Environmental Planning [1 ed.] 9781617610233, 9781617286544

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Copyright © 2010. Nova Science Publishers, Incorporated. All rights reserved.

Copyright © 2010. Nova Science Publishers, Incorporated. All rights reserved.

ENVIRONMENTAL SCIENCE, ENGINEERING AND TECHNOLOGY

Copyright © 2010. Nova Science Publishers, Incorporated. All rights reserved.

ENVIRONMENTAL PLANNING

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ENVIRONMENTAL SCIENCE, ENGINEERING AND TECHNOLOGY

ENVIRONMENTAL PLANNING

REBECCA D. NEWTON

Copyright © 2010. Nova Science Publishers, Incorporated. All rights reserved.

EDITOR

Nova Science Publishers, Inc. New York

Copyright © 2011 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com

NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers‘ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works.

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Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. Additional color graphics may be available in the e-book version of this book. LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA Environmental planning / editor, Rebecca D. Newton. p. cm. Includes index. ISBN H%RRN 1. Environmental management--Planning. 2. Environmental protection--Planning. 3. Environmental policy. I. Newton, Rebecca D. GE300.E623 2009 333.72--dc22 2010025443

Published by Nova Science Publishers, Inc. † New York

CONTENTS Preface Chapter 1

Chapter 2

Chapter 3

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Chapter 4

Chapter 5

Chapter 6

vii Environmental Considerations in Strategic and Tactical Planning of Supply Chains José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner

1

The Links between the Environmental Regulation and Competitiveness: The Case of the Agriculture Sector in Andalucía Francesco Testa, Natalia Marzia Gusmerotti and Fabio Iraldo

45

Enhancing Environmental Planning through the Use of the Thermodynamic Quantity Exergy Marc A. Rosen

79

Environmental Planning Inputs by the Forest Sector: The Scale Factor, the Connection Planning-Management and the Relations with Other Planning Sectors in Italy Sebastiano Cullotta and G. Federico Maetzke Operations Research Methods in Production Management with Environmental Constraints Marius Rădulescu, Constanta Zoie Rădulescu and Gheorghiţă Zbăganu Policy Analytical Capacity in the Environmental Sector: Survey Results from Canada Michael Howlett and Sima Joshi-Koop

107

135

167

Chapter 7

Governance and Public Participation in the Network Society Greg Hampton

Chapter 8

Industrial Ecology in the Planning and Management of Industrial Parks M. C. Ruiz

203

Developing a Drought Planning Evaluation System in the United States Mark Svoboda and Zhenghong Tang

221

Chapter 9

187

vi Chapter 10

Chapter 11

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Index

Contents Marine Spatial Planning: Identifying the Critical Elements for Success Fanny Douvere and Charles Ehler A Comprehensive Approach for Participatory Land Use Planning in Areas Affected by Desertification of the European Mediterranean Region Luis Recatalá Boix and Juan Sánchez Díaz

233

251 269

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PREFACE Environmental and ecological impacts are important considerations in environmental planning. This book presents current research data in the field of environmental planning including the strategic and tactical planning of supply chains; the links between environmental regulation and competitiveness; industrial ecology in the planning and management of industrial parks; developing a drought planning evaluation system in the United States; and incorporating environmental hazards mitigation into local land use planning. Chapter 1 - Corporate approaches towards reducing its environmental footprint cannot be undertaken in isolation. Nowadays, it is recognized that a concerted effort is required, embracing the different supply chain entities, in order to correctly estimate environmental burdens and to propose effective environmental strategies. Such an effort poses an important and complex challenge to managers. On the one hand, the economic and environmental tradeoffs existing within a supply chain network must be pondered so as to make proper decisions. This is not a straightforward task;, thus, analytical tools are desirable to support environmental decision-making. On the other hand, environmental performance is seldom quantified appropriately. Traditional current accounting practices which do not clearly consider environmental issues and the availability of diverse environmental metrics make it arduous to assess firms‘ environmental performance. This chapter proposes the use of analytical tools to tackle environmental planning. The proposed approach addresses the optimization of the supply chain planning and design by considering economic and environmental issues. The strategic decisions contemplated in the mathematical model are facility location, processing technology selection and the production– distribution planning. The Life Cycle Assessment (LCA) approach is envisaged to incorporate the environmental aspects of the model. The IMPACT 2002+ methodology is selected to perform the impact assessment within the SC since it provides a feasible implementation of a combined midpoint–endpoint evaluation. Moreover, traditional accounting practices have been extended to include different costs associated with environmental issues. The environmental costs estimation has been carried out using a Total Cost Assessment (TCA) approach and taking into consideration a CO2 trading scheme as well. Additionally, the model performs an impact/cost mapping along the nodes and activities that comprise the supply chain. Such mapping allows focusing financial efforts to reduce environmental burdens to the most promising subjects. The mathematical formulation of this problem becomes a multi-objective MILP (moMILP). Criteria selected for the objective

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Rebecca D. Newton

function are damage categories impacts, overall impact factor and net present value (NPV) considering different environmental costs. The main advantages of this model are highlighted through a realistic case study of a maleic anhydride SC production and distribution network in Europe. Chapter 2 - In general, the effects of environmental regulation and market incentives on society can redistribute income streams and can have an impact on the standard of living. These effects are also often analyzed in relation to the concept of ―competitiveness‖. Literature and empirics on competitiveness focuses on price and cost developments of production factors and other parameters that can potentially affect economic growth, market shares and other performances of companies in the targeted sectors. After a brief description of the main findings emerging in literature on the different ways of defining and measuring the effects of environmental regulation on market forces and on the relationship between environment and competitiveness, we focus on the role of the policy maker in Andalucía Region, describing the effect of water regulation and planning on the environment as well as on the competitiveness of the firms. The case studies was carried out according to the following structure, including a general background information and a detailed analysis of the environmental, in particular water, policy issues most affecting industries: water resources (hydrological, geographical, climatic, ecological situation), water policy framework and description of policy instruments (focus on water pricing, regulation of point sources, water abstraction, best environmental practices), qualitative and quantitative assessment of effects on competitiveness. The study aims at demonstrating how and the extent to which the policy maker can, by a stringent environmental regulation and planning, improve the quality of local environment and provide competitive opportunities to the firms. Chapter 3 - Environmental planning takes into consideration many factors, one of which sometimes is thermodynamics. The justification for including thermodynamics in such activities is that efforts to improve understanding of and to reduce environmental impact often can be enhanced by combining thermodynamics with environmental disciplines. Most such assessments consider thermodynamics in terms of energy. Recent research has suggested that environmental impact is better understood and reduced using the thermodynamic quantity exergy. An important justification for this statement is that energy often is not a measure of the potential for environmental impact, whereas exergy has attributes of such a measure. Consequently, exergy may be able to provide a meaningful and useful tool in environmental planning. Here, we summarize existing analysis techniques that integrate exergy environmental factors, e.g. environomics, exergy-based life cycle analysis and exergy-based ecological indicators. Correlations between exergy and environmental parameters are identified using thermodynamic and environmental data, and utilized to demonstrate that exergy factors into environmental improvement. As the objectives of most exergy-based methods include improving understanding of environmental impact and ultimately reducing it through use of appropriate environmental improvement measures, the links to environmental planning have become increasingly evident and important. Several applications are considered, including the use of exergy for different environments and ecosystems to help predict and improve their wellbeing and thereby enhance environmental planning initiatives. Chapter 4 - In the twentieth-century, Italy, as well as many other densely populated European countries, has been characterized by a progressive reduction of the forest cover, especially in the Southern Mediterranean regions. Generally, the mountain areas developed a

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Preface

ix

forest-based economy, especially in the Northeast Alps and in the Mediterranean Apennine inner mountains. Several distinctions must be taken into account, for example, with regard to ownership of the woods. On the Alps, generally the forests are municipal, community or private properties. In the Mediterranean Apennines inner areas there are many wide stateowned forests, followed by municipal properties, while the private property is, on average, less diffuse. In the recent past, after the destruction and the intensive exploitation, mainly due to the two world wars, reconstitution by reforestation or improvement of the existing woods has been diffusely realized. The most recent period has been characterized by the acknowledgment of the necessity of a more sustainable use of lands and, at the same time, by the evolution of programming and management tools at different scale levels. From continental to local levels, passing through national and sub-national, the planning actions run from a list of main program points to a detailed indication of specific management practices. Nevertheless the core of forest management remained based on the management plan of the local level only, often grounded with classical schemes, with shallow planning at upper and intermediate levels. In this work a critical analysis of current programming and management tools adopted in Italy at different levels is carried out. In the same way, the authors attempt to highlight the relations with other planning tools involved in environmental management (landscape plan, town plan, protected areas plan, etc…). Starting from the foregoing assumptions, which characterized the management approach during the last fifty years, differentiation elements, between the more flexible and integrated forest-environmental planning and management applied in the Alpine environment and the traditional, classical forest management in the Mediterranean Apennine environment, could be pointed out. The classical reference models, mostly strongly anchored to a dominant economic view, have not always applied in reality, because they are based on rigid and pre-arranged schemes of management planning.. Chapter 5 - Economic growth is frequently considered to be in conflict with sustainable development and environmental quality. With increasingly stringent environmental regulations, there is a growing need for efficient production planning models that take into account the trade-off between return and environmental costs and therefore reduce the penalties paid for overcoming the pollution levels. This chapter surveys partially the current state of the literature in operations research approaches to production management in the presence of environmental constraints. A special attention is paid to the application of portfolio theory and to loss function theory to production planning models with environmental constraints. Our research has been focusing in the area of pollution prevention, consequently the models can be considered sustainable production planning models. Chapter 6 - Governments and increasingly, non-governmental actors in Canada and elsewhere are being asked to design effective long-term policy measures for climate change adaptation and mitigation. Whether they have the necessary kinds of resources to successfully do so, through the use of enhanced evidence-based analytical techniques, remains unknown. This is due in large part because work on the behaviour and behavioural characteristics of inhouse policy analysts in supplying advice to government, let alone those working outside it, is exceedingly rare. In most countries empirical data on almost every aspect of policy analysis in government are lacking.

