysis of using natural materials in environmental engineering systems and the components ensuring the sustainability of environmental engineering systems.

1.1

Technogenesis and the Extent of the Chemical Elements Entering the Noosphere

The concept of the technosphere (gr. technetos—artificial) applies to the technical activity of humanity, including the Earth’s surface, its depths as well as near and far space. Lietuvninkas (2012a, b) describes the technosphere as a part of the biosphere modified by human technogenic activity that is a non-natural, technogenesis-related human activity. Technogenesis involves targeted changes in the biosphere due to human technical activity, which results in the transformation of the geochemical field and frequently in negative consequences for natural complexes and human health. According to scientific calculations, the mass of all man-made technical systems is tens of times higher than the Earth’s biomass, and the production of technogenesis exceeds that of natural ecosystems several times (Baltrėnas and Ščupakas 2007).

© Springer Nature Switzerland AG 2020 P. Baltrėnas, E. Baltrėnaitė, Sustainable Environmental Protection Technologies, https://doi.org/10.1007/978-3-030-47725-7_1

1

2

1 The Importance of Technogenesis and Sustainable Environmental Protection. . .

Fig. 1.1 Principal scheme for the system of the interaction between humanity and the environment (Baltrėnas and Ščupakas 2007)

Scientific technical revolution

Increase in the population of the Earth, urbanization Development of economic activity Natural resources Environmental pollution

Loss of natural resources Environmental protection

Human impact (technogenic activity) on the environment can be direct and indirect, intentional and unintentional, short-term and long-term, local, regional, global, mechanical, physical, chemical and biological. The consequences of the impact can be reversible and irreversible. The principal scheme for the interaction between man and the environment is presented in Fig. 1.1. The result of technogenic activity is a technogenic load in a particular area and is calculated applying Eq. 1.1 (Baltrėnas and Ščupakas 2007): P Ta KT ¼ P V ; TaN

ð1:1Þ

where KT—the value of the overall technogenic pollution indicator for the specified investigated area; ∑TaV—the overall technogenic pollution of the specified investigated area; ∑TaN—the overall technogenic pollution under the approved legislation. The prevention of pollution and the recovery of resources are becoming more important targets worldwide, because the intensity of mining materials has been growing to satisfy human needs since the industrial revolution. The main features of the current global ecosystem stability crisis include accelerating urbanization, food scarcity, the creation of genetically modified organisms, the development of the genetically modified products, the export of environmentally hazardous technologies and waste to the economically undeveloped and developing countries, the emergence of local ecologic conflicts and the ecologically motivated migration of the population. Yet in 2007, the main contemporary ecologic problems, their trends and forecasts by 2030 were defined in the following way (Baltrėnas and Ščupakas 2007): • A decline in the areas of natural ecosystems annually ranges between 0.5 and 1.0%, which may result in almost complete extinction on land.

1.1 Technogenesis and the Extent of the Chemical Elements Entering the Noosphere

3

• Variations in greenhouse gas concentrations in the atmosphere up to 1–2%, a further increase in greenhouse gas concentrations due to the decomposition of biota. • The depletion of the ozone layer, 1–2% annual thinning, an increase in ozone holes. • A reduction in the wooded areas, tropical deforestation from 18 mill. km2 in 1990 to 9–11 mill. km2 in 2030. • Technogenic growth in desert areas; on average over 60 thous. km2 per year considering that this trend may remain in the future due to lack of humidity in the soil and its subsequent pollution. • Soil degradation, erosion, salinization, acidification, pollutant accumulation, loss of fertility. • Rising water levels in the oceans from 1 to 2 mm per year, with the potential of annual acceleration up to 7 mm. • 5–7% annual rise in natural disasters and technogenic catastrophes, 10–15% annual increase in losses, 6–12% annual growth in casualties. • The extinction of biological species. • The depletion of ground and underground water resources, an increase in the amount of wastewater and pollution sources discharged into the environment, the exhaustion of other non-recovering natural resources. • The accumulation of pollutants in environmental components and living organisms, pollutant migration through nutritional (trophic) chains. • The degradation of life quality, the further spread of ecological diseases, particularly in the developing countries and densely populated agglomerations. In the context of growing industrial development, increased urban areas and the negligible return of potentially toxic elements (PTEs) to the deeper layers of the Earth, the pollution load is increasing in the noosphere. The need for reducing the mobility of pollutants (i.e. for increasing the immobilization of pollutants) is growing, considering persistent and long-term pollutants, e.g. PTEs in particular. Immobilization is one of the three innovative environmental protection technologies allowing pollutants to be retained in two main directions—using biosphere components (e.g. natural barriers) and engineering approaches (e.g. engineered barriers). PTEs extracted from the Earth enter the noosphere and are involved in natural–technogenic migration flows. The migration of chemical elements in the noosphere and the Earth’s crust (at least, 99% of its mass) are closely related to living matter. The biomass of terrestrial organisms makes approximately 99.5% of living matter while 90% of the biomass of terrestrial organisms consists of tree biomass (Lietuvninkas 2012a, b), which shows that forests (trees) play an important role in regulating climate change as well as are involved in the biogeochemical cycle of the elements. The latter becomes more important due to a decrease in environmental quality, an increase in the load of technogenic pollution and a higher contaminant footprint. More than 11 chemical elements (aluminium (Al), As, Cd, Cr, Cu, gold (Au), iron (Fe), Pb, Hg, Ni and Zn) are found in the database of the intensively mined, recycled

1296

Ba Co Ti Li

1207

2063

12310

5348

20779

12800

Hg Ni As Mn F

691

Cr Pb Mo Zn Cd Sn S

63

Cu Ag P

21471

56250

5.0E+04 0.0E+00

38793

112000

69300

1.5E+05 1.0E+05

156579

2.0E+05

115000

2.5E+05

301250

372857

3.5E+05 3.0E+05

227000

Technophilicity

4.0E+05

307071

5.0E+05 4.5E+05

421739 385714

1 The Importance of Technogenesis and Sustainable Environmental Protection. . .

4

Sr V

Be

Fig. 1.2 The technophilicity of chemical elements (calculated using 2016 World mining data provided by USGS 2017)

and consumed materials in the world. Over the 35-year period (from 1970 to 2004) characterized by an increase in both human population and gross domestic product (GDP measured in constant 2000 U.S. dollars) making 72 and 225%, respectively, the global extraction of chemical elements exceeded 75%. During the period from 1970 to 2004, an increase in the extraction of chemical elements was mainly caused by a rise in consumption, which was 3 times larger for Al and Cr, 2 times larger for Cu and Zn and around 1.75 times larger for Ni. An increase in the consumption of Pb by 1.5 times was lower (from 4 to 6 million metric tons). An increase in Cr and Ni consumption was closely related to a growth in demand for steel production. The extraction of Hg declined significantly during this period, whereas Cd extraction remained relatively constant (USGS 2008). The total output and use of chemical elements can be more precisely estimated when compared to the abundance of the chemical elements in the lithosphere (i.e. Clarke is mean concentration values for a chemical element in the given geosphere or geological object as discussed in Baltrėnaitė et al. (2012)). Such characteristic of a chemical element is described as its technophilicity, which shows the intensity of chemical element consumption (tons per year) with respect to its concentration in the lithosphere (Eq. 1.2). Ti ¼

Qi Cilit

ð1:2Þ

where Ti is the technophilicity of the element i; Qi is the annual amount of element i, extracted on the global scale, t; Cilit is the Clarke of element i in the lithosphere, %. Figure 1.2 presents technophilicity data on the chemical elements based on the data obtained in 2016. Among the chemical elements having technophilicity coefficients higher than 10,000, PTEs such as Cu, Cr, Pb, Zn and Cd can be observed (Fig. 1.2).

1.2 Technogenic Flows of Pollutants: An Example of Potentially Toxic Elements

5

A high technophilicity level is based on their intensive use to satisfy increasing demand for modern industrial society. The numerical value of the technophilicity of the chemical element is characteristic of the intensity of its use in regard to its abundance in the lithosphere. Along with the rapid development of the new fields of using chemical elements (e.g. military, space, advanced technologies), the technophilicity level of chemical elements increases. Among chemical elements, difference in technophilicity values is lower than Clarke values, which indicates that technogenesis leads to a reduction in geochemical contrast between the natural environment and the Earth. In other words, most technophilic elements are transferred and spread in various ways on the surface of the Earth at increasing levels. Therefore, technogenesis causes a rise in the number of chemical elements (including PTEs) on the surface of the Earth. Thus, the technophilicity value based on the quantity of the chemical elements extracted on the global scale can be an important factor in estimating the pollution load and the urban contamination footprint.

1.2 1.2.1

Technogenic Flows of Pollutants: An Example of Potentially Toxic Elements Sources of Potentially Toxic Elements

In the year 2000, the European emissions of PTEs from anthropogenic sources were estimated within the project ESPREME (http://espreme.ier.uni-stuttgart.de). The 2000 emission datasets for the analysed PTEs were prepared using emission factors in the pollutants emitted from the major emission sources, statistical data on the production of industrial goods and the consumption of raw materials (EMEP 2006). Some types of pollutant emissions such as the combustion of fuels in stationary sources, iron, steel or cement production were obtained from the EMEP/CORINAIR Atmospheric Emission Inventory Guidebook (http://reports.eea.eu.int/ EMEPCORINAIR3/en/) (UN ECE 2000). The conducted analysis shows that in the year 2000, the major anthropogenic sources of PTEs such as As, Cd, Cr, Ni and Pb emissions in Europe included the combustion of coal and oil in utility furnaces, industrial boilers, residential units, iron, steel and cement production (Pacyna 2007). Table 1.1 shows that the combustion of fuels to produce heat and electricity was the main emission source of As, Cd, Cr and Ni while the combustion of gasoline was the main source of Pb. Coal combustion in power plants contributed around 18% to total As in the emissions, and 17% contribution came from coal combustion in industrial boilers and small residential units. The World average As content in coals (coal Clarke of As) for the bituminous coals and lignites are 9.0  0.8 and 7.4  1.4 ppm, respectively. On an ash basis, these contents are higher: 50  5 and 49  8 ppm, respectively. Therefore, As is a very coalphile element: it has strong affinity to coal matter—organic and (or) inorganic but obligatory authigenic

6

1 The Importance of Technogenesis and Sustainable Environmental Protection. . .

Table 1.1 Atmospheric emissions of, Cd, Cr, Ni and Pb in Europe in 2000, t/y (EMEP 2006)

Fuel combustion to produce heat and electricity Non-ferrous metal Iron and steel production Waste disposal Other sources and cement production Gasoline combustion Sum

Arsenic (t/y) 391

Cadmium (t/y) 367

Chromium (t/y) 1394

Nickel (t/y) 3795

Lead (t/y) 1623

132 114 2 124

52 46 9 116

54 571 0 692

49 171 13 769

763

590

2711

4797

1471 2282 116 892 6772 13,156

(Yudovich Ya and Ketris 2005). The contributions are 17 and 17% for Cd and 15 and 24% for Cr (Pacyna 2007). Oil combustion is the main emitter of Ni in industrial boilers and residential units, which contributes as much as 55% to the total anthropogenic emissions. It should be also added that oil combustion in industrial boilers and residential units contributed substantially to total As and Cd anthropogenic emissions making 15% and 26%, respectively. More than a half of anthropogenic emissions arrive from the combustion of gasoline. Nowadays, gasoline is defined as that with no Pb additives. However, there is Pb as an impurity in gasoline due to the Pb content of crude oil. It was assumed that Pb content in unleaded gasoline was 15 mg/L. It was also supposed that 75% of Pb in gasoline was emitted to the atmosphere during gasoline combustion (Pacyna 2007). Iron, steel, cement production and high-temperature non-ferrous metal manufacturing are the three main industrial processes emitting all PTEs. The contribution of emissions from these categories to the total emissions in Europe varies from 37% for As to 11% for Ni. Finally, pollutant emissions from ‘other sources’ and waste incineration contributed to the total emissions in Europe from 3% for Pb to 14% for Cr (Pacyna 2007).

1.2.2

PTE Transportation and Removal from the Atmosphere

Atmospheric pollution generated by PTEs contaminated the air, pollutes the soil, water, damages the living environment and thus worsens the quality of all environmental resources. The wind quickly mixes huge air masses that absorb various PTEs and other pollutants, easily spread across the environment and adversely affect human health. A significant part of those remain in the air for a long time without recognizing state borders, thus travelling from one place to another. The polluted air primarily affects the inhabitants of large cities and industrial zones. Most of PTEs are toxic, dangerous to humans and wildlife, and therefore research on their spread and deposition processes, concentration in the atmosphere and tendencies towards changes in the amount of pollutants on the land surface play a

1.2 Technogenic Flows of Pollutants: An Example of Potentially Toxic Elements

7

crucial role. PTEs have the ability to accumulate in environment by migrating from one natural system to another. The natural migration of PTEs is ensured by the water medium as most of their compounds are soluble. The accumulated PTEs adversely affect the living systems of live organisms. Due to the carcinogenic properties of PTEs, even very small contaminant concentrations can cause unwanted or even irreversible changes in nature. The effects of PTEs are usually cumulative due to their ability to accumulate in living organisms. PTEs enter the atmosphere both from anthropogenic sources—industrial plants, thermal power plants and vehicles—and from natural sources—volcanoes, soil erosion and forest fires. When released to the atmosphere, PTEs spread inside aerosol particles with air flow at various distances and enter the ground and water surface by dry or wet deposition. PTEs are persistent pollutants. If many organic pollutants and photo-oxides decompose in nature, the natural environment cannot decompose and destroy PTEs. They can either be diluted or switched to temporary relatively non-hazardous complexes. When such complexes are broken, PTEs re-circulate into the environment and become dangerous to living organisms. PTEs have been found washed out from the atmosphere quite effectively by rain and snow—approximately 70% of Pb, 30% of Cu and 50% of Zn are washed out from the atmosphere to the Earth’s surface, whereas the rest is removed from the atmosphere by dry deposition. The main processes of removing PTEs from the atmosphere include wet precipitation and dry precipitation (sedimentation, merging). The dry precipitation process is highly dependent on the size of PTEs particles, some meteorological parameters and the structure of the receptor surface. The wet precipitation of PTEs is determined by the intensity of precipitation. Except for Hg, the major part of PTEs present in the atmosphere appears in the form of dust. The elements are of different particle sizes. Fine particles (2.5 μm) in the air. These particles are formed by mechanical processes such as soil erosion or incomplete burning processes (ash). Large-size particles are the result of dry precipitation in the atmosphere. The lifespan of such particles takes from several minutes to several hours. Since particle size is the key factor in determining the rate of precipitation, the relative rate of dry deposition compared to the overall precipitation rate is higher near emission sources. Meanwhile, wet deposition is the main mechanism for removing the particles smaller than l μm in diameter from the atmosphere in remote areas.

8

1.2.3

1 The Importance of Technogenesis and Sustainable Environmental Protection. . .

PTEs in the Soil

The total concentrations of PTEs in the soil, their chemical forms, mobility and availability to the food chain provide the basis for a range of problems in crop, animal and human health. Some elements present in rock and soils, normally in very small amounts, are essential for plant or animal nutrition. As for large concentrations, many of them may be toxic to the ecosystem or affect the quality of foodstuffs for human consumption. These PTEs include As, Cd, Co, Pb, Ni and Zn (Lepp 1981). The ranges of the natural concentrations of most PTEs in the soil are wide. The main sources are the parent materials from which the soil is derived. These are usually weathered bedrock transported by wind or water, which may be of local or exotic origin. However, man-effected inputs may add to those from natural geological sources. The main sources of PTEs in the soil are from metalliferous mining and smelting activities, other industrial emissions and effluents, urban development, vehicle emissions, dumped waste materials, polluted dusts and rainfall, sewage sludge, pig slurry, composted town refuse, fertilizers and pesticides. Both deficiencies and excesses of PTEs may give a rise in nutritional or toxicological problems in plants and animals (Lepp 1981). The soil is the primary supplier of PTEs to the soil–plant–animal system and the soil–food–human system. Certainly, PTEs do not occur in isolation in these systems, and a number of synergistic and antagonistic interactions are recognized at both deficiency and excess concentrations. These interactions sometimes involve the major elements as well as PTEs (Lepp 1981). The total amount of PTEs in the soil is primarily derived from weathering rock minerals but may be increased substantially by man’s industrial and agricultural activities (Kabata-Pendias 2000a, b). There are generally higher quantities of PTEs in igneous rather than in sedimentary rocks. Igneous and metamorphic rocks are the most common source of PTEs in the soil. They account for 95% of the Earth’s crust with sedimentary rocks making up the remaining 5%. As for sedimentary rocks, 80% are shales, 15% are sandstones and 5% are limestones. Sedimentary rocks are the most important soil parent material since they overlie most igneous formations to account for 75% of the outcrops at the earth’s surface (Wedepohl 1991). The concentrates of typical elements in the soil are shown in Table 1.2. The results of a study reviewing the environmental fate and effects of Cd in Europe over the last 10 years show that the average Cd concentrations in European soils are estimated to range from 0.06 to 0.5 mg/kg with a tendency towards lower concentrations in Scandinavian soils. Unfortunately, this study refers essentially to Northern European countries due to lack of information in Southern Europe (Jensen 1992). As for the polluted soils (mining areas in particular), concentrations are 10–100 times greater than the average found in surface soils. In Europe, fertilizers produced from rock phosphate give the most important but highly variable contribution to Cd in the soil (from 0.3 to 38 g/ha/year); farmyard manure can give a similar and higher input than commercial fertilizers; atmospheric deposition adds to the Cd load that has brought about 2–7 g/ha/year to the soil over the past 50 years. As for Europe as a

1.2 Technogenic Flows of Pollutants: An Example of Potentially Toxic Elements Table 1.2 The content of typical elements in the soil and vegetative above-ground plant organs (Adriano 2001; Kabata-Pendias 2000a, b)

Element Antimony Arsenic Barium Beryllium Boron Cadmium Chromium Cobalt Copper Fluorine Iron Lead Manganese Mercury Molybdenum Nickel Selenium Thallium Tin Vanadium Zinc

Soil (mg/kg) 0.1–2.0 1.0–10 100–1000 0.1–10 2.0–100 0.05–1.0 10–50 1.0–10 10–40 100–500 1000–5000 10–30 300–1000 0.05–0.5 0.5–2.0 10–50 0.1–2.0 0.02–0.5 0.1–10 30–150 20–200

9 Plant (mg/kg) 0.01–0.1 0.1-0.5 10–100 0.01–0.1 3.0–90 0.05–0.5 0.1–0.5 0.02–0.5 3.0–12 1.0–10 50–200 0.1–0.5 20–400 0.005–0.05 0.1–4.0 0.2–2.0 0.01–0.5 0.005–0.05 0.1–1.0 0.2–1.0 20–100

whole, increasing Cd concentrations have been found in European soils, especially during the last 20–30 years. However, only a few cases have faced a significant longterm increase in Cd concentration in harvested crops (Stanners 1995). PTEs accumulate in the soil where they are fixed on mineral particles. From there, they can be mobilized by ‘triggers’ such as acidification and released to the soil solution. Then, they can be taken up by soil organisms and plant roots or leached into groundwater, thus polluting the food chain or affecting drinking water quality. The pollution of the agricultural soil by PTEs may lead to reduced yields (e.g. growth inhibition of leafy vegetables is reported at Cd concentrations of 0.9– 1.5 mg/kg in sandy soils and about 3 mg/kg in clay soils). Pollution can also result in the elevated levels of PTEs in agricultural products, and thus in their introduction into the food chain (Alloway 1990). PTEs deposited on grassland soils remain predominantly in the top few centimetres and are directly ingested with the soil by grazing animals. Soil ingestion is a major pathway of PTEs to livestock grazing polluted land (Thornton and Abrahams 1983). PTEs are toxic, and therefore it cannot be discounted that low levels may have long-term effects that may not have become apparent yet. They may have negative impacts through the inhibition of soil microorganism activity; for example, surface accumulation of PTEs in acid forest soils can inhibit litter decomposition by influencing fungal and faunal communities, e.g. Cd

10

1 The Importance of Technogenesis and Sustainable Environmental Protection. . .

concentration in the soil exceeding 4 mg/kg of dry weight can inhibit microbial processes occurring in the soil, the growth and reproduction of living organisms. PTEs may accumulate in the soil, especially in that having the large binding capacity for PTEs (for instance, in non-acid soils and ‘black earth’). The most important factors governing plant uptake of PTEs from the soil are soil pH, clay content (texture), organic matter content and metal concentration. In the soil with low binding capacity, no accumulation of PTEs is observed even under high input load, which implies a relatively high concentration of PTEs in groundwater, important leaching and high plant uptake. Forest soils seem to accumulate more PTEs than grasslands because forest crowns constitute receptors with a larger deposition surface, and forest litter is not exported (De Temmerman 1987). PTEs concentrations in the soil solution can remain low for decades or even centuries, as long as the binding capacity of the soil is not saturated. This reservoir of PTEs in the soil may turn into a source if the binding capacity of the soil is lowered. This may occur through a change in pH (pH < 4) due, for example, to atmospheric deposition, changes in land use or climate.

1.2.4

Soil–Plant Transfer of PTEs

The soil–plant transfer of PTEs is a part of chemical element cycling in nature. This complex process is governed by several factors, both natural and anthropogenic. Several factors control the processes of mobility and bioavailability of PTEs; in general, they are of geochemical, climatic and biological origin. Thus, the prediction of PTE uptake by plants from a given growth media should be based on a few biotic and abiotic parameters that control their behaviour in the soil. The soil is the main source of PTEs for plants both as micronutrients and as pollutants. Soil conditions play a crucial role in the behaviour of PTEs. It can be generalized that in the wellaerated acid soils, several trace metals, especially Cd and Zn, are easily mobile and available to plants, whereas in the poorly aerated (reducing) neutral or alkaline soils, PTEs are substantially less available. The origin of PTEs influences their behaviour in the soil and therefore to some extent controls their bioavailability. Lithogenic elements are related to either primary or secondary minerals that occur in the parent material. Their mobility depends first on weathering processes and second on the anion and cation exchange capacity of minerals. Pedogenic trace elements are of double origin, including lithogenic and anthropogenic, but their distribution and speciation are affected as a result of various pedogenic processes, among which fixation by clay minerals and complexing by the organic matter of the soil play a crucial role. The cation and anion exchange capacity of the soil for PTEs is closely related to the specific surface area of soil particles. This value varies within the range from 25 to above 800 m2/g in different clay minerals. As for soil organic matter, it has been calculated to be 560–800 m2/g. The contribution of soil organic matter to cation

1.2 Technogenic Flows of Pollutants: An Example of Potentially Toxic Elements Table 1.3 The concentrations of some PTEs in the soil solution (Kabata-Pendias and Pendias 2001)

Elements Boron Cadmium Cobalt Chromium Copper Manganese Molybdenum Nickel Lead Zinc

11 Soil solution (μg/L) 12–800 0.01–5 0.3–29 0.4–29 0.5–135 25–8000 2–30 3–150 0.6–63 1–750

exchange capacity is significant in most arable soils and varies from 25 to 90%, depending on the type of the soil. The impact of soil microorganisms and enzymes on all redox and dissolution processes is crucial and can exert a high degree of control on the behaviour of PTEs. The biological methylation of some elements such as As, Hg, Se, Te, Ti and Pb have a significant impact on their behaviour. Biomethylation is the pathway for converting some PTEs into more mobile or more lethal derivatives that can enter the food chain (Burns 2002). The transfer of PTEs between soil phases can be considered as the main processes controlling their behaviour and bioavailability. However, the soil liquid phase (soil solution) constantly and rapidly changes in amount and chemical composition due to the contact with a highly diverse soil solid phase and by the uptake of ions and water by plant roots. Data on the concentrations of PTEs in the soil solution can be useful for predicting their availability, toxic effects on crops and biological activities in the soil. The concentration of free metal ion species in the soil solution is controlled by several factors, the most significant of which are thermodynamic parameters. The ranges of some elements measured in the solution obtained by various techniques from the polluted soils are presented in Table 1.3 (Kabata-Pendias and Pendias 2001). In general, the total content of PTEs in the solutions of unpolluted mineral soils range from 1 to 100 μg/L while in the polluted soils these values can be much higher. In both kinds of the soil, however, these are the negligible portions of the total concentrations of soil metals (Kabata-Pendias and Pendias 2001). The bioavailability of PTEs has been the most crucial problem in agricultural and environmental studies. During their evolution, plants have developed several biochemical mechanisms that have resulted in adaptation to and the tolerance of new or chemically imbalanced growth media. It is known that plant roots exude substances involved in uptake mechanisms. Root and rhizosphere exudates vary in composition but normally consist of low molecular weight compounds. The composition of root exudates can greatly change under any environmental stress. The excess of PTEs in the soil

12

1 The Importance of Technogenesis and Sustainable Environmental Protection. . .

is a stronger stress to plants than their deficiency, and some plants can develop a protective mechanism against the excess of PTEs in particular. These mechanisms, however, can operate until the biochemical resistance of plant cells exists. In the urban areas of high aerial pollution, the soil becomes enriched with PTEs and there is uptake from the soil via roots. Soil type, pollution and microclimatic conditions may differ between sampling sites and might therefore have an impact on the significance of pollution impact (Sawidis 2011).

1.2.5

PTEs Uptake and Accumulation in Trees

Trees have very wide geographical distribution, which allows carrying out correlation over large areas (Savard 2006). They can be found in both natural and human environments; their rings can easily be sampled, and their rate of growth is well suited for monitoring environmental changes on a large scale (Barrelet 2008). The concentrations within the rings are a trusted source with regard to ‘Environmental Chemistry’ and are well suited for the study of space-time distribution of air pollutants (Aznar 2008). PTEs are long-term pollutants with the ability to accumulate in the soil and plants and have an unnatural way to be removed. The use of vegetation monitoring (mosses, ferns, plants, higher plants-trees, leaves, etc.) provides the cheapest and simplest indicator for monitoring PTEs levels. However, trees are preferable to other vegetation monitoring, because they are widely distributed and remain in the fixed position for a considerable period, thus enabling the analysis of trends over the intervals of time (Padilla 2002). Each ring is in fact ideally able to record the inputs of pollutants in the environment that occur each year, thus allowing the use of trees as bio-indicators to assess environmental changes at both global and local level. Dendrochronological studies are important since they provide indications about the impacts of air pollution and information with high temporal resolution (e.g. annually) (Watmough 1999; Danesino 2009). The reliability of the results of the dendrochemistry test depends on the behaviour of different tree species, the analytical methodology, wood structure, the bioavailability and nature of elements, mechanisms and absorption pathways (Schweingruber 1996; Yu 2007). A further distinction can then be made between the pollutants (e.g. PTEs) that leave a trace specific and measurable and those (e.g. ozone) that cannot produce very specific answers such as a reduction in growth. In addition, the sensitivity of trees to pollutants will change over time as a consequence of ageing (Ferretti 2002). There are three main ways environmental pollutants can enter inside the trees. The most important one is root absorption from the soil, which results in transporting a woody tissue via the transpiration flow. The second one is foliar absorption with subsequent displacement from the leaf through the phloem followed by lateral movement from the phloem to the xylem. The last one is direct deposition on the surfaces of the stems followed by lateral movement in the internal bark down to wood (Lepp 1975). Absorption by the roots is considered the main point of entry for most of the elements (Lepp 1975). Accumulation through the soil in the woody rings

1.2 Technogenic Flows of Pollutants: An Example of Potentially Toxic Elements

13

is strongly affected by the chemistry of the soil, the pH and type of the pollutant in particular. The absorption and immobilization of PTEs are unique to each plant and are influenced by abiotic and biotic factors; concentrations may be affected by the age of the tree, and therefore, in the sampling strategy, should be considered as the trees of a similar age for comparison between the polluted and non-polluted site. On the other hand, absorption through bark is the main way of incorporation in the rings in the case of metals with low mobility, i.e. lead (Pb) (Watmough 1999). Once PTEs enter the tree, they are not necessarily attached to the ring of the current year (Lepp 1975). The accumulation of pollutants inside growth rings is a complex process strongly influenced by water solubility, the species of the tree to which it refers and to other environmental factors such as temperature and precipitation which, in the course of the growing season, affect the rate of the growth of trees, the absorption of roots and the concentration of the PTEs in trees (Aznar 2008). It is necessary to sample mature trees, so as to ensure that the past polluting event is localized within the tree rings. Thus, it would be ideal to take more than one sample per tree. It is also important to understand the mode of transporting the element and its behaviour within the xylem before drawing conclusions about its deposition within the rings and making connections with the surrounding environment (Watmough 1999). Within the same xylem, it is estimated that As, Na and Mg have greater mobility between the rings active; Sr, Ca, Zn, Cu and Cr have moderate mobility and Pb, Ba, Al and Cd have lower mobility (Padilla 2002). Given the small amount of xylem obtained from the cores of wood, many previous studies have used the segments of 5–10 years to obtain sufficient material for analysis, thus reducing resolution and making imperceptible changes in the short term. Although there are several problems of interpreting dendrochronological data, a careful sampling strategy combined with a great understanding of the behaviour of PTEs in wood allow to dendrochemistry to provide historic changes in the levels of PTEs in the soil and atmosphere (Watmough 1999). The effect of urban pollution that consequently means the accumulation of PTEs differs between various tree species or the parts of trees. A critical factor that determines PTE uptake from a certain plant would be the structure of its leaf or bark surface. Evergreen plants absorb a higher percentage of leaf nutrients than deciduous species (Kikuzawa 1995). Fast-growing, high-biomass-producing woody plants that tend to accumulate PTEs in aerial tissues could be a source for developing feasible phytoextraction technology (Unterbrunner et al. 2007). Several authors have shown that some Salix and Populus species are able to accumulate substantial amounts of PTEs in their leaves. Robinson found up to 209 mgCd/kg in the leaves of Populus trichocarpa and Populus deltoides growing on the polluted site (up to 300 mgCd/kg in soil) in Northern France (Robinson 2000). Up to 12.5 mgCd/kg and 1130 mgZn/kg were found in the leaves of Salix phylicifolia and Salix borealis growing on mine tailings containing 52.4 mgCd/kg and 14,500 mgZn/kg (Stoltz 2002). Watmough suggested that species with diffuse porous wood (sycamore, linden and beech) were able to record changes in Pb and Cd deposition in tree rings (Watmough 2003). He also found that Pb concentrations in wood were rarely

14

1 The Importance of Technogenesis and Sustainable Environmental Protection. . .

greater than 10 mikrog/g (Watmough 1997). With a few exceptions, it was observed a general trend of Cd and Zn concentrations increasing from wood towards leaves (wood < bark < leaves) (Unterbrunner et al. 2007). The data revealed that Salix caprea, Salix purpurea and Populus tremula have large Cd and Zn accumulation potential when growing on metal-polluted soils, and may therefore provide a valuable source for developing phytoextraction technologies (Unterbrunner et al. 2007).

1.2.6

Hazards and Exposure of PTEs Pollution

PTEs have been used by humans for thousands of years. Although several adverse health effects of PTEs have been known for a long time, exposure to PTEs continues, and is even increasing in some parts of the world, particularly in the less developed countries, though emissions have declined in most developed countries over the last 100 years. At the end of the twentieth century, however, the emissions of PTEs started decreasing in the developed countries: for example, the emissions of PTEs fell by over 50% between 1990 and 2001 in the UK. The emissions of PTEs to the environment occur via a wide range of processes and pathways, including the air (e.g. during combustion, extraction and processing), surface waters (via runoff and releases from storage and transport) and the soil (groundwater and crops). Atmospheric emissions tend to be of the greatest concern in terms of human health both because of the quantities involved and widespread dispersion and potential for exposure that often ensues (Järup 2003). Although some individuals are primarily exposed to these pollutants in the workplace, for most people, the main route of exposure to PTEs is through the diet (food and water). The pollution chain of PTEs almost always follows a cyclic order: industry, atmosphere, soil, water and food (Morais 2008). People may be exposed to potentially harmful chemical, physical and biological agents in the air, food, water or soil. However, exposure does not result only from the presence of a harmful agent in the environment. The key word in the definition of exposure is contact (Berglund 2001). There must be contact between the agent and the outer boundary of the human body, such as airways, skin or the mouth. Exposure is often defined as a function of concentration and time: ‘an event that occur when there is contact at a boundary between the human and the environment with a pollutant of specific concentration for an interval of time’ (NRC 1991). The methods of human exposure to chemicals in general throughout their life cycle are depicted in Fig. 1.3. Throughout the life cycle, chemicals affect humans in two spheres: the living environment and work area. When exposed to chemicals, a human experiences various doses of pollutants. The human body react differently to different doses of chemicals. Figure 1.4 shows dose–response curves for PTE compounds. The effects of higher severity are formed when the range of the daily oral intake of the metallic compound increases to a

1.2 Technogenic Flows of Pollutants: An Example of Potentially Toxic Elements

Water and food safety

Naturally occurring chemicals, for example, arsenic and fluoride in water

Marking

Raw materials, for example, fossil fuels, raw chemicals

Production and transportation

Chemicals

15

Safety in terms of chemicals

Safety at work shipping and using chemicals

Effect Manufactured products made, for example, chemicals and petroleum products used in industry and agriculture

Effect on human

Political strategies and programmes Processes

Use and disposal

In

Effect in the work environment

ci ne ra tio n

Environmental impact

Transfer and health, air quality

Combustion products, for example, pollutants in the working environment and ambient air

Waste and by-products, for example, e-waste, persistent organic pollutants

Product safety working with chemicals

Safety at work, safe work with chemicals, food and water safety

Waste management; working with chemicals, food and water

Fig. 1.3 Human exposure to chemicals throughout their complete life cycle, policy tools and programmes to prevent exposure to chemicals

certain level (curves 5–8). Minor changes in biochemical markers that do not have a high functional or clinical value (curve 5) are not critical to public health. Subclinical1 markers of the effects related to the functional deficiency of PTE compounds or indicating the development of a clinical disease are more important from the point of view of public health and are often essential for preventive measures (e.g. setting exposure limits for PTE compounds, formulating recommendations for the safe doses of the PTE compound entering the human body). Such effects are called critical effects. Subclinical effect markers are occasionally not inducible, and therefore a clinical effect that occurs at the lowest dose of the PTE compound is considered a critical effect. People can be exposed to PTEs in the professional (working) environment and emissions from the polluted environmental sources. Direct human exposure to PTEs occurs via the following major routes of access to the body (Fig. 1.5): (a) by inhalation of PTEs present in ambient air; (b) using food containing PTEs; (c) drinking water containing PTEs; (d) by swallowing dust containing PTEs.

1 Subclinical markers—in the case of a disease or lesion, such markers are not symptomatic and do not appear clinically but can be detected by physical examination or conducting laboratory tests.

1 The Importance of Technogenesis and Sustainable Environmental Protection. . .

5

4

Function biochemically insignificant al marker Subclinical bi effect indica omarker of the impairment ting functional

Toxicity 6 7

8

Death

3

rker of the Subclinical bioma nctional effect indicating fu impairment ificant lly insign Functiona al marker biochemic

1

Clinical effects

100 %

2

Death

Deficiency

Clinical effects

16

0% LD 50

NNPL LBNR

Dose

Fig. 1.4 Theoretical dose–response curves for various effects that occur in the population under varying quantities (doses) of PTEs entering the human body. Mortal effects and clinical illnesses must always be prevented, but subclinical effects that disclose worsening organ functions are always indicated as critical effects. The lower part of the dose–response curve to critical effects related to lack (deficiency) (Curve 3) and toxicity (Curve 6) describes the acceptable range of oral intake (AROI) with no observed (adverse) effect level (NO(A)EL). Functionally insignificant biochemical effects (Curves 4 and 5) are considered having no effect on health and are not classified as critical effects

Air

Soil

Breath

Skin contact

Blood

Food

Transfer to plants

Drinking water

Swallowing

Other body tissues

Release from the body Fig. 1.5 A conceptual model for human exposure to PTEs

1.2 Technogenic Flows of Pollutants: An Example of Potentially Toxic Elements

17

The main threats to human health from PTEs are associated with exposure to Pb, Cd, Hg and As. Cd emissions have increased dramatically during the twentieth century, which shows that Cd-containing products are rarely recycled but often dumped together with household waste. Cigarette smoking is the major source of Cd exposure. As for non-smokers, food is the most important source of Cd exposure (Järup 2003). The general population is primarily exposed to Hg via food, fish being the major source of methyl Hg exposure and dental amalgam. The general population does not face a significant health risk from methyl Hg, although certain groups with high fish consumption may attain blood levels related to a low risk of neurological damage to adults (Järup 2003). The general population is exposed to Pb from the air and food in roughly equal proportions. During the last century, Pb emissions to ambient air have caused considerable pollution, mainly due to Pb emissions from petrol. Children are particularly susceptible to Pb exposure due to high gastrointestinal uptake and the permeable blood–brain barrier. Although Pb in petrol has dramatically decreased over the last decades, thereby reducing environmental exposure, phasing out any remaining uses of Pb additives in motor fuels should be encouraged (Järup 2003). Exposure to As is mainly via the intake of food and drinking water. Food is the most important source in most populations. Long-term exposure to As in drinking water is mainly related to the increased risks of skin cancer as well as to some other cancers and other skin lesions such as hyperkeratosis and pigmentation changes (Järup 2003).

1.2.7

Transport of PTEs Within Environmental Compartments

Atmospheric air occupies a specific place in the complex of natural environmental sustainability—the atmosphere is incomparably more dynamic than other natural spheres. Atmospheric self-purification processes are also significantly faster than those in water bodies or the soil. It is important to note that all other spheres are polluted through the atmosphere. Techniques for air pollution transfer to other spheres are very diverse and complex, the majority of them have not been extensively explored yet, and most importantly, the atmosphere, as the most vulnerable part of the ecosystem, is at serious risk. An obvious example is acid rain, the formation of which is caused by an enormous rise in the amount of fuel consumed, increased metal smelting rates and the insufficient number of efficient systems for removing pollutants that accumulate in the production process. Various sulphates and nitrates emitted into the atmosphere return in the form of acid rain, thus causing significant damage to the environment and human health. Extreme changes in the physical and chemical properties of the atmosphere should result in a collapse crossing all other links of the ecosystem (Aleksandro Stulginskio universitetas 2012).

18

1 The Importance of Technogenesis and Sustainable Environmental Protection. . .

The fate of pollutants in the atmosphere passes the following stages: emission, transmission (dissemination and transformation of pollutants in the air) and deposition (fall of air pollutants at the site of action). Emissions are the processes through which pollutants are introduced in atmospheric substances that did not exist in the air before. Anthropogenic (e.g. vehicle traffic or residential units), industrial, agriculture and commercial activities produce the emissions of sulphur dioxide (SO2), nitrogen oxides (NOx), carbon monoxide (CO), volatile organic compounds (VOC), particulate matter (PM) and PTEs (e.g. lead and cadmium). Transmission is the second step of air pollution and covers the processes that include the advective or turbulent transport of pollutants as well as their chemical–physical transformations due to the reaction of some factors such as solar radiation. Finally, the deposition of pollutants can be seen like the final result and the real impact of pollutants on the objects present on the earth’s surface, i.e. dry and wet deposition. The transfer and fate of PTEs in the atmosphere and transfer to other compartments depend on climate factors. The Earth’s surface is a boundary on the domain of the atmosphere. Transfer processes at this boundary modify the lowest 100–3000 m of the atmosphere, thus creating the so-called boundary layer. The remainder of the air in the troposphere is loosely called the free atmosphere (Stull 1989). We can define the boundary layer as the part of the troposphere that is directly influenced by the presence of the Earth’s surface and responds to surface forcings with a timescale of about an hour or less. These forcings include frictional drag, evaporation and transpiration, heat transfer, pollutant emission and terrain-induced flow modification. Diurnal variations in temperature near the ground are an example of surface forcings. Ninety percent of solar radiation transmitted to the ground cause the warming and cooling processes of it in the response of radiation. The alternation of soil temperature in turn forces changes in the boundary layer via transport processes (Stull 1989). Mean wind is responsible for very rapid horizontal transport (advection). Horizontal winds on the order of 2–10 m/s are common in the boundary layer. The waves frequently observed in the night-time boundary layer transport little heat, humidity and pollutants. The obstacles like trees and buildings deflect the flow, thus causing turbulent wakes adjacent to and downwind of the obstacle. Buoyancy is one of driving forces for turbulence in the boundary layer (Stull 1989). Over land surfaces in high-pressure regions, the boundary layer has a welldefined structure that evolves with the diurnal cycle (Fig. 1.6). The three major components of this structure are the mixed layer, the residual layer and the stable boundary layer. Turbulence in the mixed layer is usually convectively driven. Convective sources include heat transfer from a warm ground surface and radiative cooling from the top of the cloud layer. The mixed layer is tied to solar heating of the ground. Starting about a half hour after sunrise, a turbulent mixed layer begins to grow in depth. It reaches its maximum in late afternoon. The pollutants emitted from smoke stacks exhibit characteristics looping (Fig. 1.6) as the portions of the effluent emitted into warm thermals begin to rise (Stull 1989). Smoke plumes emitted into the residual layer tend to disperse at equal rates in vertical and lateral directions, thus creating a cone-shaped plum (coning) (Stull 1989). Pollutants emitted into the stable

1.2 Technogenic Flows of Pollutants: An Example of Potentially Toxic Elements

19

2000 Height (m)

Free Atmosphere Entrainment Zone

Cloud Layer

Capping Inversion Entrainment Zone

1000 Residual Layer

Convective Mixed Layer

Surface Layer

Noon

Residual Layer

S1

Convective Mixed Layer

Surface Layer

Sunset

S2

Midnight Local Time

S3

Sunrise

S4 S5

S6

Noon

Fig. 1.6 The structure of the planetary boundary layer in high-pressure regions over land (Physics 2013)

layer disperse relatively little in the vertical. They disperse more rapidly in the horizontal (Stull 1989).

1.2.8

Dispersion of Pollutants

The emission of pollutants in the air involves the consideration of the phenomena of atmospheric dispersion in order to determine the spatial distribution of the concentration of the pollutant in the surrounding area. Depending on the nature of pollutants, they remain in the atmosphere for longer or shorter periods (typically 1 day to 1 year) on different timescales, including local, regional, continental and global. In all cases, the base of the phenomenon of dispersion is the action of wind and atmospheric turbulence. The wind is the driving force of pollutant transport away from the point of release as well as a fundamental component of dilution. However, the dilution of pollutants mainly depends on turbulence, which can be both mechanical and thermal. Mechanical turbulence depends mainly on wind speed and the roughness of the surface (e.g. hills or high buildings). Thermal turbulence is rather in relation to thermal exchanges between the atmosphere, soil and space extraterrestrial exchanges that affect the stability of the atmosphere. In this regard, Pasquill and Gifford defined seven stability classes referred to as by letters A (extreme stability) to G (extreme instability), which can be determined based on the simple observation of the sky and the measurement of wind speed (Pasquill 1971). In daytime with strong isolation and low wind speed ( 5, extremely heavily polluted area. The potential ecological risk index (RI) calculates the overall degrees of the ecological risk of all metals under investigation (Eq. 1.9) (Devanesan et al. 2017) RI ¼

X

E ir

ð1:9Þ

where E ir—potential ecological risk index. RI < 150, low; 150 < RI < 300, average; 300 < RI < 600, significant; RI > 600, very serious ecological risk. The potential ecological risk index (Eir ) calculates a degree of the ecological risk of a single PTE (Eq. 1.10) (Hakanson 1980). E ir ¼ CF  T ir

ð1:10Þ

where CF—contamination factor; T ir —factor of the toxic impact of PTE. T ir for Zn ¼ 1, Cr ¼ 2, Cu ¼ 5, Ni ¼ 5, Pb ¼ 5, Cd ¼ 30. E ir < 40 describes low risk; 40 < E ir < 80 indicates moderate risk; 80 < E ir < 160 indicates significant risk; 160 < E ir < 320 indicates high risk; E ir > 320 indicates very high risk. Enrichment factor (EF) is used for assessing the area polluted with heavy metals (Shafie et al. 2012) (Eq. 1.11).

1.3 Evaluating Pollution Level

23

EF ¼ ðCn =Rref Þsample =ðBn =Bref Þreference material

ð1:11Þ

where Cn—the concentration of PTE in the sample; Bn—the concentration of PTE used for normalization in the sample; Rref—the concentration of PTE used for normalization in the reference material. Al, Fe, Ti, Sc, Si and Zr are often used as reference elements for normalization (Yongming et al. 2006). EF < 2 indicates light saturation; EF ¼ 2–5 indicates moderate saturation; EF ¼ 5–20 indicates heavy saturation; EF ¼ 20–40 indicates very heavy saturation; EF > 40 indicates extremely heavy saturation. Contamination factor (CF) is calculated according to Eq. (1.12) (Banu et al. 2013) CF ¼ C m =C ref

ð1:12Þ

where Cm—the concentration of a PTE in the sample; Cref—reference value; CF < 1 indicates pollution is low; 1 < CF < 3 indicates moderate pollution; 3 < CF < 6, indicates the significant pollution; CF > 6 indicates very high pollution. The pollution coefficient (Ko) of polluting the soil by PTEs is calculated according to Eq. 1.13 (HN 60 2004) Ko ¼

Ci DLK

ð1:13Þ

where Ci—PTE concentration in the investigated sample of the soil, mg/kg DM; DLKi—maximum permissible PTE concentration in the soil, mg/kg DM. Permissible level is when Ko < 1, moderately risky—1 < Ko < 3; risky— 3 < Ko < 10; extremely risky—Ko > 10.

1.3.2

Dynamic Factor Method for Transferring Metallic Elements in the Soil–Plant System

The development of environmental sciences in the second half of the last century (1950–2000) and, eventually, the synthesis of ‘old’ and ‘new’ ecology based on the principle of sustainability stimulated the further collection of information about environmental quality based on the ability of living organisms to accumulate chemical elements (including PTEs) that could often indicate their level. The researchers studying bioindication and biomonitoring problems also investigated PTE transfer and accumulation in living organisms as well as a possibility of their quantitative and qualitative expression (Adriano 1986, 1992; Baltrėnaitė et al. 2012, 2014, 2016a, b, c, d, 2018; Butkus et al. 2014; Markert and Weckert 1993; Golan-Goldhirsh et al. 2004; Lux et al. 2004; Renella et al. 2004; Lepp and Madejon 2007; Fraenzle et al. 2008; Schroeder et al. 2008; Cakmak 2008; Chaney et al. 2008; Cook and Kairiūkštis 1999; Gimbert et al. 2008; Greger 2008; Irtelli and Navari-Izzo

24

1 The Importance of Technogenesis and Sustainable Environmental Protection. . .

2008; Li et al. 2008; Kupčinskienė 2011; Lietuvninkas 2012a, b; Marmiroli and Maestri 2008; Poschenrieder et al. 2006; Prasad 2008; Schwitzguébel et al. 2008; Stravinskienė 2010; Verbruggen et al. 2009; Verkleij 2008). The examination of phytotechnology and assessment of its economic impact further encouraged the development of methodologies for evaluating their effectiveness based on PTE transfer (particularly in the soil–plant system) and discussing the concepts of bioaccumulation. A widely known type of biological accumulation is based on the relationship between the plant and the soil, or, in other words, it is the coefficient referred to as the index of bioaccumulation (IBA), transfer factor (TF), transfer coefficient (TC) (Antoniadis et al. 2006), bioaccumulation factor (Prasad 2006), mobility ratio (MR) (Mingorance et al. 2007; Baker 1981; Chamberlain 1983), accumulation factor (Wilson and Pyatt 2007), bio-concentration factor (BCF) (Pulford and Dickinson 2006; Gál et al. 2008; Yoon et al. 2006) and plant– soil coefficient (Kovalevsky 1987) and is expressed by the concentration of PTE in a plant with respect to the soil. The factors/coefficients expressing the concentration of PTEs in plants compared to that in the soil have some drawbacks: (a) they reflect a comparison of PTE concentrations in various media (plants and soil), but this refers only to a particular area and to particular environmental conditions characteristic of this area in a particular period of time; (b) a comparison of various plants based on the considered factors/coefficients could hardly be accurate because these plants could have been growing in different conditions as well as in different types of the soil and elementary landscape, which could result in different levels of PTE mobility and accumulation in them; (c) not only PTE concentrations in plants should be compared with their concentrations in the soil or a control plant, but also differences in the process of their transfer and its intensity with respect to the control case should be described; (d) numerical evaluation of the relationship between transferring PTEs to the investigated plant and their transfer to control plants, which could facilitate evaluating variations in PTEs transfer, is still lacking; (e) it is important that the effect of natural processes on transferring PTEs should be integrated into the estimate. These needs could be achieved by introducing higher-order factors calculated by comparing the value of the PTE transfer factor obtained for the investigated area with the respective value for the control area. The third-level factors are referred to as dynamic factors (Fsdyn). The authors recommend using Fsdyn for describing five types of the behaviour of PTEs depending on changes taking place in the soil–plant system: the dynamic factor of bioaccumulation, the dynamic factor of biophilicity, the dynamic factor of translocation, the dynamic factor of phytoremediation and the dynamic factor of bioavailability. First, the concept of Fsdyn was presented in the paper by Baltrėnaitė et al. (2012) and provided by the example of applying them in the case of studying sludge effect on tree seedlings. Later, more cases of applying Fsdyn were described in Baltrėnaitė et al. (2015), Zheng et al. (2015), Morichetti et al. (2017) and Baltrėnaitė-Gedienė et al. (2020). In addition to their biogeochemical characteristics, dynamic factors have the following practical advantages: (1) they integrate information by combining data

1.3 Evaluating Pollution Level

25

about the concentration of chemical elements in two adjacent medias with data on control and treated sites into the single value, thereby facilitating the estimation of transferring the chemical element; (2) dynamic factors are non-dimensional, and therefore easy to use and discuss; (3) they eliminate the risk of systematic errors in analytical work, thus increasing the reliability of the obtained results and the quality of estimation. Baltrėnaitė-Gedienė et al. (2020) discussed and included the cases of the practical applications of Fsdyn (a) under the different pathways of PTEs into the soil–plant system; (b) under the influence of biotic (e.g. tree disease) and abiotic factors (e.g. environmental pollution) and (c) under typical soil modification conditions (e.g. amending soil with a polluted amendment or stabilizing pollution with a sustainable amendment). Table 1.4 presents the specific features of dynamic factors and defines the areas of their application. The main feature of this method is its ability to assess variations in PTE transfer achieved by using the dynamic bioaccumulation factor. It allows for determining the relationship between PTE transfer changes in control and the affected cases referring to the soil–plant system. This estimate is useful for assessing the effectiveness of phytoremediation and presents the rough evaluation of phytoremediation effectiveness. Another feature of dynamic factors is the possibility of assessing variations in PTE involvement in the metabolism of plants referring to dynamic biophilicity factors. Comparing PTE concentration in the plant with its Clark value, this factor shows variations in PTE uptake by the plant with respect to other PTEs compared to a general case in the context of the world’s living matter. This information is useful for describing, for example, the effect produced by the soil amendment on the transfer of a particular PTE to the considered plant. On the other hand, this allows identifying changes in PTE biophilicity sequence in the case of a classical sequence—Zn19.6Cu9.1Mn6.9Pb3.7Ni1.5Cr1.0 (Dobrovolsky 2008). Changes in a biophilicity sequence (particularly, if considered in a wide context) can also help with explaining variations in PTE technophilicity (Baltrėnaitė et al. 2018). The ability of assessing phytoremediation effectiveness is the third important feature of dynamic factors. Using the dynamic phytoremediation factor allows for comparing the efficiency of particular plants used for phytoremediation at removing pollutants from the soil (or the aqueous medium in testing aquatic plants). The considered comparison of efficiency is relevant both to the process of choosing more effective plants and to preliminary determining the time required for soil remediation. In the case of determining the specific features of basipetal and acropetal plants and their pollution, the dynamic translocation factor allowing for comparing the effect of changes taking place in the modified soil on the migration of pollutants from the below-ground to the above-ground parts of the plants should be used. It is particularly important when plants are used for food or as fodder, because, in this case, the trends of pollutants to the accumulated in the below-ground parts (e.g. roots) or the above-ground parts (e.g. shoots, leaves, grains) of a plant should

26

1 The Importance of Technogenesis and Sustainable Environmental Protection. . .

Table 1.4 The characteristics and fields of applying dynamic indicators (Baltrėnaitė et al. 2018) Major features of dynamic factors Variations in chemical element uptake

Variations in the chemical element involved in plant metabolism

Phytoremediation efficiency

• Variations in translocation intensity • Variations in the process of translocating the chemical element

Variations in the bioavailability of the chemical element

The intensity of biogeochemical transfer

Description of the feature Dynamic factors allow for comparing changes in the process of metal uptake by different plants (trees) with reference to the evaluation of the geochemical characteristics of the analysed area (BAdyn) Dynamic factors provide the possibility of comparing the influence of soil modification on the involvement of chemical elements in the metabolism of plants (BFdyn) The dynamic factor of phytoremediation helps to more accurately evaluate phytoremediation efficiency (specifies the annual increment features of a phytoremediator (PHYdyn)) The dynamic factor of translocation can be used for evaluating the behaviour of the chemical element and its translocation intensity within the plant under conditions of environmental changes (soil) (TRdyn)

The dynamic factor of bioavailability effect shows the effect of a stressor of the impact of environmental changes on the ratio of the bioavailable form with reference to the total concentration (BIOdyn) It shows the extent of transfer, thereby describing a stressor not only based on its effect/influence, but also on the extent of the effect/influence. This may be a characteristic of environmental risk (BAdyn)

Cases of practical application • Estimating phytoremediation performance

• Determining the effect of various soil amendments (e.g. sludge or biochar) on the activity of chemical elements in plants

• Comparing the performance of different phytoremediators

• Determining soil modification effect on the translocation of chemical elements in the plant (e.g. assessing the strength of the modification effect on the translocation process); soil modification can cause more intensive translocation of chemical elements from the roots to the shoots, which in turn can produce a harmful environmental/health effect in the case of edible plants • The intensity of transferring chemical elements between different media as a result of the produced effect. This may be a characteristic of environmental risk

1.3 Evaluating Pollution Level

27

Fig. 1.8 Dynamic factors, their features and the fields of application

be known. This factor can be used for determining the intensity of translocation and variations in the translocation of pollutants. The intensity of PTE transfer among various media also expresses the effect of environmental changes, which is relevant to evaluating the produced effect and risk. For this purpose, the dynamic factor of bioavailability showing the ratio of the PTE bioavailable form on the basis of the total concentration should be used. The dynamic bioaccumulation factor is also important for determining the scope of biogeochemical transfer in ecosystems. In this case, the environmental factor can be defined by the extent of the effect/influence on biogeochemical processes. The use of dynamic indicators in environmental assessment methods is presented in Fig. 1.8. The dynamic bioaccumulation factor describing variations in PTE uptake by plants (or their particular parts), the intensity of PTE biogeochemical migration and the dynamic factor of bioavailability defining the extent of PTE bioavailability can be used for evaluating the environmental risk. This was demonstrated by the case when the transfer of PTEs was changed by biochar amended on the soil. The latter factors as well as the dynamic biophilicity factor assessing variations in PTE involvement in the metabolism of the plant will be used for assessing the process of biogeochemical migration. If the translocation factor that assesses variations in PTE translocation intensity and translocation behaviour is added to the aboveconsidered factors, the evaluation of environmental effect will be more accurate. The dynamic phytoremediation factor becomes helpful in phytoremediation

28

1 The Importance of Technogenesis and Sustainable Environmental Protection. . .

assessment. The possibility of dynamic factors to assess variations in PTE transfer relating it to changes in the soil as the main medium of plants and integrating data on the multi-facet environment into the numerical value are the main advantages and benefit of dynamic factors explaining their applicability.

1.4

Footprints

Recently, various types of footprints related to the intensity of anthropogenic activity and the development of technogenesis have been widely studied. Starting from the ecological footprint developed at the beginning of the 1990s (Wackernagel and Rees 1996a, b) and extended by and Wackernagel et al. (2018), several other footprints were defined. Čuček et al. (2012) reviewed and presented environmental (e.g. carbon (Wiedmann and Minx 2008) and water footprints (Martins et al. 2018)). Economic (e.g. economic footprint) and social (e.g. social and poverty footprint) footprints have been developed to assess sustainability. Strongly focusing on pollution, more types of footprints such as chemical (Panko and Hitchcock 2011), urban nutrient (Lin et al. 2014), nutrient (Groenman et al. 2016) and urban contamination footprint (Baltrėnaitė et al. 2018) were developed. A ‘footprint’ is understood as a quantitative measure of the appropriation of natural resources by humans (Hoekstra 2008) and is suggested to describe how anthropogenic activities impose different types of impacts on the environment and thus the global sustainability. Some of conceptual formulas for footprints will be provided.

1.4.1

Ecological Footprint

The concept of the ecological footprint was first introduced in 1996. Wackernagel and Rees (1996a, b) also described a methodology for calculating the ecological footprint, which integrated the concepts of the ecological footprint and bio-capacity. The ecological footprint covers the quantity of biologically productive land or marine area required for particular economic activity or population in order to obtain supplies and to absorb waste. The ecological footprint is measured in gha of the global earth (Eq. 1.14) (Galli 2015). EFc ¼ EPP þ EFI  EFE ¼ n n n X X X Pi Ii Ei ¼  EQFi þ  EQFi   EQFi Y Y Y W,i W,i i¼1 i¼1 i¼1 W,i

ð1:14Þ

where EFc—the ecological footprint of consumption (gha); EFP, EFI, EFE—the ecological footprint of production, import and export; Pi, Ii, Ei—produced, imported

1.4 Footprints

29

and exported quantity of product i (t per year); Yw,i—the global average of product i (t product per year i); W—global average (t per year). The ecological footprint (EF) of the state can be calculated according to Eq. 1.15 (Galli 2015). EF ¼

X Ti  EQFi , Y wi i

ð1:15Þ

where Ti—the annual quantity of product i consumed by state n (t); Ywi—world average yield product i (t ha); BC ¼

X

AN,i  YFN,i  EQFi

ð1:16Þ

where BC—biological capacity (g/ha) (Eq. 1.16); AN,i—area required for product i in a particular country (ha); EQFi—equivalence factor characteristic of the type of land to manufacture product i (gha/ha); YFN,i—yield factor typical of each country to manufacture product i (non-dimensional value). The concept of ecological ‘deficit’ is also used (Eq. 1.17). Ecological deficit ¼ ecological footprintðghaÞ  biological capacityðghaÞ ð1:17Þ The ecological footprint is calculated with reference to the global hectare called the relative surface area. Each global hectare corresponds to the capacity per hectare of land of the global average productivity (crop, pasture, forest, fishing) to provide ecosystem services (Galli 2015). The ecological footprint is widely used as an indicator for measuring ecological sustainability and is presented as generalized, multiple anthropogenic assessment (Galli 2015). The ecological footprint methodology is applied for assessing product impact on different economic sectors, world regions and countries, and therefore is an area of interest at the scientific and political level. For calculating the ecological footprint of different cities representing the same state, it can vary considerably depending on the country. It is estimated that the ecological footprint in Canadian cities makes 9.86 gha in Calgary, 9.45 gha in Edmonton, 6.89 gha in Quebec, 7.36 gha in Toronto and 7.71 gha in Vancouver. UK cities are presented by 5.22 gha in Bristol, 5.76 gha in Edinburgh, 5.21 gha in Glasgow, 5.25 gha in Liverpool, 5.48 gha in London and 5.36 gha in Manchester (Baabou et al. 2017). The ecological footprint helps with understanding complex relationships between many environmental problems but does not include economic and social indicators. Converting data into the area unit can be problematic. Data may be difficult to obtain, and therefore the problems of data uncertainty may occur. The ecological footprint can be used at household, urban, regional and state levels.

30

1.4.2

1 The Importance of Technogenesis and Sustainable Environmental Protection. . .

Nutrient Footprint

The N footprint model was first developed in 2010 by Galloway and Leach who defined N footprint as the total amount of N released to the environment as a result of entity resource consumption (Leach et al. 2012). Taking a life cycle approach to nutrient supply for a city, the nutrient footprint can be calculated by Eqs. (1.18) and (1.19) (Lin et al. 2014): XX NPfp ¼ Ni  L j XX N i  L j  Rij NPfpr ¼

ð1:18Þ ð1:19Þ

where NPfp is the nutrient footprint that represents all nutrients lost to the environment during the life cycle of a good expressed in the total units of N or P; j represents different stages of the life cycle, including mining, production, transportation, consumption and waste treatment; Lj is the amount of nutrient released at different life stages; Ni represents the consumption of different goods containing N and P in the city; i shows different types of goods, including food and non-food; Rij is the release factor of good i into different environments, including air, water and soil at life stage j; NPfpr indicates the amount of nutrient release of a good into different environments R that involve the air, water or soil environment.

1.4.3

Chemical Footprint

The chemical footprint describes the potential environmental hazard posed by the product with reference to its chemical composition, human health and environmental hazardous ingredients. The carried out analysis describes in detail the chemicals used throughout the complete life cycle of the product (Panko and Hitchcock 2011). Research literature has not fully explored the concept of the chemical footprint, and therefore no exact definition has been proposed. According to Panko and Hitchcock (2011), the chemical footprint is defined as potential risk caused by a product due to its chemical composition, human and ecotoxicologically hazardous constituents as well as because of the impact of certain components during the life cycle. Its analysis should include statistics for chemical elements as far as they are consumed, produced and replaced during the life cycle. The above definition of the chemical footprint requires the life cycle approach in combination with the risk assessment approach. It is the fundamental element that allows the concept of the chemical footprint to be applied as the concept of the sustainable management of chemicals. A sustainable approach to the management of chemicals in the assessment of chemical pollution must integrate their impact on ecosystems, benchmark product analysis and evaluate the impact of different industries (Rockstrom et al. 2009).

1.4 Footprints

31

Sala and Goralczyk (2013) evaluated the chemical footprint on the macro-scale across the European Union. The introduced method involved life cycle assessment applying databases, including a limited number of products and evaluation methods for product exposure. The chemical footprint was calculated on the basis of statistical information on the amount of emissions in the European Union, which covered more than 300 chemicals and 30 representative items of import and export data. The concept uses two steps to calculate the chemical footprint: • Step 1 includes the assessment of the impact done by the chemical on various environmental media (soil, water, air), the typology of pollution sources (focused, diffuse pollution), potential impact on human health and the environment. This is in line with the definition of the chemical footprint by Panko and Hitchcock (2011) and the current assessment of chemical risk. Thus, it is possible to calculate direct and indirect emissions of the chemical during the life cycle. • Step 2 assesses the potential environmental impact of the chemical in excess of its ability to recover. Life cycle assessment covers the following phases: (1) when the testing system is defined, the mass of the chemical is calculated for each environmental medium (soil, water, air) at each stage of the product cycle from raw material extraction to the stage of the final product (emissions per unit of output); (2) The assessment of the life cycle of the chemical includes its environmental impact. Sorme et al. (2016) evaluated the chemical footprint of Sweden using data from the European Pollutant Emission Register, which is openly available and contains data on the emissions of 54 materials to the air and water from stationary sources. This register covers 91 substances falling into 7 categories: heavy metals, pesticides, chlorine organic compounds, organic and inorganic materials, greenhouse gases and other gases. This study provides data on emissions to the air and water from energy industry, metal production and processing, mineral industry, waste and sewage treatment, paper and wood production and processing, intensive livestock farming, aquaculture, food and beverage industries. Data were transformed and combined using the USEtox model and life cycle assessment. The method developed by the scientist allows assessing the potential impact of polluted industrial emissions on human toxicity and ecotoxicity. The effects of the chemical are evaluated using toxicity data and expressed as comparative toxic units. Sorme et al. (2016) found that a toxic impact on human in Sweden was 720 kg of comparative toxic units (CTU). The comparative toxicity unit is calculated by anticipating the total human population sickness rate per unit mass (kg). Zn emissions account for 68% in the air and water and Hg emissions account for 13% in the air of the total human toxicity. As, Cr and Pb emissions into the air are also an important issue. In Sweden, steel, metal and paper industries cause the highest toxicity to humans. The chemical footprint for ecosystems has been estimated to be 6.26  109 (CTUe) kg. Ecosystem toxicity is caused by Zn, Cu and fluoranthene. Zn emissions make 63% of all emitted pollutants, fluoranthene counts 13%, halogenated organic compounds, anthracene, Ni and As are also important. Paper industry contributes to the greatest impact on ecosystems. Sala and Goralczyk (2013) found

32

1 The Importance of Technogenesis and Sustainable Environmental Protection. . .

that Cu, Va and Zn were the most important chemical elements and, along with endosulfan (active substance of plant protection products), exerted a toxic effect on ecosystems in Europe. Meanwhile, Sorme et al. (2016) established that Zn, fluoranthene and Cu were the most important chemicals producing toxic effects on ecosystems in Sweden.

1.4.4

Urban Contamination Footprint

The present urban population worldwide makes approximately 50% (UNFPA 2007; WB 2012) and is likely to reach 60% by 2020 and 65–70% by 2030 (UNPD 2002; Zhou et al. 2015). The role of urban areas on the global scale becomes very critical, since urban settlements consume 70–80% of all resources. The growing population and urbanization are responsible for the increasing release of pollutants into the environment on the global scale. In the case of non-sustainable urban metabolism, the urban ecological footprint increases mainly due to inadequate consumption and technological inefficiency leading to the generation of a large amount of waste (in the broad sense), which in turn intensifies a technogenic load on the biosphere (Fig. 1.9). Pollution density should be considered in both vertical and horizontal dimensions and might represent a growth in pollution intensity. Pollution density was referred to the contamination Boundaries of urban contaminant footprint Local urban aerogenic emissions

Long-range aerogenic emissions

ECONOMY

Urban contaminants discharged to surface water

Resources

Contaminants leached to urban soil

Contaminants leached to groundwater

Fig. 1.9 The inflow and outflow of pollutants within the boundaries of the urbanized area (Baltrėnaitė et al. 2018)

1.5 Geochemical Barriers Preventing from the Spread of Pollutants

33

footprint suggesting that the impact of urban activities was negligible as long as it was neutralized by the self-purification of the biosphere. When applying the form of mass balance, the mass of the urban contamination footprint (Mfootprint) can be described by Eqs. 1.20 and 1.21: M footprint ¼ M extracted  M returned to entrails   M footprint ¼ M in products þ M immobilized by barriers þ M labile  M returned to entrails ,

ð1:20Þ ð1:21Þ

where Mextracted is the amount of pollutants extracted in the form of ores from the Earth, Mreturned to entrails is the amount of pollutants returned to the deep layers of the Earth, Min_products is the amount of pollutants used for manufacturing products, Mimmobilized by barriers is the amount of pollutants released in the form of waste (through emissions to the air, water and soil) to the environment but immobilized by barriers and Mlabile is the labile (mobile and bioavailable) amount of pollutants transported by transporting media. The equations include static (e.g. amount of pollutants in products and immobilized in barriers) and dynamic (e.g. amount of pollutants in the labile form) amounts of pollutants. Although the equations are conceptual, they indicate the factors that influence the urban contamination footprint. As soon as a pollution load exceeds the self-purification capacity of the biosphere, deterioration starts. It manifests itself as a lower quality of food (mainly due to a lower quality of the soil as the effect of mass-production, which, to some extent, is characteristic of non-sustainable urban metabolism), climate change (carbon footprint is a widely discussed feature), decline in soil quality and the subsequent health problems.

1.5

Geochemical Barriers Preventing from the Spread of Pollutants

As for the natural environment, chemical elements are melted and removed in some sections of migration flows while others are precipitated under changes in migration conditions. This creates areas for the removal and precipitation (accumulation) of chemical elements. They often coincide with geochemical barriers—due to various reasons, with the areas of a sudden decrease in the mobility of chemical elements. Lietuvninkas (2012a, b) defines the geochemical barrier as a relatively small section of the hypergenesis zone or the Earth’s crust in general where the intensity of the migration of chemical elements suddenly decreases and concentration occurs. It can be described as landscape geochemical barriers in the areas of hypergenesis. Many technologies, especially designed to clean up the environment (i.e. environmental protection technologies), are based on the phenomena existing in the natural environment. These phenomena are then transferred to the engineered systems (e.g. biofiltration systems, adsorption systems for pollutant adsorption from

34

1 The Importance of Technogenesis and Sustainable Environmental Protection. . . Aerodynamicsedimentary Mechanical

Natural or anthropogenic Geochemical barriers

Physico-chemical Biogeochemical By phase creation or addition

Engineered

Using barrier Using solid agent Using foree field or gradient Using biological systems

Aerogenic

Adhesive Hydrodynamicsedimentary

Hydrogenic

Filtrative

Based on Eh conditions

Oxidative Sulfur hydroxide Gleyic

Based on pH conditions Based on key media parameters Multiple

Acid Alkaline Volatilization Sorptive Thermodynamic Carbon dioxide Complex Concurrent Mixed

Fig. 1.10 The classification of natural, anthropogenic and engineered geochemical barriers (adopted from Perelman 1967; Seader and Henley 2006; Lietuvninkas 2012a, b)

water). While natural and anthropogenic geochemical barriers exist in the natural environment (e.g. humus layer in the forest) or are built within the reach of the immediate environment (e.g. barriers for limiting pollutant migration from a landfill), the engineered barriers are designed in the engineered systems (e.g. biocharbased adsorption systems for water cleaning purpose). Figure 1.10 presents the extended classification of natural, anthropogenic and engineered geochemical barriers adopted from Perelman (1967), Seader and Henley (2006), and Lietuvninkas (2012a, b). It was described in detail by Baltrėnaitė et al. (2018).

1.6

Sustainable Environmental Protection Technologies

The impact of production on the environment is determined by the fact that, during the process of manufacturing, raw materials are used, products are manufactured and waste is generated. The process of manufacturing includes physical, chemical and biological processes actualized through technological equipment. Environmental technologies are technological solutions to environmental problems and mitigate the impact of manufacturing on the environment. Environmental technologies are applied in such sectors as industry, agriculture, services and transport as well as everyday household. Klavins et al. (2010) classified

1.6 Sustainable Environmental Protection Technologies

35

environmental technologies into the following three groups according to the stage at which the environmental problem is addressed: • Clean production technologies eliminating the root causes of environmental pollution or reducing their impact. Production can be made ‘clean’ if emissions and waste are used as resources for another plant. It is possible to make production more efficient with lesser input (materials or energy) producing the same output of the same or higher quality. In order to implement clean production, technological processes stimulated in the enterprises are changed or enhanced by other processes. • End-of-pipe environmental pollution reduction technologies minimize pollutants entering the environment. Environmental pollution reduction technologies are installed in order to purify exhaust gases and wastewater and organize waste management. • Climate technologies reduce greenhouse gas emissions or separate these gases before release into the environment. Climate technologies include both abovementioned groups of technologies when they reduce the impact on climate change and those technological processes that decrease greenhouse gas emissions into the atmosphere. Eco-efficiency is considered as a parameter for the operational efficience of technologies and shows the consumption of raw materials, water and energy per unit of the good produced or services rendered. Eco-efficiency is used for describing the progress of production and national economy towards sustainable development. The most eco-efficient environmental protection technologies are those solving environmental problems at the earliest stage and are characteristic of (1) reduced consumption of materials, energy and water; (2) reduced toxic discharges; (3) increased recycling of materials; (4) sustainable use of renewable sources and (5) increased durability of materials and products (Klavins et al. 2010). Clean [environmental] technology is the most important factor in the economic growth of industries and seems to play the main role not only in the idea of cleaner production but also in sustainable development (Shramm and Hackstock 1998). Each company that strives for reaching a competitive position on the market and wants to be environmentally friendly should compile the strategy for technology (Babilas et al. 2006; Szewieczek et al. 2003). In practice, the technology and realization of technological processes is in exact relationship from the elements of working and natural environments (Fig. 1.11) (Schramm 1998; Doniec 2002). Considering the fact that process technologies should be carried out from a cleaner production point of view, the development of sustainable technology should be based on general cleaner production aims. The sustainable technological process is based on clean production, and therefore should tend to reducing or minimizing the amount of (Schramm 1998): • Resources consumed • Waste and emissions generated

36

1 The Importance of Technogenesis and Sustainable Environmental Protection. . .

Fig. 1.11 Technology and the natural environment (Doniec 2002)

Natural

id w

Technology

es ast

sw

Li qu

Ga

ast es

Working

Solid wastes

Environment Environment • Hazards of waste and emissions generated (mainly by using the substitution of input materials) • Risk of accident or malfunction The above-mentioned purposes essentially correspond to prevention criteria for the IPPC-Directive. According to the above pro-ecological targets, companies should apply environmental protection technologies with technological innovations (Moors et al. 2005): • Auxiliary technology that includes all supporting technologies to monitor and control the existing production process and all logistics and technological infrastructure. • End-of-pipe technology that can be defined as all techniques added at the end of the existing processes to decrease the amount of environmentally harmful emissions. • In-process technology that includes improvement in and the application of the existing technology—changes are integrated within the process hardware of the existing production steps. • New technology that embraces a new production process principle or a new technical plant design. Generally, most companies, when leading changes in their production process, apply the first three stages of technological innovations: auxiliary technology, endof-pipe technology or in-process technology. However, introducing a new (sustainable) technology brings the best profits. Table 1.5 presents some exemplary technological innovations in material processes (Hooper 1995). The minimization of waste and emissions and reductions in material and energy inputs are the most important environmental aims. Sustainable technological development and innovations do not automatically lead to the total reduction in the environmental burden of industrial production. However, technological innovation

1.6 Sustainable Environmental Protection Technologies

37

Table 1.5 The sequences of pro-ecological modifications in the field of materials and processes (Hooper 1995) No. 1.

Stage Improvement of cleaning methods

2.

Reduction of wastes stream

3.

Designing

4.

Formation of new infrastructure forms Integration of technical sciences

5.

Contents • Improvement of measuring methods • Investigation of new cleaning method • Modification of technology, production process, machines • Introduction of effective steering systems • Modification of materials • Reduction of water, energy and raw materials consumption • Designing of products in recycling aspects • Modification of energy using systems • Modification in range of transport and communication • Joining of new technical disciplines

is an important factor and seems to play the central role in the long-term initiation of cleaner production. Environmental improvement in company’s strategy by applying the idea of cleaner production linked with sustainable technologies leads to manufacturing environmentally friendly products and to an increase in the company’s position on the market. Cleaner products must be given an essentially stronger meaning in the future because of necessary transition to sustainable economy and development (Nowosielski et al. 2007). Brey (2017) suggested that the absence of modern technology there probably would not be a problem of sustainability to begin with. Many sources of pollution and environmental degradation are the result of the large-scale development and use of modern technology, including the extraction, processing and consumption of fossil fuels, the large-scale dissemination of chemical pollutants, the production of non-biodegradable waste like plastics, glass and pesticides and soil degradation through modern mechanized agriculture. At the same time, technology is also a key factor in any solution to the environmental problem. Any such solution will have to consider how technologies can be made more ecological and sustainable and how new technologies can be developed to mitigate environmental pollution and degradation. Environmental efficiency is indeed a new goal of technology, including economics and management science. The overall system involving the institutions of technology and economy as well as most of the basic principles of these two institutions are to remain intact. The increased environmental efficiency and ecological soundness of the products manufactured by more ecological industry under conditions of a more ecological economic system is then to guarantee the sustainable patterns of consumption. Sustainable technologies must be developed and applied in a way that the manufactured products contribute to sustainable consumption:

38

1 The Importance of Technogenesis and Sustainable Environmental Protection. . .

• The use of sustainable materials (e.g. biodegradable plastics, recyclable metals) and sustainable, renewable energy sources (e.g. devices that run on solar energy or green batteries). • Designing energy efficiency in the products that consume energy. • Making durable products that are made of durable materials, have a long life cycle and the ability to be repaired or upgraded so that no replacement product is needed. • The adoption of product life cycle approaches in which company’s total environmental impact is accounted with respect to the product, from raw materials to production, distribution, consumer use and disposal. • Designing products that impede or discourage unsustainable behaviour and lifestyles and encourage conservation (e.g. showers that switch off after 5 min of use). • Designing products that support or require sustainable behaviour and lifestyles (e.g. products that make the use of bicycles as a means of transportation more attractive). To achieve sustainable development, the contribution of manufacturing must be based on clean production requiring that manufacturing must incorporate sustainable environmental protection technologies. These cannot be limited to cleaner production technologies that help with avoiding manufacturing residues due to the fact that manufacturing process is not 100% efficient or 100% safe. Therefore, cleaner production technologies combined with end-of-pipe technologies driven by technical innovation, supported with the emphasis on ecological modernization and the need to increase the eco-efficiency can be defined as sustainable environmental protection technologies.

Chapter 2

Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies

The chapter provides the classification of barriers. The position of natural and artificial biogeochemical barriers in this classification is defined as an example of the first-level sustainability of environmental protection technologies. The role of the barriers is shown considering the bio-accumulating properties of the ligneous and phytoremediation capacity of gracious plants. The chapter also discusses the application of the method for dynamic factors used for assessing the risk of contamination and the effectiveness of the considered barriers. The obtained results are discussed based on the studies into real operational conditions for waste incineration and oil refining plants. Technology is commonly accepted as ‘a coherent set of processes and equipment required for producing a certain product’. In the case of environmental protection technology, processes are realized as activities removing pollutants from the air, water or soil and focus on engineering equipment, whereas production is understood as treated air, water or soil. The dimension of sustainability should complement them with the aspects of sustainable development philosophy. This work imposes a wider view on environmental protection technologies. Thus, let us have a look at a specific example. Pine bark is well known for accumulating pollutants, and the greater is their concentration, the higher is expected the content of contaminants in ambient air. Therefore, pine bark resembles the equipment. The process in this case is the indication of ambient air quality. The engineering concept of technology is broadened by offering the identification of ‘processes’, ‘equipment’ and ‘production’ in the natural environment. Processes should include the wellknown pollutant retention phenomenon, e.g. aerodynamic sedimentation based on a drop in pollutant air flow capacity caused by pollutants due to the roughness of bark surface, which acts as a flow barrier and reduces air flow. The ‘output’ of this technology is cleaner air. Pollutants move from one component of the biosphere— air—to the composition of another component of the biosphere—tree. However, pollutants are not eliminated, thus decreasing their mobility. This example is the one of two technologies—pollutant immobilization and monitoring ambient air quality. The sustainability features of these technologies are obvious: technology based on © Springer Nature Switzerland AG 2020 P. Baltrėnas, E. Baltrėnaitė, Sustainable Environmental Protection Technologies, https://doi.org/10.1007/978-3-030-47725-7_2

39

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2 Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies

natural processes is a direct function of the biosphere, which is socially highly acceptable to society, and economic costs are incurred only when it comes to quantifying the chemical composition of bark. Thus, the function of bark to store airborne pollutants can be attributed to sustainable environmental protection technologies for immobilizing pollutants and indicating environmental quality. Nevertheless, bark is only one example of biosphere components that work in the direction of reducing environmental pollution. Onwards in this chapter, in terms of pollutant retention, more examples of other biosphere components generally referred to as deposition media are provided. It is worth distinguishing between natural and seminatural technologies (barriers). The latter differ from the former ones due to possible human intervention into semi-natural technologies. The cultivation of plants opted for the accumulation of a specific pollutant in the contaminated sites is a good example of semi-natural technology (barrier). It can be accepted as semi-natural because of human input manifested in the selection and concentration of plants in the specific locations reporting a decrease in local pollution with the help of plants (phytoextraction, phytostabilization). The following sections concentrate on more detailed examples of the environmental protection technologies of the first-level sustainability and discuss their applicability and benefits.

2.1

Natural and Semi-Natural Barriers

People have long been interested in plant properties that can indicate the quality of the environment. Plants are immobile and adapt to changing environmental conditions by their external and internal structure, activity, proliferation or decay. The direct measurement of pollutants gives an indication of their concentrations, but such studies are expensive. For example, continuous air quality monitoring in Lithuania takes place in 14 air quality survey stations situated in 9 cities and in 3 background air quality stations built in national parks. Twelve parameters are monitored in the cities and 7 in the background stations. Still, the number of monitoring stations in the cities and areas affected by huge industrial objects is insufficient. What is more, the structure of the technogenic pollution of the atmospheric air is quite complex and dynamic. The assessment of environmental quality using sensitive or pollutantaccumulating organisms—bioindicators or biomonitors—is a cheaper option (Kupčinskienė 2011). Bioindication is the evaluation of environmental effects on biological objects or systems according to their response to those effects (Stravinskienė 2005, 2009). It is essentially an instrument of traditional biology. Indicator taxa are used for determining the consequences of environmental changes, habitat variations or decomposition. Several years ago, the effects of climate change and the impact of rapid changes were also taken into consideration. Indicator species can be used for representing other groups of organisms or larger communities. Bioindication and biomonitoring must provide information on the extent or degradation of the polluted ecosystems. The applied bioindication may assist in generating

2.1 Natural and Semi-Natural Barriers Fig. 2.1 Bioindication and an illustrative diagram of biomonitoring (Stravinskienė 2009)

41

Bioindication (quality) Biomonitoring (quantity)

Optical Physical-chemical Chemical Sensitivity

Accumulation

two types of data—generic risk-oversimplifying information and specific data that is comprehensive, objective, reproducible and accurate. A biomonitor is an organism (or a part of an organism or the community of organisms) that has collected information on the quantitative aspects of environmental quality. The biomonitor is always a bioindicator; however, the bioindicator does not necessarily meet the requirements for the biomonitor (Fig. 2.1) (Markert et al. 2012). Gravity and surface phenomena (electrostatic and Van der Waals forces) determine the release of air pollutants into the ecosystem. Thus, the use of plants for evaluating aerosol deposition can provide more realistic results than the employment of special collecting equipment. Vegetation and forest floor (such as moss) are pollutant deposit media allowing retrospective monitoring that cannot be performed using collecting equipment. In addition to the above, there are many economic and practical benefits, including low cost, high availability, the absence of maintenance, redundant sources of electricity or other types of energy. Certainly, the total biological response of the plant assesses the synergistic and antagonistic effects of pollutants, and therefore is more comprehensive than instrumental measurements. The major shortcoming of biological systems as biomonitors is that their response (both instantaneous and accumulative) is subject to the substance tested, specific parameters for the plant (age, health status), environmental parameters (soil type, humidity, nutrient content in the soil, precipitation, relative air humidity, location, temperature) for the cultivated plants and conditions for cultivation. Therefore, the reproducibility and standardization of biomonitoring data may not be as accurate as instrumental monitoring. Another shortage is lower accuracy of the data provided. The reaction of an organism is frequently non-specific. The ability of biological systems to integrate synergistic and antagonistic effects of pollutants is an advantage if the overall ecological situation is assessed. Basic requirements for passive cumulative biomonitoring of air pollutants include (a) widespread throughout the monitoring area; (b) wide geographical range; (c) the possibility of distinguishing contributions of an atmospheric origin; (d) easy sampling and (e) easy identification. Because of unfavourable locations, many plants have developed the ability to enrich high concentrations of individual elements, often regardless of whether these elements are physiologically useful or not. These plants are called accumulators. With respect to biomonitoring, there should be the correlation between the

i

Ind

Increasing environmental pollutant concentration

Acute dose

ct c effe

Rejector

100 ni Chro

or cat

b)

Chronic dose t Time shiffing

50

Activity of organisms, populations or ecosystems, in %

Accumulator

fect te ef Acu

Increasing pollutant concentration in organisms

a)

2 Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies

Conc. of toxic substances

42

Fig. 2.2 The impact of substrate concentration on living organisms: (a) varying uptake activities in living organisms as a function of substrate concentration; (b) comparison of the effect of the acute and chronic doses of toxic substances on living systems

environmental concentration of a pollutant to be observed and the content in the proper organism. So far, a linear, indicative interrelation of both measure values of any organism has not been found. Concentration ranges that might be interesting for bioindication and biomonitoring showed very small ‘measuring ranges’ (black bars) in accumulator and excluder organisms (Fig 2.2a). For example, regardless of the number of elements in the soil, beeches have a high amount of Zn. Accumulative behaviour that may have genetically predetermined origins rather than the ones determined by locations makes it possible to chemically fingerprint a very wide variety of plant types. In the future, this might lead to chemical characterization, and therefore to the systematization of individual plant types, which could provide information about evolutionary connections at the phytosociological level. The rejection or reduced uptake of individual elements occurs less frequently than the accumulation of elements, but rejection behaviour has been demonstrated for the numerous species of plants. A reduction in the concentration of an element in an organism can be the result of complete or partial exclusion. For example, bacteria, algae and higher plants contain populations resistant to PTEs and able to reduce considerably the uptake of PTEs by excreting mucilagenous substances or by changing their cell walls (Markert et al. 2012). In the context of activity studies, toxicity monitoring in particular, one must generally differentiate between acute and chronic working models. As shown in Fig. 2.2b, the acute delivery of a substance is usually followed by a direct short-term effect on the organism or population. These types of toxic effects are relatively easy to generate experimentally in the laboratory by adding different substances to the tested organisms. However, it is more difficult to investigate the chronic effects of a substance, i.e. the sub-threshold long-term application of a substance that only shows an effect (usually the toxic one) after lengthy constant uptake. These mechanisms of chronic activities are considerably more difficult to study because all other values and parameters that could influence the tested organism have to be kept constant over a considerable period of time. The chronic effect of the substance often differs from an acute effect only by its chronologically displaced occurrence. Thus,

2.1 Natural and Semi-Natural Barriers

43

the chronic effect usually only creeps along and, in reality, is often recognized too late. The use of the PTEs accumulating plants becomes a useful technique (called phytoremediation) for environmental clean-up (Chaney et al. 1997). Hyperaccumulators are called plants able to accumulate more than 0.1% of PTEs in their dry weight (d.w.) (Baker and Brooks 1989). There are three principal mechanisms used in phytoremediation technology: phytoextraction, rhizofiltration and phytostabilization (Salt et al. 1995b; Donahue 2000). Phytoextraction is the use of plants for removing inorganic contaminants, primarily PTEs, from the polluted soil. In this approach, the plants capable of accumulating high levels of PTEs are grown in the contaminated soil. At maturity, PTE-enriched above-ground biomass is harvested, and a fraction of the soil contaminated with PTEs is removed (Lasat 2002). Phytoextraction is the easiest way to remove PTEs such as Ni, Zn and Cu because these PTEs are preferred by a majority of the 400 hyperaccumulator plants. Most hyperaccumulators (approximately 75%) are characterized like Ni hyperaccumulators (Baker and Brooks 1989). Some problems associated with the continuous phytoextraction of PTEs from soils is related to the fact that some PTEs such as Pb are largely immobile in the soil and their extraction rate is limited by solubility and diffusion to the root surface (Lombi et al. 2001; Watanabe 1997). Several chelating agents such as citric acid or EDTA have been studied for their ability to mobilize PTEs and increase their accumulation in the different species of plants (Huang et al. 1997; Cooper et al. 1999). Rhizofiltration is the use of plant roots for removing toxic PTEs from polluted waters (Dushenkov et al. 1995). Once the roots are saturated with the contaminant, the plants are harvested including the roots. In Chernobyl, Ukraine, sunflowers were used in this way to remove radioactive contaminants from groundwater (EPA 1998). Phytostabilization is the use of plants for reducing the bioavailability of PTEs in the soil (Ruttens et al. 2006). Phytostabilization focuses on the long-term stabilization and containment of the pollutant. Different from phytoextraction, phytostabilization focuses mainly on sequestering pollutants in the soil onto the roots or precipitated within the rhizosphere, but not in plant tissues (Conesa et al. 2007). Phytostabilization reduces the mobility of the contaminant and prevents the further movement of the contaminant into groundwater or the air and reduces bioavailability for entry into the food chain. An example application of this sort uses a vegetative cap to stabilize and contain mine tailings (Mendez and Maier 2008). Thus, organism bioaccumulation functions as a barrier. The need for reducing the mobility of pollutants (i.e. for increasing the immobilization of contaminants) is growing, especially when considering persistent and long-term contaminants, e.g. metals. Immobilization is one of the three innovative environmental protection technologies discussed by Freanzle et al. (2012). Therefore, the immobilization of pollutants can be achieved in two main directions—by using biosphere components (e.g. via natural barriers) and engineering approaches (e.g. via engineered barriers). A natural barrier is understood as the place where the migration of contaminants reduces dramatically while their concentrations increase. According to Perelman (1967), lithologic boundaries in the supergene zone where conditions for migration

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2 Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies

change drastically and the concentrations of chemical elements begin to rise are called geochemical barriers. The biological type of the geochemical barrier was referred to as biogeochemical and was defined as an organism or its organ, the chemical composition of which implies it is related to the concentrating function of living organisms (Lietuvninkas 2012a, b). In general, all above-mentioned types of geochemical barriers can be observed in the natural environment and are natural geochemical barriers. Natural barriers used for determining the level of contamination are classified as natural depositing media (Butkus and Baltrėnaitė 2007a; Butkus et al. 2008; Baltrėnaitė et al. 2010; Baltrėnas and Vaitkutė 2011). These include the geochemical and biogeochemical components of the biosphere and indicate and/or accumulate environmental pollutants. Next, the main ones will be described.

2.1.1

Snow Cap

A snow cap is considered an almost ideal short-term depositing medium for assessing atmospheric deposition (Lietuvninkas 2012a, b). The analysis of domestic and world practice shows the growing interest in theoretical and applied investigations into the snow cap (Kalyuzhnyi and Shutov 1998). The pollution of the snow cap reflects the degree of human impact on the environment, because the snow cap is able to retain and accumulate the substances depositing on its surface from the atmosphere. Information on the chemical composition of the snow cap allows deriving integral pollution estimates of various ecosystems over long periods and differentiating the areas around towns and industrial regions according to the degree of technogenic impact. This is especially important under the conditions of northern landscapes where the snow cap persists over 6–8 months. Thus, the snow cap may be considered the most suitable research object for assessing environmental pollution by industrial aerosols (Meyer and Wania 2008). Data on the amounts of individual pollutants and their total amount accumulated in the snow cap in both the areas adjacent to industrial enterprises and background areas allow one to assess the environmental impact of various enterprises (Vasilenko et al. 1985). Pollutants effectively accumulate in snow, which acts as an aerodynamic mechanical barrier for small particles suspended in the air. The soluble forms of snow cap chemical elements in urban areas, in comparison with the insoluble ones (snow dust), are many times lower, and therefore snowmelt water analysis is not always necessary; however, there is a relation between soluble and insoluble forms. This relation is characterized by inverse proportionality, for example, closer to contamination sources in urban areas, the part of the soluble forms of metals relatively decreases while the load of dust increases when approaching the city or contaminated area (Lietuvninkas 2002). Snow and ice records have provided historical indications of changes in the occurrence of PTEs in the atmosphere in response to the anthropogenic emissions of such elements. Atmospheric pollution from the mid-1700s to present times has also been documented for various PTEs, including Pb, Cd, Cu and Zn (Murozumi

2.1 Natural and Semi-Natural Barriers

45

et al. 1969; Boutron et al. 1991; Candelone et al. 1995) and Hg, Pt, Pd and Rh. Snow and ice records have provided evidence that the natural cycles of PTEs such as Cr, Cu, Zn, Ag, Pb, Bi and U have been greatly perturbed in the recent decades even in the remote Antarctic atmosphere. This is primarily due to the long-range transport of manmade pollutants from the surrounding source areas (Rosman et al. 1994; Wolff and Suttie 1994; Planchon et al. 2002; Vallelonga et al. 2002. Data obtained from Greenland and Antarctic snow and ice have shown that environmental pollution by PTEs has become global. Spatial data on the occurrence of PTEs in temperate to low-latitude snow and ice are required to better characterize the extent of human impact on the natural geochemical cycles of these elements. Recently, several studies have reported changes in the occurrence of PTEs related to human activities in dated snow and ice from the Alps and high-altitude Bolivian ice-cap (Van de Velde et al. 1999). The concentrations of PTEs were measured in snow and ice samples at highaltitude sites in the Eastern Tien Shan (Li et al. 2007), on Muztagh Ata in the Eastern Pamirs in northwest China (Li et al. 2006a, b) and on Everest in the Himalayas (Kang et al. 2007; Duan et al. 2007). Such data provided the aspects of the changing occurrence of various PTEs in snow and ice from one area to another. PTEs captured in permanent snow can be used as tracers of air mass transport, thus revealing the history of local and global pollution. PTEs show distinct seasonality, i.e. higher concentrations during the non-monsoon season than those during the monsoon season (Liu et al. 2010). Snow samples indicate seasonal differences in the concentrations of the measured elements. Glacio-chemical studies of snow and ice in the central Himalayas have also revealed seasonal differences in major ions (e.g. Ca2+ and SO42
) related to the influx of mineral dust between monsoon and non-monsoon seasons (Shrestha et al. 2000; Kang et al. 2004). Analytical instrumentation enabling analysis at the ultra-trace level of chemical elements has become available, and therefore the regional surveys of snow chemistry can be carried out to answer such questions. Chemistry studies of surface snow in Svalbard seem to confirm an environment charged with the relatively high concentrations of pollutants. found that anthropogenic pollutants in the snow cap display marked seasonality, concluded that the three main man-made measured pollutants (i.e. NO3
, NH3+, and SO42
) were all highly correlated and suggested that each was derived from the same source region (Simoes and Zagorodnov 2000). Three main factors could cause changes in concentration at the deposition site (i.e. original precipitation at the core sites): (1) modifications in the path followed by air masses transporting impurities from the source to the receptor; (2) the scavenging process; (3) changes in the strength of the source. In general, PTEs such as Pb, Cd, Ni, Zn, Mn and Cu are not found in snow. Therefore, even trace amounts of these PTEs indicate possible pollution. The essential characteristics of atmosphere pollution in the area of heavy snowfall were investigated in detail in Sivas city, Turkey. It was aimed at monitoring PTEs in snow as an indicator of pollution in the urban atmosphere. The obtained results showed that the snow cap could be used as a simple and effective indicator for the urban and industrial pollution of the atmosphere (Elik 2001). Investigation into the occurrence

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of PTEs in the successive dated snow and ice layers that have accumulated in central Greenland over time has allowed us to obtain valuable information on past and recent changes in the hemispheric scale cycles of these metals. Attention has been paid to short-time scales, i.e. intra-annual variations, although a good understanding of metallic element variations on such short time scales has the potential to provide very valuable information. It should allow us to better resolve the changing patterns of troposphere transport of PTEs from various sources over different periods of the year and this will assist in the interpretation of long time series data (Barbante et al. 2003). Compared to stormwater runoff, urban roadway snow exposed to traffic and winter maintenance practices has much greater capacity to accumulate and retain PTEs and other anthropogenic constituents. PTEs once released in the environment are not degraded. Partitioning between the dissolved and particulate-bound fractions of PTEs is influenced by their residence time, solid loadings, alkalinity, hardness and pH. For residual analyses, the specific surface area generally increased with a decreasing particle size while the predominance of the total surface area (SA) was associated with the medium to coarser size fractions. Metallic element mass trends followed similar general trends to that of surface areas. The characterization of the accretion and partitioning of these metals is the necessary first step towards the development of management and treatment strategies designed to address urban snow pollution (Glenn and Sansalone 2002). The release of organic pollutants from snowmelt water poses risks to aquatic and terrestrial organisms and to humans who rely on drinking water and food production from the regions that are seasonally snow-covered. Measured and model-predicted spring peak concentrations in waters receiving snowmelt motivate thorough investigation into organic pollution behaviour during melting. On the basis of the current understanding of snow metamorphosis, snowmelt hydrology and chemical partitioning in snow provide a qualitative picture of the processes involved in the release of organic pollutants from the melting snow cap. The elution sequence of organic substances during snowmelt is strongly dependent on their environmental partitioning properties and the physical properties of the snow cap. Water-soluble organic pollutants can be discharged in greatly elevated concentrations at an early stage of melting while the bulk of the hydrophobic chemicals attached to particles are often released at the end of the melt period. Melting of the highly metamorphosed and deep snow cap promotes shock load releases, whereas a shallow snow cap over a relatively warm ground experiencing irregular melting over the winter season is unlikely to generate notable peak releases of organic substances. Reliable numerical process descriptions will need to be developed to integrate water quality and pollution fate models (Meyer and Wania 2008). In contrast to inorganic snow chemistry, which has generated a wealth of information in the past several decades, the study of the fate of organic chemicals in association with snow and ice has been largely neglected. The limited understanding of the physics and chemistry of these systems and difficulties in conducting field studies under reproducible and controllable conditions have retarded the development of quantitative models describing snow pollution interactions. In order to

2.1 Natural and Semi-Natural Barriers

47

assess and evaluate the environmental fate and behaviour of hydrophobic organic chemicals (HOCs) in cold ecosystems, it is of particular importance to gain an extensive and, if possible, quantitative understanding of the efficiency and nature of snow scavenging of HOCs from the atmosphere, the behaviour of organic chemicals in the snow cap, especially as they age, the release of organic chemicals from the snow cap into the ecosystem during melting and the potential preservation of a depositional record of organic chemicals in glacier ice (Wania et al. 1998). Snow acts as a reservoir for acids in wintertime by absorbing and storing atmospheric pollutants. Falling snow collects pollutants in the atmosphere and snow also accumulates pollutants on the ground from the dry deposition of gases, aerosols and atmospheric particles. Normally, snow protects vegetation from the harmful effects of dry deposition for several months. The solubility of sulphur dioxide in snow is the highest just before snowmelt because the amount of water in snow is at its highest. ‘Black snow’ is coloured by carbon rich particles and has higher concentrations of acids than the other snow. The pH of black snow can be nearly as low as vinegar—about pH 3.0. Black snowfalls have been observed on Cairngorm Mountain in the Scottish Highlands where pollutants from Eastern Europe accumulate. When black snow forms just above the base of the snow drift, it can deliver especially high solute concentrations to the soil below. A deep blanket of snow contains many layers from different snowfalls with the varying levels of pollutants. The concentrated bands of impurities are formed as snowmelt and refreezes. Since wind and other forces redistribute and mix the layers in a snow drift, measuring the total amount of chemicals in the snow drift is difficult. Undisturbed polar snow is an accurate record of the past atmospheric conditions. Sampling snow cores in the Greenland ice sheet have revealed an increase in the amount of acids deposited, especially in the last 40 years. When snow begins to melt in spring, there is a concentrated surge of ions. Sulphate ions and nitrate ions liquefy first; hydrogen ions and chloride ions follow just after. Most precipitation stays in the snow pack until snow reaches the melting point. This concentrated surge of ions is known as acid shock that can cause the sudden death of many fish simultaneously. After a spring thaw, the pH of lake and stream water plummets and the concentration of aluminium in water rises. Fish are very sensitive to aluminium, as it blocks their gills and hinders their breathing. Although such fish kills are rare in North America and Britain, animals are still weakened by the sudden high acidity of water. At the end of the northern winter 1996–1997, 21 snow samples were collected from 17 arctic localities in Norway, Sweden, Finland, Svalbard, Russia, Alaska, Canada, Greenland and Iceland. Snow was moderately acidic with pH values between 4.6 and 6.1. The most acid samples (pH < 5.11, the 25th percentile) were from the sector of northern Europe between Sweden and Nova Zemblya. The samples from more remote areas or higher latitudes tend to have higher pH. Snow composition varies regionally by up to four orders of magnitude in terms of major element concentrations. Therefore, while attempting to reconstruct past changes in snow (or ice) composition, it is important to consider that at least a part of the reported variability can depend on the geographic location and weather pattern changes (influence of sea spray etc.) from winter to winter or within any season’s

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accumulated snow cap. Mineral dust inputs were detected by the ‘excess’ of Ca contents relative to seawater dilution trends, as observed in Alaska, Svalbard, Greenland and Sweden. There was no overall correlation between melt water pH and total SO42
concentration, although some samples defined a trend in decreasing pH with increasing non-sea salt SO42
. A weak local relationship existed between pH and NO3
in Sweden, Finland and Russia. No arctic-wide contamination or acidification process was detected, thus suggesting that long-range atmospheric transport was not operating at that scale.

2.1.2

Soil

Although aerogenic pollutant flows are not the only pollution source trapped on the soil surface, the soil is an alternative cover for snow during warm seasons and is a depositing medium occupying the largest area and having several active geochemical barriers that prevent from the migration of pollutants. This is a biological geochemical barrier where pollutants are trapped by living organisms and humic substances; a physicochemical barrier may be oxidative, reducing, sulphide, carbonate, alkaline, acidic, volatile, adsorptive and thermodynamic in nature; the formation process of a mechanical barrier is affected by changes in the rates of humidity (or air) movement due to soil density, porosity and other factors such as granulometry and structure.

2.1.3

Mosses

The active surface area of mosses is close to the surface area of foliage, does not have a well-developed root system and act as perennially green plants. Taking chemical elements directly from the atmosphere, mosses are reliable passive biomonitors (Rüling and Tyler 1968, 1970; Tyler 1990). As an absorber of atmospheric pollutants, mosses have a number of advantages: (1) due to their limited size, mosses are easy to grow, occupy a small area in the growing room and are simply prepared for chemical analysis; (2) abundantly collect air impurities of a different size as a result of forming a dense carpet (in some cases, they form 20–80% of the total vegetation carpet); (3) they can be easily transferred to the other location different in the level of air pollution; (4) most types of mosses are evergreen, perennial plants that can be studied all year round; (5) mosses producing easy-to-separate annual shoots (such as Hylocomium splendens) are of a particularly high value; (6) moss gametophytes are free of stomata, and thus pollutants penetrate evenly day and night; (7) plenty of the species of mosses are widespread geographically, and therefore grow in the different types of habitats (Kupčinskienė 2011).

2.1 Natural and Semi-Natural Barriers

2.1.4

49

Bark and Annual Tree Rings

Trees, their bark and annual rings make a global and widely used passive biomonitor having a humid, rough and electrically charged surface able to trap metal-absorbed suspended particles (Panichev and McCrindle 2004; Catinon et al. 2009). Trees are considered to be one of the most sensitive indicators of the state of the environment and represent the most suitable form of life for assessing environmental changes. Due to the peculiarities of the tree crown structure, trees are more in contact with the atmosphere and filter the mass of the transmitted air more frequently than the other forms of vegetation, thus indicating the state of forest ecosystems by their anatomical and morphological features. Morphological tests on trees are most consistent with the principals of an ‘ideal’ test, as they have inherent integrity, are independent of short-term environmental changes and are relatively simple, inexpensive and fast. Although most of morphological changes are non-specific, they accurately reflect and send ‘signals’ on the state of the environment with reference to easily measurable and visually evaluated indicators. Having an objective assessment of the condition of trees, we can also judge the state of the natural environment and its suitability for other life forms (Stravinskienė 2009). The suitability of bark for biomonitoring has been substantiated by a large number of scientists worldwide. The pollutants such as heavy metals can enter bark in two ways: through the roots and in the form of particles that come directly from the air. Runoff through the stem, which is the content of rainfall flowing through the stem of a tree, can leach or wash PTEs from bark; it can also bring large quantities of PTEs by washing away the foliage of a large surface area. The radial migration of PTEs from bark to wood changing the chemical composition of bark and burdening the interpretation of data is also possible. The trees growing in the differently polluted areas adjacent to industrial enterprises, highways and low-contamination soils were studied. A conclusion that only a very small amount of Pb entered the outer layers of bark through the roots was made. The concentrations of Pb, Cd and Zn in the bark of Douglas and Silver fir in the polluted and relatively unpolluted areas of southwest Germany confirmed that Pb in bark was of atmospheric origin, whereas the concentrations of Cd and Zn in the bark of the trees from the polluted sites were significantly higher than those in the bark of those growing in the decontaminated areas. Bark has little contact with the soil, i.e. the flow of materials from the soil to the leaves passes through the middle of the stem, and from the leaves to the roots—through the outer layers of the stem. PTEs cannot pass from the soil to bark, and therefore the chemical composition of bark also reflects air pollution. The analysis of annual rings is one of the most informative methods for assessing anthropogenic loads and the impact of environmental pollution on forest ecosystems in particular. According to the dynamics of ring width, the ratio and width of the earlier and later formed parts of the annual ring and relationships with environmental factors, this method makes possible to indicate the impact of the present anthropogenic factors on the environment and past natural anomalies. Trees, especially conifers, are considered to be one of the most sensitive

50

2 Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies

Dry

Deposition On the tree crown Wet

Dry

On bark

Blowing off

Forest floor

Washing away

Wet Dry Tree-falling objects

On the soil Wet

Uptake through the roots Fig. 2.3 Principal scheme for the metabolism of air pollutants in bark

environmental indicators. Their ability to respond to environmental effects (sensitivity) is subject to the genetic characteristics and age of the species. Each year, the tree adds a new layer of wood—an annual ring. Its width and change in chemical composition are different because they depend on the environmental conditions of the year—air and soil humidity, the mode of direct temperature, the content of precipitation, soil fertility, direct and indirect human activity and environmental chemical composition (Cherubini et al. 2002). The concentrations of air pollutants in bark is the result of the interaction of various natural processes such as sedimentation, diffusion, wind and precipitation. The principal scheme for the metabolism of air pollutants in bark is shown in Fig. 2.3. Absorption through the roots or foliage is negligible for most of the components studied, and their concentrations are largely determined by the composition of the air in the outer layers of bark. The main processes affecting the concentrations of pollutants in bark include the dry deposition of contaminants, a reverse process of blowing off and leakage along the stem that removes the washedout pollutants from the tree crown and stem as well as leaches and washes away them from bark.

2.1.5

Lichens

Lichens are called unique bioindicators/depositing media because they are very sensitive to negative environmental factors. The high sensitivity of lichens is the

2.1 Natural and Semi-Natural Barriers

51

result of their biology. Lichens are the organisms in which fungi, algae or bacteria form symbiosis. The fungal component fed by algae or cyanobacteria (sometimes both) with the nutrients produced in the photosynthesis process dominates in the lichen association. The disturbed balance between mycobiont and phycobiont can disrupt the association. Epiphytic lichens are most commonly used for environmental assessment because of their rapid and sensitive response to environmental pollution with sulphur and nitrogen oxides, acidification and contamination by heavy metals, methylene, fluorine compounds and ozone (Stravinskienė 2009). The most important indicative properties of lichens are as follows (Gries 1996; Stolte 1993): (1) lichens are long-life perennial organisms that, under the impact of long-term contamination, reflect general information on long-term environmental conditions; (2) unlike other plants higher in classification, they do not have parts fallen apart, and therefore cannot escape from the effects of contaminants; (3) lichens have no epidermis and waxy cuticle, which are specific water- and gas-permeable organs, and thus do not control gas circulation and air humidity and airborne materials are absorbed across the whole surface of the thallus; (4) various types of lichen react differently to air pollution and dissimilar pollutants.

2.1.6

Precipitation (Rain and Snow)

Approximately 70–90% of the PTEs of technogenic origin are deposited on the earth surface as precipitation (Salomons and Förster 1984), and, therefore, studies on the composition of precipitation partly reflect atmospheric pollution with PTEs, which assists in the more accurate evaluation of PTE flows to the earth surface. Snowmelt water can be filtered, and the analysis of PTEs can be done after digestion while the determination of PTEs in snowmelt water without filtration can strictly be done by using acids. Snow pollution with PTEs decreases in snow dust with increasing distance from the sources of emission (Zajac 1981). Snow analysis, if possible, to sample the snow cap of the winter period, enables us to distinguish the deposition of pollutants during the cold period. If experimental data can provide a distinctive spatial concentration pattern close to the point of the pollution source, then, calculations can be performed to describe the washout of PTEs from the atmosphere. Human being applied the phenomena of natural barriers in the environment for particular purposes in the places where these barriers naturally do not occur. They were referred to artificial geochemical barriers, for instance, the surface insulation of sand-gravel bases and fractured rock in waste storage facilities (Chanturiya et al. 2014) or carbonate barriers, either enclosing the entire pollution source or blocking the pathways of waste leaking to terrain or groundwater in order to eliminate the necessity of creating plants for copper solution recovery, thus diminishing capital investment (Zhizhayev et al. 2002). The following sections discuss the examples and characteristics of applying natural and artificial barriers.

52

2.2 2.2.1

2 Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies

Natural Barriers as an Example of Retention for Aerogenic Contamination from the Oil Refinery Oil Refineries and Typical Pollutants

According to the volume of oil refining (270 mill. t/year) worldwide, American oil companies Exxon Corp. and Mobil Corp. take the leadership and own 44 oil refineries. Royal Dutch/Shell processing 211 mill. tons of oil per year is the leader in Europe. The largest Chinese plant in the Asian region Sinopec processes 125 mill. tons of oil per year (Petro Strategies. . . 2012). In Russia, refining and petrochemical industry is based on 26 different profile oil refineries like fuel, lubricant-fuel, lubricant-fuel-oil chemistry. Among the largest ones, the average capacity of a single oil refinery makes around 9.71 million tons. In 2000, the average volume of refined oil reached 6067 million tons. The average annual capacity of a single oil refinery (including small oil refineries) in Russia is 5.59 million tons. The average volume of oil refined in a single refinery reached 3477 million tons, and the largest volume made 15,966 million tons in 2000 (Abrosimov 2002). JSC ORLEN Lietuva located in the territory of Lithuania (Mazeikiai district, Juodeikiai village) is an oil refinery operating the only oil product plant, the oil and product pipeline network and the offshore oil terminal in the Baltic States. The main activities of the plant include refining oil and other raw materials (fuel oil, gas condensate and middle distillates), the transportation of oil products through the pipeline, loading oil products into tank wagons and road tankers and electricity generation and distribution. The suggested efficiency of the plant reaches 15 million tons of refined crude oil per year (approximately 315 thousand barrels per day) (Sweco Lietuva 2009). The output of JSC ORLEN Lietuva involves (Orlen Lietuva. . . 2012) unleaded petrol 98, 95, denatured ethanol-added petrol (95 only), ETBE-added (ethyl tertbutyl ether) petrol, summer and winter diesel, FAME-added diesel (Fatty Acid Methyl Ester), arctic second-class diesel, labelled agricultural diesel, fuel oil for heating, jet fuel JET-A1, LPG for cars and household use, road, roof and building bitumen, elemental sulphur and emulsified fuel. Oil refineries (ORs) are typically large and fully integrated industries processing large volumes of crude oil, managing huge product reserves and consuming massive amounts of energy and water. Significant amounts of pollutants are released from ORs into the atmosphere, water and soil during product storage and manufacturing processes. The main air pollutants include carbon, sulphur, nitrogen oxides, particulates (mainly from combustion processes) and volatile organic compounds (Taršos integruota. . . 2003). The problem of gas and dust emissions from ORs is an equally important issue, which results in polluting the atmosphere with dust and gas. Thus, more than 1050 million tons of emissions from ORs enter the atmosphere while filtering retains only 47.5% of those. According to some data provided, Russian ORs release around 0.45% of the recycled material into the atmosphere compared with

2.2 Natural Barriers as an Example of Retention for Aerogenic Contamination from. . . Fig. 2.4 The amount of pollutants emitted into the ambient air (tons) recycling one million tons of crude oil (Taršos integruota. . . 2003)

53

20 000 - 820 000 t CO2 10 - 6000 t PM

60 - 700 t NOx AIR

30 - 6000 t SOx

50 - 6000 t VOC

Refining 1 ton of crude oil 100 000 - 5 000 000 t Wastewater

10 - 2000 t

Solid waste

0.1% in Western countries. Irreversible environmental damage is caused by the tank farms of ORs. Fuel combustion in tank furnaces produces aerosol particles, i.e. carbon condensation products and carcinogenic benzo(a)pyrene hydrocarbons (Abrosimov 2002). The main pollutants produced by ORs are those emitted to the air (Fig. 2.4.). The amounts of pollutants released into the ambient air within the process of recycling one million tons of crude oil (refineries in Europe produce from 0.5 to over 20 million tons) are shown in Fig. 2.4. (Taršos integruota. . . 2003). ORs refine one million tons of crude oil, discharge between 0.1 and five million tons of wastewater and produce between 10 and 2000 tons of solid waste. The high levels of emissions generated in European ORs can be partly explained by the different level of integration and variations in the types of plants (e.g. simple to complex). However, the main differences are due to unequal environmental legislation systems in Europe (Taršos integruota. . . 2003). The use of treatment technologies during the oil refining process assists in burning gaseous pollutants. The amounts of pollutants resulting from the combustion of 1 kg of fuel (Baltrėnas and Vaišis 2007) are provided in Table 2.1. If pollutants released into the ambient air decomposed in a relatively short period of time, there would be no risk of chemical, physical or biological contamination of the environment. However, it is problematic that environmental pollutants have relatively high stability and longevity. During their existence, they are collected in various components of the environment prior to being eventually accumulated in the biosphere or one of the abiotic spheres. The dispersion of pollutants entering the environment depends on a number of physical and geochemical processes. The distribution of environmental pollutants is determined by various environmental processes and the physical and chemical properties of materials (Teršalų migracija. . . 2012). During the refining process, various pollutants are released directly into the ambient air. To evaluate their airborne levels, different methods for directly measuring air quality can be employed. Some of the pollutants remain in the atmosphere while the others precipitate dry or wet in the environment. Environmental components such as the soil, mosses, trees, bark and snow should be analysed to evaluate long-term pollution. The airborne pollutants present in the rain are leached, and therefore for analysing rain samples, the former airborne pollutants can also be

54

2 Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies

Table 2.1 The amounts of pollutants (g) resulting from the combustion of 1 kg of different kinds of fuel (Baltrėnas and Vaišis 2007) Pollutants Carbon monoxide Volatile organic compounds (VOC) Nitrogen oxides Sulphur oxides Aldehydes Lead (using ethyl petrol) Benzo(a)pyrene Carbon black Total

Petrol 270 34 28 10 0.9 0.3 23  10
5 0.8 344

Diesel 35 11 51 45 0.8 – 31  10
5 5 148

Gas 110 15 31 – – – – – 156

detected. The elements such as V, As and Cr (Hope 1997) are released into the air from ORs by wet or dry deposition, enter ecosystems and are found in the increased quantities in bio-media (e.g. mosses, lichen, wood, bark, soil) (Tsai et al. 1995; Cetin et al. 2003; Nadal et al. 2007). The soil in the area around the largest petrochemical complex in southern Europe in Tarragona (Catalonia, Spain) pointed to the highest established mean concentrations of As, Cr, Mn and V making around 1.5 times and reported on the concentrations of Cd and Pb that were approximately two times higher compared to the background area (Nadal et al. 2007). Bosco et al. (2005) discovered that the refinery complex in the Gela region of Sicily (Italy) resulted in higher than background concentrations of As, Mo, Ni, S, Se, V and Zn in pine needles used for identifying aerogenic contamination. Genoni et al. (2000) observed that the plant burning oil caused a 3.3-time increase in Ni and a 5.5-time increase in V concentrations in the soil of the surrounding area compared to the background values. As a result of a rise in pollution, the values of V and Ni in bioaccumulation biofilters (mosses) were the highest among other heavy metals. In 1993, the forest floor of coniferous trees in the area of Elektėnai, the town situated close to the Lithuanian power plant that used fuel oil as a type of fuel, counted Ni concentration equal to 424 mg/kg and V—226 mg/ kg, whereas the soil humus horizon of the adjacent grassland made 46 mg/kg and 71 mg/kg, respectively (Lietuvninkas 1993). Meanwhile, the background concentrations of these metals in Lithuanian sandy loam soils are estimated as having Ni— 13.8 mg/kg and V—37.8 mg/kg (Kadūnas et al. 1999a, b), i.e. the concentration coefficient of Ni in the soil under coniferous trees was almost 31 units and that of V—6 units. Persistent exposure to PTEs (As, Cd, Hg, Pb), although at low concentrations, may be related to various adverse effects (Christensen 1995; Chang 1996). The chemical compounds formed during refining and petrochemical production processes are toxic (Mehlman 1992). These are polyaromatic hydrocarbons, halogenated hydrocarbons, aromatic amines and nitrosamines as well as organometallic compounds that are attributed to mutagenic and carcinogenic materials (Kaldor et al. 1984). Some of these toxic compounds are released into the atmosphere, which increases the risk of leukaemia, bone, brain or bladder cancer and other diseases for

2.2 Natural Barriers as an Example of Retention for Aerogenic Contamination from. . .

55

people living in the near areas of refineries and chemical plants (Kaldor et al. 1984; Pan et al. 1994; Lin et al. 2011). A positive correlation was found between air pollution in the oil industry and pregnancy complications or early miscarriages (Yang et al. 2002; Nadal et al. 2007). Some elements are also carcinogenic (i.e. causing the development of malignancy) (Cd, Cr(VI), Ni) and teratogenic (i.e. causing gene and chromosomal mutations) (As, Cd, Hg, Pb) for mammals (Domingo 1994; Chang 1996).

2.2.2

Deposit Media in the Vicinity of the Oil Refinery

JSC ORLEN Lietuva is the second-category petroleum refining plant operating as the only petroleum refinery, a crude oil and petroleum product network and a marine terminal in the Baltic States (Fig. 2.5). The plant manages the network of filling stations of VENTUS and ORLEN Lietuva trademarks through its subsidiary PLC Ventus—Nafta. The production and sales of petroleum products are the key areas of activity done by the plant. The oil refinery processes approximately ten million tons of crude oil a year. JSC ORLEN Lietuva is one of the most well-known companies, the impact of which on Lithuanian economy is considerable. It is the largest taxpayer in the state, the plant having the biggest revenue in Lithuania and one of the largest exporters of the country. The plant is the most important supplier of petrol and diesel fuel in Lithuania, Latvia and Estonia. The products of the plant are also exported to Western Europe, the USA, Ukraine and other countries. To study the impact of oil refinery on the environment and identify the effect of barriers, snow cap samples were taken around the vicinity of the oil refinery near the town of Mažeikiai in the North-Western region of Lithuania (56 230 1500 N 22 100 3400 E). Oil refining constitutes about 92% of the total PM emissions in the area. No other pollution sources were observed in the vicinity of the oil refinery. Snow cap samples were taken at a distance of 100 m from any roads. To identify the impact of the oil refinery on ambient air quality and evaluate the snow cap as deposit media, sampling sites were grouped into four zones according to the prevailing direction of the wind (Fig. 2.6). These zones were organized at a distance of 0.2 to 3 km from the sanitary protection zone of JSC ORLEN Lietuva. The snow cap was sampled at 11 sites, including 4 sites in the north-west direction (Zone 1), 2 sites in

Fig. 2.5 JSC ORLEN Lietuva

56

2 Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies

Fig. 2.6 A sampling site in the vicinity of the oil refinery

Zone 2

N

Zone 1

Zone 4

Zone 3 1 km

the north-east direction (Zone 2), 2 sites in the south-west (Zone 3) and 3 sites were chosen to the south-east (Zone 4). The analysis of soluble and insoluble forms of PTEs was done according to distances at 0.5 km, 1.5 km and 2 km around the oil refinery. The background areas were chosen with account for experimental data on the qualitative and quantitative composition of the snow cap, and parameters were stable and independent of emissions from JSC Orlen Lietuva. During the winter season for the period 2006–2010, the prevailing wind direction was observed in the south-east and north-west directions. Snow cap samples were taken from the undisturbed snow cap in the middle of February. Temperature was
3  C with no snow. Snow cover lasted for 19 days. Each composite sample consisted of 14 to 28 sub-samples taken by the snow sampling tool. To determine the pollution level in the oil refinery, the daily load of snow dust was calculated. Estimating the load of snow dust was made after drying filters together with dust particles in a clean drying chamber on the fresh sheets of paper. The daily load of snow dust was calculated using Eq. (2.1): An ¼

D  Xn  10
3 ; ST

ð2:1Þ

where An—the daily load of snow dust, mg/m2, Xn—the concentration of element ‘n’ in dust, mg/kg; D—the mass of dust, g; S—the area taken by the snow sample, m2; T—a snowy period of time before sampling, number of days. The snowy period of time was determined using information from the data collected at the nearest weather station. Table 2.1 is based on a number of long-term and reliable geochemical research studies done by Russian scientists (Rare-element Geochemical and Mineralogical Institute, Moscow, Russia). The research was carried out by doctors, hygienists, environmentalists and experts in soil and plant sciences. The main media accumulating pollutants such as the snow cap, soil, ponds and river bottom sediments,

2.2 Natural Barriers as an Example of Retention for Aerogenic Contamination from. . .

57

Table 2.2 The classification of the pollution level according to the load of snow dust (Saet et al. 1990) Risk level Medium risk High risk Particularly high risk

Daily snow dust load, mg/m3 The average daily load of snow dust 250-450 mg/m2 The average daily load of snow dust 450-800 mg/m2 The average daily load of snow dust in excess of 800 mg/m2

children and adult bio-substrates (mostly hair) were studied. Consistently the researched mediums that transported pollutants included the air and river water. Large varieties of industries and various pollution sources were examined. The classification of the pollution level related to health risk and the nature of diseases were investigated continually taking into account children and adults. In order to assess the load of snow cap dust in different areas, load factors were calculated (Table 2.2). Computation was made applying Eq. (2.2). K¼

Ann ; Ans

ð2:2Þ

where K—the load factor, Ann—the daily load of snow dust in the northern areas of the oil refinery impact zone, mg/m2, Ans—the daily load of snow dust in the southern areas of the oil refinery impact zone, mg/m2. According to the classification of the daily load of snow dust, a lower than the medium-risk level of pollution was determined in the vicinity of the oil refinery. After the correlation analysis of the daily load of snow dust and metal concentrations, negative coefficients were obtained, which showed that the high concentrations of pollutants were regularly related to a low rate of the load. On the contrary, separate metal concentration correlated positively—an increased concentration of one metal was regularly related to a high concentration of the other. Data analysis showed that the highest daily rate of the snow dust load (45.81  12.35 mg/m2) was observed in Zone 1 (Fig. 2.7). The prevailing winds in the region probably had an influence, because northwest and southeast winds blew to the oil refinery impact zone. A comparison of Zones 1 and 4 with Zones 2 and 3 shows that the daily load of snow was 1.2 times higher. The results obtained from calculating snow dust load coefficients in different zones are presented in Table 2.3. The values of the coefficients confirm the existing impact of the oil refinery on air quality; otherwise the coefficients should be equal to 1. Sulphates, chlorides and three forms of nitrogen—ammonium, nitrite and nitrate—were analysed in snowmelt water. Their accumulation in the snow cap is mostly related to the emission of gaseous pollutants resulting from the combustion of organic materials. The concentration of nitrite ( Cd. Generally, a ratio of the snow cap between soluble and insoluble metal forms depends on the type of the pollution source, the distance between the latter and the load of snow dust and their nature (Lietuvninkas 2002). Distances for analysis fell in the categories of 0.5 km, 1.5 km and 2 km around the oil refinery. The concentrations of PTEs in snow dust were determined thousands times higher than those in snowmelt water. The concentrations of Pb, Cr, Cu and Cd varied. The highest concentrations of Cd (3.22  0.09 mg/kg), Cu (72.49  14.96 mg/kg) and Pb (325.91  3.20 mg/kg) were determined in the closest sampling sites from the oil refinery and made 0.5 km. The concentrations of these pollutants decrease along with an increase in the distance from the pollution source. The biggest amount of Cr (114.53  21.7 mg/kg) was determined at a distance of 1.5 km from the pollution source. The minimum amount of Cr was found 2 km around from the oil refinery and made 50.23  33.99 mg/kg, which was 2.3 times higher compared to the highest concentration of Cr (Fig 2.11a). As for the impact zone of the oil refinery, the concentrations of Cd and Cr were detected in snow dust only, since they were below the analytical method detection limit in all samples of snowmelt water. The highest concentrations of Pb (0.012  0.025 mg/L) and Cu (0.200  0.03 mg/L) were determined at a distance of 1.5 km from the oil refinery. The lowest concentration of Pb was found near the oil refinery at a distance of 0.5 km and made 0.004  0.003 mg/L (Fig 2.11b). The obtained results confirm the trend that when approaching the contaminated area, the part of the soluble forms of PTEs closer to the contamination source relatively decreases while the concentrations of the insoluble forms of metals increase. Thus, theoretical and practical research on the snow cover shows an increased interest in snowmelt as an indicator for determining ambient air pollution.

2.2 Natural Barriers as an Example of Retention for Aerogenic Contamination from. . .

300 300 250 200 150 100 50 0

b) Cd Cu Pb Cr 0.5 km

1.5 km

2 km

Concentration, mg/m3

Concentration, mg/m3

a)

63

0.25 0.20 Cu Pb

0.15 0.10 0.05 0.00

0.5 km

1.5 km

2 km

Fig. 2.11 The distribution of the concentrations of PTEs in (a) snow dust and (b) snowmelt water at different distances from the oil refinery

Snow is the main seasonal natural coating that accumulates airborne pollutants. Snowfall removes atmospheric impurities (dust, carbon black, gaseous components) from the air. Later, they accumulate on the already formed and constantly renewing portion of precipitated snowfall. Snow is an inert medium where pollutants do not migrate actively. They effectively accumulate in snow, which acts as an aerodynamic barrier for the particles suspended in the air. The ability of the snow cover to accumulate contaminants depends on the physical properties of pollutants. The soluble forms of the chemical elements of the snow cover in urban areas are significantly smaller compared to the insoluble ones (mineral dust of snow), and therefore the analysis of snowmelt water is not always required (Kadūnas et al. 1999a, b); however, there is a relationship between soluble and suspended particles. Their relationship is characterized by inverse proportionality, i.e. a share of soluble metal forms in the pollution sources closer to the urban area decreases while the load of dust increases. The deposition of gaseous air pollutants (sulphur and nitrogen oxides, volatile organic compounds, etc.) in the snow cover is very limited: special studies conducted in Western Siberia showed they had a deposit coefficient of only 0.015–0.020, i.e. only 1.5–2% of airborne gaseous emissions were deposited in the snow cover in the close proximity to pollution sources. Figure 2.12 shows the radial differentiation of heavy metals in the soil profile at the depths of 0–10, 10–30 and 80–100 cm. In most cases (except for the concentrations of Cr, Ni, and Pb at a depth of 80–100 cm), the concentrations of heavy metals were significantly lower at all investigated soil depths of the background area than those in the impact zone of the plant. This identifies the long-term load of heavy metals are infiltrated into the deeper layers of the soil and accumulated within the existing geochemical barriers during the long period of its operation. Particular attention should be paid to the soil at a depth of 0–10 cm as it is closest to the dry and wet deposition of metals from the atmosphere (not including the vegetation cover). The highest concentrations in this layer had Zn in Zone 4 and Cu, Ni and Pb in Zone 1. A significant increase in the concentrations of Ni and Cr at a depth of 0-30 cm compared to those at a depth of 80–100 cm was observed in all zones, that in Pb—in Zones 1 and 3 and that in Cu—in Zone 1 (Fig. 2.12). As

0-10 Background Zone 4 Zone 3 Zone 2 Zone 1

10-30

80-100

Soil depth, cm

0

0-10

80-100 0

Background Zone 4 Zone 3 Zone 2 Zone 1

10-30

80-100

Soil depth, cm

10 20 30 40 50 Ni concentration, mg/kg DW

Background Zone 4 Zone 3 Zone 2 Zone 1

10-30

5 10 15 20 25 Zn concentration, mg/kg DW

0-10

0

Soil depth, cm

2 Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies

Soil depth, cm

Soil depth, cm

64

2 4 6 8 10 Cu concentration, mg/kg DW

0-10 Background Zone 4 Zone 3 Zone 2 Zone 1

10-30

80-100 0

10 20 30 40 50 Cr concentration, mg/kg DW

0−10 Background Zone 4 Zone 3 Zone 2 Zone 1

10−30

80−100 0

2 4 6 8 Pb concentration, mg/kg DW

Fig. 2.12 The concentrations of heavy metals in the soil at the depths of 0–10, 10–30 and 80–100 cm in the impact zone of JSC Orlen Lietuva

mentioned above, Zones 1 and 4 formed downwind and upwind areas around the plant and therefore clearly characterized the effect of the plant. The soil polluted with metals has traditionally been evaluated by the contamination of the surface layer of the soil (0–10 cm), since the surface layer covered with vegetation and humus horizon acts as an effective attenuating geochemical barrier to pollutant migration and accumulation. The pollution of the surface layer of the soil was evaluated in two ways—according to the hazard coefficient (Ko) of individual PTE (Fig 2.13a) and the overall pollution index (Zd) (Fig 2.13b) integrating the effect of more than one metal. The latter takes a more realistic view of soil pollution. The heavier metals are included, the more accurate is estimation. Figure 2.13a shows that Zone 1 is characteristic of hazardous soil pollution with Ni (3 < Ko < 10), and Zones 2, 3 and 4 are typical of moderately hazardous soil pollution with (1 < Ko < 3). Moderately hazardous soil pollution with Cr is typical of Zones 1 and 3. Ko of other metals (Zn, Cu and Pb) had less than 1, i.e. concentrations did not exceed the MAC. Figure 2.13b shows the values of the index of the overall pollution with metals (Zd). The highest values (Zd ¼ 5.2) were typical of Zones 1 and 4, i.e. the areas located on the axis of the prevailing winds. According to HN 60–2004 classification,

2.2 Natural Barriers as an Example of Retention for Aerogenic Contamination from. . .

b)

3.0 2.5

Zn 0-10 Cu 0-10 Ni 0-10 Cr 0-10 Pb 0-10

2.0 1.5 1.0 0.5 0

Zone 1 Zone 2 Zone 3 Zone 4

Index of the total pollution with metals, Zd

Coefficient soil pollution by metals, K0

a) 3.5

65

6.0 5.0 4.0 3.0 2.0 1.0

Zone 1 Zone 2 Zone 3 Zone 4

Fig. 2.13 The indexes of the surface layer of the soil polluted with metals (0
10 cm): the values of (a) pollution coefficient (Ko) and (b) overall index of pollution with heavy metals (Zd) in different areas of the impact zone of JSC ORLEN Lietuva

under Zd < 16, the site is classified as the below-average polluted area; however, it should be considered that this is the minimum estimation of the potential pollution level, because for a more accurate assessment of the polluted surface layer of the soil, a broader spectrum of metals should be explored (in terms of thermal boiler houses and electro centric, HN 60–2004 finds Pb, Zn, Sn, Cu, Ag, Hg, Cd, Ni, Cr, Mo, Mn, V, Co, U, Ga, Sc, Be, Yb and W). In 2011, a soil monitoring report documented that Zd did not exceed 16 in all monitoring sites attributed to the impact zone of JSC ORLEN Lietuva (UAB “Ingeo” 2011a, b). For assessing ambient air quality according to a single metal in biotechnology, Müller (1981) proposed using the Geo-accumulation Index (Igeo) (Eq. 2.3). For evaluating contamination with a few metals according to their concentrations in bio-media, Tomlinson et al. (1980) suggested using the air quality index (AQI) (Eq. 2.4). Guéguen et al. (2012) (2012) recommend the below indicators for measuring ambient air pollution in terms of metal concentrations in tree bark and mosses.
I geo,dt ¼ log 2

Ci 1:5  C

 ð2:3Þ

, f ,i

where Ci is the concentration of PTE i in bark or the moss sample (mg/kg DW); Cf,i is the background concentration of PTE i in bark or moss samples (mg/kg DW); coefficient 1.5 shows variations in background concentrations due to lithogenic variations.  TCIdt ¼ C

f ,1

C

f ,2

 ...  C

f ,i

1n

,

ð2:4Þ

where Cf,i is the pollution index, i.e. the concentration of the PTE in the sample (mg/kg DW) divided by the background concentration of PTE i in the sample (mg/kg DW); n is the number of considered PTEs having Cf  1.

66

2 Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies 0.5 Zn Cu Ni Cr Pb 0

Total contamination index, BUIž

Geoaccumulation index of metals in bark, Igeo,ž

2.0

1.0

0

Zone 1 Zone 2 Zone 3 Zone 4

a)

b)

Zn Cu Ni Cr Pb

0

Zone 1 Zone 2 Zone 3 Zone 4

c)

Total contamination index, BUIS

Geoaccumulation index of metals in mosses, Igeo,s

2.0

1.0

Zone 1 Zone 2 Zone 3 Zone 4

4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0

Zone 1 Zone 2 Zone 3 Zone 4

d)

Fig. 2.14 The values of the geo-accumulation index and air quality index in the impact zone of oil industry according to the depositing media (a, b—pine bark; c, d—mosses)

The bark of Pinus sylvestris L. is recognized as a passive biomonitor and is widely used to for investigating ambient air quality (Haapala and Kikuchi 2000; Narewski et al. 2000; Huhn et al. 1995; Harju et al. 2002a, b; Saarela et al. 2005). Figure 2.14a shows an assessment of ambient air quality with respect to metal concentrations in bark. Pollution with metals can be seen in Zones 1, 2 and 4. Zones 1 and 4 show pollution with Ni and Zone 2 is polluted with Cr. Pollution is rated as weak to moderate because 0 < Igeo,ž < 1 (Guéguen et al. 2012). Considering concentrations in pine bark, the overall pollution of the ambient air with metals is expressed as the air quality index (AQIB) in Fig 2.14b. According to AQIB index, a higher level of pollution is observed in Zone 4 following by Zones 1, 2 and 3. The highest concentrations of Cr, Cd and Mn (6.68 mg/kg, 0.69 mg/kg and 382 mg/kg, respectively) were greater than those typical of the impact zone of oil industry. For assessing environmental pollution with metals considering their concentrations in mosses, similarly to the case of bark, Eqs. (2.3) and (2.4) were used for calculating the values of Igeo,M and AQIM (Fig 2.14c,d). Moderate pollution with Ni, Pb and Cr considering mosses is identified in Zone 1, that with Ni and Pb in Zone 2 and that with Ni only in Zone 4. According to metals present in mosses, Zone 3 is attributed to the weakly to moderately polluted area (Fig 2.14c). The values of the AQIM index, similarly to Igeo,M, tend to decrease in the zones in the following order: Zone 1 > Zone 2 > Zone 4 > Zone 3. To sum up, the highest concentrations of most heavy metals (Zn, Cu, Cr, Mn and Ni, except from Cd) in mosses were found in the

2.3 Natural Biogeochemical Barriers as a Retention Example of Aerogenic Pollution. . .

67

northern area of Mazeikiai district in terms of the plant (Zn, Cu, Cr, Mn—in Zone 1 and Ni—in Zone 2) (Fig 2.14c).

2.3

Natural Biogeochemical Barriers as a Retention Example of Aerogenic Pollution Caused by Waste Incineration Plant

COSMARI (Consorzio Obbligatorio SMAltimento RIfiuti) is a waste disposal consortium of the Province of Macerata where waste is collected and incinerated (Fig. 2.15). The consortium is located in ‘Piane di Chienti’, the Municipality of Tolentino (MC), Italy. The plant is extended over an area of around 5 ha between the Chienti River and a highway (SS77). The plant area is substantially flat, and the average height above the sea level is approximately 150 m (N 43 140 2100 ; E 13 230 1700 ) (Morichetti 2013). . Production activities carried out by COSMARI are summarized in the following list showing the macro processes of the consortium: the acceptance of waste, the storage of waste and grouping waste into dry and organic waste (Fig. 2.16). According to the project, the incineration of the consortium has a capacity of 250 t/day and the effective productivity makes 220 t/day. Currently, all 57 municipalities of the province are involved in the consortium. Since 1997, for the treatment and disposal of municipal solid waste, approximately 90 employees have included drivers, maintenance workers, crane operators, employees taking control over the plant and administrative employees. Table 2.5 shows data on the average quantity of waste incinerated for the period from 2006 to 2010 (COSMARI 2010). The emission sources of pollutants in COSMARI may be summarized as follows (Fig. 2.17): (a) incinerator, which is the emission point of waste incineration

Fig. 2.15 The position of the plant (1:10000000) and the area of COSMARI (Cronachemaceratesi. it 2013)

68

2 Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies

Acceptance of waste Wet waste

Municipal solid waste

Storage of waste

Storage of waste

Processing waste

Selection of waste Dry waste

Organic waste

Compost

Stabilization of organic waste Landfill

Colleted waste

Processing of dry waste

Incineration

Landfill

RDF

Production of electricity Fig. 2.16 A flowchart of the processing activity of COSMARI (COSMARI 2010)

Table 2.5 The quantity (t/year) of waste incinerated at COSMARI (COSMARI 2010) 2006 19420 t

2007 17140 t

2008 16490 t

2009 18170 t

2010 16180 t

Fig. 2.17 The emission sources of COSMARI (1:1000) (COSMARI 2010)

monitored continuously with regard to the values of PM (particulate matter), NO2 (nitrogen oxide), O2 (oxygen), CO (carbon monoxide), SO2 (sulphur dioxide), HCl (hydrochloric acid), H2O (water), pressure, temperature and flow; (b) biofilters are used for breaking down odours produced in the places for storing, refining and selecting waste; (c) RDF dryer aspires hot air produced by the oil burner applied for drying RDF in processing; (d) RDF coolers show the air supplied by a fan to cool RDF (COSMARI 2010). The incineration plant with heat recovery is constituted by a grate furnace with non-reusable fractions coming from the selection section. It has nominal potentiality

2.3 Natural Biogeochemical Barriers as a Retention Example of Aerogenic Pollution. . .

69

Table 2.6 The types and quantity of pollutants in the incinerator for the period 2008–2010 (AIA 2010) Pollutants Mercury (Hg) Cadmium (Cd) + Titanium (Ti) Antimony (Sb) + Arsenic (As)+ Lead (Pb) + Chromium (Cr) + Cobalt (Co) + Copper (Cu) + Manganese (Mn) + Nickel (Ni) + Vanadium (V)

μg/Nm3 0.53–1.15 1.73–2.48 22.61–51.7

t/y 9.29  10
5– 1.97  10
4 2.96  10
4– 4.34  10
4 3.86  10
3– 9.06  10
3

equal to 2500 kg/h (60–70 t/d) with an overload for a maximum of 30 min to 2750 kg/h. Combustion generates steam in the water pipe of the boiler and then produces electrical energy by a turbine capable of giving a power from 1200 kW to 6900 r.p.m. (revolutions per minute). The three-phase alternator has a rated power of 1500 kVA, a voltage of 380 V, 50 Hz frequency, 4 seats and a rotation speed of 1500 r.p.m. (AIA 2010). Flue gases leaving the boiler, after selling most of their heat, are purified. Through a special removal system, pollutants are removed from the combustion of MSW waste. Such smoke removal covers the following steps such as electro filtration, cooling, first wash, filtration, second wash and heating (COSMARI 2010). The treatment of fumes produced by the incineration process involves two processes: dry purification and the final wet washing. The combination of the two processes allows obtaining the high efficiency of removing acid gases (HCl, SO2, HF, NO2 and NO), metals and dioxins-furans, which facilitates better reliability of the entire treatment section. Table 2.6 provides data on the emissions of PTEs (AIA 2010). The type of the tree chosen in the present study is Populus Alba, commonly called Silver Poplar. It is a medium-sized deciduous tree growing to the heights of up to 16-27 m with a trunk of up to 2 m in diameter and the leaves of 4-15 cm long, fivelobed (Rushforth 1999). To identify the impact of the incinerator on the environment, sampling sites were grouped into seven points according to the prevailing wind direction. In order to know the meteorological characteristics of the area close to the consortium, meteorological analysis performed by ARPAM (Agenzia Regionale Potrezione Ambiente Marche) has been consulted. The analysis of the values related to rising winds was conducted in 2007 and showed uniformity in the examined area. The prevailing direction of the origin corresponds to the WSW (West South West) area that occurs around 30% for all months. Consequently, the predominantly occurring direction is ENE (East North East), particularly in January (14%), during the spring and beginning of the summer (with a recurrence of up to 20% in April). The intensity of the prevailing winds is between 0.3 and 4 m/s occurring between 30% and 50% of all cases (ARPAM 2007). Twenty-five soil samples with a depth between 0.10 and 0.40 m were collected; 24 samples were taken in the points selected based on the prevailing (East-North-

70

2 Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies

Fig. 2.18 Soil and wood sampling sites (Morichetti 2013)

East) wind direction while one sample was taken within a natural reserve (Abbadia di Fiastra) out of the zone of the prevailing wind at a distance of around 2.5 km from COSMARI (South-East direction). The last one is the control soil sample (Bianco01) (Fig. 2.18) (ARPAM 2011). To take tree samples in order to do the present study (‘02 ENE’, 07 ‘NE’, ‘05 NE’ and ‘06 ENE’), four points in the North-East direction from the sampling points of the soil and two new points, 01 SO and 01 NO, respectively, in the southwestern and northwestern directions were selected (Fig. 2.18). The first selected sampling point 02-ENE-A is distant from the plant approximately 1.4 km, very close to the incinerator and in the direction of the predominant wind, and therefore was chosen as the most ‘polluted scenario’. Then, two points in the North-East direction were selected. The first one, 05 NE-A, was chosen in the Municipality of Casette Verdini and was distant from the incinerator by around 2.4 km as the representative of the ‘urban scenario’. The second one, 06 ENE-A, was at a distance of at 2.4 km from COSMARI in the Municipality of Piane di Chienti and was very close to the highway. This point was selected as the traffic ‘scenario’. The last one, 07 NE-A, was faraway nearly 3 km from the emission point and represented the ‘distance scenario’. Finally, a study of the wind was made in 2007 only, and therefore it was necessary to consider the downwind zone in respect of the consortium. Thus, two new sampling points, 01 NO-A and 01SO-A, were selected out of the main wind direction (North-West and South-West). They represented the ‘downwind scenario’. The control sampling point is the same of the precedent soil study, Bianco-01-A (Morichetti 2013).

2.3 Natural Biogeochemical Barriers as a Retention Example of Aerogenic Pollution. . .

71

Two trees were sampled in each sampling point and, in order to consider statistical analysis, two samples per tree were collected (e.g. one sampling point contains 4 tree samples: 07 NE-A and 07 NE-A’ from the same tree and 07 NE-B and 07 NE-B0 from another tree). A total of 28 samples, including 24 tree samples and four samples in the control point, were collected in the polluted sampling plot. The selected trees were at least 10 m away from each other and at least 100 m from any type of the road. The samples of the tree were taken at breast height (1.5 m) (Pundyte et al. 2011). Before and following each sampling, the tool was washed with acid liquid and the samples were immediately sealed in dry paper bags stored for further analysis (Pundyte et al. 2011). Subsequently, the samples were sanded so as to make visible tree rings. Accurate dating was then performed. Where possible, trees were chosen with the same diameter in order to be able to make the sampling phase standard. The diameters of the selected trees fall in a range that runs from 0.8 m and up to a maximum of 2.2 m. Regarding the stage of agreeing the date of the samples, the chosen time range for analysis was 10 years. The incinerator has been operating since 1995, but Silver Poplar is a fast-growing tree, and, considering the prevailing samples, the ideal time interval is the one mentioned above. The mean values of the PTEs were compared with data on references. Data are given for the range that can be observed frequently according to the authors such as Andriano and Kabata-Pendias and their analysis (Kabata-Pendias 2000a, b; Adriano 2001). Data on metal concentrations in the soil and wood samples are presented in Fig. 2.19 and 2.20. In all graphs reported above, there is one sampling point that has the average value of Sb, Cr, Pb, Ni and Zn higher than that of the other elements. In particular, two elements, Pb and Cr, have a higher value than the maximum level of the one presented in literature. The point at issue is the ‘traffic scenario’ (06 ENE). As mentioned above, the elements such as Pb, Cr and Cd are recognized by literature as good indicators for pollution within the urban area (Wischow 1995). Considering the concept described above, it is reasonable to think that these values are influenced by the small village next to the sampling point. Also, another factor that may interfere with these values is the fact that this small town is located in the north-eastern part of the incinerator, which is also on the freeway located at a distance of around 700 m. Another factor that confirms the theory of Wischow is that the other two points having the high values of the concentrations of the elements such as Pb and Cr are the points of the ‘distant scenario’ (07 NE) and ‘urban scenario’ (05 ENE). These three points have in common the fact that they are in the vicinity of the urban zone, points 06 ENE and 05 ENE in particular. The ‘distant scenario‘ is not very close to the incinerator and the city, but probably the fact it is near an important road could influence the value of metal within the plants. The concentrations of remaining metals are lower than the maximum value reported in literature and can be considered in a normal situation. The values of metal concentrations in the soil are all in the range of the values suggested in literature. Some elements have the values that are closer to the upper limit compared to the others. These elements include As, Cd,

1.00 0.60 0.20 0

01

Sampling points

Sampling points

05 NE 01 SO 0 BI 6 EN AN E CO 01

O

01 SO 0 BI 6 EN AN E CO 01

NE

05

E EN

02

NO

01

NE

0

1.20 0.80

Vanadium (V) min max

01 S 06 O BI EN AN E CO 01

NE

05

E EN

02

01

NE

0

NO

0.40

07

Concentration, mg/kg DW

EN 05 E NE 01 SO 0 BI 6 EN AN E CO 01

02

NO

NE

07

01

Concentration, mg/kg DW

Cobalt (Co) min max

0.20

Sampling points

Copper (Cu) min max

Sampling points

E

0.40

Sampling points 14.0 10.0 6.0 2.0 0

EN

0.60

07

Concentration, mg/kg DW

EN 05 E NE 01 SO 0 BI 6 EN AN E CO 01

02

NO

NE

07

01

Concentration, mg/kg DW

0

02

07 N

0

Sampling points

Cadmium (Cd) min max

0.20

Arsenic (As) min max

0.20

Sampling points

0.60 0.40

01 N

E

0.40

01 N

0

0.60

E

Zinc (Zn) min max

Concentration, mg/kg DW

Sampling points

120

07 NE 01 N 02 O EN 05 E NE 01 SO 0 BI 6 EN AN E CO 01

Concentration, mg/kg DW

Sampling points

40

02 O EN 05 E NE 01 SO 0 BI 6 EN AN E CO 01

Nickel (Ni) min max

07 N

07 NE 01 N 02 O EN 05 E NE 01 SO 0 BI 6 EN AN E CO 01

Lead (Pb) min max

80

02

NE NO

Chromium (Cr) min max

EN 05 E NE 01 SO 0 BI 6 EN AN E CO 01

2.50 2.00 1.50 1.00 0.50 0

02

07

01

NE NO

0

EN 05 E NE 01 SO 0 BI 6 EN AN E CO 01

0.04

1.40

07

1.60 1.20 0.80 0.40 0

Antimony (Sb) min max

0.08

Concentration, mg/kg DW

0.12

Concentration, mg/kg DW

Concentration, mg/kg DW

2 Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies

Concentration, mg/kg DW

72

Sampling points

Fig. 2.19 The concentrations of PTEs in wood (mg/kg of d.w.) at each sampling site (Morichetti 2013)

Co, Ni and Cu in particular. In fact, the last one has the values of all sampling points higher than a half of the upper limit. Surprisingly, the highest value is assigned to control point ‘BIANCO 01’. Copper can be used for producing the compounds of nutritional supplements and fungicides in agriculture, and therefore the samples having a high value of this element could be taken on a land to agricultural use. To complete the series of all analysed metals, all missing components are listed in the following graphs. A single element, antimony, is not listed because its values have never exceeded the limit of determination. In general, all elements in the soil do not have high values but are around the minimum level. Five composite samples of the soil and wood were taken in the vicinity of the waste incineration plant. The first sample was taken in the upwind zone of the plant

Concentration, mg/kg DW

12.0

12.0

8.0

05 NE 07 NE 0 BI 6 EN AN E CO 01

NE

02 E

05 NE 07 NE 0 BI 6 EN AN E CO 01

NE

O

02 E

Zinc (Zn) min max

NE 0 BI 6 EN AN E CO 01

NE

07

05

E EN

02

01

NO

50 0

SO

150

01

SO EN 05 E NE 07 NE 0 BI 6 EN AN E CO 01 02

Sampling points

Concentration, mg/kg DW

250

NO

01

01 S

0

O

20

Sampling points

Lead (Pb) min max

01

Concentration, mg/kg DW

Chromium (Cr) min max

40

Sampling points

35.0 25.0 15.0 5.0 0

O

60

01 N

Concentration, mg/kg DW

0

01 NO 01 SO 02 EN 05 E NE 07 NE 0 BI 6 EN AN E CO 01

Concentration, mg/kg DW

Sampling points

Nickel (Ni) min max

20

01 S

0

Sampling points

60 40

02 EN 05 E NE 07 NE 0 BI 6 EN AN E CO 01

O

4.0

O

0

Cobalt (Co) min max

8.0

01 N

Cadmium (Cd) min max

0.8 0.4

O

Sampling points

1.2

01 NO 01 SO 02 EN 05 E NE 07 NE 0 BI 6 EN AN E CO 01

Concentration, mg/kg DW

Sampling points

01 S

0

73

Arsenic (As) min max

4.0

01 N

Copper (Cu) min max

Concentration, mg/kg DW

50 40 30 20 10 0

01 NO 01 SO 02 EN 05 E NE 07 NE 0 BI 6 EN AN E CO 01

Concentration, mg/kg DW

2.3 Natural Biogeochemical Barriers as a Retention Example of Aerogenic Pollution. . .

Sampling points

Fig. 2.20 The concentrations of PTEs in the soil (mg/kg of d.w.) at each sampling site (Morichetti 2013)

and represents the ‘upwind scenario’ (UP0.5). The second sampling point (DW1.0) was located at a distance of 1 km from the plant in the downwind direction. It was very close to the incinerator and straight downwind of prevailing winds. Therefore, it was selected as the ‘polluted scenario’. Two more points were selected in the NorthEast (NE) direction. The sampling point (DW2.5) was located in the populated area around 2.5 km from the incinerator and was considered the representative of the ‘urban scenario’. One more sampling point (DW3.0) was also approximately at a distance of 3 km from the emission source but very close to a motorway and was accepted as the ‘traffic scenario’. The last point (DW3.6) was located 3.6 km away from the emission point and was considered the representative of the ‘remote scenario’. The composite soil samples were collected on each site from the top layer of the soil. The value of the dynamic factor in the bioaccumulation of PTEs in Populus alba was calculated (Fig. 2.21). In addition to the considered characteristics of the dynamic bioaccumulation factor (Baltrėnaitė et al. 2012), its new useful feature was identified following the analysis of this case. In determining the influence of various objects on the environment and their risks to environmental quality, the data obtained using the dynamic

Concentration coefficient

7.0 Cd

6.0 5.0 4.0

3.16

3.0 2.0 1.0 0

3.06 2.19

1.37 1.14 UP0.5

0.94

0.70

1.281.16 1.50

DW1.0

4.0 Ni Concentration coefficient

Pb

DW2.5 DW3.0 a) Cu

DW3.6

Zn

3.0 2.19 2.0

1.69

1.42 0.97 1.01 0.91 0.77 1.0 0.74 0.58 0.49 0.37 0

UP0.5

DW1.0

1.26 1.14 1.13

DW2.5 DW3.0 c)

0.49 DW3.6

Dynamic factor of bioaccumulation

2 Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies

Dynamic factor of bioaccumulation

74

3.5

Cd

Pb

3.16 3.06

3.0 2.5

2.19

2.0 1.5

1.41 1.32 1.18 1.11

1.0

1.50 1.28 1.16 0.94 0.70

0.5 0

UP0.5 UP0.5 DW1.0 DW2.5 DW3.0 DW3.6 b) 4.0 3.69 Ni Cu Zn 3.5 3.0

2.82 2.36 2.39

2.5

1.89

2.0 1.79 1.5 1.0 0.5 0

1.23 0.75 0.58 0.67 0.27 UP0.5

DW1.0

1.28

1.78 1.58 0.73

DW2.5 d)

DW3.0

DW3.6

Fig. 2.21 The concentration coefficients (a, c) of PTEs (Cd, Pb, Ni, Cu and Zn) and dynamic factors in bioaccumulation (b, d) for lime-trees (Populus alba) growing in the vicinity of the operating incineration plant

bioaccumulation factor are more informative than the direct evaluation of the concentrations of PTEs in plants, because they show the scope of biogeochemical uptake compared to the concentrations of PTEs in the soil. Data on the concentrations of PTEs in the plant or its concentration coefficient are not sufficient because they do not link the concentrations of PTEs to the one of the main media where PTEs are taken from, i.e. soil. Moreover, the dynamic factor in bioaccumulation helps with defining the chemical and biogeochemical characteristics of PTEs. Thus, let us analyse the current case and obtained data in Fig. 2.21. For example, the bioaccumulation of Pb and Cd in the tree reached its maximum with respect to that in the investigated area at a distance of 3.6 km from the incineration plant (downwind) (Fig. 2.21b), whereas bioaccumulation maximum of Ni, Cu and Zn was reached at a distance of approximately 3 km downwind from this plant (Fig. 2.21d). This can be attributed to the different types of PTEs transferred to the atmosphere and varying distances from the plant, because Pb and Cd are transported by small aerosol particles (with the accumulation coefficient reaching 50–100) while Zn, Cu and Ni are conveyed by larger particles (taking into account the accumulation coefficient reaching 10–50). Smaller aerosol particles are transported over larger distances, and thus transport the accumulated PTEs (i.e. Cd and Pb). Larger particles, due to greater gravitational forces, are transported over shorter distances and settle near the areas closer to the pollution source. Therefore, at these distances, the settled

2.4 Artificial Biogeochemical Barriers as Phytoremediation Potential of Herbaceous. . .

75

PTEs make their maximum. Besides, it shows that the zone affected by pollutants is rather extended because of its distance of 1 km from the plant. The values are smaller than 1, while at the distance of 3 km downwind, the values are even larger than 3. Figure 2.21 a, c provides the values of the concentration coefficients of PTEs in wood calculated by dividing the concentration of particular CE in the considered area by its concentration in the control area. Though the concentration coefficient could describe the specific features of the transfer area of PTEs over a particular distance, the dynamic factor in bioaccumulation describes it in a more effective way. It can be explained by the fact that calculation based on using the BAdyn involves the concentrations of PTEs in the soil, which helps with determining the ratio of the pollution level of the tree to the pollution level of the soil. The cases of Pb and Cd show that the particles containing these PTEs reach more distant territories (both their soil and trees) in greater amounts. However, since trees make the primary barrier to this aerogenic transfer and retain larger amounts of the particles enclosing PTEs, the concentrations of PTEs in the soil increases along with a rise in the distance from the pollution source.

2.4

Artificial Biogeochemical Barriers as Phytoremediation Potential of Herbaceous Plants

Metals remain in the environment, thus causing soil pollution. Metals do not degrade (the only exceptions are Hg and Se that can be transformed and volatilized by microorganisms). However, in general, it is very difficult to eliminate metals from the soil. The traditional treatment of the soil polluted with metals is expensive and cost prohibitive when large areas of the soil are contaminated. The available types of soil treatment removing PTEs include high temperature treatment (produce a vitrified, granular, non-leachable material), solidifying agents (produce cement-like material) and the washing process (leaches out pollutants). They all are extremely expensive comparing with phytoremediation (Donahue 2000). Phytoremediation may be applied wherever the soil or static water environment have become polluted or suffer from ongoing chronic pollution. The phytoremediation system (Fig. 2.22) works because of the plant ability to absorb contaminants through the root system, store them in root biomass and transport them into stems and leaves. A living plant may continue to absorb metals until harvested. Then, a lower level of the pollutant will remain in the soil, and therefore the growth cycle must usually be repeated through several years to achieve the allowable limits. After the process, the treated soil may support other vegetation (EPA 1998). The harvested biomass can be converted into bioenergy using different energy recovery techniques such as anaerobic digestion, incineration, gasification and biodiesel production (Ginneken et al. 2007). To treat the soil, more effective plants have to be removed with the roots, as the concentrations of some types of PTEs (Al, Cr, Cu, Fe, Pb) in the roots can be 10–100 times greater than those in the shoots (Baker 1981). If plants are

76

2 Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies

Fig. 2.22 The phytoremediation system (Kloosterman 2008)

Harvest

Transport to upper plant parts

Root absorption from soil fluids

Processing (e.g. as bio-fuel or by composting)

Reuse or depositing Impact on accessibility and absorption via the plant itselt (secretion of chelates, enzymes, etc.) or via additives

incinerated, ash must be disposed in hazardous waste landfill, but the volume of ash is much smaller than that of the polluted soil if dug out and removed for treatment (Donahue 2000).

2.4.1

Tolerance to PTEs in the Plants of the Brassicaceae Family

Most of PTEs are emitted from anthropogenic sources (Druteikienė et al. 2002). Industry, transport, manure and herbicides used in agronomy, industrial waste as well as sewage sludge cause an environmental hazard to polluting plants, animals and people in contact with PTEs (Fargasova 1999). In addition to anthropogenic sources, the natural sources of PTEs cover the soil matrix, seawater, dust, volcano gas and forest fire. Many PTEs are trace elements essential to plants, yet a large amount of Mn, Cu, Zn, Mo, Co and B may have a toxic impact on the physiological process of plants (Lukšienė and Račaitė 2008). The plants called hyperaccumulators can be used for treating the polluted soil (Baker et al. 2000; Cosio et al. 2004; Lombi et al. 2001; Yang and Bin 2001). T. caerulescens (Fig. 2.23) is a hyperaccumulating plant having an ability to accumulate Zn concentration in excess of more than 1% in its foliar dry matter and can be considered a hyperaccumulator of this metal (Baker and Brooks 1989; Reeves and Brooks 1983; Reeves 1988). T. caerulescens tolerate Zn and Cd but also has an elevated tolerance to other metals such as Pb, Cu and Ni (Baker et al. 1994). However, it is quite sensitive to Cu (McLaughlin and Henderson 1999). Thlaspi goesingense (Fig. 2.23) is a member of the Brassicaceae family closely related to Arabidopsis thaliana (Salt 2000). Thlaspi goesingense collected in Austria had been reported to hyperaccumulate Ni (Reeves and Brooks 1983). Ni hyperaccumulator Thlaspi goesingense is tolerant to Ni, Zn, Co and slightly resistant

2.4 Artificial Biogeochemical Barriers as Phytoremediation Potential of Herbaceous. . .

77

Fig. 2.23 The plants of the Brassicaceae family

to Cd. Freeman and Salt (2007) observed that elevated glutathione driven by the constitutive activation of serine acetyltransferase (SAT) played a role in Ni tolerance to T. goesingense. Another species from the Brassicaceae family is Thlaspi montanum (Fig. 2.23) var. Montanum. The analysis carried out by Boyd and Martens (1998) showed that Thlaspi montanum populations were able to hyperaccumulate Ni, thus showing Ni hyperaccumulation to be a constitutive trait in this species. The populations of the plant differed in their ability to extract some elements (e.g. Ca, Mg, P) from the soil. The scientists suggest that Ni hyperaccumulation ability of T. montanum may be an inadvertent consequence of an efficient nutrient (possibly Zn or Ca) uptake system (Boyd and Martens 1998). The plant called Arabidopsis halleri (Fig. 2.23) from the Brassicaceae family is also used to know as Zn hyperaccumulator. This plant has the ability to accumulate Zn and Cd in shoot biomass. The high concentrations of Zn and Cd found in Kupper

78

2 Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies

et al. (2000) analysis were in the leaves, roots and also flowers that contained very little of these metals. Arabidopsis thaliana (Fig. 2.23), as an accumulator of PTEs, is under research for his tolerance to Zn, Cd and Ni (Cho et al. 2003). Arabidopsis thaliana in Keilig and Ludwig-Müller (2008) work was used for investigating the possible effects of flavonoids on tolerance to PTEs. Arabidopsis wild-type and mutant lines with a defect in flavonoid biosynthesis were grown on media containing different PTEs, and two growth parameters were evaluated. It was shown that root length and seedling weight were reduced in mutants more than in the wild type when grown on Cd while on Zn only root length was affected.

2.4.2

The Accumulation of Cu, Pb, Cd and Zn in the Aboveand Under-Ground Parts of Plants

The phytoremediation of the soil polluted with PTEs is emerging technology aimed at extracting inactivate metals in the soil (McGrath 1998; Salt et al. 1998). In recent years, it has attracted attention for the low cost implementation and environmental benefits. Moreover, the technology is likely to be more acceptable to the public than to other traditional methods (Lombi et al. 2001). There are wide variations in the extent to which the accumulated metals are transported from the root system to the shoot. The plant body consists of two basic parts—the shoot system and the root system (Fig. 2.24). The shoot system is above the ground and includes organs such as leaves, buds, stems, flowers and fruits. The functions of the shoot system include photosynthesis, reproduction, storage, transport and hormone production. The root system is below the ground and includes the roots and modified stem structures like tubers and rhizome. Fig. 2.24 Metal ions in the plant roots and the shoot system (Narasimba et al. 1999)

Shoot system V, Pb Ni, Mn, Zn, Mn, Ag, Cr, Pb, Sn, V, Pb, Ni, Mn, Zn, V, Pb Ag, Cr, Pb, Sn, Ni, Mn V, Pb, V, Pb Zn Mn Cd Fe Ni Fe Zn Cd Cu Co Fe Fe Cu Ni Root system

2.4 Artificial Biogeochemical Barriers as Phytoremediation Potential of Herbaceous. . .

79

If plants are from one population, the concentrations of Al, Cr, Cu, Fe and Pb in the roots can be from 10 to 100 times greater than those in the shoots. This lack of internal transport (Baker 1981) is emphasized in the shoot/root quotients. For Zn, Ni, Co and Mn, shoot concentrations exceeded those in the roots, which is typical of an accumulator plant (Baker 1981). The behaviour with respect to Cd, Mo and Ag is usually intermediate and shows some restriction on internal transport. In the cases of Cr, Cu, Al, Fe and Pb, the greater fraction of the accumulated metal is fixed in the roots where concentrations are so high as to give the roots characteristic colours when they were ashed. However, for Co, Ni, Mn, Zn and Cd, there was no evidence for fixation in the roots with the concomitant restriction of transport to the shoots. With the exception of Mn, Ni and Pb, most of metals inhibit root growth. The tested concentrations of the three metals mentioned above brought approximately on average only a 10–20% reduction in root elongation. A generalized pattern of partitioning metals in the root and shoot system. Silver (Ag), Cr, Tin (Sn) and Vanadium (V) accumulate more in the shoots (stems and leaves) compared to the roots and rhizomes (Fig. 2.24). Cd, Co, Cu, Iron (Fe) and Molybdenum (Mo) accumulate more in the roots and rhizomes than in the shoots (stems and leaves). Ni, Manganese (Mn) and Zn are distributed more or less uniformly in the root/shoot of the plant (Narasimha et al. 1999). The study by Kupper et al. (2000) suggests that with 5 μM of Zn in the nutrient solution, Zn was primarily accumulated in the shoots, but a higher concentration of Zn like 500 μM of Zn in the roots exceeded that in the shoots. This was probably because of precipitation in the root apoplast (Kupper et al. 2000). Cd concentration in the roots was always larger than that in the shoots. The paper also shows that the highest concentrations of Zn and Cd were found in the bases of trichomes on the leaf surface of T. caerulescens. During the experiment on A. halleri, Zn content was measured in both shoots and roots. The obtained results showed that the population from the polluted area accumulated Zn in its shoots and roots quicker than that from the contaminated site (Bert et al. 1999). Bert et al. (1999) found out that the content of zinc in the shoots of the seedlings of A. halleri from both sites was much higher than that of the roots, whereas Zn content of the roots of A. thaliana seedlings was 4  5 times greater than that of the shoots. The analysis demonstrated that most of Zn in A. halleri was translocated from the roots to the shoots. Metallophilic root foraging analysis shows that root metal foraging could therefore be related to the high levels of tolerance to the metal in question rather than to the efficiency of high metal accumulation (Assuncao et al. 2003). The enhanced translocation of metals from the roots to the leaves typically results in high metal concentrations in xylem fluid and shoot-to-root metal concentration ratios higher than 1 (Shen et al. 1997; Lasat et al. 1998; Schat et al. 2000). Lasat et al. (1998) found the indications of faster Zn efflux out of the vacuoles of the root cells of T. caerulescens compared with T. arvense when determining Zn compartmentalization conducting radiotracer efflux analysis. Following 96 h of exposure, Zn accumulation in the roots was higher in T. arvense than that in T. caerulescens (Lasat et al. 1996). This could indicate a difference in root tonoplast transport

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2 Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies

characteristics with a smaller influx and a larger efflux of root vacuoles from T. caerulescens when compared to T. arvense (Lasat and Kochian 2000). It is a discussion that T. caerulescens rather than T. arvense should have a higher amount of Zn readily available for loading into xylem (Lasat et al. 1998). When immersing separated leaf sections in the radiolabelled Zn solutions, Zn accumulation was higher in T. caerulescens than that in T. arvense. Thus, this suggests that both enhanced xylem loading and enhanced uptake into leaf cells could play a role in Zn hyperaccumulation in T. caerulescens (Assuncao et al. 2003).

2.4.3

Extractability or Bioavailability Changes in Time

Two opposing hypotheses have been put forward to explain metal behaviour in the sludge treated soil in the long term. The first one is called the ‘time bomb’ hypothesis (Berrow and Burridge 1980; McBride 1995), in which metal availability is predicted to increase due to the decomposition of the organic matter of sludge. This, however, ignores evidence from non-sludge contaminated soils, which shows that other soil properties and chemical factors control metal solubility when organic matter has not been added. The alternate hypothesis is that of fixation, which states that metals will gradually revert (Lewin and Beckett 1980) to more stable and insoluble forms in the soil with time, particularly as the added organic matter decomposes. The archived samples from the Woburn Market Garden Experiment were used for testing these hypotheses over a period of 20 years when sludge was applied following almost 25 years with no sludge application. Two indicators of changes including those in the chemical extractability of metals in the soil and changes in uptake by crops were assessed. This is unique among long-term sludge experiments where pH usually drifts down because of the decomposition of the added organic matter. As for practical situations, the possibility of future changes in pH has to be considered, especially if land is removed from arable agriculture and liming is stopped. The concentration of organic carbon in the soils that had received the highest rate of sludge was almost 3% in 1960 and decreased to 1.9% in 1984. All types of organic treatment showed similar declines, but control treatment increased slightly from 0.9% before the experiment and rose to 1.0% in 1960 but has remained largely stable since then. A later group of scientists discovered that the soils receiving sewage irrigation for 10 years exhibited a significant increase in Zn, Fe, Ni and Pb while only Fe was positively affected in the soil by sewage irrigation for 5 years (Rattan et al. 2005). The extractability of Zn and Cd was assessed with 0.1 M CaCl2 (Sauerbeck and Styperek 1985) and expressed as a percentage of the total concentrations of aqua regia. Extractability ranged between 0.5 and 3.2% for Zn and from 4 to 18% for Cd (Fig. 2.25). Sludge-amended soils consistently had higher percentages of CaCl2-extractable Zn and Cd than the soils receiving inorganic fertilizer or farmyard manure. This is consistent with several studies (Sanders et al. 1987; Sloan et al. 1997) and indicates

CaCl2 extractability, %

Fig. 2.25 Changes in the extractability of Zn (top) and Cd (bottom) from the soil as a percentage of the total metal concentration of aqua regia

CaCl2 extractability, %

2.4 Artificial Biogeochemical Barriers as Phytoremediation Potential of Herbaceous. . .

81

3.5 Arable Grass 3.0 2.5 Sludge 2 2.0 1.5 FYM 2 1.0 Inorganic Sludge 0.5 stops 0.0 1955 1960 1965 1970 1975 1980 1985 Year 20.0

Arable

16.0

Grass Sludge 2

12.0 FYM 2 Inorganic

8.0

4.0 Sludge stops 0.0 1955 1960 1965 1970 1975 1980 1985 Year

Table 2.7 The properties of Soil_I Organic content 75-85%

pH 5.5-6.5

Humidity 60-70%

Working time Not limited

Producer JSC Vitaplantas, Tilzes 52, Klaipeda, Lithuania

that higher proportions of sludge-borne Zn and Cd compared to soil-native Zn and Cd were in soluble or exchangeable forms, and hence of potentially higher bioavailability. The percentages of CaCl2-extractable Zn and Cd fluctuated over time, but there was no clear evidence of either an increasing or a decreasing trend. However, for Zn, there was an indication of lower extractability during the period after 1970 when the experiment was laid to grass. However, scientists could not give an explanation for this phenomenon.

2.4.4

Seedling Preparation

Seeds were planted and grown in the clean soil. The properties of soil_I are given in Table 2.7. The germination period lasted for 2 weeks in the clean soil. In late March, plants were transplanted to peat pots with the clean soil for further growth. Later in June, half of the plants were transplanted to the pots with control soil—soil_II (Table 2.8)

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2 Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies

Table 2.8 The properties of Soil_II Organic content 92-96%

pH 56

Humidity 60-70%

Supplements Limestone powder, manure with microelements, FIBA ZORB, that prompts absorption of water

Main component Sphagnum peat H3-H7.

Fig. 2.26 Seedlings before the last sampling (S-grown with sewage sludge, C-control)

while the others to the soil II mixture with sewage sludge (soil:sludge ¼ 2:1). Sewage sludge for treatment was taken from the Vilnius wastewater treatment plant (Kisielyte 2011). Plants were watered using clean water and nutrient Zalsta®Multivit (NPK-5-2,52,5 with microelements) that contained nitrogen (N)—5%, including amide (N-NH2) (5%); phosphorus pentoxide soluble in water (P2O5)—2.5%; potassium oxide soluble in water (K2O)—2.5%; boron (B)—0.01%; copper (Cu)—0.01%; iron (Fe)— 0.04%; manganese (Mn)—0.01%; molybdenum (Mo)—0.001%; zinc (Zn)—0.01%; EDTA chelated trace elements (microelements). Seedlings were harvested three times in 2008. The first harvesting took time in July, the second in August and the third in September (Fig. 2.26). To evaluate acropetal and basipetal metal translocation, the ratio factor (R) equation was used: controlshoots controlroots treatedshoots Rtreated ¼ treatedroots

Rcontrol ¼

ð2:5Þ ð2:6Þ

There are three ways to evaluate the results of these equations: R < 1 acropetal metal translocation; R ¼ 1 none; R > 1 basipetal metal translocation.