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Rebecca D. Newton

This is despite the common assertion made by policy scholars that governance regimes are often to blame when resource management fails. Given the significance of public sector analysts in the policy advice system of government, studies of their activities, behaviour, and impact are required if our understanding of policy capacity for climate change mitigation and adaptation is to be informed. As Beem has written, ―government officials can help define, frame, implement, and enforce new conceptualizations of what is good and/or appropriate policy.‖ And their potential influence over public policy is not limited to the domestic realm either: through their framing of domestic policy and interaction with other governments and non-governmental actors, public policy bureaucracies can affect the expectations of other jurisdictions and can help cultivate a policy discourse subsequently informing policy development and implementation elsewhere. Because civil servants are crucial policy actors when it comes to designing and implementing systems to respond to climate change, it is important that we understand what they do and how they do it. Here, we will investigate education levels and training, day-today policy activities, sources and types of information collected and use of analytical tools and methods to determine the policy analytical capacity of sub-national governments in Canada on environmental policy issues. The first section of this chapter will introduce the concept of evidence-based decision-making and its importance to environmental policy capacity, before turning to the results of a national survey of Canadian provincial environmental policy analysts. Chapter 7 - The public participation movement in planning and policy development is regarded as anachronistic in the network society. Politicians, administrators and citizens deliberate together to perform governance. In the network society co-governance is carried out jointly and politicians need to become adept at meta-governance in order to maintain representative democracy. Meta-governance – regulating the self-regulated – is important in facilitating co-governance. This can be achieved through modifying public participation methodology to include politicians and administrators and making use of modes of communication which are prevalent in the network society. Chapter 8 - The planning and design of an industrial area is quite a complicated process, due to the large number of agents involved. It is also a long process due to the scope of the action itself: selection and design of the location, design of the physical infrastructures, of the industrial installations and buildings, construction, operation and design of the management systems and disassembly-dismounting. Integration of the environmental variable throughout all the design stages is essential in order to ensure that it works over time and that it coexists with the environment where the estate is located. In this chapter we analyse the concept and the types of sustainable industrial areas (Eco-Industrial Parks, EIPs). Application of industrial ecology is the main strategy supporting change towards a new development model, based on a sustainable economy. Depending on the applicable geographical scale, there are different types of EIPs. Thus arise new opportunities for seeking alternative strategies and solutions for making use of resources, minimising negative environmental impact and maximising financial profits. However, developing an industrial area of this nature requires a large amount of coordination between all the agents involved. The types of organisms and current management forms and trends are summarised. The roles, opportunities and risks to be assumed by the organisms involved in the development of EIPs are established based on this framework The manager or coordinator is an important figure throughout the operational life

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Preface

xi

of the estate, as a feasible combination of companies must be managed and infrastructures and competitive services must be maintained. Chapter 9 - Drought is a normal part of the climate cycle, affecting every climate regime on the planet. Drought indicates a special period in which an unusual moisture scarcity causes a serious hydrological imbalance. Drought is related to the timing and effectiveness of the rains, high temperature, high wind, and low humidity. The typical impacts of drought may include dry lands, low or empty water-supply reservoirs, low groundwater levels (dried up wells), crop damage, and ensuing environmental degradation. In the United States, drought accounts for losses in the billions of dollars. In fact, a FEMA (1995) report estimates the average annual losses due to drought at $6-8 billion, on a par with hurricanes, making these the two most costly hazards impacting our country. Drought often affects several sectors (agriculture, recreation and tourism, energy, forestry, and others) at the same time and typically impacts large areas and many people. These impacts serve as indicators of our vulnerability and risk during extended periods of rainfall deficits. Our vulnerability to drought is affected by (among other factors) population growth and shifts, urbanization and sprawl, demographic characteristics, technology, water use trends, government policy, social behavior, and environmental awareness. These factors are continually changing, and society‘s vulnerability to drought can increase or decrease in response to these changes. Although drought is a natural hazard, society can reduce its vulnerability and therefore lessen the risks associated with drought episodes. The impacts of drought, like those of other natural hazards, can be reduced through mitigation and preparedness. Planning ahead in an attempt to mitigate drought gives decision makers the chance to relieve the most suffering at the least expense. Reacting to drought in ―crisis mode‖ decreases self-reliance and increases dependence on government and donors. As a proof of concept approach, this paper looks into the process of comparing and evaluating state drought plans within the United States. The idea of evaluating (scoring) drought plans may be new, but similar methods have been applied to other hazards and in other planning fields, such as the environmental and urban/rural planning. Even so, the planning profession itself has developed relatively few criteria for evaluating the quality of plans, so plan quality is difficult to define. Now, and in a changing climate with changing vulnerabilities, Brody aptly notes that planners must be flexible, adapting and planning for changing conditions by gearing their efforts more toward uncertainty and surprise. Thus, the purpose of this paper is to assess the potential transferability of evaluation techniques in other fields and hazards to the evaluation of drought plans in the United States. Chapter 10 - Human use of ocean space is rapidly expanding – a trend primarily driven by the quest for cleaner energy, food security, and the effects of climate change. Offshore renewable energy in Europe could provide 15% of its total energy demand in 20 years. In the US, offshore wind is moving forward in Massachusetts and Rhode Island. While climate change is opening the Arctic ocean to new (and often contentious) proposals for economic development, ocean warming is likely to alter the distributions and critical habitats of fish and protected species, such as polar bears or narwhals. Further, proponents of offshore aquaculture are seeking places to meet the rising global demand for healthy seafood in the face of declining stocks of wild fish. Simultaneously, more traditional uses like recreational and commercial fishing, shipping and oil and gas extraction continue to expand their footprint in a recovering global economy.

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Around the globe, governments increasingly recognize that without more comprehensive and proactive management, the health of ocean resources will continue to decline. Without strong support for the sustainable use of ocean spaces rich in natural resources (wind, waves, oil, fish), opportunities for energy and food security, jobs, and income will remain unexplored. Without protection for ecologically critical places, conflicts between human activities and nature are inevitable, resulting in crucial natural services reduced or lost entirely. Marine spatial planning (MSP) is a pragmatic approach that can help achieve ecological, economic and social objectives simultaneously by placing the spatial and temporal heterogeneity of the ocean at the heart of a legally authorized decision-making process. Chapter 11 - This chapter deals with the application of a comprehensive approach for participatory land-use planning in the Valencian region (east of Spain), a representative area of the European Mediterranean region. In this region, land-use conflicts and environmental issues have emerged rapidly as a consequence of the intensification of agrarian activity and the expansion of industrial-urban uses that occurred in recent decades. These environmental issues increase the risk of desertification in extensive areas of the region. Several relevant land-use plans were developed in accordance with information from the relevant stakeholders identified in the region, using the Land Use Planning Information System (LUPIS) as a spatial decision support system. LUPIS facilitates the generation of alternative land-use plans by adjusting the relative importance attributed by multiple stakeholders to preference and avoidance guidelines. From these plans, a possible consensus plan is proposed to address the land use conflicts between agrarian uses, industrial-urban activity and conservation, and to mitigate natural resource degradation caused by intensive agriculture and expansion of industrial-urban uses. Given that the land-use conflicts and environmental issues characterising the study area are similar to those identified in the European Mediterranean Region, it follows that the approach can be extended to areas affected by desertification of this region.

In: Environmental Planning Editor: Rebecca D. Newton

ISBN: 978-1-61728-654-4 © 2011 Nova Science Publishers, Inc.

Chapter 1

ENVIRONMENTAL CONSIDERATIONS IN STRATEGIC AND TACTICAL PLANNING OF SUPPLY CHAINS José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner* Chemical Engineering Department, Univesitat Politècnica de Catalunya, ETSEIB, Av. Diagonal 647, E08028, Barcelona, Spain

ABSTRACT Copyright © 2010. Nova Science Publishers, Incorporated. All rights reserved.

Corporate approaches towards reducing its environmental footprint cannot be undertaken in isolation. Nowadays, it is recognized that a concerted effort is required, embracing the different supply chain entities, in order to correctly estimate environmental burdens and to propose effective environmental strategies. Such an effort poses an important and complex challenge to managers. On the one hand, the economic and environmental trade-offs existing within a supply chain network must be pondered so as to make proper decisions. This is not a straightforward task;, thus, analytical tools are desirable to support environmental decision-making. On the other hand, environmental performance is seldom quantified appropriately. Traditional current accounting practices which do not clearly consider environmental issues and the availability of diverse environmental metrics make it arduous to assess firms‘ environmental performance. This chapter proposes the use of analytical tools to tackle environmental planning. The proposed approach addresses the optimization of the supply chain planning and design by considering economic and environmental issues. The strategic decisions contemplated in the mathematical model are facility location, processing technology selection and the production–distribution planning. The Life Cycle Assessment (LCA) approach is envisaged to incorporate the environmental aspects of the model. The IMPACT 2002+ methodology is selected to perform the impact assessment within the SC since it provides a feasible implementation of a combined midpoint–endpoint evaluation. *

Corresponding author: Email: [email protected]

2

José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner Moreover, traditional accounting practices have been extended to include different costs associated with environmental issues. The environmental costs estimation has been carried out using a Total Cost Assessment (TCA) approach and taking into consideration a CO2 trading scheme as well. Additionally, the model performs an impact/cost mapping along the nodes and activities that comprise the supply chain. Such mapping allows focusing financial efforts to reduce environmental burdens to the most promising subjects. The mathematical formulation of this problem becomes a multi-objective MILP (moMILP). Criteria selected for the objective function are damage categories impacts, overall impact factor and net present value (NPV) considering different environmental costs. The main advantages of this model are highlighted through a realistic case study of a maleic anhydride SC production and distribution network in Europe.