2.4 Artificial Biogeochemical Barriers as Phytoremediation Potential of Herbaceous. . .

Height, cm

12.0

8.3

7.3

6.6

8.0

2.00

12.0

11.1 6.1

Control Treated

4.0 0

1

2 Month

Total dry mass, g

16.0

1.33

1.60 1.01

1.20

Control Treated

0.80 0.40 0

3

0.44

0.34 0.28 1

2 Month

Total wet mass, g

3.43

4.0 3.36

1.91

3.0 2.0

1.54

Control Treated

1.32 0.89

1.0 0

1

2 Month

0.27 3

b)

3

Wet mass of roots, g

a) 5.0

83

0.40

0.24

0.20

0.30 0.20

0.15 0.11 0.12 0.11

Control Treated

0.10 0

c)

1

2 Month

3

d)

Fig. 2.27 Biomass development related traits (a) height, (b) total dry mass, (c) total wet mass, (d) root wet mass of control and treated plants (Kisielyte 2011)

To evaluate how effective T. caerulescens can treat the polluted soil, the metal removal equation (Porębska and Ostrowska 1999) was used: R ¼ B  C  n,

ð2:7Þ

where R—metal removal, g/ha, B—biomass, kg/ha of d.w., C—metal content, g/ha of d.w., n—years of application (1, 5, 10, 20). To determine differences in removal, the calculations of the roots and shoots were made separately. Control plants were higher than the plants treated with sewage sludge (Fig. 2.27a). The highest control plants are approximately 12 cm while the highest treated plants are around 7 cm in height. High differences in control and sewage sludge plants vary from 2.3 to 8 cm, but differences between plant heights are not significant ( p > 0.05). The possible reason why Thlaspi caerulescens grew poorly in the soil polluted with sewage sludge could be plant sensitivity to Cu. Its exposure can induce toxic symptoms such as growth inhibition, chlorosis or necrosis and thus affect the uptake of Zn and Cd by T. caerulescens. Inhibition caused by Cu stress was observed earlier by Lehotai et al. (2011), Beckett and Davis (1978) and Ebbs and Kochian (1997). Hyperaccumulating plants are slow-growing because HMs are making slow damage to their tissue. Damage to the cell membrane system is one of the primary effects in HM toxic action in plants (Janicka-Russak et al. 2008). HMs also cause an oxidative stress (Flora et al. 2008). Because of their high reactivity, HMs can directly influence growth, senescence and energy synthesis processes (Maksymiec 2007). Pb and Cd inhibit photosynthesis and transpiration (Bazzaz et al. 1974). Metals also cause structural and ultra-structural changes, damage to

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2 Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies

water relations in the plant, changes in mitochondrial respiration and some more effects (Prasad 1999). A few of the researchers show that Zn probably causes the lowest damage, as, for example, Helianthus annuus was able to germinate and grow efficiently under all Zn concentrations (Jadia and Fulekar 2008). Dry mass tendencies in Fig. 2.27b show that control plants continued growing while the plants treated with sewage sludge had very similar biomass during all 3 months. However, no statistically significant difference ( p > 0.05) was determined. The total wet mass of plants was also compared. Control plants had higher wet mass (Fig 2.27c). The highest average of wet mass was found after the second harvesting (3.43 g) that could mean water uptake was the most intensive during the second month. The third month shows the end of vegetation, plants had the highest height while water content was the lowest. Treated plants had 57% lower wet mass than control plants. However, no statistically significant difference ( p > 0.05) was determined between the total wet mass of control and treated plants. The lower wet mass of treated plants was observed earlier, when toxic metals such as Cd affected plasma membrane permeability, which might result in the reduction of water content. The same situation occurs in the root development process (Fig 2.27d). The roots of control plants contained 28% more water. The obtained results show that the roots of control plants were able to develop better. The maximum weight of control roots was measured following the first harvesting (0.24 g), while the roots of treated plants had the highest level of water caused by the second harvesting. Higher sensitivity to the stressful condition could be a reason for poor root development. Long-term Cu exposure can result in a serious decrease in shoot and root growth. The reason for the higher sensitivity of the root system is larger proportions of Cu accumulated inside it, possibly because under these conditions plants exclude toxic metals from their shoots to roots (Lehotai et al. 2011). Other metals, like Mn, Ni and Pb, can cause a 10–20% reduction in root elongation.

2.4.5

Acropetal and Basipetal Metal Translocation

Cu ratio factor is shown in Fig 2.28a. Treated and control plants had only acropetal Cu translocation, which means that the highest Cu concentration was found in plant roots. It had been estimated that the concentration in plant roots was 10–100 times greater than that in the shoots (Baker 1981; Lombi et al. 2001). The highest value of Cu in T. caerulescens roots was 13.19 mg/kg of d.w. and was found after the second harvesting. In the third month, Cu concentration dropped in the shoots and roots. Pb shows other tendencies and different metal translocation places (Fig 2.28b). A higher concentration of this metal is accumulated in the shoots of control plants, which is basipetal metal translocation. As for treated plants, acropetal translocation is changed by basipetal in the last vegetation month. The highest Pb ratio factor was found in the second month control plants and reached 5.09. The basipetal and acropetal translocation ratio of Zn is shown in Fig 2.28c. Throughout the investigated period, treated and control plants had the highest

Ratio factor

0.30 0.25 0.25 0.23 0.20 0.16 0.15 0.12 0.10 0.08 0.06 0.05 0 1 2 3 Month

Treated Control

Ratio factor

2.4 Artificial Biogeochemical Barriers as Phytoremediation Potential of Herbaceous. . . 6.00 5.09 5.00 4.00 3.00 2.42 2.37 2.00 1.31 1.00 0.69 0.09 0 1 2 3 Month

a) 1.76 1.19

1.27

1.06

0.4 0

Treated Control

0.68

0.8 0.23 1

2 Month

c)

Ratio factor

Ratio factor

1.2

Treated Control

b)

2.0 1.6

85

0.59

0.60 0.40 0.20

0.32 0.23

0.22

Treated Control

0.08 0.03 3

0

1

2 Month

3

d)

Fig. 2.28 The translocation type of (a) Cu, (b) Pb, (c) Zn and (d) Cd (Kisielyte 2011)

concentration of Cd located in plant roots (Fig 2.28d). The same metal location tendency was found earlier, as Cd and Cu were more accumulated in the roots and rhizomes than in the shoots, whereas Zn was distributed more or less uniformly in the roots and shoots of the plant (Narasimha et al. 1999). Comparing all four metals, the lowest accumulated concentration was found in Cd. The highest accumulated concentration was established in Zn.

2.4.6

The Accumulation of PTEs in Treated Plants

The plants grown in the treated soil were able to accumulate Cu up to 32.10 mg/kg of d.w. Three months of vegetation shows that the most active accumulation of Cu can be seen during the second month of growth (Fig. 2.29a). The highest accumulated concentration of Pb reaches 13.89 mg/kg of d.w. Figure 2.29b shows that concentration was measured after the second month harvesting. Pb values in plant shoots are much lower than those in plant roots but are more stable by time scale. Baker work (1981) also shows that Pb concentration in the roots can be much greater than that in the shoots. Pb concentration accumulated by plants could be higher, but the solubility of this metal remains low in all types of sludge at all pH values ranging from pH 3 to pH 10 (Rothe et al. 1988). Comparing with other three metals, plants have accumulated the highest concentration of Zn (Fig 2.29c), which reaches 1720.52 mg/kg of root dry weight and was found after the second month harvesting. However, a comparison of Zn concentration in the shoots during all 3 months points to differences that are not significant

2 Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies 40.0

32.10

30.0 Shoots Roots

20.0 10.0

7.71

0.64 0 1

1.77 2 Month

3.99 0.99 3

Concentration, mg/kg

Concentration, mg/kg

86

1721

1600 1200 800 400 0

467 392 390 1

2 Month

c)

13.89

12.0 Shoots Roots

8.0 4.0 0

1.24

1.80

1

1.19

0.89 0.67

2 Month

3

b)

433

636

3

Shoots Roots

Concentration, mg/kg

Concentration, mg/kg

a) 2000

16.0

3.50 1.51 3.00 2.50 2.00 1.50 1.00 0.26 0.13 0.50 0.028 0.155 0.05 0 1 2 3 Month

Shoots Roots

d)

Fig. 2.29 The concentrations of (a) Cu, (b) Pb, (c) Zn and (d) Cd in treated plants (Kisielyte 2011)

( p > 0.05). T. caerulescens is able to accumulate up to 30,000 mg/kg in this body (Brown et al. 1995a). Treated plants accumulated the lowest concentration of Cd. Figure 2.29d shows that the highest amount reaches 1.51 mg/kg of root dry weight. Plant shoots had the lowest concentration of Cd, but it rose during the three-month period. Concentrations in the roots differ more widely and are low after the first and third months but appear to be much higher after the second month harvesting. A case reported by Lombi et al. (2000) shows that T. caerulescens can remove up to 10,000 mg/kg of Cd. Only few works analyse metal removal according to the plant age. A group of scientists (Robinson et al. 1998) considered that growing T. caerulescens under field conditions possibly lowered metal concentrations in older plants due to the dilution effect of higher biomass if metal uptake was not proportional to increasing biomass. The possibility of higher metal concentrations in younger plants because of their greater proximity to the ground and hence a greater risk of contamination from the wind-borne soil was also discussed by the authors. Another opinion comes from the experiment on the transplanted and directly sown to the field plants (Hammer and Keller 2003). This research shows that the concentrations of Cd and Zn in transplanted T. caerulescens decrease over the three-harvest period. However, for the sown plants, no decrease was observed. After analysing these facts, the authors still think that metal concentrations in plants are somewhat unpredictable but may stay constant throughout the period of phytoextraction in some circumstances. One more study shows that at harvest young leaves rather than the older ones exhibited a higher concentration of Cd (Perronnet et al. 2003). The authors concluded that the distribution of Cd and Zn in hyperaccumulator T. caerulescens varied according to

2.4 Artificial Biogeochemical Barriers as Phytoremediation Potential of Herbaceous. . .

87

the age of the organ and plant. The obtained results showed that the whole-plant content of Zn decreased with time while Cd increased or remained unchanged.

2.4.7

PTEs in the Soil and Sewage Sludge

The concentrations of PTEs were estimated in the samples of the control soil. The obtained results are shown in Fig. 2.30a. Similarly to the plant, the highest concentration of Zn was found and reached 23.00 mg/kg of the control soil (Kisielyte 2011). The lowest concentration was that of Cd and reached only 0.29 mg/kg of the soil. Cu and Pb were found in similar proportions—4.19 and 5.17 mg/kg of the soil, respectively. The samples of the mix of the soil and sewage sludge (2:1) were also analysed. The evaluation of PTEs shows that higher metal concentrations were established in the treated rather than in the control soil (Fig 2.30b). Zn concentration is the highest (24.87 mg/kg) in the treated soil too. Cd composes only 1.92 mg/kg, Cu—18.84 mg/kg and Pb
14.30 mg/kg of the soil. HM concentrations take the form of Zn > Cu > Pb > Cd that was found earlier. The research carried out by Walter and Cuevas (1999) showed that the amount of Zn in the treated soil was the highest from all four metals and made 2250(535) mg/kg. Cu concentration took the second position equal to 1640(577) mg/kg, Pb was the third and counted 665(180) and Cd was determined with the lowest amounts—82(54) mg/kg. A similar result was estimated in Greece (Zorpas et al. 2000) where sewage sludge collected from the Psittalia wastewater treatment plant in Athens had a descending concentration of the following metals: Zn > Pb > Cu > Cd.

2.4.8

Modelling the Removal of PTEs from Plants

30.0 25.0 20.0 15.0 10.0 5.0 0

23.00 Zn Cu Pb Cd

6.1 4.19 5.17 Zn

Cu Pb Metals

a)

0.29 Cd

Concentration, mg/kg

Concentration, mg/kg

The Phyto-DSS model was chosen for this work because it considered the whole system related to plant use for phytoextraction. It calculates plant growth, water flux, component (e.g. pollutant or nutrients) flux and costs that embrace the income of 30.0 24.87 25.0 20.0 15.0 10.0 5.0 0

19.23 14.30

Zn Cu Pb Cd

6.1 1.92 Zn

Cu Pb Metals

Cd

b)

Fig. 2.30 The concentrations of Cu, Pb, Cd and Zn in (a) control soil and (b) treated soil

88

2 Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies

exploiting large vegetated areas. These simulations reveal the feasibility, risk and potential outcomes of phytomanagement. The system requires daily climate data as well as information on the substrate and plants. The Phyto-DSS makes economic assessment by comparing the costs of phytoremediation with those of inaction and the best alternative technology (polluted soil treatment). The model is mostly based on using plant water and soluble PTEs in the soil solution (Kisielyte 2011). The Phyto-DSS was created in 2000 at the Instituto de Recursos Naturales y Agrobiología de Sevilla in Spain (during OECD fellowship). Subsequently, the Phyto-DSS was developed at HortResearch, Palmerston North, New Zealand (2001–2004), and the Swiss Federal Institute of Technology, Zurich, Switzerland (2005–2007) (Soil Protection. . .2010). Plant transpiration is the cornerstone of phytomanagement, and therefore forms the foundation of the Phyto-DSS that uses potential evapotranspiration (ETo) calculated from solar radiation, temperature, relative humidity and wind-speed using the FAO Penman–Monteith equation (Allen et al. 1998). The Phyto-DSS considers the amount of component (M ) removed by the plant, which is therefore proportional to the transpiration rate (T ) over a given period of time (t). Z

t

M/

Tdt,

ð2:8Þ

0

Phytoextraction induced change in soil component concentration over time. The local concentration of the component in the soil solution and hence the potential amount of the component entering plant roots will be depth-dependent. Plant component-uptake causes a change in the concentration of the soil component (mg/kg) at depth d and is calculated as l Δ½M z ¼ ρz

Z

t

Rz TC∅dt,

ð2:9Þ

0

where D[M]z ¼ change in the concentration of the contaminant component (mg/kg) at depth z, rz ¼ bulk density of the soil (g cm-2) at depth z, t ¼ time (days), Rz ¼ root density fraction (root mass at depth z)/(total root mass), T ¼ water use (L/day), C ¼ the concentration of the component in the soil solution (mg/L), f ¼ root absorption factor for the component. Modelling for this work was done by the Phyto-DSS program. The purpose of this part of the chapter is to evaluate how much and how effective T. caerulescens can remove metals from the soil mixed with sewage sludge. The plant is assumed to have dry biomass of 0.7 t/ha. As can be seen from Fig 2.31a, up to 529 g/ha of Zn could be extracted every year. That is the biggest amount compared with all four metals. The model shows that only up to 1 g/ha of Cd could be annually extracted (Fig 2.31b), but Cd remains only at a low concentration in the investigated soil and sludge.

2.4 Artificial Biogeochemical Barriers as Phytoremediation Potential of Herbaceous. . .

140 120 100 80 60 40 20 0

Plant response curve Plant concentration, mg/kg

Plant concentration, mg/kg

Plant response curve

89

0.12 0.10 0.08 0.06 0.04 0.02 0

0 10 20 30 40 50 Total soil component, mg/kg a)

0 3 4 1 2 Total soil component, mg/kg b)

0.0050 0.0045 0.0040 0.0035 0.0030 0.0025 0.0020 0.0015 0.0010 0

Component extracted

Component extracted Component extracted, kg/ha

Component extracted, kg/ha

Fig. 2.31 Plant response and extraction for (a) Zn, (b) Cd, by the Phyto-DSS model

0 10 20 30 40 50 Total soil component, mg/kg a)

0.0045 0.0040 0.0035 0.0030 0.0025 0.0020 0.0015 0.0010 0 0 10 15 20 5 Total soil component, mg/kg b)

Fig. 2.32 Plant response and extraction for (a) Cu, (b) Pb, by the Phyto-DSS model (Kisielyte 2011)

According to the model, Cu extraction with T. caerulescens could reach up to 4 g/ ha and 3 g/ha of Pb annually (Fig. 2.32a, b). As can be seen from Table 2.9, the Phyto-DSS model shows higher extraction of all four metals. Using the metal removal equation assisted in calculating removal with the roots and shoots separately, thus summarizing the final results. There is no possibility of simulating root and shoot removal on individual basis applying the Phyto-DSS program. The model assumes that all components will be translocated to the above-ground portions of the plant. The analysis of the root material invariably

90

2 Natural and Semi-Natural Biogeochemical Barriers as Natural Technologies

Table 2.9 A comparison of metal extraction per year

Model Metal removal equation Phyto-DSS Difference

g/ha Cu 1.8 4.0 55%

Pb

Cd

1.1 3.0 63%

0.1 1.0 90%

Zn 307.4 529.0 42%

shows that this assumption is not correct due to the presence of the component in the root tissue. On the other hand, it is appropriate to expect that the results of the PhytoDSS model should be more accurate, because the program also employs the soil, temperature, water use and lots of other data having influence on the accuracy of simulation results. The Phyto-DSS shows higher extraction for all four metals (Kisielyte 2011). Lots of researches demonstrate that metal removal can be induced by selecting from a variety of experimental conditions. Some scientists use fertilizing, greenhouses or grow plants in a prepared liquid solution. The previous group of scientists (Robinson et al. 1998) conducted the field experiment and evaluation disclosing that 60 kg/ha of Zn could be annually extracted from 5.2 t/ha of highly fertilized Thlaspi caerulescens biomass. This makes 1.16% of plant dry weight. 8.4 kg/ha of Cd, i.e. 0.16% of dry biomass, could be removed using the same amount of biomass, whereas the unfertilized plants had an annual biomass production of 2.6 t/ha and removed only 30.2 kg/ha of Zn and 4.2 kg/ha of Cd. During the experiment, Baker and Brooks (1989) reached Zn content to make up to 3% of d.w. Later, McGrath et al. (1993) reported 30.1 kg/ha for Zn extracted by moderately fertilized plants from the soils containing only 444 mg/kg and 0.25–0.66% of Zn in the plants when the concentration of Zn in the soil was around 300 mg/kg. Pollard and Baker (1996) reported 1.8–3.3% of Zn in foliar material. For the successful practical application of phytoremediation, a number of variables must be considered. Among the most important of those is the product of biomass and metal content of the plant material. This has been shown by the experiments conducted by Bennett et al. (1998) where Thlaspi caerulescens was grown over base metal mine waste. The product of biomass and Zn concentration in plants rose from 22 μg for unfertilized specimens to 497 μg for the plants fertilized with 50 μg/g of nitrogen as calcium ammonium nitrate. The second variable that has to be considered is time span, i.e. the number of annual crops needed to achieve the desired degree of remediation of the soil. For making these calculations, it cannot be assumed that the entire target element is plant-available. The adoption of the conservative approach provides (Robinson et al. 1998) that only half of the total metal content of soils will be available to plants. Thus, the total number of annual croppings of T. caerulescens was calculated, thus removing half of the metal content of the treated soil down to a depth of 5 cm assuming that the soil had a bulk density of 1601 kg/m3 and 50% humid sewage sludge had the density of 891 kg/m3. The plant is supposed to have the biomass of 0.7 t/ha. McGrath et al. (2000a, b) proposed using the zero-order kinetic equation causing no decrease in the concentrations or yield of PTEs in the plant and assisting with calculating the number of years

2.4 Artificial Biogeochemical Barriers as Phytoremediation Potential of Herbaceous. . .

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Table 2.10 Time span required for achieving the desired degree of remediation Metals, g/ha Amount of available metals in the treated soil Number of annual cropping

Cu 2330

Pb 3783

Economically unviable

Economically unviable

Zn 7070

Cd 184

13

5

necessary to remediate all available metals. Considering the accuracy of the obtained results, it should be taken into account that linear uptake can sometimes lead to overestimating (McBride 2002). However, earlier Lombi et al. (2001) estimated that phytoextraction efficiency of Zn and Cd did not decrease along with croppings. The findings are shown in Table 2.10. The made calculations show that T. caerulescens can effectively remove Cd and Zn. For Cd—only 5 and for Zn—13 annual croppings will be needed. It was observed earlier that T. caerulescens showed sensitivity to Cu (McLaughlin and Henderson 1999; Lombi et al. 2001). To remediate all available Cu would be economically unviable, because the application of phytoremediation for 20-year removal would reach approximately 2%. The same situation is seen in the case of Pb, but a more plausible reason for removal ineffectiveness would be very low Pb solubility in the soil rather than plant sensitivity to this metal (Rothe et al. 1988). Pb is largely immobile in the soil and its extraction rate is limited by diffusion to the root surface (Lombi et al. 2001). Even if Pb accumulates at the root, usually it is not translocated significantly to leaves (McBride 2002). Lots of studies show that the major limit to the uptake of metals by a plant is the solubility of metals in the soil (Whiting et al. 2003; Brown et al. 1994; Wang et al. 2006).

Chapter 3

Sustainable Natural Materials and Their Importance for Waste Management and Stabilization of Soil Pollution

The use of sustainable natural materials in environmental engineering systems is presented as the second sustainability level of environmental protection technologies. This chapter focuses on employing such materials in the stabilization of soil pollution and waste management, explores biochar produced from various kinds of waste materials containing potentially toxic elements (e.g. sewage sludge and waste from paper manufacturing), deals with a comparative analysis of its properties, presents research into the stability of potentially toxic elements found in biochar, evaluates environmental risk and discusses the results of investigating the use of biochar for stabilizing metallic elements in the polluted soils and the effect of biochar on the bioavailability of these elements in the soil.

3.1

The Second Sustainability Level of Environmental Protection Technologies. A Carbon Footprint of Wood as a Feedstock for Biochar

Sustainability is a metadisciplinary endeavour with a goal of achieving balance between the economic, environmental and societal objectives of development. Achieving sustainability goals while promoting economic development, however, is not an easy task. It requires understanding the impacts of developmental activities through the integration of information and insights across multiple systems and perspectives in the realms of industrial, environmental and societal systems. Sustainability, as a system, also institutes that products or processes cannot be sustainable on their own, as they are the elements of a system. Similarly, it states that environmental sustainability strategies (i.e. pollution prevention and industrial ecology) need to be modified to also address social and economic concerns (Mihaljevič et al. 2004). This chapter describes the sustainability aspects of production and the use of biochar as a sustainable and value-added product for promoting sustainability. © Springer Nature Switzerland AG 2020 P. Baltrėnas, E. Baltrėnaitė, Sustainable Environmental Protection Technologies, https://doi.org/10.1007/978-3-030-47725-7_3

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The cases suggest that environmental issues and sustainability challenges can be addressed through the development of technological innovations such as biochar that could simultaneously tackle water-energy-food-carbon nexus, which is a key area of importance to global sustainable development initiatives.

3.1.1

Carbon Footprint Assessment of Woody Products

Forest protection is a critical component of climate policy for global, regional and local aspects (Table 3.1). The forested ecosystems, including soils, store more carbon than is currently present in the atmosphere. In many places, these important reserves of carbon are threatened by forestland conversion or degradation. Globally, about 20% of recent anthropogenic greenhouse gas emissions can be traced to deforestation, which is a larger percentage of emissions than those originating from the transportation sector. The continuing conversion of forests to other uses represents a significant climate threat that is well recognized by the public, the scientific community and policymakers (The Wilderness Society and Ingerson 2010). Forest harvesting changes the natural carbon cycle between the forest ecosystem and the atmosphere. Carbon is released during harvesting and manufacturing wood products and in disposing or incinerating wood products. Therefore, the management of forest harvesting and wood products affects atmospheric CO2 concentrations (Hashimoto et al. 2002). Wood is a renewable resource and an ‘environmentally friendly’ material (Puettmann and Wilson 2005). Moreover, wood as a building material is competitive on price in those studies that include costs (Petersen and Solberg 2005). Environmental type pressures from the public and government to reduce harvesting, and in some locations to completely quit all forestry operations, are on the rise (Puettmann and Wilson 2005). Otherwise, it is believed that harvesting and re-growing the forest are effective instruments for neutral CO2 emissions. During the harvesting process, Table 3.1 The total forest area (natural forests and forest plantations) (Bowyer et al. 2007)

Region Africa Asia Europe N. and Central America Oceania South America World total

Land area (million ha) 2978 3085 2260 2137

Area (million ha) 650 548 1039 549

% of land area 22 18 46 26

% of world’s forest? 17 14 27 14

Natural forest (million ha) 642 432 1007 532

Forest plantation (million ha) 8 116 32 18

849 1755

198 886

23 51

5 23

194 875

3 10

13,064

3870

186

100

3682

187

3.1 The Second Sustainability Level of Environmental Protection Technologies. A. . . Fig. 3.1 The carbon cycle (Global Warming 2011)

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Atmosphere Cardon Store

Fossil Fuel Photosynthesis Emissions Biosphere Diffusion Carbon Store Respiration and Biomass Decomposition Deforestation Aquatic Biomass Soil Organic Matter Ocean Limestone and Coal, Carbon Store Dolomite Oil and Gas Lithosphere Carbon Store

Marine Deposits

carbon is released. On the other hand, the same quantity of CO2 is absorbed when the forest grows. Therefore, it is called ‘carbon-neutral’. Wood is a better alternative than other materials with regard to GHG emissions. Wood causes less emissions of SO2 and generates less waste compared to alternative materials. Preservative-treated wood, on the other hand, might have toxicological impacts on human health and ecosystems. Impacts on the acidification, eutrophication and creation of photochemical ozone vary in different comparisons (Petersen and Solberg 2005). There is a clear case for wood as a positive material in green building and to help mitigate climate change (Murphy 2009). Wood used in longterm products provides the greatest reduction in fossil fuel use and emissions (Puettmann and Wilson 2005), but fossil fuels are still needed. The carbon cycle is the biogeochemical cycle by which carbon is exchanged among the biosphere, pedosphere, geosphere, hydrosphere and atmosphere of the Earth (Fig. 3.1). Carbon transport between and among reservoirs is primarily accomplished via CO2 gas exchange (Kujanpää et al. 2009). The role of forests is significant in terms of the greenhouse effect, because forests regulate CO2 concentration in the atmosphere. Earth’s atmosphere currently contains around 78% of nitrogen, 20% of oxygen and 0.038% of carbon dioxide along with the trace amounts of other gases. Millions of years ago, more CO2 in the atmosphere was extracted over a very long period of time through the growth, death and ‘fossilization’ of plants and animals forming oil, coal and gas underground. Carbon in oil, coal and natural gas is referred to as ‘fossil’ carbon. By burning these fossil fuels, we contribute to a net increase in the current atmospheric concentration of CO2 (Abbott 2008). It is approximated that living biomass (animals, plants and humans) bind as much carbon as there is free carbon in the atmosphere. Forests in their natural state are in equilibrium, they bind as much CO2 as they release through the breakdown of biomass. When trees from forests are used for producing forest products, carbon bound in trees is stored and the removed trees give room for a new forest to grow and bind new carbon. In this way, forest products are carbon storages and forest carbon sinks. However, carbon stored in the forest products is finally released into the atmosphere as CO2 from energy production or as landfill gas from the decay of

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products at landfills consisting of both CO2 and CH4. The most important industrial ecosystem feature with regard to the flow of carbon in the forest ecosystem is that the annual cuttings of forests are lower than the annual growth (Kujanpää et al. 2009). Burning wood or biomass also releases CO2. However, if more trees are planted, CO2 is then taken up again by photosynthesis as a part of the carbon cycle, and thus there is no net increase in the atmospheric concentration of CO2. Carbon in wood or biomass can be thought of as ‘non-fossil’ carbon (Abbott 2008).

3.1.2

Life Cycle Assessment

It is important to evaluate the life cycle of woody products when analysing carbon cycle in the wood use. Life cycle assessment (LCA) is one approach to accurately assess environmental burdens related to manufacturing a product from resource extraction to end-of-life (Puettmann and Wilson 2005). First, evaluating the LCA of wood products, carbon is lost at each step of the processing chain due to the physical breakdown of wood releasing carbon dioxide, methane and other by-products. Second, the transportation of wood to mills, transformation into a variety of products and delivery to customers and eventually to landfills require energy, a large proportion of which is derived from fossil fuels (The Wilderness Society and Ingerson 2010). The extraction of raw materials, production, use/maintenance and waste handling are common steps in LCA. Nevertheless, in this wood product case, forest growth and harvesting are the first steps. A comprehensive LCA for a solid wood product might begin with forest growth and harvesting trees and end with the disposal and decomposition of wood products made from those trees (Fig. 3.2). At each link in the processing chain, a portion of wood is transformed into waste. Waste wood may be incorporated into other products, burned or transferred to landfills or other waste sites where much of wood will decompose (Ingerson 2010). For the future use of the environmental value of wood products within sustainable development, the general perception of the beneficiary use of wood products has to be increased at the various stages of decision-making (Schweinle 2007). The major LCA stages of wood products are described below. • Forest growth. Pristine old-growth forests are rich in biomass while sustained yield forestry implies steady-state biomass. Forests gain biomass in many areas of temperate and boreal zones but lose the area and biomass in other parts of the world, for instance, rainforests (Kauppi et al. 2009). Carbon sequestration into tree biomass can be explained by three mechanisms including the recovery of understocked stands towards the full-stocking potential, the shift of forest stands towards older age classes along the growth curves and the shift of growth curves higher up (more favourable growth conditions). Creating new forests on the abandoned croplands and pastures can affect carbon sequestration especially in the very long term. There are three mechanisms making an impact on carbon

3.1 The Second Sustainability Level of Environmental Protection Technologies. A. . .

INPUTS

97

OUTPUTS

Forest growth (regeneration) Harvesting

Gaseus (carbon dioxide, methane, nitrogen oxides)

Wood production Sunlight

Distribution

Use by consumer

Disposal (incineration, aerobic/anaerobic decomposition)

Renovation and reuse

Energy

Recycling

Live-long products manufacturing Material

Solid waste Wastewater Heat Products

Fig. 3.2 Life cycle assessment of wood products

sequestration and understand forest management effects. The first mechanism represents the recovery of the degraded forests. The second one represents forest management decisions about harvesting levels, harvest sites, rotation ages and forest regeneration decisions. Finally, the last one mechanism represents the contribution of changes in environmental factors and the possible long-term impacts of improved forest management such as introducing into the region genetically fast-growing tree seedlings (Kauppi et al. 2009). Figure 3.3 shows carbon dependence on forest years. It can be seen that more years for the forest influence a higher quantity of carbon per hectare of the forest; for instance, if 80 years after planting passed, there are 400 tons of carbon in hectare as a consequence. Carbon absorption by trees depend on individual trees, soil condition, water supply and the length of the vegetation period. The most reliable evidence shows that a single-hectare forest absorbs about 3.8 tons of carbon, which equates to 13.82 tons of CO2 per year (Kauppi et al. 2009). Europe is characterized by a general increase in the forest area. During the last 50 years, the forest area in Western Europe has increased by almost 30%. The growth was significantly lower in Central and Eastern as well as in Southern Europe and made approximately 20% and 16%, respectively (Gold et al. 2006). • Harvesting. The treatment of harvested wood as a carbon reservoir is particularly controversial. Carbon stocks in the managed forests go up and down in response to harvesting and regrowth, but over long time periods and areas, carbon stocks are relatively stable (Miner 2009). Figure 3.4 shows the stability of carbon stock in years. Moreover, the situation of carbon storage is repeated in every 50 years. Once wood losses and fossil emissions are accounted for, the process of harvesting wood and turning it into

3 Sustainable Natural Materials and Their Importance for Waste Management and. . .

Unmanaged forests Managed forests and wood products carbon storage, plus avoided emissions

700 600 500 400

Over 60 % improved carbon impact

300 200

Carbon (tonnes/hectare)

98

100 0

20

40

60

80 120 100 Years after planting

140

160

0

Carbon stock in stand (tonnes carbon per hectare)

Fig. 3.3 The role of carbon in the forest (Green Building Material 2011)

250 200 150 100 50 0

0

50

100 150 Stand age (years)

200

Fig. 3.4 Carbon stock in stand (Murphy 2009)

products may release more greenhouse gases than the emissions saved by storing carbon in products and landfills (The Wilderness Society and Ingerson 2010). • Wood production. The logs removed from a harvest site represent approximately 60% of the volume—and hence, stored carbon—of the trees from which they came. The harvested logs may be destined for pulp, fuelwood, sawlogs or other specialized uses, but long-term carbon storage benefits come mainly from the sawlog portion. The portion of wood going to each use varies widely by the region and will also differ among harvesting operations within the region. Longterm carbon storage benefits derive mainly from the sawlog portion of the harvested volume; wood used for fuel or pulp and bark removed at the mill can be considered the sources of relatively rapid carbon losses (Ingerson 2010). Once wood destined for short-lived uses (fuel and pulp or chips) has been removed from the solid wood stream, further losses during primary processing will vary

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considerably depending on the product and the equipment used. Moreover, it was estimated wood waste losses during primary solid wood processing ranging from 26 to 58% of the raw log. A study from Finland estimated 56% losses for softwood lumber and 62% for plywood. With around 36% of the original standing tree volume available for processing into the long-lived products, primary mill losses amount to about 4–22% (average of 13%) of the standing tree volume, thus leaving approximately 23% of the original volume to be incorporated into the long-lived wood products such as lumber or panels (The Wilderness Society and Ingerson 2010). • Product manufacturing. Once wood leaves the primary mill, further processing may occur to transform the lumber or panels into the secondary products. LCA examples of furniture, flooring and window frames yield secondary processing waste estimates from 2 to 18% of the original tree volume (Ingerson 2010). Roughly 50% of forest carbon in the harvest is exported to lumber, a long-term product. The remaining 50% of carbon is exported to wood chips, sawdust, bark and shavings—all short-term products or hog fuel used for producing energy. Short-term products are assumed to decay at 10% per year (Garcia et al. 2005). Assuming that 76% of wood volume in the long-lived products is construction lumber, with the remaining 24% in furniture, cabinetry and other products, total secondary processing and construction losses might be about 5% of the original standing tree volume. If 23% of the tree remains after primary processing, this leaves about 18% of the original live tree volume actually incorporated into the long-lived products (The Wilderness Society and Ingerson 2010). The amount of carbon going into new products is more than that coming out of old products and returning to the atmosphere, thus causing some products to remain in use for long times. A growth in stored carbon represents a net removal of carbon from the atmosphere (Miner 2009). • Distribution. The average distance for transport between the harvested trees or sawn timber and sawmill could be different. Certainly, it is good when sawmill is closer to the forest from where the raw material is taken. Sawn timber to manufacturers is transported by trucks or trains; even logs can be transported by water. Therefore, distribution channels, i.e. from the forest to the station or from the goods station to the manufacturer, are necessary. Moreover, distribution is used when the final products go to shops or consumers from manufacturers. Raw materials, intermediate products and the final products—all of them are transported from one place to another. Therefore, it is also necessary to evaluate the carbon footprint of transport. Transport-related emissions were estimated to be 19.6 million tons CO2 per year (Miner 2009). • Use stage. Once processing is completed, carbon losses begin to occur as completed products or the portions of products are disposed of over time. In order to contribute to climate change mitigation, the pool of wood products must increase over time, which is best achieved by keeping products in use for extended periods. About 60% of all primary solid wood materials in the United States find their way into the long-lived products such as buildings or furniture

3 Sustainable Natural Materials and Their Importance for Waste Management and. . .

Persent of live tree carbon remaining in-use

100

1st order (Smith et al. (2006) revised) Row Phelps EFI - Europe Kurz - Canada NIES - Japan

20

15

10

5

0

0

10

20

30 40 50 60 70 80 Years after construction

90

100

Fig. 3.5 The longevity of carbon in products (Ingerson 2010)

(Ingerson 2010). Otherwise, carbon is stored in products for periods ranging from years to centuries (Miner 2009). There is considerable uncertainty about the length of time that wood products remain in use, and assumptions significantly affect the estimates of carbon remaining in year 100 (Fig. 3.5). Miner (2009) proposed that (GHG) emissions are equal to zero during the use stage. The Wilderness Society (2010) assumed that carbon density in wood products was similar to that in the live tree, so that losses in wood volume provide the rough estimates of carbon losses at each step. The synthesized data from multiple studies indicate that as little as 1% of carbon present in the standing tree may remain in solid wood products in use after 100 years. Interestingly, landfills make a much larger contribution to long-term carbon storage, thus sequestering perhaps 13% of carbon originally present in the standing tree. Wood products are treated with wood preservatives to extend their service lives in the weather exposed to the wet environment or to that subject to microbial and insect attack. Preservatives allow products that would otherwise fail within months or years to last from decades to nearly a century. A preserved wood product service life continues until the product, or the structure in which it is a part, must be replaced (Smith and Bolin 2010). In consequences, these wooden products should be treated and sorted before burning or disposal. • End-of-life. The last stage of the wood product life cycle is end-of-life disposition. Until recently, manufacturers and end users have paid little attention to this stage; however, with increasing environmental concerns and more rigorous regulation, the need for eco-friendly product importance of end-of-life stage is growing. Several models of end-of-life wooden products include renovation and reuse, recycling, incineration and aerobic/anaerobic decomposition.

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– Renovation and reuse. Residential repairs and renovations utilized 61% as much lumber, 42% as many square feet of structural panels and 60% as many square feet of non-structural panels. Renovations generate about 20% of all wood waste, more than the percentage of wood waste from new construction (The Wilderness Society and Ingerson 2010). Timber products can be repaired and maintained 100%, thus extending its useful lifetime with a positive environmental contribution. Although many preserved wood products such as combustion systems, kiln fuel or gasification are being reused for energy, the significant increased market reuse of treated wood products is possible (Smith and Bolin 2010). – Recycling. Recycling can save landfill space, but the process of recycling a given product may take more energy and adversely affect air quality more profoundly than would production from virgin resources. The focus on recycling ignores this possibility and implicitly gives more weight to solid waste and resource depletion issues than to global warming or other measures. Recycling has always been only a means to the objective of reduced flows from and to nature, but over time it has taken on the mantle of an objective in its own right (Trusty and Horst 2008). – Incineration. Much of carbon removed from the forest returns to the atmosphere quickly, for instance when wooden material burned for energy (Miner 2009). The incineration of wood products can cause higher impacts of acidification and eutrophication than other products, although thermal energy can be recovered (Werner and Richter 2007). Biomass is often considered ‘carbonneutral’ fuel, but climate impact depends upon the management of the source forest and the efficiency of use. In evaluating the potential for long-term carbon storage in harvested wood, burning must be treated like any other wood loss because it definitely accelerates the release of carbon. However, carbon losses from the source would be included as a part of processing waste (The Wilderness Society and Ingerson 2010). Moreover, some preservative chemicals could be combusted and do not need to be sorted before burning. The carbon-based preservatives such as creosote and pentachlorophenol are destroyed by combustion in appropriate combustion devices. Metals such as Cu, Cr, arsenic and boron are effectively controlled by appropriate combustion and control equipment and operating procedures. It is the appropriate matching of combustion conditions and equipment with the fuel being used, which affects emissions (Smith and Bolin 2010). – Anaerobic/aerobic decomposition. Some wooden products end up in landfills where some of carbon remains stored for long times (Miner 2009). Some carbon in landfills on anaerobic conditions is converted by bacteria into methane, a much more potent greenhouse gas than CO2 (Miner 2009). Field tests near Sydney, Australia, found that 17–18% of wood carbon had been released by 46 years after disposal (Ximenes et al. 2008). The majority of longterm off-site wood carbon storage occurs in landfills where decomposing wood gives off significant amounts of methane, a gas with high global warming potential (The Wilderness Society and Ingerson 2010). Wood carbon in

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landfills can persist for some time, as anaerobic conditions inhibit the fungi that specialize in breaking down lignin, but landfill decomposition rates vary considerably with environmental and management factors (The Wilderness Society and Ingerson 2010). Many carbon accounting schemes address only the rate at which carbon is released from decomposing products without accounting for the form in which it is released. However, the global warming potential for methane (CH4) is 25 times that of CO2. Due to anaerobic conditions, over half the carbon released from decomposing wood in landfills will be in the form of methane, or about 20% once flaring or burning for energy use, which converts CH4 to CO2 (US EPA 2007). If 23% of the mass of landfilled solid wood products eventually decomposes and 20% of carbon thus emitted is released as CH4, the global warming potential of these emissions would be approximately 60% of CO2e originally stored in discarded wood. Moreover, CH4 climate impacts, landfilled wood waste from mills, construction sites and house demolition stores make only around 13% of CO2e present in the standing tree. Including carbon remaining in wood products in use, total harvested wood CO2e at 100 years is about 14% of that present in the standing tree (The Wilderness Society and Ingerson 2010). Generally, timber products could be significantly better carbon storage places than previously thought. Until recently, it has been assumed it took about 10 years in landfill for timber and paper products to decompose and release their carbon emissions, but researches showed that timber had been in landfill for 46 years (Toyne et al. 2006).

3.1.3

The Potential for Production of Biochar from Wood Wastes

The most valuable among raw materials recommended by the EBC for biochar production is ligneous biomass. Ligneous waste potential for production of biochar consists of wood cutting waste (stumps, bark, tops, small stems and branches). Forest cutting waste consists of the tree stump part above the ground, shredded section wood, tops, branches (except for usable branches), stems of small trees, the diameter of which at the height of 1.3 m is 5 cm and less, off-cuts that appear when cutting tree stems, waste from cleaning of burning sites, wood chips, wood sawdust and repeatedly used wood (construction and demolition wood waste, used pallets and other wooden packaging, remnants of furniture and other wooden products). Feedstock for production of biochar received from forests and from energy forests can be considered sustainable, but that cannot be said about repeatedly used wood. Compared to forest wastes, used wood is drier, more calorific and denser. Usually such wood is impregnated, painted or varnished, and it contains various additives (PTE, glass, plastic, etc.); therefore, further processing of such wood is complicated. In case of thermal processing of such wood (e.g. by use of pyrolysis), emissions are

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subject to stricter requirements, special technologies for detaining contaminants are required, smoke cleaning systems are necessary. It is noteworthy that some wood wastes are considered to be hazardous wastes. Often it is wood that contains hazardous substances (e.g. non-halogenated organic wood preservatives, organochlorinated wood preservatives, organometallic wood preservatives, inorganic wood preservatives, other wood preservatives with hazardous ingredients (chromated copper arsenate (CCA); creosote)) (Commission Regulation (EC) No. 574/2004).

3.2

Is Biochar a Sustainable Natural Material?

Biochar is a product containing 50–80% of carbon and produced treating biomass in the thermochemical (e.g. pyrolysis or gasification) or hydrothermal (e.g. hydrothermal carbonation) processes. The concept of biochar became important when scientists, who studied rich Amazon soils called Terra Preta, discovered that they had over 70 more times of carbon, more nitrogen, phosphorus, potassium and calcium than the surrounding soils. It is believed that soils of considerably better quality were formed over a long period of time as people living in those places at that time fertilized soil with waste and charcoal, which, as a fertilizer, performed the functions of disinfecting waste and improving the quality of soil (Schmidt 2012a, b). Nowadays, it is aimed to approach the quality of Terra Preta soil by meliorating the soils, especially degraded ones with ‘black carbon’, which comes close to the substances called ‘biochar’. According to the definition given by the European Biochar Foundation (EBC) (EBC 2012), biochar is described as a heterogeneous material rich in aromatic carbon and minerals. It is produced through the pyrolysis from sustainably obtained biomass under the controlled conditions and with the help of environment-friendly technology. Use of biochar in soil reduces CO2 emissions and its final use would be for soil melioration. Biochar creates conditions for carbon-negative technology and can compensate for 0.25 Gt/year of carbon emitted to the atmosphere by 2030 by stabilizing the carbon in the soil. And this is only by producing biochar from biomass waste. Why is biochar carbon-negative? In view of climate change, production and use of biochar not only helps to avoid adding carbon to the atmosphere in the form of CO2, as happens when fossil fuels are burnt, or just to maintain the current level of greenhouse gas in the atmosphere, as happens during the process of burning biomass, which is ‘carbon-neutral’, it is much more. When biomass is thermally processed using pyrolysis, biomass is transformed into (bio)char. Carbon becomes more stable, emissions of pollutants into the atmosphere are lower than in the case of normal combustion, and when biochar is used to meliorate soil, it improves the quality of the soil and the soil becomes an effective reservoir of carbon due to increased carbon stability and considerable limitation of CO2 emissions caused by it. This makes the production and usage of biochar in

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agriculture a ‘carbon-negative’ technology. Carbon-stable biochar is produced by pyrolytic processing of biomass in an oxygen-limited environment. Traditional pyrolysis conditions, which maximize formation of solid biochar products, are processing biomass in an oxygen-free environment at 350–800
C (Bridgwater and Peacoke 2004). Biochar production becomes a practical waste management process using livestock waste (e.g. manure), crop waste (e.g. crop), urban area waste (e.g. green) or industrial waste (e.g. sewage sludge). The introduced sources of waste frequently ensure long-lasting waste generation, and therefore biochar production becomes economically attractive.

3.2.1

The Properties and Use of Biochar for Soil Improvement

A chemical impact of biochar is more commonly referred to as a temporary positive effect in the form of ash runoff and soil acidity (pH) modification, which promotes short-term microbial activity, including effects on fine labile particles. Positive benefits to the physical properties of the soil include modifying soil density and water retention capacity and promoting soil aggregates. These effects can be temporary or permanent. The thermal properties of the soil may also change (Ogutunde et al. 2008). Other effects are related to cation-exchange capacity (CEC), specific surface area (SSA), biological relationships (with microorganisms, fungi and plant roots) and biophysical benefits (mediate between microorganisms and microbial substrate, promote mesofauna activity, including earthworms). A potential detrimental effect on the soil is subject to the source, time and content of using biochar. A negative effect is related to nutrient leakage and the release of potentially toxic elements (metals) and organic pollutants into the soil. The places where biochar is capable of attracting nitrogen may encounter a short-term adverse effect on cereal nutrient resources, thus potentially reducing nitrogen availability to plants following exposure to biochar. Biochar exhibits the properties that enhance soil quality, assist in soil remediation and improve ecosystem services (Wingate et al. 2008). These properties cover high cation-exchange capacity (CEC), high absorption capacity, high mechanical power, high carbon productivity, high organic content, long half-life (>100 years), high water retention capacity, high nutrient retention capacity and high pesticide retention capacity. The rapid utilization of labile substrates in the soil can provide nutrient reserves for the microbial biomass of the soil, which can be employed for plant growth. The benefit of potentially labile carbon for the soil results from promoting cereal growth if the substrate is low in nitrogen and if the addition of inorganic nitrogen is limited at that time. Thus, carbon and nitrogen are needed for new biomass development and microbial competition with the roots. Nitrogen progressively evaporates during

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pyrolysis, and therefore the ratio of carbon to nitrogen in biochar is usually higher than that in the starting feedstock. On the other hand, in case biochar is very stable, it will not become rapidly available carbon substrate required by microorganisms for external nitrogen. The immobilization of nitrogen from the soil depends on the amount of biochar used, the size of labile particles and the ratio of carbon to nitrogen in the labile fraction of the biochar sample. In the context of mitigating climate changes, in situ mean residence time is over 100 years. The total content of stable and labile carbon does not reflect the overall carbon content in biochar, since it also contains the particles of moderate stability. With the exception of nitrogen, the potential nutrients of pyrolyzed biochar are retained during pyrolysis (similarly to potentially toxic elements). An increase in the removal of carbon, oxygen and hydrogen during the pyrolysis process rises the total mineral content of biochar residues, likewise in ash. The content of biochar ash increases in inverse proportion compared to carbon raw material analogous to that produced during combustion. Ash solubility can lead to the availability of minerals to plants, although phosphorus (as phosphates) is strongly bound to minerals in the soil, which may subject to the direct release of the roots or symbiotic mycorrhizal fungi. In general, providing nutrients that are readily available in cereals can promote the mineralization of organic matter, especially in the marginal environment. On the other hand, porosity and more specific pore interconnection can influence the release of soluble bio-carbon nutrients, which is more progressive than the instantaneous solubility of combustible ash. This process could be related to the mineralization of condensed resin and oil that close the pores of biochar (Fernandes et al. 2003). The natural alkalinity of biochar can boost the activity of microorganisms in the acidic soil by increasing pH, which becomes a source of organic matter decomposition and may increase plant productivity by adding carbon substrate in the process of modifying soil pH. Subject to the capability of biochar to modify soil pH, its value may be equivalent to the one-third of agricultural lime (Van Zwieten et al. 2010) and may increase soil pH by 1 unit under experimental conditions. The accelerating abiotic and biotic oxidation of carbon surface leads to a rising number of surface carboxyl groups and a growing ability to absorb cations (Cheng et al. 2008), which explains significant variations in cations in the ancient soils (Liang et al. 2006). A negative change promotes the opposite of accumulating available nitrogen (NH4+) related to N2O emissions and nitrogen leakage. A mechanism based on phosphorus and carbon dehydration has also been described for phosphorus absorption (Beaton et al. 1960), which may explain the perceptible effect of biochar on cereal phosphorus uptake by mycorrhizal fungi (Lehmann et al. 2006) (Table 3.2). Subject to particle size distribution in the soil and depending on the amount and timing of used biochar, particle size distribution and water retention capacity may be affected. The porosity of carbon varies widely, thus having an effect on the proportion of water that can be maintained and on the equivalent availability and solubility of water accumulated in the plants that can sufficiently stretch and extract content from the macropores of 0.1 to 30 μm in diameter that cannot release water naturally.

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Table 3.2 The effect of biochar on the studied properties investigated by different authors (www. fluxfarm.com/biochar.html) Factor Cation exchange capacity Effectiveness of fertilizers Alkalizing factor Soil water retention Cereal efficiency Methane emissions Emissions of nitric oxide Bulk density Mycorrhizal fungi Biological fixation of nitrogen

Effect Increase by 50% Decrease by 10–30% Increase in pH by 1 unit Increase up to 18% Increase by 20–120% Decrease by 100% Decrease by 50% Subject to the soil Increase by 40% Increase by 50–72%

Sources Glaser et al. (2002) Lehmann et al. (2006) Lehmann et al. (2006) Rondon et al. (2007) Renner (2000) Warnock et al. (2007) Lehmann et al. (2006)

The structurally solid pores of this dimension are abundant in bio-charcoal (Brodowski et al. 2006). Carbon has the capacity of adsorbing polar compounds, including many environmental pollutants (Yu et al. 2006), particularly polycyclic aromatic hydrocarbons (PAHs) deposited in the soil and sediments (Rhodes et al. 2008). The significance of using biochar for environment decontamination depends on its capacity of performing this function, much like carbon, stabilization reliability and reversal as well as the role of carbon and pollutants themselves. Provided that most of carbon in biochar is strongly stable, microbial outflow after primary mineralization and their settling in the micro-pores of biochar will depend mainly on the indirect effect of biochar to obtain the enhanced substrate. This may also occur due to the retention of soluble organic matter, which may otherwise leak into the deeper layers of the watercourse or may be affected by changes in plant root activity. Increased plant productivity should be reflected in the rising carbon deposition through the roots of the plant and in the carbonaceous growth of sediments (Major et al. 2010). Many plants may symbiotically be related to mycorrhizal fungi, the filamentous hyphae of which protrude beneath the roots of the plant and can promote both nutrient and water uptake. Although the most limiting factor is inoculum, the chemical conditions of the soil and the amount of the nutrients used are more likely to limit the proliferation of mycorrhizal fungi under most conditions. Mycorrhizal activity promoted by biochar (Rondon et al. 2007; Yamato et al. 2006) could be used for storing water and soluble nutrient supplies. Many possible mechanisms were described by Warnock et al. (2007). The amount of biochar that can be added to the soil due to beneficial properties when assessing the usefulness and potential harm of biochar can be a limiting factor in using biochar as a soil improver (Woolf 2008). There is clear evidence of the benefits of high concentrations of black carbon for certain types of the soil in the cases of terra preta and terra mulata on Amazonian dark earth that has approximately three times more soil organic matter, nitrogen and phosphorus compared to adjacent soils and therefore twice exceeding efficiency (Glaser 2007). One hectare of

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terra preta can contain 250 mg of soil organic carbon in the upper layer at a depth of 30 cm (compared to 100 mg in non-enriched soils from similar parent rock) and up to 500 mg/ha in the upper layer of 1 m. This soil organic carbon includes around 40% of black carbon (Lehmann 2007a, b), although most biochar-enriched layers comprise approximately 20% of black carbon at a depth of 40 cm (Glaser 2007). The average content of black carbon in the terra preta soil reached 25  10 mg/ha and 25  9 mg/ha at the soil depths of 0–30 cm and 30–100 cm, respectively (Glaser 2007). These values do not necessarily reflect the limit values that black carbon may have to enrich the soil. Furthermore, the source of biochar feedstock can vary greatly in its characteristics, and therefore the specific origin of such material (e.g. pH, ash content) also affects the potential amount of biochar for soil improvement. The reviewed literature documented that several studies showed positive effects of biochar on crops, and biochar content in the soil ranged from 5 to 50 t/ha. This is a wide range, but multiple concentrations are frequently used, and the investigated areas having higher levels of biochar show better results (Chan et al. 2007, 2008; Major et al. 2010). The efficiency of carbon in every type of biochar raw material varies, and therefore investigation into an appropriate amount of utilized carbon present in biochar per hectare should be a valid point. Chicken manure biochar making 10 t/ha has lower carbon efficiency (and higher ash content) than the concentration of similar utilized wood waste biochar. On the other hand, a high ash content of biochar can be a source of various nutrients required for plants and thus should be considered as soil fertility studies under field conditions.

3.2.2

Pollutants That May Be Contained in Biochar

The primary raw material and conversion are two main potential sources of pollution arising from biochar. Subject to the origin and distribution of the pyrolyzed primary raw material, biochar may contain pollutants such as PTEs or organic compounds. Some of these compounds undergo changes during the conversion process while others remain unchanged or turn into potentially harmful compounds. When some pollutants are already present in the primary raw material, others may be formed during conversion (pyrolysis). These are polycyclic aromatic hydrocarbons (PAHs) and, in some cases, dioxins. The physical forms of pyrolysis products may pose a direct risk to human health, reduce or increase the risk of the primary raw materials, compounds and crystalline substances or may result from pyrolysis. PTEs found in the primary raw materials (solid municipal waste, sewage sludge, treated wood, etc.) tend to persist and concentrate in biochar (Lievens et al. 2009; Ryu et al. 2007). Therefore, it is important to carefully select and examine the primary raw material for producing biochar in order to avoid pollution by the elevated levels of PTEs that have stable matter and thus remain retaining their related organic matter during

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Fig. 3.6 Secondary and tertiary reactions of fuel pyrolysis particles (Mašek 2007)

Dehydration

Depolymerization

Carbonization Carbon

Fuel

Soot

S Soot

Coke

H2O, CO2 Primary

Primary volatile compounds

Furans, phenols, BTX, ketones, CO, CO2, H2, H2O

Secondary

PAH, CO2, H2 CO, H2O, CH4 Tertiary

evaporation. Most PTEs will therefore be found in the form of ash in biochar itself (along with other nutrient elements such as phosphorus or potassium). PAHs can be formed from any type of the carbonating primary raw material. The main chemical conditions leading to PAH formation include high pyrolysis temperature and secondary and tertiary pyrolysis reactions (homogeneous and heterogeneous) (Fig. 3.6). The formation of the above-introduced tertiary pyrolysis products increases along with the severity of pyrolysis (temperature and exposure time) and becomes noticeable when temperature reaches 750
C. PAHs (polycyclic aromatic hydrocarbons) include benzo(a)pyrene B(a)P, benzo(a)anthracene, benzo(b)fluoranthene, benzo(j) fluoranthene, benzo(k)fluoranthene, indene(1,2,3-cd)pyrene and dibenz(a, h) anthracene.

3.2.3

European Policies and Regulations Related to Biochar

Biochar (BC) production is a cross-cutting technology addressing issues covered by several European Union (EU) policy areas such as waste management, agricultural policy, climate change and energy policy (Montanarella and Lugato 2013). At present, no EU regulation or directive expressly refers to BC (Hammond 2016). As regards the use of BC for soil amendment purposes, it is likely that the regulation of BC application to the soil could resemble soil amendment guidance relating to sewage sludge and composts (Freddo et al. 2012). The Circular Economy Package (EC 2006) listed BC, as an inorganic soil improver, among the products to be included in the annexes to the new EU fertilizer regulation that is currently under revision. These annexes are expected to set the end-of-waste criteria regarding BC adoption for soil amendment purposes. According to Meyer et al. (2017a, b), once the carbonaceous material obtained through the thermochemical treatment (e.g. pyrolysis) of waste biomass ceases to be considered waste because of achieved safety and quality levels and labelled as BC, it might be registered under the REACH directive (EC 2006). As to meeting feedstock sustainability criteria (EBC European Biochar Certificate 2015), biomass waste with minor or no use is generally selected for BC production. To this respect, BC technology is intimately linked to policy drivers such as the sustainable and smart use of resources (EC 2006) that are at the

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forefront of the European Union. High-quality biochar must meet the following criteria: • It is important to show that biochar does not contain potentially dangerous amounts of toxic substances such as potentially toxic elements (PTE) and organic molecules (dioxins/furans, polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons, BETX (benzene, ethylbenzene, toluene, xylene)). • Biochar must meet criteria for stable carbon sequestration in the soil in order the carbon cycle, subject to production and use, should restore an appropriate carbon balance. • Any quality biochar, irrespective of its class (high or standard), must contain at least 10% of organic carbon mass based on dry weight. • A ratio of hydrogen to organic carbon (H:Corg) must not exceed 0.7 in biochar.

3.3

The Stability of Chemical Elements in Biochar

From an environmental point of view, taking control over biochar parameters that pose the risk of microbiological and chemical pollution plays a significant role. One of the most important parameters of possible pollution is PTEs that can be stored in the raw material used for producing biochar. The production of biochar from a PTE-rich raw material makes the stability of metals in biochar and conditions controlling immobilization time important. The low stability of metals (i.e. high lability) may mean that the application of such type of biochar to the soil can lead to an increase in the mobility of metals. As a result, metals can enter food and feed vegetation more rapidly, migrate to deeper soil layers and reach groundwater, thereby posing risks to human health; for instance, Cu, Cr and As may enter from biochar derived from wood waste, the increased amounts of Na introduced by biochar can cause the degradation of the soil structure and decrease its fertility, a rise in the content of K in the soil can lead to a deficit of other cations (Brady and Weil 2002).

3.3.1

Sewage Sludge as a Potential Biochar Feedstock

Wastewater sewage sludge is a by-product of the wastewater treatment process and is composed of organic compounds, macro- and micronutrients, trace elements, microorganisms and micropollutants as well as industrial sewage sludge. Due the high concentration of phosphorus and nitrogen, micro and macro materials in sludge are valuable to apply into soils for the cultivation of crops (Hossain et al. 2011). Sewage sludge is a more problematic material comparing with feedstock of wood, because it is dried before pyrolysis. At the same time, sewage sludge has more advantages and can be used for soil reclamation and contribute to sewage sludge management (Lu et al. 2013). Plant-available phosphorus in sludge varying between

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25 and 40% compared to inorganic phosphorus showed that phosphorus in sludge acted as a slow release P fertilizer in deficient soils. On the other hand, phosphorus accumulation in soils through the application of sludge could have adverse environmental impacts on surface and ground water through leaching (Hossain et al. 2011). Sewage sludge as a raw material for producing biochar can reduce odours, the amount of pesticides and various organic pollutants. Sewage sludge is enriched with PTEs, pathogens and low concentration antibiotics that are of the major concern limiting its potential use as a fertilizer.

3.3.2

Industrial Sewage Sludge and Its Composition

Industrial sewage sludge from paper mill and leather production companies have the potential for a high number of contaminants. The composition of this type of industrial sludge is given in Table 3.3. The conversion of organic materials to biochar through pyrolysis supports an alternative way to manage a range of waste. The pyrolysis of sewage sludge can potentially be a method of choice for its management. This process reduces the volume of solid residues and eliminates the pathogens and organic compounds of concern present in sludge (Hossain et al. 2011).

3.3.3

The Process of Leaching Metals from Biochar Produced from Industrial Sludge

Biochar samples generated from various types of biowaste under specific conditions of the pyrolysis process involve different physical–chemical properties that will have an impact upon leaching (Lehmann and Joseph 2009). Table 3.3 The composition of industrial sludge Elements Dry solids (%) C/N ratio Water pH Heavy metals (ms/kg DM) Cadmium Chromium Copper Nickel Lead Zinc

Pulp and paper industry sludge Min Max Mean 17 65 31.60 12.5 200 77.80 45 9.4 7.30

Tannery sludge Min Max 4.10 13.21 – – 6.7 7.20

Mean 7.38 – 6.86

0.2 Zn(0.51) > Cr(0.35) > Cu(0.0196) > Pb(0.01) > Cd(0.00097). According

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to leaching from type PSB700, PTEs take the order Ni(0.84) > Cr(0.41) > Zn (0.34) > Cu(0.0239) > Pb(0.01) > Cd(0.001). For both types of the pyrogenic product, the highest leaching was observed in the case of Ni (0.84–2.02 mg/kg) while the lowest—in the case of Cd (0.0009–0.0011 mg/kg). Slightly higher amounts of PTEs were leached from the pyrogenic product produced at a lower temperature of 450
C, which could be explained by the fact that PTEs treated at 400–500
C still remained in the mobile ionic state, whereas at a temperature of 600
C elements formed stable oxides (Volungevičienė et al. 2014).

3.5

Potentially Toxic Elements and Dissolved Organic Carbon in Biochar

Biochar may contain potentially hazardous inorganic substances that may limit or prevent the utilization of biochar for environmental remediation purposes. Biochar contains carbon in labile forms that are prone to be leached as dissolved organic carbon (DOC). To avoid potential drawbacks when utilizing biochar both in the soil and water system application, it is necessary to evaluate PTEs present in biochar, the content of dissolved organic carbon and leachability. The content and the extent to which PTE and dissolved organic carbon are released from biochar limit or prevent the application of biochar for environmental management. Biochar (BC) as a filtering media has been reported to be a promising remediating tool for a variety of potential hazardous organic and inorganic substances both in the soil and water systems. Biochar used for environmental remediation (Zheng et al. 2015) purposes has received considerable attention in recent years both as filtering media (Chen et al. 2011; Baltrėnas et al. 2015a, b, c; Komkienė and Baltrėnaitė 2016) and as a soil amendment for releasing nutrients (Mukherjee and Zimmerman 2013) sequestering carbon, enhancing soil quality and sequestering a variety of PTEs (Karami et al. 2011; Park et al. 2011). As a low-cost sorbent (Ahmad et al. 2014), biochar has attracted increasing attention for applications in treating multi-elementpolluted water such as landfill leachate (Chemerys and Baltrėnaitė 2017) and urban stormwater runoff (USWR) (Beck et al. 2011; Reddy et al. 2014; Tian et al. 2014; Shimabuku et al. 2016; Kuoppamäki et al. 2016). Biochar from slow pyrolysis encompasses BC produced in the range of 350–1000
C within the low oxygen thermal process (EBC European Biochar Certificate 2015) characterized by a low heating rate (up to 100
C/s) and a residence time of hours (Spokas et al. 2011a, b). PTEs in a water-soluble form may represent an environmental issue when they are bioavailable or mobilize through the soil or water media. In water systems, DOC interacts with dissolved PTEs affecting their mobility and bioavailability through the formation of DOC–PTE complexes. As regards environmental risk caused by PTE species within biochar, the safe level of BC application to the soil depends on the PTE content of biomass feedstock and pyrolysis conditions (McHenry 2009; Shackley et al. 2010). PTEs such as Cd and Pb are nonessential elements having

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no definite biological function in the organism and plant (Bolan et al. 2013). Therefore, introducing the trace amount of bioavailable Cd and Pb in the soil through biochar land application is highly undesirable (Wu et al. 2016a, b). BC-borne DOC may represent a source of the impairment of the aquatic environment containing organic species producing an inhibitory effect on the growth of aquatic microorganisms (Smith et al. 2012), increasing PTE mobility through complexation and altering redox reactions and the speciation of PTEs (Qu et al. 2016). Uchimiya et al. (2012) observed that DOC released by biochar in the temperature ranging from 350
C to 500
C was enriched with carboxyl and poly(phenolic) functionalities that were able to affect PTE mobilization via complexation with PTE ions. The formation of DOC-PTE complexes competing with the adsorption capacity of biochar (Iqbal et al. 2015) and fouling of the biochar surface (Ulrich et al. 2015) have been reported as potential negative effect of DOC on biochar effectiveness of filtering polluted water. Furthermore, DOC may reduce biochar effectiveness in carbon sequestration (Wu et al. 2011; Liu et al. 2016). Having lower aromaticity and less fused aromatic structures than bulk biochar, DOC is expected to have lower environmental recalcitrance (Qu et al. 2016). Regarding the recalcitrance of BC-borne DOC in water media (i.e. river water), Norwood et al. (2013) reported a half-life of 30–40 days for DOC from biochar at a temperature of 250
C. Biochar may be subject to postproduction treatment (e.g. rinsing) to limit the release of DOC (Ngueleu et al. 2014). Hence, to limit the content of DOC in biochar, Smith et al. (2016) suggested to adopt pyrolysis temperatures above 400
C. However, the environmental implications of biochar-derived DOC were not properly elucidated, and therefore further studies are on demand (Luo et al. 2015). A large variety of feedstock types has been utilized for biochar production (Aller 2016). Both pristine feedstock (e.g. forestry residue) produced in large quantities with minor or no use and potentially contaminated feedstock (e.g. phytoremediation biomass, wood processing waste, and sewage sludge) are of particular interest to meet sustainability criteria and add value to biochar production. Biochar from wood chips (BCWC), sewage sludge (BCSS) and lignin (BCLG) waste was produced and studied for PTE and DOC leaching behaviour. Lithuania produces approximately 2.5 million m3 of forest cutting waste per year for potential use in biochar production (Baltrėnaitė et al. 2016a, b, c, d). Lignin is a massive by-product of biorefinery industries (Li et al. 2014). Biochar produced from lignin at a moderate temperature is seldom reported even though lignin is used for producing activated carbon through the pyrolysis process (Li et al. 2014).

3.5.1

The Leachability of PTEs from Biochar

The results of the up-flow percolation test are reported as the cumulative released quantity of PTEs detected in the eluate at each cumulative liquid-to-solid (L/S) ratio and expressed as a percentage of the respective total PTE concentration detected in biochar.

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With respect to the PTEs analysed in the eluate collected from BCWC and BCLG, leaching behaviour varied depending on the element. Irrespective of pyrolysis temperature, at the final L/S ratio, Cu was retained in the range of 92–99% in BCWC and BCLG. Low leached amounts of PTEs such as Cu and Zn may be related to pH values in the alkaline range measured in the eluates collected at L/S ratios equal to 1, 3 and 5 from BCLG and BCWC. Mellbo et al. (2008) performed an up-flow percolation test on wood ash and found no leaching of Cu and Zn. The authors suggested that a high pH value (8.8–12.4) of the eluates was responsible for hindering the release of Cu and Zn. Leaching behaviour of Cd in BCLG and BCWC varied with the temperature. At the final L/S ratio, BCWC450 and BCLG450 retained more than 99% of the respective total Cd concentration, whereas around 20% and 40% of the total Cd concentration were retained in BCWC700 and BCLG700, respectively. Irrespective of pyrolysis temperature, at the final L/S ratio, more than 96% of Pb was retained in BCLG (Fig. 3.16). Conversely, Pb was calculated to be approximately four times more likely to be released from BCWC700 compared to BCWC450 (Mancinelli 2018). At the final L/S ratio, all analysed PTEs were mostly retained in BCSS, irrespective of the temperature adopted for pyrolysis treatment. PTEs retained in BCSS450 were in the range of 95.25–99.96% and BCSS700—in the range of 95.94–99.98%. BCDSS450 exhibited a relatively higher tendency to releasing PTEs such as Cd (about nine times), Pb and Zn (about two times) compared to BCSS700. Roberts et al. (2017) reported negligible risks for Cd, Cu and Zn when leaching biochar from biosolids at high temperatures of pyrolysis (i.e. >600
C) (Mancinelli 2018). In order to avoid potential drawbacks in biochar water application (e.g. filtering media) resulting from leaching potentially harmful PTEs, the results of the up-flow percolation test were compared to the annual average maximum allowable concentrations (AAMACs) for the environment provided by Order No D1–236 on Wastewater Management Regulation issued by the Minister of the Environment of Lithuania on 17 May 2006. There was no risk of leaching for Cd, Cr, Cu, Pb and

140 BCWC450 BCWC700 BCLG450 BCLG700

120 100 DOC, mg/l

Fig. 3.16 The mean values of dissolved organic carbon (DOC) of biochar eluates collected at various liquidto-solid (L/S) ratios. The values are shown as the mean of two observations (n ¼ 2), (DW for is dry weight) (Mancinelli 2018)

80 60 40 20 0

1

2 L/S, l/kg DW

3

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3 Sustainable Natural Materials and Their Importance for Waste Management and. . .

Zn from all types of biochar as their cumulative released quantities were under AA-MACs for the environment. The upper limit of the cumulative released concentration of Ni calculated for BCLG and BCSS equals to AA-MACs for the environment. Therefore, only BCWC can be considered suitable for water application with no concern for introducing the excessive amounts of PTEs in surface water.

3.5.2

Leaching Dissolved Organic Carbon from Biochar

Figure 3.16 shows that DOC concentrations determined in the eluates collected at various L/S ratios in the up-flow percolation test on BCWC and BCLG utilized deionized water as a leachant. Irrespective of the temperature adopted for pyrolysis treatment, BCWC and BCLG showed a similar release trend characterized by a significant decrease in DOC concentrations of the eluates collected at increasing L/S ratios. An increase in the L/S ratio from 1 to 3 L/kg of d.w. produced the highest decrease in DOC concentrations of the eluates collected from BCLG700 (50%) and BCWC450 (49%) following by BCLG450 (30%) and BCWC700 (21%). A further increase in the L/S ratio from 3 to 5 L/kg of d.w. showed a substantial decrease (71%) in the DOC concentration of the eluate collected from BCLG450, followed by BCWC700 (49%), BCWC450 (18%) and BCLG700 with the slightest decrease of 1%. In the works by Beesley and Marmiroli (2011) and Iqbal et al. (2015), DOC was observed to be rapidly released from biochar with no substantial amount of DOC recorded after a few eluate samples. Low temperature (450
C) BCLG and BCWC significantly released greater amounts of DOC compared with the respective high temperature (700
C) BC. A decrease in DOC content with an increase in pyrolysis temperature was reported in the previous study on biochar leaching trends by Mukherjee and Zimmerman (2013). In order to analyse the fraction of carbon released from biochar, DOC content present in biochar was expressed as a percentage of respective TC content (Table 3.10). The calculated cumulative released quantity of DOC at the cumulative Table 3.10 The content dissolved organic carbon (DOC) in biochar from wood chips and lignin determined via the up-flow percolation test expressed as a percentage of respective total carbon (TC) content (Mancinelli 2018)

BCWC450 BCWC700 BCLG450 BCLG700

Amount of DOC as a % of TC L1/S L2/S L3/S 0.02 0.03 0.04 0.01 0.03 0.03 0.01 0.03 0.01 0.00 0.01 0.01

Cumulative amount of DOC as a % of TC ΣLi/S 0.09 0.07 0.06 0.02

DW dry weight, Li/S—liquid-to-solid (L/S) ratio equal to 1, 3, and 5 1/kg DW for i equal to 1, 2, and 3, respectively. ΣLi/S—cumulative L/S ratio. Values are shown as the mean value (n ¼ 2)

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L/S ratio of 9 L/kg of d.w. was highest for BCWC450 (0.09% of TC content) and was followed by BCWC700 (0.07% of TC content), BCLG450 (0.06% of TC content) and BCLG700 (0.02% of TC content) (Table 3.10). As regards the temperature-related trend towards the cumulative released quantity of DOC expressed as a percentage of respective TC content, with an increase in pyrolysis temperature, BCWC and BCLG showed a decrease in around 22% and 67%, respectively. For both pyrolysis temperatures, BCWC exhibited a higher tendency to release DOC compared with BCLG. The cumulative released quantity of DOC of BCWC expressed as a percentage of TC content was 1.5 times higher at a temperature of 450
C and 3.5 times higher at a temperature of 700
C than the respective quantity of DOC calculated for BCLG. In the work by Li et al. (2014), biochar from wood and lignin pyrolyzed at the temperatures of 400 and 600
C had different surface properties concerning biochar from wood exhibiting a higher micropore structure (specific surface area, micropore area and volume) compared with biochar from lignin at both temperatures of pyrolysis. The closed or blocked pores that were formed in biochar during pyrolysis open due to swelling biochar in water (Ahmad et al. 2014). Therefore, organic matter entrapped in the char matrix may become more accessible to leaching. It is likely that the leaching condition applied in the up-flow percolation test enhanced swelling BCWC in water, thus resulting in more DOC as a percentage of TC released with increasing L/S ratios compared with BCLG. DOC concentrations (mg/L) measured in the eluates from biochar of pine bark (BCPB) showed significant differences for pyrolysis temperatures and the types of the leachant. For all BCPB, leaching tests on roof USWR showed higher concentrations of DOC (mg/L) compared to those on pathway USWR (Fig. 3.17). An increase in L/S ratios in the range of 0.5–5 L/kg of d.w. produced the highest decrease in DOC concentrations in the eluates collected from leaching tests on pathway USWR with BCPB700 (78%) and BCPB300 (77%). For both types of the leachant, a steady trend was observed for DOC concentrations in the eluates from BCPB450 with the values varying fairly tightly for L/S ratios in the range of 0.5–5 L/ kg of d.w. The up-flow percolation test on roof USWR, at the final cumulative volume of the eluate (i.e. ΣLi/S equal to 11.5) BCPB produced at higher temperature released lower cumulative quantities of DOC expressed as a percentage of the respective TC content. For the up-flow percolation test utilizing pathway USWR as the leachant, at the final cumulative volume of the eluate, the calculated cumulative released quantities of DOC expressed as a percentage of respective TC content were in the order of PB > BCPB700  BCPB450  BCPB300, which was in contrast with the results reported by Liu et al. (2015a) and Mukherjee and Zimmerman (2013). The authors observed a decrease in DOC quantities released by biochar with an increase in pyrolysis temperature (Table 3.11). Differences in the DOC leaching behaviour of BCPB observed for pyrolysis temperatures and the types of the leachant may be explained by variations in pH and DOC concentration of two types of the leachant. According to Jones et al. 2011, DOC is released at first from the surface and later from the BC matrix following a diffusion-limited mechanism. It is likely that the

3 Sustainable Natural Materials and Their Importance for Waste Management and. . . Pathway USWR eluate

Roof USWR eluate

100 DOC, mg/l

Fig. 3.17 The mean values of dissolved organic carbon (DOC) released by pine bark (PB) (a) and biochar (BC) from PB at the temperatures of 300
C (b), 450
C (c) and 700
C (d) in the eluates collected at various liquid-to-solid (L/S) ratios from roof and pathway urban stormwater runoff (USWR) up-flow percolation tests. DW is for dry weight. The values are shown as the mean of two observations (n ¼ 2) (Mancinelli 2018)

50

0

0.5 1.0

3.0

2.0

5.0

L/S, l/kg DW a) 30 DOC, mg/l

140

20 10 0

0.5 1.0

2.0

3.0 L/S, l/kg DW

5.0

b) DOC, mg/l

30 20 10 0

0.5 1.0

2.0

3.0 L/S, l/kg DW c)

5.0

0.5 1.0

2.0

3.0 L/S, l/kg DW d)

5.0

DOC, mg/l

30 20 10 0

leachant having lower DOC concentration (i.e. roof USWR) leads BCPB to release higher quantities of DOC from the BC matrix. Hence, DOC concentrations (mg/L) were highest in the eluate from BCPB after roof USWR up-flow tests compared to those measured in the respective eluates from pathway USWR up-flow tests. Furthermore, the leachant with relatively higher pH and DOC concentration (i.e. pathway USWR) may have limited the release of DOC from the BC matrix (Table 3.11). Hence, a similar cumulative released quantity of DOC expressed as a

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141

Table 3.11 Dissolved organic carbon (DOC) content in pine bark (PB) and biochar from PB determined via the up-flow percolation test on urban stormwater runoff (USWR) expressed as a percentage of respective total carbon (TC) content (Mancinelli 2018)

Leachant Pathway USWR

Roof USWR

Material PB BCPB300 BCPB450 BCPB700 PB BCPB300 BCPB450 BCPB700

Amount of DOC as a % of TC L1/S L2/S L3/S L4/S L5/S 0.01 0.01 0.01 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.01 0.02 0.02 0.00 0.00 0.01 0.01 0.01 0.00 0.00 0.01 0.01 0.01 0.00 0.00 0.00 0.01 0.01

Cumulative amount of DOC as a % of TC ΣLi/S 0.04 0.01 0.01 0.01 0.07 0.03 0.03 0.02

Value are shown as the mean value, (n ¼ 2). Li/S—liquid-to-solid (L/S) ratio equal to 0.5, 1, 2, 3, and 5 1/kg day weight for i equal to 1, 2, 3, 4, and 5 respectively. ΣLi/S—cumulative L/S ratio

percentage of TC content was calculated for BCPB in the pathway USWR up-flow percolation test. For the eluates collected from BCPB700, positive linear correlations were observed for DOC concentrations (mg/L) plotted against EC (r2 ¼ 0.99) and pH (r2 ¼ 0.88) values of the eluates collected from up-flow percolation test on pathway USWR. The blocked pores that were formed in biochar during pyrolysis became accessible due to the dissolution of inorganic salts coating the surface of biochar (Spokas et al. 2014), thus increasing accessibility to leaching the portion of DOC carried on the surface of biochar (Jones et al. 2011). Furthermore, the portion of DOC carried on the surface of biochar is more susceptible to leaching with an increase in the pH of the leachant (Li et al. 2017).

Chapter 4

Sustainable Natural Materials Used for Adsorbing Pollutants from the Aqueous Medium

This chapter continues a discussion on the second sustainability level of environmental protection technologies and focuses on the use of natural materials for removing pollutants (for example, potentially toxic elements) from the aqueous media. This chapter describes PTEs found in waters and the use of biochar as a sustainable material for removing them. This part of the book looks into the adsorptive capacity of biochar and the effectiveness of contaminant removal subject to its type and the characteristics of the adsorbable material. Moreover, the influence of biochar composition as an adsorbent on its capacity is analysed with respect to syngenetic elements.

4.1

Potentially Toxic Elements in the Aquatic Environment

According to the World Health Organization, 2.1 billion people live without safe water at home. Polluted water can transmit diseases such as diarrhoea, cholera, dysentery, typhoid and polio. Contaminated drinking water is estimated to cause 502,000 diarrheal deaths each year. At least 10% of the world’s population has been documented to consume food irrigated by wastewater that usually contains contaminants such as potentially toxic elements (PTEs) (e.g. Cu is a typical PTE in wastewater, Shen 2019) and organic contaminants (WHO (World Health Organization) 2017). Both natural (soil erosion, urban runoff, aerosols and particulates) and anthropogenic (metal finishing and electroplating processes, mining extraction operations, textile industries and nuclear power; Zeng et al. 2018; Oluwatuyi et al. 2019) sources of PTEs entering waterbodies are driven by intensive technogenesis and the increased consumption of society. The need for environmentally friendly biotechnologies for removing organic and inorganic water pollutants was investigated (Rene et al. 2018) with the focus on the sustainably produced adsorbents for eliminating pollutants from water (Begum et al. 2018; Feng et al. 2018; Rai et al. 2018). © Springer Nature Switzerland AG 2020 P. Baltrėnas, E. Baltrėnaitė, Sustainable Environmental Protection Technologies, https://doi.org/10.1007/978-3-030-47725-7_4

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4 Sustainable Natural Materials Used for Adsorbing Pollutants from the Aqueous. . .

Table 4.1 The types of effects relevant to pollution from surface runoff (Hvitved-Jacobsen et al. 2009) Effect Physical habitat changes

Dissolved oxygen depletion Eutrophication Toxic pollutant impacts Public health risks Aesthetic deterioration and public perception

Subdivision and comments 1. Flooding in urban and rural areas 2. Erosion caused by overland flow and peak flows in channels and rivers 3. Sediment deposition in receiving waters Effects on the biological communities Effects of both nutrients (N and P) and organic matter as substrates for excessive biological growth and activity Effects of both heavy metals and organic micropollutants 1. Direct impacts by pathogenic microorganisms and viruses 2. Indirect impacts via contaminated animal food For example, caused by the discharge of gross solids and sediments

With an increase in gross domestic product (GDP) and human population by around 225% and 72%, respectively, since 1994, the world extraction of PTEs increased by over 75%. As a result, the emissions of PTEs to the biosphere, including waterways, have increased by a factor of 1.5–3 since 1983. The stocks and flows of the global cycles of Ag, Al, Cr, Co, Fe, Ni, Pb and Zn will have comprised over 98% of the total mass of PTEs mobilized by human activities at the turn of the twenty-first century (Rauch and Pacyna 2009). The following groups such as biodegradable organic matter, nutrients, potentially toxic elements, organic micropollutants, solids (suspended solids) and pathogenic microorganisms are typical of and relevant to a number of corresponding potential effects (Hvitved-Jacobsen et al. 2009). These pollutants may cause different outcomes. In addition to the effects related to these pollutants, hydraulic conditions also make an impact on the environment. The combined effects of both pollutants and water flow can be organized as provided in Table 4.1.

4.1.1

Potentially Toxic Elements in Surface Runoff

Potentially toxic elements in the surface runoff represent a serious environmental problem because of potential toxicity to biota and human. The concentrations of potentially toxic elements in surface runoff represents a major concern due to their impact in terms of their acute and chronic effects onto the aquatic environment (Cordey 1977; Wanielista et al. 1977). Recently, there has been an increase in the public awareness of the hazards posed by contaminating the environment by potentially toxic elements, the concentrations of which in the atmosphere and atmospheric deposition have risen due to a growth in the anthropogenic impact on the environment. The contamination of the aquatic environment with potentially toxic elements leads to toxic effects and is accepted as a worldwide problem, especially in the

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countries with a long industrial history. During rainstorms and other precipitation events, urban stormwater runoff collects a wide range of potentially toxic elements affecting the quality of surface, seepage and ground water. Significant loads of potentially toxic elements are detected in urban surface runoff (Davis et al. 2001). Potentially toxic elements and sediments are among the pollutants commonly found in urban stormwater. Sediments can represent a source of potentially toxic elements, thus increasing pollutant concentrations in waters (e.g. 20% for Cd, 30% for Cu and 10% for Zn). As for potentially toxic elements typically found in surface runoff, Cu, Cd, Pb and Zn are of the major concern (Weiss et al. 2006). According to Gnecco et al. (2008), the dominant species of dissolved PTEs are the ionic form and organic and inorganic complexes. Dissolved PTEs are most toxic due to enhanced bioavailability and potential not to degrade in the environment. Therefore, surface runoff must be considered as a source of polluted water bodies from which pollutants should be removed before discharging them into the water stream. In terms of both environmental effects and the choice of an appropriate control methodology, it is important to note that the variability of the pollutant load occurs in surface runoff in different ways: • Within an event. It is observed that the highest concentrations or the largest quantity of pollutants transported will occur during the initial period of a runoff event compared with the later stages of the same event. This phenomenon is defined as ‘first flush’ or sometimes ‘first foul flush’ and can be quantified based on the development of the cumulated relative flow and relative pollutant mass transport during the runoff event. It occurs because the accumulated pollutants related to particles are subject to erosion and resuspension followed by their transport in the water phase. The relative impervious catchment area, the length of the dry weather period, the duration of the rain event and the relative distribution of intensity during the event are the major factors that affect the magnitude of the first flush. • Between events at a specific site. The stochastic nature of runoff events, including pollutant build-up in drainage systems, affects the amount of pollutants, is available for transport and implies that both pollutant load and pollutant concentrations may vary between runoff events at the specific site. • Between sites. Each site has specific characteristics in terms of urban runoff that concerns climate conditions, including the rainfall pattern, the type of infrastructure and technology applied. Human behaviour and activities determine dominating pollutants and to what extent they will turn up in urban runoff. A rather significant variability exists and is of the same order of magnitude as variability between the events at the specific site (Hvitved-Jacobsen et al. 2009). In the aquatic environment, PTEs can be found in the dissolved form, particulatebound form, suspended form, colloidal form and volatile fractions of particulates. The chemical properties of PTEs play an important role in their transport mechanism. As for the aquatic environment, the major processes driving geochemical interactions include precipitation, dissolution, adsorption and desorption, ion

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4 Sustainable Natural Materials Used for Adsorbing Pollutants from the Aqueous. . .

exchange, oxidation and reduction (redox) and complexation. The speciation process (i.e. partitioning PTEs between the aqueous and solid phases) is a result of sorption or ion exchange processes and plays a major role in determining the bioavailability of PTEs in the environment. The aqueous speciation or complexation of PTEs affect their toxicity and bioavailability waters.

4.1.2

Factors Affecting the Load and Transport of Potentially Toxic Elements in Surface Runoff of Urban Areas

Different factors affect pollutant load and transport in stormwater runoff, thus influencing toxicity levels during and after a storm event. For example, the accumulation of contaminants on the surfaces depends on the extension of the dry period prior to a storm event and atmospheric deposition; the velocity of the transported contaminants is affected by storm intensity and the presence or absence of impervious surfaces. The parameters such as rainfall intensity and volume are important factors in influencing the mobility of PTEs in the urban area (Sonzogni et al. 1980). Lamprea and Ruban (2008) provides that the highest concentrations measured for suspended solids and PTEs (Cd, Cr, Cu, Ni, Pb and Zn) at the outlet of the surface runoff system were detected when a long antecedent dry period occurred before rain events (Mancinelli et al. 2016). Urban areas are responsible for local and remote pollution. A significant amount of dry and wet deposition occurs locally, thus contributing to the contamination of urban runoff and taking part in the urban cycle of metals, and subsequently in the contamination of receiving water basins. Activities such as transportation, waste incineration and some industries can be responsible for remote pollution because of the emitted fine particles transported over long distances. Regarding the chemical analysis of surface runoff in Vilnius city, Milukaitė et al. (2010) detected a wide range of the concentrations of both suspended solids and PTEs such as Cd, Cu, Pb and Zn. The bulk deposition analysis of pollutants both in the solid and liquid forms showed that all PTEs were predominant in the insoluble form: Cu and Zn made up to 70% of the total amount measured and Pb and Cd up to 90%. Milukaitė et al. (2008) observed a close relationship between the investigated PTEs and the concentrations of Pb and oil products suggesting that traffic represented the major source of pollution that could affect the chemical composition of atmospheric deposition. According to Valiulis et al. (2002), in the last decade of the twentieth century, the registered ever-growing air pollution in Vilnius city had to be related to an increase in the number of cars as well as to the average age and flow management of cars. Milukaitė et al. (2008) presented the analysis of PTEs such as Pb, Cd, Cu and Zn in bulk deposition over 1 year in two sites in the centre of Vilnius (Lithuania), i.e. a residential area and a street with high traffic intensity and a rural site located on the cost of the Baltic Sea. Lower differences between fluxes in the residential area and the street zone were determined for Cd and Zn. The amount of PTEs accumulated on the ground surface of the residential site of the city were presented in a decreasing

4.1 Potentially Toxic Elements in the Aquatic Environment

147

order of mass as follows: Zn > Cu > Pb > Cd. The concentrations of the majority of pollutants in atmospheric deposition were up to 8 times higher at the residential site of the city, and the order of magnitude was higher in the street with intensive traffic than that determined at the urban site. The average pH of precipitation was 4.8
0.30 at the rural site and 6.8
0.40 in the city. The recorded average value of pH suggested that the high pollution of rain and snow melt water in the city by alkaline leaching admixture could influence the form and mobility of PTEs in the environment. Zn and Cu showed the biggest difference between cumulative deposition at the urban and rural sites and made, respectively, 2.4 and 4.7 times higher than that at the rural site; a similar level of flux was determined for Pb only. A large amount of PTEs such as Zn and Cu depositing on the surface of the city can represent a major concern to the wastewater balance (Mancinelli et al. 2016).