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1. INTRODUCTION Supply Chain Management (SCM) can be defined as the handling of material, information and financial flows through a network of organizations interconnected with the aim of producing and delivering goods or services to consumers. SCM has been a major source of competitive advantage in the global economy. Moreover, it is well recognized that an optimum management of the Supply Chain (SC) offers a key opportunity for preserving a firm‘s value. The proper handling of a SC should be concerned with the sharing of responsibility from various aspects of performance which include environmental matters. It has been realized that significant improvements in terms of environmental performance and market competitiveness may be achieved by concentrating efforts from all SC partners. Actually, managerial practice related to environmental issues has expanded from a narrow focus on pollution control within a single firm to include a larger set of inter-organizational management decisions, programs, tools, and technologies that prevent pollution before its generation (Klassen and Johnson, 2004). Consequently, these issues are being considered in recent works and call for further research in the integration of environmental management with SC operations. The aforementioned integration may be achieved through the emerging concept regarded as ―Green Supply Chain Management‖ (GrSCM), which is defined as the integration of environmental thinking into SCM, including product design, raw materials sourcing and selection, manufacturing process selection, delivery of final product to the consumers as well as end of life management of the product after its useful life (Srivastava, 2007). Traditionally, the methodologies devised to assist SC operation and design have focused on finding a solution that maximizes a given economic performance indicator while satisfying a set of operational constraints imposed by the manufacturing/processing technology and the topology of the network. In recent years, however, there has been a growing awareness of the importance of including environmental and financial aspects associated with the business decision support levels (Puigjaner and Guillén, 2007). In fact, there are some documented success stories of enterprises that have integrated environmental and SCM issues. For instance, Hart (1997) has presented the Xerox‘s Asset Recycle Program which redirects 90% of all materials and components for its photocopiers through reuse, remanufacturing, and recycle; in this case, annual savings are estimated in US$300 million. Also, Hoeffer (1999) has reported a scrap management system deployed by Daimler-Chrysler which allows for

Environmental Considerations into Strategic and Tactical Planning

3

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annual savings of US$4.7 million. These examples illustrate the potential benefits that can be achieved by integrating environmental aspects along the SC. The environmental science and engineering community have developed several systematic methodologies for the detailed characterization of the environmental impacts of chemicals, products, and processes. All of these methodologies have embodied the concepts of life cycle, i.e., they are based on a Life Cycle Assessment (LCA) which is described in a series of ISO documents (ISO14040, 1997). The LCA framework includes the entire life cycle of the product, process or activity, encompassing extraction and processing of raw materials; manufacturing, transport and distribution; re-use, maintenance recycling and final disposal. Most importantly, it takes a holistic approach, bringing the environmental impacts into one consistent framework, wherever and whenever these impacts have occurred or will occur (Guinee et al., 2001). Examples of these methodologies in the field of process systems engineering are the Minimum Environmental Impact (MEI) methodology (Stefanis et al., 1995), the Waste Reduction (WAR) algorithm (Young and Cabezas, 1999), the Optimum LCA Performance (OLCAP) framework (Azapagic, 1999; Azapagic and Clift, 1999), the Environmental Fate and Risk Assessment tool (EFRAT) (Chen and Shonnard, 2004) and the methodologies proposed by Alexander et al. (2000) and by Guillén-Gosálbez et al. (2008). All these methodologies are based on the incorporation of an optimization step into the four classical phases that comprise an LCA study, namely, goal definition, life cycle inventory-LCI, life cycle impact assessment-LCIA and interpretation (see Figure 1). All of the former methodologies optimize process conditions or topology just considering a single SC echelon. Also common to all of them is the implementation of multi-criteria optimization strategies in order to evaluate the trade-off between economic and environmental issues.

Figure 1. Life cycle assessment steps (Puigjaner & Guillén-Gozalbez, 2008)

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José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner

The concept of SC refers to the network of interdependent entities (i.e., retailers, distributors, transporters, warehouses and suppliers) that constitute the processing and distribution channels of a product from the supply of its raw materials to its delivery to the final consumer. Because an LCA study ideally covers a cradle-to-grave approach, it can be clearly seen that LCA fits as a suitable tool for quantitatively assessing the environmental burdens associated with designing and operating a SC. Two possible LCA approaches can be distinguished, namely, comparison/selection and improvement (Klassen and Greis, 1993). The former approach focuses on identifying environmentally preferable products or processes alternatives as an attempt to leverage marketplace and financial forces in order to displace environmentally harmful activities (Klöpffer and Rippen, 1992). The latter one uses LCA as a tool to identify the SC stages that have a particularly strong negative impact on the environment, and thus, where improvements would be most beneficial. This last alternative allows improving the allocation of limited management time and financial resources within the SC (Freeman et al., 1992). Both types of analysis are performed in this chapter by means of an SC design-planning optimization model. Some works have already addressed the integration of LCA and SC models. Recently, Mele et al. (2008) have shown a quantitative tool for decision making support in the design of sugar cane to ethanol SCs. Also, Hugo and Pistikopoulos (2005) have shown how a set of SC network designs can form an environmentally conscious basis for the investment decisions associated with strategic SC level. Similarly, Chakraborty et al. (2003, 2004), propose a methodology for long term operation and planning. Their proposed framework uses as an MILP formulation with a planning horizon of typically five years. In their approach the estimation of wastes are inputs and the decisions to be made include choosing the plant-wide waste treatment facility. The planning also incorporates a forecast on environmental regulation and a CO2 emission cap is enforced as a constraint into the model. One topic that deserves further attention is the accounting of environmental costs. It is generally recognized that environmental accounting words such as ―full‖, ―total‖ and ―lifecycle‖ are used to indicate that not all costs are captured in traditional accounting and capital budgeting practices (Rosselot & Allen, 2002). The principle followed is that if costs are properly accounted for, business management practices that foster economic performance will also foster superior environmental performance. However, the major proportion of costs arising from environmental damage is borne by the natural environment and the wider community. Since these costs fall outside the conventional accounting framework of the polluter, they are called external costs or externalities. Several techniques below the environmental cost assessment (ECA) umbrella have been developed to assess such costs and to further include them into traditional accounting practices. In this regards, Hertwig et al. (2002) and Xu et al. (2005) propose a methodology which incorporates economic, environmental and sustainability costs combined in the objective function to be optimized. The economic function includes a simplified version of the Ache‘s Total Cost Assessment (TCA) metrics while the environmental impact is assessed using the WAR methodology. The environmental impact is included in the optimization function as a given percentage of the raw material costs (Xu et al., 2005). The plants modeled include an agro-chemical complex plant which also incorporates several CO2 processing facilities. In Singh et al. (2007) the same problem is studied using the Tool for the Reduction and Assessment of Chemical and Other Environmental Impacts (TRACI) metrics but without considering the environmental impact as a cost. The authors show that improving the environmental performance for some

Environmental Considerations into Strategic and Tactical Planning

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impact potentials worsens others. Thus, attempts to optimize global warming ends-up increasing fossil fuel usage, human health and photochemical smog. It has been pointed out that tools, specifically LCA models, should be useful in pursuing more effective climate change policies and international trade should be included within this type of analysis. With regard to this, it is noteworthy that climate change policies are applied based on the temporal distribution of emissions. Usually SC environmental impacts are evaluated at the end of the planning horizon, and the temporal distribution is disregarded at all in the case of LCA. Consequently, the incorporation of constraints associated to the temporal emission distributions is necessary when studying climate change policies in a SC planning model. This chapter describes an analytical approach for SC design and planning focusing on environmental impact and its sources. The approach applies mixed integer modeling techniques. The model is optimized so as to select the most appropriate technology, the appropriate raw material/service supplier and the most convenient production and distribution profiles. The mathematical model encompasses direct emissions, purchased energy emissions, raw materials production emissions and transport distribution emissions. LCA concepts are embedded in the approach, and going further in order to attain a comprehensive LCA application, not merely an overall environmental impact indicator is calculated but also partial environmental impact categories are studied. Furthermore, the impact associated to every SC echelon is mapped aiming at discovering possible opportunities to focus management efforts and resources for environmental impact reduction. The temporal emission distribution is considered for the calculation of environmental and financial metrics, accounting for possible emissions trading. In this way the traditional LCA scheme is extended by including the emissions temporal distribution.

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2. ENVIRONMENTAL AND OPERATIONS PLANNING This chapter deals with the strategic-tactical problem associated to the optimal design and operation of a SC network taking into account environmental considerations. The SC network consists of a number of existing multi-product manufacturing sites and distribution centers at given locations, a number of potential locations where either a manufacturing site or distribution center or both of them can be installed, and finally a number of sales regions and suppliers at fixed locations. In general, each product can be produced at several plants located at different locations using different technology equipment. The production capacity of each manufacturing/processing site is modeled by relating the nominal production rate per activity to the availability of the equipment technology at each plant. Distribution centers are described by upper and lower bounds on their material handling capacity and they can be supplied from more than one manufacturing plants and can supply more than one market place. Given the manner the problem is modeled, materials flows between any facilities may appear if selecting such flow allows improving the performance of the SC. Each market demands one or more products. A market may be served by more than one distribution center, or even directly from any manufacturing site. The mathematical model is an analytical tool intended to support managers on planning decisions such as:

6

José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner The active SC nodes and links; The facilities capacity expansion in each time period; The product portfolio per plant, production amounts, utilization level, and transportation links to establish in the network alongside with material flows; The amount of final products to be sold; The environmental impact associated to each SC node or activity.