4.1.3

Different Surfaces

Wet atmospheric deposits are subject to strong evolution due to transport and runoff on different urban surfaces. Regarding xenobiotics detected in surface runoff, the distribution and concentration of pollutants is surface-dependent in runoff water. Urban surfaces modify very significantly the distribution of particulate PTE. The similar distribution and concentration of PTEs can be noticed in roof runoff and rainwater. Regarding the presence of PTEs in roof runoff, roof covering or gutters and down pipes produced of metal materials such as Cu, Pb and Zn can release PTEs because of corrosion. That is to be related to the pH value of rainwater and the age of materials (i.e. new roof surfaces can act as pollution sink until maximal load capacity is reached) (Göbel et al. 2007). The analysis and comparison of roof runoff from bitumen flat, tile, zinc sheets and slates showed no significant difference in Ni, Cr, Cu and Cd whereas the concentrations of Pb and Zn were found to be highly variable. Roof runoff was found to be a large source of Zn, Cd and Pb while bulk atmospheric deposition was characterized by the high concentrations of Ni, Cr and Cu. This was explained by leaching Pb added to PVC gutters and the erosion of Zn used as a roofing material (Lamprea and Ruban 2008). A comparison of the loads of PTEs in bulk atmospheric deposition with the ones in roof runoff inferred that Ni, Cr and Cu were found in roof runoff mainly because of the contribution of bulk atmospheric deposition whereas the concentrations of Cd, Pb and Zn in roof runoff were due to leaching from roofs (Lamprea and Ruban 2008). In road runoff water, inorganic substances such as K, Ca and Mg are also found (Hvitved-Jacobsen and Yousef 1991). In addition, PTEs such as Pb, Cd, Cr, Cu and Ni can be detected in traffic affected runoff (Lord 1978; Golwer and Schneider 1982, 1983; Muschack 1989; Gath et al. 1990; Innacker and Malessa 1991; Berbee et al. 1999; Dierkes and Geiger 1999; Baun et al. 2001). The sources of pollution caused by Cr, Cu, Ni, Pb and Zn in road runoff include tyre and brake pad abrasion, gases and aerosol produced by engine combustion (Göbel et al. 2007). Garnaud et al. (1999) presented a comparison of the distribution of PTEs in rainwater and urban runoff and showed that suspended solids, pH and PTEs

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4 Sustainable Natural Materials Used for Adsorbing Pollutants from the Aqueous. . .

particulate fractions severely increased in runoff. In the samples of the yard, street and catchment outlet, Cd and Zn were mainly adsorbed by particulates, whereas mostly dissolved in rain samples; as for roof runoff samples, Cd and Zn were dissolved.

4.1.4

The Influence of Storm Parameters on the Concentrations of Potentially Toxic Elements

Parameters such as rainfall intensity and rainfall volume are important factors that influence washing potentially toxic elements off impervious surfaces (Sonzogni et al. 1980). Westerlund and Viklander (2006) provided that different sizes of particles were transported at different times during a high flow, whereas a lower flow transported particles at the same time. Milukaitė et al. (2010) analysed surface runoff samples taken from the drainage system with direct discharge into the Neris River (Vilnius, Lithuania) and disclosed that the concentrations of suspended solids and the insoluble form of Cd, Cu, Pb and Zn in water runoff samples increased with a rise in rainfall intensity (Table 4.2). In the case of stormwater, the mobilization of substances is not constant and sometimes exhibit first-flush behaviour (i.e. the concentrated discharge of pollutants into waterways due to washing down the dry atmospheric deposition off impervious surfaces). In the first flush, the chemical parameters of water such as pH and EC increase in the first 2 mm of stormwater and then decrease (Göbel et al. 2007). An example of typical first-flush behaviour is PTEs coming from traffic activities (Kern et al. 1992; Sansalone and Buchberger 1997; Göbel et al. 2007). Regarding the wash off behaviour of PTEs from asphalt and concrete roads, different PTEs show different behaviour. For instance, Zn shows generally higher dissolved parts in runoff than Pb. According to Kern et al. (1992), since the dissolved part of PTEs mainly originates in stormwater, their concentrations are stable during runoff. The dissolved part of runoff is low compared to the particulate fraction only after short dry weather periods. Table 4.2 The dependence of the concentrations of potentially toxic elements and suspended solids on rainfall intensity

Sample A B C D E F

Rainfall intensity [mm/h] 0.6 3.4 4.8 5.9 6.7 10.2

Cd [μg/L] 4.80 10.4 17.5 12.5 8.33 13.1

Adapted from Milukaitė et al. (2010)

Pb

Cu

Zn

19.0 32.7 58.5 46.8 68.3 64.1

12.6 35.1 70.2 55.6 64.7 66.1

37.5 49.6 134 367 188 272

Suspended solids [mg/L] 0.17 1.45 2.25 1.66 3.64 3.22

Antecedent dry days 2 1 4 8 2 3

4.2 Adsorption and Desorption Processes of PTEs in the Aquatic Environment

4.1.5

149

The Seasonality of the Concentrations of Potentially Toxic Elements

Milukaitė et al. (2008) provided the analysis of atmospheric deposition in Vilnius city compared to the rural site and found no clear seasonal trends both at the urban and rural site. A fact that only Cd showed higher fluxes at the city residential site during summertime was inferred to the presence of soil particles in the deposition sampler because of a more intensive mixture of the atmosphere during that season. In many countries with a cold climate, salt (in the form of NaCl) or anti-skid materials (e.g. sand) are displaced on roads in order to avoid ice and slippery road conditions. Deicing salts can affect water quality increasing TDS and contributing to the mobilization of PTEs by the processes such as ion exchange, desorption, complexing, acidification and mineral dissolution (Amrhein and Strong 1990; Shanley 1994; Granato et al. 1995). Westerlund and Viklander (2006) provided that the concentration, load, transportation and relation to the PTEs of particles in different size fractions were noticed to differ strongly comparing snowmelt- and rainfall-induced runoff that could collect large amounts of fine particles, salt and PTEs; the snowmelt level of PTEs can be by several orders of magnitude higher than that of rainfall runoff (Sansalone and Buchberger 1997).

4.2

Adsorption and Desorption Processes of PTEs in the Aquatic Environment

According to Drever (1997) and Bricker (1999), a sorption mechanism is one of the most important chemical processes that affect the movement and behaviour of PTEs in the aquatic environment. As a result of the sorption of PTEs onto particulate matter (e.g. organic matter or iron and manganese oxyhydroxides), the concentrations detected in natural waters are lower than would be expected from mineral solubility calculations. In the aqueous solution, adsorption occurs at the interface of solids; depending on the characteristics of the surface and the sorbed ion, the forces acting in the process may range from weak to very strong. According to Alloway and Ayres (1997) and Sandroni et al. (2003), many factors like PTE properties such as valence, radius, a degree of hydration and co-ordination with oxygen, physicochemical environment, the nature of the adsorbent, other existing PTEs and their concentrations and the presence of soluble ligands in the surrounding fluids can influence the degree to which PTEs are adsorbed. If chemical conditions change in receiving waters and soils or if organic matter is decomposed, PTE adsorbed on inorganics or organic particulate matter can be released to the aqueous solution (Bricker 1999).

150

4.2.1

4 Sustainable Natural Materials Used for Adsorbing Pollutants from the Aqueous. . .

Adsorption Mechanisms

When the composition of the electrolyte solution in which solids are present changes, ions bounded to solids are replaced by other ions (Bricker 1998). Solids such as zeolites, clay minerals, oxyhydroxides, colloids and natural organic compounds can exhibit this kind of behaviour. The presence of exchangeable ions can determine the composition of water (e.g. areas where road salt is applied for deicing purposes (Shanley 1994; Granato et al. 1995; Bricker 1998)). Oxidation and reduction are simultaneous reactions consisting of the transfer of electrons. In the environment, a number of elements (e.g. O, H, C, Mn) can exist in more than one oxidation state. The redox state of minor elements is important because it affects their chemical and biological behaviour, toxicity and mobility in the environment. The redox reaction can be represented as half reactions, and the whole reaction can be obtained combining them. The form of the reduction reaction can be written as follows (Eq. 4.1): aA þ bB þ e ¼ cC þ dD

ð4:1Þ

and the half reaction for oxidation can be expressed as Eq. 4.2: fF þ gG ¼ hH þ iI þ e

ð4:2Þ

where A, B, H, and I stand for the species of oxides, C, D, F and G are reduced species and e1 is the number of transferred electrons (Eq. 4.3). aA þ bB þ fF þ gG ¼ cC þ dD þ hH þ iI

ð4:3Þ

According to Langmuir (1997), the majority of PTEs and many major elements can be found in their complexed forms in natural systems. As a result of the complexation process due to the interaction between DOC and PTEs, the majority of those can be found in the dissolved phase (Herngren et al. 2005). In the presence of a complexing agent, a much larger amount of an element can solubilize and be transported than would be expected considering only its solubility constant. Regarding the toxicity of an element, its speciation in the solution can be more important than its total concentration. For example, at the same concentrations of total PTEs such as Cu, Pb and Cd, the uncomplexed ionic forms are much more toxic than the complexed ones. Also, the characteristics and bioavailability of element sorption depend on speciation. Carbonate, sulphate or chloride complexes can strongly sorb these elements when they are in a simple uncomplexed ionic form; hydroxyl and phosphate complexes are often sorbed readily. This behaviour affects the transport and mobility of elements: free and complexed ions that have little tendency to sorb onto surfaces will be transported within the aqueous phase; the elements that sorb onto particulates will be transported and deposited with them or released depending on changes in the chemical condition.

4.2 Adsorption and Desorption Processes of PTEs in the Aquatic Environment

151

In the aquatic environment, a fraction of PTEs is in the dissolved form, but most of PTEs are related to suspended matter. According to Sansalone and Buchberger (1997) and Gnecco et al. (2008) the processes governing the distribution of PTEs in dissolved and particulate fractions depend on parameters such as rainfall pH, alkalinity, runoff residence time and characteristics of solids. The partition of PTEs between soluble and particulate fractions in stormwater is strongly affected by DOC (Herngren et al. 2005). According to Warren et al. (2003) and Herngren et al. (2005), DOC can act as a solubility enhancer for PTEs. When stormwater has a low pH value, potentially toxic elements such as Cd, Cr, Cu, Ni, Pb and Zn can be partly detected in the dissolved form (Göbel et al. 2007). Potentially toxic elements can be mostly found in the dissolved phase as a result of the complexation processes in the interaction between PTEs and DOC (Herngren et al. 2005). A number of investigations have addressed partitioning of PTEs between the dissolved and solid phase. Regarding the interaction between PTEs and suspended solids in surface runoff, the majority of PTEs can be found in suspended solids (Bodo 1989; Dong et al. 1984; Herngren et al. 2005; Davis and McCuen 2005; Marsalek et al. 2001; Weiss et al. 2006). The amount of suspended solids in water affects the particulate portion of PTEs in road runoff (Herrmann et al. 1998; Göbel et al. 2007), which correlates with traffic density. PTEs coming from traffic activities are mainly found as particulate matter in runoff (Kern et al. 1992; Sansalone and Buchberger 1997; Göbel et al. 2007). Many researchers found that the highest concentrations of PTEs were related to the smallest sediment fractions detected in urban runoff and snowmelt (Lau and Stenstrom 2005; Sansalone and Buchberger 1997; Nordqvist et al. 2011). Because of the large surface area of fine sediments and high CEC (Dong et al. 1984; Herngren et al. 2005), the concentrations of PTEs increase with a rise in particle size (Liebens 2001; Ujevic et al. 2000; Herngren et al. 2005). Kazemi (1989) and Göbel et al. (2007) analysed road dust and discovered that the particles with a diameter smaller than 20 μm were characterized by the highest concentrations of PTEs. Chemical parameters such as pH and DOC can increase the desorption of PTEs from suspended solids (Herngren et al. 2005). Lamprea and Ruban (2008) determined that PTEs were detected mainly in the dissolved phase because of low pH values and low concentrations of suspended solids in roof and water runoff. According to Pitt et al. (1995) and Weiss et al. (2006), Pb has the highest potential of adsorption to soil particles while Cd has the lowest potential: Pb > Cu > Ni > Co > Zn > Cd

4.2.2

Theoretical Aspects of Adsorption

Liquid–solid adsorption is divided into four basic steps (Fig. 4.1). 1. Liquid phase mass transfer. Molecules or ions in the column can move in both axial and radial directions (Xu et al. 2013). A macroscopic mass conservation

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equation is acquired to represent the relationship between the corresponding variations. Regarding a control volume shown in Fig. 4.2 (Costa and Rodrigues 1985; Tien 1994; Fournel et al. 2010), 2

ε

∂C ∂C ∂q ∂ C þu þ ð1  εÞρa ¼ Dz 2 ∂t ∂z ∂t ∂z

ð4:4Þ

where the initial and boundary conditions are (Eqs. 4.5a–4.5d): t ¼ 0 ! C ðz, t Þ ¼ 0,

ð4:5aÞ

t ¼ 0 ! qðz, t Þ ¼ 0,

ð4:5bÞ

z ¼ 0 ! C ð0, t ¼ 0Þ ¼ 0, C ð0, t > 0Þ ¼ CF ,

ð4:5cÞ

z¼H!

∂C ¼ 0: ∂z

ð4:5dÞ

When axial dispersion is ignored,

Fig. 4.1 Adsorption process (Xu et al. 2013)

External surface of the “film” 1

A B

C

2

A: bulk fluid B: interface region C: adsorbent pellet 1: film diffusion 2: intrapellet diffusion

Fig. 4.2 Schematic diagram of the mass conservation of a control volume (Xu et al. 2013)

Internal surface of the “film”

1: convective mass transfer 1+ 2: axial dispersion 3: adsorbed by adsorbent 4: accumulation of adsorbate u δC δz δ 2C (2+) (2 ) Dz 2 δz q (3 ) (1 ε )ra δt (4) ε δC δt

2+

(1+) (1 )

4

1-

3-

2-

4.2 Adsorption and Desorption Processes of PTEs in the Aquatic Environment

∂C ∂C ∂q þu þ ð1  εÞρa ¼0 ∂t ∂z ∂t

153

ð4:6Þ

The initial and boundary conditions turn to Eqs. 4.7a–4.7c: t ¼ 0 ! C ðz, t Þ ¼ 0, z ¼ 0 ! C ¼ CF þ z¼H!

DZ ε ∂C , u ∂z

∂C ¼ 0: ∂z

ð4:7aÞ ð4:7bÞ ð4:7cÞ

where ε—bed porosity; t—time; ρa—adsorbent density; CF—the initial concentration of the influent; H—bed height, DZ—axial dispersion coefficient (in the case axial dispersion is not ignored); u—superficial velocity; z—distance to the inlet; C— the concentration of the bulk solution; q—the concentration of the adsorbed adsorbate. Equations (4.4) and (4.6) are based on the following assumptions: • The process is isothermal. • No chemical reaction occurs in the column. • The packing material is made of porous particles that are spherical and uniform in size. • The bed is homogenous and the concentration gradient in the radial direction of the bed is negligible. • Flow rate is constant and invariant with the column position (Warchoł and Petrus 2006). • The activity coefficient of each species is unity. 2. Film diffusion. The driving force of film diffusion is the concentration gradient located at the interface region between the exterior surface of adsorbent pellets and the bulk solution. The film diffusion of the flux can be expressed in the linear form (Eq. 4.8) (Tien 1994; Fournel et al. 2010) as follows: dq ¼ J f ¼ k f að C  C S Þ dt

ð4:8Þ

where: Jf—mass-transfer flux; a—the area of the volumetric surface; Cs—adsorbate concentration at the exterior surface of the adsorbent; kf—the coefficient of film diffusion. An increase in flow rate decreases film thickness and resistance, whereas stronger film resistance can be caused by packing smaller adsorbent pellets due to the extension of the exterior surface area (Xu et al. 2013). 3. Intrapellet diffusion and reaction. Surface diffusion and pore diffusion proceed in parallel accompanying with Knudsen diffusion and adsorption reactions (Xu et al. 2013). Of note, when the pore size is only slightly larger than the diameter of adsorbate ions or molecules, Knudsen diffusion begins playing a significant role

154

4 Sustainable Natural Materials Used for Adsorbing Pollutants from the Aqueous. . . a)

c)

d) b)

2 3 1 4

3 2

Fig. 4.3 A macroscopic schematic illustration of the basic diffusion and adsorption steps inside the pore: a—surface diffusion, b—pore diffusion, c—pore diffusion with significant Knudsen diffusion, d—combination of intrapellet diffusion and adsorption, 1—pore diffusion, 2—surface diffusion, 3—adsorption, 4—desorption (Xu et al. 2013)

as shown in Fig. 4.3. There are two generally recognized mathematical relationships that were developed to describe the equilibrium distribution of a solute between dissolved (liquid) and adsorbed (solid) phases. These relationships help interpret the adsorption data obtained during tests at a constant temperature and are referred to as an adsorption isotherm (Walter and Weber 1980). Physical and chemical adsorption and desorption isotherms are important for characterizing the overall adsorbent surface. The slightest change in the shape of the plotted isotherm is indicative of a particular surface feature. For adsorption from liquid solutions, solution concentration, c, is used in the abscissa instead of P2.

4.2.3

Isotherm Models

The adsorption isotherm shows how the adsorbed molecules distribute between the liquid and solid phase when the equilibrium state is reached in the process. All below presented adsorption isotherms can be plotted from the same experimental data and choosing the abscissa and ordinate parameters is arbitrary (Yildirim 2006) (Fig. 4.4). In most practical adsorption processes, more than one component are adsorbed. The measurements of the adsorption capacities of multiple-component mixtures are much more complex than those of a single adsorbate.

4.2.4

Henry’s Law Isotherm

The most basic isotherm is a linear increase in the amount of adsorbate with an increase in adsorptive gas pressure, which is described by the Henry’s law limit isotherm (Eq. 4.9). For the simplest case, it is directly proportional to the partial pressure of adsorptive gas, P2, and then

4.2 Adsorption and Desorption Processes of PTEs in the Aquatic Environment Γ or θf

Γ or θf

θf=1

θf=1

Γ or θf

TYPE-II (B.E.T.)

155

TYPE-III (B.E.T.)

TYPE-I (LANGMUIR) P/Po

Γ or θf

P/Po

1 Γ or θf

TYPE-IV

P/Po

1

1

Γ or θf

TYPE-V

(LINEAR) (HENRY) P/Po

P/Po

1 Γ or θf

Γ or θf

P/Po

1

1

Γ or θf (HIGH AFFINITY) (STEP)

(FREUNDLICH) P/Po

1

P/Po

1

P/Po

1

Fig. 4.4 Typical adsorption isotherm plots (Yildirim 2006)

x ¼ K dc

ð4:9Þ

where x—the amount of ion adsorbed per unit mass; c—the concentration of ions in the equilibrium solution ion, mg/L; Kd—distribution coefficient. For solutions, concentrations are used instead of partial pressures. The linear isotherm can be applied for describing the initial part of many practical isotherms. It is typically taken as valid for low surface coverages and adsorption energy being independent of the coverage (lack of inhomogeneities on the surface) (Yildirim 2006).

4.2.5

Two-Parameter Isotherms

The Langmuir isotherm is derived from the proposed kinetic mechanism and is based on four hypotheses: 1. 2. 3. 4.

The surface of the adsorbent is uniform, i.e. all adsorption sites are equal. Adsorbed molecules do not interact. All adsorption occurs through the same mechanism. At the maximum adsorption, only a monolayer is formed: the molecules of adsorbate do not deposit on the other, already adsorbed molecules of adsorbate; they only deposit on the free surface of the adsorbent (Walter and Weber 1980).

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4 Sustainable Natural Materials Used for Adsorbing Pollutants from the Aqueous. . .

For liquids adsorbed on solids, the Langmuir isotherm can be expressed by Eq. 4.10: m¼

Amax kc 1 þ kc

ð4:10Þ

where m—the amount of the substance of adsorbate adsorbed per gram of the adsorbent, mol/g; Amax—the maximal substance amount of adsorbate per gram of the adsorbent, mol/g; k—adsorption constant, mol/dm3; c—the concentration of adsorbate in liquid, mol/dm3. The Freundlich isotherm assumes that the adsorbent has a heterogeneous surface composed of adsorption sites with different adsorption potentials. This equation presumes that each class of the adsorption site adsorbs molecules, as in the Langmuir Equation. The Freundlich isotherm equation is the most widely used one (Pure Water Lab 2011) and was developed empirically but can very accurately describe a wide range of adsorption data. The equation has the following forms (Eqs. 4.11 and 4.12): 1

qe ¼ K  C ne x qe ¼ m

ð4:11Þ ð4:12Þ

where qe—the amount adsorbed per unit mass of biochar, mg/g; x—the amount of solute adsorbed, mg; m—the weight of the adsorbent, g; Ce—solute equilibrium concentration, mg/L; K—constant of the capacity of the adsorbent for adsorbate; 1/ n—constant measuring the strength of adsorption characteristic of the system. The Freundlich equation can be linearized to the equation below (Eq. 4.13). log

x 1 ¼ log K þ log C e m n

ð4:13Þ

The Temkin isotherm was proposed to describe the adsorption of hydrogen on platinum electrodes within acidic solutions. Temkin noted experimentally that the heats of adsorption would more often decrease than increase with the rising coverage. The derivation of the Temkin isotherm is based on the assumption that a decline in the heat of sorption as a function of temperature is linear rather than logarithmic, as implied in the Freundlich equation (Eq. 4.14): qe ¼

RT ln AT C e bt

ð4:14Þ

where AT—equilibrium binding constant of the Temkin isotherm, L/g, bT—constant of the Temkin isotherm, R—universal gas constant, 8.314 J/mol/K, T—temperature at 298 K, Ce—the equilibrium concentration of PTE molecules in a fluid, mol or mg/L.

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157

It is apparent that the Temkin equation is superior in the prediction of gas-phase equilibrium. However, in liquid phase adsorption, especially for heavy metals adsorption using biosorbent, this model falls-short in representing the equilibria data. Adsorption in the liquid phase is a more complex phenomenon than that in the gas phase as the adsorbed molecules here are not necessarily organized in a tightly packed structure with identical orientation. Further on, the presence of solvent molecules and the formation of micelles from the adsorbed molecules add to the complexity of liquid phase adsorption. Numerous factors, including pH, the solubility of adsorbate in the solvent, temperature and surface chemistry of the adsorbent, influence adsorption from the liquid phase. Since the basis of derivation for the Temkin equation is a simple assumption, the complex phenomenon involved in liquid phase adsorption is not taken into account by this equation, which is often not suitable for the representation of experimental data in complex systems. An advantage is a simple expression. Disadvantages are the same as Freundlich does not have the correct Henry’s law and finite saturation limit not applicable over a wide range of concentrations. The Temkin isotherm described data (R2 ¼ 0.935) better than Langmuir and Freundlich models; constants A and bT obtained for the Temkin isotherm model were 210.5 L/g and 11.7, respectively, thus further confirming that chemisorption played an important role in controlling the sorption of As(V) onto Fe-impregnated biochar (Hu et al. 2015). The constants included in the equation have substantial importance when characterizing the adsorption system. Constant K is a function of the adsorption capacity of the specific adsorbent. The value of 1/n is a measure of the strength of adsorption. When holding all other variables constant, the value of the adsorbed solute will increase with rising K. For smaller values of 1/n, a stronger adsorption bond will be for that specific adsorbate (Pure Water Lab 2011). The Flory–Huggins isotherm occasionally derives the degree of surface coverage characteristics of adsorbate onto the adsorbent and can express the feasibility and spontaneous nature of the adsorption process (Eq. 4.15). θ ¼ K FH ð1  θÞnFH Co

ð4:15Þ

where θ is the degree of surface coverage, KFH is equilibrium constant, nFH is model exponent, Co—the equilibrium concentration of PTE molecules in a fluid, mg/L.

4.2.6

Three-Parameter Isotherms

The model for the Redlich–Peterson Isotherm is used for representing adsorption equilibrium over a wide range of concentrations and can be applied in either homogeneous or heterogeneous systems due to its versatility. The Redlich–Peterson isotherm contains three parameters and incorporates the features of Langmuir and

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the Freundlich isotherms. Comparing with Langmuir or Freundlich isotherms, the equation for the Redlich–Peterson isotherm is more generalized (Eq. 4.16): qS ¼

K J CS , 1 þ bJ C βS

ð4:16Þ

where qS—the amount adsorbed per unit mass of biochar, mg/g; CS—solute equilibrium concentration, mg/L; KJ, bJ, β—Redlich–Peterson constants. The Redlich–Peterson equation can be linearized to Eq. 4.17:


C ln K J S  1 qS

 ¼ g ln ðC S Þ þ ln ðbJ Þ,

ð4:17Þ

The Redlich–Peterson isotherm is graphically shown in Fig. 4.5. The Redlich–Peterson isotherm gradually rises, which allows describing few adsorption processes at the same time. This isotherm defines the adsorption process in the heterogenic adsorbent because of multidisciplinary factor β. Due to inconvenience to calculate three isotherm constants, the Redlich–Peterson isotherm is not widely applied in practice for mathematical modelling (Valentukevičienė 2003). The Sips isotherm is a combined form of Langmuir and Freundlich expressions deduced for predicting heterogeneous adsorption systems and circumventing the limitation of the rising adsorbate concentration related to the Freundlich isotherm model. At a low adsorbate concentration, it reduces to the Freundlich isotherm, while at a high concentration, it predicts monolayer adsorption capacity characteristic of the Langmuir isotherm. As a general rule, the equation parameters are governed mainly by operating conditions such as the alteration of pH, temperature and concentration (Eq. 4.18).

Fig. 4.5 A classical adsorption isotherm formed by: a—Langmuir equation, b—Freundlich equation, c—Redlich–Peterson equation (Valentukevičienė 2003)

K LF Cne qmax 1 þ K LF C ne

The amount adsorbed per unit mass of biochar, (qs, mg/g)

qe ¼

ð4:18Þ

a c

b

Initial concentration of adsorbate (Cs, mg/l)

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159

where Ce—the equilibrium concentration of PTE molecules in a fluid, mol or mg/L; qe—the equilibrium mass of the sorbed molecules per mass of the sorbent, mol or mg/g; qmax—maximum adsorbed amount, mg/g; KLF is Sips adsorption constant, L/mg. The Toth isotherm is another empirical equation developed to improve Langmuir isotherm fittings (experimental data), which is useful for describing heterogeneous adsorption systems satisfying both low- and high-end boundary of the concentration (Eq. 4.19). qe ¼

K T Ce ðaT þ C e Þ1=t

ð4:19Þ

where Ce—the equilibrium concentration of PTE molecules in a fluid, mol or mg/L, qe—the equilibrium mass of the sorbed molecules per mass of the sorbent, mol or mg/g, KT and t are equation constants. Parameter t characterizes the heterogeneity of the system. Similarly to the Sips isotherm model, the Koble–Corrigan isotherm is the threeparameter equation incorporating both Langmuir and Freundlich isotherm models for representing equilibrium adsorption data. Isotherm constants A, B and n are evaluated from the linear plot using trial and error optimization (Eq. 4.20). qe ¼

AC ne 1 þ BC ne

ð4:20Þ

where Ce—the equilibrium concentration of PTE molecules in a fluid, mol or mg/L, qe—the equilibrium mass of the sorbed molecules per mass of the sorbent, mol or mg/g, A and B are equation constants.

4.2.7

Modelling the Multi-component Adsorption Process

In general, the mathematical modelling of the multi-component adsorption process is the expansion of the described modelling of the single-component adsorption process. Multi-component equilibrium can be formed by correlation and/or extended methods based on empirically expanded formula. Easy-to-use and simple equations are created with reference to classical theoretical formulas but do not give very accurate results (Valentukevičienė 2003). The Redlich–Peterson isotherm equation (Eq. 4.21) is as follows: qSi ¼

1þ

K Ji C Si , Pn βji j¼1 bJj C Sj

ð4:21Þ

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4 Sustainable Natural Materials Used for Adsorbing Pollutants from the Aqueous. . .

where qS—the amount adsorbed per unit mass of biochar, mg/g; CS—solute equilibrium concentration, mg/L; KJ, bJ, β—Redlich–Peterson constants. When mathematically modelling multi-component adsorption processes, the extended method does not guarantee sufficiently accurate results. The deficiency of certain mathematical formulas does not mathematically express the effects of multiple solutions, and therefore in many cases experimental data are used for assessing processes. This forms the basis for the correlation method. Data on the multi-component adsorption process is used for creating interaction factors (Valentukevičienė 2003). For multi-component systems, the extended Freundlich isotherm is widespread due to its accuracy and is recommended for most cases of multi-component adsorption. Freundlich constants are determined using the linear form of the equation for calculating experimental data. The expressions of the two-component adsorption system are obtained in Eqs. 4.22 and 4.23: 1 n

q1 ¼

K 1 C 11

2

1 n1

1 n

K 1 C1 þ K 2 C 22 1 n

q2 ¼

þn1

K 2 C 21 1 n1

ð4:22Þ

þn1

2 1 n

K 1 C1 þ K 2 C 22

ð4:23Þ

where q1, q2—the amount of the adsorbed PTE per unit mass of biochar, mg/g; K1, K2—the capacity of biochar for the PTE; C1, C2—pollutant equilibrium concentration, mg/L; 1/n1; 1/n2—the function of adsorption intensity.

4.3

Geochemical Models for Estimation of Bioavailability of PTEs

In order to evaluate the processes that determine the toxicity and bioavailability of contaminant species (e.g. solubility, speciation, complexing, sorption, ion exchange, ion pairing, mobilization, and transport), the conducted analysis must determine toxic and non-toxic major dissolved constituents that are essential to calculate the ionic strength of water and the activity and speciation of the dissolved major and minor constituents (Breault 2000). The concentrations, transport and fate of potentially toxic elements are difficult to quantify, especially in stormwater-runoff studies because of the complexity of the physical and chemical processes involved and the difficult monitoring of the environment. The model output relies on the quality and completeness of data obtained from water analysis. Mass-transfer models (e.g. EQ3/6 Wolery 1992a, b; the Geochemist’s Workbench Bethke 1994, 1996; PHREEQE Parkhurst et al. 1980; PHRQPITZ Plummer et al. 1988; MINTEQA2 Allison et al. 1991; cited in Bricker 1999) are used for

4.3 Geochemical Models for Estimation of Bioavailability of PTEs

161

simulating changes in solution chemistry due to the mass-transfer process and for predicting the overall geochemical behaviour of contaminants in the case reactions in a system go to equilibrium. Mass-balance models (e.g. NETPATH Plummer et al. 1991, 1994 cited in Bricker 1999) are useful for identifying and quantifying the major geochemical processes taking control over the evolution of water chemistry. These models only depend on mass-transfer considerations: the detected difference between the initial and final water compositions is inferred to the dissolution and precipitation of each mineral phase present in the system. CHMTRNS (Noorishad et al. 1987 cited in Bricker 1999), PHREEQM-2d (Nienhuis et al. 1994 cited in Bricker 1999) and PHREEQC (Parkhurst 1995 cited in Bricker 1999) are the examples of geochemical mass-transport models and can be applied for evaluating the hydrodynamic advection and dispersion of dissolved species in porous media, speciation processes in the aqueous solution and geochemical mass transfer. The Biotic Ligand Model (BLM) considers both free ion activity and interactions at the site of the toxic action since it is based on the assumption that the toxicity of potentially toxic elements occurs as a result of forming a metal-biotic ligand complex (i.e. free ions of potentially toxic elements reacting with binding sites at the organism-water interface). The magnitude of the toxic effect is determined by the concentration of the metal-biotic ligand complex rather than by the physical–chemical water characteristics of the tested medium (de Schamphelaere and Janssen 2002). The BLM is seen as a powerful tool-developing criteria for water quality and performing an ecological assessment of potentially toxic elements in aquatic systems. Speciation models are employed for calculating the partitioning of an element among different aqueous species and complexes. The thermodynamic database must contain information on all species present in the system being modelled. In addition, depending on the completeness of thermodynamic information in the program, the saturation state of solid phases and gases can be evaluated. Bricker (1999) cited WATEQF (Plummer et al. 1976) and WATEQ4F (Ball and Nordstrom 1991) as the examples of speciation models such as Model V or Model VI (Tipping 1998; Lofts and Tipping 2002 cited in Lock et al. 2006) used in BLM for calculating the activity of free metal ions. In the work by Lock et al. (2006), WHAM 6.0.8 Software (Tipping 1998; Lofts and Tipping 2002 cited in Lock et al. 2006) was used for calculating speciation processes involved in the evaluation of toxicity effects of cobalt on a pot worm by means of the BLM. The speciation model such as WHAM is a part of the BLM because the calculation and representation of cationbiotic ligand interactions is like any other reaction of a cation with an inorganic or organic ligand.

162

4.4

4 Sustainable Natural Materials Used for Adsorbing Pollutants from the Aqueous. . .

Biochar as the Potential Adsorption Medium for PTEs

SRW is a major contributor to the pollution of receiving waters in the case it is discharged directly without retention and treatment. To face environmental quality degradation caused by stormwater runoff in urban areas, new technical solutions to improving the action of traditional urban storm drainage are on demand. As an example of stormwater management policies, many states in the USA developed the method of Best Management Practice (BMP) where source control, runoff treatment and flow control are the adopted strategies to prevent or reduce the release of pollutants. Porous pavement, green roof, detention/retention ponds and wetlands will be introduced as interesting structural BMP that can be adopted for urban runoff management. In parking spaces and residential streets, porous pavements with reservoir structure for the infiltration of runoff can represent an effective stormwater management technique if pollutant retention in the structure can avoid the risk of affecting the quality of soils and groundwater. In the work by Dierkes et al. (1999), a simulation of 50 years proved the efficiency of porous pavements with reservoir structures to trap dissolved potentially toxic elements in runoff. The study of Legret and Colandini (1999) found that the porous pavement could improve the quality of stormwater, thus abating pollution loads (suspended solids, Pb, Cu, Cd and Zn) compared to the one drained by a sewer system. A considerable proportion of Pb bounded to suspended solids was captured in the porous surfacing of the pavement, whereas Cu, Cd and Zi in the soluble form were mostly infiltrating the soil under the structure. In addition, up to 96.7% of the stormwater volume can infiltrate in the soil below the reservoir structure (Colandini 1997; Legret and Colandini 1999). With the aim of finding sustainable and cost effective methods, many stormwater management techniques are being developed copying nature. Green roofs can be useful for the local management of stormwater reducing the load of potentially toxic elements in roof runoff and providing stormwater retention. In the work by Gregoire and Clausen (2011), the vegetated roof was successful in reducing roof runoff and in acting as a sink for Pb and Zn. Building materials must be chosen with accuracy in order to avoid that the green roof itself becomes an unintended source of pollutants. In the study by Alsup et al. (2011), the high concentrations of potentially toxic elements such as Cd, Ni, Pb and Zn in the leachate from the simulated green roof were related to the material used as substrate. Vegetated control facilities such as natural or constructed wetlands are proved to be effective in tackling the load of suspended solids and potentially toxic elements bound to particulates or in particulate form in urban runoff. In a detention pond, a large volume of stormwater can be treated by means of the sedimentation, filtration or phytoextraction of potentially toxic elements from contaminated water before releasing them to a local water basin (Muthukrishnan 2006). According to Cheng et al. (2002), the use of constructed wetlands is an inexpensive and effective system for reducing the discharge of pollutants found in stormwater and for wastewater treatment (e.g. removal of potentially toxic elements from mining effluent and special industrial wastewater). Regarding the methods that are currently adopted to

4.4 Biochar as the Potential Adsorption Medium for PTEs

163

remove potentially toxic elements from urban stormwater runoff, according to Patterson (1997) and Xu et al. (2013), the main ones are filtration, chemical precipitation, coagulation-flocculation, solvent extraction, electrolysis, ion exchange, membrane process and absorption. These technologies involve disposal problems related to the large volumes of sludge and waste produced in the process or high capital and operational costs, whereas the adsorptive removal of contaminant technology is characterized by low investment costs, limited waste production and simple design. A major obstacle to the use of sorption processes is the relatively high cost of commercial sorbents (e.g. AC and ion exchange resins). Thus, there is continuing search for cheap and high-capacity sorbents for the ions of potentially toxic elements (Ho et al. 2002). An interesting treatment method for removing the ions of potentially toxic elements from the aqueous solution is represented by sorption with sorbents made of agricultural or industrial by-products because of their abundant availability, low cost and favourable physical and chemical characteristics of the surface (Sawalha et al. 2008; Iqbal et al. 2009). A thorough knowledge of the mobility and bioavailability of potentially toxic elements is necessary for the adoption of effective environmental strategies to solve environmental problems (Li et al.1995; Sandroni et al. 2003). For example, conventional pollutant abatement programs (e.g. street sweeping) are not effective in reducing toxic runoff levels, because most potentially toxic elements have a greater affinity for smaller particle sizes that are not influenced by these techniques (Herngren et al. 2005). Biochar is a fine-grained, porous and carbon-rich material produced from biomass pyrolysis. Biochar may be a key component in achieving a comprehensive carbon management strategy since among carbon dioxide mitigation technologies, the production of biochar via pyrolysis and deposition in the soil is thought to be a viable option for storing permanent carbon capture, forming a C sink and sequestering atmospheric CO2. Biochar can be produced in combination with bioenergy from the thermal treatment of biomass feedstock and applied to the agricultural soil both to sequester C and to improve the production potential of crops. Biochar used for environmental remediation purposes has received considerable attention in recent years as a soil amendment for sequestering carbon, releasing essential nutrients, enhancing soil quality and sequestering a variety of contaminants such as organic pollutants and potentially toxic elements. In a pyrolizer, organic materials are thermally decomposed to release a vapour phase and a residual solid phase (biochar). On cooling pyrolysis vapour, polar and high-molecular-weight compounds condense out as a liquid (bio-oil) while low-molecular-weight volatile compounds remain in the gas phase (syngas). The yield of biofuel and biochar as well as the chemical and physical properties of biochar are greatly affected by the choice of pyrolysis temperature and conditions under which it has been produced (e.g. biochar production is optimized in the absence of oxygen) and by the type of the feedstock used. Regarding biomass feedstock, since the main impact on CO2 emissions is estimated mixing biochar with the soil, almost any organic matter is considered suitable to produce biochar. Household, municipal or industrial waste is not considered as feedstock, because it may contain potentially toxic elements or organic pollutants that could cause environmental contamination by land application of biochar. The

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best feedstock of biomass could be obtained by recycling agricultural and forestry waste: a significant amount of non-contaminated organic matter could be received from recycling crop residues, forest residues, mill residues, field crop residues or urban waste (yard trimmings, site clearing, pallets, wood packaging). Therefore, not all agricultural waste materials are suitable to produce biochar and the amount of the opportunity depends on the location and available specific crop residues (Lehmann et al. 2006). Regarding the concern about biochar contamination, there are no official standards for the material or processing conditions that can provide sound basis for biochar quality regulations about the presence of contaminants, thus avoiding soil and water contamination related to some of its components. Since the potential occurrence of potentially toxic elements in biochar may constitute a serious public health issue, it is necessary to assess mechanisms as well as to identify specific operational and feedstock conditions that may cause the formation and retention of such toxic pollutants. Recently, many researchers have tested its ability to adsorb pollutants in the soil, but a few of them are focused on its effects on filtering water contaminated with potentially toxic elements. Among the current methods of removing potentially toxic elements from the solution, activated carbon is one of the most commonly used adsorbents for wastewater applications, but it represents a very expensive solution to be adopted for the remediation of the volumes of water such as the ones that should be treated after a storm event. Since biochar has properties and molecular structures that resemble activated carbon, it is thought that biochar can be used as a low-cost sorbent playing an important role in controlling contaminants in the environment (e.g. in the filtering process of contaminated water). Literature on AC is often relevant to the study of BC because char precursors used in the process are similar to BC (Lehmann and Joseph 2009). In addition, BC itself can be used as a precursor product of AC if its porous structure and the surface area are appropriate and the adopted feedstock is characterized by high C and low inorganic contents (Lehmann and Joseph 2009). Regarding the physical and structural characteristics of BC and AC, both the porosity and structure of the raw material remain in the mineral and C skeleton formed in the charring process. Biochar and AC have a high affinity and capacity for sorbing organic compounds (Lehmann and Joseph 2009). It is supposed that plant-derived biochar and AC have similar mechanisms for the sorption of potentially toxic elements: cation/proton exchange on deprotonated functional groups and C π-PTE bonding on graphitic surfaces (Liu and Zhang 2009; Sanchez-Polo et al. 2002; Youssef et al. 2004; Harvey et al. 2011). High mineral-ash biochar (e.g. chicken manure biochar) and AC have been proven to be effective in adsorbing potentially toxic elements (Swiatkowski et al. 2004; Lima and Marshall 2005; Lehmann and Joseph 2009). In the study of Chen et al. (2008), the similar sorption behaviour of AC and pine needle biochar (produced at 700  C) was related to a monolayer surface coverage where pores were accessible to both non-polar and polar aromatic contaminants. Pietikäinen et al (2000) and Lehmann and Joseph (2009) found that biochar from humus and wood had a higher water-holding capacity than AC. The study by Cao et al. (2009)

4.4 Biochar as the Potential Adsorption Medium for PTEs

165

investigated the ability of dairy-manure biochar to sorb Pb and organic contaminant atrazine; a comparison of the sorption characteristics of BC and that of commercial AC showed that BC was 6 times more effective in Pb sorption than AC.

4.4.1

Biochar Properties

The scientific community is still debating about the hierarchy of the preferred properties of biochar and a common language about its characteristics is still on demand. In addition, it is still not possible to correlate individual biochar with performance for a potential application. For this reason, biochar characteristics are evaluated by standardized tests developed for other materials. For example, Proximate and Ultimate Analyses are two ASTM tests that are intended for the characterization of solid fuels; therefore, these procedures yield appropriate measurements when are applied to charcoal that is intended for burning. The work by McLaughlan and Al-Mashaqbeh (2009) suggested a modified Proximate Analysis in order to have more reliable data about biochar performance when added to the soil and not subjected to high heat. The work by Shinogi and Kanri (2003) and Laird et al. (2011) disclosed a combination of physical and chemical properties such as the surface area, bulk density, total carbon, total nitrogen, pH, fixed carbon, ash content and volatile matter content as the indicators of biochar quality. International Biochar Initiative (IBI) is developing standards about product definitions and testing guidelines with the aim of providing the standardized information system about the characterization of biochar and qualitative specification guidelines in order to provide a uniform quality standard throughout research, industry and consumers. In the work of IBI, official standards such as International Standards Organization (ISO), American Society for Testing and Materials (ASTM) and Institute of Electrical and Electronics Engineers (IEEE) were followed (International Biochar Initiative 2012). Biochar qualities have not been standardized yet since they are strongly related to the end purpose of the product. For instance, the adsorption capacity and hydraulic conductivity of biochar are the key properties when biochar is adopted as a filter material to remove organic or inorganic contaminants from an effluent stream (Laird et al. 2011). It has to be noticed that for specific environmental applications, a fundamental knowledge of the sorption mechanism is still required. Biochar properties are highly heterogeneous; individual biochar particles and biochar originating from different types of feedstock or produced under different pyrolysis conditions show different characteristics. The variety of the physical and chemical properties of biochar depends on the source of biomass, pyrolysis conditions as well as post- and pre-treatment (Uchimiya et al. 2010). Particle size and macro-, meso- and micropore size distribution in biochar are subject to a combination of the type of feedstock and the adopted conditions of pyrolysis. Particle size distribution in biochar concurs in determining the suitability of the biochar product for a specific application (Downie et al. 2009; Verheijen et al. 2010). The properties such as a high content of carbon and a strongly aromatic structure are the constant

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features of the structural and chemical composition (Sohi et al. 2009; Verheijen et al. 2010). Despite the highly heterogeneous structural and chemical composition of biochar made from different types of feedstock, pH values are almost homogeneous and largely neutral to the basic ones that are typically greater than 7 in a total range of pH and made 6.2–9.6 (Chan and Xu 2009; Verheijen et al. 2010). The study of Lu et al. (2011) investigated the feasibility of using sludge-derived biochar (SDBC) (i.e. the resulting product of the pyritization process of sewage sludge) as a treatment of acidic solutions containing potentially toxic elements such as acid mine drainage. The obtained Pb sorption capacity in a range of acidic pH value showed that SDBC could be a promising technique for removing potentially toxic contaminants from acid solutions. In comparison with the extensive studies about determining sorption mechanisms for organic contaminants on char, limited information is available on the factors controlling the immobilization of inorganic contaminants on BC and the impact of BC on the retention of potentially toxic elements.

4.4.2

The Characteristics of Biochar Properties Influencing Adsorption

The chemical and physical characteristics of biochar depend on the nature of the feedstock used (woody vs. herbaceous), operating conditions and the environment of the pyrolysis unit (low vs. high temperature, residence time, slow vs. fast pyrolysis, heating rate and feedstock preparation) (Soil and Water Conservation Society 2008). A wide range of process parameters leads to the formation of biochar products that vary considerably in their elemental and ash composition, density, porosity, pore size distribution, the surface area, the chemical properties of the surface, water and ion adsorption and release, pH and the uniformity of biochar physical structure (Baldock and Smernik 2002; Antal and Grønli 2003; Downie et al. 2009; Krull et al. 2009; Chan and Xu 2009). Studies on the adsorption of potentially toxic elements show that, in general, it was a function mainly of the specific surface area, cation exchange capacity (CEC) and pH (Chantawong 2004). Generally, the rate of adsorption increases when the size of the particle decreases, as the process step of diffusion to the carbon surface should be enhanced by smaller particles. Another critical aspect of adsorption rate is pore size distribution and the development of ‘transport pores’ within the particle that allows the effective migration of contaminants to the point of adsorption (U.S. Army Corps of Engineers 2001). The surface area is the biochar particle area available for adsorption. In general, the larger is the surface area, the greater is adsorption capacity; however, this surface area needs to be effective. A high degree of the area needs to be in the region of ‘adsorption pores’ as well as accessible to the contaminant with an effective ‘transport pore’ structure for the capacity to be useful. The surface area of biochar generally increases with a rise in the highest treatment temperature (HTT) until it reaches the one at which deformation occurs, thus resulting in a subsequent decrease

4.4 Biochar as the Potential Adsorption Medium for PTEs

10 µm

167

10 µm

Fig. 4.6 The image of Scots pine (Pinus sylvestris L.) (on the left) and Pedunculate oak (Quercus robur) (on the right) biochar made by the scanning electron microscope (SEM)

in the surface area (Australian Government. Department of Agriculture, Fisheries and Forestry 2010). Mesopores are important to many liquid–solid adsorption processes. When biochar is assessed mainly for its role as an adsorbent, macropores (>50 nm diameter) are considered to be important as feeder pores for the transport of adsorbate molecules to meso- and micropores (Lehmann and Joseph 2009). Obvious differences in the macroporous structure between the images of pine and oak biochar at the same magnification (1000 times) using the scanning electron microscope (SEM) are shown in Fig. 4.6. Though differences in pore size are not rigorously assessed (because of the inaccuracy of images), it is obvious that the edges of pine biochar are sharper than those of oak biochar, and the distribution of the porous cavities of oak biochar is denser than that of pine biochar. Techniques for evaluating porosity and the surface area include physical gas adsorption, mercury intrusion porosimetry (Fig. 4.6), chemical gas adsorption, scanning electron microscopy, transmission electron microscopy and pycnometry. Under certain conditions, a high temperature causes micropores to widen because it destroys the walls between adjacent pores and thus resulting in the enlargement of pores (Zhang et al. 2004). This leads to a decrease in the fraction of volume found in the range of micropores and an increase in the total volume of pores. Cation exchange capacity (CEC), usually expressed in milliequivalents per 100 g of mass, is a measure of the quantity of readily exchangeable cations neutralizing negative charge (Bolt et al. 1976). Fresh biochar can have net positive or net negative surface charge. High-ash biomass generates biochar with slightly greater CEC and charge density upon the normalization of CEC to the surface area. On the other hand, greater temperatures of pyrolysis cause a decrease in CEC, especially in charge density as a result of a greater surface area produced at the high temperatures of up to 600  C and loss of volatile matter, which may contain a substantial portion of negative charge and CEC as organic acids. Many methods for determining CEC are provided by using different combinations of biochar pre-treatment, saturation,

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washing and extraction procedures as well as different saturation and replacing cations, washing solvents and pH control. Most methods used may be categorized as one of four: • • • •

Summation method. Direct displacement method. Displacement after washing method. Radioactive tracer method (Lehmann and Joseph 2009).

Typically, biochar with a high content of mineral ash has greater pH values than that with a lower content of ash. Between the temperatures of 300 and 600  C, organic acids and phenolic substances are created and alkali salts are formed and raise biochar pH (Shinogi and Kanri 2003). Biochar used for filtering water is usually alkaline and may have the effect of raising the pH of water to which it is filtrated. However, not all types of biochar are alkaline. The pH of biochar can range from 4 to 12 depending on the feedstock used and pyrolysis conditions (Bagreev et al. 2001; Lehmann 2007a, b). Further, it has been observed that a rise in pyrolysis temperature can increase the pH of some types of biochar. It was found that an increase in pyrolysis temperature from 310 to 850  C resulted in a rise of bagasseproduced biochar, the pH of which grew from 7.6 to 9.7 (Sohi et al. 2010). Although high pH biochar can be produced, it may have an impact on pH related to acid neutralizing the capacity of biochar.

4.4.3

The Major Mechanisms and Parameters for Controlling PTE Adsorption by Biochar

The direct mechanisms of PTE immobilization by biochar include, but are not limited to, fundamental chemical and largely ‘at-surface’ processes such as adsorption and complexation (Beesley et al. 2015). Hilber et al. (2017a, b) emphasized that the sorption capacity of biochar was high for cationic elements and low for anionic PTEs and metalloids such as As, Sb and Mo. Five mechanisms governing PTE sorption from water by biochar have been proposed (Li et al. 2017): (a) Electrostatic interaction between PTEs and the BC surface (physical sorption). (b) Cation exchange between PTEs and protons or alkaline PTEs on the BC surface (chemical sorption). (c) PTE complexation with functional groups and π electron-rich domain on the aromatic structure of BC. (d) PTE precipitation to form insoluble compounds. (e) Reduction in PTE species and the subsequent sorption of reduced PTE species. The mechanisms for PTE adsorption in biochar are based on the findings reported by Lindsay (1979), Sánchez-Polo & Rivera-Utrilla (2002), Cao et al. (2009), Uchimiya et al. (2010), Trakal et al. (2011) and Beesley et al. (2015) and are

4.5 Adsorption Behaviour of PTEs on Biochar

169

Table 4.3 Mechanisms promoting the adsorption of the selected potentially toxic elements on biochar PTE Cd

Major mechanism For a high CEC group, cation exchange was the predominant mechanism for Cd sorption

Minor mechanism Complexation with carboxyl groups is a minor mechanism for Cd sorption

Pb

Cation exchange with Ca and Mg at low pH Precipitation in BC with the high concentrations of phosphate and carbonate Complexation of Cr(III) with oxygen-containing functional groups

Complexation with functional groups

Cr (III)

Cr (VI)

Among various mechanisms, Cr(VI) reduction in Cr(III) followed by Cr(III) complexation with functional groups and is a major sorption mechanism for Cr(VI)

Cation exchange with Ca+ and Mg+ (more intense in the case of biosolids) –

Supplementary mechanism Based on lone pair electrons related to ‘graphene-like’ structures that would most likely drive Cd(II)-π bonding on biochar with a low charge and low O/C (low CEC biochar) –

Electrostatic attraction (higher intensity at higher solution pH) –

described in Table 4.3. CEC and the complexation of potentially toxic elements with oxygen-containing functional (carboxyl, hydroxyl, phenol and carbonyl) groups are among the main mechanisms for the adsorption of Cd, Pb and Cr on biochar. The conditions are highly relevant to biochar produced at a temperature of 450  C.

4.5

Adsorption Behaviour of PTEs on Biochar

To understand the extent and degree of adsorption favourability, Freundlich and Langmuir isotherms are often used. In the work by Wilson et al. (2003), a good fit to the Langmuir isotherm was observed regarding the data obtained in batch experiments on monitoring bone charcoal sorption behaviour of two cationic potentially toxic elements Cu and Zn. In the research done by Lu et al. (2011), the isotherm describing Pb2+ sorption behaviour of SDBC at different pH was well fit with the Freundlich equation. Inyang et al. (2012) used different isotherm equations to simulate the sorption isotherms of Pb on biochar produced from the anaerobically digested biomass. The Freundlich model best described Pb sorption on digested dairy waste biochar while Langmuir and Langmuir-Langmuir models best represented sorption data on the digested biochar of the whole sugar beet.

170

4.5.1

4 Sustainable Natural Materials Used for Adsorbing Pollutants from the Aqueous. . .

Freundlich Isotherms and Extended Adsorption Equilibrium

The extended Freundlich isotherm is used for representing the adsorption of potentially toxic elements from the solution contaminated with potentially toxic elements on biochar. The curvature and steepness of the isotherm is determined by Kf and n (Low and Lee 2000). The affinity of the adsorbent towards the uptake of the ions of potentially toxic elements is indicated by the value of n (Dada et al. 2013): when n ¼ 1, partition between two phases is independent of the concentration; when 1/n < 1, normal adsorption occurs; when 1/n > 1, cooperative adsorption occurs (Mohan and Karthikeyan 1997). When the value of n is in the range between unity and ten, the adsorption process is favourable (Goldberg 2005). A linear regression on logarithmic data is shown in Figs. 4.7, 4.8 and 4.9. Plots formed lnq vs. lnC. Figure 4.7 shows the obtained linear progressions that produced equations in the following way:

where qCd, qPb, qCu, qZn—the amount of the adsorbed potentially toxic elements per unit mass of biochar, mg/g; CCd, CCu, CPb, CZn—pollutant equilibrium concentration, mg/L. Figure 4.8 shows the obtained linear progressions that produced equations in the following way:

171 6.0 5.8 ln q, μg/g

5.4 5.2 5.0 4.8 4.6 4.4 4.2 4.0

3.0

6.4

3.2 3.4 3.6 ln CCd, μg/l

5.4 4.0

6.2

4.2 4.4 4.6 ln CPb, μg/l

4.8

6.0 ln q, μg/g

6.0 5.8 6.5 6.7 6.9 7.1 7.37.5 7.7 7.9 ln CCu, μg/l

5.8 5.6 5.4 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2 ln CZn, μg/l

5.8

6.2

5.6 5.4

ln q, µg/g

ln q, µg/g

6.0 5.2 5.0 4.8 3.9 7.0

4.1 4.3 ln CCd, µg/l

5.6 4.0

6.8

4.2 4.4 4.6 ln CPb, µg/l

4.8

ln q, µg/g

6.6

6.8 6.7 6.6 6.6

5.8

5.4

4.5

6.9 ln q, µg/g

Fig. 4.8 Freundlich isotherms: the adsorption of potentially toxic elements on biochar-derived (Betula pendula) biochar (square) and pine-derived (Pinus sylvestris L.) biochar (triangle) when the composition of the leaching solution is twofold value of MCL for the selected potentially toxic elements (Silinskaite 2014)

5.6

5.2

3.8

6.2 ln q, μg/g

Fig. 4.7 Freundlich isotherms: the adsorption of potentially toxic elements on biochar-derived (Betula pendula) biochar (square) and pine-derived (Pinus sylvestris L.) biochar (triangle) when the composition of the leaching solution is onefold value of MCL for the selected potentially toxic elements (Silinskaite 2014)

ln q, μg/g

4.5 Adsorption Behaviour of PTEs on Biochar

6.8 7.0 7.2 ln CCu, µg/l

7.4

6.4

6.2 7.0

7.2 7.4 7.6 ln CZn, µg/l

7.8

where qCd, qPb, qCu, qZn—the amount of the adsorbed potentially toxic elements per unit mass of biochar, mg/g; CCd, CCu, CPb, CZn—pollutant equilibrium concentration, mg/L. Figure 4.9 shows the obtained linear progressions that produced equations in the following way:

4 Sustainable Natural Materials Used for Adsorbing Pollutants from the Aqueous. . . 6.2

6.6 6.5 ln q, μg/g

6.0 5.8 5.6 5.0

5.1 5.1 5.3 ln CCd, μg/l

5.4

7.9

6.4 6.3 6.2

6.0

6.1 6.2 ln CPb, μg/l

6.3

8.2 8.0 ln CZn, μg/l

8.4

7.7 7.6

7.8

ln q, μg/g

ln q, μg/g

Fig. 4.9 Freundlich isotherms: the adsorption of potentially toxic elements on biochar-derived (Betula pendula) biochar (square) and pine-derived (Pinus sylvestris L.) biochar (triangle) when the composition of the leaching solution is fivefold value of MCL for the selected potentially toxic elements (Silinskaite 2014)

ln q, μg/g

172

7.7

7.5 7.4 7.3

7.6 7.1

7.2 7.3 7.4 ln CCu, μg/l

7.5

7.2 7.8

where qCd, qPb, qCu, qZn—the amount of the adsorbed potentially toxic elements per unit mass of biochar, mg/g; CCd, CCu, CPb, CZn—pollutant equilibrium concentration, mg/L. From isotherm models, the parameters were calculated as in the example below: log qCd ¼ 0:9052 log CCd þ 1:1783 ln K ¼ 1:178 K ¼ 3:249 1 ¼ 0:905 n n ¼ 1:1

4.5 Adsorption Behaviour of PTEs on Biochar

173

The approximate indicators of adsorption capacity K and adsorption intensity n of all isotherm equations are shown in Table 4.4. The values of n > 1 indicate the degree of nonlinearity between solution concentration and adsorption as the physical process (Desta 2013). In all cases, n is between 1 and 10, and thus the adsorption process was favourable. R2 values confirm that Freundlich isotherms fit the conducted experiments. A comparison of the parameters K and n of the Freundlich equation showed that the higher adsorption capacity of silver birch (Betula pendula) biochar was more frequent than the adsorption capacity of Scots pine (Pinus sylvestris L.) biochar. The expressions in the general form of the adsorption system for four-potentially toxic elements are obtained in Eqs. 4.24a–4.24d (Silinskaite 2014): 1 n

qCd ¼

Cd K Cd C Cd 1 nCd

Cu

Pb

1 nCu

Zn 1

1

ð4:24aÞ

1

ð4:24bÞ

Zn K Cd C Cd þ K Cu CCu þ K Pb C PbPb þ K Zn CZn 1 n

K Pb CPbCd

qPb ¼

þn 1 þn 1 þn 1

1 nCd

n

n

þn 1 þn 1 þn 1 Cu

Pb

1 nCu

Zn 1

Zn K Cd C Cd þ K Cu CCu þ K Pb C PbPb þ K Zn CZn 1 n

qCu ¼

Cd K Cu C Cu 1 nCd

n

þn 1 þn 1 þn 1 Cu

Pb

1 nCu

Zn

1 nPb

1 nZn

K Cd C Cd þ K Cu CCu þ K Pb C Pb þ K Zn CZn 1 n

qZn ¼

n

Cd K Zn C Zn 1 nCd

ð4:24cÞ

þn 1 þn 1 þn 1 Cu

1 nCu

Pb

Zn 1

1

Zn K Cd CCd þ K Cu C Cu þ K Pb C PbPb þ K Zn CZn n

ð4:24dÞ

n

where qCd, qPb, qCu, qZn—the amount of the adsorbed potentially toxic elements per unit mass of biochar, mg/g; KCd, KCu, KPb, KZn—the capacity of biochar for a PTE; CCd, CCu, CPb, CZn—pollutant equilibrium concentration, mg/L; nCd, nCu, nPb, nZn—the function of adsorption intensity. From expressions (Eqs. 4.24a–4.24d) and estimated parameters in the case of adsorption on Scots pine (Pinus sylvestris L.) biochar (when the initial concentration of a PTE is onefold MCL in the leaching solution), the extended Freundlich equations had the following expressions (Eqs. 4.25a–4.25d) (Silinskaite 2014): 1

qCd ¼

1

1

1

1

ð4:25aÞ

1

1

ð4:25bÞ

1:0 2:3 1:2 3:25C 1:1 Cd þ 1:86C Cu þ 2:92C Pb þ 14:0C Zn 1

qPb ¼

1 1 1 þ1:2 þ1:0 þ2:3

3:25C 1:1 Cd

1 1 1 þ1:2 þ1:0 þ2:3

2:92C1:1 Pb 1

1

1:0 2:3 1:2 3:25C 1:1 Cd þ 1:86C Cu þ 2:92C Pb þ 14:0C Zn

174

4 Sustainable Natural Materials Used for Adsorbing Pollutants from the Aqueous. . .

Table 4.4 Parameters for plotting Freundlich adsorption isotherms of the selected potentially toxic elements on biochar (Silinskaite 2014) Concentration of heavy metal ions in leaching solution Onefold value of MCL

Adsorbent Scots pine (Pinus sylvestris L.) biochar

Adsorbate Cd(II) Pb(II) Cu(II) Zn(II) Cd(II) Pb(II) Cu(II) Zn(II) Cd(II) Pb(II) Cu(II) Zn(II) Cd(II) Pb(II) Cu(II) Zn(II) Cd(II) Pb(II) Cu(II) Zn(II) Cd(II) Pb(II) Cu(II) Zn(II)

Silver birch (Betula pendula) biochar Twofold value of MCL

Scots pine (Pinus sylvestris L.) biochar Silver birch (Betula pendula) biochar

Fivefold value of MCL

Scots pine (Pinus sylvestris L.) biochar Silver birch (Betula pendula) biochar

1

qCu ¼

1 1 1 þ1:2 þ1:0 þ2:3

1:86C 1:1 Cu 1

1

1

3.249 2.919 1.859 14.034 4.911 4.490 58.236 25.682 5.382 3.765 2.302 23.222 5.233 2.365 128.715 1.034 2.216 1.289 41.087 107.018 5.042 2.846 2.208 34.203

1

ð4:25cÞ

1

1

ð4:25dÞ

1 1 1 þ1:2 þ1:0 þ2:3

14:0C 1:1 Zn 1

K

1

1:0 2:3 1:2 3:25C 1:1 Cd þ 1:86C Cu þ 2:92C Pb þ 14:0C Zn 1

qZn ¼

Estimated parameters of Freundlich isotherm 1/n n lnK 0.905 1.105 1.178 0.989 1.012 1.071 0.801 1.248 0.620 0.436 2.293 2.642 0.962 1.039 1.592 0.939 1.065 1.502 0.278 3.600 4.065 0.343 2.917 3.246 0.786 1.272 1.683 0.866 1.155 1.326 0.894 1.118 0.834 0.477 2.095 3.145 0.887 1.128 1.655 0.974 1.026 0.861 0.283 3.535 4.858 0.863 1.159 0.033 0.987 1.013 0.796 0.997 1.004 0.254 0.564 1.773 3.716 0.358 2.796 4.673 0.848 1.179 1.618 0.891 1.122 1.046 0.942 1.061 0.792 0.488 2.049 3.532

1:0 2:3 1:2 3:25C 1:1 Cd þ 1:86C Cu þ 2:92C Pb þ 14:0C Zn

In the case of adsorption on Silver birch (Betula pendula) biochar (when the initial concentration of a PTE is onefold MCL in the leaching solution), the extended Freundlich equations had the following expressions (Eqs. 4.26a–4.26d):

4.5 Adsorption Behaviour of PTEs on Biochar

175 1

qCd ¼

1

1

ð4:26aÞ

1

1

ð4:26bÞ

1

1

ð4:26cÞ

1

1

ð4:26dÞ

1 1 1 þ3:6 þ1:1 þ2:9

1

1

2:9 3:6 1:1 4:91C 1:0 Cd þ 58:2C Cu þ 4:49C Pb þ 25:7C Zn 1 1 1 þ3:6 þ1:1 þ2:9

58:2C 1:0 Cu 1

1

2:9 3:6 1:1 4:91C 1:0 Cd þ 58:2C Cu þ 4:49C Pb þ 25:7C Zn 1

qZn ¼

1

4:49C1:0 Pb 1

qCu ¼

1

2:9 3:6 1:1 4:91C 1:0 Cd þ 58:2C Cu þ 4:49C Pb þ 25:7C Zn 1

qPb ¼

1 1 1 þ3:6 þ1:1 þ2:9

4:91C 1:0 Cd

1 1 1 þ3:6 þ1:1 þ2:9

25:7C 1:0 Zn 1

1

2:9 1:1 3:6 4:91C 1:0 Cd þ 58:2C Cu þ 4:49C Pb þ 25:7C Zn

In the case of adsorption on Scots pine (Pinus sylvestris L.) biochar (when the initial concentration of a PTE is twofold MCL in the leaching solution), the extended Freundlich equations had the following expressions (Eqs. 4.27a–4.27d) (Silinskaite 2014): 1

qCd ¼

1

1

ð4:27aÞ

1

1

ð4:27bÞ

1

1

ð4:27cÞ

1

1

ð4:27dÞ

1 1 1 þ1:1 þ1:2 þ2:1

1

1

1:1 1:2 2:1 5:38C 1:3 Cd þ 2:30C Cu þ 3:77C Pb þ 23:2C Zn 1 1 1 þ1:1 þ1:2 þ2:1

2:30C 1:3 Cu 1

1

1:1 1:2 2:1 5:38C 1:3 Cd þ 2:30C Cu þ 3:77C Pb þ 23:2C Zn 1

qZn ¼

1

3:77C1:3 Pb 1

qCu ¼

1

1:1 1:2 2:1 5:38C 1:3 Cd þ 2:30C Cu þ 3:77C Pb þ 23:2C Zn 1

qPb ¼

1 1 1 þ1:1 þ1:2 þ2:1

5:38C 1:3 Cd

1 1 1 þ1:1 þ1:2 þ2:1

23:2C 1:3 Zn 1

1

1:1 1:2 2:1 5:38C 1:3 Cd þ 2:30C Cu þ 3:77C Pb þ 23:2C Zn

In the case of adsorption on Silver birch (Betula pendula) biochar (when the initial concentration of a PTE is twofold MCL in the leaching solution), the extended Freundlich equations had the following expressions (Eqs. 4.28a–4.28d): 1

qCd ¼

1 1 1 þ3:5 þ1:0 þ1:2

5:23C 1:1 Cd 1

1

1

1

3:5 1:0 1:2 5:23C1:1 Cd þ 129C Cu þ 2:37C Pb þ 1:03C Zn

ð4:28aÞ

176

4 Sustainable Natural Materials Used for Adsorbing Pollutants from the Aqueous. . . 1

qPb ¼

1

1

1

ð4:28bÞ

1

1

ð4:28cÞ

1

ð4:28dÞ

1 1 1 þ3:5 þ1:0 þ1:2

129C 1:1 Cu 1

1

3:5 1:0 1:2 5:23C1:1 Cd þ 129C Cu þ 2:37C Pb þ 1:03C Zn 1 1 1 þ3:5 þ1:0 þ1:2

1

qZn ¼

1

3:5 1:0 1:2 5:23C1:1 Cd þ 129C Cu þ 2:37C Pb þ 1:03C Zn 1

qCu ¼

1 1 1 þ3:5 þ1:0 þ1:2

2:37C1:1 Pb

1:03C 1:1 Zn 1

1

1

3:5 1:0 1:2 5:23C 1:1 Cd þ 129C Cu þ 2:37C Pb þ 1:03C Zn

In the case of adsorption on Scots pine (Pinus sylvestris L.) biochar (when the initial concentration of a PTE is fivefold MCL in the leaching solution), the extended Freundlich equations had the following expressions (Eqs. 4.29a–4.29d) (Silinskaite 2014): 1 1 1 þ1:8 þ1:0 þ2:8

1

qCd ¼

2:22C 1:0 Cd 1

1

1

qPb ¼

ð4:29aÞ

1

1

ð4:29bÞ

1

1

ð4:29cÞ

1

1

ð4:29dÞ

1 1 1 þ1:8 þ1:0 þ2:8

1

1

1:8 1:0 2:8 2:22C1:0 Cd þ 41:1C Cu þ 1:29C Pb þ 107C Zn 1 1 1 þ1:8 þ1:0 þ2:8

41:1C 1:0 Cu 1

1

1:8 1:0 2:8 2:22C1:0 Cd þ 41:1C Cu þ 1:29C Pb þ 107C Zn 1

qZn ¼

1

1:29C1:0 Pb 1

qCu ¼

1

1:8 1:0 2:8 2:22C1:0 Cd þ 41:1C Cu þ 1:29C Pb þ 107C Zn

1 1 1 þ1:8 þ1:0 þ2:8

107C 1:0 Zn 1

1

1:8 1:0 2:8 2:22C 1:0 Cd þ 41:1C Cu þ 1:29C Pb þ 107C Zn

In the case of adsorption on Silver birch (Betula pendula) biochar (when the initial concentration of a PTE is fivefold MCL in the leaching solution), the extended Freundlich equations had the following expressions (Eqs. 4.30a–4.30d): 1

qCd ¼

1

1

1

1

ð4:30aÞ

1

1

ð4:30bÞ

2:0 1:1 1:1 5:04C 1:2 Cd þ 2:21C Cu þ 2:85C Pb þ 34:2C Zn 1

qPb ¼

1 1 1 þ1:1 þ1:1 þ2:0

5:04C 1:2 Cd

1 1 1 þ1:1 þ1:1 þ2:0

2:85C1:2 Pb 1

1

2:0 1:1 1:1 5:04C 1:2 Cd þ 2:21C Cu þ 2:85C Pb þ 34:2C Zn

4.5 Adsorption Behaviour of PTEs on Biochar

177 1

qCu ¼

1

1

1

1

ð4:30cÞ

1

1

ð4:30dÞ

2:0 1:1 1:1 5:04C 1:2 Cd þ 2:21C Cu þ 2:85C Pb þ 34:2C Zn 1

qZn ¼

1 1 1 þ1:1 þ1:1 þ2:0

2:21C 1:2 Cu

1 1 1 þ1:1 þ1:1 þ2:0

34:2C 1:2 Zn 1

1

2:0 1:1 1:1 5:04C 1:2 Cd þ 2:21C Cu þ 2:85C Pb þ 34:2C Zn

A comparison of the adsorption capacity of both types of biochar samples shows that the higher adsorption capacity of silver birch (Betula pendula) biochar was more frequent than the adsorption capacity of Scots pine (Pinus sylvestris L.) biochar.

4.5.2

Redlich–Peterson Isotherms and Extended Adsorption Equilibrium

Three  constants  (KJ, bJ, and g) of the isotherm were evaluated from the linear plot of CS ln K J q  1 vs. ln(SC). Constant KJ was calculated using the solver add-in of S

Microsoft Excel®. A linear regression on logarithmic data is shown in Figs. 4.10, 4.11 and 4.12. Figure 4.10 shows the obtained linear progressions that produced equations in the following way:

7.2 6.7

.

ln ((K C/q-1), μg/g

.

8.2 7.7

.

6.2 3.2 3.3 3.4 3.5 3.6 3.7 ln CCd, μg/l 7.8 7.8 7.6 7.4 7.2 7.0 5.8 5.9 6.0 6.1 6.2 6.3 ln CCu, μg/l

8.9 8.7 8.5 8.3 8.1 7.9 7.7 7.5 4.2

4.3 4.4 4.5 ln CPb, μg/l

4.6

5.5

6.1

8.0 ln ((K C/q-1), μg/g

ln ((K C/q-1), μg/g

8.7

ln ((K C/q-1), μg/g

Fig. 4.10 Redlich–Peterson isotherms: the adsorption of potentially toxic elements on biochar-derived (Betula pendula) biochar (square) and pine-derived (Pinus sylvestris L.) biochar (triangle) when the composition of the leaching solution is onefold value of MCL for the selected potentially toxic elements (Silinskaite 2014)

.

7.8 7.6 7.4 7.2 7.0 5.3

5.7 5.9 ln CZn, μg/l

178

4 Sustainable Natural Materials Used for Adsorbing Pollutants from the Aqueous. . .

where qCd, qPb, qCu, qZn—the amount of the adsorbed potentially toxic elements per unit mass of biochar, mg/g; CCd, CCu, CPb, CZn—pollutant equilibrium concentration, mg/L. Figure 4.11 shows the obtained linear progressions that produced equations in the following way:

where qCd, qPb, qCu, qZn—the amount of the adsorbed potentially toxic elements per unit mass of biochar, mg/g; CCd, CCu, CPb, CZn—pollutant equilibrium concentration, mg/L. Figure 4.12 shows the obtained linear progressions that produced equations in the following way:

.

8.5 8.4 8.3 8.2 8.1 8.0 7.9 7.8 7.7 3.9 4.0 4.1 4.2 4.3 4.4 ln CCd, μg/l

179

ln ((K C/q-1), μg/g

ln ((K C/q-1), μg/g

4.5 Adsorption Behaviour of PTEs on Biochar

.

8.70 8.65 8.60 8.55 8.50 5.0

.

ln ((K C/q-1), μg/g

ln ((K C/q-1), μg/g

8.50 8.45 8.40 8.35

.

8.30 8.25

8.20 6.3 6.4 6.5 6.6 6.7 6.8 ln CZn, μg/l

9.2 9.1 9.0 8.9 8.8 8.7 8.6 8.5 8.4 8.3 6.7

5.2 5.1 ln CPb, μg/l

5.3

6.8 6.9 ln CCu, μg/l

7.0

Fig. 4.11 Redlich–Peterson isotherms: the adsorption of potentially toxic elements on biocharderived (Betula pendula) biochar (square) and pine-derived (Pinus sylvestris L.) biochar (triangle) when the composition of the leaching solution is twofold value of MCL for the selected potentially toxic elements (Silinskaite 2014)

ln ((K C/q-1), μg/g

.

ln ((K C/q-1), μg/g

ln ((K C/q-1), μg/g

ln ((K C/q-1), μg/g

9.0 8.9 8.8 8.7 8.6 . 8.5 8.4 8.3 8.2 8.1 4.9 5.0 5.1 5.2 5.3 5.4 ln CCd, μg/l 10.3 10.2 10.1 10.0 9.9 9.8 . 9.7 9.6 9.5 9.4 9.3 7.8 7.9 7.6 7.7 ln CCu, μg/l

.

9.6 9.4 9.2 9.0 8.8 8.6 8.4 8.2 5.9

6.0 6.1 6.2 6.3 ln CPb, μg/l

6.4

7.4 7.5 7.6 ln CZn, μg/l

7.7

9.5 9.3 9.1 8.9 8.7 8.5 7.3

Fig. 4.12 Redlich–Peterson isotherms: the adsorption of potentially toxic elements on biocharderived (Betula pendula) biochar (square) and pine-derived (Pinus sylvestris L.) biochar (triangle) when the composition of the leaching solution is fivefold value of MCL for the selected potentially toxic elements (Silinskaite 2014)

180

4 Sustainable Natural Materials Used for Adsorbing Pollutants from the Aqueous. . .

where qCd, qPb, qCu, qZn—the amount of the adsorbed potentially toxic elements per unit mass of biochar, mg/g; CCd, CCu, CPb, CZn—pollutant equilibrium concentration, mg/L. Redlich–Peterson constants K, b and β were calculated from linear plots (Figs. 4.10, 4.11 and 4.12), and the obtained data are presented in Table 4.5. The extended expressions of Redlich–Peterson in the general form of the adsorption system for four-potentially toxic elements are obtained in Eqs. 4.31a–4.31d: qCd ¼ qCu ¼ qPb ¼ qZn ¼

1þ

β bCd C CdCd

K Cd CCd β β β þ bCu CCuCu þ bPb C PbPb þ bZn CZnZn

ð4:31aÞ

1þ

β bCd C CdCd

K Cu CCu β β β þ bCu CCuCu þ bPb C PbPb þ bZn CZnZn

ð4:31bÞ

1þ

β bCd C CdCd

K Pb CPb β β β þ bCu CCuCu þ bPb C PbPb þ bZn CZnZn

ð4:31cÞ

1þ

β bCd CCdCd

K Zn CZn β β β þ bCu C CuCu þ bPb C PbPb þ bZn CZnZn

ð4:31dÞ

where qCd, qPb, qCu, qZn—the amount of the adsorbed potentially toxic elements per unit mass of biochar, mg/g; CCd, CCu, CPb, CZn; bCd, bCu, bPb, bZn, βCd, βPb, βCu, βZn—Redlich–Peterson constants. From expressions and estimated Redlich–Peterson constants (Table 4.2), in the case of adsorption on Scots pine (Pinus sylvestris L.) biochar (when the initial concentration of a PTE is onefold MCL in the leaching solution), the extended Redlich–Peterson equations had the following expressions (Eqs. 4.32a–4.32d): qCd ¼

2:12C Cd 0:79 0:76 0:91 1 þ 1:52C0:88 þ 3:14C Cd Cu þ 1:77C Pb þ 2:92C Zn

ð4:32aÞ

4.5 Adsorption Behaviour of PTEs on Biochar

181

Table 4.5 Parameters for plotting Redlich–Peterson adsorption isotherms of the selected potentially toxic elements on biochar (Silinskaite 2014) Concentration of heavy metal ions in leaching solution Onefold value of MCL

Adsorbent Scots pine (Pinus sylvestris L.) biochar

Silver birch (Betula pendula) biochar

Twofold value of MCL

Scots pine (Pinus sylvestris L.) biochar

Silver birch (Betula pendula) biochar

Fivefold value of MCL

Scots pine (Pinus sylvestris L.) biochar

Silver birch (Betula pendula) biochar

Adsorbate Cd(II) Pb(II) Cu(II) Zn(II) Cd(II) Pb(II) Cu(II) Zn(II) Cd(II) Pb(II) Cu(II) Zn(II) Cd(II) Pb(II) Cu(II) Zn(II) Cd(II) Pb(II) Cu(II) Zn(II) Cd(II) Pb(II) Cu(II) Zn(II)

Estimated Redlich– Peterson constants K b β 2.12 1.52 0.879 12.3 1.77 0.799 5.02 3.14 0.761 7.31 2.92 0.912 6.03 1.82 0.882 8.31 1.94 0.821 6.22 2.30 0.791 10.2 2.92 0.895 10.1 2.01 0.795 10.3 2.02 0.712 8.44 2.29 0.718 8.96 2.62 0.791 8.36 1.95 0.800 11.3 1.99 0.812 6.12 3.22 0.782 12.3 2.34 0.766 14.1 1.97 0.784 15.0 1.92 0.813 7.93 2.69 0.807 10.2 3.14 0.792 11.3 2.01 0.833 18.1 2.15 0.831 17.3 1.97 0.793 14.1 2.81 0.844

12:3CCu 0:76 0:91 þ 3:14C0:79 Cu þ 1:77C Pb þ 2:92C Zn

ð4:32bÞ

qPb ¼

5:02C Pb 0:79 0:76 0:91 1 þ 1:52C0:88 þ 3:14C Cd Cu þ 1:77C Pb þ 2:92C Zn

ð4:32cÞ

qZn ¼

7:31CZn 0:79 0:76 0:91 1 þ 1:52C 0:88 þ 3:14C Cd Cu þ 1:77C Pb þ 2:92C Zn

ð4:32dÞ

qCu ¼

1þ

1:52C 0:88 Cd

In the case of adsorption on Silver birch (Betula pendula) biochar (when the initial concentration of a PTE is onefold MCL in the leaching solution), the extended Redlich–Peterson equations had the following expressions (Eqs. 4.33a–4.33d):

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4 Sustainable Natural Materials Used for Adsorbing Pollutants from the Aqueous. . .

qCd ¼

6:03C Cd 0:79 0:82 0:9 1 þ 1:52C0:88 þ 2:30C Cd Cu þ 1:94C Pb þ 2:92C Zn

ð4:33aÞ

qCu ¼

6:22CCu 0:79 0:82 0:9 1 þ 1:52C 0:88 þ 2:30C Cd Cu þ 1:94C Pb þ 2:92C Zn

ð4:33bÞ

8:31C Pb 0:82 0:9 þ 2:30C0:79 Cu þ 1:94C Pb þ 2:92C Zn

ð4:33cÞ

10:2CZn 0:79 0:82 0:9 1 þ 1:52C 0:88 þ 2:30C Cd Cu þ 1:94C Pb þ 2:92C Zn

ð4:33dÞ

qPb ¼ qZn ¼

1þ

1:52C0:88 Cd

The extended Redlich–Peterson equations had the following expressions for adsorption on Scots pine (Pinus sylvestris L.) biochar (when the initial concentration of a PTE is twofold MCL in the leaching solution) (Eqs. 4.34a–4.34d): qCd ¼

10:1C Cd 0:72 0:71 0:79 1 þ 2:01C0:8 þ 2:29C Cd Cu þ 2:02C Pb þ 2:62C Zn

ð4:34aÞ

qCu ¼

8:44CCu 0:72 0:71 0:79 1 þ 2:01C 0:8 þ 2:29C Cd Cu þ 2:02C Pb þ 2:62C Zn

ð4:34bÞ

1þ

2:01C0:8 Cd

10:3C Pb 0:71 0:79 þ 2:29C 0:72 Cu þ 2:02C Pb þ 2:62C Zn

ð4:34cÞ

1þ

2:01C 0:8 Cd

8:96CZn 0:71 0:79 þ 2:29C 0:72 Cu þ 2:02C Pb þ 2:62C Zn

ð4:34dÞ

qPb ¼ qZn ¼

The extended Redlich–Peterson equations had the following expressions for adsorption on Silver birch (Betula pendula) biochar (when the initial concentration of a PTE is twofold MCL in the leaching solution) (Eqs. 4.35a–4.35d) (Komkienė and Baltrėnaitė 2016): 8:36C Cd 0:81 0:77 þ 3:22C 0:78 Cu þ 1:99C Pb þ 2:34C Zn

ð4:35aÞ

qCu ¼

6:12CCu 0:78 0:81 0:77 1 þ 1:95C 0:8 þ 3:22C Cd Cu þ 1:99C Pb þ 2:34C Zn

ð4:35bÞ

qPb ¼

11:3C Pb 0:78 0:81 0:77 1 þ 1:95C0:8 þ 3:22C Cd Cu þ 1:99C Pb þ 2:34C Zn

ð4:35cÞ

qZn ¼

12:3CZn 0:78 0:81 0:77 1 þ 1:95C 0:8 þ 3:22C Cd Cu þ 1:99C Pb þ 2:34C Zn

ð4:35dÞ

qCd ¼

1þ

1:95C0:8 Cd

From expressions and estimated Redlich–Peterson constants (Table 4.2), in the case of adsorption on Scots pine (Pinus sylvestris L.) biochar (when the initial

4.5 Adsorption Behaviour of PTEs on Biochar

183

concentration of a PTE is fivefold MCL in the leaching solution), the extended Redlich–Peterson equations had the following expressions (Eqs. 4.36a–4.36d): 14:1C Cd 0:81 0:81 0:79 1 þ 1:97C0:78 þ 2:69C Cd Cu þ 1:92C Pb þ 3:14C Zn

ð4:36aÞ

7:93CCu 0:81 0:79 þ 2:69C0:81 Cu þ 1:92C Pb þ 3:14C Zn

ð4:36bÞ

qPb ¼

15:0C Pb 0:81 0:81 0:79 1 þ 1:97C0:78 þ 2:69C Cd Cu þ 1:92C Pb þ 3:14C Zn

ð4:36cÞ

qZn ¼

10:2CZn 0:81 0:81 0:79 1 þ 1:97C 0:78 þ 2:69C Cd Cu þ 1:92C Pb þ 3:14C Zn

ð4:36dÞ

qCd ¼ qCu ¼

1þ

1:97C 0:78 Cd

The extended Redlich–Peterson equations had the following expressions for adsorption on Silver birch (Betula pendula) biochar (when the initial concentration of a PTE is fivefold MCL in the leaching solution) (Eqs. 4.37a–4.37d) (Komkienė and Baltrėnaitė 2016): qCd ¼

11:3C Cd 0:79 0:83 0:84 1 þ 2:01C0:83 þ 1:97C Cd Cu þ 2:15C Pb þ 2:81C Zn

ð4:37aÞ

qCu ¼

17:3CCu 0:79 0:83 0:84 1 þ 2:01C 0:83 þ 1:97C Cd Cu þ 2:15C Pb þ 2:81C Zn

ð4:37bÞ

18:1C Pb 0:83 0:84 þ 1:97C 0:79 Cu þ 2:15C Pb þ 2:81C Zn

ð4:37cÞ

14:1CZn 0:79 0:83 0:84 1 þ 2:01C 0:83 þ 1:97C Cd Cu þ 2:15C Pb þ 2:81C Zn

ð4:37dÞ

qPb ¼ qZn ¼

1þ

2:01C0:83 Cd

A comparison of the adsorption capacity of both types of biochar samples showed that the higher adsorption capacity of silver birch (Betula pendula) biochar was more frequent (1 of 2 times) than the adsorption capacity of Scots pine (Pinus sylvestris L.) biochar.

4.5.3

A Comparison of the Results of Freundlich and Redlich Peterson Isotherms

To test the best-fitting isotherms to experimental data, the coefficient of determination (R2) of all isotherms was estimated. The values of R2 are shown below (Table 4.6).

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4 Sustainable Natural Materials Used for Adsorbing Pollutants from the Aqueous. . .