2.1. Planning Drivers

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All the aforementioned decisions will be taken such that an economic indicator, i.e., Net Present Value (NPV), and an environmental impact metric, are optimized at the end of a predefined planning horizon.

2.1.1. Cost benefit analysis The usage of NPV is the back bone of cost benefit analysis (CBA) of any project. A generic CBA consists of three steps: (i) valuation of the yearly costs and benefits of the project, (ii) discounting costs and benefits in future years to make them commensurate with present costs and benefits, and (iii) calculation of the metric. Here, in order to compute the NPV, Operational costs include those associated with production, handling of material, transportation and raw materials. Transportation costs are assumed to be linear functions of the actual flow of the product from the source echelon to the destination echelon. Revenue is obtained from the selling of products. Investments on facilities and equipment are also taken into account. The cash flows are discounted at a given return rate. However, the calculation of cash flows gets complex when dealing with environmental issues. These complexities are related to the possibility of using realistic accounting for internal and external costs associated with pollution, waste minimization, waste treatment and waste management (Brennan, 2007). According to Bartelmus (2002), environmental economists attempt to put a monetary value on the loss or impairment of environmental services as a first step towards ―internalizing‖ these ―externalities‖ into the budgets of enterprises. Most environmental cost methodologies aim at including costs which are not usually considered. One of these environmental accounting practices is Total Cost Assessment (TCA). TCA can be briefly defined as ―the identification, compilation, analysis, and use of environmental and human health cost information associated with a business decision‖. The TCA method proposed by the AIChE CWRT (2000) uses five tiers for costs as follows: Type 1 costs are direct costs for the manufacturing site, such as direct costs of capital investment, labor, and raw materials. These types of costs are the ones that traditional accounting practices take care. Type 2 costs are potentially hidden corporate and manufacturing site overhead costs, such as indirect costs not allocated to the product or process. These costs can be grouped into (i) waste treatment costs, (ii) regulatory compliance and (iii) hidden capacity costs. Type 3 costs are future and contingent liability costs, such as potential future contingent costs include fines and penalties caused by non-compliance, future liabilities for clean-

Environmental Considerations into Strategic and Tactical Planning

7

up, personal injury and property damage lawsuits, natural resource damages, and industrial accident costs. In general the procedure for their estimation relies on risk estimation and the expected cost of such risk. Type 4 costs are internal intangible costs paid by the company; these are difficult to measure and include cost entities such as, consumer acceptance, customer loyalty, worker morale, worker wellness, union relations, corporate image, and community relations. Type 5 costs are external costs that the company does not pay directly, including those borne by society and from deterioration of the environment by pollution within compliance regulations.

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From Type 1 towards Type 5 costs, the difficulty of estimation/measurement increases greatly (Emblemsvag, 2003). Among the easiest environmental costs to track are the ones associated with treating emissions and disposing of wastes (Type 2). These costs have already been proven to be a high percentage of the expenditures and of the value added for several industrial sectors (see Table 1). With regards to Type 4 and 5 costs, the TCA methodology (AIChE-CWRT, 2002) provides possible data sources and examples, but no standardized method to fulfill such estimations. Here, Type 1, 2 and 3 costs are included in the NPV assessment as it will be described later in the model formulation. It is important to point out the close relationships between LCA and TCA, since TCA is a support tool for making informed decisions, having a detailed understanding of the pollutants generated and the human health exposure effects for a product or process is essential. The outputs from the LCI can serve as inputs for the TCA methodology, where they are translated to an economic value (AIChE-CWRT, 2002).

2.1.2. Environmental metrics Regarding the selection of environmental metrics, different methodologies have been developed, however all of them rely on the accurate estimation of environmental interventions. Environment is compromised by industry mainly in two ways, namely, its emissions and the consumption of raw materials. This broadly separates typical environmental metrics in two classes (Bare et al, 2001): Pollution categories associated to system's output flows: ozone depletion, global warming, human toxicology, eco-toxicology, smog formation, acidification, eutrophication, odor, noise, radiation and waste heat. Depletion categories associated to system's input flows: abiotic resource depletion, biotic resource depletion, land use, and water use. With regards to environmental impact assessment two schools of methods have evolved (Finnveden et al., 2009): Problem oriented or mid-point methods like CML (Guinee, et. al 2001a), EDIP (Hauschild & Potting, 2004) and TRACI (Bare et al., 2003), which restrict quantitative modeling to relatively early stages in the environmental mechanism to limit uncertainties and classify and characterize emission results in the so-called mid-point categories.

8

José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner

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Damage oriented or end-point methods such as Eco-indicator 99 (Goedkoop & Spriensma, 2001) or EPS (Steen, 1999), try to model the environmental mechanism up to the damage to a given area of protection. Most methods differ on the way mid- or end-point impacts are measured and in the way that weights are assessed for each impact. Moreover not all methods consider the same environmental areas of protection, or how each mid-point indicator affects the end-point. However there is a tendency to define indicators at common mid-points to ensure simplicity in their definitions and to minimize perceived uncertainty (Finnveden et al., 2009). While reliable end-point modeling seems within reach for some categories such as acidification, cancer effects and photochemical ozone formation, it is still under development for climate change (a mid-point indicator is still used early along the environmental mechanism, i.e. increase in radiative force), and the end-point modeling is encumbered with large uncertainties due to many unknowns of the global climate system and due to the long time horizon of some of the involved balances (Finnveden et al., 2009).The selection between one of the impact assessment methods or the usage of different mid-point models from different methods is a matter of the decision maker and the goal that the study follows. Here, the environmental metrics used are the ones devised in the work of Humbert et al. (2005), which presents an implementation working at both mid-point and end point (damage) levels. For each environmental intervention two characterization factors are proposed, which eases model implementation. Their methodology, IMPACT 2002+, is mainly a combination between IMPACT 2002 (Pennington et al., 2005), Eco-indicator 99 (Goedkoop and Spriensma, 2001) using egalitarian factors, CML (Guinee et al., 2001) and the Intergovernmental Panel on Climate Change (IPCC) considerations for CO2 emissions. IMPACT 2002+ has grouped similar category end-points into a structured set of damage categories by combining two main schools of impact model methods: classical impact assessment methods (CML/IPCC) and damage oriented methods (Eco-indicator 99). This methodology proposes a feasible implementation of a combined mid-point/damage-oriented approach. It links all types of LCI results via 15 mid-point impacts (human toxicity, respiratory effects, ionizing radiation, ozone layer depletion, photochemical oxidation, aquatic ecotoxicity, terrestrial ecotoxicity, terrestrial acidification/nitrification, aquatic acidification, aquatic eutrophication, land occupation, global warming, non-renewable energy and mineral extraction) to four areas of protection end-point categories (human health, ecosystem quality, climate change-global warming potential and resources). Table 1. Pollution control expenditures, for selected industrial sectors in the US (Rosselot & Allen, 2002) Industry sector capital expenditures Petroleum Primary metals Chemical manufacturing

As a % of sales 2.25 1.68 1.88

As a % of value added 15.42 4.79 3.54

As a % of total 25.7 11.6 13.4

This approach contains the advantages of being able to calculate both mid- and end-point indicators.

Environmental Considerations into Strategic and Tactical Planning

9

Within the presented model, and in order to avoid emission double counting, raw material emissions are not aggregated to product manufacturing, similarly transport and energy consumption are considered separately.

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2.2. Legislation Constraints and CO2 Trading From another standpoint, as the planet warms up, so does legislation to reduce greenhouse gas (GHG) emissions worldwide. Within this scenario much of the opportunity to manage carbon (CO2) emissions effectively relies on the capacity of the organization to have an overall view of its specific responsibility and associated cost, from a life-cycle point of view. With estimated economic damage of about US$85 for each ton of CO2, capping GHG emissions and establishing a price tag on them became inevitable (Stern, 2006). Regarding to eco-taxes, Brennan, (2007), emphasizes that several different economic instruments are available for the government to encourage greater environmental responsibility, such as: (i) emission charges related to quantity and quality of pollutant and damage done; (ii) user charges for treatment of discharges, related to cost of collection, disposal and treatment; (iii) tradable/marketable permits, which enables pollution control to be concentrated amongst those who can do it economically without increasing total emissions, and (iv) deposit refund systems involving refundable deposit paid on potentially polluting products. Due to the former considerations environmentally benign process designs are bound to be more profitable, given that they will incur in lower waste treatment and environmental compliance costs while converting a higher percentage or raw materials into saleable products (Khor et. al., 2007). This is also true for the case of recycle options where the benefits from avoiding manufacturing impacts tend to dwarf energy/materials used for recycling the materials (Constable et al, 2009), which makes design of environmentally benign supply chains worth of consideration. In the case of tradable permits there exists SO2 (acid rain program) and NOx air emission markets for some zones in the USA1, and there is a European Union Emission Trading System (EU-ETS) market2 for CO2 emissions. The idea behind these schemes is to make firms pay for their emissions so that a financial incentive to decrease them is provided. A cap is set on emissions, businesses are allowed to buy or sell from each other the right to emit emissions. Firms exceeding their emissions cap have to buy extra credits to cover the excess, providing an incentive for them to operate under the capped level, while those that do not use up all their allowances can sell them, providing the least-polluting firms with extra revenue and an incentive to further reduce emissions (Young, 2008). In this sense, organizations should expect to be charged for their CO2 emissions and consequently much of the opportunity to address CO2 emissions rests on SCM, compelling companies to look for new approaches to manage CO2 emissions effectively. Most certainly, this CO2 related charge will force a change in the way organizations run their SCs (Butner et al., 2008). Several institutions (e.g. the California Climate Action Registry (CCAR), The Climate Registry (TCR), the World Resources Institute (WRI), World Business Council for 1 2

http://www.epa.gov/airmarkets/index.html http://ec.europa.eu/environment/climat/emission/index/_en.htm

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José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner

Sustainable Development (WBCSD) have determined protocol definitions for carbon registries in order to help organizations analyze their CO2-footprints. Nevertheless, according to Matthews et al. (2008) the scope of these protocols varies with regards to emission sources, generally suggests estimating only direct emissions (Tier 1) and emissions from purchased energy (Tier 2), with less focus on the SC context which will lead to large underestimates of the overall CO2 emissions. The authors propose a footprint estimation that includes the total SC up to the production gate, also known as cradle-to-gate approach (Tier 3). Furthermore, the authors refer to Tier 4 emission estimations when the whole product life-cycle is taken into account by considering emissions occurring during distribution and product end of life. This extended scope is expected to better aid effective environmental strategies since both firms and consumers have an important influence over the carbon footprints through their ―purchase‖ decisions.