Table 4.6 A comparison of the estimated R2 of Freundlich and Redlich–Peterson isotherms (Silinskaite 2014) Concentration of heavy metal ions in leaching solution Onefold value of MCL

Adsorbent Scots pine (Pinus sylvestris L.) biochar Silver birch (Betula pendula) biochar

Twofold value of MCL

Scots pine (Pinus sylvestris L.) biochar Silver birch (Betula pendula) biochar

Fivefold value of MCL

Scots pine (Pinus sylvestris L.) biochar Silver birch (Betula pendula) biochar

Adsorbate Cd(II) Pb(II) Cu(II) Zn(II) Cd(II) Pb(II) Cu(II) Zn(II) Cd(II) Pb(II) Cu(II) Zn(II) Cd(II) Pb(II) Cu(II) Zn(II) Cd(II) Pb(II) Cu(II) Zn(II) Cd(II) Pb(II) Cu(II) Zn(II)

Estimated R2 of Freundlich isotherm 0.947 0.969 0.993 0.987 0.991 0.991 0.993 0.995 0.973 0.979 0.987 0.914 0.956 0.985 0.969 0.924 0.992 0.932 0.950 0.976 0.940 0.969 0.832 0.972

Estimated R2 of Redlich–Peterson isotherm 0.843 0.878 0.987 0.988 0.863 0.855 0.831 0.989 0.905 0.972 0.795 0.944 0.949 0.986 0.966 0.965 0.907 0.979 0.761 0.973 0.821 0.553 0.925 0.936

Due to a higher coefficient of determination, better (in 3 from 4 cases) fit was obtained by Freundlich isotherms as compared with Redlich–Peterson linear equations: – In all cases, the Freundlich isotherm better fit experimental data on Cd (II) adsorption. – Freundlich and Redlich–Peterson isotherms equally (1 of 2 times) fit experimental data on Pb(II) adsorption. – In 7 of 8 times the Freundlich isotherm better fit experimental data on Cu (II) adsorption. – In 5 of 8 times the Redlich–Peterson isotherm better fit experimental data on Zn (II) adsorption. The maximum adsorption capacity of Cd(II) on Scots pine (Pinus sylvestris L.) biochar at a concentration of twofold value of MCL was 0.65 and 2.4 times higher than that at the concentrations of onefold and fivefold values of MCL, respectively.

4.6 The Sustainable Role of Biochar

185

A comparison of the adsorption capacity of Cd(II) on Silver birch (Betula pendula) biochar showed that differences were slighter: only 6% and 4% higher than those at the concentrations of onefold and fivefold values of MCL, respectively. The adsorption capacity of Pb(II) on Silver birch (Betula pendula) and Scots pine (Pinus sylvestris L.) biochar varied and made 1.29–3.77 and 2.37–4.49 μg/g, respectively. The maximum reached adsorption capacity was that of Cu(II) on Silver birch (Betula pendula) biochar (128.7 μg/g) and that of Zn(II) on Scots pine (Pinus sylvestris L.) biochar (107.0 μg/g) (Komkienė and Baltrėnaitė 2016). As for the assessed adsorption capacity, the most frequent selectivity sequence of adsorbing the ions of potentially toxic elements on Scots pine (Pinus sylvestris L.) biochar is as follows: Zn(II) > Cd(II) > Pb(II) > Cu(II). In the sequence, each PTE to the left of the previous one had higher adsorption selectivity than the one to the right, i.e. the adsorption of zinc was optimum. The selectivity sequence of adsorbing the ions of potentially toxic elements on Silver birch (Betula pendula) biochar took the form of Cu(II) > Cd(II) > Pb(II) > Zn(II).

4.6

The Sustainable Role of Biochar

The International Biochar Initiative (IBI) states that ‘Large amounts of agricultural, municipal and forestry biomass are currently burned or left to decompose and release CO2 and methane into the atmosphere. Using only 27% of the world’s crop and forestry waste (the portion of waste not currently used for anything else) for biochar, could by 2030 sequester 0.25 gigatons of carbon a year from biochar alone’. Agricultural and/or municipal biomass left for decomposition also can pollute the local ground and surface waters. Using these materials to make biochar removes them from the pollution cycle, but biochar can be obtained as a by-product of producing energy from this biomass. Moreover, Hans-Peter Schmidt identified 55 ways of employing biochar in different fields (Schmidt 2012a, b) such as animal farming (e.g. as a silage agent, feed additive/supplement, litter additive), building sector (e.g. for insulation, the decontamination of the air and earth foundations, humidity regulation), biogas production (e.g. as biomass additive or for treating biogas slurry), the treatment of wastewater and drinking water (e.g. for micro- or macro-filters), metallurgy (e.g. metal reduction), cosmetics (e.g. for manufacturing soap, skin-cream, therapeutic bath additives) and textile production (e.g. fabric additive for functional underwear, thermal insulation). On account of a wide range of biochar applications and different forms of production technology, quality control is crucially important. That is the reason why the European Biochar Foundation has developed the European Biochar Certificate (EBC). The intention of the European Biochar Foundation in issuing guidelines on how to gain biochar certification is to introduce a control mechanism based on the latest research and practices. The biochar certificate aims to enable and guarantee sustainable biochar production, provides firm state-ofthe-art knowledge transfer as a sound basis for future legislation and is introduced to

186

4 Sustainable Natural Materials Used for Adsorbing Pollutants from the Aqueous. . .

prevent and hinder misuse or dangers from the start as long as no ‘special interests’ are calling for exceptions (e.g. cutting down native forests to produce biochar). It is introduced to give customers a reliable quality basis while giving producers the opportunity of proving that their product meets well-defined quality standards (Schmidt 2012a, b). The European Cooperation in Science and Technology (COST) has identified biochar as an option for sustainable resource management (COST 2011). Food and Agriculture COST Action TD1107 connects scattered European Biochar research to enable the quick implementation of intelligent material flow management systems. Objectives include the assessment of harmonization of biochar production and characterization, environmental impact (evaluation of biochar benefits versus risks), knowledge expansion and handling and life cycle assessment. There are four working groups that focus on (1) biochar production and characterization; (2) land use management; (3) economic and life cycle analyses and (4) environmental impact (COST 2011). It is stated that ‘Innovative Biochar strategies can help the EU mitigating greenhouse gases while industries and farmers benefit from new markets, opportunities and the use of the improved soils, e.g. for biofuel production without endangering food supply’. An increasing interest in the beneficial application of biochar has opened up multidisciplinary areas for science and engineering. The potential biochar applications include carbon sequestration, soil fertility improvement, pollution remediation and agricultural by-product/ waste recycling. Biochar can be considered as an adsorbent for managing contaminated water. Management methods that tend to protect the beneficial uses of water are understood as – Procedures and concepts undertaken to reduce adverse effects related to wet weather impacts, particularly in the case of pollutant discharge into the environment. – Methods for the beneficial use of runoff. – Consideration that tend to improve the entire performance of the urban drainage system. Following the analysis of foreign practices, it can be concluded that many countries (e.g. USA, UK, Germany, Estonia) are aware of the influence of surface water on aquatic ecosystems and the environment and manage surface runoff. Each country, regarding factors in the administrative division of the area, central and local government division, etc., determines an acceptable surface runoff management scheme (Hvitved-Jacobsen et al. 2009).

Chapter 5

Biotechnology as Sustainable Environmental Protection Technology

In this chapter the third level of sustainability of environmental protection technologies is presented with the example of biological treatment of air. The major principles and applications of the method of biological air treatment, the loadings used, their characteristics and influence on air cleaning effectiveness, as well as the analysis of biological air treatment facilities and their influence on air cleaning effectiveness are discussed in this chapter. The method used in the study of physical and aerodynamic characteristics of the loads includes the factors supporting the activities of microorganisms oxidizing volatile compounds found in the biological air treatment systems and their characteristics. Theory of biological treatment principles is analysed and the models describing biofiltration processes and the simulation programs of the processes are presented.

5.1

The Principles and Application of the Biological Air Treatment Method

The polluted living and working environment is one of the key environmental issues in Lithuania and in the majority of other countries. The main sources of polluting the air with volatile organic compounds include oil refineries and the manufactures of furniture, varnish, paints, food and plastic products. The technological processes taking place in the industrial companies release benzene, toluene, xylene, hydrogen sulphide, ammonia and other volatile compounds. The problem of removing volatile organic (e.g. acetone (C3H6O), xylene (C8H10)) and inorganic (ammonia (NH3)) pollutants has always remained a burning issue. The emissions of the above-mentioned pollutants from anthropogenic sources are strictly regulated as they remain high enough. Xylene is one of the four volatile organic compounds that overall make 59% (in terms of weight) of all gaseous pollutants emitted into the environment from oil refineries (Barona et al. 2005). © Springer Nature Switzerland AG 2020 P. Baltrėnas, E. Baltrėnaitė, Sustainable Environmental Protection Technologies, https://doi.org/10.1007/978-3-030-47725-7_5

187

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5 Biotechnology as Sustainable Environmental Protection Technology

Along with this group, xylene is included in the list of regulated harmful air pollutants. The Clean Air Act Amendments provide xylene is integrated into the European Pollutant Release and Transfer Register (E-PRTR). Ammonia emissions remain important on a large scale and are one of the EU-set criteria for evaluating environmental quality. For the period 1990–2010, ammonia concentrations decreased by 28% in the EU Member States; however, in 2010, agricultural activity remained as the main source of ammonia emissions and resulted in around 94% of releases. Acetone is intensively produced industrially, enters the environment from natural sources and is known as a compound harmful to human health and the environment. In order to regulate acetone emissions, technologies for removing acetone from the air were considered in industrial plants (Rene et al. 2010a, b). Biotechnologies for reducing the emissions of the above-mentioned pollutants concentrate on biofiltration—a relatively simple and effective method. Biofiltration uses microorganisms that survive on the substrate of the packing material and decompose pollutants. The advantages of this process involve the effectiveness of reducing the low concentrations of volatile organic pollutants, the diversity of pollutants (Gallastegui et al. 2011), relatively low operating costs (Devinny et al. 1999) and the absence of secondary pollution (Devinny et al. 1999). The biofiltration process is widely applied in chemical industry, domestic and industrial wastewater treatment plants, composting equipment, the production of timber products and painting and surface coating processes. As for European chemical industry, more than 600 companies apply biofiltration in practice. Biofiltration, as biotechnology, is an effective instrument for reducing pollutant concentrations, which helps with addressing the problem of making neutral the odours emitted by pollutants. The pollutants are transferred by diffusion and advection from the gas phase to the biofilm in the liquid phase. For a more in-depth analysis of biofiltration, the integrated system for the introduced process comprises diffusion in the gas phase, solubility and reaction—in the liquid phase, diffusion into pores, adsorption on the substrate of the packing material and biomass degradation (Baltrėnas et al. 2015a, b, c) (Fig. 5.1). The microorganisms involved in the biodegradation process oxidize organic compounds into CO2 and H2O and increase biomass. • Odour-emitting hydrogen sulphide (Thiobacillus microorganisms are particularly active) is oxidized by microorganisms to odourless sulphate (Eq. 5.1): þ H2 S þ 2O2 ! SO2 4 þ 2H

ð5:1Þ

• Ammonia dissolved in water is oxidized to odourless nitrate (Formulas 5.2 and 5.3):  NH3 þ H2 O ! NHþ 4 þ OH

ð5:2Þ

5.1 The Principles and Application of the Biological Air Treatment Method

189

Air flow format Biofilm boundary layer

Advection Variations in the pollutant stage

x

z Pollutant diffusion

Boundary of the packing material

Dispersion Variations in the oxygen stage

Adsorption Oxygen diffusion

Biofilm formation

Biodegradation

PROCESSES IN THE BIOFILTER

Water evaporation

Fig. 5.1 Processes taking place in the biofilter (according to Devinny and Ramesh 2005) þ 2NH4 þ 3O2 ! 2NO 3 þ 8H

ð5:3Þ

• Bacteria oxidize volatile organic compounds to carbon dioxide and water (Eq. 5.4): VOC0 s þ O2 ! CO2 þ H2 O

ð5:4Þ

The efficacy of the biological air treatment process depends on the crops of the microorganisms proliferating in the bio-medium. A growth in microorganisms can be achieved using rich nutrients applying the primary air treatment method supplying pollutants to the biofilter and activating microorganisms. The microorganisms oxidizing carbohydrates are an important group of the organisms involved in the cycle of carbon metabolism. Microorganisms can utilize all organic and inorganic carbon compounds during the metabolism process. Bacteria and micromycetes are the most important in this group, and bacteria make the major part. They can accept various types of carbohydrates from the medium, and their life cycle is often short. The most commonly found strains of Arthrobacter, Acinetobacter, Pseudomonas, Bacillus, Flavobacterium, Mycobacterium, Micrococcus and Rhodococcus are among the bacteria that can oxidize carbohydrates. The microorganisms of more than 70 strains decompose carbohydrates (Jankevičius

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5 Biotechnology as Sustainable Environmental Protection Technology

Fig. 5.2 A comparison of the methods for removing volatile compounds according to the concentration of the supplied pollutant and air traffic flow (Deshusses and Cox 1999a, b; Zagorskis 2009)

Air traffic flow m3/h 1000000 Biofiltration 100000 Adsorption 10000 Adsorption (including regeneration)

1000

Thermal or catalytic oxidation Ionization

Adsorption 100

(with no regeneration)

0.1

Concentration 1

10 100 Pollutant concentration, g/m3

and Liužinas 2003; Malhautier et al. 2005a, b; Liu et al. 2005). There are a number of strains that can decompose carbohydrates present among micromycetes. Frequently found types of micromycetes involve Penicillium, Aspergillus, Cladosporium, Alternaria, Botrytis, Fusarium and Mucor (Lugauskas et al. 1997). Traditional biofilters are relatively cheap (in both cases of capital and operational expenditures), require little energy and maintenance as well as are easy to service and reliable; they are characteristic of the constant decomposition rates of pollutants, and the products of the initiated reaction are non-hazardous compounds. The drawbacks of the employed equipment include considerable space occupied by the device, low effectiveness at the high concentrations of pollutants and more complex humidity control and pH during the process (Baltrėnas and Vaiškūnaitė 2002a, b, 2003a, b, 2004). Figure 5.2 shows that the biofiltration method for removing pollutants can be used under different pollutant concentrations varying from 0.01 to 10 g/m3. From an economic point of view, it is more rational to use biological air treatment at the pollutant concentration up to 1 g/m3 (Leethochawalit et al. 2001). In practice, installing biofilters is not a complex problem; moreover, the cost of installing and maintaining them is low and their lifetime is quite long (up to 10 years). The filters have a relatively large area of the bio-medium with the porosity of 40–60% when the bio-medium is full of microorganisms. All this assists with achieving high air treatment effectiveness (up to 90–99%) (Krishayya et al. 1999; Wani et al. 1999. The main indicators defining the efficiency of the biofilter cover treatment effectiveness, productivity (or removal capacity) and its dependence on the loaded pollutants, the duration of the contact between the pollutant and the packing material. The activity of microorganisms is mainly characterized by the biodegradation rate of the pollutant and the biodegradation rate constant. The below formulas are used for calculating the above-introduced parameters.

5.1 The Principles and Application of the Biological Air Treatment Method

191

The destruction efficiency of the volatile organic and inorganic compounds present in the biofilter is quantitatively evaluated considering pollutant load and is expressed through the parameter for the pollutant and removing capability (ECi) (Song and Kinney 2005; Rahul et al. 2013) calculated according to Eq. 5.5: ECi ¼

ðCi,in  C i,out Þ ∙ Qi V

ð5:5Þ

where ECi—the removal capability of the gaseous pollutant, g/m3/h; Ci,in—the concentration of the incoming gaseous pollutant (g/m3); Ci,out—the concentration of the outgoing gaseous pollutant (g/m3); Qi—polluted gas traffic flow (m3/h), V— the volume of the packing material of the biofilter (m3). The effectiveness of purifying the gaseous pollutant (Φi, %) (Bohn 1992) is calculated according to the equation Φi ¼

ðCi,in  C i,out Þ  100: Ci,in

ð5:6Þ

The duration of the contact between the gaseous pollutant and the packing material (Ti, s) (Devinny et al. 1999) is calculated according to the equation Ti ¼

V : Qi

ð5:7Þ

The load of the gaseous pollutant (Ai, g/m3/h) (Devinny et al. 1999) is calculated according to the equation Ai ¼

Q  C i,in : V

ð5:8Þ

The biodegradation rate constant of the gaseous pollutant is equal to μi (1/h) (McNevin and Barford 2000) μi ¼ 

ln ð1  Φi Þ : T

ð5:9Þ

The biodegradation rate of the gaseous pollutant ri (g/m3/h) (McNevin and Barford 2000) is calculated according to the equation r i ¼ μi  C i,in :

ð5:10Þ

The scope of removing pollutant Ri (g pollutant/kg packing material) (McNevin and Barford 2000) equals

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5 Biotechnology as Sustainable Environmental Protection Technology

Ri ¼

ECi  Q : m

ð5:11Þ

where m—the mass of the packing material, kg.

5.2

The Properties of the Packing Materials Used for Biological Air Treatment

The packing material is one of the most important parts of the biofilter. The material is aimed at creating the surface area for adsorption and at making a substrate for surviving and nourishing microorganisms involved in biofiltration. Further trends in improvements to the biofiltration of various pollutants are manifested by the efficiency of the biofiltration process employing more efficient, cheaper packing materials selected based on the principles of sustainable development, simulating optimal aerodynamic conditions and analysing their assurance (Gallastegui et al. 2011; Rahul et al. 2013; Lee et al. 2013a, b). The main function of the packing material of the biofilter is creating a large surface area for adsorption and absorption. The packing material must have the following essential physical characteristics: a large surface area and a porous structure necessary for the proliferation of microorganisms, cost-effectiveness, a low mechanical load to avoid high pressure, good moisture sorption properties, the preserved homogeneity of the packing material, which allows humidification to be evenly spread over the entire surface area of the packing material and the longest possible time for applying the packing material (Wani et al. 1998; Shareefdeen et al. 2003). Figure 5.3 shows widely used inorganic packing materials employed in biofilters. The packing materials of different origin can be employed in biofilters. Substances commonly used for biological air treatment removing organic and inorganic chemical pollutants include peat (Oh and Choi 2000; Zilli et al. 2001), soil, compost and mixtures thereof (Delhomenie et al. 2002). For example, the treatment effectiveness of the biofilter containing the peat-based packing material to remove hydrogen sulphide from the air reaches 97–99% (Hartikainen et al. 2002). The air can also be purified using the packing material made of cellulose pellets and coconut shavings. Wood sawdust, bark and various types of shredded waste as well as sewage sludge from which water has been removed are also widely used worldwide (Shareefdeen et al. 2003). However, these types of the packing material do not last long and need to be replaced in a few years. Most biopacking materials can be used from 2 to 5 years (Tymczyna et al. 2004). Over the last decade, efforts have been made to find ways to extend the lifetime of the packing material of the biofilter using inorganic packing materials. To ensure high treatment effectiveness and equipment sustainability, organic and inorganic packing materials such as perlite, polyurethane and activated carbon are mixed up (Yamamoto et al. 2005). US researchers used the mixtures of wood shavings and compost to remove ethyl acetate and toluene from

5.2 The Properties of the Packing Materials Used for Biological Air Treatment

PVC balls

Pressed solid waste

Ceramic cubes

Polymeric stars

Polyvinylchloride blocks

Polyurethane cubes

193

Polypropylene cylinders

Linen cloth

Cork packing material

Fig. 5.3 The packing materials of artificial origin used for biological air treatment (Zagorskis 2009)

the air. Also, in order to reduce a drop in pressure and to extend the lifetime of the packing material, wood shavings and polystyrene balls were merged (Sheridan et al. 2002). Inorganic packing materials are currently widely applied for biological air treatment. To reduce a drop in the pressure of these packing materials, they are usually used in the form of balls or cylinders. Microorganisms proliferate in the synthetic packing material only when sprayed on it or otherwise inserted into it. Some American scientists also suggested using crushed hardened lava granules for decomposing volatile organic compounds (Chitwood and Devinny 2001). Studies have shown that inorganic natural rocks, i.e. zeolite, have high resistance to the impact of physical, chemical and biological processes (Cheng and Reinhard 2006). Zeolite is an alternative packing material to biofilters. Zeolites are attributed to the crystalline aluminosilicate structure with an open mesh composed of (AlSi)O4 tetrahedrons and are classified according to the ratio SiO2:Al2O3. The higher is the

194

5 Biotechnology as Sustainable Environmental Protection Technology

Table 5.1 Some types of biofilter packing materials and their final values of pollutant removal capacity and effectiveness Pollutant Acetone

Packing material Polyurethane foam

Acetone

Perlite pellets

Ammonia

ECmax, g/m3/h and/or (Φ, %) (>95%)

T, s 30

Source Lee et al. (2013a, b) Rene et al. (2010a) Lee et al. (2013a, b) Lee et al. (2013a, b) La Pagans et al. (2005) Gallastegui et al. (2011) Jorio et al. (2002)

17.1

Polyurethane foam

325.9 g/m3/h (54%) (>95%)

Ammonia

Perlite

(>95%)

30

Ammonia

Stabilized compost

86

Xylene

Mixture of pig manure and sawdust Aerated peat

836 g/m3/h (>98.8%) 130 g/m3/h (>95%) 236 g/m3/h (66%) 73  14 61 g/m3/h (93%) 80 g/m3/h (96%) 67 g/m3/h

150

77 g/m3/h (53%) 58 g/m3/h (49%)

59

Saravanan and Rajamohan (2009) Jorio et al. (2009)

59

Jorio et al. (2009)

Xylene Xylene Xylene Xylene Xylene

Xylene Xylene

Mixture of compost and wood shavings Mixture of peat and mineral additives at a ratio of weight 70:30 Mixture of pig manure, forest soil and polyethylene Pressed commercial sludge (waste from sugar industry) Wood shavings (including selected mushroom species) Wood shavings (including selected species of bacteria)

30

180–270 68 60

132 42

Torkian et al. (2003) Elmrini et al. (2004) Wu et al. (2006)

ratio, the more zeolite is acid-resistant (Baltrėnas and Paliulis 2002; Cheng and Reinhard 2006). Liang et al. (2000) examined the long-term (over 8 months) results of ammonia removal from biofilters. Compost was used as a biofilter medium and activated carbon as an additional material. Ammonia removal typically exceeded 95% under the concentration fluctuating between 20 and 500 ppm (million parts per volume). According to the findings of the test, ammonia concentration should be 98.8%)

86

130 g/m3/h (>95%)

180–270

Gallastegui et al. 2011

236 g/m3/h (66%)

68

Mixture of compost and wood chips

73
14

60

Jorio et al. 2002 Torkian et al. 2003

61 g/m3/h (93%)

150

Acetone

Xylene

Xylene

Ammonia

Ammonia

Xylene

Xylene Xylene

Xylene

Source This research

(continued)

410

7 The Importance of Biofiltration System Performance Parameters for the Effective. . .

Table 7.2 (continued)

Pollutant

Packing material Mixture of peat and mineral additives 70:30 (v/v)

Xylene

Mixture of pig manure-forest soil and polyethylene Compressed commercial sludge (sugar industry waste) Wood chips (including the species of selected mushrooms) Wood chips (including the selected species of bacteria)

Xylene

Xylene

Xylene

The highest value of the capacity of pollutant removal, E Ci, g/m3/h and/or the effectiveness of pollutant removal, Φi%

Duration of contact between gas flow and the packing material, T, s

80 g/m3/h (96%)

132

Wu et al. 2006

67 g/m3/h

42

77 g/m3/h (53%)

59

Saravanan and Rajamohan 2009 Jorio et al. 2009

58 g/m3/h (49%)

59

Source Elmrini et al. 2004

Jorio et al. 2009

load of around 250–280 g/m3/h, the biofilter containing natural microorganisms managed to remove pollutants at the average removal capacity of 160–180 g/m3/h while in the case of selected microorganisms—at the average removal capacity of 210–230 g/m3/h. Thus, selected microorganisms increased pollutant removal capacity by approximately 1.2 times. The carried out experiments that used wood fibre and non-woven cork as a packing material of the biofilter resulted in the air flow rate of 0.08 m/s in the inlet duct in order to achieve a rate of 0.04 m/s between the plates for the effective pollutant decomposition in the biofilter. The use of the biofilter with the straight inner structure and filtering volatile organic compounds at a rate of 0.04 m/s between the plates applying non-woven cork and wood fibre determined a high air treatment degree when the concentration of acetone, xylene and ammonia vapour in the supplied air did not exceed 500 mg/m3 thus obtaining the treatment effectiveness of 88–90%. The removal of acetone, xylene and ammonia vapour from the polluted air at an air flow rate of 0.04 m/s between the plates through the packing material of nonwoven cork and wood fibre estimated wavy lamellar plate treatment effectiveness ranging from 90 to 93% and pollutant concentration that did not exceed 500 mg/m3. The removal of acetone, xylene and ammonia vapour from the polluted air at an air flow rate of 0.04 m/s between the plates and under the concentration of 700 mg/m3 showed that the biodegradation of these pollutants reached 80–86% for the straight structure and 83–85% for the wavy structure.

Noninoculated packing material 100 % removal 80 % removal 65 % removal

350 300 250 200 150 100 50 0 0

300 200 100 Load of supplied acetone, g/m3/h a)

400

Capacity of removing xylene, g/m3/h

450 Noninoculated packing material 100 % removal 80 % removal 65 % removal

400 350 300 250 200 150 100 50 0 0

300 200 100 Load of supplied xylene, g/m3/h

400

Efficiency of the biofilter-absorber removing xylene (removal capacity), g/m3/h

Capacity of removing acetone, g/m3/h

450 400

Efficiency of the biofilter-absorber removing acetone (removal capacity), g/m3/h

7.3 Air Treatment Effectiveness of Biological Filters

411

450 Inoculated packing material 100 % removal 80 % removal 65 % removal

400 350 300 250 200 150 100 50 0 0

50

250 200 150 100 50 0 300 200 100 Load of supplied ammonia, g/m3/h e)

400

Efficiency of the biofilter-absorber removing ammonia (removal capacity), g/m3/h

Capacity of removing ammonia, g/m3/h

300

0

400

350

400

350

400

Inoculated packing material 100 % removal 80 % removal 65 % removal

400 350 300 250 200 150 100 50 0 0

50

100 200 100 250 300 Load of supplied xylene, g/m3/h d)

Noninoculated packing material 100 % removal 80 % removal 65 % removal

350

350

450

c) 450 400

100 200 100 250 300 Load of supplied acetone, g/m3/h b)

450 Inoculated packing material 100 % removal 80 % removal 65 % removal

400 350 300 250 200 150 100 50 0 0

50

100 200 100 250 300 Load of supplied ammonia, g/m3/h f)

Fig. 7.28 The dependence of capacity for removing pollutants (E Ci, g/m3/h) on load Ai of gaseous pollutant i applying natural and selected microorganisms during testing: (a) load of acetone applying natural microorganisms; (b) load of acetone applying selected microorganisms; (c) load of xylene applying natural microorganisms; (d) load of xylene applying selected microorganisms; (e) load of ammonia applying natural microorganisms; (f) load of ammonia applying selected microorganisms

Under the low concentrations of pollutants supplied to the biofilter having the straight and lamellar inner structure and an air flow rate of 0.04 m/s between the plates, i.e. 100 and 200 mg/m3, the received treatment effectiveness was 90–95% and 92–97% for straight and wavy lamellar plates, respectively (Baltrėnas et al. 2015a).

412

7.4

7 The Importance of Biofiltration System Performance Parameters for the Effective. . .

Odours Produced by Biological Air Treatment Filters

The research results were obtained using three different types of laboratory biofilters equipped with (1) straight lamellar plates; (2) wavy lamellar plates and (3) tubes. The biofilters are of a unique design that incorporates a capillary humidification system allowing less energy to be used for irrigating the biopacking material while providing stable operation even in the event of a power outage. Four different types of the biofilter packing material such as non-woven cork, wood fibre, linen fabric and biochar have been applied. These materials have been selected taking into account their longevity and high strength of capillary effect. For research purposes, three pollutants, including acetone, xylene and ammonia, have been selected to design and install a device for removing harmful vapour from the air in the objects and areas such as sewage treatment plants, livestock farms, rubber production and processing, detergent production, agrochemicals, lubricant production and printing works because these pollutants account for most of air pollution in these places. All three laboratory biofilters were subjected to odour detection using an olfactometer. Odour tests were performed at three different concentrations for each pollutant. Experimental studies were conducted using natural microorganisms.

7.4.1

Odour Identification when Applying the Olfactometry Method

Regulations on Lithuanian Hygiene Norms HN 121:2010 and HN 35:2007 specify the concentrations of chemical compounds undesirable, dangerous and harmful to humans and the environment. However, despite the regulatory base and due to inadequate control and preventive measures, the air is polluted with volatile organic compounds. In industry, the main pollutants emitted to the environment include volatile organic compounds (VOCs), xylene, acetone and ammonia that have an impact on odours. Involvement in photochemical sunlight reactions is the major environmental hazard posed by VOCs as some of those react with nitric oxide present in the atmosphere to form smog. VOCs strongly contaminate indoor air. For example, when the paint dries, the amount of VOCs indoors is approximately 1000 times higher than that monitored outside. The usual concentration of VOCs indoors is 2–5 times higher than that outdoors. VOCs cause headache, fatigue, breathing difficulties, eye and skin irritation as well as may cause cancer and developmental disorders. They are particularly harmful to pregnant women and babies. Xylene is classified as hazardous to human health and the environment, enters the human body by inhalation, skin, the gastrointestinal tract or through direct contact with skin or eyes; the pollutant may interfere the functioning of human organs,

7.4 Odours Produced by Biological Air Treatment Filters

413

including the central nervous system. In high concentrations, it causes headache, dizziness, disorientation and other disorders (Zagorskis 2009). Ammonia may cause hypersensitivity reactions in some people, for instance, urticaria, skin and mucous membrane irritation. Inhaling too much ammonia vapours may result in bronchospasm, the shortness of breath and even stopping breathing (Zagorskis 2009). The chemical and physical methods for analysis are used for determining odours in the air or a water sample; however, it is not possible to determine the ‘quality’ of the odour, and therefore the olfactometry method is required. Important factors in characterizing unpleasant sensation or irritation caused by the odour include the nature and persistence of the odour (Ribikauskas, Vaičionis 2003, Zuokaitė 2011) (Table 7.3). On the basis of laboratory tests, odours may be classified according to their intensity: • 1 OUE/m3—the limit of odour detection. • 5 OUE/m3—weak odour. • 10 OUE m3—strong odour (Van Harreveld et al. 2001). The recognition threshold is usually around three odour units. The effect of the air treatment biofilter with the capillary packing material humidification system on odour reduction in pollutants emitting xylene, ammonia and acetone has been investigated and evaluated. The research was performed using three different types of laboratory biofilters containing three different packing materials.

Basic Concepts Volatile organic compounds consist of carbon, oxygen, nitrogen, chlorine and other atoms that easily release gas. Organic solvents used in household and industrial applications are the examples of VOCs. A dynamic olfactometer provides the flows of a mixture of odorant and neutral gas containing the identified dilution factors to the general flow outlet of the device. Odour is an organoleptic property sensed by the olfactory organ through the inhalation of certain volatile substances (HN 121 2010). The presented research methodology has been prepared taking into account and employing techniques developed by other scientists working in this field. The methodologies of researchers Aly-Hassan and Sorial (2011), Baltrėnas and Vaiškūnaitė (2002a), Baltrėnas and Zagorskis (2010a), Chung et al. (2001), Duan et al. (2006), Jun and Wenfeng (2009), Ramirez et al. (2008), Singh et al. (2010), Zigmontienė and Žarnauskas (2011), Zuokaitė (2011), Zagorskis (2009) have been reviewed. On the basis of the analysed methodologies that provided the distribution and number of measurement points, the estimated parameters, etc., a new methodology of the air treatment biofilter with the lamellar plate structure and capillary packing material humidification system for odour analysis has been developed.

414

7 The Importance of Biofiltration System Performance Parameters for the Effective. . .

Table 7.3 The maximum allowable concentration of chemicals (pollutants) in the ambient air of the living environment (HN 35 2007) Chemical compound Acetone (dimethyl ketone) Xylene (dimethyl benzene) Ammonia

Nature of the odour Salty, solvent Aromatic, sweet Sharp, irritating

Chemical formula CH3COCH3 C8H10 NH3

Odour units upstream and downstream of the biofilter within a distance of 1 m from the air outlet duct of the biofilter, including all types of the structure and biopacking material of the biofilter, are determined using a dynamic olfactometer under laboratory conditions. The treatment effectiveness of the odour units of the biofilter is established by measuring the concentration of the pollutant before (in the inlet duct of the polluted air) and after (in the outlet duct of the polluted air) the treatment procedure. The effect of the biofilter on the ambient air odour is uncovered by taking odour samples at around a distance of 1 m from the outlet duct of the biofilter. Determining the odour unit. Odour concentrations upstream and downstream of the device are found employing the AC’SCENT® International dynamic olfactometer (Fig. 7.29), which is air mixing and dilution equipment for establishing the threshold values of odorous air samples. The device mixes fragrant air samples with clean air at precisely selected dilution ratios and provides the blended air to the assessor (smeller). • Each assessor/smeller is provided with the diluted air in the sample and clean air through an odour respirator to evaluate the odour. • Reliable and accurate. The linear rate of air supply is approximately 0.25 m/s at a volumetric rate of 20 L/min. • Customer user-friendly—adjusts delivery time for the assessor (smeller) from 1 to 60 s. The device is supplied with the air dried and treated employing carbon filters. • The obtained data are processed with reference to computer calculations. The device applies to software automatically collecting data, calculating results and creating a database. Each assessor (smeller) is provided with the air diluted in the sample and with clean air supplied through a respirator to evaluate the odour. The linear rate of air supply is approximately 0.25 m/s at a volumetric rate of 20 l/min. The dynamic olfactometer meets requirements for standard EN 13725:2004 + AC:2006—Air Quality—Identifying Odour Concentration Applying Dynamic Olfactometry Methods (European Union). The quality of testing odours is also assured following requirements for standard EN 13725:2004 + AC:2006 (Fig.7.29a) (Baltrėnas et al. 2014a). A vacuum chamber operating on the ‘lung principle’ is used for air sampling. A special pump is installed to extract the air from the chamber thus creating a vacuum in the chamber. Due to the vacuum created in the chamber, the volume of the

7.4 Odours Produced by Biological Air Treatment Filters

415

Tedlar bag

Pump Pipe for connecting sample valve and bagedlar bag

Pump outlet valve (A) Pump inlet valve (B)

Sample valve (D) Silicon connecting Pipe for hose fixing (1 ) hose Chamber Pressure Sample hose outlet relief valve valve (C)

a)

b)

Fig. 7.29 (a) Dynamic olfactometer AC’SCENT® International; (b) VAC’SCENT vacuum chamber for air samples

samples contained inside the chamber starts to be filled with the air of the working environment. The sampling process consists of preparing the vacuum chamber, capacity conditioning, emptying the container, filling the sampling line and taking a sample. The vacuum chamber of air sampling is shown in Fig. 7.29b. Operation. Experimental studies are carried out using biofilters as air treatment equipment. Figures 6.15, 6.16, 6.17, 6.18, 6.19 and 6.20 provide schemes for biofilters with straight lamellar plates, wavy lamellar plates and tubes. The biofilter is composed of the packing material, a system for maintaining the humidity and temperature of the packing material in the filter, a blower, air inlet and outlet ducts installed in the device and an air flow control valve. The polluted air is supplied to the biofilter through the polluted air duct (1) with a diameter of 100 mm. The polluted air duct has the built-in valve (9) that takes control over air flow rate and thus the discharge of the supplied air. This air duct is also equipped with the sampling (2) determining air flow rate, temperature, pressure and pollutant concentration supplied to the biofilter. Also, this point is used for taking samples to detect odours. Then, the polluted air flow enters the biofilter. The perforated plate (8) distributes air flow throughout the entire volume (7) of the packing material. The polluted air moves between the plates of the biofilter (7) soaked in a liquid medium and spaced 4 mm apart towards the duct of the treated air the flow of which enters the treated air duct (11) with a diameter of 100 mm and is discharged into the environment. The treated air duct has a built-in blower and equipped with the sampling opening (2) determining air flow rate, temperature, pressure and pollutant concentration supplied to the biofilter. Also, this point is used for taking samples to detect odours. The biofilter maintains the optimal humidity of the packing material and the medium temperature set employing an electric heating element with a thermostat (5).

416

7 The Importance of Biofiltration System Performance Parameters for the Effective. . .

Determining the odour unit. Figures 6.15 and 6.16 (sections A-A and B-B), Figs. 6.17 and 6.18 (sections A-A and B-B) show the points for taking the samples determining odour units using straight and wavy biofilter cartridges. The dimensions of the cartridge are 0.9 m long and 0.2 m high, depending on the material used. The samples for specifying odour units are taken upstream and downstream of the biofilter in the inlet and outlet ducts. The distribution of points in the polluted and treated air ducts is given in Fig. 6.15 (section C-C) and Fig. 6.17 (section C-C). Prior to the performance of biological air treatment equipment (2–3 weeks), it is furnished with the biopacking material that is biologically activated by supplying the air contaminated with organic pollutants (Baltrėnas et al. 2004b). The biopacking material is considered biologically active when covered by a thin layer (5–30 μm thick) of the biofilm inhabited by microorganisms Alternatively, the biological activation of the packing material can be achieved when the microorganisms are first grown in the specific medium thus subsequently inoculating their cultures on the inactivated packing material. Thereafter, investigations are initiated in 2 to 3 weeks time. The VAC’SCENT vacuum camera takes samples for odour detection. The olfactometer is warmed to the required temperature before the odour samples are evaluated. The sample is supplied to the dynamic olfactometer and tested applying the forced-choice analysis method. The evaluation session is conducted by five assessors who meet requirements set by standard EN 13725:2004 + AC: 2006. An assessment team of five members performs a 3-cycle measurement. The data on the first (pre) measurement cycle are always discarded thus leaving only the figures of the next two cycles used for calculation purposes. The application of the forced selection method involves the members of the assessment team that specify the location of the odorous irritant and point out whether they have indicated this location by guessing, assuming or being confident. The required volume of the sample to be analysed is 2.5 L. It takes 3 s for five assessors to smell the odours under the flow rate of 20 l/min. The geometric means of dilutions for all 14 channels are worked out thus calculating the geometric means of individual threshold estimates (ZITE) in cycles 2 and 3. The first retrospective inspection is carried out on the basis of parameter ΔZ, individual threshold estimate ZITE and the geometric mean of all values of individual threshold estimate Z ITE . In the case ΔZ of any member of the group exceeds the limits of criterion 5 ΔZ 5, the highest ΔZ result of the member of the assessment team is rejected. The second retrospective inspection is performed, and all ΔZ values must be within the range of
5. When a single structure of the biofilter and one type of the material are present, odour levels are investigated at three different concentrations of acetone, xylene and ammonia. Three different types of the packing material are used for a single structure of the biofilter thus resulting in 27 cases of studying the levels of odours the tests on which are performed employing three different biofilter structures, each containing three different types of the packing material, which overall makes 81 times to determine the levels of the whole odour.

7.4 Odours Produced by Biological Air Treatment Filters

417

Determining Odour Concentration in the Sample The concentration of the odour of the investigated sample Cod is calculated as C od ¼ Z ITE,pan  1 OUE=m3

ð7:2Þ

The obtained results are described, analysed and compared with those of the researchers that conducted similar studies and published findings in scientific articles. Research results are systematized and presented graphically. Also, the statistical evaluation of the experimental results obtained using Excel and STATISTICA 8.0 software was performed. This section presents the results of experimental studies using laboratory stands of the biofilter with three different types of the internal structure (straight lamellar, wavy lamellar and tubular). The research was carried out employing four different types of the biopacking material and embraced NWC—non-woven cork, WF— wood fibre, LF—linen fabric and BC—biochar (Baltrėnas et al. 2014a).

7.4.2

Odour Identification when Applying the Olfactometer and Using the Biofilter with Straight Lamellar Plates

Wood Fibre and Non-woven Cork and as a Packing Material Straight lamellar plates containing WF (wood fibre) and NWC (non-woven cork) are the samples required for investigating the odours of the supplied pollutant and are taken next to the ducts of the polluted and treated air. The taken samples are studied using the olfactometer according to the instructions provided in the methodology. Figure 6.15 shows a structural scheme for the biopacking material with straight lamellar plates. The biopacking material consists of three main components, including 3 mm of non-woven cork, 1 mm of wood fibre and 2 mm of the polymer plate. Both non-woven cork and wood fibre are fastened on both sides of the polymer plate. The total thickness of the biopacking material makes 10 mm (Fig. 6.19). The error of the investigation method is 36% and is depicted in each of the below charts providing the results of natural studies. Figure 7.30a shows that the largest number of odour units (6 OUE/m3) was formed from the air sample having the highest concentration of acetone (175 ppm) before treatment. A comparison of the same air sample after treatment when acetone concentration made 17 ppm shows that the value of odour units dropped to 3 OUE/m3. As expected, the smallest number of odour units (2 OUE/m3) was found in the air sample having the lowest acetone concentration (5 ppm) after treatment. Under acetone concentration of 28 ppm in the same air sample before treatment, the value of odour units was 5 OUE/m3.

418

7 The Importance of Biofiltration System Performance Parameters for the Effective. . .

A comparison of percentage reduction in odour intensity before and after treatment illustrates it reached 50.0% in the first air sampling, 40.0%—in the second and 60.0%—in the third. Figure 7.30b shows that the largest number of odour units (5 OUE/m3) was formed from the air sample having the highest concentration of xylene (178 ppm) before treatment. A comparison of the same air sample after treatment when xylene concentration made 18 ppm shows that the value of odour units dropped to 3 OUE/m3. As expected, the smallest number of odour units (2 OUE/m3) was found in the air sample having the lowest acetone concentration (6 ppm) after treatment. Under xylene concentration of 30 ppm in the same air sample before treatment, the value of odour units was 4 OUE/m3. The evaluation of the values of the odour units (OUE/m3) of acetone and xylene pollutants provides that the odour intensity of acetone at similar concentrations is slightly higher than that of xylene (0.83 times on average). A comparison of percentage reduction in odour intensity before and after treatment illustrates it reached 50.0% in the first air sampling, 50.0%—in the second and 50.0%—in the third. Figure 7.30c shows that the largest number of odour units (6 OUE/m3) was formed from the air sample having the highest concentration of ammonia (181 ppm) before treatment. A comparison of the same air sample after treatment when ammonia concentration made 17 ppm shows that the value of odour units dropped to 4 OUE/m3. As expected, the smallest number of odour units (2 OUE/m3) was found in the air sample having the lowest acetone concentration (6 ppm) after treatment. Under ammonia concentration of 32 ppm in the same air sample before treatment, the value of odour units was 4 OUE/m3 (Baltrėnas et al. 2014a). A comparison of percentage reduction in odour intensity before and after treatment illustrates it reached 33.3% in the first air sampling, 50.0%—in the second and 50.0%—in the third. A summary of odour intensity established in the biopacking material with straight lamellar plates containing WF (wood fibre) and NWC (non-woven cork) demonstrate that the odour intensity of ammonia at similar concentrations is significantly higher than that of acetone or xylene. On average, the odour intensity of ammonia is 1.2 times higher than that of xylene and acetone, which determines its stronger sense in the environment near the investigated biofilter. The samples of the straight lamellar plate containing wood fibre required for testing the odours of the supplied pollutant are taken next to the polluted and treated air ducts. The collected samples are tested employing the olfactometer, which is done according to the instructions provided in the methodology. The findings are tabulated and presented graphically. Figure 6.19a shows a structural scheme for the biopacking material with straight lamellar plates. As provided in Fig. 6.19a, the biopacking material consists of three main components, including 3 mm of non-woven cork, 1 mm of wood fibre and 2 mm of the polymer plate. Both non-woven cork and wood fibre are fastened on both sides of the polymer plate. The total thickness of the biopacking material makes 7 mm (Fig. 6.19).

4

40

2

20

0

0

1 prior to/after

2 prior to/after 3 prior to/after

Air samples c) Effectiveness of removing the pollutant, % Prior to treatment After treatment 100 6

80 60

4

40 2 0

20 1 prior to/after

2 prior to/after 3 prior to/after

Air samples e)

0

1 prior to/after

8

Effectiveness, %

Odour units, OUE/m3

Effectiveness of removing the pollutant, % Prior to treatment After treatment 7 100 6 80 5 60 4 3 40 2 20 1 0 0 2 prior to/after 3 prior to/after

Air samples b) Effectiveness of removing the pollutant, % Prior to treatment After treatment 100 80

6

60

4

40

2

20

0

0

1 prior to/after

2 prior to/after 3 prior to/after

Effectiveness, %

60

419

Air samples d) Effectiveness of removing the pollutant, % Prior to treatment After treatment 100 8

80

6

60

4

40

2

20

0

0

1 prior to/after

2 prior to/after 3 prior to/after

Effectiveness, %

80

6

Odour units, OUE/m3

Air samples a) Effectiveness of removing the pollutant, % Prior to treatment After treatment 100

Odour units, OUE/m3

2 prior to/after 3 prior to/after

Effectiveness, %

1 prior to/after

Effectiveness, %

Odour units, OUE/m3

8

Effectiveness of removing the pollutant, % Prior to treatment After treatment 100 80 60 40 20 0

Effectiveness, %

10 8 6 4 2 0

Odour units, OUE/m3

Odour units, OUE/m3

7.4 Odours Produced by Biological Air Treatment Filters

Air samples f)

Fig. 7.30 (a) intensity of acetone (CH3COCH3) odour, (b) intensity of xylene (C8H10) odour, (c) intensity of ammonia (NH3) odour, (d) intensity of acetone (CH3COCH3) odour, (e) intensity of xylene (C8H10) odour, (f) intensity of ammonia (NH3) odour

Figure 7.30d shows that the largest number of odour units (6 OUE/m3) was formed from the air sample having the highest concentration of acetone (175 ppm) before treatment. A comparison of the same air sample after treatment when acetone concentration made 17 ppm shows that the value of odour units dropped to 3 OUE/m3. As expected, the smallest number of odour units (2 OUE/m3) was found in the air sample having the lowest acetone concentration (5 ppm) after treatment. Under acetone concentration of 28 ppm in the same air sample before treatment, the value of odour units was 5 OUE/m3. A comparison of percentage reduction in odour intensity before and after treatment illustrates it reached 50.0% in the first air sampling, 50.0%—in the second and 50.0%—in the third. A comparison of the odour intensity of acetone between the biopacking material with straight lamellar plates and NWC (non-woven cork) and that with WF (wood

420

7 The Importance of Biofiltration System Performance Parameters for the Effective. . .

fibre) did not produce significant changes. At similar concentrations, odour intensity remained almost identical. Figure 7.30e shows that the largest number of odour units (5 OUE/m3) was formed from the air sample having the highest concentration of xylene (178 ppm) before treatment. A comparison of the same air sample after treatment when xylene concentration made 18 ppm shows that the value of odour units dropped to 3 OUE/m3. As expected, the smallest number of odour units (2 OUE/m3) was found in the air sample having the lowest acetone concentration (6 ppm) after treatment. Under xylene concentration of 30 ppm in the same air sample before treatment, the value of odour units was 4 OUE/m3. A comparison of percentage reduction in odour intensity before and after treatment illustrates it reached 40% in the first air sampling, 40.0%—in the second and 50.0%—in the third. The assessment of the values of the odour units (OUE/m3) of acetone and xylene pollutants provides that the odour intensity of acetone at similar concentrations is slightly higher than that of xylene (0.76 times on average). Figure 7.30f shows that the largest number of odour units (6 OUE/m3) was formed from the air sample having the highest concentration of ammonia (181 ppm) before treatment. A comparison of the same air sample after treatment when ammonia concentration made 17 ppm shows that the value of odour units dropped to 4 OUE/m3. As expected, the smallest number of odour units (3 OUE/m3) was found in the air sample having the lowest acetone concentration (6 ppm) after treatment. Under ammonia concentration of 32 ppm in the same air sample before treatment, the value of odour units was 5 OUE/m3. A summary of odour intensity established in the straight lamellar plate containing WF (wood fibre) demonstrates that the odour intensity of ammonia at similar concentrations is significantly higher than that of acetone or xylene. On average, the odour intensity of ammonia is 1.3 times higher than that of xylene and acetone, which determines its stronger sense in the environment near the investigated biofilter. A more noticeable difference is observed only at lower concentrations under the efficiency of 81.25%. The samples of the straight lamellar plate containing linen fabric (LF) required for testing the odours of the supplied pollutant are taken next to the polluted and treated air ducts. The collected samples are tested employing the olfactometer. Figure 6.19a shows a structural scheme for the biopacking material with straight lamellar plates. As provided in Fig. 6.19a, the biopacking material consists of three main components, including 3 mm of non-woven cork, 1 mm of wood fibre and 2 mm of the polymer plate. Both linen fibre and wood fibre are fastened on both sides of the polymer plate. The total thickness of the biopacking material makes 6 mm (Fig. 6.19). Figure 7.31a shows that the largest number of odour units (6 OUE/m3) was formed from the air sample having the highest concentration of acetone (175 ppm) before treatment. A comparison of the same air sample after treatment when acetone concentration made 17 ppm shows that the value of odour units dropped to 3 OUE/m3. As expected, the smallest number of odour units (2 OUE/m3) was

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found in the air sample having the lowest acetone concentration (5 ppm) after treatment. Under acetone concentration of 28 ppm in the same air sample before treatment, the value of odour units was 4 OUE/m3. A comparison of percentage reduction in odour intensity before and after treatment illustrates it reached 50% in the first air sampling, 60.0%—in the second and 50.0%—in the third. Figure 7.31a shows that the effectiveness of removing acetone exceeds 80% in all three cases. The pollutant is most effectively removed at a higher concentration (175/17 ppm) and reaches 90.3%. Figure 7.31b shows that the largest number of odour units (5 OUE/m3) was formed from the air sample having the highest concentration of xylene (178 ppm) before treatment. A comparison of the same air sample after treatment when xylene concentration made 18 ppm shows that the value of odour units dropped to 3 OUE/m3. As expected, the smallest number of odour units (2 OUE/m3) was found in the air sample having the lowest acetone concentration (6 ppm) after treatment. Under xylene concentration of 30 ppm in the same air sample before treatment, the value of odour units was 4 OUE/m3. The evaluation of the values of the odour units (OUE/m3) of acetone and xylene pollutants provides that the odour intensity of acetone at similar concentrations is slightly higher than that of xylene (0.85 times on average). The intensity of the odour emitted by all three air samples is directly proportional to an increase in the concentration of the ambient air sample. A comparison of percentage reduction in odour intensity before and after treatment illustrates it reached 40.0% in the first air sampling, 50.0%—in the second and 50.0%—in the third. Figure 7.31c shows that the largest number of odour units (6 OUE/m3) was formed from the air sample having the highest concentration of ammonia (181 ppm) before treatment. A comparison of the same air sample after treatment when ammonia concentration made 17 ppm shows that the value of odour units dropped to 4 OUE/m3. As expected, the smallest number of odour units (2 OUE/m3) was found in the air sample having the lowest acetone concentration (6 ppm) after treatment. Under ammonia concentration of 32 ppm in the same air sample before treatment, the value of odour units was 5 OUE/m3. A summary of studies on the odour intensity of the biopacking material containing straight lamellar plates shows that the odour concentration of the pollutants under investigation is determined by a higher concentration of the pollutant. No significant changes in the results of all pollutants are observed. At similar concentrations, odour intensity remained almost identical. Taking into account three different types of the biopacking material, the highest odour values were recorded for ammonia while the lowest odour intensity was emitted by xylene. The intensity of the odour emitted by all three air samples is directly proportional to an increase in the concentration of the ambient air sample (Baltrėnas et al. 2015c, Baltrėnas et al. 2014a, b).

7 The Importance of Biofiltration System Performance Parameters for the Effective. . .

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7.4.3

423

Odour Identification when Applying the Olfactometer and Using the Biofilter with Wavy Lamellar Plates

Wood Fibre and Non-woven Cork and as a Packing Material The biopacking material containing wavy lamellar plates with WF (wood fibre) and NWC (non-woven cork) are the samples required for investigating the odours of the supplied pollutant and are taken next to the ducts of the polluted and treated air. The taken samples are studied using the olfactometer. Figure 6.19b shows a structural scheme for the biopacking material with wavy lamellar plates. The biopacking material containing wavy lamellar plates similarly to the material containing straight lamellar plates consists of three main components, including 3 mm of non-woven cork, 1 mm of wood fibre and 2 mm of the polymer plate. Both non-woven cork and wood fibre are fastened on both sides of the polymer plate. The total thickness of the biopacking material makes 10 mm. Figure 7.32a shows that the largest number of odour units (6 OUE/m3) was formed from the air sample having the highest concentration of acetone (179 ppm) before treatment. A comparison of the same air sample after treatment when acetone concentration made 17 ppm shows that the value of odour units dropped to 3 OUE/m3. As expected, the smallest number of odour units (2 OUE/m3) was found in the air sample having the lowest acetone concentration (5 ppm) after treatment. Under acetone concentration of 28 ppm in the same air sample before treatment, the value of odour units was 5 OUE/m3. A comparison of percentage reduction in odour intensity before and after treatment illustrates it reached 50% in the first air sampling, 40.0%—in the second and 60.0%—in the third. Figure 7.32b shows that the largest number of odour units (5 OUE/m3) was formed from the air sample having the highest concentration of xylene (175 ppm) before treatment. A comparison of the same air sample after treatment when xylene concentration made 18 ppm shows that the value of odour units dropped to 3 OUE/m3. As expected, the smallest number of odour units (2 OUE/m3) was found in the air sample having the lowest acetone concentration (6 ppm) after treatment. Under xylene concentration of 30 ppm in the same air sample before treatment, the value of odour units was 4 OUE/m3. The evaluation of the values of the odour units (OUE/m3) of acetone and xylene pollutants provides that the odour intensity of acetone at similar concentrations is slightly higher than that of xylene (0.78 times on average). The intensity of the odour emitted by all three air samples is directly proportional to an increase in the concentration of the ambient air sample. A comparison of percentage reduction in odour intensity before and after treatment illustrates it reached 40.0% in the first air sampling, 50.0%—in the second and 50.0%—in the third.

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Fig. 7.32 (a) intensity of acetone (CH3COCH3) odour, (b) intensity of xylene (C8H10) odour, (c) intensity of ammonia (NH3) odour, (d) intensity of acetone (CH3COCH3) odour, (e) intensity of xylene (C8H10) odour, (f) intensity of ammonia (NH3) odour

Figure 7.32c shows that the largest number of odour units (6 OUE/m3) was formed from the air sample having the highest concentration of ammonia (180 ppm) before treatment. A comparison of the same air sample after treatment when ammonia concentration made 18 ppm shows that the value of odour units dropped to 4 OUE/m3. As expected, the smallest number of odour units (3 OUE/m3) was found in the air sample having the lowest acetone concentration (6 ppm) after treatment. Under ammonia concentration of 32 ppm in the same air sample before treatment, the value of odour units was 5 OUE/m3. At similar concentrations, the odour intensity of ammonia established in the wavy lamellar plate containing WF (wood fibre) and NWC (not-woven cork) is significantly higher than that of xylene and acetone. On average, the odour intensity of ammonia is 1.3 times higher than that of xylene and acetone, which determines its stronger sense in the environment near the investigated biofilter.

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The samples required for investigating the odours of the supplied pollutant present in the wavy lamellar plate containing WF (wood fibre) are taken next to the ducts of the polluted and treated air and studied using the olfactometer. Figure. 7.32d shows that the largest number of odour units (5 OUE/m3) was formed from the air sample having the highest concentration of acetone (172 ppm) before treatment. A comparison of the same air sample after treatment when acetone concentration made 17 ppm shows that the value of odour units dropped to 3 OUE/m3. As expected, the smallest number of odour units (2 OUE/m3) was found in the air sample having the lowest acetone concentration (5 ppm) after treatment. Under acetone concentration of 25 ppm in the same air sample before treatment, the value of odour units was 4 OUE/m3. A comparison of percentage reduction in odour intensity before and after treatment illustrates it reached 40% in the first air sampling, 60.0%—in the second and 50.0%—in the third. A comparison of the odour intensity of acetone in the straight and wavy lamellar plates containing WF (wood fibre) did not indicate significant changes. At similar concentrations, odour intensity remained almost identical after treatment. However, before removal, the odour intensity of acetone was by 14% higher in the straight lamellar plate, which might be determined by a longer contact time of the packing material containing wavy lamellar plates. Figure 7.32e shows that the largest number of odour units (5 OUE/m3) was formed from the air sample having the highest concentration of xylene (176 ppm) before treatment. A comparison of the same air sample after treatment when xylene concentration made 18 ppm shows that the value of odour units dropped to 3 OUE/m3. As expected, the smallest number of odour units (2 OUE/m3) was found in the air sample having the lowest acetone concentration (6 ppm) after treatment. Under xylene concentration of 30 ppm in the same air sample before treatment, the value of odour units was 4 OUE/m3. A comparison of percentage reduction in odour intensity before and after treatment illustrates it reached 40% in the first air sampling, 40.0%—in the second and 50.0%—in the third. The assessment of the values of the odour units (OUE/m3) of acetone and xylene pollutants present in the straight and wavy lamellar plates and containing (wood fibre) provides that the odour intensity of acetone present in the straight plate at similar concentrations is slightly higher than that of xylene (0.79 times on average). Figure 7.32f shows that the largest number of odour units (7 OUE/m3) was formed from the air sample having the highest concentration of ammonia (177 ppm) before treatment. A comparison of the same air sample after treatment when ammonia concentration made 17 ppm shows that the value of odour units dropped to 4 OUE/m3. As expected, the smallest number of odour units (3 OUE/m3) was found in the air sample having the lowest acetone concentration (6 ppm) after treatment. Under ammonia concentration of 32 ppm in the same air sample before treatment, the value of odour units was 6 OUE/m3 (Baltrėnas et al. 2015c).

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7 The Importance of Biofiltration System Performance Parameters for the Effective. . .

At similar concentrations, the odour intensity of ammonia established in the wavy lamellar plate containing WF (wood fibre) is significantly higher than that of xylene and acetone. On average, the odour intensity of ammonia is 1.3 times higher than that of xylene and acetone, which determines its stronger sense in the environment near the investigated biofilter. Figure 7.33a shows that the largest number of odour units (6 OUE/m3) was formed from the air sample having the highest concentration of acetone (175 ppm) before treatment. A comparison of the same air sample after treatment when acetone concentration made 17 ppm shows that the value of odour units dropped to 3 OUE/m3. As expected, the smallest number of odour units (2 OUE/m3) was found in the air sample having the lowest acetone concentration (5 ppm) after treatment. Under acetone concentration of 28 ppm in the same air sample before treatment, the value of odour units was 5 OUE/m3. A comparison of percentage reduction in odour intensity before and after treatment illustrates it reached 50% in the first air sampling, 60.0%—in the second and 50.0%—in the third. Figure 7.33a shows that the effectiveness of removing acetone exceeds 80% in all three cases. The pollutant is most effectively removed at higher concentration (175/17 ppm) and reaches 90.3%. Figure 7.33b shows that the largest number of odour units (5 OUE/m3) was formed from the air sample having the highest concentration of xylene (178 ppm) before treatment. A comparison of the same air sample after treatment when xylene concentration made 18 ppm shows that the value of odour units dropped to 3 OUE/m3. As expected, the smallest number of odour units (2 OUE/m3) was found in the air sample having the lowest acetone concentration (6 ppm) after treatment. Under xylene concentration of 30 ppm in the same air sample before treatment, the value of odour units was 4 OUE/m3. The assessment of the values of the odour units (OUE/m3) of acetone and xylene pollutants provides that the odour intensity of acetone at similar concentrations is slightly higher than that of xylene (0.72 times on average). The intensity of the odour emitted by all three air samples is directly proportional to an increase in the concentration of the ambient air sample. A comparison of percentage reduction in odour intensity before and after treatment illustrates it reached 40.0% in the first air sampling, 50.0%—in the second and 50.0%—in the third. Figure 7.33c shows that the largest number of odour units (7 OUE/m3) was formed from the air sample having the highest concentration of ammonia (181 ppm) before treatment. A comparison of the same air sample after treatment when ammonia concentration made 17 ppm shows that the value of odour units dropped to 4 OUE/m3. As expected, the smallest number of odour units (3 OUE/m3) was found in the air sample having the lowest acetone concentration (6 ppm) after treatment. Under ammonia concentration of 32 ppm in the same air sample before treatment, the value of odour units was 5 OUE/m3. At similar concentrations, the odour intensity of ammonia established in the wavy lamellar plate containing LF (linen fabric) is significantly higher than that of xylene and acetone. On average, the odour intensity of ammonia is 1.2 times higher than

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that of xylene and acetone, which determines its stronger sense in the environment near the investigated biofilter (Baltrėnas et al. 2014a).

7.4.4

Odour Identification when Applying the Olfactometer and the Tubular Biofilter

The samples required for analysing the odours of the supplied pollutant of the tubular biopacking material containing pine charcoal Pf6: fibre [10:1] are taken next to the polluted and treated air ducts. The collected samples are tested employing the olfactometer, which is done according to the instructions provided in the methodology. The findings are tabulated and presented graphically. Figure 6.20 shows a structural scheme for the tubular biopacking material. As provided in Fig. 6.20, the tubular plate is made of a perforated plastic tube of 18 mm in inner diameter and 20 mm in outer diameter. The height of the perforated tube is 300 mm. The perforated meshes are 2 mm in diameter and a step between them is equal to 3 mm. The entire perforated tube is filled with crushed pine charcoal in a 10:1 ratio with wood fibre. Figure 7.34a shows that the largest number of odour units (5 OUE/m3) was formed from the air sample having the highest concentration of acetone (172 ppm) before treatment. A comparison of the same air sample after treatment when acetone concentration made 17 ppm shows that the value of odour units dropped to 3 OUE/m3. As expected, the smallest number of odour units (2 OUE/m3) was found in the air sample having the lowest acetone concentration (5 ppm) after treatment. Under acetone concentration of 25 ppm in the same air sample before treatment, the value of odour units was 4 OUE/m3 (Baltrėnas et al. 2014a). A comparison of percentage reduction in odour intensity before and after treatment illustrates it reached 40% in the first air sampling, 60.0%—in the second and 50.0%—in the third. A comparison of the odour intensity of acetone among straight lamellar, wavy lamellar and tubular plates does not indicate any significant changes. After treatment, at similar concentrations, odour intensity remained almost identical, whereas before treatment the odour intensity of acetone was on average 11% higher compared to the straight lamellar plates. Figure 7.34b shows that the largest number of odour units (5 OUE/m3) was formed from the air sample having the highest concentration of xylene (178 ppm) before treatment. A comparison of the same air sample after treatment when xylene concentration made 18 ppm shows that the value of odour units dropped to 3 OUE/m3. As expected, the smallest number of odour units (2 OUE/m3) was found in the air sample having the lowest acetone concentration (6 ppm) after treatment. Under xylene concentration of 30 ppm in the same air sample before treatment, the value of odour units was 4 OUE/m3.

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A comparison of percentage reduction in odour intensity before and after treatment illustrates it reached 40% in the first air sampling, 40.0%—in the second and 50.0%—in the third. The evaluation of the values of the odour units (OUE/m3) of acetone and xylene pollutants provides that the odour intensity of acetone at similar concentrations is slightly higher than that of xylene (0.73 times on average). Figure 7.34c shows that the largest number of odour units (7 OUE/m3) was formed from the air sample having the highest concentration of ammonia (177 ppm) before treatment. A comparison of the same air sample after treatment when ammonia concentration made 17 ppm shows that the value of odour units dropped to 4 OUE/m3. As expected, the smallest number of odour units (3 OUE/m3) was found in the air sample having the lowest acetone concentration (6 ppm) after treatment. Under ammonia concentration of 32 ppm in the same air sample before treatment, the value of odour units was 6 OUE/m3. At similar concentrations, the intensity of ammonia odour at a ratio (10:1) of the tubular plate containing pine charcoal (Pf6) to that filled with wood fibre is notably higher than that of acetone or xylene. On average, the intensity of ammonia odour is 1.4 times higher than that of xylene and acetone, which determines its stronger sense in the environment near the investigated biofilter. The evaluation of the values of the odour units (OUE/m3) of acetone and xylene pollutants provides that the odour intensity of acetone at similar concentrations is slightly higher than that of xylene (0.80 times on average). The intensity of the odour emitted by all three air samples is directly proportional to an increase in the concentration of the ambient air sample. A comparison of percentage reduction in odour intensity before and after treatment illustrates it reached 42% in the first air sampling, 50.0%—in the second and 48.0%—in the third. The conducted experimental study on odours shows that the effectiveness of removing all three pollutants (acetone, xylene and ammonia) exceeds 80% in both cases (straight and wavy lamellar plates). The pollutant is most effectively removed at a higher concentration of 175/17 ppm and reaches approximately 90.0%. A comparison of the odour intensity of all three pollutants (acetone, xylene and ammonia) does not point out significant changes in the straight and wavy lamellar plates. After treatment, at similar concentrations, odour intensity remained almost identical, whereas before treatment the odour intensity of acetone was on average 15% higher compared to straight lamellar plates, which might be determined by a longer contact time of wavy lamellar plates. The conducted experimental study on odours shows that the effectiveness of removing all three pollutants (acetone, xylene and ammonia) exceeds 80% in all three pieces of equipment (straight and wavy lamellar and tubular plates). The pollutant is most effectively removed at a higher concentration of 175/17 ppm and reaches approximately 90.0%.

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7 The Importance of Biofiltration System Performance Parameters for the Effective. . .

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A comparison of the odour intensity of all three pollutants (acetone, xylene and ammonia) does not indicate any significant changes in the straight and wavy lamellar and tubular plates. After treatment, at similar concentrations, odour intensity remained almost identical, whereas before treatment the odour intensity of acetone was on average 13% higher compared to straight lamellar plates, which might be determined by a longer contact time of wavy lamellar plates (Baltrėnas et al. 2015c; Baltrėnas et al. 2014a).

Chapter 8

Natural and Inoculated Microorganisms as Important Component for Sustainability of Biofiltration System

This chapter presents the effect of natural (favoured by natural microorganisms) and engineered (governed by introduced microorganisms) phenomena on sustainability of biofiltration system constructed using natural materials for microorganism substrate. The results obtained in studying activities of microorganisms to produce cellulose and xylanase needed for lignocellulosic component hydrolysis as well as the provision of the load’s microorganisms with nutrients and the selection and the properties of microorganisms (i.e. bacteria, microscopic fungi and yeast) for effective biofiltration are presented in this chapter. The influence of such parameters as temperature and pH on the activities of the biofiltration system’s microorganisms as well as generated odours and their measurements by using the olfactometric method are described. Temperature is the major factor in determining the proliferation rate of microorganisms and the intensity of biochemical reactions. Different groups of microorganisms are adapted to living at varying temperatures. The microorganisms involved in the biodegradation processes of pollutants are divided into psychrophilic, mesophilic and thermophilic. Psychrophilic microorganisms can reproduce at a temperature between 7
C and 30
C. The membranes of psychrophilic microorganisms are high in unsaturated fatty acids, and therefore remain semi-liquid under cold conditions. The introduced microorganisms best proliferate at a temperature of 10–20
C. Mesophilic microorganisms are most frequently used for decomposing volatile organic compounds (VOCs) in small-scale biofilters at an optimum proliferation temperature of 20–45
(Darlington et al. 2001; Yamamoto et al. 2005). The optimum temperature for thermophilic microorganisms is 45–75
C (Dhamwichukorn et al. 2001; Kong et al. 2001; Van Liere and Van Groenestijn 2003). The scientists from the USA and Canada established high 99% efficiency of the droplet biofilter removing ethanol and methanol from the air using thermophilic bacteria. The best results were obtained by maintaining the temperatures of 53
C (ethanol decomposition) and 60
C (methanol decomposition) (Cox et al. 2001; Kong et al. 2001; Baltrėnas et al. 2015a).

© Springer Nature Switzerland AG 2020 P. Baltrėnas, E. Baltrėnaitė, Sustainable Environmental Protection Technologies, https://doi.org/10.1007/978-3-030-47725-7_8

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The cellular transport mechanisms of microorganisms, reactions, growth rate, the decomposition of one type and the synthesis of the other types of substances forming new compounds depend on the acidity of the medium expressed in pH ranging from 0 to 14. The pH of the neutral solution is 7, that of the acid solution—from 0 to7 and the alkaline solution varies from 7 to 14 (Biogas . . . 2013). Generally, optimal pH for the growth of microorganisms fluctuates between 6.5 and 7.5. Most microorganisms tolerate variations in pH in the range of 1–2 from the optimal value (Pukalskas 2007). Along changes in the reaction of the medium, the activity of heterotrophic enzymes also alters. Neutral and weakly alkaline or acidic media are used for biological air treatment. The concentration of hydrogen ions may range from 6 to 8 in the medium (MacNevin and Barford 2001). Most media applied for decomposing volatile organic compounds have a neutral concentration of hydrogen ions (pH ¼ 7).

8.1

8.1.1

The Selection and Properties of Microorganisms (Bacteria, Microscopic Fungi, Yeast) Capable of Removing Organic and Inorganic Volatile Compounds from the Polluted Air in the Biofilters Under Laboratory Conditions Screening Micromycetes Capable of Growing Under the Effect of Volatile Compounds

The ability of 8 strains of micromycetes to grow under the effect of acetone and xylene vapour was tested examining the collection of microorganisms from Research Laboratory for Biodegradability. Acetone was better tolerated than xylene. Five of eight strains grew in the environment of acetone vapour (Table 8.1; Figs. 8.1 and 8.2) Table 8.1 Growth in micromycetes under the effect of acetone and xylene vapour No. 1. 2. 3. 4. 5. 6. 7. 8.

Micromycetes Cladosporium resinae Cladosporium sp. Alternaria alternata Sporotrichum sp. Trichoderma harzianum Fusarium oxysporum Phoma eupyrena Acremonium sp.

Diameter of colonies, mm Control Acetone 30 + 10 0 78 10 51 0 90 0 90 3 47 ++ 53 18

Remark: + growth under scattered colonies; ++ growth intensity

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Fig. 8.1 The growth of Fusarium oxysporum in acetone vapour (control medium on the left)

Fig. 8.2 The growth of Trichoderma sp. in acetone and xylene vapour (control medium below)

although colonies were very small (3–34% compared to the control medium). Acetone was best tolerated by Acremonium sp. strain. Xylene vapour was tolerated by two tested strains only, but the colonies of Alternaria alternata and Phoma eupyrena were 32 and 57% in diameter, respectively, compared to the control medium (Baltrėnas et al. 2016a). Also, the ability to tolerate the volatile matter of nine strains of the micromycetes secreted from woven cork in the biofilter was verified. Besides, the introduced fungal strains had the highest tolerance for acetone vapour, except Aureobasidium sp. that did not grow in their environment (Table 8.2). Three tested strains (Geotrichum sp., Myrothecium sp. and Trichoderma sp.) tolerated xylene vapour, whereas only Trichoderma sp. strain remained in the ammonia-contaminated medium. It should be noted that Trichoderma sp. strain rather than control media was only once secreted form the packing material of the biofilter and grew better in the acetone-contaminated medium.

436

8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

Table 8.2 Growth in the micromycetes secreted from the biofilter under the impact of volatile vapour No. 1. 2. 3. 4. 5. 6. 7. 8. 9.

Micromycetes Aureobasidium sp. Geotrichum sp. Myrothecium sp. Rhizomucor pusillus Paecilomyces variotii Fusarium sp. Trichoderma sp. Penicillium sp. 14BF Penicillium sp. 2/3BF

Colony diameter, mm Control Acetone 15 8 15 10 16 20 53 30 10 10 58 45 30 60 15 13 16 5

Xylene 0 4 10 0 0 0 90 0 0

Ammonia 0 0 0 0 0 0 10 0 0

Fig. 8.3 Yeast tolerance for acetone

Evaluating the ability of micromycetes to absorb ammonia. All fungi, except for Cladosporium resinae, grew better or worse in the medium containing 0.1 M of urea. However, larger colonies compared to the nitrogen-free medium were made of the strains secreted from carbon or cork and included Cladosporium sp. K2, Aspergillus restrictus K6, Penicillium sp. BF-12, Paecilomyces variotii K7 and Penicillium sp. 2 K1. The latter three strains also grew well in the medium containing 0.6 M of urea although the remaining studied strains grew very poorly in this type of the environment. The ability of fungi to grow in the urea medium indicates the urease activity and the ability of these strains to tolerate or even absorb ammonia released during decomposition. Evaluating urease activity of yeast and tolerance for acetone and xylene. Fortyfour yeast species were studied for determining the urea activity of yeast and tolerance for acetone and xylene. All investigated species of Rhodotorula, Rhodosporidium, Tellomyces, Cryptococcus humicola, Sporobolomyces roseus, Trichosporon pullulans and Exophiala sp. were characteristic of urea activity. Acetone was tolerated by Yarrowia, some investigated species of Debaryomyces and Rhodotorula, all studied species of Tellomyces and Rhodosporidium, Cryptococcus humicola, Sporobolomyces roseus and Geotrichum fermentans (Fig. 8.3).

8.2 Cellulase and Xylanase Activity of Microorganisms to Provide them with the. . .

437

Only the yeast Aureobasidium pullulans and Yarrowia lipolytica were managed to grow in the xylene-contaminated environment. Evaluating urease activity of bacteria and tolerance for acetone and xylene. The results of the carried out study showed that none of 24 tested bacterial cultures grew under the effect of ammonia. Nine bacterial strains, including Burkholderia convexa 1, B. cepacia 2, B. cepacia 5, B. cepacia 7, Pseudomonas putida B 10, Ps. aeruginosa 17, Staphylococcus aureus 18 and Bacillus subtilis 21 grew well and were resistant to acetone and xylene (Baltrėnas et al. 2016a). Xylene-resistant strains were found to contain more bacteria than acetone. From 24 cultures tested, 16 bacterial strains were resistant and embraced Burkholderia cepacia 1, 2, 3, 4, 5, 7, Pseudomonas putida 10, 11, 13, 14, 15, Ps. aeruginosa 16, 17, Staphylococcus aureus 18, Bacillus subtilis 21 and Rhodococcus sp. 24. Thirteen bacterial strains were found to be acetone-resistant and embraced Burkholderia cepacia 1, 2, 5, 6, 7, Pseudomonas putida 9, 10, 11, 12, Ps. aeruginosa 17, Staphylococcus aureus 18, 19 and Bacillus subtilis 21. Research results have shown that fungi easily adapt to acetone vapour while xylene is more difficult to tolerate. All tested pollutants were tolerated by Trichoderma sp. strain secreted from the cork material of the biofilter. Xylene and ammonia were discovered to better tolerate micromycete strains secreted from the biofilter under laboratory conditions. The yeast Aureobasidium pullulans was found to have urease activity and tolerance for xylene, and Yarrowia lipolytica was tolerant for acetone and xylene. Ammonia was set to be intolerant for 24 tested bacterial strains, while acetone and xylene were tolerated by 9 bacterial strains attributed to Burkholderia cepacia 1, B. cepacia 2, B. cepacia 5, B. cepacia 7, Pseudomonas putida B 10, Ps. aeruginosa 17, Staphylococcus aureus 18 and Bacillus subtilis 21. The study has determined the microorganisms (bacteria, microscopic fungi, yeast) suitable for removing pollutants (ammonia, acetone and xylene) from gas.

8.2

Cellulase and Xylanase Activity of Microorganisms to Provide them with the Nutrients Contained in the Biopacking Material of the Biofilter Under Laboratory Conditions

The initial search for cellulase production. For the primary selection of cellulase and xylanase producers, the strains of the microorganisms secreted from the biofilters under laboratory conditions (22 strains of micromycetes, 5 strains of yeast and 14 bacterial strains) and stored in the collection of the Biodestruction Research Laboratory (12 strains of micromycetes, 8 strains of yeast and 7 bacterial strains) were used. Primary qualitative screening demonstrated that 12 of 34 tested strains of micromycetes showed higher cellulase activity. The strains were represented by 3 available and 9 secreted examples from biofilters (Tables 8.3 and 8.4; Fig. 8.4).

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8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

Table 8.3 Cellulase activity of micromycetes in Czapek medium containing carboxymethyl cellulose (CMC) No. of the specimen 1. 6. 7. 8. 10. 21 27 28 29 30 31 34

Micromycete Paecilomyces lilacinus EŽ-29 Phoma eupyrena BI-32C Stachybotrys atra BI-TP-D Curvularia lunata BI-AR2 Cladosporium resinae AK-01 Acremonium strictum 1–40-L Fusarium oxysporum Mi-122 Cladosporium herbarum 7KA Phoma pannorum BI-Al-19 Chaetomium globosum 3SA Cladosporium sp. L-7 pp Chrysosporium sp. L-G-3

The diameter of the area formed around the colony following 7 days, mm 4 2 4 2 1 2 1 8 2 5 8 2

Four micromycete strains (Paecilomyces variotii BF-K7-ac, P. variotii BF-K7-ks, Myrothecium sp. BF-20, Cunninghamella echinulata BF-1 K) secreted from the biofilter did not show any cellulase activity. The study disclosed that the cellulase activity of all other examined micromycetes was lower (zones ranged from 1 to 4 mm) (Baltrėnas et al. 2015a). Thirteen strains of yeast were tested, and five strains were found to have the highest cellulase activity: four strains—in the collection of the BRL (Aureobasidium pullulans BIA1.2, A. pullulans BIA1.1.1, A. pullulans BIA1.1.2, and A. pullulans BIA1.2.1) and one strain was secreted from biofilters (Aureobasidium sp.) in the zones of 10–11 mm. The cellulase activity zone of the yeast Exophiala sp. was smaller (3 mm). The other tested strains of yeast showed no cellulase activity. Preliminary qualitative screening included testing 21 bacterial strains, and 2 strains, including Bacillus subtilis 28 and Rhodococcus sp. 30, were secreted from biofilters and had the highest cellulase activity. The growth of all other bacterial strains tested in the medium was poor or moderate (Baltrėnas et al. 2016a). The initial search for xylanase producers. Enzymatic activity was considered taking into account the growth rate of microorganisms, the development of colonies

8.2 Cellulase and Xylanase Activity of Microorganisms to Provide them with the. . .

439

Table 8.4 Cellulase activity of micromycetes secreted from biofilters and grown in Czapek medium containing carboxymethyl cellulose (CMC) No. of the specimen 2. 3. 4. 5. 9. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 22. 23. 24. 25. 26. 32. 33.

Micromycete Penicillium sp. BF-28 Alternaria alternata BI-17 Aureobasidium pullulans BF-58 Geotrichum fermentans BF-55 Penicillium sp. BF-59 Paecilomyces variotii BF-K7-ac Paecilomyces variotii BF-K7-ks Penicillium sp. BF-14 Penicillium sp. BF-2 Trichoderma sp. BF-24ks Trichoderma sp. BF-24ac Aspergillus flavus BF-ks Rhizomucor pusillus BF-7 Myrothecium sp. BF-20 Fusarium sp. BF-15 Aspergillus fumigatus BF-81 Gliocladium viride BF-81 Aspergillus versicolor BF-4 Cunninghamella echinulata BF-1 K Mycelia sterilia (black) BF-70 Cladosporium cladosporioides BF-77 Stachybotrys sp. BF-90

The diameter of the area formed around the colony following 7 days, mm 3 2 8 6 2 0 0 5 6 Zone below the colony Zone below the colony 3 Zone below the colony 0 2 3 5 13 0 8 7 6

and the pigmentation of the micelle in the xylene-contaminated medium compared to analogous properties growing strains in carbon-free Czapek medium. Thirty four strains of micromycetes were tested, and ten strains showed the highest xylanase activity, including four strains from the collection of the BRL and six strains secreted from biofilters (Tables 8.5 and 8.6). The tested micromycete strains Curvularia lunata BI-AR2, Acremonium strictum 1–40-L, Cladosporium herbarum 7KA, Chrysosporium sp. L-G-3, Alternaria alternata BI-17, Aureobasidium pullulans BF-58, Penicillium sp. BF-14, Penicillium sp. BF-2,

440

8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

Fig. 8.4 Cellulase activity of micromycetes Aspergillus versicolor BF-4 (a) (zone of 13 mm) and Myrothecium verrucaria BF-81 (b) (zone of 5 mm) grown in Czapek medium containing carboxymethyl cellulose (CMC) Table 8.5 Xylanase activity of micromycetes stored in the laboratory of the BRL and grown in Czapek medium containing xylene No. of the specimen 1. 6. 7. 8. 10. 21 27

28 29

30 31 34

Micromycete Paecilomyces lilacinus EŽ-29 Phoma eupyrena BI-32C Stachybotrys atra BI-TP-D Curvularia lunata BI-AR2 Cladosporium resinae AK-01 Acremonium strictum 1–40-L Fusarium oxysporum Mi-122 Cladosporium herbarum 7KA Phoma pannorum BI-Al19 Chaetomium globosum 3SA Cladosporium sp. L-7 pp Chrysosporium sp. L-G-3

Colony diameter following 7 days, mm 30

Peculiarities of colony development Denser micelle

36

40

Colony is denser and larger than that in the control medium Colony is denser than that in the control medium Dense and dark micelle

33

Rare micelle

50

Dense, sporulating micelle

80

Growth equates to the control medium

22

Dense, sporulating micelle

42

Micelle is denser than that in the control medium

73

Micelle is denser than that in the control medium Micelle is denser than that in the control medium Micelle is denser than that in the control medium

33

28 65

8.2 Cellulase and Xylanase Activity of Microorganisms to Provide them with the. . .

441

Table 8.6 Xylanase activity of micromycetes secreted from biofilters and grown in Czapek medium containing xylene No. of the specimen 2. 3. 4. 5. 9. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 22. 23. 24. 25. 26. 32.

33.

Micromycete Penicillium sp. BF-28 Alternaria alternata BI-17 Aureobasidium pullulans BF-58 Geotrichum fermentans BF-55 Penicillium sp. BF-59 Paecilomyces variotii BF-K7-ac Paecilomyces variotii BF-K7-ks Penicillium sp. BF-14 Penicillium sp. BF-2 Trichoderma sp. BF-24-ks Trichoderma sp. BF-24-ac Aspergillus flavus BF-ks Rhizomucor pusillus BF-7 Myrothecium sp. BF-20 Fusarium sp. BF-15 Aspergillus fumigatus BF-81 Gliocladium viride BF-81 Aspergillus versicolor BF-4 Cunninghamella echinulata BF-1 K Mycelia sterilia (black) BF-70 Cladosporium cladosporioides BF-77 Stachybotrys sp. BF-90

Colony diameter following 7 days, mm 40

Peculiarities of colony development Dense micelle

65

Dense micelle

28

Dense micelle

20

Growth equates to the control medium Growth equates to the control medium Sporulation is more intense than that in the control medium Growth equates to the control medium Sporulation is more intense than that in the control medium Dense micelle Growth equates to the control medium Growth equates to the control medium Dense micelle

22 40 20 21 30 90 90 26 100 70 70 56 34 18 90

Growth equates to the control medium Colonies are larger than that in the control medium Colony throughout the plate Dense, sporulating micelle Sporulating micelle, denser than in the control medium Dense, sporulating micelle

25

Sparse high micelle throughout the plate Denser micelle throughout the plate Reduced sporulation

40

Dense, sporulating micelle

90

442

8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

Aspergillus fumigatus BF-81 and Stachybotrys sp. BF-90 had the highest xylanase activity. The growth of all their colonies was more intense than that in Czapek control medium, and the micelle was dense and sporulating. Six strains of micromycetes (Geotrichum fermentans BF-55, Penicillium sp. BF-59, Paecilomyces variotii BF-K7-ks, Trichoderma sp. BF-24-ks, Trichoderma sp. BF-24-ac, Rhizomucor pusillus BF-7) were secreted from the biofilter and had no xylanase activity. Their growth was similar to that in the control medium. All other tested micromycetes had lower xylanase activity (Baltrėnas et al. 2015c). The obtained results showed that all tested yeast strains did not show higher xylanase activity. Their growth was similar to that of the control medium (Baltrėnas et al. 2015c). Preliminary qualitative screening demonstrated that higher xylanase activity showed 4 in 21 tested bacterial strains that were secreted from biofilters (Staphylococcus aureus 17, Bacillus subtilis 20, Rhodococcus sp. 32, Rhodococcus sp. 39) and 5 strains included in the collection of the BRL (Burkholderia cepacia 2, B. cepacia 7, Pseudomonas aeruginosa 11, Burkholderia cepacia 12, Pseudomonas aeruginosa 24). The growth of these bacteria was quite intensive, but not much different from those grown the control medium. Higher xylanase activity was expressed in Rhodococcus sp. 39 strain the growth of which compared to the control medium was the highest. The xylanase activity of all other tested bacteria was poorly expressed.

8.2.1

Quantitative Evaluation of Cellulase Complex Activity

Cx (endoglucanase)—the evaluation of enzyme activity. Based on the pre-selection results, 8 micromycete strains (Aureobasidium pullulans BF-58, Penicillium sp. BF-2, Acremonium strictum 1–40-L, Myrothecium verrucaria BF-81, Aspergillus versicolor BF-4, Cladosporium herbarum 7KA, Cladosporium sp. L-7 pp., Stachybotrys sp. BF-90), 2 yeast strains (Aureobasidium pullulans BIA1.1.2 and Exophiala sp.) and 2 bacterial strains (Bacillus subtilis 28 and Rhodococcus sp. 30) were selected for quantitative research (Baltrėnas et al. 2015b). The obtained results showed that the cultivated microorganisms had different endoglucanase activity under liquid-phase fermentation conditions. The tested strains demonstrated that micromycete Acremonium strictum 1–40-L (21%) and the bacterium Bacillus subtilis 28 (15.9%) had the highest endoglucanase activity (Fig. 8.5). Heightened activity was observed in micromycete Cladosporium sp. L-7 pp. and the yeast A. pullulans BIA1.1.2, which made 10% and 10.2%, respectively. Endoglucanase activity of the strains of other tested microorganisms ranged from 4 to 9.6%. The evaluation of β—glucosidase activity. β-glucosidase activity of the tested microorganisms was found to be variable. Almost all studied strains of micromycetes had higher β-glucosidase activity than those of yeast and bacteria (Fig. 8.5). The highest β-glucosidase activity was expressed by Cladosporium sp. L-7 pp. (21%) and Acremonium strictum 1–40-L (17.6%). This activity of other

8.2 Cellulase and Xylanase Activity of Microorganisms to Provide them with the. . . C1

B-Glucosidase

Cx

443

25 20

%

15 10

Rhodococcus sp. 30

B. subtilis 28

Exophiala sp.