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3. THE MATHEMATICAL MODEL This chapter describes a comprehensive tool that can be used to assist in the planning and design of a SC under economical and environmental impacts considerations. The resulting model is solved by using a multi objective MILP (moMILP) algorithm, which allows observing possible environmental tradeoffs between damage categories and the economic indicator. This approach reduces the value-subjectivity inherent to the assignment of weights in the calculation of an overall SC environmental impact, which is also calculated. The analysis of partial environmental impacts for every echelon is performed with the aim of discovering improvement opportunities; this analysis also provides information about where to focus emission control activity and hints on possible strategies for emission reduction at source. The temporal emissions distribution and trading schemes considerations contributes to understand how regulatory schemes may induce environmental impact reductions. The mathematical formulation of the LCA-SC problem is briefly described next. The variables and constraints of the model can be roughly classified into three groups. The first one concerns process operations constraints given by the SC topology. The second one deals with the environmental model used while the third refers to the economic metric applied.

3.1. Supply Chain Design - Planning Model The design-planning approach presented is a translation of the State Task Network (STN) formulation (Kondili et al., 1993) to SC modeling, which has been presented in the work of Laínez et al. (2009). Such a formulation is suitable to collect all SC node information through a single variable, which eases the environmental and economic metrics formulation. This way SC node characteristics are modeled with a single equation set, since manufacturing nodes and distribution centers are treated in the same way as well as production and distribution activities. Subsequently, it turns out that the model most important variable is Pijff t ; which represents the specific activity of task i performed using technology j receiving input materials from site f and ―delivering‖ output materials to site f  during period t . Indeed, to

Environmental Considerations into Strategic and Tactical Planning

11

model a production activity it must receive and deliver material within the same site ( Pijfft ). In case of a distribution activity, facilities f and f  must be different. The model's equations are briefly described in the next paragraphs. The separation between tasks and technologies allows for a flexible formulation of different scenarios. Materials mass balance must be satisfied in each of the nodes. Eq. (1) represents the mass balance for each material (state in the STN formulation) s consumed at each potential facility f in every time period t . Parameter  sij is defined as the mass fraction of material s that is produced by task i performed using technology j ; Ts set refers to those tasks that have material s as output, while  sij and Ts set, refer to tasks that consume material s . Ssft  Ssft 1 = 



 sij Pijf ft  

f  iTs j( Ji  J f  )



 sij Pijff t

f  iTs j( Ji  J f )

(1)

s, f , t

The model assumes that process parameters are fixed (such as reaction conversion, separation factors, temperatures, etc.), this is one of the reasons for the model to be linear. In this sense  sij and  sij are fixed and constant due to the replacement of all the potentially non-linear relationships by fixed specified parameters. This assumption is acceptable since the model deals with strategic and tactical decisions. Such decision levels require the usage of aggregated figures in which some details (e.g. process operating parameters, scheduling decisions) are disregarded, making the decision making process manageable. Equation (2) models the temporal changes in facility capacities, in this sense the model allows for the simultaneous consideration of design and retrofit of SCs. Equation (3) serves for total capacity ( F jft ) bookkeeping taking into account the amount increased during planning period Copyright © 2010. Nova Science Publishers, Incorporated. All rights reserved.

t ( FE jft ). f , j  J f , t

V jft FE Ljft  FE jft  V jft FEUjft Fjft = Fjft 1  FE jft

f , j  J f , t

(2) (3)

Equation (4) ensures the total production rate in each plant to be greater than a minimum desired production rate and lower than the available capacity. Furthermore, parameter  jf defines a minimum utilization rate of technology j in site f , while ijff  determines the resource utilization factor.

 jf Fjft 1  ijff  Pijff t  Fjft 1 f  iI j

f , j  J f , t

(4)

ijff  , is the capacity utilization rate of technology j by task i whose origin is location f and destination location f  . This parameter is one of the key factors to be determined

12

José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner

when addressing aggregated planning problems, considering strategic and tactical decisions. This operational model may be applied in continuous as well as in semi-continuous processes. Firstly let us consider the continuous processes. For these cases, the capacity utilization factor is a conversion factor, which allows taking into account the equipment j capacity in site f in terms of task i kg of produced material per time unit. In this way the ijff factor is the maximum throughput per planning period. On the other hand, this parameter is closely related to tasks operation time in the case of semi-continuous (batch) processes. Notice that in this kind of production processes the time period scale utilized in aggregated planning is usually larger than the time a task (production/distribution activity) requires to be performed. Therefore, the sequencing-timing problem of short term scheduling is transformed into a rough capacity problem where aggregated figures are used. It is important to have in mind that capacity is expressed as equipment j available time during one planning period, then

ijff  represents the time required to perform task i in equipment j per unit of produced material. Thus, once operation times are determined this parameter can be easily estimated. Eq. (5) forces the amount of raw material s purchased from site f at each time period t to be lower than an upper bound given by physical limitations ( Asft ). Also, the model assumes that part of the demand can actually be left unsatisfied because of limited production or supplier capacity. Thus, Eq. (6) forces the sales of product s carried out in market f during time period t to be less than or equal to demand.

  P

ijff t

f  iTs jJ i

  P Copyright © 2010. Nova Science Publishers, Incorporated. All rights reserved.

f  iTs jJ i

 ijf ft

 Asft

 Demsft

s  RM , f  Sup, t

s  FP, f  Mkt , t

(5)

(6)

For further model details the reader should refer to Laínez et al. (2009).

3.2. Supply Chain - Environmental Model The application of the LCA methodology to a SC requires of four steps, namely (i) goal setting, (ii) life-cycle inventory (LCI), (iii) life-cycle impact assessment (LCIA), and (iv) results interpretation towards improvement. Regarding goal setting, it is important to define the boundaries of the system under study, and which is the functional unit (FU) or service that the SC will provide. Boundaries in the case of the chemical industry are usually drawn from cradle to gate, this is due to the fact that most chemicals are used in different ways and the use phase of products made of these chemicals is too difficult to model appropriately. Consequently raw material extraction, its processing and shipment to a market are considered as part of the chemical SC system. Regarding the FU, commonly a certain amount of product produced is considered. The LCI step requires the estimation of SC environmental interventions (emissions or natural raw material consumptions) which requires assessment of raw material producers,

Environmental Considerations into Strategic and Tactical Planning

13

transportation and product manufacturingimpacts. This step is the most time consuming within a LCA due to the large amount of information that is required to be gathered, however the usage of LCI databases eases this issue. The results of the LCI step of the LCA can be interpreted by means of different environmental metrics. Environmental interventions are translated into metrics related to environmental impact as end-points or mid-points metrics by the usage of characterization factors (CFs), this translation is the LCIA. These metrics differ in their position along the environmental damage chain (environmental mechanism). The equations of the environmental model are briefly described next. Equation (7) models ICaft which represents the mid-point a environmental impact associated to site f which rises from activities in period t ;  ijff a is the a environmental category impact CF for task i performed using technology j , receiving materials from node f and delivering them at node f  .

ICaft =

 

jJ f iI j f 

P

 ijff t ijff a

a, f , t

(7)

Similarly to the case of  sij and  sij , the value of  ijff a is fixed and constant, provided that all environmental impacts are directly proportional to the activity performed in that node ( Pijfft ). This issue is common practice in LCA, where all direct environmental impacts are considered linear with respect to the FU (Heijungs and Suh, 2002). In the case of transportation the FU commonly considered is the ammount of kg of material transported a given distance [kg·km]. Consequently the value of  ijff a can be calculated by Eq. (8) in the

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case of transportation, which considers the distance between sites ( distance ff  ) and where T  ija represents the a environmental category impact CF for the transportation of a mass unit

of material over a length unit. The study of environmental impacts associated to transport or production can be performed by setting the indices summation over the corresponding tasks (i.e i  Tr or i  NTr ).It should be noted that environmental impacts associated to materials transport are assigned to their origin node. T  ijff a =  ija distance ff 

i  Tr , j  J i , a, f , f 

(8)

Equation (9) introduces DamC gft which are a weighted sum of all mid-point environmental interventions combined using g end-point damage factors  ag and then further normalized with NormFg factors. Equation (10) is used to compute the g normalized end-point damage along the whole SC ( DamC gSC ).

14

José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner

DamCgft =

 NormF  g

aAg

ag

ICaft

DamC gSC = DamC gft f

g , f , t

(9)

g

(10)

t

CO2 emissions trading is modeled by introducing Eq. (11). The climate change damage category accounts for all the equivalent-CO2 kg. Eq. (11) states that the total equivalent CO2 emission occurring in the SC (Tier 4 emissions do not considering for product use and end of life emissions, given that fall outside system boundaries) in period t to be equal to the free allowance emissions cap ( MaxCO2t ) plus the extra rights bought to emit ( BuytCO2 ) minus the sold rights ( SalestCO2 ) in period t . TL is the subset of those periods when the emission trading is executed, usually every year. In this model it is assumed that any amount of rights can be sold or obtained at the emissions market. L is the number of periods that accounts for the emission trading interval (e.g., in case that emissions trading occurs yearly and each period t represents one month, L is equal to 12). t

 

 ag ICaft  = MaxCO2t  BuytCO  SalestCO 2

f a Ag t  = t  L 1

2

(11)

g = ClimateChange, t  TL Equations (12) and (13) sum up the environmental damage category results for each site

f and for the whole SC, respectively.

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Impact 2002 = DamC gft f g

f

(12)

t

2002 Impactoverall = DamC gft f

g

(13)

t

2002 DamC gSC or Impactoverall are both used as objective functions in the moMILP

formulation. In this sense the use of damage categories is sometimes preferred given that they are easier to comprehend compared to mid-point values.

3.3. Supply Chain - Economic Model Many economic performance indicators have been proposed to assess the economic performance of a SC network design. The most traditional indicators are profit, NPV, and total cost. Other more holistic measures have been recently proposed. Laínez et al. (2007) proposed a model that pursues the maximization of a financial key performance indicator, the corporate value of the firm at the end of the time horizon. The corporate value is computed by a discounted-free-cash-flow (DFCF) method which can be introduced as part of the

Environmental Considerations into Strategic and Tactical Planning

15

mathematical formulation. Most SC modeling approaches usually ignore net working capital (NWC), which represents the variable assets associated with the daily SC operations (e.g., material inventories, accounts receivable, accounts payable). By using the DFCF method to compute the corporate value, the actual capital cost, the changes in NWC, the liabilities and other financing funds required to support SC operations and thus liquidity are explicitly considered when appraising SC performance. Next, expressions to calculate (i) operating revenue, (ii) operating cost, and (iii) capital investment are presented which would eventually permit integration with detailed financial models. Here, NPV will be used for the sake of simplicity and comprehensiveness. The application of other kind of metrics is out of the scope of this chapter, given the specific characteristics of the problem addressed in this work. Operating revenue is calculated by means of net sales which are the income source related to the normal SC activities. Thus, the total revenue incurred in any period t can be easily computed from products sales executed in period t as stated in Eq. (14).

ESalest =





t

Salessf ft Pricesft

(14)

sFP f Mkt f ( Mkt  Sup )

In order to calculate overall operating cost an estimation of indirect costs and direct costs are required. The total fixed cost of operating a given SC structure can be computed using Eq. (15). Where FCFJ jft is the fixed unitary capacity cost of using technology j at site f.

FCostt =



 FCFJ

f ( Mkt  Sup ) jJ f

jft

t

Fjft

(15)

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The cost of purchases from supplier e, which is computed through Eq. (16), includes raw materials purchases, transport and production resources.

EPurchet = Purchetrm  Purchettr  Purchetprod

e, t

(16)

The purchases ( Purchetrm ) associated to raw materials made to supplier e can be computed through Eq. (17). It should be noted that in this formulation and for the case of raw material suppliers and transport providers each one of them uses a different technology. Variable  est represents the cost associated to raw material s purchased from supplier e.

Purchetrm =

  P

sRM f Fe iTs jJi

ijfft

est

e  Erm , t

(17)

The costs of production and transportation are determined by Eqs. (18) and (19), tr respectively. Here,  eff t denotes the e provider unitary transportation cost associated to ut1 material movement from location f to location f' during period t.  ijfet represents the unitary ut 2 production cost associated to perform task i using technology j, whereas  sfet represents the

16

José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner

unitary inventory costs of material s storage at site f, both of them using provider e during period t.

Purchettr = 

 P f

iTr jJ i  J e f

Purchetprod = 



ijff t

efftr t

e  Etr , t

ut1 Pijfft ijfet 

f iTr j( J  Jˆ ) i f



(18)

ut 2 Ssft sfet

s f ( Sup  Mkt )

(19)

e  E prod , t ut1 In the case of  ijfet , this parameter entails restrictions associated with  sij and  sij ,

which forces the plant to operate at the same fixed conditions, meaning that the amount of utilities and labor spent is proportional to the amount of raw material processed. However the utilities and labor unitary cost may change in time. Moreover, possible cost decrease associated to economies of scale are disregarded by using the former assumption, higher production rates are associated linearly to higher production costs. Finally, the total investment on fixed assets is computed through Eq. (20). This equation includes the investment made to expand the technology‘s capacity j in facility site f in period t (

Price FJ jft FE jft ). FAssett = Price Jjft FE jft  I ftJ JB ft f

t

(20)

j

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In order to take into consideration the compliance with environmental regulations the environmental cost ( Nettenv ) is considered as in the TCA methodology. These costs include type 2 costs related to waste treatment costs, and environmental reporting, and type 3 costs related to environmental liabilities.

Nettenv  CosttWT  CosttCompliance  CosttEnvLiabilities

t

(21)

Waste treatment (WT) costs ( CosttWT ) are usually pooled for the whole site, and consequently are very hard to quantify, however there exists order of magnitude prices WT

( Pricew ) that can be used for the calculation of the waste treatment cost depending on the WT facility to different w sinks (e.g. air, water, landfill or incineration, see Sinclair-Rosselot WT

and Allen, 2002), and the waste flow ( Flowwt ). WT CosttWT =  PriceWT w Flowwt w

t

(22)

Environmental Considerations into Strategic and Tactical Planning

17

In the case of regulatory costs, these are also ―hidden‖ when a project is evaluated; given that these costs are usually personnel costs associated to staff that might divide their time between many different tasks. In the case of the US, the Resource Conservation and Recovery Act (RCRA) requires to maintain records, to notify, and to report for relevant legislations while in the case of the EU similar legislation is found (e.g., REACH, EMAS). These activities entail several costs, which can be roughly estimated considering: a frequency of occurrence ( FreqOccrt ), and an associated cost for the generation of the required documents ( CostDocr ). In the case of the RCRA, some guidelines are available, see appendix E Sinclair-Rosselot and Allen, 2002. reports

CosttCompliance =

 FreqOcc CostDoc rt

t TL

r

(23)

r

Similarly to compliance costs, environmental liabilities can be estimated by assuming a frequency of environmental ( FreqLiabilitylt ) events that might end in: administrative or civil fines ( CostFinel ). possibleliabilities

CosttEnvLiabilities =



FreqLiabilitylt CostFinel

t TL

(24)

l

The net income due to emissions trading ( NettCO2 ) is calculated by Eq. (25). Here,

Cost CO2 and PriceCO2 represent the emission right cost and price respectively.

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NettCO2 = PricetCO2 SalestCO2  CosttCO2 BuytCO2

t  TL

(25)

Equation (26) represents the calculation of profit at period t. To conclude, NPV is computed by means of Eq. (27).

Profitt = ESalest  NettCO2  Nettenv  ( FCostt  EPurchet ) t

(26)

 Profitt  FAssett  NPV =    (1  rate)t t  

(27)

e

The selection of the discount rate (rate) for any time discounted metric is subject to controversy, given that it represents the trade-off between the enjoyment of present and future benefits and affects directly intergenerational aspects of sustainability. Higher values of rate devaluate future impacts and consequently they count little on long time horizon projects,

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José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner

which could be perceived as contrary to the interest of future generations3. In some cases it has been suggested to adopt very low discount rates (even zero), in cases where mortality or extinction of species is possible. As pointed out by Gasparatos et al. (2008), most CBAs have used the Kaldor-Hicks criterion4 allowing for some social actors to lose and not be compensated provided that society gains as a whole. Identically to the case of a weighting set for a composite environmental index, the selection of a given discount rate is highly subjective and should represent the decision maker beliefs in terms of intergenerational aspects. Finally, the SC network design-planning problem whose objective is to optimize a given set of objective functions can be mathematically posed as follows: SC 2002 Min  NPV , DamC g , Impactoverall   ,

subject to Eqns. (1) to (27)

 {0,1};     Here X denotes the binary variables set, while Y corresponds to the continuous variable set.

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4. CASE STUDY: A SUPPLY CHAIN FOR MALEIC ANHYDRIDE The case study used to illustrate the concepts behind the presented strategy addresses a SC design problem comparing different technologies for maleic anhydride (MA) production. MA is an important raw material used in the manufacture of phthalic-type and unsaturated polyester resins, co-polymers, surface coatings, plasticizers and lubricant additives (USEPA, October 1980). Two main technologies are available for its manufacture by catalytic oxidation of different hydrocarbons, benzene or butane (Chen and Shonnard, 2004). Main process reactions are as follows:

3

4

Butane Route : C4 H 8  3O2  C4 H 2O3  3H 2O

(28)

Benzene Route : C6 H 6  4.5O2  C4 H 2 O3  2CO2  2 H 2 O

(29)

This could lead to a non-equitable distribution of costs and benefit through time by forcing future generations to bear a disproportionate cost. A project should be undertaken if the size of benefits is such the gainers could compensate the losers in theory though compensation would not have to be actually carried out.