A. pullulans BIA1.1.2

Stachybotrys sp. BF-90

Cladosporium sp. L-7pp

C. herbarum 7KA

A. versicolor BF-4

M. verrucaria BF-81

A. strictum 1-40-L

Penicillium sp. BF-2

0

A. pullulans BF-58

5

Fig. 8.5 The activity of micromycetes cultivated in Czapek medium containing carboxymethyl cellulose (CMC), endoglucanase, β-glucosidase and cellobiohydrolase (%)

tested micromycetes fluctuated from 9.6 to 15.8%. Yeast strains exhibited higher β-glucosidase activity than the investigated bacterial strains. C1 (cellulobiohydrolase)—the evaluation of enzyme activity. The obtained results showed that the cultivated micromycetes under liquid-phase fermentation conditions had low cellulobiohydrolase activity and ranged from 0.2 to 1.4% (Fig. 8.5). Higher activity of this enzyme was expressed in Acremonium strictum 1–40-L (5%), whereas Aspergillus versicolor BF-4 did not indicate any activity at all. No cellulobiohydrolase activity was detected by cultivating yeast and bacteria in the medium containing cellulose powder as a carbon source. The strains of higher endoglucanase activity were also found to have the elevated activity of the enzymes of the cellulase complex. According to the results of the initial qualitative selection, the 12 most active cultures of microorganisms producing both cellulases and xylanases were selected. Quantitative screening disclosed that all tested micromycete strains demonstrated cellulase activity except for Aspergillus versicolor BF-4 that had no detectable cellulobiohydrolase activity.

444

8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

8.3

The Effect of Temperature and pH on the Activity of Microorganisms Present in the Biofilter Under Laboratory Conditions

8.3.1

Micromycetes Ability to Grow at Different Temperatures

The strains that showed cellulase or xylanase activity or were more frequently secreted from the packing material of the biofilter were selected for studying the effect of temperature on fungal growth. A total of 17 micromycete strains were tested for their ability to grow at the temperatures ranging between 18
C and 37
C (Baltrėnas et al. 2015c). The results of the conducted study showed that all examined fungal strains could grow at the temperatures of 18
C, 26
C and 30
C (Table 8.7, Fig. 8.6). However, as many as five tested strains did not tolerate a temperature of 37
C and died. Aureobasidium pullulans BF-58 and Mycelia sterilia (black) BF-70 strains showed the widest spectrum of growth.

8.3.2

Yeast Ability to Grow at Different Temperatures

A study of yeast ability to grow at different temperatures demonstrated that not all yeast strains were capable of developing at the varying temperature (Table 8.8). Compared to other investigated temperatures, all tested yeast strains showed slower growth at a temperature of 18
C. The yeast strains Candida lipolytica BIC6.3, C. lipolytica BIC6.6.9, Candida sp., Rhodotorula sp. and Sporobolomyces sp. secreted from different types of biofilters showed a capability of growing at all tested temperatures, including 18
C, 26
C, 30
C and 37
C. Aureobasidium sp. secreted from the biofilter did not grow at the temperatures of 18
C and 37
C, whereas Exophiala sp.—at a temperature of 37
C (Baltrėnas et al. 2016b).

8.3.3

Bacteria Ability to Grow at Different Temperatures

The study documented (Table 8.9) that 9 bacterial cultures, including Burkholderia cepacia 1, 2, 7, 12, Pseudomonas putida B 10, 25, Ps. aeruginosa 11, Bacillus subtilis 28 and Staphylococcus aureus 34, compared to the control medium, substantially grew at a temperature of +18
C. Thirteen bacterial cultures such as Burkholderia cepacia 1, 2, 7, 12, Pseudomonas putida B 10, 25, Ps. aeruginosa 11, 24, Staphylococcus aureus 17, 34, 37, Bacillus subtilis 20, 28 significantly developed at a temperature of +25
C.

8.3 The Effect of Temperature and pH on the Activity of Microorganisms Present in. . .

445

Table 8.7 The growth of micromycetes in Sabouraud agar at different temperatures No. of the specimen 2. 3. 4. 6. 8. 13. 14. 19. 20. 21. 23. 24. 26. 28. 31. 33. 34.

Micromycete Penicillium sp. BF-28 Alternaria alternata BI-17 Aureobasidium pullulans BF-58 Phoma eupyrena BI-32C Curvularia lunata BI-AR2 Penicillium sp. BF-14 Penicillium sp. BF-2 Myrothecium sp. BF-20 Fusarium sp. BF-15 Acremonium strictum 1–40-L Myrothecium verrucaria BF-81 Aspergillus versicolor BF-4 Mycelia sterilia (black) BF-70 Cladosporium herbarum 7KA Cladosporium sp. L-7 pp Stachybotrys sp. BF-90 Chrysosporium sp. L-G3

Diameter of colonies, mm 18
C 26
C 30
C 10.0  0 9.0  1.0 6.3  0.6 45  1.0 49  2.9 44  1.0

37
C 0 10  0.1

18.7  1.5

18.0  0

23.3  2.9

15.0  0

30.5  0.7

30.5  0.7

28.0  2.8

7.0  0.1

40  2.9

45  1.0

45  1.0

10  0.6

10.0  0 10.0  0 21.7  1.5 75  0.7 7  0.1

9.0  1.0 11.0  1.0 35.3  0.6 80  0 15  0.6

7.7  0.6 5.3  0.6 40.0  0 65  0.6 30

15  0.1

20  0.6

23  0.6

20  0

3.5  0.7

7.0  1.4

8.0  0

3.0  0

10  0

10  0.1

12  0.1

50

10.0  0

4.0  0

0

12.5  0.7

2.0  0

0

12  0 8  0.1

7  0.1 0

8.5  0.7 10.0  0 7  0.1 30  2.9

11  0.3 38  0.6

2.7  0.6 5.0  0 32.0  2.8 5  0.1 0

Five bacterial cultures covered Burkholderia cepacia 1, 7 Pseudomonas aeruginosa 11, 24, Staphylococcus aureus 27, 37 and rapidly grew at a temperature of +37
C.

8.3.4

pH Effect on the Activity of Biofilter Microorganisms

A study of micromycete ability to grow under different pH. The ability of 22 micromycete strains, embracing both the collection of the BRL and the agents of the packing material newly secreted from biofilter, to grow in the Sabouraud agar medium of different acidity (pH 3.5 to pH 8.5) was investigated. The obtained results showed that most of the tested strains tolerated both the acidic and alkaline medium (Table 8.10, Fig. 8.7). Compared to the control medium (pH 5.5) 11 tested strains

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8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

Fig. 8.6 The growth of some fungal strains at the temperatures of +18
, +26
, +30
and + 37
C: (a)—Phoma eupyrena BI, (b)—Chrysosporium sp. L-G-3 Table 8.8 Yeast ability to grow at different temperatures Tested temperature 18
C 26
C Yeast Yeast strains from the collection of the BRL Candida lipolytica BIC6.3 + + Candida lipolytica BIC6.6.9 + + Candida lipolytica BIC6.2 + + Candida lipolytica BIC6.4 + + Aureobasidium pullulans BIA1.2 + + Aureobasidium pullulans BIA1.1.2 + + Aureobasidium pullulans BIA1.1.1 + + Aureobasidium pullulans BIA1.2.1 + + Yeast secreted from different types of biofilters Candida sp. + + Sporobolomyces sp. + + Rhodotorula mucilaginosa + + Rhodotorula sp. + + Exophiala sp. + +

30
C

37
C

+ + + + + + + +

+ + – – – – – –

+ + + + +

+ + + + –

grew better or equally in the medium of pH equal to 3.5, 16—in the medium of pH equal to 7 and 14—in the medium of pH equal to 8.5. Although the growth was not uniform under different acidity of the medium, 7 fungal strains grew well in both the acidic and alkaline environments and covered Penicillium sp. BF-59, Paecilomyces variotii K7-ks, Trichoderma sp. BF-24-ks, Cunninghamella echinulata BK-1 K, Fusarium oxysporum Mi-122, Cladosporium herbarum 7KA and Cladosporium sp. L-7 pp. (Baltrėnas et al. 2015c).

8.3 The Effect of Temperature and pH on the Activity of Microorganisms Present in. . .

447

Table 8.9 The effect of temperature on the tested bacterial strains Bacterial strains Burkholderia cepacia 1 Burkholderia cepacia 2 Pseudomonas putida B 10 Burkholderia cepacia 7 Pseudomonas aeruginosa 11 Burkholderia cepacia 12 Bacillus subtilis 20 Staphylococcus aureus 17 Staphylococcus aureus 34 Pseudomonas putida 25 Bacillus subtilis 28 Pseudomonas aeruginosa 24 Staphylococcus aureus 27 Pseudomonas putida 26 Rhodococcus sp. 30 Staphylococcus aureus 37 Methylobacterium mesophilicum 29 Bacillus subtilis 31 Rhodococcus sp. 32 Bacillus subtilis 33 Bacillus subtilis 36 Micrococcus sp. 35 Bacillus subtilis 38 Rhodococcus sp. 39

+30
C (control medium) ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++

+18
C ++++ ++++ ++++ ++++ ++++ ++++ ++ +++ ++++ ++++ ++++ + +   +++ + +  +    

+25
C ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++ ++++ + + + ++++ +++ +  + +++   +

+37
C ++++ +++  ++++ ++++ +++  +++ +++  ++ ++++ ++++   ++++     ++   

Yeast ability to grow at different pH. Investigations into yeast ability to grow at different pH demonstrated that all tested yeast strains were capable of growing at different pH ranges (Table 8.11). All investigated Candida lipolytica strains showed better growth at pH equal to 7 and 8.5. The ability of bacteria to grow at different pH of the medium. The study found that acidic pH (pH 4.5) had the greatest negative effect on the tested bacteria. Under the aforementioned pH, only Pseudomonas putida B 26 grew very well and Staphylococcus aureus 27 grew well (Table 8.12). The media having pH 5.5 was more suitable for bacterial growth: the bacterial strains Pseudomonas aeruginosa 11, 24, P. putida B 10, 25, 26, Burkholderia cepacia 1, 2, 7, 12, Staphylococcus aureus 27, Rhodococcus sp. 32 and Bacillus subtilis 36 grew very well (Table 4.25) (Baltrėnas et al. 2016c). The bacterial strains Bacillus subtilis 28 and 38, Staphylococcus aureus 34, Methylobacterium mesophilicum 29 as well as the genera Rhodococcus sp. and Micrococcus sp. failed to grow. No effect on bacterial growth was observed when the pH of the medium reached 6.5 and 8.5. Similarly to the control medium, they grew very well under the pH of 7.03. The results of the study showed that

448

8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

Table 8.10 The growth of micromycetes in Sabouraud agar and the media of varying acidity No. of the specimen 2. 4. 6. 8. 9. 10. 12. 14. 15. 19. 20. 21 23 24 25 26 27 28 31 32 33 34

Micromycete Penicillium sp. BF-28 Aureobasidium pullulans BF-58 Phoma eupyrena BI-32C Curvularia lunata BI-AR2 Penicillium sp. BF-59 Cladosporium resinae AK-01 Paecilomyces variotii K7-ks Penicillium sp. BF-2 Trichoderma sp. BF-24ks Myrothecium sp. BF-20 Fusarium sp. BF-15 Acremonium strictum 1–40-L Myrothecium verrucaria BF-81 Aspergillus versicolor BF-4 Cunninghamella echinulata BK-1 K Mycelia sterilia (black) BF-70 Fusarium oxysporum Mi-122 Cladosporium herbarum 7KA Cladosporium sp. L-7 pp Cladosporium cladosporioides BF-77 Stachybotrys sp. BF-90 Chrysosporium sp. L-G-3

Diameter of colonies, mm pH 3.5 pH 5.5 pH 7 6.7  0.6 7.3  0.6 4.7  0.6 33.5  0.7 24.3  1.2 24.0  1.7

pH 8.5 4.7  0.6 32.0  1.0

24.3  1.6 20  0.6

34.3  1.6 40  1.2

24.0  1.7 40  0

32.0  1.0 40  0

17.3  0.6 32.0  3.6

14.3  1.2 26.3  1.5

28.3  1.5 16.5  0.7

14.3  1.2 10.0  0

+++

+++

+++

+++

17.0  1.0 90  0

19.7  0.6 90  0

17.3  1.2 90  0

17.3  1.2 90  0

90  0 50  1.7 13  0.6

90  0 80  0 14  0.1

90  0 80  0 18  0.1

70  0 80  0 17  0.1

18  1.0

22  0.7

23  0.6

35  1.7

9.0  0

9.5  0.7

10.5  0.7

6.0  0

90  0

90  0

90  0

90  0

60

10  0

11  0.6

8  0.1

45  0.7

40  1.7

48  0.7

50  1.7

10.0  0

10.0  0

11.0  1.4

12.5  2.1

13.5  0.7 15  0.7

10.0  0 13  0.0.1

12.5  0.7 10  0

11.0  1.4 10  0

7  0.1 33  1.4

10  0.1 37  1.0

11  0.1 44  1.7

10  0.1 47  1.4

5 micromycete strains out of 17 grew better at a temperature of 18
C, 7—at a temperature of 30
C and only 1—at a temperature of 37
C. Micromycete strains grew intensively over a wide range of pH varying from pH 3.5 to pH 8.5. It was found that tested Candida lipolytica BIC6.3 and C. lipolytica BIC6.6.9 from the collection of the BRL as well as the bio-filtered yeast Candida sp., Rhodotorula sp. and Sporobolomyces sp. were capable of growing at different temperatures and various pH. The best temperature for bacterial growth and development is +25–30
C. Thus, bacteria grow very slowly or do not grow at all in the acidic medium (pH 3.5) and best develop when pH equals 6.5–8.5. (Baltrėnas et al. 2015b).

8.3 The Effect of Temperature and pH on the Activity of Microorganisms Present in. . .

449

Fig. 8.7 The growth of some fungal strains under the pH of 3.5, 5.5, 7 and 8.5: (a)—Stachybotrys sp. BF-90, (b)—Chrysosporium sp. L-G-3 Table 8.11 Yeast ability to grow at different pH in the medium

pH of the medium 3.5 5.5 7 Yeast Yeast from the collection of the BRL Candida lipolytica BIC6.3 + + + Candida lipolytica BIC6.6.9 + + + Candida lipolytica BIC6.2 + + + Candida lipolytica BIC6.4 + + + Aureobasidium pullulans BIA1.2 + + + Aureobasidium pullulans BIA1.1.2 + + + Aureobasidium pullulans BIA1.1.1 + + + Aureobasidium pullulans BIA1.2.1 + + + Yeast secreted from different types of biofilters Candida sp. + + + Sporobolomyces sp. + + + Rhodotorula sp. + + + Rhodotorula mucilaginosa + + + Exophiala sp. + + +

8.5 + + + + + + + + + + + + +

450

8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

Table 8.12 The effect of pH on the tested strains of bacteria Bacterial strains Burkholderia cepacia 1

Control medium pH -7.03 ++++

Burkholderia cepacia 2

++++

Burkholderia cepacia 7

++++

Burkholderia cepacia 12

++++

Pseudomonas putida B 10

++++

Pseudomonas aeruginosa 11

++++

Staphylococcus aureus 18

++++

Bacillus subtilis 20

++++

Pseudomonas aeruginosa 24

++++

Pseudomonas putida 25

++++

Pseudomonas putida B 26

++++

Staphylococcus aureus 27

++++

Bacillus subtilis 28

++++

Methylobacterium mesophilicum 29 Rhodococcus sp. 30

++++

Bacillus subtilis 31

++++

Rhodococcus sp. 32

++++

Bacillus subtilis 33

++++

Staphylococcus aureus 34

++++

pH of the medium 4.5 5.5 6.5  +++ +++ + +  +++ +++ + +  +++ +++ + +  +++ +++ + + ++ +++ +++ + +  +++ +++ + +  ++ +++ +  ++ +++ +  +++ +++ + +  +++ +++ + + +++ +++ +++ + + + +++ +++ +++ + +   +++ +   +++ +   +++ +  + +++ +  +++ +++ + +  + +++ +   

Micrococcus sp. 35

++++





Bacillus subtilis 36

++++



Staphylococcus aureus 37

++++



+++ + +

Bacillus subtilis 38

++++





++++

+++ + +++ + +++ +

8.5 +++ + +++ + +++ + +++ + +++ + +++ + +++ + +++ + +++ + +++ + +++ + +++ + +++ + +++ + +++ + +++ + +++ + +++ + +++ + +++ + +++ + +++ +

(continued)

8.4 Microorganisms Abundance and the Varying Species in the Diversely Structured. . .

451

Table 8.12 (continued) Bacterial strains

Control medium pH -7.03

Rhodococcus sp. 39

++++

8.4

8.4.1

pH of the medium 4.5 5.5 6.5 +++ + 



+++ +

8.5 +++ + +++ +

Microorganisms Abundance and the Varying Species in the Diversely Structured Biofilters Under Varying Packing Materials and the Removal of Airborne Volatiles Under Laboratory Conditions The Development of Microorganisms and Varying Species in the Laboratory Biofilter with Straight Lamellar Plates Covered with the Packing Material of Non-woven Cork Under the Removal of Airborne Volatiles

The abundance of micromycetes and variations in dominant species. The carried out investigation included 54 samples of the biofilter packing material made of nonwoven cork with birch fibre (Figs. 6.15 and 6.16). Yet from the beginning of the experiment, the removal of acetone resulted in the development of micromycetes. Initially, a larger part of those were found at the bottom of the plate (wettest place), and, following 7 days, their number increased in the middle of the plate. Later, a tendency for the highest number of micromycetes at the top of the plate and the lowest number—at the most soaked bottom of the plate was observed (Fig. 8.8a) (Baltrėnas et al. 2015b). Higher humidity of the biofilter material in the middle and upper parts of the plate was observed during the process of removing xylene. The content of micromycetes increased slightly at the beginning of this stage. However, a decrease in micromycetes was observed at the end of the first week, especially in the upper and lower parts of the plate. At the beginning of the second week, the content of micromycetes reached its maximum values, but at the end it dropped to normal values again (except the middle of the plate where the large numbers of micromycetes remained). The removal of ammonia disclosed that the material was found to be highly soaked in almost all parts of the plate. This, along with the authorized pollutant, may have played a role in a rather significant reduction in the number of micromycetes. If 1  105–1.4  107 of micromycetes were found at the end of the xylene removal process, 1  103–5.4  106 g of d.w. was detected when ammonia was released.

8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

cfu/g of d.w.

cfu/g of d.w.

cfu/g of d.w.

452

1E+08 1E+07 1E+06 1E+05 1E+04 1E+03 1E+02 1E+01 1E+00

1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1E+03 1E+02 1E+01 1E+00

1E+12 1E+11 1E+10 1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1E+03 1E+02 1E+01 1E+00

1

2

3

3 7 10 14 16 21 24 28 31 35 3 7 10 14 3 7 10 14 Ammonia Xylene Acetone a) 1

2

3

3 7 10 14 16 21 24 28 31 35 3 7 10 14 3 7 10 14 Ammonia Xylene Acetone b) 1

2

3

3 7 10 14 16 21 24 28 31 35 3 7 10 14 3 7 10 14 Ammonia Xylene Acetone c)

Fig. 8.8 The content of micromycetes (a), yeast (b) and bacteria (c) in the packing material of nonwoven cork removing acetone, xylene and ammonia from the air (1—top, 2—middle and 3— bottom of the plate)

8.4 Microorganisms Abundance and the Varying Species in the Diversely Structured. . .

453

The high abundance of micromycetes in the acetone removal process taking place at the top of the plate was due to the development of the fungus Paecilomyces variotii characterized by lavish sporulation. The greatest diversity of the species of micromycetes (fungi of 3–4 genera) was identified in the middle of the plate, which may have been due to favourable humidity conditions. From the very start of the test, the fungus Aureobasidium was plentifully secreted, however, since the tenth day, more and more above-mentioned P. variotii was produced. At the bottom of the plate, the composition of the species of micromycetes changed the most: initially the species of the genera Aureobasidium and Fusarium were secreted. Also, the species of Aspergillus niger or Penicillium genera were frequently found. In the second half of the test, Aureobasidium and P. variotii were common, and Aspergillus niger and Rhizopus stolonifer occasionally grew. The fungus Geotrichum sp. sparingly existed at the beginning of the experiment and disappeared thus occasionally progressing from the 16th day and strongly developing from the 28th day at the bottom and top of the plate next to Aureobasidium sp. Between the 7th and 16th days, the fungus Fusarium, and following 10 days—the fungus Myrothecium sp. abundantly spread and later disappeared completely. Micromycete species in the xylene removal process remained similar to those in acetone removal from the air. Next, the fungus P. variotii and the species of the genera Aureobasidium sp. and Geotrichum sp. continued to dominate. Micromycete species changed slightly in the ammonia removal process. Along with the previously dominant species, Penicillium sp. and Myrothecium sp. reappeared. However, the fungi Geotrichum sp. and P. variotii took a dominant position. The abundance of yeast and variations in dominant species. Research results have shown that yeast can develop on the biofilter containing non-woven cork removing various pollutants (Fig. 8.8b). Yeast count was steadily increasing at all points in the biofilter plate when acetone was removed. The peak of their content was reached in the sample of the top of the biofilter plate on the 16th day and reached 1.5  107 cfu/g. From the 21st day of the study, yeast count stabilized at 106 cfu/g of d.w. and remained unchanged until the end of the test. The content of yeast at the bottom and middle of the biofilter plate was similar from the seventh day of the study and ranged from 105 to 106 cfu/g of d.w. The highest content of yeast for xylene removal was recorded in the sample of the top of the biofilter plate on the 40th day of the study and made 1.8  108 cfu/g of d.w. In the course of ammonia removal, the abundance of yeast was observed in the middle of the plate where yeast count reached 8.5  106 cfu/g of d.w. on the 50th day of testing. The yeast genera Rhodotorula was found to be predominant in the removal of acetone in the non-woven cork material of the laboratory biofilter. The yeast genera Rhodotorula and Exophiala were dominating in the removal of xylene and ammonia. Moreover, the yeast Candida guilliermondii was secreted. The abundance of bacteria and variations in dominant species. When removing acetone, bacterial count increased steadily at the top of the plate throughout the study up to the 28th day at 1.4  1011 cfu/g of d.w. (Fig. 8.8c). From the 31st day onwards, their numbers began declining (down to 5.7  109 cfu/g of d.w. on the 35th day). At the beginning, bacterial count decreased in the middle of the plate and started

454

8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

increasing from the 21st day to 7.8  1010 cfu/g of d.w. Following 35 days, a rapid bacterial decline is observed. At the beginning, bacterial count decreased steadily at the bottom of the plate, increased to 1.4  1011 cfu/g of d.w. from the 21st to the 28th days and remained similar up to the 35th day. Along with xylene removal, bacteria increased uniformly in all parts of the plate throughout the test. The highest bacterial secretion was established at the top of the plate and made 3.7  109 cfu/g of d.w. (on the 47th day), whereas the lowest reached 2.4  107 at the bottom of the plate on the 37th day. The beginning of ammonia removal demonstrated that the established maximum bacterial count made 5.1  1010 cfu/g of d.w. in the middle of the plate. At the subsequent stages of the study, bacterial count decreased evenly in the middle but remained higher at the bottom of the plate where the minimum content of bacteria was secreted throughout the test. Bacteria belonging to the genera Bacillus (B. cereus, B. subtilis), Pseudomonas (P. aeruginosa, P. putida and Staphylococcus (S. aureus) were found to be most abundant in the acetone removal process. Some bacterial genera Rhodococcus and Micrococcus were secreted. The greatest diversity of bacterial species was determined up to the 16th day. The composition of bacterial species changed along with xylene removal. The content of the bacterial species Rhodococcus increased P. and putida and B. subtilis prevailed in all analysed samples. The bacterium S. aureus was secreted only a couple of times. The removal of ammonia was dominated by S. aureus and B. subtilis. A low content of the bacterial genera B. cereus, Rhodococcus and Micrococcus was detected. The bacterial genus Pseudomonas was secreted only at the beginning of the ammonia removal process.

8.4.2

The Development of Microorganisms and Varying Species in the Laboratory Biofilter with Straight Lamellar Plates Covered with the Packing Material of Wood Fibre Under the Removal of Airborne Volatiles

The abundance of micromycetes and variations in dominant species. A total of 18 samples of the packing material of the laboratory biofilter with straight lamellar plates containing wood fibre are presented in Figs. 6.15 and 6.16. 3700 cfu/g of micromycetes were secreted from the control sample of birch fibre. When using this substance for the packing material of the biofilter, the abundance of fungi ranged from 2.9 to 33.9 thou cfu/g of d.w. in the first 2 weeks but following 15 days their number increased to 106 cfu/g of d.w. of the packing material in the middle and top of the plate and remained similar until the end of the experiment (Fig. 8.9a). Xylene was found not to reduce the content of micromycetes in comparison with acetone, while the content of fungi on the packing material decreased by 25 to 30 times with ammonia removal but remained highest in the middle part of the plate.

8.4 Microorganisms Abundance and the Varying Species in the Diversely Structured. . . 2

1

1E+08

455

3

cfu/g of d.w.

1E+07 1E+06 1E+05 1E+04 1000 100 10 0

II

I

1E+08

IV III Samplings a)

Top

Middle

8

10 Days

V

VI

18

23

Bottom

cfu/g of d.w.

1E+07 1E+06 1E+05 1E+04 1000 100 10 0

5

13

1E+13 1E+12 1E+11 1E+10 1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 0

At the bottom of the plate At the middle of the plate At the top of the plate

Control medium 1 Control medium 2

Content of bacteria, (cfu)

b)

1

2

3

1

2 3 1 Acetone

2

3

1

2

3

1

2 3 Xylene

1 2 3 Ammonia

Number of the sample c)

Fig. 8.9 The content of micromycetes (a), yeast (b) and bacteria (c) in the laboratory biofilter covered with wood fibre removing volatile substances acetone (I–IV), xylene (V) and ammonia (VI)

456

8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

At the start of the experiment, yeast predominated (only 1–2 fungal colonies grew). However, following 2 weeks, the diversity of fungal species increased. Next to Paecilomyces variotii, a rapid development of the yeast genera Aureobasidium and Geotrichum was observed. When removing xylene, P. variotii is particularly abundant in all parts of the plate. The process of removing ammonia reduces the content of fungi and changes the composition of species. Penicillium sp. appears alongside P. variotii and remains as the only fungal genus in the middle of the plate along with Geotrichum sp. The abundance of yeast and variations in dominant species. The removal of acetone resulted in the increased content of yeast and made 7.2  107 cfu/g. The removal of ammonia caused a sudden drop in the content of yeast down to 6.3  105 cfu/g. of d.w. (Fig. 8.9b). The yeast Rhodotorula mucilaginosa was found predominating in the removal of all investigated volatile substances. The yeast Sporobolomyces sp. was also frequently detected in the removal of acetone. A slight change in yeast species was recorded when ammonia was removed. The abundance of bacteria and variations in dominant species. The investigated bacterial count rose steadily at the top of the plate increasing the concentration of acetone and xylene until the 26th day (5.3  109 cfu/g of d.w. (Fig. 8.9c). Under the impact of ammonia, their content dropped to 8.4  108 cfu/g of d.w. The content of bacteria grew rapidly in the middle of the plate and reached its peak on the 19th day (1.1  1012 cfu/g of d.w.). At the bottom of the plate, bacterial count grew until the 12th day (4.0  1010 cfu/g of d.w.) and remained similar under xylene removal, but increased to 9.0  1010 cfu/g of d.w. when ammonia was removed. Thus, it can be assumed that a high concentration of the pollutant has no effect on bacterial growth. The bacterial genera Bacillus (B. cereus, B. subtilis), Pseudomonas (P. aeruginosa, P. putida), Staphylococcus (S. aureus) and Rhodococcus sp. were mostly detected. The richest diversity of bacterial species was found following 12 days. The bacterial species B. subtilis were particularly abundant in 33 days (Baltrėnas et al. 2015a).

8.4.3

The Development of Microorganisms and Varying Species in the Laboratory Biofilter with Straight Lamellar Plates Covered with the Packing Material of Wood Fibre and Linen Fabric Under the Removal of Airborne Volatiles

The abundance of micromycetes and variations in dominant species. A total of 18 samples of the packing material of the laboratory biofilter with straight lamellar plates containing wood fibre and linen fabric are presented in Figs. 6.15 and 6.16. The use of these materials assisted in a rapid development of micromycetes thus making their content equal to 1  105 in 1 week and 1  106 cfu/g—in 2 week time

cfu/g of d.w.

8.4 Microorganisms Abundance and the Varying Species in the Diversely Structured. . . 2

1

1E+10 1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 0

I

1E+08

457

3

II

IV III Samplings a)

Top

Middle

8

16 12 Days b)

V

VI

21

26

Bottom

cfu/g of d.w.

1E+07 1E+06 1E+05 1E+04 1000 100 10

1E+13 1E+12 1E+11 1E+10 1E+09 1E+08 1E+07 1E+06 100000 10000 1000 100 10 0

3

At the bottom of the plate At the middle of the plate At the top of the plate

Control medium 1 Control medium 2

Content of bacteria, (cfu)

0

1

2

3

1

2 3 1 Acetone

2

3

1

2

3

1

2 3 Xylene

1 2 3 Ammonia

Number of the sample c)

Fig. 8.10 The content of micromycetes (a), yeast (b) and bacteria (c) in the laboratory biofilter having straight lamellar plates covered with wood fibre and linen fabric removing volatile substances acetone (I–IV), xylene (V) and ammonia (VI)

458

8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

(Fig. 8.10a). The further removal of acetone resulted in the fungal growth of 108 cfu/ g, which did not decrease and even increase when removing xylene. Under the removal of ammonia, the content of micromycetes declined only in the middle and top parts of the plate. Compared to other biofilters, smaller reduction was noticed. At the beginning of the test, the yeast genera Geotrichum and Aureobasidium were more abundantly secreted at the bottom of the plate while Paecilomyces variotii was dominant at the middle and top parts of the plate. A week later, Aspergillus fumigatus was hardly detected on the types of the packing material containing nonwoven cork and wood fibre, and therefore spread quite widely across all parts of the plate. The quantity of this fungus increased until the end of the acetone removal process but was replaced by the fungal genus Penicillium as xylene was started to be removed. The removal of ammonia did not affect the composition of fungal species but their total number decreased slightly. The abundance of yeast and variations in dominant species. In 3 days of testing, the minimum yeast count was determined in the sample covering the top of the plate at 3.3  104 cfu/g of d.w. (Fig. 8.10b). The removal of acetone at the top of the plate resulted in a steady increase in yeast count and reached a maximum (1.8  106 cfu/g) on the 16th day of testing. Yeast count remained unaffected changing the pollutant (xylene) in the samples of the middle and top areas of the plate and increased to 6.6  107 cfu/g of d.w. As ammonia removal started, yeast count remained unchanged in the middle and top areas of the plate but decreased to 1.1  106 cfu/ g of d.w. For removing volatile matter, the yeast Rhodotorula mucilaginosa and Sporobolomyces sp. dominated in all samples of the biofilter plate. As ammonia removal started, variations in yeast species were established, and the yeast Rh. mucilaginosa and Exophiala sp. started dominating (Baltrėnas et al. 2015c). The abundance of bacteria and variations in dominant species. The highest bacterial count was observed in the middle of the plate on the seventh day at 1.3  1012 cfu/g of d.w. and the lowest—on the first day at 1.8  107 cfu/g of d.w. (Fig. 8.10c). Bacterial count at the bottom of the plate steadily decreased (from 1.1  1012 on the first day to 2.9  109 cfu/g of d.w. on the 35th day), and therefore it can be assumed that other investigated pollutants have a negative effect on bacterial growth. At the top of the plate, bacterial count continues to increase exposing the biofilter to acetone and xylene. Biofilter treatment with ammonia reduces bacterial count down to 3.4  109 cfu/g of d.w. The bacterial genera Bacillus (B. cereus, B. subtilis, B. mycoides), Pseudomonas (P. aeruginosa, P. putida), Staphylococcus (S. aureus) and Micrococcus sp. made the largest part. The widest diversity of bacterial species was detected following 21 days. On the 7th and 28th days, the new bacterial species Methylobacterium mesophilicum abundantly developed. B. mycoides were secreted in 21 days and the typical fluorescent bacterium P. aeruginosa—in 28 days (Baltrenas et al. 2015).

8.4 Microorganisms Abundance and the Varying Species in the Diversely Structured. . .

8.4.4

459

The Abundance of Microorganisms and Varying Species in the Laboratory Biofilter with Wavy Lamellar Plates Covered with the Packing Material of Wood Fibre and Linen Fabric Under the Removal of Airborne Volatiles

The abundance of micromycetes and variations in dominant species. The study involved 33 samples of the laboratory biofilter with wavy lamellar plates covered with the packing material containing linen fabric and wood fibre (Figs. 6.17 and 6.18). Micromycetes developed intensively since the beginning of decontamination (Fig. 8.11a). Following 3 days of acetone removal, fungal count reached 108 cfu/g of d.w. and remained until the end of the test. The number of fungi was lower in the biofilter with straight lamellar plates. This might be an effect of the micromycetes prevalent during the test rather than the influence of plate configuration. The fungi Paecilomyces variotii and Geotrichum sp. prevailed testing the biofilter with straight lamellar plates, and the fungal genera Penicillium predominated testing the biofilter with wavy lamellar plates producing a large number of spores. During the acetone removal process, most fungi were present at the top part of the plate although at the end of the test a slightly larger number of those were secreted at the bottom of the plate. When removing xylene, more fungi were available in the middle and top areas of the plate, whereas when removing ammonia they concentrated in the middle. The removal of ammonia was found not to be related to a decrease in micromycetes. Since the very beginning of the test, the fungal genera Penicillium and P. variotii widely spread. Following 3 days, the fungus Aureobasidium sp. dominated at the top of the plate and later disappeared. At the same time, the fungal genus Trichoderma was detected in the lower wet part of the plate but not secreted at the later stage. The composition of fungal species remained almost unchanged when removing xylene and ammonia, and Penicillium sp. was more predominating in the middle and P. variotii—at the top of the plate (Repečkienė et al. 2015). The abundance of yeast and variations in dominant species. The highest yeast count was found to be 5.5  109 cfu/g of d.w. (Fig. 8.11b). When removing xylene, the content of yeast decreased at all points of the biofilter with wavy lamellar plates. While removing ammonia, yeast count dropped at the top and middle areas and remained unchanged at the bottom of the plate. The yeast genus Candida was found to be predominant in the removal of various pollutants. Only C. guilliermondii was detected in the xylene filtration process, and the yeast Rhodotorula mucilaginosa and Exophiala sp. were secreted supplying ammonia. The abundance of bacteria and variations in dominant species. Throughout the study, bacterial count ranged from 107 to 109 cfu/g of d.w. at both the top and middle area of the plate (Fig. 8.11c). The highest bacterial count was found at the bottom of the plate under supplied xylene and made 3.9  108 cfu/g of d.w., whereas

8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

log cfu/g of d.w.

460

1E+10 1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 0

I

II

III

1

2

IV V VI Acetone

VII

3

I II Xylene

I II Ammonia

a)

log cfu/g of d.w.

Top 1E+10 1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 0

I

II

III

IV V VI Acetone

Middle

VII

Bottom

I

II Xylene

I II Ammonia

log cfu/g of d.w.

b) At the bottom of the plate At the middle of the plate At the top of the plate 1E+10 1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 0 I II III IV V VI VII I II I II Acetone Xylene Ammonia c)

Fig. 8.11 The content of micromycetes (a), yeast (b) and bacteria (c) in the packing material made of wood fibre and linen fabric in the biofilter having wavy lamellar plates removing acetone, xylene and ammonia from the air

8.4 Microorganisms Abundance and the Varying Species in the Diversely Structured. . .

461

the lowest was established at the top of the plate and equalled 1.0  107 cfu/g of d.w. Meanwhile, ammonia adversely affected bacteria and their number decreased down to 8.5  107 cfu/g of d.w. The bacterial genera Bacillus (B. cereus, B. subtilis), Pseudomonas (P. aeruginosa, P. putida) and Staphylococcus (S. aureus) made the largest part. The greatest diversity of bacterial species was established under ammonia removal (Repečkienė et al. 2015).

8.4.5

The Abundance of Microorganisms and Varying Species in the Laboratory Biofilter with Wavy Lamellar Plates Covered with the Packing Material of Non-woven Cork and Wood Fibre Under the Removal of Airborne Volatiles

The study was performed employing the laboratory biofilter (Figs. 6.17 and 6.18). The abundance of micromycetes and variations in dominant species. Eleven samples of the biofilter with straight and wavy lamellar plates covered with the packing material of non-woven cork and wood fibre were analysed. Micromycetes were found to develop very intensively since the beginning of the acetone removal process and gradually increased over the course of the test for 4 weeks (Fig. 8.12a). From the fifth week onwards, a decrease in the initial fungus content was observed: at that time, only 5.8  105 cfu/g of d.w. was secreted on the wavy lamellar plates of the biofilter. On the sixth week, the minimum content of fungi on the straight lamellar plates was reached and made 8.9  106 cfu/g of d.w. This could be due to a significant drop in the humidity of the plates at that time. Subsequently, micromycetes returned to baseline levels and remained high in the xylene and ammonia removal processes. It should be noted that a higher initial content of micromycetes was established on the straight rather than on wavy lamellar plates of the biofilter throughout the testing period (except xylene removal). This may have been due to the prevalence of different types of micromycetes on the plates of different configurations. A study of straight lamellar plates demonstrated that the fungi Penicillium sp. and P. variotii (on the fifth–sixth weeks) developed very rapidly due to abundant spore production. Meanwhile, the fungal genus Trichoderma dominated on the wavy plates. On the eighth week, the fungus Acremonium sp. appeared. The removal of ammonia involved a large quantity of yeast that developed rapidly thus inhibiting the growth of other fungi. The fungus Trichoderma sp. dominated on the wavy plates of the biofilter; however, from the third to the fifth week, instead of them, Penicillium sp. grew faster. Also, Zygorhynchus sp., P. variotii and Aspergillus fumigatus were detected. The abundance of yeast and variations in dominant species. Under the removal of acetone in the biofilter with straight lamellar plates coated with the packing material

462

8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

cfu/g of d.w.

Straight 1E+10 1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 0

I

Wavy

II III IV V VI VII VIII IX Acetone a) Straight

XI X Xylene Ammonia

Wavy

cfu/g of d.w.

1E+12 1E+09 1E+06

1000 0

I

II III IV V VI VII VIII IX Acetone

XI X Xylene Ammonia

b)

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Fig. 8.12 The content of micromycetes (a), yeast (b) and bacteria (c) in the biofilter having straight and wavy lamellar plates covered with the packing material made of non-woven cork + wood fibre removing volatile substances acetone, xylene and ammonia from the air

8.4 Microorganisms Abundance and the Varying Species in the Diversely Structured. . .

463

of non-woven cork, the maximum yeast count was set on the seventh day and reached (4.5  0.2)  107 cfu/g of d.w. Yeast count was highly variable throughout the study (Fig. 8.12b). A large content of yeast was observed in the biofilter with wavy lamellar plates covered with non-woven cork and made (1.5  0.1)  108 cfu/ g of d.w. Sporobolomyces roseus was found to be dominating for removing volatile compounds in both types of the biofilters with straight and wavy lamellar plates covered with non-woven cork. Also, the yeast Exophiala sp. was secreted from the biofilter with wavy lamellar plates. The abundance of bacteria and variations in dominant species. When removing pollutants, the content of bacteria in the packing material of straight lamellar plates ranged between 107 and 1010 cfu/g of d.w. Compared to acetone, the elimination of xylene reduced bacterial count. Ammonia had no significant effect on bacterial growth (Fig. 8.12c). The content of bacteria in the biofilter with wavy lamellar plates was similar throughout the study and made approximately 108 cfu/g of d.w. The composition of the bacterial genera and species secreted from the investigated biofilters was almost the same. The bacterial genera Bacillus (B. cereus, B. subtilis), Pseudomonas (P. aeruginosa, P. putida, P. fluorescens), Staphylococcus (S. aureus), Rhodococcus sp. and Micrococcus sp. made the largest part. B. cereus was secreted until the middle of the test. The highest bacterial diversity was established in the biofilter with wavy lamellar plates sampling for the eighth time. The obtained results included the bacterial genera B. subtilis, B. cereus, S. aureus, P. fluorescens, Rhodococcus sp. and Micrococcus sp. (Baltrėnas et al. 2015b).

8.4.6

The Abundance of Microorganisms and Variations in Dominating Species in the Laboratory Biofilter with Straight Lamellar Plates and Selected Microorganisms Under the Removal of Airborne Volatiles

The beginning of decontamination demonstrated that the laboratory biofilter with straight lamellar plates (Figs. 6.15 and 6.16) was heavily polluted with the fungal genus Penicillium. After the adaptation period (3 days), the content of fungi ranged from 1.8  107 to 5.8  108 cfu/g of d.w. (Fig. 8.13a). A similar content of fungi remained throughout acetone filtration but decreased abruptly (to 106 cfu/g of d.w.) when xylene removal started. The content of fungi increased slightly to 107cfu/g of d.w. during ammonia removal. The inserted micromycetes were not secreted at the beginning of the test but survived on the biopacking material of the biofilter because a share of the total number of micromycetes began increasing gradually over time. Their growth was mostly frequently overshadowed by the abundant population of the fungal genus

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8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . . Top 1E+10 1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 0

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Fig. 8.13 The content of microorganisms in the laboratory biofilter with straight lamellar plates containing the microorganisms selected for the collection of the BRL. (a)—micromycetes, (b)— yeast, (c)—bacteria

8.4 Microorganisms Abundance and the Varying Species in the Diversely Structured. . .

465

Penicillium. In the third sampling, the selected fungi were secreted from all parts of the plate. The highest amounts of the inserted micromycetes were observed when the total number of fungi decreased. The removal of xylene and ammonia showed a reduction in the fungal genus Penicillium, and the proportion of the inserted fungi ranged from 0 to 66.7% (under xylene removal) and from 4.8 to 27.3% (under ammonia removal). The composition of the prevailing micromycetes on biofilter plates varied depending on the pollutant being removed. When removing acetone, the fungal genus Penicillium constantly prevailed. The colour of colonies suggests those were various species that changed during the test. The removal of xylene, and ammonia in particular, led to a significant increase in the proportion of the fungal genus Geotrichum, which might be a cause for the simultaneous proliferation of the inserted micromycetes. The most commonly detected genera included Cladosporium herbarum (detection rate—33.3%), Myrothecium verrucaria (24.2%), Stachybotrys sp. (18.2%) and Aspergillus versicolor (9.1%). The supply of the suspension of the yeast A. pullulans, Exophiala sp. and Sporobolomyces roseus disclosed that not all yeast were capable of adapting in the laboratory biofilter with straight lamellar plates. While removing pollutants, the total number of yeast ranged from 106 to 109 cfu/g of d.w. throughout the test (Fig. 8.13b). The second removal of xylene and the onset of removing ammonia decreased yeast count. The study proved that the selected yeast best adapted in the middle of the straight lamellar plates of the laboratory biofilter with a detection rate ranging from 1 to 100%. The detection rate of yeast selected for acetone removal ranged from 0.8% to 78.3% at the top of the plate. Supplying xylene showed that the detection rate of the selected yeast increased continuously at all points of testing while in the case of removing ammonia only the selected yeast were detected in the middle of the plate. No selected yeast A. pullulans was detected throughout the study. Other transmitted yeast Exophiala sp. and Sporobolomyces roseus were detected removing various contaminants. In addition to the yeast mentioned above, the yeast R. mucilaginosa was also found at all investigation points of the plate. The study reported that the bacteria Bacillus subtilis, Burkholderia cepacia and Rhodococcus sp. adapted to the removal of airborne volatile substances—acetone, xylene and ammonia. Investigation into the removal of acetone indicated that bacterial count ranged from 107 to 1012 cfu/g of d.w. at all points of the plate (Fig. 8.13c). The removal of xylene showed a decrease in bacterial count at the top, bottom and in the middle of the plate. As for ammonia supply, the investigated bacterial count ranged from 1.0  108 cfu/g of d.w. in the middle to 4.1  108 cfu/g of d.w. at the bottom of the plate. Thus, it can be assumed that ammonia had no effect on bacterial growth, and the number of the selected bacteria Bacillus subtilis, Burkholderia cepacia and Rhodococcus sp. was much lower. Most of the selected bacteria were secreted by removing acetone in the middle of the plate taking samples the fifth time and reached 5.0  105 cfu/g of d.w. In the course of further studies, the content of the selected bacteria started decreasing.

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8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

Extremely low bacterial secretion was observed after last removal—the sixth time, which made only 31 cfu/g of d.w. at the bottom of the plate. An interesting point is that the content of the selected bacteria decreased after last filtration while the total number of bacteria was simultaneously set to be the highest. The bacterial genera Bacillus (B. cereus, B. subtilis), Pseudomonas (P. aeruginosa, P. putida, P. fluorescens), Staphylococcus (S. aureus), Rhodococcus sp. and Micrococcus sp. made the largest part. As for the selected bacteria Bacillus subtilis, Burkholderia cepacia and Rhodococcus sp., the latter counted 24% thus making the least amount. Burkholderia cepacia accounted for 36%, and Bacillus subtilis for—60% (Baltrėnas et al. 2015b).

8.4.7

The Abundance of Microorganisms and Variations in Dominating Species in the Laboratory Biofilter with Wavy Lamellar Plates and Selected Microorganisms Under the Removal of Airborne Volatiles

Micromycetes developed intensively in the laboratory biofilter with wavy lamellar plates (Figs. 6.17 and 6.18) since the beginning of the decontamination and their number gradually increased. In 3 days of acetone removal, fungal count reached the values of 105–106 cfu/g of d.w. and increased up to 107–108 cfu/g of d.w. During xylene removal, fungal count decreased again to their original values. Throughout the investigated period, the removed increased concentrations of ammonia included almost 105 cfu/g of d.w. of fungi. Subsequently, xylene was again removed by reducing its concentrations. The content of fungi increased again to 106 cfu/g of d.w. The largest fluctuations in their content were observed while removing acetone concentrations that decreased from 5.6  103 to 2.6  106 cfu/g of d.w. In most cases, fungi were mainly found in the middle part of wavy lamellar plates eliminating only the low concentrations of xylene. More fungi were secreted from the top part of the plates. No fungi were secreted at the beginning of the study. Following 5 days, individual fungi appeared on the top of the plate and after 10 days on the whole plate. However, the proportion of the selected fungi was small, and Cladosporium herbarum was mostly frequently secreted. When a high concentration (700 mg/ m3) of the pollutant is eliminated, the selected fungi disappear because they are overshadowed by the fungal genus Penicillium. For xylene removal, the selected fungi on individual biofilter samples accounted for 30–50% of all fungal colonies. In addition to the aforementioned C. herbarum, Aspergillus versicolor evolved. Myrothecium verrucaria was occasionally exposed to ammonia and Stachybotrys sp.—to the reduced concentration of the pollutant. However, their proportion to all fungi varied between 0.7 and 27.3%.

8.4 Microorganisms Abundance and the Varying Species in the Diversely Structured. . .

467

The removal of low xylene concentrations succeeded in secreting all species of the selected fungi, but not every time and not in varying abundance. A significant growth in these fungi (Stachybotrys sp. in particular) was observed removing the low concentrations of acetone for the last three times. They accounted for 33–100% of all fungal isolates. This indicates that the fungi selected in the laboratory biofilter with wavy lamellar plates survived to remove all pollutants and, under favourable conditions, intensified their development. As for the microorganisms stored in the BRL and additionally selected for straight lamellar plates, the number of fungi was by one order higher in the removal of all pollutants. This was due to the natural micromycetes prevalent during the test rather than because of the configuration of the plates. The study of straight lamellar plates demonstrated that the fungus Penicillium sp. producing a large number of spores developed rapidly while taking into account wavy lamellar plates, their number was reduced, particularly in the second half of the test when the fungal genus Trichoderma became very widespread. It was also observed that wood fibre detached from the plates in many places and therefore slowed down fungal development. When removing ammonia from the air, the fungi Geotrichum sp. and consequently Trichoderma became widespread. The latter disappeared only at the end of the test removing the low concentrations of acetone. Not all yeast were found to be capable of adhering and developing in the laboratory biofilter with wavy lamellar plates. By removing and gradually increasing the concentration of various pollutants, the total number of yeast ranged from 106 to 107 cfu/g of d.w. throughout the study. The removal of acetone in the middle and top parts of the biofilter plate disclosed that the selected yeast were overshadowed by microscopic fungi. For removing the high concentrations of acetone, the detection rate of the selected yeast ranged from 1.2% in the middle of the plate to 100% at all points throughout the plate. During the xylene removal process, the number of yeast ranged from 105 to 7 10 cfu/g of d.w. When supplying the high concentrations of xylene, the selected yeast Sporobolomyces sp. and Exophiala sp. were most frequently detected, except for the first step of removing xylene when, in addition to the above-mentioned yeast, Rhodotorula mucilaginosa was identified at the bottom of the plate. At the lower removal concentrations of xylene from the third to the fifth step, yeast was not detected at the bottom of the plate because it was overshadowed by Trichoderma sp. At the removal of the high concentrations of ammonia, yeast count ranged from 105 to 107 cfu/g of d.w. At the end of the ammonia removal process, no yeast was secreted at the bottom of the biofilter plate, because it was completely suppressed by Trichoderma sp. The percentage of the selected yeast was highly variable at the removal of the low concentrations of ammonia. On the third day of removing ammonia, the content of the yeast inserted at the bottom and top of the plate ranged from 0.9 to 2.8%. No inserted yeast A. pullulans was detected throughout the study. Other transmitted yeast Exophiala sp. and Sporobolomyces roseus were identified during the

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8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

removal of various pollutants and, in addition to the above-mentioned yeast, R. mucilaginosa was found at all points of the tested plate. An uneven decrease in different pollutant concentrations adversely affects yeast count and decreases the diversity of species. The inserted yeast A. pullulans and Sporobolomyces sp. were not detected reducing pollutant concentration. Other inserted yeast Exophiala sp. was found during the removal of various pollutants. Besides the inserted yeast Exophiala sp., the yeast Rhodotorula mucilaginosa was detected. The study showed that the bacteria Bacillus subtilis, Burkholderia cepacia and Rhodococcus sp. adapted and survived the removal of volatile substances such as acetone, xylene and ammonia from the air. Bacterial count at the bottom, middle and top of the plate ranged between 106 and 1010 cfu/g of d.w. For acetone removal, most bacteria were secreted by sampling for the third time, and the number of bacteria reached 1.0  1010 cfu/g of d.w. at the top of the plate. The smallest amount of bacteria was detected by sampling for the first time at the top of the plate where bacterial count made 2.5  106 cfu/g of d.w. Bacterial count was higher in xylene rather than in acetone removal and increased steadily at the top, middle and bottom of the plate from 9.0  107 cfu/g of d.w at the bottom to 6.0  109 cfu/g of d.w. in the middle of the plate. For ammonia supply, the investigated bacterial count ranged from 4.0  107 cfu/g of d.w. at the top of plate to 6.0  109 cfu/g of d.w. in the middle of the plate. The content of the inserted bacteria Bacillus subtilis, Burkholderia cepacia and Rhodococcus sp. was significantly lower. For acetone and xylene removal, the number of the inserted bacteria ranged between 102 and 105 cfu/g of d.w. Most of bacteria secreted in the middle of the plate while removing xylene made 1.1  105 cfu/g of d.w, whereas the lowest content was equal to 2.3  102 cfu/g of d.w. while eliminating acetone at the bottom of the plate. The study found that the total number of bacteria and the number of the inserted bacteria were the highest under xylene removal. The release of ammonia demonstrated that the content of the inserted bacteria significantly decreased from 104 to 0 cfu/g of d.w. No bacteria were detected at the bottom of the plate at the time of sampling for the second time, at the middle and top of the plate and at the time of sampling for the fourth time. The supply of pollutants and a reduction in their concentrations resulted in a slight decrease in the total bacterial count and ranged from 106 to 109 cfu/g of d.w. The smallest amount of bacteria was secreted in the middle of the plate supplying acetone at 4.2  106 cfu/g of d.w. while the largest content was that of ammonia making 3.8  109 cfu/g of d.w. at the bottom of the plate. Extremely low levels of bacteria were secreted from acetone removal, which ranged from 0 to 102 cfu/g of d.w. The detected bacterial genera Bacillus (B. cereus, B. subtilis), Pseudomonas (P. aeruginosa, P. putida, P. fluorescens), Staphylococcus (S. aureus, Staphylococcus sp.), Burkholderia (Burkholderia cepacia), Rhodococcus sp. and Micrococcus sp. made the largest part. The richest diversity of species was found in the removal of acetone following the fourth sample—the bacteria Bacillus subtilis, B. cereus, Pseudomonas putida, P. aeruginosa, P. fluorescens, Staphylococcus aureus, Rhodococcus sp. and

8.4 Microorganisms Abundance and the Varying Species in the Diversely Structured. . .

469

Burkholderia convexa were prevailing. While removing ammonia after the first sampling, the bacterial species Bacillus subtilis, B. cereus, Staphylococcus aureus, Pseudomonas putida, P. fluorescens, Burkholderia convexa as well as Micrococcus sp. and Staphylococcus sp. were predominating. Ammonia removal in the descending order after the second sampling resulted in the secreted bacterial species Bacillus mycoides, and after the third sampling—in the bacterial species B. Anthracis. When removing xylene and acetone in the descending order, Staphylococcus sp. was intensively secreted. As for the inserted bacteria Bacillus subtilis, Burkholderia cepacia and Rhodococcus sp., the content of the latter genus appeared to be the lowest and accounted for 14% of the total bacterial input. Burkholderia cepacia accounted for 26% and Bacillus subtilis for 60%. A summary of the research findings of laboratory benches for biofilters with different packing materials provides that the use of innovative laboratory biofilters assisted with integral investigation into the appropriateness of different packing materials (wood fibre, linen fabric and non-woven cork) for the growth and bio-destructive activity of various groups of microorganisms involved in the process of removing airborne volatile pollutants. All tested types of the packing material were suitable for the growth of micromycetes, yeast and bacteria removing acetone, xylene and ammonia in succession. The results of the study showed that the number of microorganisms and the composition of species in the biofilters were subject to the type of the packing material. Although the fungal genera Paecilomyces variotii and Penicillium prevailed, however, Aspergillus fumigatus was also common on linen fabric. The most common yeast genera were represented by Rhodotorula mucilaginosa, Candida guilliermondii, Sporobolomyces and Exophiala, bacteria included the species of the genera Bacillus, Pseudomonas and Staphylococcus. Also, the bacteria Methylobacterium mesophilicum and Bacillus mycoides were detected in the biofilter containing linen fabric and wood fibre. The removed pollutants were observed to have an effect on the development of the individual groups of microorganisms in the packing materials of the biofilter. Acetone and xylene were the least inhibitors of proliferating microorganisms. Ammonia had the greatest negative effect on the abundance of micromycetes and yeast. The use of the packing material made of linen fabric and wood fibre reduced their number less than the application of the packing materials containing nonwoven cork and wood fibre. The removal of xylene and ammonia compared to acetone reduced bacterial count. A comparison of the distribution of microorganisms on the straight and wavy lamellar plates disclosed that micromycetes developed intensively employing the biofilter with wavy lamellar plates containing linen fabric since the very beginning of the test and their content reached 108 cfu/g of d.w. Meanwhile, the same figure in the biofilter with straight lamellar plates was achieved only from the second half of the test. Yeast developed faster on wavy lamellar plates, and the number of the secreted bacteria was similar but more stable on wavy lamellar plates. The fungal genera Penicillium sp. and Paecilomyces variotii predominated on straight and Trichoderma—on wavy lamellar plates made of non-wove cork. The

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8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

biofilter with wavy lamellar plates made of non-woven cork was characterized by a higher content of yeast and species diversity. The composition of bacterial genera and species isolated from these biofilters was almost the same. For the first time, investigation covered the developmental intensity of microorganisms in different parts of biofilter plates. Micromycetes and yeast were found to develop better in the top and middle sections of the plates. The abundance of micromycetes and species diversity was different. The yeast genera Aureobasidium and Geotrichum predominated in the lower most soaked while the fungi Paecilomyces variotii—in the top more drier part of the plate. The highest variety of fungal species was established in the middle part. The largest number of bacteria was found in the middle and lower parts of the plate. The insertion of the laboratory biofilter with straight lamellar plates and the set of the microorganisms stored in the BRL demonstrated that the microorganisms successfully evolved although not all inserted microorganisms uniformly adapted to the packing material of the biofilter. The proportion of the inserted microscopic fungi ranged from 0% to 81%, and effectively developed under xylene and ammonia removal. Micromycetes Cladosporium herbarum and Myrothecium verrucaria adapted best. For removing acetone, the detection rates of the inserted yeast ranged from 0.8% to 78.3%, while those of xylene and ammonia increased continuously. All inserted bacteria adapted to the laboratory biofilter. The investigated Bacillus subtilis accounted for 60%, Burkholderia cepacia—for 36% and Rhodococcus sp.— for 24%. The insertion of the laboratory biofilter with wavy lamellar plates and the set of the microorganisms stored in the BRL showed that the microorganisms strongly developed. For removing the increased concentrations of acetone, microscopic fungi developed intensively, whereas a slight decrease in their content was noticed eliminating xylene and ammonia. The most frequently secreted inserted fungi were Cladosporium herbarum at the beginning and Stachybotrys sp. at the end of the test. The development of the inserted fungi was favoured by the lower concentrations of pollutants as a result of a reduction in natural fungal species. The removal of the higher concentrations of various pollutants was found to have an impact on the uneven distribution of the inserted yeast while the unevenly reduced concentrations of different pollutants had a devastating effect on the content of yeast thus reducing their diversity. The bacterial count of Bacillus subtilis, Burkholderia cepacia and Rhodococcus sp. adapted and survived the removal of airborne volatiles. Bacillus subtilis dominated accounting for 60%, Burkholderia cepacia made 26% and Rhodococcus sp.—14%. The communities of microorganisms formed during the removal of volatile matter remained stable during the long-term test and were actively involved in pollutant biodegradation processes. The prevalence of different groups of microorganisms in the ecosystem of the packing material of the biofilter allows for the more efficient removal of different volatiles from the environment. The obtained results are important for optimizing biological processes in industrial biofilters eliminating various airborne pollutants (Baltrėnas et al. 2015b).

8.4 Microorganisms Abundance and the Varying Species in the Diversely Structured. . .

8.4.8

471

The Abundance of Natural Microorganisms and Variations in Species in the Tubular Air Treatment Laboratory Biofilter Containing Biochar Produced of Birch and Pine Wood Incinerated at Different Temperatures Under the Removal of Airborne Volatiles

The study involved the samples taken from the tubular air treatment biofilter (Fig. 6.20) with natural microorganisms and biochar samples produced of birch and pine wood incinerated at various temperatures. Nine different biochar samples made of birch and pine wood incinerated at different temperatures were submitted for analysis: birch biochar (750
C) fraction of 2–4 mm + wood fibre (Bf4_10), birch biochar (750
C) fraction of 4–6 mm + wood fibre (Bf6_10), birch biochar (300
C) fraction of 2–4 mm, birch biochar (450
C) fraction of 2–4 mm, birch biochar (750
C) fraction of 2–4 mm, pine biochar (300
C) fraction of 2–4 mm, pine biochar (300
C) fraction of 4–6 mm, pine biochar (450
C) fraction of 2–4 mm and pine biochar (750
C) fraction of 2–4 mm. The study showed that microorganisms evolved on the provided biochar samples but their numbers varied widely. Throughout the study (version of the control medium following 10, 20 and 30 days), the amount of the secreted bacteria was the highest while that of yeast—the lowest (Fig. 8.14a–c). As for the samples of the control medium, bacterial count ranged from 1.0  104 to 8.0  104 cfu/g, but no bacteria were detected in the sample of pine biochar (450
C) fraction of 2–4 mm. The content of micromycetes in these samples was very low (1.3–20.0 cfu/g) and was not found on three samples of pine biochar. No yeast was detected in all tested control samples of birch and pine biochar incinerated at the temperatures of 300
C and 750
C. Yeast was secreted only from the sample of the pine biochar (450
C) fraction of 2–4 mm (Fig. 8.14a–c). However, under non-sterile conditions, the microorganisms exposed to biochar began developing quite intensively at sufficient humidity, and in 10 days the number of their colony-forming units reached thousands or even millions of 1 g. For longer periods of sample storage (20 and 30 days), the abundance of bacteria and micromycetes increased steadily in all analysed biochar samples, except that yeast was not secreted from birch biochar samples incinerated at all temperatures, and their growth was inhibited by microscopic fungi and bacteria. Bacteria rapidly developed in the birch biochar (750
C) fraction of 2–4 mm + wood fibre (Bf4_10) and pine biochar (750
C) fraction of 2–4 mm: cfu/g reached 1.4  109 and 1.3  109, respectively, in 30 days. The growth of micromycetes was best suited to birch biochar with fibre additives—their growth was visually seen and secreted cfu/g made 3.9  107 (in 20 days) and 1.8  108 (in 30 days). Micromycetes intensively grew on the birch biochar (300
C) fraction of 2–4 mm and amounted to 9.8  109 (in 30 days). The most suitable substrate for yeast growth was found to be the birch biochar (750
C) fraction of 4–6 mm + wood fibre (Bf6_10): yeast count varied from 0 to 9.8  107 cfu/g within 30 days.

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8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . . Control medium

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Fig. 8.14 The content of bacteria (a) micromycetes (b) and yeast (c) at different temperatures of burnt birch and pine wood: I—birch biochar (750
C) fraction (2–4 mm) + wood fibre (Bf4_10), II—birch biochar (750
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473

Thus, the most suitable substrate for the development of microorganisms was the birch biochar (750
C) fraction of 4–6 mm + wood fibre (Bf6_10) and the birch biochar (750
C) fraction of 2–4 mm + wood fibre (Bf4_10). The composition of microorganism species on biochar was not diverse and varied relatively little. The investigated samples mainly involved the bacterial families Bacillaceae: Bacillus subtilis, B. cereus and Staphylococcus aureus. The maximum composition of bacterial species was established in the sample of the birch biochar (750
C) fraction of 4–6 mm + wood fibre (Bf6_10): Bacillus subtilis, B. cereus, Pseudomonas aeruginosa, P. putida, Staphylococcus aureus, Burkholderia cepacia and Xanthomonas sp. The spread of the fungal genus Fusarium was observed in the middle of the test (in 20 days exposure in the humid chamber). The sporulating fungal genera Aspergillus, Penicillium and Paecilomyces were the most widespread. The composition of micromycete species also changed over time. Only four fungal genera, including Aspergillus flavus, A. niger, Penicillium sp. and Paecilomyces variotii, were secreted from control birch biochar. No biochar micromycetes were found on pine wood, except the sample (300
C) of the fraction of 2–4 mm where Aspergillus flavus developed (Baltrėnas et al. 2015b). The yeast Rhodotorula mucilaginosa and Candida guilliermondii predominated in the sample of the birch carbon (750
C) fraction of 4–6 mm + wood fibre (Bf6_10). The study disclosed that the yeast Rhodotorula mucilaginosa and Candida guilliermondii prevailed in pine biochar incinerated at various temperatures (300
C, 450
C, 750
C).

8.4.9

The Abundance of Natural Microorganisms and Variations in Species in the Tubular Structure of the Plate of the Laboratory Biofilter Filled with Pine Wood Biochar (Pf6) and Wood Fibre Under the Removal of Airborne Volatiles

The study involved the samples taken from the tubular air treatment biofilter (Fig. 6.20) with natural microorganisms that form under certain conditions, including a temperature of 30
C and the relative humidity of around 95%. Pine biochar (Pf6) and wood fibre (10:1) were selected for the biopacking material of the biofilter. A total of 12 samples were submitted. The study revealed that bacteria, yeast and micromycetes were capable of growing on the wood biochar biofilter thus removing airborne volatiles such as acetone,  ⁄ Fig. 8.14 (continued) fraction (2–4 mm), VI—pine biochar (300
C) fraction (2–4 mm), VII—pine biochar 300
C) fraction (4–6 mm), VIII—pine biochar (450
C) fraction (2–4 mm) and IX—pine biochar (750
C) fraction (2–4 mm)

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8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

xylene and ammonia, but their numbers varied considerably. Their content ranged from 4.4  107 cfu/g (14th day) for removing acetone to 1.3  1011 cfu/g (59th day) for removing ammonia from the air (Fig. 8.15a). Therefore, the lowest level of supplied ammonia does not have a significant negative effect on bacteria and even promote their growth. Micromycetes were sparse and ranged from 60 to 2200 cfu/g for the first 2 weeks (Fig. 8.15b). The packing material was noticeably dry at the time. However, in 21 days, as the humidity of the packing material increased significantly, the abundance of micromycetes also began rising. Yet following 28 days, their number reached 10 million cfu/g of d.w., remained for 42 days, and then another row grew. It should be noted that when ammonia removal started, the humidity of the filter was very high. The number of micromycetes possibly did not actually decrease during the first week. The previous tests showed this volatile substance was highly toxic, and therefore the content of fungi found on biochar declined significantly in 2 week time. Yeast is capable of developing on this type of the filter, but its growth is partially suppressed by proliferating micromycetes. Yeast peak was reached in 1 month (28 days) of acetone removal and reached 1.9  108 cfu/g. As the pollutant changed, yeast count increased to 5.9  107 cfu/g under xylene removal but decreased significantly down to 1.3  104 cfu/g when removing xylene (Fig. 8.15c). The study identified the predominant genera and species of bacteria. The majority of bacteria secreted from the wood biochar biofilter belonged to the genera Bacillus (Bacillus subtilis, B. cereus), Staphylococcus (Staphylococcus aureus), Pseudomonas (Pseudomonas aeruginosa, P. putida), Methylobacterium (Methylobacterium mesophilicum), Rhodococcus sp. and Micrococcus sp. (Baltrėnas et al. 2016b). After the first day, the composition of bacterial species did not differ from that of the control version—two bacterial genera and species, including Staphylococcus aureus and Bacillus subtilis, were secreted. The highest species diversity was observed in 42 days treating the biofilter with acetone—7 bacterial genera and 8 bacterial species were secreted (Bacillus subtilis, B. cereus, Staphylococcus aureus, Pseudomonas aeruginosa, Micrococcus sp., Rhodococcus sp., Methylobacterium mesophilicum). In 71 days, only the most resistant bacteria such as Bacillus subtilis, Staphylococcus aureus and Rhodococcus sp. remained. The variety of micromycete species was subject to the time of disposal and removed volatile substances. At the beginning of the test, the biofilter was moisture-free, and therefore the dry matter fungal genera Cladosporium and Aspergillus dominated. Later, the spore-producing fungal genera Paecilomyces variotii and Penicillium spread, but the aforementioned genera did not disappear either. Towards the end of xylene and the beginning of ammonia removal processes, the fungal genus Penicillium gradually decreased until only Cladosporium herbarum and Aspergillus versicolor remained (Baltrėnas et al. 2015b). Rhodotorula mucilaginosa was found dominating on the packing material containing biochar (Pf6) and wood fibre when removing volatile matter. For eliminating acetone, Rhodotorula mucilaginosa and Candida sp. prevailed. Changes in

Content of bacteria CFU

8.4 Microorganisms Abundance and the Varying Species in the Diversely Structured. . .

1E+12 1E+11 1E+10 1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 0

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II III IV V VI VII VIII IX X a)

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II III IV V VI VII VIII IX X

XI

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Content of bacteria CFU

1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 0

b)

Content of yeast CFU

1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 0

I

II III IV V VI VII VIII IX X

XI

c) Fig. 8.15 The content of bacteria (a) micromycetes (b) and yeast (c) making colony-forming unit per 1 g of dry weight (cfu/g of d.w.) on the wood biochar biofilter (removed volatile substances include: I–VII—acetone (days 1, 7, 14, 21, 28, 35 and 42), VIII–IX—xylene (days 49 and 52) and X–XI—ammonia (days 59 and 71))

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8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

pollutants resulted in the removal of the yeast Candida sp. and Aureobasidium pullulans began predominating.

8.4.10 The Abundance of Microorganisms and Variations in Species in the Tubular Air Treatment Biofilter Filled with Pine Biochar (Pf6), Wood Fibre and Selected Microorganisms Under the Removal of Airborne Volatiles A study of the samples taken from the tubular air treatment biofilter (Fig. 6.20) disclosed that the suspension of the selected bacteria (Bacillus subtilis, Burkholderia cepacia (¼B. convexa) and Rhodococcus sp.), micromycetes (Cladosporium herbarum and Stachybotrys sp.) and yeast (A. Pullulans, Exophiala sp. and Sporobolomyces roseus), more or less adapted and survived under the removal of airborne volatiles—acetone, xylene and ammonia. A total of 20 biofilter samples of pine biochar (Pf6) were provided. For removing the increasing concentrations of volatiles from the air, acetone included six, xylene—four and ammonia—three samples, while descending concentrations made two samples of ammonia and xylene each and three samples of acetone. During the study, for removing acetone, xylene and ammonia from the air, the total amount of bacteria in the carbon biofilter was sufficiently high and ranged between 107 and 1011 cfu/g of d.w. Most bacteria throughout the study were secreted in 20 days. The elimination of acetone resulted in the amount of bacteria equal to 1.2  1011 cfu/g of d.w. (Fig. 8.16a) (Baltrėnas et al. 2015a). The number of the selected bacteria was significantly lower (Fig. 8.16b). In the first 5–20 days of acetone removal, the amount of the selected bacteria ranged from 1.3  101 (fifth day) to 7.3  101 cfu/g of d.w. (20th day). Meanwhile, the number of the bacteria selected on the 22nd day increased significantly and reached 7.6  104 cfu/g of d.w. This bacterial count remained highest throughout the study. After xylene removal in 30 days time and ammonia removal in 45 days time, no bacteria were secreted (Fig. 8.16b). Acetone had the minimal effect on the selected bacteria. At the beginning of the experiment, under acetone removal, the content of fungi was very high and grew from 107 to 109 (Fig. 8.17a). The main part consisted of the widely spread fungal genus Penicillium. Higher fluctuations in content were observed removing xylene, while for ammonia elimination, the number of fungi was reduced to 106. A drastic reduction in fungi occurred at the end of removing low ammonia concentrations. Their numbers were difficult to recover when removing xylene. Fungal content increased only after the removal of acetone. The study found that not all selected yeast were capable of developing on the carbon filter: yeast count ranged from 0 to 108 cfu/g of d.w. (Fig. 8.17b).

log cfu/g of d.w.

8.4 Microorganisms Abundance and the Varying Species in the Diversely Structured. . .

1E+12 1E+11 1E+10 1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 0

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Increase

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Decrease

5 10 15 20 22 27 30 32 33 35 40 45 50 55 60 65 70 75 80 Ammonia Xylene Acetone Acetone Xylene a) Increase

Decrease

1E+04 1000 100 10 0 Days 5 10 15 20 22 27 30 32 33 35 40 45 50 55 60 65 70 75 80 Ammonia Xylene Acetone Xylene Acetone b)

Fig. 8.16 The total number (a) of bacteria and the content of selected (b) bacteria on the biochar biofilter containing the selected bacteria of the BRL

The detected bacterial genera Bacillus (B. cereus, B. subtilis), Pseudomonas (P. aeruginosa, P. putida), Staphylococcus (S. aureus), Burkholderia (Burkholderia cepacia), Rhodococcus sp. and Micrococcus sp. made the largest part. The highest species diversity was found in 71 days of acetone removal—the bacterial genera Bacillus subtilis, Pseudomonas putida, P. aeruginosa, Staphylococcus aureus, Burkholderia convexa, Rhodococcus sp. and Micrococcus sp. predominated (Baltrenas et al. 2015). At the beginning of the study, the fungal genus Penicillium developed very rapidly, which subsequently overshadowed the growth of the selected species.

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8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 0

I II III IV V VI VII VIII IX X XI XII XIII XIV XV XVI XVII XVIII XIX XX

cfu/g of d.w.

1E+10 1E+09

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1E+09

Xylene a) Increase

Ammonia Xylene Acetone

Decrease

log cfu/g of d.w.

1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 0 Days 5 10 15 20 22 27 30 32 33 35 40 45 50 55 60 65 70 75 80 Xylene Acetone Ammonia Xylene Acetone b) Fig. 8.17 The total number of micromycetes (a) and yeast (b) on the biochar biofilter containing the selected micromycetes and yeast of the BRL

However, they almost disappeared under the effect of ammonia, and then the selected microorganisms became dominant. It should be noted that all selected fungi survived in the carbon biofilter. However, under the increased concentrations of xylene and ammonia, Cladosporium herbarum was secreted more frequently, whereas Aspergillus versicolor most intensively developed at the low concentrations of xylene and acetone. After applying the suspension of the yeast A. pullulans, Exophiala sp. and Sporobolomyces roseus, not all yeast were capable of attaching and developing on the filter filled with biochar (Pf6) and wood fibre. The yeast A. pullulans was not secreted throughout the study. Exophiala sp. best adapted to the filter filled with

8.4 Microorganisms Abundance and the Varying Species in the Diversely Structured. . .

479

biochar (Pf6) and wood fibre. Under a drop in ammonia concentration and the subsequent elimination of the low concentrations of other pollutants, the selected yeast were not secreted.

8.4.11 The Abundance of Microorganisms and Variations in Species in the Tubular Air Treatment Biofilter Filled with Birch Biochar (Pf6) and Fibre Under the Removal of Xylene from the Air Having examined the tubular filter filled with pine biochar (Pf6) (Fig. 6.20), for comparison purposes, the filter with birch biochar (PF6) was studied. A total of 13 birch biochar (Bf6) biofilter samples were provided. The study of the samples taken from the biofilter with the packing material containing biochar demonstrated that microorganisms were capable of functioning on the biofilter of this material when removing xylene. The study showed bacterial count was the largest. However, compared to the findings of the previous research, the content of the secreted bacteria, micromycetes and yeast was similar (Fig. 8.18a–c). At the lowest xylene concentration, bacteria were secreted taking samples for the first time and made 3.8  1010 cfu/g of d.w. A similar content of yeast was detected taking samples for the 11th time and amounted to 1.6  1010 cfu/g of d.w. (Fig. 8.18c). The lowest bacterial detection rate was found sampling for the seventh time and reached 3.6  107 cfu/g of d.w. Yeast count was very uneven and constantly changing throughout the study (Repečkienė et al. 2015). At the beginning of the test, the amount of micromycetes was equal to 8.8  105 cfu/g of d.w. Later, the content of micromycetes increased, but fluctuation remained uneven and ranged from 5.4  105 cfu/g of d.w. on the third week to 4.4  108 cfu/g of d.w. on the fifth week of testing (Fig. 8.18b). A more significant reduction in micromycetes was observed in the last weeks of the test. A drop in the content of fungi was most often directly related to a decrease in the humidity of the packing material containing biochar. The bacterial genera Bacillus (B. cereus, B. subtilis), Pseudomonas (P. fluorescens, P. putida, P. aeruginosa), Staphylococcus (S. aureus), Rhodococcus sp. and Micrococcus sp. were found to be the most abundant. The highest species diversity was established while removing xylene for the third time when the bacterial species Bacillus subtilis, B. cereus, Staphylococcus aureus, Pseudomonas fluorescens, P. putida and the bacterial genus Rhodococcus sp. prevailed and while removing xylene for the fifth time when the bacterial species Bacillus subtilis, B. cereus, Staphylococcus aureus, Pseudomonas fluorescens, P. aeruginosa and the bacterial genus Micrococcus sp. predominated.

8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

log cfu/g of d.w.

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1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 0

Fig. 8.18 The content of bacteria (a), micromycetes (b) and yeast (c) on the biochar biofilter in the xylene removal process

8.4 Microorganisms Abundance and the Varying Species in the Diversely Structured. . .

481

The fungal genera Penicillium and starters Aspergillus versicolor were found to be the most abundantly secreted. The fungal genus Chaetomium was secreted for the first time throughout the study (third and fourth of removing). The fungal genus Aspergillus, preliminary described as A. candidus, were also secreted for the first time. In addition, the fungi Aureobasidium sp., Geotrichum sp., Aspergillus fumigatus and Stachybotrys sp. were secreted from the biofilter containing biochar. On the 11th week, the growth of all fungi was suddenly overshadowed by the abnormal spread of yeast. The yeast Aureobasidium sp. was found predominating on the biofilter with the packing material containing birch biochar and wood fibre during the xylene removal process. The summarized results of the microbiological study of the tubular air treatment biofilter demonstrate that the most suitable substrate for the development of all microorganisms is the birch biochar (750
C) fraction of 4–6 mm + wood fibre (Bf6_10) and the birch biochar (750
C) fraction of 2–4 mm + wood fibre (Bf4_10). The abundantly sporulating fungal genera Aspergillus, Penicillium and Paecilomyces, the yeast genera Rhodotorula, Candida, Cryptococcus and the bacterial genera Bacillus, Pseudomonas and Staphylococcus predominated throughout the test. For removing acetone, xylene and ammonia from the air, the spread of micromycetes on the biofilter containing pine biochar (Pf6) and wood fibre was established highly dependent on the humidity of the packing material as the content of fungi increased along with the humidification of the packing material. The fungal genus Penicillium was most frequently found, and the genera Aspergillus and Cladosporium were also quite common. The tested pollutants did not inhibit bacterial growth. The greatest diversity of bacterial species was detected by the exposure of the biofilter to acetone: Bacillus subtilis, B. cereus, Staphylococcus aureus, Pseudomonas aeruginosa, Micrococcus sp., Rhodococcus sp. and Methylobacterium mesophilicum were identified. Although yeast is capable of developing in the environment containing pollutants acetone and xylene, their number was significantly reduced by ammonia removal. This filter was dominated by Rhodotorula mucilaginosa. Also, the yeast genera Candida and Aureobadisium were detected (Baltrenas et al. 2015). Bacteria, micromycetes and yeast were capable of functioning on the biofilter containing pine biochar (Pf6) selected from the collection of the BRL and employing microorganisms to removing airborne volatiles. The selected micromycetes manage to survive in the filter containing biochar both at the high and low concentrations of pollutants. Aspergillus versicolor developed best. The bacterial species Bacillus subtilis was the most predominant thus accounting for 50% of all selected bacteria. The yeast Exophiala sp. also prevailed. A decrease in the removed ammonia concentrations at first and the removal of the low concentrations of other pollutants at the next stage did not secret the inserted yeast. Micromycetes, bacteria and yeast were discovered to develop on the packing material of the filter containing birch biochar (Bf6) by removing xylene. Fungal diversity was relatively rich, but the micromycetes of the genus Penicillium

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8 Natural and Inoculated Microorganisms as Important Component for Sustainability. . .

predominated. The fungal genus Chaetomium and the starter culture Aspergillus versicolor were secreted for the first time throughout the study. The yeast Aureobasidium sp. and the bacterial genera Bacillus (B. cereus, B. subtilis), Pseudomonas (P. fluorescens, P. putida, P. aeruginosa), Staphylococcus (S. aureus), Rhodococcus sp. and Micrococcus sp. predominated in this type of the biofilter. The content of bacteria and yeast secreted from the filter containing birch biochar (Bf6) was found to be similar (3.8  1010 cfu/g and 1.6  1010 cfu/g of d.w. respectively). The content of the microorganisms secreted from the filter filled with pine biochar varied—bacteria made the largest part—1.2  1011 cfu/g of d.w. The amount of other secreted microorganisms was lower. However, species diversity was wider in the filter containing birch rather than pine biochar.

Chapter 9

Technological Development from the Model to the Prototype: An Example of the Biofiltration System

The development of sustainable technologies from the laboratory to the pilot scale and the modelling in the case of biofiltration systems is presented in this chapter. A description of aerodynamic, physical and sorptive characteristics of the loads, their efficiency and microbiological characteristics in biological air treatment systems is given. The design of the developed biological air treatment filters of the plate and tubular types with the capillary load irrigation system and the conditions of their application are analysed.

9.1 9.1.1

Schemes for Operating Pilot Biofilter Structures The Operational Principles of the Biofilters with Straight and Wavy Lamellar Plates

Experimental studies are carried out using pilot biological air treatment equipment of three modifications. Figures 9.1 and 9.2 provide biofilter schemes for arranging the polymer straight and wavy lamellar plates of the biofilter in parallel. The biofilter consists of the systems for filtering the air, maintaining the humidity of the biopacking material and temperature in the filters, fans, air ducts for supplying and removing the air from the equipment and air flow adjustment valves. Figure 9.3 shows a scheme for the plate structure of the tubular biofilter (Baltrėnas et al. 2015a). The structures of the first two biofilters are identical and differ only in the shape of the plate (straight or wavy). The polluted air is supplied to the biofilters through contaminated air ducts (1) equipped with valves (9) taking control over air flow rates and supplied air discharge. The ducts are also provided with openings (2) for determining the investigated parameters. Subsequently, polluted air flows enter the casings having biofiltration systems. Through the perforated plates, air flows (8) are dispersed over the entire volume of the packing material (7). The polluted air moves © Springer Nature Switzerland AG 2020 P. Baltrėnas, E. Baltrėnaitė, Sustainable Environmental Protection Technologies, https://doi.org/10.1007/978-3-030-47725-7_9

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9 Technological Development from the Model to the Prototype: An Example of the. . .

Front view

Sampling / Setting parameters C-C applying the envelop principle Treated air Treated air 11 2 2 X2 Air flow rate Air flow rate and temperature and temperature sensor D2 D1 sensor 10 Fasteners 7 D5 Polluted

Connection panel between biofilter parts 1 Polluted Air 9 3

Air

12 X1

D4

5 4

2 Water supply valve

8 Water discharge opening

6

Water removal valve

D3

Air distribution duct

Fig. 9.1 Scheme for the air treatment biofilter with the capillary humidification system of the packing material when the biofiltration system is made of straight lamellar plates: 1—polluted air duct, 2—sampling point, 3—blower, 4—temperature sensor, 5—electric heating element equipped with a thermostat, 6—biofilter bearing structure, 7—biofilter plates containing the packing material, 8—perforated plate, 9—valve, 10—bearing structure of biofilter plates, 11—treated air duct

11 X2 Connection panel between biofilter parts 1 Polluted Air 9 3 12

2 Air flow rate and temperature sensor

Fasteners

2

Air flow rate and temperature sensor D1 10

D5 D4

5 4

D2

7 Polluted Air

X1 2 Water supply valve

Sampling / Setting parameters applying the envelop principle

Treated air

Treated air

D3

8

6 Water Water removal valve discharge opening

Air distribution duct

Fig. 9.2 Scheme for the air treatment biofilter with the capillary humidification system of the packing material when the biofiltration system is made of wavy lamellar plates: 1—polluted air duct, 2—sampling point, 3—blower, 4—temperature sensor, 5—electric heating element equipped with a thermostat, 6—biofilter bearing structure, 7—biofilter plates containing the packing material, 8—perforated plate, 9—valve, 10—bearing structure of biofilter plates, 11—treated air duct

9.1 Schemes for Operating Pilot Biofilter Structures

485

B Treated air 1

Polluted Air 17

6

16

A

15 220 V 14

B-B X2 2 3

X1 2 6 11

3 4

5 6 7 8 A 5 6 10

13

12

11

4 5 6 7 M4 8 D4 D3 M3

9

13 12 11

5 6 18 10 11

A-A 5

8

M1 D1 M2 D2 M5 D5

B

Fig. 9.3 Scheme for the tubular air treatment biofilter with the capillary humidification system of the packing material: 1—polluted air duct, 2—air flow rate, temperature and humidity sensor, 3— treated air duct, 4—biofilter lid, 5—sealing plate, 6—sealing plate fastener, 7—biofilter tube containing the biopacking material made of wood biochar and wood fibre, 8—biofilter casing, 9—tank for refilling the aqueous medium, 10—valve for refilling the aqueous medium, 11— biofilter bearing structure, 12—electric heating element of the aqueous medium, 13—air distribution system, 14—aqueous medium drain valve, 15—control panel, 16—blower and electric heating element, 17—polluted air duct valve, 18—water temperature monitored on the sensor screen of the aqueous medium temperature, X1—sampling inlet in the polluted air duct, X2—sampling inlet in the treated air duct, D1, D2, D3, D4, D5—points for measuring biofilter parameters, M1, M2, M3, M4, M5—points for sampling the packing material

between biofilter plates (7) soaked in the liquid medium and spaced 6 mm apart towards the ducts of the treated air the flow of which enters the treated air duct (11) and is discharged into the environment. Openings (2) are arranged in the ducts of the treated air for identifying the investigated parameters. Biofilters maintain the temperature of media, air flows and the humidity of the packing material. The temperatures of the media are under control of electric heating elements equipped with thermostats (5), and air flow temperatures are inspected applying duct heaters installed below the blowers of the supplied air (Baltrėnas et al. 2015a). The plates containing the packing material (7) are the main element of biofilters. The packing material consists of non-woven cork (NWC) mixed with heat-treated wood fibre. The polluted air flowing between the plates covered with the packing material is treated using microorganisms. The distances between the plates make up to 6 mm, and therefore the contact between the polluted air flowing between the plates (7) and the microorganisms contained in the material is good enough. The treated air is removed from the biofilter through outlet ducts (11). The optimum operating modes of blowers (3) and heating systems (4) and (5) are provided by the control unit (12). Experimental studies are also carried out applying a biofilter-adsorber—a pilot biological air treatment device (Fig. 9.3), in which the plates arranged in the biofilter are substituted for tubes forming the plate and containing the packing material (European Patent No. 3072576 by P. Baltrenas and E. Baltrenaite, 2019).

486

9.1.2

9 Technological Development from the Model to the Prototype: An Example of the. . .

The Operational Principle of the Tubular Biofilter

The polluted air is supplied through the polluted air duct (1) equipped with the valve (17). The polluted air duct is fitted with the blower (16) to take control over the air flow rate and pressure. The air passing through the blower is heated by the installed electric air heating element. The flow of the polluted air next enters the aqueous medium of the biofilter and flows towards the treated air duct (7) through the tubes filled with the packing material (7) where the polluted air is treated. The filtration system (7) consists of a number of vertically disposed tubes with waterproof walls packed with the packing material of filtration and built in between the upper and lower sealing plates (5) fixed in the casing of the biofilter (8) using fasteners (6). The pollutants are decomposed by microorganisms that need humidity for surviving, and the electric heating medium (12) of the aqueous medium is required for preheating the saline solution forming the aqueous medium to create a microorganism-survivalfriendly medium. Water temperature is monitored on the sensor display of the aqueous medium (18). Under the pressure created by the blower (16), the treated air flows upward towards the treated air duct (3). The reservoir of activated water is installed next to the filtration system (7) having the electric air heating element of activated water (12), an external refill tank of activated water (9) and an outlet valve of activated water (14). The distributor (13) of the polluted air supplied to the biofilter is installed in the tank of activated water heated to a temperature of 25
C applying the built-in electric water heating element (12). When the content of water decreases due to the natural evaporation processes of heated water, it is automatically replenished via the distribution valve (10). The perforated air distributor (13) comprises at least three branches the holes of which are arranged along the entire length of the distributor branches. The diameters of the holes increase steadily from the polluted air inlet to the disperser towards the distant end of the device in order to distribute water evenly over the entire crosssection of the biofilter. Water is used for humidifying the filtered packing material inside the tubes and consisting of biochar mixed with heat-treated wood fibre. For this purpose, the tubes are immersed in liquid at their height of 10 to 15% for producing capillary effect. The air flow exits the disperser (13), passes through the aqueous medium and enters the biofiltration system (7) consisting of a large number of tubes through the lower ends of the tubes (7) covered by a mesh (Baltrėnas et al. 2015b, Baltrėnas et al. 2016b, Baltrėnas et al. 2016c).

9.2

Applied Analytical Methods and Equipment

The presented research methodology has been developed with reference to the experience obtained by other scientists. The methodologies of the researchers, including Baltrėnas and Vaiškūnaitė (2002a), Baltrėnas and Zagorskis (2010a), Zigmontienė and Žarnauskas (2011), Aly-Hassan and Sorial (2011), Singh et al.

9.2 Applied Analytical Methods and Equipment

487

(2010), Jun and Wenfeng (2009), Chung et al. (2001), Duan et al. (2006) and Ramirez et al. (2008) have been reviewed. The analysis of the methodologies of the above-introduced authors indicated the location and number of measurement points, parameters to be measured, etc. and assisted in developing a new methodology of the plate-type biofilter equipped with the capillary humidification system of the packing material for conducting research. The effectiveness of removing acetone, xylene and ammonia from the air is found by measuring the concentration of the pollutant prior to (in the polluted air inlet duct) and following treatment (in the treated air outlet duct). The concentration of the pollutant in the air is determined applying the MiniRAE 2000 instrument that calculates VOC concentrations and provides a possibility of measuring ammonia vapour concentration in air flow (measurement accuracy—2000 ppm: 2 ppm or 10% of reading; >2000 ppm: 20% of reading). The operation of the device is based on the photoionization method referring to the ionization of neutral molecules or atoms. The process involves a certain portion of electromagnetic radiation energy absorbed by the material. The humidity of the packing material using straight and wavy lamellar plates of the biofilter may be determined by a weighing technique based on mass loss, in this case, a decrease in the content of humidity in the packing/material. However, due to technical feasibility, the application of this method for determining humidity is hardly possible in laboratory tests. Therefore, a simpler and more accurate technique for establishing the humidity content of the material was preferred, i.e. the content of humidity in the packing material is determined employing the Extech M0290 Moisture Meter shown in Fig. 4.3b (material humidity measurement ranges from 0 to 99.9% under an error of 0.1%). Odour units for all biofilter structures and different packing materials are determined using a dynamic olfactometer under laboratory conditions. The VAC’SCENT vacuum chamber (Fig. 4.3d) for air sampling is used for taking air samples to study odours. Odour concentrations upstream and downstream of treatment equipment are determined employing the AC’SCENT® International dynamic olfactometer that is an air mixing and dilution device for establishing the threshold values of odorous air samples. The dynamic olfactometer meets the requirements for EN 13725:2004 +AC: 2006—Air quality—Determining odour concentration using dynamic olfactometry methods (European Union). The tested odour quality is also assured with reference to the requirements for standard EN 13725:2004+AC: 2006. The olfactometer is warmed to the required temperature before the evaluation of the odour sample is performed. The tested sample is introduced into the dynamic olfactometer, and tests are carried out using the forced-choice analysis method. The evaluation session is conducted by 5 experts who meet the requirements for standard EN 13725:2004+AC: 2006. The assessment team of 5 members made 3-cycle measurements. Data on the first (pre) measurement cycle was always discarded thus providing information on the following two cycles. As for the forced-choice method, the members of the assessment team indicated the location of the aromatic irritant and pointed out whether they had specified the

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9 Technological Development from the Model to the Prototype: An Example of the. . .

location by predicting, implying or being assured. The sample volume required for analysis was 2.5 L. Five experts (sniffers) smelt a flow rate of 20 L/min for 3 s. Additional parameters are measured employing the multifunctional environmental meter METREL MI6201 (air temperature, pressure, humidity), and air flow humidity in the outlet duct is measured by a built-in sensor based on the operating principle of a dry and wet thermometer. Both thermometers measure temperature and, according to the indications of the dry and wet thermometer, air humidity is deducted thus displaying the obtained result on a digital medium. Ambient pressure is determined using the Testo 511 instrument. Air flow humidity, temperature and rate measurements are made applying the Testo 400 instrument, and biofilter pressure is found employing Testo 512 and Testo 400, (measurement range of air flow humidity varies from 0 to 100% under the accuracy of 0.1%, measurement range of air flow temperature fluctuates from v200 to +800
C under the accuracy of 0.1
C; air flow rate ranges from 0 to 60 m/s under the accuracy of 0.01 m/s; the pressure measuring range of Testo 512 varies from 0 to 2 hPa under the accuracy of 0.01 hPa). Testo 400 uses attachment 0638.1445 that gives pressure values in hectopascals. The measurement range of attachment 0638.1445 fluctuates from 0 to 100 hPa (error from 0 to 20 hPa  0.1 hPa, and from 20 to 100 hPa  0.5% from the calculated value). Pressure in the duct is measured according to the standardized method given in LAND-27-98/M-07. The temperature of the aqueous medium is determined applying an electronic sensor mounted in the biofilter while the pH of the aqueous medium and the packing material is specified using the Mettler Toledo’s meter (pH ranges from 2000 to +19,999 pH at an error of 0.001). pH is established according to the requirements for standard LST ISO 10523 ‘Water quality. Determining pH’. The standard defines the method for determining the pH value of rain, potable and mineral water, bathing water, surface water and groundwater as well as domestic and industrial wastewater and liquid sludge to find the pH value ranging from 2 to 12 at a temperature from 0
C to 50
C. The oxygen content dissolved in the aqueous medium is found out employing the Oxi 3205 instrument (Fig. 4.3i). Oxygen concentration in the biofilter is determined using the TESTO 350 XL instrument the operating principle of which is based on the electrochemical method. Electrochemical analysis methods cover processes on the surface of the electrodes of the electrochemical cell or in the interelectrode space. Different system parameters such as impedance and electrical conductivity, electrode potential, electrical length and the amount of electrical charge may vary during the process. The content of the total organic carbon in biochar and the packing material is determined by the total carbon analyser (TOC-V SHIMADZU) and the testing module SSM-5000A. The operating principle of the device is based on incinerating a dry sample at a temperature of 900
C and measuring the emitted content of carbon dioxide (CO2) by the infrared camera. Ash content in biochar is determined applying the following principle: the samples of biochar are dried at room temperature, weighed and incinerated to ash at 450
C for 2.5 h. Next, ash mass is established and ash content is calculated according to the formula. Chamber furnace SNOL

9.2 Applied Analytical Methods and Equipment

489

30/1100 is used for specifying the ash content of biochar. The furnace is equipped with the E5CK-T digital controller. The relative and absolute humidity of the packing material is found employing the weighted method based on weight loss, in this case, on a drop in humidity content in the packing/material. The porosity of the material is determined by the saturation method. First, the material is saturated and then weighed for calculating porosity according to the formulas in the end. Capillary humidification is clarified visually, i.e. the plate is immersed in water to observe the height of water rise in the material. Sorption parameters (pore diameter and volume, surface area) for the tested material are found out using mercury porometry, electronic scanning and optical microscopy. A study of the porous structure of the material was performed employing mercury porometer QUANTACHROME POREMASTER PM-33-12. The maximum developed pressure made 231 MPa. The measured diameter of pores ranged from 950 μm to 6.4 nm. Electron scanning microscopy was done applying field emission scanning electron microscope JEOL ISM—7600 F. The microscope magnified from 25 to 1,000,000 times. Electron accelerating voltage ranged from 0.1 to 30 kV. Image resolution reached 5120  3840 pixels (JSM-7600F. . . 2013). Optical microscopy was performed under stereo microscope MOTIC K-400 L equipped with Pixera VSC camcorder (K-400L. . . 2013). The microscope magnified  50. Prior to experimental experiments on laboratory biofilters, 4 substances out of 25 were selected and used as fillers (packing materials) in biofilters. Twenty five materials were involved in testing relative and absolute humidity, porosity, capillary humidification and microscopy. Four materials, including non-woven cork, wood fibre, linen fabric and wood biochar were selected from the performed study. Wood biochar assisted in establishing parameters (pore diameter, surface area and volume) for total organic carbon, heavy metals, ash content and sorption. Preceding the use of biochar, it must be activated as the packing material used for testing in the biofilteradsorber. Biochar was mixed with NaOH pellets at a ratio 4:1 (NaOH: biochar) and 10 mL of water and left to be stirred for 2 h. Next, it was dried at a temperature of 130
C for 4 h. The mixture was heated again at a temperature of 700
C for 1.5 h. The cooled mixture was washed applying 0.1 M HCl solution and hot deionized water up to pH reaching 6.5. At the washing stage, activated carbon is separated using the filters of 0.45 mm in diameter. The resulting carbon is dried for 24 h at a temperature of 110
C and stored in the closed containers for further analysis (Vargas et al. 2011). Having selected substances for the packing material of the biofilter, 3 gaseous pollutants, i.e. acetone, xylene and ammonia, were chosen to be supplied to the biofilter. Acetone, xylene and ammonia are among the largest amounts of pollutant emissions from stationary sources considering their emissions into the ambient air compared to the content of other VOCs (Statistikos departamentas 2014). Experimental studies were carried out using natural and selected microorganisms. Eight strains of micromycetes (Aureobasidium pullulans BF-58, Penicillium sp.

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9 Technological Development from the Model to the Prototype: An Example of the. . .

BF-2, Acremonium strictum 1–40-L, Gliocladium viride BF-81, Aspergillus versicolor BF-4, Cladosporium herbarum 7KA, Cladosporium sp. L-7 pp., Stachybotrys sp. BF-90), 2 yeast strains (Aureobasidium pullulans BIA1.1.2 and Exophiala sp.) and 2 bacterial strains (Bacillus subtilis 28 and Rhodococcus sp. 30) were selected and inoculated onto the packing material (liquid with the selected microorganisms was sprayed onto the packing material). The selected microorganisms were applied in both laboratory and pilot biofilters. Prior to the experimental stage of a study of pilot biofilters (the first is a biofilter with straight lamellar plates, the second includes wavy lamellar plates and the third is tubular biofilter), the selected microorganisms are inserted into the packing material inside the biofilters. Having inserted the microorganisms, for 3 weeks, tests are carried out supplying air flow to the biofilters at a rate of 30 m3/h. The porous plates forming the cartridge of the biofilter were immersed in the solution saturated with biogenic elements. The tested solution consisted of 1 g of K2HPO4, 0.5 g of KCl, 0.5 g of MgSO47H2O, 0.1 g of FeSO47H2O and 0.9 g of NaNO3 and1000 mL of distilled water (Baltrėnas and Zagorskis 2009a; TrejoAguilar et al. 2005; Liao et al. 2008; Chang and Lu 2003a; Wright 2005; Dorado et al. 2008). The immersion depth of the porous plates reached 50 mm. The total height of the plate was 200 mm. The porous structure of the plates and the size of the adjacent plates (2–5 mm) leads to the capillary humidification effect of the packing material, which causes a spontaneous rise of the solution (medium) to the surface and humidifies the packing material. Thus, this self-humidification system does not use extra energy, and the packing material is properly humidified in the cases of interrupting the technological process, technical maintenance and repairs or other electrical faults and outages. External parameters for the biofilter environment, i.e. ambient pressure, temperature and relative humidity, are determined on each day of experimental studies. All three parameters are measured three times over time and the obtained results are averaged. A study of different types of the packing material demonstrated that the material was activated from the beginning to the tenth day of the experiment supplying the biofilter with acetone vapour-polluted air. The initial pollutant concentration reached 20–25 mg/m3. The device was supplied with acetone vapour four times daily for 15 min. As for other days, acetone concentration increased by 20–25 mg/m3 thus extending acetone vapour delivery time to 1 h. Following activation, the concentrations of pollutants were supplied to the biofilter throughout the day of the experiment. Acetone vapour was periodically supplied to the biofilter at a concentration of approximately 300 mg/m3 for 3 days. Subsequently, acetone vapour at the concentrations of 500 mg/m3 and 700 mg/m3 was supplied to the biofilter for the next 3 days. At the end of this stage, the vapour of the second pollutant xylene was supplied to the biofilter thus making 300 mg/m3 for the next 3 days. Subsequently, xylene vapour at the concentrations of 500 mg/m3 and 700 mg/m3 was supplied to the biofilter for the following 3 days. The third pollutant ammonia was present in the biofilter at similar stages and concentrations like other pollutants: vapour at the

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491

concentrations of 300 mg/m3, 500 mg/m3 and 700 mg/m3 was supplied for 3 days in each case. Similar tests were conducted supplying vapour at the concentrations of 100, 50, 20, 10 mg/m3 in the reverse order of pollutants for 3 days in each case. The required pollutant concentrations are achieved by diluting the liquid phase contaminant with distilled water and monitoring and taking control over the concentration of pollutant vapour in the biofilter during the study. Also, investigation in the dependence of air treatment effectiveness of the biofilter on the air flow rate was carried out. Airflow rate was reduced from 0.12 m/s to 0.08 m/s in the air inlet duct. As for pilot biofilters, acetone vapour at a concentration of 300  25 mg/m3 and under the air flow discharge of 30  1.5 m3/h is supplied to the biofilter during the first week of the study. Under the removed air temperature of 28  1
C, xylene vapour was supplied during the second and ammonia vapour—during the third week. The concentration of the supplied pollutants reached 300  20 mg/m3. In three-week time, the efficiency of the biofilter increased to 100  5 m3/h and in six-week time experimental studies included the supply of acetone vapour to the biofilters maintaining the removed air temperatures of 24  1
C, 28  1
C and 32  1
C (for 2 weeks, acetone vapour-polluted air was supplied, and the maintained temperature of the removed air was 24  1
C; for the next 2 weeks acetone vapour-polluted air was supplied, and the maintained temperature of the removed air was 28  1
C; for the rest of time, acetone vapour-polluted air was supplied, and the maintained temperature of the removed air was 32  1
C). The same principle applies to the other two pollutants xylene and ammonia. Pollutant vapour is supplied to the device four times for 1 h each day of the experiment. The target of biofilter air treatment effectiveness was preferred to be at least 90% and pollutant concentration in the supplied air had not to exceed 300  25 mg/m3. Such pollutant concentration was selected based on the obtained results of experimental studies that involved the layouts of laboratory biofilters. Thus, the allowed daily concentration of the pollutant (acetone, xylene and ammonia) made 300  25 mg/m3 monitoring air treatment effectiveness of pilot biofilters. In the case of effectiveness that is less than 90%, pollutant concentration is reduced to find the limit value. The required pollutant concentrations are achieved by diluting the liquid phase contaminant with distilled water and monitoring and taking control over the concentration of pollutant vapour in the biofilter during the study. Pollutant concentration was measured upstream and downstream of the treatment device and at five points following the packing material. Measurement points are given in Figs. 9.1, 9.2 and 9.3. (measurement points X1, X2, D1, D2, D3, D4 and D5). At a single point, pollutant concentration was measured over a period of 3 to 5 min, and instrument MiniRAE 2000 gave the average and maximum values over the estimated period. Also, the humidity of the packing material was determined at five points every day of the experiment applying the envelope principle (see Figs. 9.1, 9.2 and 9.3). Air flow rate and temperature were also measured upstream and downstream of the treatment device at five points next to the packing material. The composite sample of the packing material was also tested twice a week thus determining the spread of microorganisms on packing materials. The composite

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9 Technological Development from the Model to the Prototype: An Example of the. . .

sample for testing microorganisms was taken at five points with reference to the envelope principle (see Figs. 9.1, 9.2 and 9.3). Also, at the beginning and end of the study, the content of total organic carbon present in the packing material was analysed. The total organic carbon analyser (TOC-V series analyser SHIMADZU) and testing module SSM—5000A were used for receiving the results of this parameter. A total sample was obtained taking 5 g of the packing material from each of the five measurement points (D1, D2, D3, D4, D5) inside the biofilter. The sample is subsequently crushed to a suitable size for analysis and total carbon is measured having made three separate samples. Then, a standard deviation and the coefficient of variation are derived. The obtained results are compared drawing conclusions. From the beginning to the end of the study, sorption parameters for the packing material (pore diameter, volume and surface area) were tested four times. The first sample was taken on the first day of testing, the second—on the first day after the test of acetone removal was completed, the third sample followed the first day after the xylene removal period and the fourth—on the last day of testing ammonia removal. Each sample represented research on sorption parameters for the packing material and was taken from the place where the sample of any other species was taken for the last time. The humidity of the packing material was set at 9 points applying the M0290 instrument every day of the experiment. One point was measured three times and the average was derived. When the humidity of the packing material was measured, air flow rate, pressure, temperature and humidity and oxygen content were estimated. To assess whether air flow was evenly distributed between the plates of the biofilter, air flow measurements were made at 36 points, i.e. 12 measurements in each section (sections A, B and C; see Figs. 9.1, 9.2 and 9.3). Also, air flow rate was measured at 24 points in the air inlet and outlet ducts. One point was measured three times and the average was derived. Air flow temperature, pressure, oxygen content and humidity measurements were also made at 36 points (see Figs. 9.1, 9.2, 9.3; for instance, tested points A1H1, A1H2, A1H3, A2H1, A2H2, A2H3, etc.) between biofilter plates and 24 points in the air inlet and outlet ducts (see Figs. 9.1, 9.2 and 9.3; tested points X1 and X2). Each air flow parameter was measured at the tested point for 3 to 5 min, and then the instrument provided an average value recorded in the research register. The analysis of the aqueous media follows research on air flow parameters. The content of dissolved oxygen, temperature and pH are determined in the aqueous medium. These three parameters are established at four locations of the biofilter (see Figs. 9.1, 9.2 and 9.3; tested points TpH1, TpH2, TpH3, TpH4). The points were measured three times and the average was derived. Each air flow parameter was measured at the tested point for 3 to 5 min, and then the instrument provided an average value recorded in the research register.

9.2 Applied Analytical Methods and Equipment

9.2.1

493

Air Flow Permeability in the Biofiltration System

Air flow permeability in the biofiltration system is calculated according to the formula PR ¼

vX1 , vX2

ð9:1Þ

where PR—air flow permeability in the biofiltration system; vX1—air flow rate at measurement point X1, (m/s), vX2—air flow rate at measurement point X2, (m/s) (Figs. 9.1, 9.2 and 9.3). The graphical representation of the received experimental research data on air flow permeability in the biofiltration system provides that a standard deviation and the coefficient of variation are calculated and reported at each average value of the obtained result.

9.2.2

Aerodynamic Resistance of the Biofiltration System

Aerodynamic resistance was determined considering differences in pressure received from the values of pressure measured in the air flow inlet and outlet ducts of the biofilter, points X1 and X2, respectively. The Testo 512 instrument was employed for measuring air pressure between the plates. The measurement range of the Testo 512 instrument varied from 0 to 2 hPa with an accuracy of 0.01 hPa and error of 0.5%. Pressure at points X1 and X2 was calculated applying the Testo 400 instrument and using attachment Testo 0638.1445 providing the values in hectopascals. The measurement range of attachment 0638.1445 fluctuated from 0 to 100 hPa (error from 0 to 20 hPa  0.1 hPa, and from 20 to 100 hPa  0.5% from the calculated value). The aerodynamic resistance of the biofiltration system is calculated according to the formula K ¼ P0X1  P0X2

ð9:2Þ

where K—the aerodynamic resistance of the biofiltration system, (Pa); P0X1—air flow pressure at measurement point X1, (Pa); P0X2—air flow pressure at measurement point X2, (Pa). The graphical representation of the received experimental research data on the aerodynamic resistance of the biofiltration system provides that a standard deviation and the coefficient of variation were calculated and reported at each average value of the obtained result.

494

9.3

9 Technological Development from the Model to the Prototype: An Example of the. . .

Aerodynamic Parameters for the Packing Materials of Pilot Biofilters

Experimental studies were performed applying three different types of pilot biofilters (inner structure made of straight lamellar plates, inner structure made of wavy lamellar plates and tubular structure shifted at an angle of 45
). The carried out research referred to methodologies for pilot biofilters. The study analysed the aerodynamic properties (pressure, velocity, aerodynamic resistance) of the three structures and air treatment effectiveness of the biofilter. In addition, to more accurately evaluate the optimal conditions and effective operation of the functioning biofilters, other parameters, i.e. the humidity of the packing material, air flow humidity, air flow temperature, oxygen content in the air, the pH of the aqueous medium, temperature and dissolved oxygen content in the aqueous medium, the content of total organic carbon in the packing material were observed. Also, the porous structure and the packing materials (non-woven cork, wood fibre and biochar) of the biofilter were investigated. The study was conducted prior to testing biofilters, i.e. at the beginning of experimental studies when the selected microorganisms were had not been inserted into the packing material and following each stage of testing the pollutant. Microscopy data are shown below. Experimental studies demonstrated that three different types of pollutants (acetone, xylene and ammonia) were supplied to pilot biofilters and the concentration of each pollutant in the air flow reached 300  25 mg/m3. The efficiency of all three pilot biofilters made 100m3/h. Air flow temperature of the biofilter varied from 24
C to 28
C and to 32
C. The research under each of the temperatures was performed for 10 days. The developed pilot biofilters are innovative in their internal structure. The focus of the design is shifted on the formation of capillary effect that positively affects the humidity of the packing material. Under capillary effect, the aqueous medium rises through the pores of the material due to small space between the plates thus humidifying the packing material without additional energy.

9.3.1

The Porous Structures of Biochar Samples Obtained by Testing a Tubular Pilot Biofilter Supplied with Different Types of Pollutants

For testing the tubular biofilter, the packing material containing birch biochar Bf6 and birch fibre at a ratio 10:1 was used. The dimensions of the pre-study samples of biochar were 10  6  3 mm. The temperature was 24, 28 and 32
C during the study, the concentration of acetone, xylene and ammonia made 300 mg/m3 and air flow discharge was 100 m3/h. The pictures of biochar samples were taken applying scanning electron microscopy before and after testing the biofilter. Two types of

9.3 Aerodynamic Parameters for the Packing Materials of Pilot Biofilters

495

Fig. 9.4 Sample Bf6 before testing: (a)—magnified 100, (b)—magnified 1000

Fig. 9.5 Data on the elemental analysis of the porous walls of sample Bf6

granules, including a metallic-black shiny surface and a matt black surface, were observed in the selected samples. Two types of pores embracing those of large (40–45) μm and small (5–8) μm diameter (Fig. 9.4a and b) were monitored in the cross-section of the birch biochar sample. Small amounts of wood fibre observed on the surface of the tested biochar were found. (Fig. 9.4). The transverse section also shows membranes continuously covering the cross-section of small-diameter pores (Fig. 9.4b). Data on the analysed elemental composition of biochar surfaces were obtained using an electronic microscope—energy-dispersive X-ray spectrometer Inca Energy 350 (Figs. 9.5 and 9.6). Only elements C and O were found in the porous walls of birch biochar. Since this method did not detect H, it can be stated that the employed

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9 Technological Development from the Model to the Prototype: An Example of the. . .

Fig. 9.6 Acetone-treated sample Bf6: (a)—magnified 100, (b)—magnified 3000

birch biochar consisted of elemental carbon and the remaining relatively significant amount of transitional organic compounds. Birch biochar (without estimating H content) consisted of 84.68% of C and 15.32% of O. The membranes completely covering small pores of biochar were observed for the first time, and therefore elemental analysis was performed to determine their nature. The obtained data are shown in Fig. 9.4. These membranes should be assigned to the wood structure. Their elemental composition differed little from that of porous walls, but the content of C was higher (87.39%) and the content of O was lower (12.61%). Although these elements were extremely low in thickness, the full conversion of organic wood compounds to C was not achieved. The images of the surface structure of the biochar samples treated with acetone in the tubular biofilter are presented in Fig. 9.6a and b. No birch fibre on the surface and membranes covering the cross-section of pores was observed in these samples. The diameter of the large pores observed in the sample is equal to 50–—60 μm and that of the small ones—6–7 μm. New elongatedform formations of 0.5–1 μm were observed on the side surfaces of pores (Fig. 9.6b). They were not present in the sample before treatment. The porous-structure images of biochar samples treated in the tubular biofilter with xylene and ammonia are presented in Fig. 9.7. The provided photos show damages to the surface layer of biochar. The monitored broken tracheids are observed, the surface is uneven and many small fragments of 10–50 μm in length are identified. Data obtained on the studied porous structure of birch biochar Bf samples have been obtained by the Mercury porometry method and are presented in Table 9.1. The obtained data show significant differences in the porous structure of the analysed samples, which is possibly the result of difficulties in selecting an average sample from the tested ones. As noted above, the selected Bf6 samples differed in colour as well as apparently in structure. However, the porosity of the untreated sample (62.89%) and particularly the porous surface area (6.15 m2/g) are significantly lower than those of the treated samples. The specific pore volume is also

9.3 Aerodynamic Parameters for the Packing Materials of Pilot Biofilters

497

Fig. 9.7 Treated sample Bf6: (a)—magnified 500 (xylene), (b)—magnified 1000 (ammonia) Table 9.1 Data on the studied porous structure of birch biochar samples No 11. 22. 33. 44.

Sample Bf 6 Bf 6 (Acetone) Bf 6 (Xylene) Bf 6 (Ammonia)

Porosity, % 62.89 79.70 73.29 75.95

2

Surface area of pores, m /g 6.15 13.49 20.39 12.84

Specific pore volume, cm3/ g 1.08 1.91 1.71 1.91

smaller. The effect of xylene, which mainly increases the surface area of biochar pores, is to be considered exceptional. This can be explained by the effect of xylene on residual organic compounds dissolving them and forming an additional micropore structure. Additional information on pore volume distribution in differentially treated tubular biofilter samples is given in Figs. 9.8, 9.9, 9.10 and 9.11. The pore volume of all biochar samples was distributed according to the diameter in three areas, including maximum values, in the following way: • • • •

Untreated Bf6: 1–35 μm; 2- 6 μm; 3–0.8 μm. Acetone-treated Bf6: 1–25 μm; 2- 6 μm; 3–1.5 μm. Xylene-treated Bf6: 1–20 μm; 2- 6 μm; 3–1.5 μm. Ammonia-treated Bf6: 1–20 μm; 2- 7 μm; 3–1.5 μm.

Since biochar treatment should not affect the largest diameter pores (their distribution varies), it can be stated that the samples selected for testing were not similar. However, the pore volume of the xylene-treated samples smaller than 0.1 μm is significantly larger and should be attributed to the effect of xylene (Baltrėnas et al. 2015a, 2016a).

498

9 Technological Development from the Model to the Prototype: An Example of the. . .

Fig. 9.8 Variations in the pore volume of untreated sample Bf depending on pore diameter

Fig. 9.9 Variations in the pore volume of acetone-treated sample Bf depending on pore diameter

9.3.2

Microscopic Structures of Non-woven Cork (NWC) Samples Obtained when Testing Pilot Biofilters with Straight and Wavy Lamellar Plates Supplied with Different Types of Pollutants

NWC samples were selected before use from biofilters after testing for acetone, xylene and ammonia. A study of experimental biofilters with straight and wavy lamellar plates was performed under the air flow temperature of 24
C, 28
C and

9.3 Aerodynamic Parameters for the Packing Materials of Pilot Biofilters

499

Fig. 9.10 Variations in the pore volume of xylene-treated sample Bf depending on pore diameter

Fig. 9.11 Variations in the pore volume of ammonia-treated sample Bf depending on pore diameter

32
C, the pollutant concentration of 300 mg/m3 and the air flow discharge of 100 m3/h. Two-sided surface pictures of NWC were magnified x25 employing the Motic optical microscope and are shown in Figs. 9.12 and 9.13. NWC consisted of the woven base made of the flat filaments of 1 mm wide and the fibre of a smaller diameter attached to this base. Less fibre was observed on one of NWC sides, and therefore it was called the base in the photographs. The other side was named fibre.

500

9 Technological Development from the Model to the Prototype: An Example of the. . .

Fig. 9.12 NWC basis: (a)—magnified 25, untreated; (b)—magnified 25, acetone-treated biofilter surface made of wavy lamellar plates

Fig. 9.13 NWC-fibre basis: (a)—xylene-treated biofilter surface made of wavy lamellar plates, magnified 25; (b)—xylene-treated biofilter surface made of straight lamellar plates, magnified 25; (c)—ammonia-treated biofilter surface made of wavy lamellar plates, magnified 25, (d)— ammonia-treated biofilter surface made of straight lamellar plates, magnified 25

No extraneous matter was observed in the untreated non-woven samples (Fig. 9.12a). After treatment with acetone, small amounts of the brown dispersive material were observed in the samples on the both sides of the material, including the straight and wavy surface of the biofilter (Fig. 9.12b). Longer operation time had no effect on the structure of the NWC material that was found to remain unchanged. However, an increase in processing time accumulated new brown-colour derivatives better observed on the side of the base covered with non-woven material (Fig. 9.13). The new derivatives were found on the NWC of the biofilter with both straight and wavy lamellar plates. Parameters for the aqueous material included pH, temperature and the content of dissolved oxygen and are given in Table 9.2. The required pH of the biogenic element-saturated solution (bio-medium) was maintained employing buffer solutions (Baltrėnas and Zagorskis 2010b). pH and temperature were recorded daily. The porous plates forming the cartridge of the biofilter were immersed in the solution (medium) saturated with biogenic elements. The composition of the tested solution is given in Table 9.3. The initial pH of the medium ranged from 7.4 to 8.3 (Table 4.27) and was subject to the chemicals present in the medium. In the course of the experiment, the pH of the medium continued to increase to the maximum value of 9.0, which was 1.1 times higher than the recommended upper limit of 8.0. However, this is not a large deviation from the optimum value. Optimal pH is maintained for the efficient and stable operation of microorganisms. Thus, considering this condition, a slight pH deviation from the optimal value did not interfere with the efficient activity of microorganisms (yeast, micromycetes and

9.3 Aerodynamic Parameters for the Packing Materials of Pilot Biofilters

501

Table 9.2 Operating parameters for water consumption (within a period of 105 days), n—number of the days of experimental studies Inner structure of the biofilter Straight lamellar plates

Wavy lamellar plates

Tubular structure

Parameter pH Dissolved content of oxygen in the aqueous medium, mg/L Temperature,
C pH Dissolved content of oxygen in the aqueous medium, mg/L Temperature,
C pH Dissolved content of oxygen in the aqueous medium, mg/L Temperature,
C

Table 9.3 The composition of the aqueous solution

Material K2HPO4 KCl MgSO47H2O FeSO47H2O NaNO3 Distilled water

Interval of values (n ¼ 105) 8.3–8.9 0.27–1.65

Average value  error (n ¼ 105) 8.6  0.10 0.96  0.13

23.0–35.0 8.1–9.0 0.29–1.64

29.0  1.0 8.55  0.23 0.96  0.04

23.0–35.0 7.4–8.7 0.20-3.63

29.0  1.0 8.1  0.10 1.91  0.04

24.0–37.0

30.5  1.0

Content 1g 0.5 g 0.5 g 0.1 g 0.90 g 1000 g

bacteria) decomposing acetone, xylene and ammonia vapour supplied to the layouts of the biofilter. Throughout the experiment, the temperature of the aqueous medium ranged from 23
C to 35
C and varied to be adjusted to take control over air flow temperature in the biofilter. Oxygen dissolved in the aqueous medium ranged from 0.2 to 3.63 mg/L, with an average oxygen content of around 1.0 mg/L indicating that the activity of microorganisms had not been disturbed. If the oxygen level falls below 0.2 mg/L and persists for a longer period of time, then microorganisms run out of oxygen and start dying thus decreasing biofilter air treatment effectiveness. By monitoring the humidity of the packing material and air flow in the biofilter, the recommended optimum humidity was maintained. Air flow humidity between biofilter plates was 99.9% for all layouts of the biofilter, and that in the air flow outlet ranged between 77% and 99%. The humidity of the packing material reached 64.2% in the biofilter with straight lamellar plates, 65.5%—in the biofilter with wavy lamellar plates and 56.3%—in the tubular biofilter. Air flow humidity in the biofilter depends on the temperature of the supplied air flow and the temperature of the aqueous medium. The latter has a greater effect on the humidity of air flow and the packing material of the biofilter because the higher it is, the more water evaporates and the air becomes more saturated with water vapour, which increases air humidity

9 Technological Development from the Model to the Prototype: An Example of the. . .

Fig. 9.14 The content of carbon (%) in the packing materials before and after experimental studies removing acetone, xylene and ammonia under air flow temperatures of 24
C, 28
C and 32
C

Before experimental studies After experimental studies Content of carbon in the packing material, %

502

100 88.6 90 92.7 80 68.9 70 60 50 40 28.9 30 20 Biochar and wood NWC + WF, fibre, tubular straight lamellar structure structure

68.9 38.7

NWC + WF, wavy lamellar structure Packing material and biofilter structure

and positively affects the working environment of microorganisms that absorb volatile organic compounds through water and vapour. The analysis of the content of total organic carbon in the packing materials prior to the test and after experimental studies showed that the content of carbon in the packing material made of biochar and wood fibre decreased by around 4.1 (Fig. 9.14), in the packing material made of non-woven cork and wood fibre using the biofilter with straight lamellar plates—by 40% and in the biofilter with wavy lamellar plates and the packing material made of non-woven cork and wood fibre— by 30.2%. A decrease in the content of carbon in the packing material indicates that microorganisms used carbon as a food source present in the packing material for supporting their vital functions and performing the function of decomposition. The content of oxygen in the air reached 21% in the inlet and outlet ducts and between the plates throughout the experimental period, which indicates that aerobes, e.g. microorganisms growing in the atmospheric oxygen environment, were fully supplied with oxygen. Thus, optimal working conditions for microorganisms were ensured. Air flow temperature in the inlet and outlet ducts and between the plates was recorded each day of the experiment. During experimental studies, the controlled air flow temperature of the biofilter was from 24
C to 32
C. Control over air flow temperature included monitoring the dependence of air temperature and air treatment degree on volatile organic and inorganic compounds. The air flow temperature of 24
C between the plates was maintained for 10 days of the experiment thus following by 28
C for 10 days and 32
C for the next 10 days. The procedure embraced each pollutant (acetone, xylene, ammonia). The temperature of the removed air flow was slightly different from air temperature in the biofilter between the plates. However, a higher supplied air flow temperature was maintained in the air inlet duct to sustain a stable air temperature in the biofilter as the supplied air flow passed through a 25 cm water layer and cooled down. Taiwanese scientists Chang and Lu (2003b) researched biofilter treatment effectiveness and recommended achieving higher treatment efficiency under biofilter air humidity varying from 85% and 95% and biofilter air temperature ranging between 25
C and 35
C.

9.3 Aerodynamic Parameters for the Packing Materials of Pilot Biofilters

503

The above-introduced necessary conditions were met during experimental studies. Khan and Ghoshal (2000) also agree that air temperature in the biofilter should be up to 40
C for the effective biofiltration process. An increase or a decrease in the temperature of the removed air can be influenced by the temperature of the supplied air flow and by the fact that microorganisms release heat when decomposing pollutants (Baltrėnas et al. 2014b, 2015a, 2016a).

9.3.3

Aerodynamic Resistance and Air Pressure in the Inlet and Outlet Ducts of Pilot Biofilters

X2 D X1 50 450 3 3 100 m /h 100 m3/h 100 m /h 400 40 350 300 30 Xylene Acetone Ammonia 250 200 20 150 100 24oC 28oC 32oC 24oC 28oC 32oC 24oC 28oC 32oC 10 50 0 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 100 Experiment time, d

Air pressure in the outlet duct (X2), Pa and between the plates (D), Pa

Air pressure in the inlet duct (X1), Pa

Figure 9.15 shows the conducted experimental air pressure research on the pilot biofilter with straight lamellar plates when air pressure ranged from 350 to 400 Pa in the air inlet duct and from 14 to 20 Pa in the outlet duct during the experimental period. Considering data obtained by examining pressure between straight polymeric plates with a gap of 6  0.2 mm between the plates and measuring pressure at five points, pressure distribution was uniform throughout the area of the packing material and pressure averaged around 5.3 Pa at each point (D1, D2, D3, D4 and D5) (Figs. 9.1, 9.2 and 9.3). Figure 9.16 shows air pressure at measurement points X1, X2 and D. A comparison of the resultant pressure in the biofilter with wavy lamellar plates to that with straight lamellar plates demonstrated that higher pressure was observed in the biofilter with wavy lamellar plates because the latter structure made more difficult for air to flow. Air flow hits against the wavy part of the polymer plate thereby compressing the air and providing greater pressure. Air pressure in the inlet duct X1 ranged from 380 to 480 Pa. Pressure in the outlet duct varied from 25 to 30 Pa and that in the gaps between wavy lamellar plates averaged 7.3 Pa.

Fig. 9.15 Air pressure in the inlet duct, outlet duct and the gaps between the plates of the pilot biofilter with straight lamellar plates

Air pressure in the inlet duct (X1), Pa

3

X2

D

X1

600

50

100 m3/h

100 m3/h

100 m /h 500

40

400

30

300 Acetone 200

o

24 C 100 0

o

28 C

Xylene o

32 C

o

o

Ammonia o

o

o

20 o

24 C 28 C 32 C 24 C 28 C 32 C 10

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 100 Experiment time, d

0

Air pressure in the outlet duct (X2), Pa and between the plates (D), Pa

9 Technological Development from the Model to the Prototype: An Example of the. . .

504

600

X2

D

X1 100 m3/h

100 m3/h

100 m3/h

Acetone

Xylene

Ammonia

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500 400

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300 200 24oC 28oC 100 0

40

5

20 32oC

24oC

28oC

32oC

24oC

28oC 32oC

10 15 20 25 30 35 40 45 50 55 60 65 70 75 Experiment time, d

10 0

Air pressure in the outlet duct (X2), Pa and between the plates (D), Pa

Air pressure in the inlet duct (X1), Pa

Fig. 9.16 Air pressure in the inlet duct, outlet duct and the gaps between the plates of the pilot biofilter with wavy lamellar plates

Fig. 9.17 Air pressure in the inlet duct, outlet duct and the gaps between the plates of the pilot tubular biofilter with wavy lamellar plates

Air pressure in the tubular biofilter approximately averaged 470 Pa in the air inlet duct, 28 Pa—in the air outlet duct and 8.2 Pa—in the tubes (Fig. 9.17). Measuring air pressure in each type of the biofilter assisted in determining the total aerodynamic resistance of each device. Figure 9.18 shows that the lowest aerodynamic resistance was established in the biofilter with straight lamellar plates and averaged 346  5.0 Pa. Similar aerodynamic resistance was found for the biofilter with wavy lamellar plates and tubular biofilter that reached 438  4.7 Pa and 440  7.5 Pa, respectively. Investigated a droplet biofilter and uncovered that aerodynamic resistance ranged between 150 and 500 Pa.

100 m3/h

600

V

B

T

700

505

600

100 m3/h

100 m3/h

500

500

400

400

300

300 200 100 0

Acetone o

24 C

o

Xylene o

o

o

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o

o

200 o

28 C 32 C 24 C 28 C 32 C 24 C 28 C 32 C 100

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 100 Experiment time, d

0

Aerodynamic resistance (V), Pa

Aerodynamic resistance (T, B), Pa

9.4 Microbiological Properties of the Packing Materials of Pilot Biofilters

Fig. 9.18 Aerodynamic resistance on all three pilot biofilters: T—biofilter with straight lamellar plates, B—biofilter with wavy lamellar plates, V—tubular biofilter

9.4

Microbiological Properties of the Packing Materials of Pilot Biofilters

The conducted experimental studies allowed gaining new knowledge about the dependence of microorganism activity on the temperature maintained by pilot biofilters equipped with the humidification system. The study also evaluated microbiological and physical-chemical processes (adsorption and pollutant absorption). Based on the results of the carried out research, the structure of the device indicating the highest (at least 108 cfu/g) activity of microorganisms was determined (Baltrėnas et al. 2015b).

9.4.1

Activity of the Selected Microorganisms Considering Temperature and Other Physical-Chemical Parameters in Pilot Biofilters with Straight and Wavy Lamellar Plates

Testing for the spread of microorganisms in the packing materials of the biofilter covers the following stages: • • • • •

Taking samples of the packing material. Preparing and inoculating suspensions on nutrient media. Producing and accounting microorganisms. Excretion of pure culture. Inoculation on diagnostic media and identification.

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9 Technological Development from the Model to the Prototype: An Example of the. . .

Taking the samples of the biofilter packing material. The samples of the packing material of the biofilter were taken two times a week under the operating mode. Nonwoven cork present in the layout of the plate structure was cut using scissors and tweezers. The taken sample was placed in a sterile container (buxes). Prior to taking the next sample, scissors, tweezers and other tools were sterilized in the flame or wiped with a disinfectant (70
ethyl alcohol) using cotton wool. The samples were transported in such a way as to minimize the alteration of humidity content in the substrate and were analysed immediately or, in the case it was required, stored in the dark refrigerator at a temperature of 4
C for a maximum of 1 week. Preparing and inoculating microorganism suspensions on nutrient media. The flushing (suspension dilution) method was used for secreting living microorganisms from the packing materials of the biofilter and calculating their content. The method refers to inoculating a specifically diluted suspension onto solid media and counting the grown colonies. The method allows characterizing the effect of different substrate types and environmental conditions on the composition of fungal, yeast and bacterial species. 1 g of the sample taken is weighed, placed in the flask of 90 mL saline solution (0.9% NaCl) and shaken for 10 min at 400 rpm. The first dilution corresponds to 1:100 or dilution at 102. The resulting suspension is diluted by transferring 1 mL of the liquid into a tube containing 9 mL of saline solution. This produces several dilutions at 1:1000, 1:10000 and 1:100000 (up to 107). The required dilution (1 mL) is inoculated into Petri dishes and made up in the dissolved agar medium. Preferably, a dilution suspension resulting in 50–200 colonies per plate is inoculated. The tube is shaken prior to inoculation. 1 mL of the selected dilution of the suspension is added to a Petri dish thus pouring onto the dissolved agar medium cooled to 40
C depending on the microorganisms to be bred. The inoculation process takes three times. While the medium is stationary, the dish is tilted to mix with the suspension and spread evenly on the bottom of the dish. The bacterial suspension is inoculated on the stagnant medium. 0.1 mL of the suspension is added and dispersed. For secreting microorganisms, the rigid media obtained adding 2% of agar are used. The media are selected according to the microorganisms to be secreted: • Nutrient agar (Liofilchem, Italy), Cetrimide agar, Bacillus cereus agar base (Liofilchem, Italy) for secreting bacteria. • Malt extract agar, potato dextrose agar (Fluka, Spain) and Czapek dox agar (Liofilchem, Italy) for secreting micromycetes. • Malt extract agar and Sabur agar (Liofilchem, Italy) for secreting yeast. The media for fungi and yeast development are either acidified to the pH of 3.8–5 or chloramphenicol (1 g/L) is added to inhibit bacterial growth. Sterile acid solutions (citric, hydrochloric, sulfuric, phosphoric acids) are added to the medium after sterilization. For secreting some species of fungi, a growth inhibitor of other microorganisms, especially bacteria, i.e. rose bengal, is used. Potassium tellurite, sodium propionate and other substances inhibiting micromycete growth are applied.

9.4 Microbiological Properties of the Packing Materials of Pilot Biofilters

507

Producing and accounting microorganisms. Upside down plates are placed in the thermostat to prevent from dripping condensation onto the surface of the medium. Growth time and temperature are subject to the secreted microorganisms: • Dishes for secreting bacteria are incubated at a temperature of 30
C for 2–3 days. • Dishes for secreting micromycetes are incubated at a temperature of 26–28
C for 5–7 days. • Dishes for secreting yeast are incubated at a temperature of 25–28
C for 2–4 days. For counting colonies, the selected dishes represent the level of dilution in which colonies are separated from each other. The dishes containing from 20 to 60 colonies of fungi or from 50 to 200 colonies of other microorganisms are considered the most appropriate. The colonies of microorganisms are counted and their initial content is estimated to be 1 of dry weight (Bilaj 1982; Segi, 1983; Kanevskaya, 1984; Prachuabmorn, Noppaporn Panich, 2010). To compare the content of microorganisms in different samples, the number of the groups of individual microorganisms per 1 g of dry weight present in the packing material is calculated. For this purpose, analytic weights are employed for weighing 1 g (at an accuracy of 1 mg) of the substrate to be analysed thus placing it in glass containers with stoppers (buxes) and dried at a temperature of 105
C to constant weight, i.e. when the substrate dried in an oven and cooled in an exicator is further dried for 4 h and does not lose more than 0.1% of the initial weight. This is usually achieved within 4 h of drying. The number of microorganisms is calculated according to the formula n ¼ abc/d, where n—the number of the initial state of microorganisms (units making colonies—umc) per 1 g of dry substrate. a—the number of the colonies grown in the dish. b—the level of diluting the suspension. c—the volume of the inoculated suspension (mL), d—weight of dry soil (g). The average is calculated from three replicates (LST ISO 4833, 1999). The excretion of pure cultures and microorganism identification. For the precise identification of microorganisms, the pure culture should be obtained. Thus, microorganisms from individual colonies are inoculated using a microbiological needle on different agar media. The microorganisms predominant in the substance of the packing material are identified. The resulting pure cultures are specified employing classical methods described by Ellis 1971; Pitt 1979; Watanabe 2002; Chaverri and Samuels 2003; Samson and Frisvad 2004; Domsh et al. 2007; Pečiulytė and Bridžiuvienė 2008 for fungi, Kurtzman et al., 2011—for yeast and Garrity 2005— for bacteria. Diagnostic kits embracing chromogenic substrates are also used for identifying yeast. Reactions are based on certain enzyme activity (peptidase, oxidase, phenol oxidase) and are evaluated considering variations in colour change and/or fungal

508

9 Technological Development from the Model to the Prototype: An Example of the. . .

growth intensity. Identification methods are described in the schemes provided by the manufacturers.

Pilot Biofilter with Straight Lamellar Plates

Fig. 9.19 Variations in the number of microorganisms present in the packing material of the pilot biofilter with straight lamellar plates during acetone removal at different temperatures (1— first week of pollutant removal, 2—second week of pollutant removal; a— beginning of the week, b— end of the week)

cfu/g of d.w.

Prior to starting an experiment on pilot biofilters, the selected microorganisms of the BRL collection were embedded in the packing materials. The microorganisms were then subjected to one-week adaptation removing different pollutants (acetone, xylene and ammonia) at a temperature of 28
C. The microorganisms are secreted from the packing material of the biofilter at the beginning and end of each week. During the adaptation period, the number of fungi increased steadily from 4.7  103 to 3.1  106 cfu/g of d.w. When removing acetone and xylene, the content of yeast remained almost constant (approximately 1.5  105–2.6  106 cfu/g of d.w.) and increased to 1.5  108 cfu/g of d.w. when ammonia was removed. Bacterial count remained almost constant throughout the adaptation period (except at the beginning of the first week) and reached up to 8.2  107 cfu/g of d.w. At the end of the adaptation period, acetone was removed from the air by changing temperature every 2 weeks (Fig. 9.19). Eliminating acetone at a temperature of 24
C initially resulted in 7.4  105–3.2  106 cfu/g of d.w. of micromycetes and yeast, and then increased significantly in the second week (up to 2.2  108). Bacterial content was higher, similar for both weeks and highest compared to other temperatures (1.3  108–1.5  1010 cfu/g of d.w.). Thus, fungal microorganisms possibly adapted to this pollutant and temperature later than bacteria. Raising temperature to 28
C leads to a drop in the content of fungi, made 7.9  105 cfu/g of d.w. in the middle of the test and then rose again up to 7.3  107 cfu/g of d.w. Yeast count remained at this level for both weeks while bacterial count increased to 1.8  109 in the first week and decreased slightly in the second (to 1.7  108 cfu/g of d.w.). Thus, this temperature was suitable for all groups of microorganisms present on the packing material, particularly for yeast and bacteria.

1E+11 1E+10 1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 1

Fungi

a

1

b 24

a o

2

b

a

b 1

Bacteria

Yeast

28

a o

2

b

a

1

b

a

b 32

o

2

9.4 Microbiological Properties of the Packing Materials of Pilot Biofilters

509

At a temperature 32
C, the content of fungi gradually decreased and counted 3.7–8.3  106 cfu/g of d.w. in the second week. At this temperature, similarly to 28
C, the content of yeast was more abundant than that of fungi (up to 6.9  107 cfu/g of d.w.). Bacterial count was slightly above the abundance of yeast and ranged from 1.2  107 to 2.0  108 cfu/g of d.w. The abundance of bacteria was found to increase slightly with a decreasing number of fungi and yeast. It should be noted that fluctuations in the number of microorganisms at the same temperature may have been dependent on the humidity of the packing material which also varied considerably. The content of microorganisms and their species composition varied at different temperatures. Similarly to wavy lamellar plates, the fungal genera Trichoderma dominated during adaptation. However, removing acetone at a temperature of 24
C gradually diminishes the above-introduced fungi because the fungus Stachybotrys sp. start dominating at a temperature of 28
C and particularly spread at 32
C. These higher temperature-resistant fungi are known to be pathogenic. Occasionally, in combination with Stachybotrys sp., the micromycetes of the genus Chaetomium were secreted. The inoculated fungi were suppressed by the native species although sometimes Aspergillus versicolor BF-4 was secreted. While removing acetone, the yeast Exophiala jeanselmei introduced at different temperatures managed to adapt and evolve. The temperatures of 24
C and 28
C were found to be particularly suitable for the growth of the yeast Ex. jeanselmei. The removal of acetone at 32
C reduced the amount of the latter yeast. The removal of acetone under varying temperatures differed in the composition of bacterial genera and species. The bacterial species Bacillus subtilis, Staphylococcus aureus, Pseudomonas putida and P. fluorescens species as well as the bacterial genera Rhodococcus sp. and Micrococcus sp. were predominating during the adaptation period. At a temperature of 24
C, the bacterial species Bacillus subtilis, Staphylococcus aureus and Pseudomonas fluorescens and the bacterial genus Xanthomonas sp. were prevailing, which is characteristic of a lower temperature. Under 28
C, the bacterial species Bacillus subtilis, Staphylococcus aureus and Pseudomonas fluorescens species and the bacterial genus Rhodococcus sp. were mainly secreted. At a temperature of 32
C, most bacteria requiring a higher temperature were presented by Bacillus subtilis, Staphylococcus aureus species and Rhodococcus sp. as well as by the secreted bacterial genera Pseudomonas aeruginosa and Enterobacter sp. The initial removal of xylene at a temperature of 24
C demonstrated that the number of fungi remained similar to that at the end of removing acetone (was 106 cfu/g of d.w.) and, with rare exceptions, little variation was observed under variations in filtration temperature (Fig. 9.20). The content of yeast within the process of removing this pollutant slightly decreased at a temperature of 28
C compared to 24
C and further dropped to 32
C (to 9.2  105 cfu/g of d.w. at the end). Bacterial count decreased slightly at the start of removing xylene compared to the end of removing acetone. At both temperatures of 24
C and 28
C, their numbers ranged from 2.7  107 to 2.6  108 cfu/g of d.w. However, a rise in the temperature

9 Technological Development from the Model to the Prototype: An Example of the. . .

Fig. 9.20 Variations in the number of microorganisms present in the packing material of the pilot biofilter with straight lamellar plates during xylene removal at different temperatures (1— first week of pollutant removal, 2—second week of pollutant removal; a— beginning of the week, b— end of the week)

cfu/g of d.w.

510

1E+10 1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 1

Fungi

a

1

a

b

o

2

b

a

cfu/g of d.w.

Fig. 9.21 Variations in the number of microorganisms present in the packing material of the pilot biofilter with straight lamellar plates during ammonia removal at different temperatures (1— first week of pollutant removal, 2—second week of pollutant removal; a— beginning of the week, b— end of the week)

1E+11 1E+10 1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 1

o

1

b 24

a o

2

b

a 1

2

b

a

32

28

a o

2

o

2

Bacteria

Yeast

b 1

b

a

b

28

Fungi

a

a

b 1

24

Bacteria

Yeast

b

a 1

b

a

b

o

32

2

to 32
C increased bacterial count significantly thus sometimes reaching as much as 1.2  109 cfu/g of d.w. The diversity of micromycetes was higher while removing xylene rather than acetone. The fungus Chaetomium sp. was detected yet at the adaptation period and remained up to a temperature of 32
C. In addition, the fungal genus Geotrichum was secreted. While removing xylene, similarly to the case of acetone, Stachybotrys sp. widely spread (Fig. 9.21). In contrast to acetone removal, no micromycetes of the genus Trichoderma were detected. The selected fungus Aspergillus versicolor occurred periodically. The yeast Exophiala jeanselmei also survived and developed well during xylene removal. A temperature of 24
C was found to be the most appropriate for Ex. jeanselmei while at a temperature of 32
C the single colonies of the yeast Ex. jeanselmei were detected. The composition of bacterial genera and species differed slightly during the process of xylene removal. Throughout the adaptation period, at a temperature of 28
C, the bacterial species Bacillus subtilis, Staphylococcus aureus and Pseudomonas putida prevailed. At a temperature of 24
C, Bacillus subtilis, Staphylococcus aureus and Pseudomonas fluorescens were predominating. Meanwhile, at a temperature of 28
C, most of Bacillus subtilis, B. cereus and Pseudomonas fluorescens bacteria were secreted. For removing xylene at a temperature of 32
C, the bacterial species Bacillus subtilis, Staphylococcus

9.4 Microbiological Properties of the Packing Materials of Pilot Biofilters

511

aureus and Pseudomonas aeruginosa species and the bacterial genus Enterobacter sp. were grown. At the beginning of ammonia removal, the content of microorganisms decreased slightly: at a temperature of 24
C, the content of fungi made 2.0–9.6  106, that of yeast –4.2  106–5.6  107, and that of bacteria –3.1  107–2.510 cfu/g of d.w. However, a rise in the temperature to 28
C increased the total number of microorganisms (e.g. yeast grew up to 8.0  108 cfu/g of d.w.). Bacterial growth was good at a temperature of 32
C, and fungal and yeast count varied possibly due to the fluctuating humidity of the packing material (Baltrėnas et al. 2016c, Baltrėnas et al. 2015c, d). Yet during the adaptation to ammonia process, the fungus Stachybotrys sp. predominated, and the removal of this pollutant changed the composition of fungal species very strongly depending on temperature. At 24
C, as in the case of xylene removal, the fungal genus Chaetomium spread, and at a temperature of 28
C Geotrichum sp. prevailed. At this temperature, unidentified bacteria resistant to antibiotic chloramphenicol were also abundant. This was also the case of xylene removal. At a temperature of 32
C, the selected myxomycete Cladosporium herbarum reappears. No yeast Exophiala jeanselmei was detected during the ammonia adaptation period. The yeast Ex. jeanselmei was most abundantly secreted at a temperature of 24
C. For removing ammonia at the temperatures of 28
to 32
C, the content of Ex. jeanselmei decreased. Other yeast were not detected on the packing material of the biofilter with straight lamellar plates when removing all pollutants. The removal of ammonia demonstrated that the bacterial species Bacillus subtilis, B. cereus, Staphylococcus aureus, Pseudomonas putida and P. fluorescens species and the bacterial genus Rhodococcus sp. were predominating at the adaptation period. At a temperature of 24
C, mainly the bacterial species Bacillus subtilis, Staphylococcus aureus, Pseudomonas fluorescens, P. aeruginosa species and the bacterial genus Methylobacterium sp. were secreted. At a temperature of 28
C, the bacterial species Bacillus subtilis, Staphylococcus aureus and Pseudomonas fluorescens as well as the bacterial genera Rhodococcus sp. and Methylobacterium sp. were predominantly secreted. When removing ammonia at a temperature of 32
C, the grown bacterial species Bacillus subtilis, Staphylococcus aureus, Pseudomonas aeruginosa and P. putida as well as the bacterial genera Enterobacter sp. and Micrococcus sp. made the largest part. It should be noted that during the removal of all investigated pollutants, the bacterial species Bacillus subtilis were secreted throughout the temperature range.

Pilot Biofilter with Wavy Lamellar Plates The content of microorganisms ranged from 104 to 108 cfu/g of d.w. in the pilot biofilter with wavy lamellar plates during the acetone adaptation period (Fig. 9.22). While removing acetone at a temperature of 24
C, the content of microorganisms increased if compared to the acetone adaptation period. At a temperature of 24
C,

1E+11 1E+10 1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 1

9 Technological Development from the Model to the Prototype: An Example of the. . . Fungi

Bacteria

Yeast

log cfu/g of d.w.

log cfu/g of d.w.

512

a

1

b

a

24o

2

b

a

b 1

a

28o

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b

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b

a

b

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1E+10 1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 1

2

Fungi

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1

b

a

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2

a

b

b 1

a

28o

2

b

a 1

b

b

a 32o

2

b)

log cfu/g of d.w.

a)

Bacteria

Yeast

1E+10 1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 1

Fungi

a

1

b

a

24o

2

b

a

b 1

Bacteria

Yeast

a

28o c)

2

b

a 1

b

b

a 32o

2

Fig. 9.22 The number of microorganisms present in the packing material of the pilot biofilter with wavy lamellar plates removing acetone—(a), xylene—(b) and ammonia—(c) at different temperatures (1—first week of pollutant removal, 2—second week of pollutant removal; a—beginning of the week, b—end of the week)

the number of microscopic fungi increased from 104 to 108 cfu/g of d.w., which was the highest result. An increase in the temperature up to 28
C had no effect on the number of yeast. After the start of removing acetone at a temperature of 32
C, the number of all groups of microorganisms decreased abruptly. The content of bacteria remained highest among all groups of microorganisms when removing acetone at different temperatures (Fig. 9.22a). From the very start of the experiment, the packing material of the biofilter was adapted to acetone. The fungal genus Trichoderma was predominating, which suppressed the growth of all other, natural and selected fungi and the yeast Exophiala jeanselmei. Subsequently, at a temperature of 24
C, the micromycetes of the genus Penicillium appeared along the fungal species Trichoderma. Chaetomium sp. or Geotrichum sp. and Cladosporium herbarum 7KA that were sometimes secreted. The composition of bacterial genera and species differed when removing acetone at different temperatures. During the adaptation period, the bacteria Bacillus subtilis, Staphylococcus aureus, Pseudomonas putida, Burkholderia convexa and Rhodococcus sp. were mainly secreted. At a temperature of 24
C, the bacteria Bacillus subtilis, Staphylococcus aureus, Pseudomonas putida, Micrococcus sp. and Erwinia sp. were prevailing. Also, the bacterium Bacillus subtilis was selected throughout the temperature range.

9.4 Microbiological Properties of the Packing Materials of Pilot Biofilters

513

For adapting to xylene, the content of microorganisms on the pilot biofilter with wavy lamellar plates ranged between 106 and 109 cfu/g of d.w. The removal of xylene at a temperature of 24
C during the first week demonstrated that the content of yeast ranged from 106 to 108 cfu/g of d.w. The content of micromycetes and yeast decreased sharply when xylene removal was started at a temperature of 28
C. When removing xylene, a temperature of 32
C was most suitable for bacterial development ranging from 107 to 109 cfu/g of d.w. The fungal genus Trichoderma remained dominant during adaptation to xylene. However, the start of removing this pollutant at a temperature of 24
C showed that fungi gradually disappeared and were only rarely found. Starting from the second week of removal, the genera Penicillium and Chaetomium began dominating. At a temperature of 32
C, the latter remained the only species secreted from the packing material of the biofilter. The isolated colonies of the fungus Stachybotrys sp. were occasionally secreted. The yeast colony Exophiala jeanselmei was found to be very abundant adapting the packing material of the biofilter with wavy lamellar plates to xylene vapour. Only single colonies of the yeast Exophiala jeanselmei were secreted at 24–32
C during xylene removal. The removal of xylene at different temperatures disclosed that the composition of bacterial genera and species differed slightly. The bacterial species Bacillus subtilis and Staphylococcus aureus prevailed at all temperatures tested. When removing xylene, the bacteria Bacillus subtilis were selected throughout the temperature range. The number of microorganisms in the packing material of the pilot biofilter with wavy lamellar plates ranged from 106 to 108 cfu/g of d.w. during the adaptation to ammonia process (Fig. 9.22c). No yeast was detected at the end of the first week of ammonia removal, and their growth was suppressed by the fungal genus Trichoderma. The removal of ammonia at a temperature of 28
C, the number of yeast and microscopic fungi ranged from 106 to 107 cfu/g of d.w. During the process of removing ammonia at 28
C, bacterial count did not exceed 108 cfu/g of d.w. The removal of ammonia at a temperature of 32
C showed that the number of microscopic fungi and yeast remained unchanged at 107 cfu/g of d.w. while bacterial count reached 109 cfu/g of d.w. Following the adaptation of microorganisms present in the packing material first to acetone and xylene and then to ammonia, the fungal genus Trichoderma was replaced by micromycetes Stachybotrys sp. and Chaetomium sp. However, once pollutant removal was started at a temperature of 24
C, Trichoderma sp. occurred again next to Chaetomium sp., and at 28
C—next to Geotrichum sp. These micromycetes also persisted at a higher temperature of 32
C, but in this case, micromycetes Stachybotrys sp. were also detected. Only very few yeast colonies of Exophiala jeanselmei were noticed adapting the packing material of the biofilter with wavy lamellar plates to ammonia vapour. For removing ammonia, only isolated colonies of the yeast Exophiala jeanselmei were secreted at a temperature of 24–32
C. The removal of ammonia at different temperatures demonstrated that the composition of bacterial genera and species differed insignificantly. The bacteria Bacillus

514

9 Technological Development from the Model to the Prototype: An Example of the. . .

subtilis, Staphylococcus aureus, Pseudomonas putida and P. fluorescens and the bacterial genus Rhodococcus sp. prevailed at all investigated temperatures. In addition to the bacteria mentioned above, Burkholderia convexa was secreted during the ammonia adaptation period. At the temperatures of 24
C and 28
C, apart from the introduced bacterial species mentioned, Bacillus cereus and Pseudomonas aeruginosa were predominating and micromycetes began developing. At a temperature of 32
C, the bacterial genera Burkholderia convexa, Erwinia sp. and Enterobacter sp. started developing. When removing ammonia at all tested temperatures, the selected bacteria Bacillus subtilis were secreted (Baltrėnas et al. 2015a, 2015c, d, Baltrėnas et al. 2016a).

9.4.2

Activity of the Selected Microorganisms Considering the Temperature and Other Physical-Chemical Parameters for Pilot Tubular Biofilters

Taking the samples of the biofilter packing material. The samples of the packing material of the biofilter were taken two times a week under the operating mode. A mixture of wood biochar and wood fibre represented the packing material of the tubular layout. The packing material present in the tube was mixed to a depth of 15–20 cm taking the samples of 5–10 g and placing them in plastic bags. Before the next sample was taken, the tools were sterilized in the flame or wiped with a disinfectant (70
ethyl alcohol) using cotton wool. The samples were transported in such a way as to minimize the alteration of humidity content in the substrate and were analysed immediately or, in the case it was required, stored in the dark refrigerator at a temperature of 4
C for a maximum of 3–4 days. Preparing, inoculating and accounting microorganism suspensions on nutrient media. The flushing (suspension dilution) method was used for secreting living microorganisms from the packing materials of the biofilter and calculating their content. The method allows characterizing the effect of different substrate types and environmental conditions on the composition of fungal, yeast and bacterial species. 1–10 g of the sample taken is weighed, placed in the flask of 90 mL saline solution (0.9% NaCl) and shaken for 10 min at 400 rpm. The first dilution corresponds to 1:100 or dilution at 102. The resulting suspension is diluted by transferring 1 mL of the liquid into a tube containing 9 mL of saline solution. This produces several dilutions (up to 107). The required dilution (1 mL) is inoculated into Petri dishes and made up in the dissolved agar medium. Following the inoculation of the suspension, the packing material is filtered and dried to constant weight. The increased colonies of microorganisms and counted thus calculating their content in 1 g of the dry weight of the sample. Preparation of the selected microorganisms. Based on a study of microorganism properties and toxicity in warm-blooded animals, four strains of microorganisms were selected thus creating the BRL collection of biofilter packing materials. The

9.4 Microbiological Properties of the Packing Materials of Pilot Biofilters Fig. 9.23 The number of microorganisms present in the pilot tubular biofilter containing biochar under supplied acetone at the temperatures of 24
C, 28
C and 32
C (1—first week of pollutant removal, 2—second week of pollutant removal; a— beginning of the week, b— end of the week)

1E+11 1E+10 1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 1

Fungi

a

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a

b

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a

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collection includes micromycetes Aspergillus versicolor BF-4 and Cladosporium herbarum 7KA, the yeast Exophiala sp. BF1 and the bacterium Bacillus subtilis B20. The cultures grown in the tubes on the agar medium were washed out using sterile saline and filtered through sterile cotton wool. All suspensions were mixed and diluted up to 1 L in order the content of conidia (cells) should make at least 108 cfu/ mL. The suspension was sprayed evenly with a hand spray on the biofilter plates. The tubular biofilter was filled with the suspension via the funnel 15 mL daily. Following 3 days of adaptation, the release of the pollutant started. The microorganisms, including bacteria, yeast and micromycetes, were found to manage to function in the tubular biofilter containing the material made of biochar and wood fibre changing temperature from +24
C to +32
C and supplying pollutants such as acetone, xylene and ammonia. The removal of acetone at all tested temperatures embracing 24
C, 28
C and 32
C showed that the number of microscopic fungi was almost constant at 1.8  109 cfu/g of DW. The highest number was established on the last week of the study and made 1.8  109 cfu/g of DW (Fig. 9.23). During the adaptation period, it was lower and reached 106 cfu/g of DW. Meanwhile, the number of yeast increased steadily adding acetone and raising temperature from 24
C to 32
C. The lowest amount of yeast was secreted on the first week and the largest—on the last week of the study (1.1  107 and 4.1  109 cfu/g of DW, respectively). Also, within the adaptation period, 2.6  108 cfu/g of DW of yeast was secreted. Bacterial count was highly dependent on temperature. An interesting point is that the highest bacterial count was found supplying acetone at a temperature of 24
C (2.4  1010 cfu/g of DW). An increase in the temperature up to 28
C reduced the content of bacteria to 109 and 108 cfu/g of d.w., and a rise in the temperature to 32
C resulted in a steady growth of bacterial count reaching 1.3  1010 cfu/g of d.w. (Fig. 4.130). Therefore, it can be assumed that acetone did not significantly affect bacterial growth. During the adaptation period, the content of the secreted bacteria was the lowest and made 6.5  107 cfu/g of DW. The species composition of microorganisms was different when removing acetone and changing the temperature from 24
C to 32
C. The fungal genus

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9 Technological Development from the Model to the Prototype: An Example of the. . .

Fig. 9.24 The number of microorganisms present in the pilot tubular biofilter containing biochar under supplied xylene at the temperatures of 24
C, 28
C and 32
C (1—first week of pollutant removal, 2—second week of pollutant removal; a— beginning of the week, b— end of the week)

1E+11 1E+10 1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 1

Fungi

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Penicillium predominated when adapting to acetone and subsequently removing the pollutant. At the temperatures of 24
C and 28
C, Paecilomyces variotii was also secreted. Under a rise in temperature to 32
C, the fungus Geotrichum sp. appeared and later started dominating. These are potential pathogenic micromycetes. During adaptation to acetone, the selected fungus Cladosporium herbarum 7KA survived well and developed abundantly. However, the other selected fungus Aspergillus versicolor BF-4 also remained because it was secreted during the acetone and ammonia removal processes. The selected yeast Exophiala jeanselmei was dominating being abundantly secreted at all temperatures tested. Micromycetes were also secreted because the filter itself was overgrown with these microscopic fungi. Acetone removal at different temperatures resulted in the different composition of bacterial genera and species. The bacterial species Bacillus subtilis, Staphylococcus aureus, Pseudomonas putida and P. fluorescens were mainly secreted during the adaptation to acetone period at a temperature of 28
C. At 24
C, the bacteria Bacillus subtilis and Staphylococcus aureus prevailed. The composition of bacterial species secreted at 28
C coincided with the bacterial species of the adaptation period, and the bacterial species Bacillus cereus was secreted. In addition, micromycetes grew at the above-introduced temperature. At 32
C, most bacteria requiring a higher temperature grew and were presented by the bacterial genera Pseudomonas aeruginosa and Enterobacter sp. The bacterial species Pseudomonas fluorescens persisted under the supplied acetone at a temperature of 32
C. When supplying xylene, micromycete count was 108–109 cfu/g of DW at all tested temperatures, including 24
C, 28
C and 32
C (Fig. 9.24). Most micromycetes compared to yeast and fungi were secreted at a temperature of 24
C. Thus, it can be assumed that this temperature was the most favourable for the growth of micromycetes and the least affected by the pollutant xylene. Meanwhile, the number of yeast secreted at the temperatures of 28
C and 32
C was highest throughout the test and made from 1.4  1010 to 2.9  1010 cfu/g of DW (32
C and 28
C, respectively). Bacterial count at the temperatures tested did not exceed 109 cfu/g of DW.

9.4 Microbiological Properties of the Packing Materials of Pilot Biofilters Fig. 9.25 The number of microorganisms present in the pilot tubular biofilter containing biochar under supplied ammonia at the temperatures of 24
C, 28
C and 32
C (1—first week of pollutant removal, 2—second week of pollutant removal; a— beginning of the week, b— end of the week)

1E+11 1E+10 1E+09 1E+08 1E+07 1E+06 1E+05 1E+04 1000 100 10 1

Fungi

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There was no significant difference in the species composition of the microorganisms during the xylene removal process and at temperature variations from 24
C to 32
C. Micromycetes were represented by the dominating fungal genus Penicillium and selected Cladosporium herbarum. Even at 32
C, the composition of fungal species did not vary. The selected yeast Exophiala jeanselmei was dominating and abundantly secreted at all temperatures tested. Also, a significant amount of micromycetes was secreted because the filter itself was overgrown with microscopic fungi. The bacterial species Bacillus subtilis and Staphylococcus aureus were predominating at all temperatures tested. In addition to the above-mentioned species of bacteria, Pseudomonas fluorescens was secreted at 28
C. At a temperature of 32
C, the diversity of bacterial species was the highest: the bacterial species Bacillus subtilis, Staphylococcus aureus, Pseudomonas aeruginosa and P. putida and a small number of the bacterial genera Rhodococcus sp. and Enterobacter sp. were secreted. The supply of ammonia at the temperatures of 24
C and 28
C increased bacterial count steadily from 109 to 1010 cfu/g of DW (Fig. 9.25). At a temperature of 32
C, the number of these microorganisms decreased again to 109 cfu/g of DW. Meanwhile, the highest number of micromycetes and yeast was established at a temperature of 24
C (5.8  109 and 2.9  109 cfu/g of DW, respectively) (Fig. 9.25). A further increase in temperature resulted in a drop in the content of the above-mentioned microorganisms. Thus, it could be assumed that a higher temperature and ammonia inhibited the growth and development of microscopic fungi, yeast and bacteria. During the adaptation period, the number of micromycetes, yeast and bacteria did not exceed 109cfu/L of DW. Ammonia removal at different temperatures caused a different composition of bacterial genera and species. The removal of ammonia both during the adaptation period and at the temperatures of 24
C and 28
C resulted in a slight increase in Paecilomyces variotii and a decrease in the number of the selected fungi. However, a rise in the temperature of 32
C disclosed that the selected fungus Cladosporium herbarum was secreted next to the dominant genus Penicillium. In addition, Geotrichum sp. Abundantly developed at this temperature. The yeast Exophiala

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9 Technological Development from the Model to the Prototype: An Example of the. . .

jeanselmei almost did not present during ammonia adaptation. For removing ammonia, a temperature of 24
C was the most suitable for growing the yeast Exophiala jeanselmei. The bacterial species Bacillus subtilis, Staphylococcus aureus and Pseudomonas fluorescens prevailed at a temperature of 28
C during the adaptation to ammonia period. The diversity of bacterial species increased significantly at a temperature of 24
C. The bacterial species Bacillus subtilis, B. cereus, Staphylococcus aureus, Pseudomonas fluorescens and P. putida as well as the bacterial genera Micrococcus sp., Rhodococcus sp. and Methylobacterium sp. were secreted. The removal of ammonia at a temperature of 28
C demonstrated that the species composition of the secreted bacteria coincided with the bacterial species secreted at 24
C. However, no growth of the bacterial genus Rhodococcus sp. was noticed. In addition, micromycetes grew under the above-introduced temperature. The findings of the study showed that the abundance of microorganisms in the packing material of the biofilter in both lamellar plate and tubular air treatment biofilters was subject to both the removed pollutant and temperature. For removing acetone from the air applying straight lamellar plate air treatment biofilters, a temperature of 28
C was the most suitable for the development of micromycetes and yeast while the highest bacterial content was found at a temperature of 24
C. Meanwhile, when removing xylene and ammonia, most bacteria were secreted at a temperature of 32
C. The composition of microorganism species varied along with the applied pilot biofilters with straight lamellar plates, different temperatures and removed pollutants. At a temperature of 32
C, relatively pathogenic microorganisms (Stachybotrys sp., Enterobacter sp., etc.) developed more abundantly, and therefore the temperature was not recommended for removing airborne volatile pollutants. The microorganisms selected from all groups took the roots and remained in the packing material until the end of the experiment. The removal of volatile compounds at different temperatures through the selected micromycetes and yeast present in the pilot biofilter with wavy lamellar plates were suppressed by the fungal genus Trichoderma. The selected bacteria Bacillus subtilis were found removing the tested volatile compounds at all different temperatures. The results of the conducted research showed that bacteria, yeast and micromycetes were capable of functioning in the tubular biofilter with the packing material containing biochar, changing temperature from 24
to 32
C and supplying pollutants acetone, xylene and ammonia. The removal of volatile substances, including acetone, xylene and ammonia, was found to favour the growth and development of microscopic fungi at a temperature of 24
C–28
C and yeast and bacteria at 28
C–32
C. The selected microorganisms, including the yeast Exophiala jeanselmei, the bacteria Bacillus subtilis and the fungi Cladosporium herbarum and Aspergillus versicolor, were secreted throughout the test at a varying temperature of 24
C– 32
C by removing the investigated volatile substances acetone, xylene and ammonia from the air. A comparison of the biofilters with straight and wavy lamellar plates with respect to microorganism development showed it was partly dependent on the pollutant

9.5 Air Treatment Effectiveness of Pilot Biofilters

519

being removed. Thus, acetone removal showed that fungi developed better on the biofilter layout with wavy lamellar plates, yeast developed equally well on straight and wavy lamellar plates and bacteria had better conditions on wavy lamellar plates. Meanwhile, when removing xylene, the type of the biofilter structure had a marginal effect on all groups of microorganisms. Under the influence of ammonia, fungi developed better on straight lamellar plates and were not affected by yeast and bacteria. A comparison of all biofilters showed that the tubular filter was the most favourable for fungi and yeast development, whereas bacteria developed similarly on tubular and wavy structure filters (Repečkienė et al. 2015; Baltrėnas et al. 2015a).

9.5 9.5.1

Air Treatment Effectiveness of Pilot Biofilters Air Treatment Effectiveness of the Pilot Biofilter with Straight Lamellar Plates

500 400

Pollutant concentration before removal Pollutant concentration after removal Effectiveness, % 30 m3/h

100 m3/h 100 m3/h

100 m3/h

300 200 A

B

C

D

100 0

1

3 5 7

9 11 13 15 17 19 21 23 25 27 29 31 33 35 Experiment time, days

100 90 80 70 60 50 40 30 20 10 0

Air treatment effectiveness, %

Acetone concentration, mg/m3

Figure 9.26 shows air treatment effectiveness of the biofilter with straight lamellar plates. The figure provides that air treatment effectiveness increased to 80.5% during the adaptation period of the microorganisms up to the fifth day of the experiment. The calculated air treatment effectiveness indicates that the embedded microorganisms successfully adapted to the packing material and did their job effectively. Air treatment effectiveness varied from 75.5% to 81.7% at the air flow rate of 100 m3/h supplied to the biofilter, under the pollutant concentration of 300  25 mg/m3 and the maintained temperature of 24
C. The reduced air treatment effectiveness following adaptation can be explained by the increased air flow discharge and a higher pollutant load on the biofilter (Baltrėnas et al. 2015a).

Fig. 9.26 The dependence of biofilter air treatment effectiveness on the supplied air polluted with acetone vapour and maintained air temperature in the biofilter with straight lamellar plates

9 Technological Development from the Model to the Prototype: An Example of the. . . Pollutant concentration before removal Pollutant concentration after removal Effectiveness, %

Xylene concentration, mg/m3

500

100 m3/h

100 m3/h

100 m3/h

400

100 90 80

300

70 200 A

B

C

100 0

60 50

1

3

5

7

9 11 13 15 17 19 21 23 25 27 29 Experiment time, days

40

Air treatment effectiveness, %

520

Fig. 9.27 The dependence of biofilter air treatment effectiveness on the supplied air polluted with xylene vapour and maintained air temperature in the biofilter with straight lamellar plates

During experimental stage B, the population of microorganisms, including micromycetes, yeast and bacteria, on the packing material varied from 6.9  1.4  105 to 2.2  0.2  108 cfu/g, from 1.6  0.1  105 to 1.0  0.9  108 cfu/g and from 1.3  0.7  108 to 1.5  0.0  1010 cfu/g, respectively. No significant changes in the number of microorganisms were observed between the 15th and 35th days of the experiment. Bacterial count ranged from 108 to 109 cfu/g, that of micromycetes—from 106 to 107 cfu/g and yeast count remained constant at 107 cfu/g. At stage C, an increase in air treatment effectiveness up to 87.5% was noticed, while at Stage D, air treatment effectiveness remained stable and averaged 87.8%. Investigated the biofilter by supplying acetone vapour to the device and disclosed that under the load of 40 g/m3/h, the achieved air treatment effectiveness made approximately 92% (our experiments demonstrated the effectiveness of around 88% in the case of straight and approximately 92% in the case of wavy lamellar plates). While removing xylene vapour through the composite packing material of nonwoven cork and wood fibre in the biofilter with straight and wavy lamellar plates, the maximum air treatment effectiveness was achieved at a temperature of 32
C and reached 88.6% and 90.1%, respectively (Figs. 9.27 and 9.30). The number of microorganisms in the packing material was very stable throughout the experiment in both the biofilter with straight and wavy lamellar plates. The biofilter with straight lamellar plates counted 106 cfu/g of micromycetes, 107 cfu/g of yeast and 108 cfu/g of bacteria. The number of the selected microorganisms in the biofilter with wavy lamellar plates reached 106–107 cfu/g of micromycetes, 107 cfu/g of yeast and 108– 109 cfu/g of bacteria. Carried out experimental studies using a biofilter to remove xylene. Air flow temperature varied from 5
C to 35
C throughout the experiment. The obtained results showed that the optimal temperature was in the range from 30
C to 35
C under the achieved average air treatment effectiveness of 95%. Spanish scientists Gallastegui et al. (2011) analysed air treatment effectiveness

521

Pollutant concentration before removal Pollutant concentration after removal Effectiveness, %

500

100 m3/h

100 m3/h

100 100 m3/h

400

90 80

300

70 200 B

A

60

C

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50 1

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11 13 15 17 19 Experiment time, days

21

23

25

40

Air treatment effectiveness, %

Ammonia concentration, mg/m3

9.5 Air Treatment Effectiveness of Pilot Biofilters

Fig. 9.28 The effectiveness of the pilot biofilter with straight lamellar plates removing ammonia vapour from the air

removing xylene and discovered it was equal to 95% under pollutant removal capacity of 50 g3 h1. The removal of ammonia through the packing material containing NWC + WF incorporated into the biofilter with straight lamellar plates (Fig. 9.28) resulted in air treatment effectiveness of 83.5% and 85.1%, respectively, at a temperature of 24
C (stage A of the study). The population of microorganisms on the packing material remained unchanged compared to removing xylene and made approximately 6.1  1.3  106 cfu/g of micromycetes, 2.5  0.3  107 cfu/g of yeast and 1.1  0.1  108 cfu/g of bacteria in the biofilter with straight lamellar plates.

9.5.2

Air Treatment Effectiveness of the Pilot Biofilter with Wavy Lamellar Plates

Figure 9.29 shows the results of experimental studies on the main parameter, i.e. biofilter air treatment effectiveness, removing acetone vapour-polluted air through the packing material using wavy lamellar plates. Prior to testing biofilter capacity to eliminate the above-introduced contaminant, an adaptation (A) stage of the packing material under biofilter efficiency of 30 m3/h lasted until the fifth day of the experiment. The pollutants of a uniform concentration of 300  25 mg/m3 were supplied throughout the experiment. The concentration was selected based on the previous experimental studies employing smaller scale laboratory biofilters. Starting from the sixth day of the experiment, tests on the biofilter supplying acetone vapour-polluted air were conducted under biofilter capacity of 100 m3/h. Air flow rate averaged 0.16 ms1 in the biofilter between wavy lamellar plates, and therefore considering the height of the packing material, the contact time between acetone and the packing

500 400

Pollutant concentration before removal Pollutant concentration after removal Effectiveness, % 30 m3/h

100 m3/h 100 m3/h

100 m3/h

300 200 A

B

C

D

100 0

1

3 5 7

9 11 13 15 17 19 21 23 25 27 29 31 33 35 Experiment time, days

100 90 80 70 60 50 40 30 20 10 0

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9 Technological Development from the Model to the Prototype: An Example of the. . .

Acetone concentration, mg/m3

522

Fig. 9.29 The dependence of biofilter air treatment effectiveness on the supplied air polluted with acetone vapour and maintained air temperature in the biofilter with wavy lamellar plates

material made 12 s. Figure 9.26 shows that a rise in air flow temperature increased biofilter air treatment effectiveness. During the process of microorganism adaptation under 30 m3/h, the effectiveness of removing acetone from air flow made 78–80% and acetone removal capacity ranged from 8.6 to 10.8 gm3 h1. A high level of pollutant removal effectiveness indicates that the microorganisms embedded in the packing material quickly adapted to removing acetone vapour. At the start of the experiment, the number of microorganisms (yeast, micromycetes and bacteria) was 1.1  0.1  104 cfu/g, 1.8  0.4  105 cfu/g and 1  0.1  107 cfu/g, respectively. As for our study, the bacterium Rhodococcus inserted in the packing material was selected for its ability to decompose volatile organic compounds, including acetone. Other researchers suggested that the bacterium Rhodococcus was capable of removing VOCs (Lee et al. 2009). At the air flow temperature of 24
C (Stage B), the number of microorganisms in the biofilter ranged from 1.2–107 to 1.8 109 cfu/g, and air treatment effectiveness reached 80–83%. At the efficiency of 100 m3/h, acetone removal capacity ranged from 31.3 to 34.5 g m3 h1. At stage C, i.e. on the 21st and 24th days, bacterial growth to 1.6  0.1  109 cfu/g and 3.3  0.0  109 cfu/g, respectively, was observed. These days, air treatment effectiveness made 88% and 92.1% correspondingly. For the stable and effective operation of the biofiltration process, the number of microorganisms must be within the range of 106 to 1010 cfu/g (Sakuma et al. 2009). Thus, under this condition, the biodegradation of acetone was effective in our case, and microorganism count varied from 107 to 109 cfu/g. At stage D, air flow temperature increased to 32
C, and the same variation tendency towards microorganisms was observed. Although their number decreased, however, on the 31st day of the experiment the number of yeast, micromycetes and bacteria rose to 9.8  1.3  107 cfu/g, 5.2  0.5  107 cfu/g and

Pollutant concentration before removal Pollutant concentration after removal Effectiveness, %

500 Xylene concentration, mg/m3

523

100 m3/h

100 m3/h

100 m3/h

400

100 90 80

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70 200 A

B

C

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60 50

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3

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40

Air treatment effectiveness, %

9.5 Air Treatment Effectiveness of Pilot Biofilters

Fig. 9.30 The dependence of biofilter air treatment effectiveness on the supplied air polluted with xylene vapour and maintained air temperature in the biofilter with wavy lamellar plates

2.3  0.1  109 cfu/g, respectively. An increase in the number of microorganisms caused a rise in air treatment effectiveness to 92.6%. The highest air treatment effectiveness was recorded at an air flow temperature of 32
C and reached 93% (30th day of the experiment). Under the above-introduced air treatment effectiveness, acetone removal capacity reached 41.6 g m3 h1. At the end of the experiment, the number of microorganisms, including micromycetes, yeast and bacteria, was 2.7  0.3  107 cfu/g, 5.2  0.7  107 cfu/g and 2.4  0.1  109 cfu/g, respectively. This indicates that the population of the microorganisms inserted in the packing material was large and the selected microorganisms were fully capable of removing acetone vapour present in air flow. Considering the population of microorganisms and air treatment effectiveness, it could be assumed that under the stable biofiltration process and the number of bacteria, yeast and micromycetes making 1.0–1.8  109, 1.0–2.0  107 and 1.9–4.2  107 cfu/g, respectively, biofilter air treatment effectiveness of approximately 80% was reached, and under 2.3–3.3  109, 2.0–5.2  107 and 4.2–9.8  107 cfu/g correspondingly, effectiveness exceeded 90% (Fig. 9.30). The number of micromycetes in the pilot biofilter with wavy lamellar plates was by 16% higher, yeast count was almost equal and reached 2.5  0.2  107 cfu/g and bacterial population amounted to 2.3  0.7  108 cfu/g. A rise in temperature to 28
C did not change air effectiveness. At stage B, the temperature ranged between 85.1 and 86.7% in the biofilter with wavy lamellar plates (Fig. 9.31). At stage C, air treatment effectiveness ranged from 82.5% to 83.6% (Fig. 9.32) in the biofilter with straight lamellar plates and made 85.6% in the biofilter with wavy lamellar plates. The population of microorganisms included micromycetes ranging from 9.9  2.5  106 cfu/g to (3.0  0.3)  107 cfu/g, yeast—1  0.65.9  0.8  107 cfu/g and bacteria—1.4  109 cfu/g (Baltrėnas et al. 2010; Baltrėnas et al. 2014a, c, d; Baltrėnas et al. 2015a; Baltrėnas et al. 2016c).