Environmental Considerations into Strategic and Tactical Planning

19

From an atom economy point of view (Domenech et al., 2002), the procedure considering the conversion of butane/butene is more environmentally friendly (see Eq. (28)), because all butene C atoms end up as MA, while for benzene reaction (see Eq. (29)), only 67% of C atoms are converted into MA. Also for the butane reaction, the oxygen efficiency is greater than in the benzene reaction (50% vs. 33%); just in terms of hydrogen consumption benzene reaction renders a higher atom efficiency than butane reaction (33% vs. 25%). Several factors such as advances in catalyst technology, increased regulatory pressures, and continuing cost advantages of butane over benzene have led to a rapid conversion of benzene- to butanebased plants, consequently to the conversion of the whole MA SC (Felthouse et al., April 26, 2001). The SC under study comprises raw material extraction facilities, processing sites, distribution centers and marketplaces, fitting a cradle to distribution center approach. Different raw material suppliers are modeled considering that each of them provides the same commodities quality, but the production is performed using different technologies. Two technologies can be implemented: (i) based on benzene (MA Technology 1) and (ii) based on butane (MA Technology 2) feedstock. Table 2 shows raw materials requirements for each of these technologies. Table 2. Different raw material consumption (sij) per kg of MA, based on literature data. (EcoinventV1.3, 2006) Technology

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Electricity consumption [kWh] Propane-butane [kg] Benzene [kg] CO2 direct emissions [kg]

MA Technology 1 Benzene based 0.540 0.000 1.026 1.800

MA Technology 2 n-Butane based 1.08 0.99 0.00 3.87

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José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner

Figure 2. SC node location in the proposed case study. Bt1 and Bt2 show n-butane suppliers, Bz1 and Bz2 show benzene suppliers; Site1-3 show possible MA production sites and M1-5 are possible markets for MA sale. Number in parenthesis below node name shows general node numbering fc1-14

MA Tech 2 (Butane)

Benzene, Supplier 2 (pyrolisis-gasolineRotterdam-fc4)

n-Butane Supplier 1 (refinery-Rotterdamfc6)

n-Butane Supplier 2 (proxy mix-Le Havrefc5)

kg C2H3Cl kg C2H3Cl

1.4E-09 2.7E-04

0.0E+00 0.0E+00

3.9E-01 1.4E-02

2.0E-01 8.9E-04

6.3E-03 7.6E-03

9.1E-02 7.5E-03

kg PM2.5

0.0E+00

0.0E+00

4.3E-03

1.3E-03

8.1E-04

1.5E-03

Bq C-14

0.0E+00

0.0E+00

1.3E+01

5.9E-03

9.3E+00

2.2E+01

kg CFC-11

0.0E+00

0.0E+00

2.4E-07

2.9E-11

4.7E-07

1.4E-07

kg ethylene kg TEG water

7.9E-06 8.8E-07

1.3E-05 2.3E-07

9.2E-03 1.5E+02

9.2E-04 6.0E+01

8.5E-04 1.5E+02

1.4E-03 1.0E+02

kg TEG soil

1.7E-07

3.2E-07

3.4E+01

2.4E-02

3.1E+01

1.7E+01

kg SO2 m2org.arable kg SO2

0.0E+00 0.0E+00 0.0E+00

0.0E+00 0.0E+00 0.0E+00

2.5E-02 2.0E-02 6.6E-03

3.8E-02 1.4E-05 8.3E-03

1.5E-02 3.4E-03 6.3E-03

3.9E-02 4.8E-03 9.4E-03

Benzene, Supplier 1 (coke plant-Bilbaofc3)

MA Tech 1 (Benzene)

Carcinogens Non-Carcinogens Respiratory inorganics Ionizing radiation Ozone layer depletion Respiratory organics Aquatic ecotoxicity Terrestrial ecotoxicity Terrestrial acid/nutri Land occupation Aquatic acidification

Unit

Impact category

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Table 3. Environmental impact for 1 kg of MA production (not considering raw materials nor transport) and raw materials production ( ijff ' a ) (EcoinventV1.3, 2006)

Environmental Considerations into Strategic and Tactical Planning Aquatic eutrophication Global warming Non-renewable energy

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Mineral extraction

21

kg PO4 P-lim

5.4E-04

5.4E-04

1.6E-05

4.4E-06

3.5E-04

4.4E-04

kg CO2eq. MJ primary energy MJ surplus energy

1.8E+00

3.9E+00

6.4E-01

1.4E+00

5.6E-01

1.6E+00

0.0E+00

0.0E+00

5.4E+01

7.1E+01

5.6E+01

6.7E+01

0.0E+00

0.0E+00

3.4E-03

2.5E-04

2.6E-03

1.5E-02

A simplified potential network is proposed and restricted to Europe (see Figure 2). Tarragona (Site1-fc7), Estarreja (Site2-fc8) and Drusenheim (Site3-fc9) are considered to be possible facilities location nodes. Benzene is supposed to be available at Bilbao (Bz1-fc3) and Rotterdam (Bz2-fc4), while n-butane can be supplied from again Rotterdam (Bt1-fc6) and Le Havre (Bt2-fc5). MA is supposed to be sold at four markets located at Madrid (M1-fc10), Paris (M2-fc11), Munich (M3-fc12), Lisbon (M4-fc13) and Barcelona (M5-fc14). The environmental impacts associated to MA production without consideration of raw material production, transportation and electricity consumption are found in Table 3. Two potential benzene suppliers are considered, benzene can be obtained from a coke plant (Benzene Supplier-Tech 1-Bz1), or from a 50% mixture of ethylene reforming and pyrolysis gasoline (Benzene Supplier-Tech 2-Bz2). For the case of butane production, two suppliers are considered, one that is a proxy model obtained from a European typical refinery (Butane Supplier-Tech 1-Bt1-fc6), and another one from a mixture of the top 20 most important organic chemicals (Butane Supplier-Tech 2-Bt2-fc5). The LCI values were retrieved from the LCI database EcoinventV1.3 (2006) and using SimaPro 7.1.6 (PRe-Consultants-bv, 2008), were converted directly to the IMPACT 2002+ mid-point indicators. The environmental impact for raw material production can be also found in Table 3 which does not consider impacts associated to transportation. Two different types of transportation services are assumed to be available: Lorries in two different sizes (16 and 32 ton). Benzene is a chemical that is liquid at standard conditions and therefore stored and transported as a liquid. Butane, on the other hand, is a gas at standard conditions and therefore needs to be liquefied in order to be transported and stored. In this case butane liquefaction has been considered during its production, and consequently both products are transported in liquid state, with similar environmental impacts by the same kg·km. Regarding electricity consumption, medium voltage electricity production from different countries grid is considered. Environmental impacts associated to transport services and electricity consumption are found in Table 4. Raw material, electricity, product and transportation prices were estimated from current economical trends, see Table 5 and 6. For the case of NPV optimization return rate is assumed to be 25%. Capital investment associated to equipment and its operating costs are based on previously published results which were obtained using process simulation of different MA production flow sheets (Chen and Shonnard, 2004). These figures are from a design basis of 2.27x107 kg of MA/year (see Table 7). Thirty-seven monthly planning periods are considered. The model has been implemented in GAMS which is algebraic modeling software (Brooke et al., 1998). The formulation of the SC-LCA model leads to a MILP with 15440 equations, 137652 continuous variables, and 1093 discrete variables. It takes 13.2 CPU s to reach a solution with a 0% integrality gap on a 2.0 GHz Intel Core 2 Duo computer using the MIP solver of CPLEX (ILOG-Optimization, 2008).

22

José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner T

Table 4. Environmental impact associated to transport services (ija) and electricity production (ijff'a), for typical European countries. (EcoinventV1.3, 2006) Impact category

Carcinogens Non-Carcinogens Respiratory inorganics Ionizing radiation Ozone layer depletion Respiratory organics Aquatic ecotoxicity Terrestrial ecotoxicity Terrestrial acid/nutri Land occupation Aquatic acidification Aquatic eutrophication Global warming Non-renewable energy Mineral extraction

Unit

kg kg kg PM2.5 Bq C-14 kg CFC-11 kg C2H2 kg TEG water kg TEG soil kg SO2 m2org-arable kg SO2 kg P-lim kg CO2 MJ primary MJ surplus

Transport lorry 32ton [tn·km] 1.2E-03 2.4E-03 2.8E-04 1.4E+00 2.3E-08 1.7E-04 1.8E+01 1.1E+01 7.6E-03 1.3E-03 1.2E-03 1.6E-05 1.6E-01 2.8E+00 1.3E-03

Transport lorry 16ton [tn·km] 2.0E-03 3.9E-03 6.5E-04 3.8E+00 4.9E-08 6.7E-04 3.2E+01 1.8E+01 1.5E-02 4.7E-03 2.4E-03 3.4E-05 3.6E-01 6.0E+00 1.9E-03

Electricity supplier 1 [kWh] 1.6E-04 1.4E-04 3.7E-05 1.1E-01 5.1E-09 1.1E-05 1.9E+00 5.2E-01 8.7E-04 5.8E-05 3.0E-04 2.0E-06 5.2E-02 7.4E-01 6.8E-05

Electricity supplier 2 [kWh] 1.4E-04 1.4E-04 2.8E-05 3.8E+00 1.7E-09 4.1E-06 1.9E+00 3.4E-01 5.0E-04 7.3E-05 1.9E-04 5.3E-07 3.6E-02 8.2E-01 9.0E-05