Pollutant concentration before removal Pollutant concentration after removal Effectiveness, %

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100 100 m3/h

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9 Technological Development from the Model to the Prototype: An Example of the. . .

Ammonia concentration, mg/m3

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Pollutant concentration before removal Pollutant concentration after removal Effectiveness, %

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Fig. 9.31 The effectiveness of the pilot biofilter with wavy lamellar plates removing ammonia vapour from the air

Fig. 9.32 The dependence of biofilter air treatment effectiveness on the supplied air polluted with acetone vapour and maintained air temperature in the tubular biofilter

9.5.3

Air Treatment Effectiveness of the Pilot Tubular Biofilter

The case of removing acetone vapour through the packing material containing biochar and wood fibre indicated that the tendency towards air treatment effectiveness observed in the tubular biofilter remained similar to that of the two previous filters. The optimal temperature was 32
C. At stage D, air treatment effectiveness reached 85.3% (Fig. 9.32). The spread of microorganism population on the biopacking material counted 1.1  0.1  106 cfu/g of micromycetes, 2.6  0.2  108 cfu/g of yeast and 6.5  1.2  107 cfu/g of bacteria. At the other

Pollutant concentration before removal Pollutant concentration after removal Effectiveness, %

500 Xylene concentration, mg/m3

525

100 m3/h

100 m3/h

100 m3/h

400

100 90 80

300

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B

C

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9.5 Air Treatment Effectiveness of Pilot Biofilters

Fig. 9.33 The effectiveness of the pilot biofilter with wavy lamellar plates removing xylene vapour from the air

three stages, the content of micromycetes, yeast and bacteria ranged from 108 to 1010 cfu/g. Air treatment effectiveness of the tubular biofilter ranged from 76 to 85% when air flow discharge reached 100 m3/h and xylene vapour was removed through the packing material. The concentration of vapour in the supplied air flow fluctuated from 282 to 323 mg/m3. At experimental stage A, air treatment effectiveness was stable and averaged around 78%. At stage B, an increase in xylene vapour removal from the supplied air flow was observed and reached 83%. At a temperature of 32
C, air treatment effectiveness was stable from the 23rd to the 27th days of the experiment and averaged 84.4% (Fig. 9.31). On the 28th and 29th days, effectiveness declined by around 0.5%. However, that was a slight change. Thus, it can be assumed that xylene removal from the supplied air flow at stage D was the most effective and averaged 84%. The population of microorganisms (micromycetes, yeast and bacteria) on the packing material containing biochar and wood fibre was stable and reached 108– 109 cfu/g, 108–109 cfu/g and 109 cfu/g respectively throughout the experiment. Amin et al. (2014) investigated air treatment effectiveness by supplying xylene vapour to the biofilter and achieved the removal effectiveness of 98% under 90 s contact time between the pollutant and the packing material. In this case, bacterial count ranged from 1010 to 1011 of cfu/g of d.w. and micromycetes fluctuated from 106 to 107 cfu/g of d.w. (Fig. 9.33) Figure 9.34 shows that air treatment effectiveness ranged from 78.4% at the start to 81.7% on the tenth day of the experiment at stage A. Changes in air flow temperature between biofilter plates caused a slight 2.5% drop in air treatment effectiveness during the first days but steadily stabilized over the course of the experiment and averaged 81.7% throughout stage B. Only on the 14th day of the experiment, a rise in air treatment effectiveness up to 84.6% was observed. At stage C, similarly to stage B, a decrease in effectiveness during the first days was

Pollutant concentration before removal Pollutant concentration after removal Effectiveness, %

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100 m3/h

100 100 m3/h

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9 Technological Development from the Model to the Prototype: An Example of the. . .

Ammonia concentration, mg/m3

526

Fig. 9.34 The effectiveness of the pilot tubular biofilter removing ammonia vapour from the air

monitored, which may have been due to variations in operating conditions that had an effect on the adaptation of microorganisms to a new temperature. At the beginning of the experiment, the number of microorganisms (micromycetes, yeast, bacteria) reached 2.7  1.3  108, 4.9  0.8  107 and 1.8  0.1  107 cfu/g, respectively. On the ninth day of the experiment, the number of microorganisms increased and made 5.8  0.1  109 cfu/g of micromycetes, 2.9  0.2  109 cfu/g of yeast and 2.3  0.3  109 cfu/g of bacteria. On the 11th day of the experiment, the number of microorganisms decreased down to 1.3  0.6  108 cfu/g of micromycetes, 3.1  0  107 cfu/g of yeast and 4.4  0.0  108 cfu/g of bacteria, which reduced air treatment effectiveness. This indicated that effectiveness was subject to variations in the population of microorganisms. When the maximum air treatment effectiveness of 84.6% was reached, bacterial count increased to 1.6  0.5  1010 cfu/g on that day. At the end of the experiment, microorganism count was 8.7  1.0  107 for micromycetes, 1.0  0.2  108—for yeast and 4.7  1.6  `109—for bacteria under air treatment effectiveness of 83%. To sum up measurement results, the achieved effectiveness of employing acetone, xylene and ammonia pollutants made 82–92%. The highest effectiveness was obtained using the biofilter with wavy lamellar plates and the lowest—applying tubular biofilters. In due course, a general trend in the increasing effectiveness was established in all experiments removing organic substances acetone and xylene from the air. It is particularly pronounced when using biofilters with straight and wavy lamellar plates since the estimated linear correlation coefficients are orders of magnitude r ¼ 0.90 to 0.98 (with a 99% confidence level). A closer look at varying trends in effectiveness showed that the maximum rate of change 0.6% per day was achieved under the maintained air temperatures of 24
C and 28
C since an increase in the temperature to 32
C stabilized effectiveness remaining at a maximum of 28
C. This was confirmed by the above-mentioned reduced content in microorganisms and by the

9.6 Assessing Odours in Pilot Biofilters

527

values of the corresponding calculated correlation coefficients making 28
C within the period r  0.9 and 32
C within the period r  0. However, regardless of air temperature (i.e. throughout the study), the use of tubular biofilters results in the increased effectiveness making 0.25–0.3% per day, in our case r ¼ 0.64–0.90. This is explained by the observed rise in the population of microorganisms. Thus, the biofilters having such structure can expect greater efficiency over time. Considering the individual stages of temperature, different trends in varying effectiveness were determined analyzing the research results of the air polluted with inorganic ammonia. Although the overall trend in efficiency gains remained, however, it was significantly slower and averaged only 0.05–0.1% per day thus reaching the maximum value at the initial stage, i.e. in 10 days, because at a later stage, the effectiveness of the biofilter actually remained unchanged: for the biofilter with wavy lamellar plates it made around 86%, for that with straight lamellar plates—83% and for the tubular biofilter—80%. This may have been caused by the previously non-increasing number of microorganisms in the ammonia medium. A comparison of the work of layouts to the laboratory biofilters containing the packing materials with the selected microorganisms did not identify any significant changes. This circumstance allows for a more reliable interpretation of the results obtained in all tests.

9.6

Assessing Odours in Pilot Biofilters

Odour intensity of pilot biofilters was determined using a dynamic olfactometer. The effect of the biofilter on ambient air odour was established taking odour samples at 1 m from the air inlet and outlet ducts of the biofilter. A vacuum chamber operating on the ‘lung principle’ was used for air sampling. A special pump was installed to extract air from the chamber thus creating a vacuum inside. Due to the vacuum created in the chamber, the inside capacity of the samples started to be filled with the air of the working environment. The olfactometer had been warmed up to the required temperature before odour samples were evaluated. The tested sample was supplied to the dynamic olfactometer. The tests were carried out applying the forcedchoice method. The assessment session was conducted by five assessors meeting requirements for standard EN 13725: 2004 + AC: 2006. The assessment team of 5 members made 3-cycle measurements. Data on the first (pre) measurement cycle was always discarded thus providing information on the following two cycles required for calculating odour intensity. As for the forcedchoice method, the members of the assessment team indicated the location of the aromatic irritant and pointed out whether they had specified the location by predicting, implying or being assured. The sample volume required for analysis made 2.5 L. Five experts (sniffers) smelt a flow rate of 20 L/min for 3 s. Under a single biofilter structure and one type of the packing material, odour assessment was performed with three different concentrations of acetone, xylene and

9 Technological Development from the Model to the Prototype: An Example of the. . .

10 9 8 7 6 5 4 3 2 1 0

Removed pollutant – acetone Odour units, OUE/m3

Odour units, OUE/m3

528

After removal

Before removal

10 9 8 7 6 5 4 3 2 1 0

Removed pollutant – xylene

After removal

Before removal b)

Odour units, OUE/m3

a) 10 9 8 7 6 5 4 3 2 1 0

Removed pollutant – ammonia

After removal

Before removal c)

Fig. 9.35 Odour intensity using the pilot biofilter with straight lamellar plates and supplying three pollutants to the device: (a)—acetone, (b)—xylene, (c)—ammonia

ammonia. Three different types of the packing material were used for a single structure of the biofilter, and therefore 27 studies of odour were carried out. The odour level was determined employing three different structures of the biofilter each of which contained three different types of the packing material thus resulting in a total odour level of 81 times. Odour intensity was established in pilot biofilters at the end of experimental studies involving each biofilter separately. The effect of the biofilter on ambient air odour was determined by taking odour samples around 1 m from the air inlet and outlet ducts of the biofilter (Baltrėnas et al. 2015a). The samples required for investigating the odour of the supplied pollutant of the straight packing material containing WF (wood fibre) and NWC (non-woven cork) were taken next to the outlets of the polluted and treated air ducts. The taken samples were subjected to the olfactometer according to the instructions provided in the methodology. The concentration of the supplied acetone was ~300 mg/m3 under air flow discharge of 100 m3/h. Figure 9.35a shows that the intensity of the supplied acetone reached 6 OUE/m3. After treatment, acetone concentration made 27 mg/m3, and the value of its odour units dropped to 3 OUE/m3. A comparison of the reduced percentage of odour intensity before and after treatment showed it made 50%. Figure 9.35b shows that the odour intensity of the supplied xylene reached 6 OUE/m3. After treatment, xylene concentration made 29 mg/m3, and the value of its odour units dropped to 4 OUE/m3. A comparison of the reduced percentage of

10 9 8 7 6 5 4 3 2 1 0

529

Removed pollutant – acetone Odour units, OUE/m3

Odour units, OUE/m3

9.6 Assessing Odours in Pilot Biofilters

After removal

Before removal

10 9 8 7 6 5 4 3 2 1 0

Removed pollutant – xylene

After removal

Before removal b)

Odour units, OUE/m3

a) 10 9 8 7 6 5 4 3 2 1 0

Removed pollutant – ammonia

After removal

Before removal c)

Fig. 9.36 Odour intensity using the pilot biofilter with wavy lamellar plates and supplying three pollutants to the device: (a)—acetone, (b)—xylene, (c)—ammonia

odour intensity before and after treatment showed it made 40%. A comparison of the values (OUE/m3) of the odour units of acetone and xylene also provides that the odour of acetone at similar concentrations was slightly higher than that of xylene. When supplying ammonia vapour to the biofilter with straight lamellar plates, ammonia intensity was 7 OUE/m3 (Fig. 9.35c). After treatment, ammonia concentration made 27 mg/m3, and the value of its odour units dropped to 4 OUE/m3. A comparison of the reduced percentage of odour intensity before and after treatment showed it made 43%. To sum up the odour intensity of the pollutants present in the packing material of the biofilter with straight lamellar plates, ammonia odour intensity at similar concentrations was significantly higher than that of acetone or xylene. On average, the odour intensity of ammonia was 1.2 times higher than that of xylene and acetone, which determined its stronger sensation in the environment. Figure 9.36 shows the odour intensity of the packing material of the biofilter with wavy lamellar plates before and after air treatment. The wavy packing material consists of three main components, the same ones as the above-ntroduced straight packing material: non-woven cork, wood fibre and polymer panels. Both non-woven cork and wood fibre are fastened on both sides of the wavy lamellar polymer plate. As shown in the diagram above (Fig. 9.36a), the intensity of the supplied acetone reached 5 OUE/m3. After treatment, acetone concentration made 25 mg/m3, and the

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value of its odour units dropped to 3 OUE/m3. A comparison of the reduced percentage of odour intensity before and after treatment showed it made 40%. Figure 9.36b shows that the odour intensity of xylene supplied to the biofilter with wavy lamellar plates reached 6 OUE/m3. After treatment, xylene concentration made 24 mg/m3, and the value of its odour units dropped to 3 OUE/m3. A comparison of the reduced percentage of odour intensity before and after treatment showed it made 50%. A comparison of the values (OUE/m3) of the odour units of acetone and xylene also provides that the odour of acetone at similar concentrations was slightly higher than that of xylene. Figure 9.36c shows the odour intensity of ammonia reaching 7 OUE/m3 before treatment. After treatment, ammonia concentration made 25 mg/m3, and the value of its odour units dropped to 3 OUE/m3. A comparison of the reduced percentage of odour intensity before and after treatment showed it made 60%. To sum up the odour intensity of the pollutants passing through the wavy packing material containing NWC (non-woven cork) and WF (wood fibre), ammonia odour intensity at similar concentrations was significantly higher than that of acetone or xylene. On average, the odour of ammonia was 1.1 times higher than that of xylene and acetone, which determined its stronger sensation in the environment. Plate structures were made of the tubular biofilter packing material containing pine charcoal and wood fibre in a ratio of 10:1. The samples required for investigating the odours of the supplied pollutant are taken next to the outlets of the polluted and treated air ducts. Three pollutants, i.e. acetone, xylene and ammonia were used for research purposes. The concentration of the supplied acetone was ~300 mg/m3 under air flow discharge of 100 m3/h. Figure 9.37a shows that the intensity of the supplied acetone reached 5 OUE/m3. After treatment, acetone concentration made 28 mg/m3, and the value of its odour units dropped to 3 OUE/m3. A comparison of the reduced percentage of odour intensity before and after treatment showed it made 40%. A comparison of the odour intensity of acetone between the linear, wavy and tubular structure did not show any significant changes in the biopacking material. At similar concentrations, odour intensity remained almost identical after treatment, whereas before purification, the odour intensity of acetone was on average 11% higher in the straight biopacking material. Figure 9.37b shows that the odour intensity of the supplied xylene reached 6 OUE/m3. After treatment, xylene concentration made 26 mg/m3, and the value of its odour units dropped to 4 OUE/m3. A comparison of the reduced percentage of odour intensity before and after treatment showed it made 40%. A comparison of the values (OUE/m3) of the odour units of acetone and xylene also provides that the odour of acetone at similar concentrations was slightly higher than that of xylene. When supplying ammonia vapour to the tubular biofilter, its intensity was 7 OUE/m3 before treatment (Fig. 9.37c). After treatment, ammonia concentration made 25 mg/m3, and the value of its odour units dropped to 3 OUE/m3. A comparison of the reduced percentage of odour intensity before and after treatment showed it made 60% (Baltrėnas et al. 2014a, 2015a).

10 9 8 7 6 5 4 3 2 1 0

Removed pollutant – acetone Odour units, OUE/m3

Odour units, OUE/m3

9.7 Created and Manufactured Lamellar-Plate-Structure Pilot Biofilters Equipped. . .

After removal

Before removal

10 9 8 7 6 5 4 3 2 1 0

531

Removed pollutant – xylene

After removal

Before removal b)

Odour units, OUE/m3

a) 10 9 8 7 6 5 4 3 2 1 0

Removed pollutant – ammonia

After removal

Before removal c)

Fig. 9.37 Odour intensity using the pilot tubular biofilter and supplying three pollutants to the device: (a)—acetone, (b)—xylene, (c)—ammonia

9.7

Created and Manufactured Lamellar-Plate-Structure Pilot Biofilters Equipped with the Capillary Humidification System of the Packing Material

The figures below show the general views of created and manufactured lamellarplate-structure pilot biofilters equipped with the capillary humidification system of the packing material. The biofilters have a unique structure designed to remove organic and inorganic compounds from the polluted air using certain cultures of microorganisms (Baltrėnas et al. 2015a). Biological air treatment applies to cheaper, more efficient, non-waste, environmentally friendly biotechnologies that assist in effectively eliminating volatile organic compounds from the air and purging odours. The packing material is the main element of the plate-type biofilter with the capillary humidification system. The packing material consists of vertically adjacent plates arranged 6 mm from each other, which reduces the aerodynamic resistance of the device. The carried out research has demonstrated that the aerodynamic resistance of the biofilter having plate arrangement introduced above may reach around 35–50 Pa, which therefore allows employing relatively long plates thus increasing air treatment effectiveness.

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9 Technological Development from the Model to the Prototype: An Example of the. . .

The biopacking material is fixed on both sides of the plates and is activated humidifying with a saturated solution of biogenic elements. The molecules of the pollutant released during air treatment slowly move along the packing material, are transferred from the gaseous to the liquid phase and are decomposed by microorganisms on the biofilm formed in the packing material during fermentation processes. Biological air treatment effectiveness is greatly influenced by the humidification systems installed in biofilters. The optimal humidity of the packing material reaches 60–80%. According to the laws of physics, when a fluid interacts with the walls of a solid body, surface tension forces tend to raise the fluid level. Thus, under the action of surface tension forces, the fluid flows through capillaries. This phenomenon, i.e. capillary, can be applied for humidifying the packing material in the air treatment biofilter. For producing capillary humidification effect, the packing material of the biofilter consists of vertically arranged adjacent polymer plates coated with the biopacking material the lower part (one third of the total height) of which is immersed in the activated solution. Due to the effect of humidifying the packing material, humidity automatically rises thus causing the humidification of the packing material. Hence, the self-humidification system does not use any additional energy, and the packing material is humidified even when the technological process is broken. The performed study has disclosed that immersing such a portion of the plate in the saline solution raises the liquid to the very top of the plate thus humidifying the entire plate. The saline solution consists of K2HPO4, KCL, MgSO47H2O, FeSO47H2O, NaNO3 and distilled water (Baltrėnas et al. 2014b, Baltrėnas et al. 2015a, b, c, d, Baltrėnas et al. 2016b, c, 2018, 2019). Figure 9.38 shows a pilot biofilter with straight lamellar plates and the capillary humidification system of the packing material. The plates of the biofilter are arranged to have a gap of 6  0.2 mm for passing the air polluted with volatile organic and inorganic compounds. The packing material is made of non-woven cork and wood fibre and fixed on the polymer plates. The space of 6  0.2 mm between the plates provides the capillary humidification of the packing material with no use of additional energy. Figure 9.39 shows a pilot biofilter with wavy lamellar plates and the capillary humidification system of the packing material. The biofilter is equipped with wavy lamellar plates arranged at the same distance from each other as in the biofilter with straight lamellar plates. Wavy lamellar plates have been selected to increase contact between pollutants and the packing material and to extend the contact time between the pollutant and the packing material to improve air treatment effectiveness. The packing material is made of non-woven cork and wood fibre. The efficiency of the biofilter with straight (Fig. 9.38) and wavy (Fig. 9.39) lamellar plates reaches 100 m3/h. Forty four plates are built in both biofilters. The packing material is affixed to each plate on both sides. The packing material consists of wood fibre and hydrophilic synthetic fabric making 400–500 g/m2. The measurements of a single plate are 0.8 m in length, 1.3 m in height and thickness is 10 mm.

9.7 Created and Manufactured Lamellar-Plate-Structure Pilot Biofilters Equipped. . . Fig. 9.38 The designed biofilter with straight lamellar plates and the capillary humidification system of the packing material

Fig. 9.39 The designed biofilter with wavy lamellar plates and the capillary humidification system of the packing material

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9 Technological Development from the Model to the Prototype: An Example of the. . .

The measurements of the device are 0.8 m in length, 2.0 m in height and 0.7 m wide. The gap between the plates makes 6  0.2 mm. The analysis of the packing material containing wood fibre and composite linen fabric under the straight lamellar plate and the air flow rate of 0.08 m/s between the plates showed that air treatment effectiveness of removing acetone, xylene and ammonia vapour reached 83–86%, 80–82% and 79–81%, respectively. Under the structure of the wavy lamellar plate and the removal of acetone, xylene and ammonia, eliminating the pollutant from air flow made 80–86%, 80–81% and 75–79%, respectively. When the biopacking material contained non-woven cork and wood fibre attached to straight polymeric plates, under the low aerodynamic resistance of 3.3 Pa and air flow rate between the plates of 0.08 m/s, high air treatment effectiveness was achieved and made 85.7% for removing acetone, 81.4%—for xylene and 83.5%—for ammonia vapour. A study of using the biofilter packing material containing non-woven cork and wood fibre under the air flow rate of 0.08 m/s between the plates and selected microorganisms used for the bio-destruction of pollutants disclosed that air treatment effectiveness of removing acetone vapour from the polluted air reached 89.1%, removing xylene—85.5% and removing ammonia—86.9%. When the packing material of the biofilter was attached to the wavy lamellar polymer plates, air treatment effectiveness made 90.7%, 84.4% and 84.1%, respectively. As for a study of low pollutant concentrations ranging from 5 to 100 mg/m3, the effectiveness of removing acetone from the polluted air ranged from 90.3 to 96.2%, eliminating xylene—from 8.3% to 93.5% and removing ammonia—from 91.3 to 96.5%. The employment of the biofilter with the straight inner structure and the removal of volatile organic compounds at a rate of 0.04 m/s between the plates using nonwoven cork and wood fibre as a packing material resulted in a high air treatment degree when the concentration of acetone, xylene and ammonia vapour reached 500 mg/m3 thus recording air treatment effectiveness of 88–90%. When the packing material of the biofilter was attached to the wavy lamellar polymer plates, air treatment effectiveness ranged from 90 to 93%. When removing acetone, xylene and ammonia vapour from air flow at the pollutant concentration of 700 mg/m3 under the packing material containing nonwoven cork and wood fibre and the air flow rate of 0.04 m/s, pollutant biodegradation made 80–86% for the straight structure and 83–85% for the wavy structure. When pollutant concentration was reduced to 20–100 mg/m3 in the supplied air, treatment effectiveness made 90–95% for the straight structure and 92–97% for the wavy structure. Figure 9.40 shows a pilot tubular biofilter. The plates of the biofilter are replaced with tubes arranged next to each other at an angle of 45
. Each tube contains the packing material made of biochar and wood fibre. The polluted air flows through the tubes filled with the packing material, and the microorganisms present on the packing material perform an air treatment function. The capillary humidification

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Fig. 9.40 The designed pilot tubular biofilter with the capillary humidification system of the packing material

effect occurs in the tubes of the biofilter. Water in pores rises thus humidifying the packing material simultaneously eliminating the need for additional energy. The tubular biofilter consists of 110 tubes. The efficiency of the device reaches 100 m3/h. The measurements of the tube include the inside diameter of 47 mm and a height of 1.3 m. The tubes of the biofilter form a cartridge (honeycomb). The tubes are arranged at an angle of 45
(see Fig. 9.40), the distance between the rows of the tubes is 5 mm, and the distance between the tubes in a row is 2 mm. Each tube contains the packing material made of biochar and wood fibre at a ratio of 10:1. The casing of all three biofilters is made of 5 mm technical plastic. The connection points of the casing are impermeable to air and water. The casing is resistant to acetone, xylene and ammonia vapour. The casing has the inspection openings of the packing material. The biofilter ensures the stiffness of each plate over its entire length and height. Sealing plates (Fig. 9.40) are installed at both ends of the tubes of the tubular biofilter. Each casing of the biofilter is equipped with level gauges and regulators. The air supply tube is submerged in water with biogenic elements (bio-medium) between the perforated plate and the well of the biofilter. The supplied air flow is distributed evenly over the entire volume of the packing material via 98 holes of 7 mm in diameter arranged in the air inlet duct through which air flow enters the biofilter equipped with an air flow regulator taking control over air flow from 0.05 to 0.2 m/s with a control error of 0.02 m/s. The installed air intake and exhaust

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9 Technological Development from the Model to the Prototype: An Example of the. . .

systems are resistant to chemicals (acetone, xylene and ammonia vapour) and a temperature of 120
C. The temperature of the bio-medium in the biofilter ranges from 20
C to 40
C. The installed sensors of the bio-medium temperature are resistant to the chemicals listed above. Data on biotechnology parameters are presented in a digital form. Also, the system for maintaining and regulating air flow and temperature is installed. The devices are equipped with a pH control system. Biofilters can control the relative humidity of air flow. Adjustment ranges from 45% to 99%. Measurement error is 3% under the flow humidity of 20% to 80%, and  (3 5)% for the flow humidity of 80% to 99%. Each biofilter has the installed emergency interlocking process. The biofilters are equipped with an automatic biotype level control system. The error of water level adjustment shall not exceed 10 mm. The biofilter is supplied with distilled water from a separate tank. Reservoir capacity is 50 l. Water intake and exhaust sensors are resistant to the microbiological effect of chemicals (potassium phosphate (K2HPO4), potassium chloride (KCl), magnesium sulphate (MgSO4  7H2O), ferrous sulphate (FeSO4  7H2O), sodium nitrate (NaNO3), acetone, xylene, ammonia) and variations in temperature from 10
C to 50
C. Each device generates a light warning signal when distilled water tanks (reservoirs) are empty. The monitored biofilter performance parameters are displayed in the digital form and on a computer screen. Also, at the same time, the monitored data can be stored on a hard disk by selecting scan time. While supplying pollutants having a concentration of 10–100 mg/m3 to the tubular biofilter, a rise in biofilter effectiveness made 5–10 percentage points (up to 80–85%) compared to the effectiveness of 75–80% at the pollutant concentration of 100–700 mg/m3. In addition, the packing materials containing the selected microorganisms increased acetone removal effectiveness by 16%, that of xylene by 13% and that of ammonia by 3%. In the case of the biofilter packing material containing the selected microorganisms, the removal capacity of acetone and xylene EC[g/m3/h] can be statistically reliably described by regression equation EC ¼ 0.821A + 0.007 where A[g/m3/h] is load. Having analysed different types of biochar, for testing the biofilter, pine biochar prepared at a temperature of 750
C was selected. This type of biochar is characteristic of a large BET surface area that determines the advanced micro-porous system allowing the microorganisms to adsorb pollutants and substrate. Bacteria are environmentally resistant, and therefore particularly active in the biodegradation processes of pollutants. The application of pine biochar in the biofilter and treatment with acetone and xylene caused the enlargement of the meso-pore surface affected by the newly formed meso-pores of 0.02–0.006 μm in diameter. The surface area of the sample treated with acetone made 10.29 m2/g. Following treatment with acetone, xylene and ammonia vapour, the specific pore volume of all pine biochar samples was reduced. The strongest effect was produced by ammonia vapour when specific pore volume decreased from 2.77 cm3/g to 1.86 cm3/g.

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A study of the selection and properties of the microorganisms capable of treating gas during the process of drying organic waste showed that microorganisms were most readily adapted to acetone vapour while xylene and ammonia were more difficult to tolerate. The microorganisms contained in the biopacking material were found to provide nutrients and managed to develop over a wide range of pH and temperature. A study of the pathogenicity and toxicity of the selected microorganisms to warm-blooded animals demonstrated that Bacillus subtilis B20, Aspergillus versicolor BF4, Cladosporium herbarum 7KA and Exophilia sp. BF1 were non-toxic and non-pathogenic to warm-blooded animals. Microbial communities formed during the removal process of volatiles, remained stable during the long-term test and were actively involved in the biodegradation of pollutants. The prevalence of different groups of microorganisms in the packing material of the biofilter ecosystem allows for a more effective removal of various volatiles from the environment. The obtained results are important for optimizing biological processes in industrial biofilters for eliminating various pollutants from the air. Bacteria, micromycetes and yeast were found to manage to function on the tubular air treatment biofilter containing both birch biochar (Bf6) and pine biochar (Pf6) when removing acetone, xylene and ammonia from the air employing the selected BRL microorganisms. The number of microorganisms is highly dependent on the humidification level of the packing material—the number of fungi increases when the packing material becomes wet. The selected micromycetes manage to survive in the carbon filter at both high and low concentrations of pollutants. The study of pressure distribution of three pilot biofilters resulted in low aerodynamic resistance, which made 350 Pa in the biofilter with straight lamellar plates, 450 Pa—in the biofilter with wavy lamellar plates and 450 Pa—in the tubular biofilter. Subject to the growth rate of microorganisms in pilot biofilter packing materials containing acetone, xylene and ammonia can be arranged in the following order of their biodegradability: acetone > xylene > ammonia. The optimum temperature for the growth of microorganisms in the biofilter packing materials containing acetone, xylene and ammonia was 28
C. As for the packing materials of pilot biofilters when removing acetone, xylene and ammonia under the optimal air temperature of 28
C, the achieved air treatment effectiveness made 85–92%, 83–88% and 83–86%, respectively. The maximum air treatment effectiveness was determined in the biofilter with wavy lamellar plates when removing acetone and reached 93%. The analysis of odour intensity in three pilot biofilters disclosed air flow discharge was equal to 100 m3/h, pollutant concentration was 300 mg/m3, acetone odour intensity reached 5–6 OUE/m3 before treatment and 3 OUE/m3 after treatment, xylene odour intensity reached 6 OUE/m3 before treatment and 3–4 OUE/m3 after treatment and ammonia odour intensity reached 7 OUE/m3 before treatment and 3 OUE/m3 after treatment. The intensity of the odour depends on the type of the pollutant. The obtained data show that the biofilters of the above-presented three

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structures manage to remove odours from air flow, and therefore the created and used equipment does not adversely affect air quality. All three tested pilot biofilters are suitable for removing volatile organic and inorganic compounds from the polluted air, which is evidenced by an air treatment rate exceeding 85%. The types of the packing material employed in the biofilters were appropriate for the development of microorganisms the population of which included micromycetes—107–109 cfu/g, yeast—107–1010 cfu/g and bacteria 108– 1010 cfu/g. The physical examination of biofilter packing materials demonstrated that damage to the surface structure of biochar rose along with an increase in processing time. Following treatment with xylene and ammonia pollutants, damage to the surface layer of biochar was observed thus counting many small fragments of 10–50 μm in length. The porosity of untreated biochar reached 62.9%. The surface area of pores made 6.15 m2/g and was significantly smaller than that of the treated samples. A similar situation was observed in the case of the specific pore volume. The effect of xylene highly increased the surface area of biochar pores up to 20.39 m2/g, which should be considered an exceptional point. This can be explained by the effect of xylene on residual organic compounds during dissolution and the formation of an additional structure of micropores. An increase in working time has no effect on the structure of non-woven cork (NWC). However, a longer processing time results in the accumulation of a brown new material available on the biofilter with both straight and lamellar plates containing NWC. Advancements in the structures of laboratory biofilters lead to producing three layouts of pilot biofilters reaching the effectiveness of 100 m3/h. The measurements of each device were 0.7  0.8  2.0 m. The layouts of pilot biofilters had the installed air flow inlets and outlets as well as the aqueous medium intake and exhaust system. The sensors and regulators of air flow and aqueous medium temperature, humidity, speed, pH, water level, etc. were installed. Each biofilter has a unique internal design. The plate structure of the biofilter is made of tubes arranged next to each other at an angle of 45
. Each tube contains the packing material of biochar and wood fibre. The polluted air flows through the tubes filled with the packing material the microorganisms on which perform an air treatment function. The capillary humidification effect occurs in the tubes of the biofilter. Water in pores rises thus humidifying the packing material simultaneously eliminating the need for additional energy. These types of biofilters can be used in adhesive, solvent, paint, varnishes, cosmetics, rubber production and processing industries, printing houses, sewage treatment plants, livestock farms, petroleum product manufacturing, etc. The biofilters are recommended for removing volatile organic and inorganic compounds (xylene represents a group of aromatic hydrocarbons, ammonia—a group of volatile inorganic compounds and acetone—a group of ketones) from the air at the pollutant concentration of 300  25 mg/m3, an air flow discharge of 100 m3/h, an air flow rate of 0.16 m/s between plates and tubes and an air flow temperature of 28
C using the packing material containing non-woven cork, wood fibre or biochar. In this case, air

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treatment effectiveness reaches approximately 90%, and the obtained aerodynamic resistance makes up to 450 Pa. For removing acetone, xylene and ammonia through different packing materials of the biofilter, the tested microorganisms selected for pollutant biodegradation in the biofilters, including Bacillus subtilis 20, Aspergillus versicolor BF4, Cladosporium herbarum 7KA, Exophiala jeanselmei BF1, are recommended. The microorganisms are non-pathogenic and non-toxic to warm-blooded animals. The use of biofilters under production conditions for maximum results should assist in conducting the assessment of the viability of the selected microorganisms present on biofilters at least twice a year and additionally insert microorganisms if required (Baltrėnas et al. 2015a).

Conclusions

The global stability crisis of ecosystems manifests itself in the growth of their technogenic load and a deteriorated quality of life, particularly in the concentrated centres of urbanization and industry. With a rise in both human population and gross domestic product by approximately 72% and 225%, respectively, the global extraction of chemical elements increased by over 75%. An upturn in the extraction of chemical elements increases the load of contaminants, which results in the expansion of the urban contaminant footprint. If not avoided, contaminants can only be stabilized by reducing their migration flows using the means of natural (biogeochemical) and engineered barriers. Trees represent the highest biomass share of the terrestrial living matter that governs the mobility of contaminants and can be employed in various types of barriers to reducing the spread of contaminants in the environment. The first sustainability level of environmental protection technologies rely on the function of the biosphere to immobilize and accumulate pollutants and to indicate the quality of the environment. The operating technologies are based on the naturally or semi-naturally occurring action of geochemical and biogeochemical barriers. The deposition media acting as a containment of pollutants are a component of such technologies (barriers). These media include the soil, snow cover, rainfall, tree bark, lichen, mosses, river and lake sediments. To indicate the quality of the environment applied, these technologies are characterized by the assessment of pollution impact on the biosphere at the ecosystem level, the integrity of synergistic and antagonistic traits and the comprehensiveness of impact (influence) determination. For example, considering the accumulation of metals in natural components and the response of the most sensitive natural objects, the studied area in the vicinity of the biggest oil refinery in the Baltic states could be classified as that of weak to moderate pollution taking into account the results of the investigated depositing media and the technological transformation of their chemical composition. Technology may assist in assessing the spread of the technogenically affected area. The most noticeable increase in metal concentrations found in natural objects is observed at a

© Springer Nature Switzerland AG 2020 P. Baltrėnas, E. Baltrėnaitė, Sustainable Environmental Protection Technologies, https://doi.org/10.1007/978-3-030-47725-7

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distance of up to 3.5 km in the downwind and up to 1 km in the upwind area from the plant. A sustainable example of environmental engineering systems is represented by phytotechnologies. Popular gaseous plant T. caerulescens was able to accumulate Cu up to 32 mg/kg of d.w. (dry weight). Pb accumulation reached 14 mg/kg of d.w. Plants accumulated the highest concentrations of Zn compared with other three metals thus reaching 1720 mg/kg of root dry weight during the second month of vegetation. Cd had the lowest amounts accumulated by plants and reached 1.85 mg/ kg of root dry weight. The analysis of metallic elements in plants shows that the highest Cu concentration was found in plant roots as acropetal translocation. Mostly all Pb was accumulated in plant shoots, which is basipetal metal translocation. However, the accumulated concentration was dropping down from the first to the third months. The highest values of Zn were found in plant shoots and made 757 mg/ kg of d.w., while the highest concentrations of Cd were established in the roots of control plants as acropetal translocation. The estimated metal removal shows lower elimination capacity compared with the simulation results of the Phyto-DSS model. The obtained results show that all available Cd can be removed within 5 annual croppings, while to remediate Zn, 13 croppings are required. To remediate Cu and Pb using T. caerulescens should be economically unviable. The dynamic factor method was developed to evaluate the effect of sustainable technologies. In determining the influence of various objects on the environment and their risks to environmental quality, the data obtained using the dynamic bioaccumulation factor are more informative than the direct evaluation of the concentration of metallic elements in plants because they show the scope of biogeochemical uptake compared to the concentration of metallic elements in the soil. Data on the concentration of metallic elements in the plant or its concentration coefficient are not sufficient because they do not link the concentration of metallic elements to one of the main media where metallic elements are taken from, i.e. soil. Moreover, the dynamic factor in bioaccumulation helps with defining the chemical and biogeochemical characteristics of metallic elements. The second sustainability level of the environmental protection technologies is related to the use of sustainable natural materials in environmental engineering systems. The focus is provided on the use of such materials in waste management, the stabilization of the contaminated soil and the removal of contaminants from the aqueous media. Compared to the limits set in the guidelines of EBC (EBC European Biochar Certificate 2015), the types of feedstock that showed high trace metal concentrations (e.g. Cu, Cr and Zn in DSS and Cu in LG) originated from BC with trace metal concentrations above the limits (i.e. Cu, Cr and Zn in BCDSS and Cu in BCLG). Furthermore, there could be a risk for an excessive leaching of Ni from BC produced from lignin or sewage sludge. Wood chips-derived (from non-contaminated sites) BC can be considered for water or land application with no concern for introducing the excessive amounts of trace metals in the environment. When designing pyrolysis treatment for producing BC from biodegradable waste, the most suitable temperature depending on the targeted trace metals, the type of biodegradable waste and the purpose of BC production should be carefully

Conclusions

543

evaluated. For example, biochar having elevated concentrations contains metals reporting high concentrations in sewage sludge and characteristic of the investigated industry. The concentrations of Cr and Pb established in the biochar of sewage sludge used in paper industry were found to be approximately 1.6–2 times higher and in the case of Cd—3 times lower than those in the biochar of sewage sludge employed in leather industry. The stability of heavy metals increased in the following order: Cr > Cd > Pb for leather and Cr > Pb > Cd for paper processing industry. It is likely that under these conditions, the properties of individual metal mobility may also appear prominently. If BC is intended for water application, including filter media, the amount of DOC that may be emitted in surface water as a result of BC release should be estimated considering BC production (e.g. pyrolysis temperatures and the types of feedstock) and chemical parameters (e.g. pH and DOC concentration) considering the type of water BC would be exposed to. At the pyrolysis temperature of 450
C, all analysed trace metals showed the same temperature trend that varied depending on feedstock thus significantly increasing concentration in BCWC (up to 191%) and BCDSS (up to 288%) and significantly decreasing BCLG (by as much as 46%). At the pyrolysis temperature of 700
C, the temperature trend in trace metals varied depending on feedstock. In all tested types of BC, trace metals Ni (up to 135%), Pb (up to 248%) and Zn (up to 283%) increased significantly, whereas the total Cr concentrations decreased drastically (by as much as 69%) compared to respective feedstock. Trace metals Cd and Cu did not show a clear temperature trend and increasing or decreasing concentrations subject to feedstock. The most suitable pyrolysis temperature for reducing trace metal leachability and bioavailability (450 or 700
C) depends on the trace metal considered. Regardless of pyrolysis temperature, trace metals Cr and Ni were not prone to leaching or present in bioavailable forms in BCWC, BCLG and BCDSS. Thus, a temperature of 450
C was effective in stabilizing Cr and Ni in the analysed BC. As for tested BC, an increase in pyrolysis temperature made trace metals Zn and Cu more stable in the char matrix, decreasing in bioavailable fractions, hindering Zn leachability and decreasing Cu leachability to less than 1% of the total Cu concentration. Trace metals Cd and Pb did not show a clear temperature trend and an increase or a decrease in bioavailable or leachable fractions depending on feedstock. Along with a rise in pyrolysis temperature, the bioavailable fraction of Cd and Pb dropped, whereas the leachable fractions of these trace metals increased in BCWC and BCLG. An opposite trend was observed for Cd and Pb in BCDSS increasing in bioavailable fractions and decreasing in leachability with a reduction in pyrolysis temperature. The conducted research showed that the formation of mobile metal forms in the eluates leached from the polluted soil and improved applying two types of biochar (PB450 and PB700) at three different ratios (1/5, 1/10 1/20) was simulated with reference to the WHAM/Model VII program. According to simulation results, Ni, Cd and Zn had the highest ratio (97–100%) of free metal ions to the dissolved fraction in all research groups, whereas Cu and Pb made (58–85%) and (63–90%),

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respectively. A comparison of all research groups showed that free metal ions were the predominant form of Ni, Cd and Zn in the soil solution. The assessment of an incubation assay disclosed similarly high Cd retention efficiency (>85%) for both types of biochar, whereas higher Zn retention (78%, 1/10) was more effective at lower temperature-produced biochar (450
C) that was effective enough at immobilizing Cu (76%, 1/20). For retaining this element in the long term under a higher level of the Cd-polluted soil, both types of biochar could be used. However, in the case of the multicomponent contaminated soil containing Cd, Zn, Cu and Pb, type PB450 rather PB700 than could be considered a more appropriate sorption product due to the higher immobilization effectiveness of these elements. The assessment of the results of leaching study disclosed that pine wood biochar (PB450) best retained Pb (retention efficiency up to 99.57%, 1/5) and Cu (retention efficiency up to 93%, 1/5) in the PTE-contaminated soil. As for other elements (Zn, Cr, Cd and Ni) contained in the soil, this type of biochar had no positive effect. Meanwhile, in the case of another type of biochar (PB700), PTE retention efficiency takes the following order: Pb > Cu > Zn > Cr. This type of biochar best retained Pb (up to 99.63%), Cu (up to 49.34%), Zn (up to 37.56%) and a small amount of Cr (15.15%). Under the soil highly contaminated with Pb and Cu, PB450 could be considered a more appropriate sorption product in the short term. In the case of the soil polluted with a number of elements (Pb, Cu, Zn and Cr), the PB700 type could be accepted a more suitable option for PTE immobilization. As for the assessment of leaching PTE from the two types of the sleepers of the pyrogenic carbonated product (PSB450 and PSB700), the leached amounts of all six tested PTEs (Zn, Cr, Ni, Cu, Cd and Pb) are not significant. Pollutant leaching ranges from 0.07 to 11.29% compared to the initial content of the elements found in pyrogenic products. Therefore, with respect to the above-mentioned PTEs, the pyrogenic product made of wooden sleepers does not pose a risk to the quality of the environment under soil protection legislation. On the other hand, the pine carbonating product produced at a temperature of 700
C had a negative or zero effect on the fresh and dry biomass of the sown oats that decreased to 34% for fresh and 12% for dry weight compared to the control group. Plant-specific phytotoxicity and its response to volatile and leachable compounds from fresh biochar could explain zero and negative plant-growth response to the addition of biochar to the soil in this study. Adding pine biochar to the soil changed PTE distribution in plants, i.e. the concentration of PTEs (Zn, Cr, Ni, Cu, Cd) in the plants grown in the improved soil decreased compared to those from the non-improved soil. However, the concentration of Pb increased possibly because the metal accumulates in oats in large quantities due to soil acidification, which leads to a gradual increase in the concentration of Pb2+ ions. Silver birch (Betula pendula) and Scots pine (Pinus sylvestris L.) biochar were characterized for adsorption potential. The determined porosity of biochar samples varied in the range of 73–79%. The total carbon of all biochar samples was determined to make at least 95%. Scots pine (Pinus sylvestris L.) biochar produced under fast pyrolysis conditions had the largest specific surface area (10 m²/g). Silver birch (Betula pendula) biochar produced under fast pyrolysis conditions had the

Conclusions

545

highest value of cation exchange capacity (6 cmolc/kg). Due to the advantageous physical and chemical characteristics of biochar, the study of adsorption capacity showed that more efficient was Silver birch (Betula pendula) biochar, which could be considered a possible adsorbent for the removal of heavy metal ions at low concentrations. Taking into account short contact time (15–20 s) and the applied flow rate (0.05–0.07 L/s) of the leaching solution, the high efficiency of removing heavy metal ions at a maximum of 35–37% on Silver birch (Betula pendula) biochar was reached. The adsorption efficiency of both types of biochar decreased with an increase in the initial concentration of heavy metal ions. The adsorption of heavy metals ions rose when the dosage of the adsorbent increased. The capacity and intensity of biochar that adsorbed heavy metal ions from the leaching solution have been modelled applying Freundlich and Redlich–Peterson isotherms, which reflected the heterogeneous properties of the surfaces and the favourable adsorption process. The adsorption capacity of Silver birch (Betula pendula) biochar (1– 107 mg/g) was by 4–26% higher than that of Scots pine (Pinus sylvestris L.) biochar (2–128 mg/g). The maximum adsorption capacity of Cd(II), Pb(II), Cu(II) and Zn (II) made 5.4, 4.5, 129 and 107 mg/g, respectively. The selectivity of heavy metal ions frequently was Zn > Cd > Pb > Cu. For evaluating the adsorption capacity of both types of biochar, experimental results showed the reliability of both Freundlich and Redlich–Peterson adsorption isotherms (average of statistical reliability R2 ¼ 0.96). However, the extended Freundlich adsorption equation described the adsorption process more accurately than the extended Redlich–Peterson equations. Due to statistical reliability (R2 ¼ 0.96), the extended Freundlich expressions can be recommended for evaluating the adsorption of heavy metals on Silver birch (Betula pendula) and Scots pine (Pinus sylvestris L.) biochar. The extended Freundlich model can be a reasonable choice for modelling the adsorption of Cd(II), Pb(II), Cu(II) and Zn(II) ions as well as other heavy metal ions in the stormwater runoff stream. The concentrations of heavy metals in biochar samples before and after the application of adsorption satisfied the premium thresholds (Pb < 120 g/t; Cd < 1 g/t; Cu < 100 g/t; Zn < 400 g/t) defined by the European Biochar Certificate. Thus, biochar could be re-applied as an adsorbent in the filtration system or reused for other purposes such as improvements to the agricultural soil, the rehabilitation of the soil in the contaminated sites and energy production. In logging sites, around 2.5 million m3/year of wood waste, including branches, chips, barks of trees, (70% are left to rot) are formed, which can be potentially used as a raw material for producing biochar. 35–37% removal efficiency of heavy metal ions on Silver birch (Betula pendula) biochar can be considered when designing facilities for the treatment of metal-polluted water. The third sustainability level includes the components ensuring the environmental sustainability of environmental engineering systems. This level is described by considering a biofiltration system as an example. The currently applied structure and design of air treatment biofilters occupy much space and have high energy consumption for the humidification of packing materials and high aerodynamic resistance. Biofilters do not contain long-lasting packing materials and form anaerobic zones reducing the activity of microorganisms certain types of which manage to

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decompose only specific types of volatile organic and inorganic compounds. Taking into account the above-presented shortcomings, the study focuses on the applied research of the structural features of biofilters, looks at the physical, aerodynamic and microbiological processes of the packing materials, provides a new knowledge of the physical, microbiological and sorption properties of biofilter packing materials, evaluates the humidity of the packing materials contained in the plate-type biofilters and the impact of gas flow permeability on air treatment efficiency, assesses the aerodynamic and physical properties of the packing material, explores the properties of the selected microorganisms (bacteria, microscopic fungi, yeast) capable of removing volatile organic and inorganic compounds, examines the effect of temperature and other physical-chemical parameters on the activity of the microorganisms and demonstrates the influence of the selected microorganisms on the pathogenicity and toxicity of warm-blooded animals. The book also presents the developed and manufactured laboratory biofilter benches of three different plate structures equipped with heating and humidification systems and a facility for changing the packing material. The structure of the first laboratory biofilter is made of straight lamellar plates, the second consists of wavy lamellar plates and the third contains tubes. The structures have been selected to improve aerodynamic, sorption and microbiological properties. The study discusses the selection of packing materials. Sampling was performed using 25 different materials. The criteria for evaluating materials included relative and absolute humidity, porosity, density, and capillary humidification as the basic property and the microscopic structure of each material. Subject to the displayed properties, four most appropriate types of the packing material, including non-woven cork (NWC), heat-treated wood fibre (WF), linen fabric (LF) and biochar, were preferred to achieve biological air treatment and capillary humidification effect. The effect of the gas flow permeability of the humidified packing material on air purification effectiveness has been evaluated because moisture is required for microbiological processes taking place in the biofilters with the capillary humidification system of the packing material the humidity of which in the biofilters containing straight and wavy lamellar plates reached from 60 to 70% and that of tubular biofilters ranged from 50 to 55%. The dependence of the aerodynamic resistance of biofilter packing materials on the surface shape of the plates and the air flow rate supplied through the biofilter was determined. The use of non-woven cork and wood fibre as a biofilter packing material attached to polymeric straight lamellar plates at an air flow rate of 0.08 m/ s between the plates has resulted in the aerodynamic resistance of 3.3 Pa. The employment of wavy lamellar plates made 6.8 Pa. The highest treatment effectiveness of 97% was determined in laboratory platetype biofilters removing volatile organic and inorganic compounds from the air. The effectiveness was achieved applying a laboratory biofilter bench containing wavy lamellar plates the surface of which was covered with non-woven cork (NWC) and wood fibre (WF) and supplied with acetone vapor-contaminated air at a rate of 0.08 m/s. The effectiveness of the employed straight lamellar plates achieved 89%

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and that of the tubular structure reached 87% when biofilter tubes were filled with a mixture of biochar and wood fibre (WF). The study has analysed the dependence of odours on the structures of laboratory biofilter benches, the concentrations of pollutants supplied to biofilters and the types of pollutants. Also, trends towards a decrease in odour intensity before and after treatment in the biofilters of all structures have been investigated. A greater reduction between 5 and 10% in odours was found using the structure of the biofilter with wavy lamellar plates. When supplying volatile organic and inorganic compounds through biofilters, odour concentrations were within margin of error and made 8 OUE/m3. For selecting the types of microorganisms (bacteria, microscopic fungi and yeast), the most effective strains of microorganisms capable of decomposing volatile organic and inorganic compounds have been identified. The bacteria Bacillus subtilis B20, Pseudomonas (P. aeruginosa, P. putida), Staphylococcus (S. aureus), Rhodococcus sp., Burkholderia cepacia, micromycetes Aspergillus versicolor BF4, Cladosporium herbarum 7KA, Myrothecium verrucaria and the yeast Exophilia sp. BF1 have been found to decompose the supplied pollutants in the most effective way. The insertion of the selected microorganisms into the packing material of the biofilter increased treatment efficiency up to 8%. The selected cultures of microorganisms manage to decompose volatile organic and inorganic pollutants acetone, xylene and ammonia. The number of microorganisms has been found to range between 1.6107 and 3.71011 CFU/g. The study of the pathogenicity and toxicity of the selected microorganisms to warm-blooded animals have shown that microorganisms are non-toxic and non-pathogenic to warm-blooded animals. The assessment of temperature effect and other physical-chemical parameters on the activity of biofilter microorganisms demonstrates that both natural and selected microorganisms can develop in the packing materials of laboratory biofilter benches within a wide range of pH and temperature. The employment of the capillary humidification system helps microorganisms with providing nutrients. Microorganisms have most easily adapted when supplying acetone and xylene vapour through the packing material. The highest activity of microorganisms has been established in the bio-medium under a temperature of 25–30 ºC and the pH of 6.5–8.5. The book introduces three air treatment pilot biofilters having different plate structures designed and manufactured by one of the authors Pranas Baltrėnas and his colleagues and intended for removing volatile organic and inorganic compounds from the air. The structure of the first pilot biofilter is made of straight lamellar plates, the second is produced from wavy lamellar plates and the third contains tubes. The efficiency of each pilot biofilter reaches 100 m3/h. The manufactured pilot biofilters and similar equipment applied in the laboratory have been tested under the same environmental conditions. The low aerodynamic resistance of the packing materials of three pilot biofilters having different plate-type modifications has been determined. The aerodynamic resistance of the pilot biofilter with straight lamellar plates made 350 Pa and that of the pilot biofilter with straight lamellar plates and the pilot tubular biofilter was the same and amounted to 450 Pa.

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The study evaluated air treatment effectiveness of pilot biofilters under the same environmental conditions as those created for the benches of laboratory biofilters and found that air treatment effectiveness of pilot biofilters was 85–92%, 83–88% and 83–86% when supplying packing materials acetone, xylene and ammonia, respectively. • The highest air treatment effectiveness reached 93% and was identified in the pilot biofilter with wavy lamellar plates supplying the packing material with the air contaminated with acetone. Depending on the growth rate of the microorganisms present in the packing materials of pilot biofilter and contaminated with acetone, xylene and ammonia, the following order of biodegradability can be arranged: acetone > xylene > ammonia. 28 ºC is the optimum temperature mode for the growth of microorganisms in the biofilter packing materials containing acetone, xylene and ammonia. • Odour intensity was determined in pilot biofilters under the air flow discharge of 100 m3/h and the pollutant concentration of 300 mg/m3. Acetone odour intensity was 5–6 OUE/m3 before and 3 OUE/m3 after treatment, xylene odour intensity made 6 OUE/m3 before and 3–4 OUE/m3 after treatment and ammonia odour intensity reached 7 OUE/m3 before and 3–4 OUE/m3 after treatment. Odour intensity is subject to the type of the pollutant. The obtained data demonstrate that the pilot biofilters of three structures manage to remove organic and inorganic pollutants and odours from air flow, and therefore the created and used equipment has no adverse effect on air quality. All three types of the pilot biofilter are suitable for removing volatile organic and inorganic compounds from the polluted air, which is evidenced by the air purification rate exceeding 85% and the employed packing material appropriate for the development of microorganisms the population of which makes 107–109 CFU/g for micromycetes, 107–1010 CFU/ g for yeast and 108–1010 CFU/g for bacteria. • The analysed physical parameters of packing materials for pilot biofilters have disclosed that damage to the surface structure of biochar rises along with an increase in processing time. Following treatment with xylene and ammonia contaminants, damage to the surface layer of biochar is observed, the surface becomes uneven, and many fine fragments 10–50 μm in length appear on the surface. The porosity of untreated biochar reaches 63% and particularly the surface area of pores (6 m2/g) is significantly smaller than that of the treated samples. The specific pore volume is also lower. The effect of xylene markedly increases the surface area of biochar pores up to 20 m2/g and is considered exceptional, which can be explained by the effect of xylene on residual organic compounds by dissolving them and forming an additional micropore structure. An increase in the operation time of non-woven cork (NWC) has no effect on its structure that remains unchanged. However, a rise in the processing time results in the accumulation of brown new materials found on NWC contained in the biofilters with both straight and wavy lamellar plates. • The study provides information on physical parameters for each pilot biofilter. The length, width and height are 800, 700 and 2000 mm, respectively. The

Conclusions

•

•

•

•

549

biofilters are equipped with air flow inlet and outlet as well as aqueous medium intake and exhaust systems. The sensors and regulators of air flow temperature, humidity, speed, aqueous medium temperature and pH as well as water level sensors are installed. The developed pilot biofilters can be successfully applied in industries such as the production and processing of adhesives, solvents, paint, varnishes, cosmetics, rubber, in printing and sewage treatment plants, livestock farms, for manufacturing oil products and in the service sector, where volatile organic and inorganic compounds embracing acetone, xylene and ammonia are emitted into the ambient air. For removing volatile organic and inorganic compounds, the suggested pilot biofilters are distinguished by their structure and high air treatment effectiveness. A pilot biofilter with straight lamellar plates. The plates of the biofilter are arranged to have the gaps of 6  0.2 mm used for transferring the air contaminated with volatile organic and inorganic compounds. The packing material fixed on the polymer plates is made of non-woven cork and wood fibre. The distance of 6  0.2 mm between the plates is maintained for the purpose of the capillary humidification of the packing material without the use of additional energy. Under the initial pollutant concentration of 300 mg/m3 supplied to the biofilter, the effectiveness of removing acetone vapour from the air through the biofilter with straight lamellar plates makes 88%, eliminating xylene—86% and removing ammonia—84%. A pilot biofilter with wavy lamellar plates. The biofilter contains wavy lamellar plates arranged at the same distance from each other as in the biofilter with straight lamellar plates. The wavy structure of the designed plates allows prolonging contact time between the pollutant and the packing material thus improving air treatment effectiveness. Non-woven cork and wood fibre are used as a packing material. Under the initial pollutant concentration of 300 mg/m3 supplied to the biofilter, the effectiveness of removing acetone vapour from the air through the biofilter with wavy lamellar plates makes 92%, eliminating xylene— 88% and removing ammonia—86%. A pilot tubular biofilter. The plates of the biofilter are made of tubes arranged side by side at an angle of 45
. Each tube contains a packing material comprising biochar and wood fibre. The polluted air flows through the tubes filled with the packing material, and the microorganisms present on the packing material perform the air purification function. The capillary humidification effect can be observed in the tubes of the biofilter. Water rises in the pores of the packing material thus humidifying it with no need for extra energy. Under the initial pollutant concentration of 300 mg/m3 supplied to the biofilter, the effectiveness of removing acetone vapour from the air through the tubular biofilter makes 83%, eliminating xylene—83% and removing ammonia—81%. For the biodegradation of gaseous organic and inorganic compounds, including acetone, xylene and ammonia, using the selected microorganisms Bacillus subtilis 20, Aspergillus versicolor BF4, Cladosporium herbarum 7KA and Exophiala jeanselmei BF1, which are non-pathogenic and non-toxic to animals, is recommended.

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• Pilot biofilters are equipped with the performance management and monitoring system. The adapted software for taking control and monitoring parameters for pilot biofilters provides a possibility of handling air flow discharge and rate as well as the temperature, humidity and pH of the aqueous medium.

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Index

A Absolute humidity, 271, 273, 283–285, 288, 289, 357, 372, 489 Absorbed humidity, 51, 262, 487 Absorption, 12, 13, 21, 50, 82, 88, 97, 104, 105, 116, 118, 120, 163, 192, 205, 219, 226–228, 260, 272, 273, 287, 406, 505 Absorption acceleration, 227 Accumulation, 3, 9, 10, 12–14, 23, 24, 33, 40, 42, 43, 57, 64, 74, 78–80, 85, 110, 146, 212, 219, 538 Acetone, 187, 188, 194, 207, 216, 217, 220, 226, 261, 262, 296–305, 307–319, 321–325, 329, 333, 335, 337, 339–343, 345, 349, 352, 354, 359, 360, 370, 372, 373, 375, 378–381, 383, 384, 386–389, 391, 393–398, 400–414, 416–431, 434–437, 451–458, 460–463, 465–470, 473–476, 478, 481, 487, 489–491, 494, 496–498, 500–502, 508–513, 515, 516, 518–524, 526–531, 534–539 Acetone removal, 405, 408, 453, 454, 458, 459, 461, 465, 466, 468, 474, 476, 477, 492, 508, 510, 516, 519, 522, 523, 536 Acid solutions, 166, 273, 434, 506 Acropetal, 25, 82, 84, 85 Actinomycetes, 261 Activated biopacking material, 331, 389 Activated carbon, 131, 136, 164, 192, 194, 206–212, 217, 283, 284, 286, 288–290, 348, 389, 489 Activated water, 197, 199, 486 Acute dose, 42 Adaptation period, 463, 508–512, 514–517, 519

Adsorption, 33, 34, 131, 136, 145, 149–160, 162–185, 188, 192, 195, 205, 208–212, 214, 260, 348, 406, 505 Adsorption equilibrium, 157, 170–183 Advection, 18, 161, 188 Aerobes, 502 Aerodynamic parameters, 494–504 Aerodynamic resistance, 196, 198, 201, 203, 206, 207, 220–222, 239–241, 253, 258, 267, 283, 359–373, 493, 494, 504, 505, 531, 534, 537, 539 Aerogenic, 48, 52–60, 62–75 Air flow inlets, 305, 307, 312, 315, 319, 361, 493, 538 Air flow outlet, 204, 308, 501 Air flow parameters, 235–238, 240, 492 Air flow permeability, 373, 389, 493 Air flow rates, 221, 222, 230, 234, 235, 238, 240, 245, 248, 266–268, 271, 280, 282, 308, 311, 321, 325, 327, 330, 355, 356, 363–365, 367–388, 390, 392, 394–396, 398, 399, 401, 403, 410, 411, 415, 483, 485, 486, 488, 491–493, 519, 521, 534, 538 Air flows, 7, 39, 194, 197–199, 201, 203–205, 221, 230, 231, 233–249, 253–257, 260, 266, 268, 269, 280, 282, 297–301, 303, 305, 307–309, 311, 312, 315–317, 319, 321, 322, 324, 325, 359, 363, 365, 367, 369–371, 374, 376, 377, 379, 380, 382, 385, 387, 389, 397, 415, 483, 485–488, 490–494, 498, 499, 501–503, 519, 520, 522, 523, 525, 528, 530, 534–538

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640 Air treatment effectiveness, 190, 205–207, 214, 219, 357, 388–411, 491, 494, 501, 519–527, 531, 532, 534, 537, 538 Airways, 14 Ammonia, 187, 188, 194, 207, 213, 217, 220, 261, 262, 296–303, 305–325, 329, 333, 334, 336–347, 349, 354, 359, 360, 370, 372, 373, 375, 376, 378–381, 383, 384, 386–414, 416, 418–422, 424–427, 429–431, 436, 437, 451–463, 465–470, 474–476, 478, 479, 481, 487, 489–491, 494, 496–498, 501, 502, 508, 511–515, 517–519, 521, 524, 526–531, 534–539 Ammonia removal, 194, 406, 453, 454, 458, 461, 463, 465, 467, 469, 470, 474, 476, 481, 492, 510, 511, 513, 516, 517 Analyser, 269, 271, 272, 488, 492 Annual rings, 49, 50 Aqueous medium, 25, 143–186, 347, 348, 368, 485, 486, 488, 492, 494, 501, 538 Arabidopsis halleri, 77, 79 Arabidopsis thaliana, 76, 78, 79 Atomic absorption spectrometer, 272

B Bacteria, 42, 51, 101, 189, 194, 214–216, 218–220, 224, 261, 277, 321, 328, 334, 338, 341, 346, 360, 373, 391, 398, 406, 410, 433–437, 442–444, 447, 448, 450, 452–466, 468–477, 479–482, 500, 506–526, 536–538 Bacterium strains, 189, 442, 447 Bacterium urease, 437 Bark, 12–14, 39, 40, 49, 50, 53, 54, 65, 66, 98, 99, 102, 125, 131, 139–141, 192, 195, 201, 203, 205, 206, 260 Barometric height, 265 Basipetal, 25, 82, 84 Batch tests, 112, 116, 118–120 Bioaccumulation, 24, 25, 27, 43, 54, 73–75, 542 Bioavailability, 10–12, 24, 26, 27, 43, 80, 81, 93, 121, 135, 145, 146, 150, 160, 161, 163 Biochar, 26, 27, 93–97, 99–141, 143, 156–158, 160, 162–186, 195, 259, 261, 262, 271–273, 329, 348, 349, 352, 354–357, 359, 372, 409, 412, 417, 471, 473–482, 485, 486, 488, 489, 494–497, 502, 514–518, 524, 525, 534–538 Biochar ash content, 105, 273 Biochar pores, 261, 497, 538

Index Biochemical, 11, 12, 15, 16, 215, 260, 334, 338, 341, 346 Biochemical reactions, 219, 328, 433 Biofilms, 188, 195–198, 201, 214, 215, 217, 224–226, 260, 331, 361, 394, 401, 416, 532 Biofilter-adsorber, 281, 282, 485, 489 Biofilter parameters, 331, 332, 485 Biofilters, 54, 68, 189–207, 212–228, 230, 231, 233, 236–238, 240–242, 245, 246, 253, 256–262, 264–268, 271, 277–283, 285, 288, 289, 292, 296–341, 343, 344, 346–349, 354–357, 359–406, 408–418, 420, 424, 426, 428, 429, 433–449, 451, 453, 454, 456, 458–463, 465–471, 473–494, 496–498, 500–506, 508, 511–539 Biofiltration, 187, 188, 190, 192, 201, 214–217, 224, 225, 230, 231, 233–238, 240–255, 257, 258, 277, 285, 433, 503, 522, 523 Biofiltration systems, 33, 194, 259–357, 359–431, 433, 483–539 Biofiltration time, 380 Biogenic elements, 195, 201, 205, 225, 260, 296, 339, 490, 500, 532, 535 Biogeochemical barriers, 39–91 Bioindication, 23, 40–42 Biological air treatment, 187–193, 195–201, 203, 205, 206, 219–229, 259, 260, 262, 282–357, 359–389, 394, 397, 398, 401, 412–431, 434, 483, 485, 531, 532 Biomass, 1, 3, 43, 75, 77, 83, 84, 86, 88, 90, 95, 96, 101–104, 108, 125, 126, 135, 136, 163–165, 167, 169, 185, 188, 195, 199, 215, 219, 222, 224, 225, 261 Bio-medium, 189, 190, 195, 203, 225, 296, 396–398, 403, 500, 535, 536 Biomonitoring, 23, 40–42, 49 Biopacking materials, 192, 197, 219, 242, 259, 260, 287–290, 296–301, 303, 305, 307, 309, 311–319, 321, 322, 327, 331, 333, 337, 339, 342, 345, 359–361, 364, 366, 371–373, 377, 379, 380, 382, 390, 392, 394–399, 401, 403, 404, 408, 412, 414, 416–421, 423, 428, 437–440, 442, 443, 463, 473, 483, 485, 524, 530, 532, 534, 537 Bioreactors, 196, 197, 214 Bioscrubbers, 196, 199, 200 Biosphere, 1, 3, 32, 33, 39, 40, 43, 44, 53, 95, 144 Biotechnologies, 143, 187–258, 531, 536

Index Birch biochar, 471–473, 479, 481, 482, 494–497, 537 Birch wood fibre, 293, 332, 341 Bituminized coal, 5 Brassicaceae, 76–78 Buxes, 506, 507

C Calibration gas, 270 Capillary humidification, 283, 287, 288, 290, 294, 296, 303, 305, 307, 310–312, 318, 319, 322, 357, 489, 490, 532, 534, 538 Capillary humidification system, 259, 261, 278, 279, 283, 329, 357, 359, 372, 412, 484, 485, 487, 531–539 Carbon cycle, 94–96, 109, 124 Carbon footprint, 33, 93–97, 99–103 Carbonization, 112 Carbon monoxide, 18, 54, 68, 264 Carboxymethylcellulose (CMC), 438–440, 443 Catabolism, 224 Cation exchange capacity (CEC), 104, 128, 151, 166, 167, 169 Chemical footprint, 30, 31 Chronic doses, 42 Circular rings, 246 Clarke, 4, 5 Column test, 112 Composts, 108, 113, 121, 132, 192, 194, 195, 201, 203, 205–207, 216, 260, 323, 389, 405, 408, 409 Concentration coefficients, 54, 74, 75 Concentric circles, 243 Condenser, 276, 277 Conglomerates, 214, 228, 229 Contamination factor, 22, 23 Contamination footprint, 1, 32 Cross-section of the biopacking material, 377, 379, 380, 385, 387 Cycle measurements, 416, 487, 527 Cylindric tube, 231, 249, 253

D Daily load, 56–58 Darcy’s law, 222, 249, 250, 253, 258 Degradation, 3, 37, 40, 94, 109, 162, 188, 215–218, 222–228 Density of the material, 285, 288, 299 Deodorants, 203 Depositing media, 44, 48, 50, 66

641 Deposition, 6–8, 10, 12, 13, 18, 21, 22, 40, 41, 44, 45, 47, 50, 51, 54, 63, 106, 120, 123, 144, 146–149, 163 Detector, 269, 270, 291 Dielectrics, 291 Dispersion, 14, 19, 20, 53, 152, 153, 161 Dispersive materials, 228, 500 Dissolved organic carbon (DOC), 135–141, 150, 151 Dissolved oxygen, 144, 261, 334, 336–338, 341, 345, 346, 492, 494, 500 Distilled water, 112, 296, 339, 390, 490, 491, 501, 532, 536 Divergence, 241 Dose-response curve, 14, 16 Droplet biofilters, 196–199, 206, 328, 433, 504 Dynamic factor method, 23–28 Dynamic factors, 24–28, 39, 73–75 Dynamic olfactometer, 413–416, 487, 527 Dynamic pressure, 267

E Ecological footprint, 28, 29, 32 Electronic scanning, 274, 275, 489 Electronic sensors, 488 Elemental analysis, 495, 496 Elemental carbon, 496 Emissions, 5–8, 14, 15, 17–20, 31, 33, 35, 36, 44, 51–53, 55–57, 63, 67–70, 73, 94, 95, 97–103, 105, 106, 111, 144, 163, 187, 188, 194, 197, 208, 226, 264, 265, 274–277, 291, 489 Engineered barriers, 1, 3, 34, 43 Environmental compartments, 17, 18 Environmental conditions of the biofilter, 24, 201, 326, 347, 548 Environmental pressure, 265 Environmental protection technologies, 1, 3, 33, 35, 36, 39, 40, 43, 93–97, 99–103, 143, 187, 259 Enzyme activity, 442, 443, 507 Enzymes, 11, 215, 223, 443 Euler’s equation, 250 Exposure, 14–17, 31, 54, 79, 83, 84, 104, 108, 120, 473, 481

F Feedstock, 93–97, 99–103, 105, 107–111, 116, 118, 121, 122, 125, 135, 136, 163–166, 168 Felt, 283, 284, 286–290

642 Fillers, 228, 239, 240, 260, 262, 283, 329, 489 Filtering medium, 195 Filtration theory, 249 Footprints, 3, 28–33 Freundlich, 156–160, 169–177, 183–185

G Gaseous phases, 391 Gaseous pollutants, 53, 57, 187, 191, 195, 261, 262, 327, 366, 405, 411, 489 Gas flow, 210, 231, 233, 250–252, 264, 265, 267, 269, 326, 327, 357, 387, 388, 405–407, 409, 410 Geoaccumulation index (Igeo), 22, 66 Geochemical models, 160, 161 Growth rates, 222, 224, 328, 406, 434, 438, 537

H Hazards, 14–17, 30, 36, 64, 76, 144, 412 Heating elements, 278, 279, 281, 282, 330, 415, 484–486 Henry’s law, 154, 155, 157, 225, 226 Heterotrophic enzymes, 328, 334, 337, 340, 346, 434 Human exposure, 14–16 Humidification of the packing material, 241, 303, 310, 311, 318, 360, 366, 370, 481, 532 Hydrophilic, 226, 532 Hydrophobic, 46, 47, 215, 226 Hydrostatic pressure, 219

I Immersion lens, 277 Immobilisation, 3, 13, 39, 43, 105, 109, 121, 123, 132, 134, 166, 168, 544 Incinerator, 67, 69–71, 73, 126 Indicators, 2, 12, 26, 27, 29, 40, 45, 49, 50, 62, 65, 71, 80, 165, 173, 190, 228, 229, 270, 285 Inorganic pollutants, 406, 408 Intake, 14, 16, 17, 261, 311, 377, 380, 385, 387, 535, 536, 538 Interelectrode space, 488 Isothermal process, 252 Isotherms, 154–160, 169–185

Index L Laboratory biofilters, 259, 261, 262, 303, 310, 317, 322, 328–330, 356, 357, 359, 370, 372, 412, 413, 453–457, 459, 461, 463–467, 469, 470, 489, 491, 521, 527, 538 Laminar movement, 230, 231 Langmuir, 150, 155–159, 169 Leaching, 10, 110–112, 116–118, 120–125, 130–135, 137–141, 147, 171–177, 179–184 Lichens, 50, 51, 54 Life-cycle assessment (LCA), 96, 99 Linen fabric, 239, 240, 242, 259, 262, 280, 284, 286–290, 294, 295, 301, 302, 316, 329, 342, 357, 359, 362, 363, 366, 367, 371, 372, 375, 376, 384, 393, 402, 408, 412, 417, 420, 426, 456, 457, 459, 460, 469, 489, 534 Liquid phases, 11, 116, 118, 151, 157, 188, 195, 196, 224–228, 273, 491, 532 Load factor, 57 Load of the packing material, 201, 221 Longevity, 53, 100, 228, 229, 259, 359, 372, 412

M Macropores, 105, 167, 209 Mass release, 227, 228 Mass transfer, 151, 160, 161, 225, 227, 228 Mathematical models, 230, 231, 233–238, 240–255, 257, 258 Medium temperatures, 265, 280, 330, 415, 485, 538 Mercury porometry, 209, 210, 348, 349, 489, 496 Mercury porosimeters, 275 Mesophiles, 218, 219 Mesophilic microorganisms, 328, 332, 334, 336, 338, 340, 341, 346, 355, 356, 433 Mesopores, 167, 209 Metabolic activity, 219 Metallic elements, 23–28, 46, 93, 118 Micromycetes, 189, 190, 215, 216, 224, 321, 360, 373, 434–446, 448, 451–467, 469–476, 478–481, 489, 500, 506–510, 512–518, 520–526, 537, 538 Micromycete strains, 437–439, 442–445, 448 Micronutrients, 10, 109, 217 Microorganism activity, 9, 195, 505

Index Microorganism development, 518 Micropores, 139, 167, 209, 210, 261, 348, 538 Micropore structure, 139, 497 Microscope, 167, 211, 274–277, 291, 292, 489, 495, 499 Microscopic fungi, 214, 433–437, 467, 470, 471, 512, 513, 515–518 Mineralization, 105, 106, 195 Modular system, 263 Mosses, 12, 41, 48, 53, 54, 65, 66, 195, 205 Muffle furnace, 111, 268, 271, 273, 274, 283, 284 Multi-component, 159, 160

N Natural microorganisms, 296–303, 309–317, 327, 332–336, 338–341, 343, 344, 355, 356, 360, 362–364, 366–369, 373, 395, 396, 403–406, 408–412, 433, 471, 473 Natural technologies, 1, 39–91 Neutral solutions, 328, 434 Nitrogen oxides, 18, 51, 52, 54, 63, 68, 264 Non-woven cork (NWC), 242, 259, 262, 280, 284, 286–290, 292, 293, 296–298, 304, 306, 308–313, 317–325, 329, 333, 337, 339, 345, 357, 359, 362, 364–372, 378–381, 386–388, 391, 393, 395, 397, 400, 402, 403, 408, 410, 412, 417–420, 423, 451–453, 458, 461–463, 469, 470, 485, 489, 494, 498–503, 506, 520, 528–530, 532, 534, 538 Noosphere, 1–5 Nutrient footprint, 30 Nutrient medium, 222 Nutrients, 13, 28, 30, 41, 51, 77, 79, 82, 87, 104–108, 123, 135, 144, 163, 189, 195–199, 205, 215–219, 222, 249, 260, 261, 328, 347, 433, 437–440, 442, 443, 506, 537

O Odour concentrations, 414, 421, 487 Odour intensity, 418–421, 423–426, 428, 429, 431, 527–531, 537 Odours, 68, 110, 188, 199, 213, 260, 280, 391, 412–431, 433, 487, 527–531, 537, 538 Odour units, 413, 414, 416–421, 423–426, 428, 429, 487, 528–530 Oil refineries (ORs), 52–66, 187 Olfactometry methods, 413, 414, 487 Organic xenobiotics, 217

643 Osmotic pressure, 328 Oxygen concentration, 343, 344, 347, 348, 488 Oxygen content, 261, 262, 264, 328–332, 335, 343, 344, 346, 355, 356, 488, 492, 494, 501 Oxygen content meter, 264, 330–332, 335, 492

P Packing materials, 153, 188, 190–198, 201, 203–212, 214–222, 224, 225, 228, 229, 241, 259–357, 359–389, 391–394, 396–403, 405, 406, 408–410, 412, 413, 415, 416, 425, 435, 444, 445, 451–454, 456, 458–463, 465–471, 473, 474, 476, 477, 479, 481–492, 494–525, 527–539 Partial pressures, 154, 155, 226 Perforated plates, 379, 415, 483, 484, 535 Perforated tube, 254, 428 Perlite, 192, 194, 195, 206, 216, 218, 389, 409 Perlite granules, 409 Phenolic groups, 261 Physical-chemical parameters, 505–514, 546, 547 Phyto-DSS, 87–90 Phytoremediation, 24–27, 39, 43, 75–91, 136 Pilot biofilters, 483, 485, 486, 490, 491, 494–532, 534–539 Pine charcoal, 428, 429, 530 Pitot tube, 266 Plate structures, 356, 413, 483, 506, 530, 538 Pollutant concentrations, 21, 145, 188, 190, 198, 199, 224, 268, 280, 321, 370, 388–390, 392, 394, 395, 397–399, 401, 403, 405, 408, 410, 415, 468, 490, 491, 499, 519, 534, 536–538 Polluted air, 6, 197, 199, 201, 203, 207, 214, 217, 237, 253, 260, 262, 268, 278–283, 287, 300, 301, 305, 311, 315, 317, 319, 329, 330, 334–336, 338, 340, 341, 343, 346, 373, 374, 377, 389, 390, 392, 394–396, 398, 399, 401, 403–405, 408, 410, 414, 415, 434–437, 483–487, 521, 531, 534, 538 Pollution index, 64, 65 Pollution level, 22–28, 56, 57, 65, 75 Pore diameter, 120, 273, 352, 354, 489, 492, 498, 499 Pore structure, 167, 497 Pore volume, 131, 207, 348, 349, 352, 354, 372, 496–499, 536, 538 Porosity of the material, 251, 271, 281, 283, 285–288, 489

644 Porous medium, 161, 249–255, 257, 258 Potentially toxic elements (PTE), 3, 5–25, 27, 28, 51, 64, 65, 93, 102, 104, 105, 109, 112–125, 128, 129, 131–141, 143–149, 151, 156, 157, 159–164, 166, 168–183, 185 Precipitation, 7, 13, 21, 22, 33, 41, 45, 47, 50, 51, 79, 122, 145, 147, 161, 163, 168, 169 Pressure isolines, 247 Prototype, 483–539 Psychrophilic microorganisms, 328, 433 PVC blocks, 147, 193, 241, 283 Pyrolysis, 102–105, 107–113, 118, 120, 122, 125–128, 132, 135–139, 141, 163, 165–168, 210

R Rate fields, 248, 249, 255, 256 Redlich-Peterson, 183–185 Redox potential, 263 Rejector, 42 Relative humidity, 88, 201, 270, 271, 283–285, 473, 490, 536 Reynolds numbers, 221, 230, 231, 241 Risk level, 57

S Salinity, 263 Samples of the packing material, 454, 456, 505, 506, 514 Sampling, 12, 13, 41, 47, 55, 56, 59, 62, 69–73, 82, 264–267, 269, 270, 278–282, 325, 331, 357, 361, 373, 414, 415, 418–421, 423, 425, 426, 428, 429, 463, 465, 468, 469, 479, 484, 485, 487, 527 Selected microorganisms, 303, 305, 307–309, 317–319, 321–323, 325–327, 336–338, 344, 346, 347, 355, 356, 360, 365–366, 369–373, 395, 396, 403–411, 478, 489, 490, 494, 508, 514, 518, 520, 523, 527, 534, 536, 537, 539 Selective, 209 Self-humidification, 290, 296, 303, 305, 310, 311, 317, 319, 322, 490, 532 Single-element lamp, 72 Sips, 158, 159 Sleepers, 125–131, 134 Sludge, 8, 24, 26, 76, 80, 82–85, 87, 88, 90, 93, 104, 107–118, 120, 122, 124, 133, 136, 163, 166, 192, 194, 196, 199, 200, 206, 216, 217, 260, 261, 391, 410, 488

Index Sniffers, 488, 527 Snow-cap, 44–48, 51, 55–62 Snow dust, 44, 51, 56–63 Snow melt, 147 Softwood, 99 Soil contamination, 22, 23 Soil improvement, 104–107 Soil-plant transfer, 10–12 Soils, 3, 6–14, 17–28, 30, 31, 33, 37, 39, 41–43, 47–50, 52–54, 56, 63–65, 69–78, 80–83, 85–88, 90, 91, 93–141, 143, 149, 151, 162–166, 186, 192, 194, 195, 205, 206, 215, 220, 249, 260, 262, 263, 273, 410, 507 Soil solution, 9–11, 88 Sorption properties, 192, 206, 260 Stabilization, 43, 93–141, 229, 333 Straight inner structures, 410, 534 Strains, 189, 190, 321, 360, 373, 434–439, 442–447, 449–451, 489, 490, 514 Substrates, 42, 88, 104–106, 124, 144, 162, 188, 192, 215, 217–220, 222–225, 328, 433, 471, 473, 481, 506, 507, 514, 536 Surface areas, 10, 29, 46, 48, 49, 104, 118, 120, 123, 131, 139, 151, 153, 164–167, 192, 195, 197, 203, 205, 206, 209–211, 215, 260, 261, 273, 291, 292, 294, 318, 352–355, 372, 489, 492, 496, 497, 536, 538 Surface density, 283, 288 Surface runoff, 144–148, 151, 186 Surface tension, 291, 348, 532 Sustainability, 1, 17, 23, 28, 29, 37, 39, 40, 93, 94, 108, 136, 187, 192, 359, 433 Sustainability level, 93–97, 99–103, 143, 259 Sustainable environmental protection technologies, 1–38, 40, 187–258 Sustainable materials, 38, 143 Sustainable role, 185, 186 System sustainability, 359–431

T Technogenesis, 1–38, 143 Technogenic activity, 1, 2 Technogenic flows, 5–22 Technogenic load, 2, 32 Technophilicity, 4, 5, 25 Temkin, 156, 157 Temperature of the aqueous medium, 488, 501 Thermochemical conversion, 261

Index Thermophilic microorganisms, 328, 433 Thermophilic yeast, 218 Thlaspi caerulescens, 76, 79, 80, 83, 84, 86, 88–91 Thlaspi goesingense, 76, 77 Tolerance, 11, 76–79, 435–437 Total organic carbon (TOC), 127, 271, 272, 488, 489, 492, 494, 502 Toth, 159 Tower-type biofilters, 203, 205, 207 Tracheids, 496 Translocation, 24–27, 79, 82, 84, 85 Transport, 14, 17–19, 34, 37, 45, 46, 48, 74–76, 78, 79, 95, 99, 145–147, 150, 160, 166, 167, 328, 434 Tree bark, 65 Tubular plates, 262, 329–331, 428, 429, 431 Tubular structure, 347–349, 354–357, 494, 501, 530 Turbulent movement, 18, 230, 231

U Untreated biochar, 538 Uptake, 10–14, 17, 21, 25–27, 42, 74, 77, 80, 83, 84, 86, 91, 105, 106, 170 Urban areas, 3, 12, 32, 44, 63, 71, 104, 146, 147, 162 Urban contamination footprint, 5, 28, 32, 33 Urea, 436

V Vacuum chamber, 414, 415, 487, 527 Visual method, 49, 255, 471, 489 Volatile organic compounds (VOCs), 197–199, 214, 226, 262, 328, 329, 332, 336, 340, 346, 412, 413, 433, 489, 522

W Waste incineration, 6, 39, 67–75, 146 Water-level rise, 3, 287, 288, 290, 291 Water quality, 9, 46, 149, 161, 334, 338, 341, 346, 488

645 Wavy lamellar plates, 246, 259, 262, 267, 277, 279–282, 309–325, 328–330, 338–345, 354–357, 359, 360, 366–373, 381, 383, 384, 386–388, 400, 402, 408, 410–412, 415, 423–426, 429, 431, 459–463, 466, 467, 469, 470, 483–485, 487, 490, 494, 498–505, 509, 511–513, 518–527, 529, 530, 532–534, 537 Wavy lamellar profile, 245 Wood fibre, 239, 240, 242, 359, 362–372, 375, 376, 378–381, 383, 384, 386–388, 391, 393, 395, 397, 400, 402, 403, 408, 410, 412, 417–420, 423–426, 428, 429, 454–462, 467, 469, 471–474, 478, 479, 481, 485, 486, 489, 494, 495, 502, 514, 515, 520, 524, 525, 528–530, 532, 534, 535, 538 Wood sawdust, 102, 192, 206, 260

X Xenobiotics, 147, 212 Xylanase producers, 437, 438 Xylene, 109, 187, 188, 194, 205, 207, 213, 216, 217, 220, 261, 262, 296–305, 307–319, 321–325, 329, 333–335, 337, 339, 340, 342, 343, 345, 346, 349, 352, 354, 359, 360, 370, 372, 373, 375, 376, 378–381, 383, 384, 386–394, 396, 397, 399–414, 416, 418–431, 434–437, 440, 441, 451–463, 465–470, 473–476, 478, 479, 481, 487, 489–491, 494, 496–498, 501, 502, 508–510, 512, 513, 515, 516, 518–521, 523, 525–531, 534–539 Xylene removal, 408, 451, 453, 454, 456, 461, 463, 465–468, 474, 476, 480, 481, 492, 510, 511, 513, 517, 525

Y Yeasts, 214, 215, 217–219, 224, 321, 360, 373, 433–438, 442–444, 446–449, 452, 453, 455–465, 467–476, 478–482, 490, 500, 506–526, 537, 538 Yeast urease, 436