Table 5. Raw material prices available at different suppliers (est),

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and MA mean prices available at different markets (Pricesft) Commodities Supplier-Tech 1 Supplier-Tech 2 Benzene [kg] Supplier-Tech 1 (Coke plant – Bilbao – fc3) Supplier-Tech 2 (Pyrolisis gasoline – Rotterdam – fc4) Butane [kg] Supplier-Tech 1(Refinery – Rotterdam – fc6) Supplier-Tech 2 (Proxy – Le Havre – fc5) Maleic anhydride [kg] Electricity [kWh]

Table 6. Raw materials and product transportation cost ($ 10 Raw Material (RM) Benzene MA Butane

Transport Cost (32 ton) 2.99 2.75 4.25

4

Price/cost [$] 0.057 0.038 0.171 0.214 0.224 0.280 1.672 tr /(km·kg ) , efft )

Transport Cost (16 ton) 2.69 2.48 3.83

FJ ut 1 Table 7. Facilities capital investment (Pricejft ) and operating cost (  ijfe ), $1107

Environmental Considerations into Strategic and Tactical Planning

Capital investment Operating cost

MA Technology 1 Benzene based 1.61 1.42

23

MA Technology 2 n-Butane based 1.95 1.30

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In order to evaluate comparable alternatives, the first step has consisted on determining a SC which maximizes NPV, which is used to fix a total production rate. From the supplied data, it is found that the production rate should be of 813x103 ton of MA for a 3 years planning horizon. Then, since two objective functions are to be optimized, namely NPV and IMPACT 2002+, the multi-objective optimization procedure known as the weighted sum is followed (Statnikov and Matusov, 1995). In order to be able to make comparisons not only the production rate is the same for both solutions, but the amount of sales has been set to the same Figure The selected figure is the resulting from NPV optimization. Following this procedure, Figure 3 shows the obtained dominant SC that maximizes NPV. It is found that its production is based on benzene feedstock, which is bought from both available suppliers; moreover production of MA is located in Estarreja (fc8) and Drussenheim (fc9). Alternatively, by the minimization of the environmental impact indicator, subject to the same production/sales rate, the resulting SC (Figure 4) uses butane as feedstock and buys raw materials from a single supplier. In this sense n-butane is selectively bought from one single supplier (fc6, refinery in Rotterdam) and is processed at all three possible manufacturing sites (fc7-fc9). Arrows width in figures 3 and 4 shows activity level. Tables 8 and 9 summarize the most significant values corresponding to both solutions regarding environmental and economic aspects.

Figure 3. SC configuration for the most profitable SC option (NPV optimization). Arrows width shows activity level. It shows a benzene based SC with production of MA located in Estarreja (fc8) and Drussenheim (fc9)

24

José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner

Figure 4. SC configuration for the most environmental friendly option (overall impact 2002+ optimization). Arrows width shows activity level. It shows that n-butane is selectively bought from one single supplier (fc6, refinery in Rotterdam) and is processed in all three possible manufacturing sites (fc7-fc9)

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Table 8. Environmental impacts arising from single economic and overall environmental objective function optimization results [Impact 2002+ pts] End-point impact category Human Health Ecosystem Quality Climate Change Resources Impact 2002+ SC-structure

Impact 2002+ Optimization Normalized Direct value value 7.87E+02 1.11E+05 3.55E+08 2.59E+04 3.85E+09 3.89E+05 4.94E+10 3.26E+05 8.52E+05 Figure 4

NPV Optimization Normalized Direct value value 3.03E+03 4.27E+05 3.35E+08 2.45E+04 2.62E+09 2.65E+05 5.69E+10 3.76E+05 1.09E+06 Figure 3

Table 9. Economic aspects arising from single objective optimization (NPV and Impact 2002+). [m.u.]

Economic aspect Investment Raw Material Cost

Impact2002+ Optimization Non Discounted discounted 1.61E+08 1.61E+08 2.28E+08 1.59E+08

NPV Optimization Non Discounted discounted 1.09E+08 1.09E+08 2.31E+08 1.61E+08

Environmental Considerations into Strategic and Tactical Planning RM Transport Cost Product Transport Cost Production cost Fixed cost Sales Profit NPV IRR

4.52E+08 7.92E+07 4.69E+08 3.62E+07 1.36E+09 -6.56E+07

3.15E+08 5.53E+07 3.27E+08 2.53E+07 9.50E+08 -9.44E+07 -31.06%

1.37E+08 1.08E+08 5.10E+08 2.91E+07 1.36E+09 2.37E+08

25

9.36E+07 7.52E+07 3.56E+08 2.03E+07 9.50E+08 1.32E+08 99.10%

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Figure 5 shows the distribution of the environmental impacts along SC echelons for these two cases, this kind of analysis are the ones that entail the fourth step of the LCA methodology. According to Bauman and Tillman (2004), most LCA studies show that the production of materials often causes a dominant proportion of the environmental impact of a product, whereas assembly often causes a very minor proportion. However, if the product requires energy during its use phase, this phase often dominates the environmental profile, whereas if the product is used in a more passive way, the production phase dominates; notably the production of materials. In spite of transport being a major source of pollution in society, transportation and distribution often contribute less to the environmental impact than expected. In the presented case study raw material production is the most important factor contributing to the overall environmental impact in both single objective optimization cases; while electricity consumption and transportation are the least impacting aspects. This clearly shows that activities to reduce environmental impact should be focused on raw material production echelon. Moreover, from Figure 5, it can also be concluded that if raw material production would be disregarded then different solutions would be obtained, thus showing the influence of ―purchase‖ decisions on the environmental impact of a SC.

Figure 5. Distribution of environmental impacts for single objective optimization solutions, according to different SC activities and end-points

26

José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner

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Figure 6. Distribution of costs for single objective optimization solutions, distributed in different SC activities

In the case of minimization of environmental impact, a negative NPV and Internal rate of return (IRR) are found. If the costs are analyzed it can be seen (Figure 6 clarifies this situation), that raw material transportation cost associated to environmental impact minimization is significantly higher and is the most significant difference between economic and environmental optimizations. This difference is due to the following reasons: butane suppliers locations are far from production facility locations, butane transport cost is 42% higher than benzene cost, and the environmental impact optimization selects lorries of 32tons which are less polluting, but more expensive (see table 5). The second and third biggest differences between the obtained solutions are regarding investment and fixed operating costs which also penalize butane based production. A comparison of the distribution of environmental impacts can be seen in Figure 7.

Environmental Considerations into Strategic and Tactical Planning

27

Figure 7. Distribution of environmental impacts along SC activities and end-point categories for single end-point environmental optimization

Table 10. Single end-point optimization results distributed along different environmental end-point metrics. Last row presents the resulting overall Impact 2002+ [Impact 2002+ pts].

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End-point indicator Human Health Ecosystem Quality Climate Change Resources Impact 2002+ SC configuration SC raw materials

Human Health Optimization 110953 25946 388736 326140 851776 Figure 7 (a) n-Butane

Ecosystem Quality Optimization 210863 12633 293764 418723 935983 Figure 7 (b) Benzene

Climate Change Optimization 520133 27337 219817 320895 1088183 Figure 7 (c) Benzene

Resources Optimization 353555 24271 279434 315826 973085 Figure 7 (d) n-But+Ben

Table 11. Environmental impact associated to different SC activities for single end-point optimization [Impact 2002+ pts]. SC activity Raw mat. Production Product manufacturing Transport Raw Mat. Transport Prod. Electricity

Human Health Optimization 427169 318002 75313 20470 10822

Ecosystem Quality Optimization 684044 147994 73128 25406 5411

Climate Change Optimization 862463 147994 46546 25770 5411

Resources Optimization 695986 213013 34968 20401 8717

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28

José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner

Tables 10 and 11 show the solutions associated to the cases in which each end-point indicator is optimized. Table 10 rows show, as expected, that the minimum value for each of the partial environmental impacts is obtained by the optimization of such objective function. The solution obtained by optimization of the human health end-point is the same as the one obtained when optimizing the overall Impact 2002+, a SC based on butane as in Figure 4 and Figure 8 (a). One of the reasons for this is due to the fact that the weighting and normalization coefficients for that end-point value are the largest in the methodology. Interestingly, each one of the other end-point optimizations provides with a different SC structure, see Figures 8 (b,c,d). In the case of ecosystem quality and climate change optimization (Figures 7 b and c), the production is based on benzene and the SC structures are similar to the one depicted in Figure 3. The difference between solutions is the MA production load on each different site and the benzene supplier which in the case of ecosystem quality is the provider that uses pyrolisis gasoline (fc4 located in Rotterdam) and the case of minimisation of climate change is a coke plant (fc3 located in Bilbao). Please note that arrows widths are wider in the case of nodes close to the supplier, to minimise environmental impact from transportation. In the case of resources impact optimization it is based on a combined use of benzene and butane technologies (see Figure 8(d)). Regarding the optimization of ecosystem quality and climate change, they both show minimum amount environmental impact due to electricity. One alternative to reduce SC environmental impacts may be to look for new feedstock providers whose production processes are more environmental friendly. It is also important to notice that Human Health impacts are considerable high in both solutions. In the case of NPV optimization this fact is due to benzene toxic properties. It is expected that CO2 emissions trading considerations will make the butane based production more economically attractive. This aspect is analyzed in the next section. There is SC-structure dependence against its total production. Other works related to SC design and environmental issues consider that demand must be completely fulfilled. This assumption leads to an invariable total production rate and suboptimal solutions. In Figure 9 iso-production/sales curves correspond to solutions following this assumption. For these cases minimum overall impact always leads to negative NPVs. These solutions are obviously dominated by the zero-production/sale solution (origin). This trade-off is absolutely necessary. Regardless of emissions, every productive sector has a ―break-even‖ point below which ―profit‖ becomes negative. It establishes the minimum production capacity required to make a profitable business. Further analysis on this issue is presented later. The actual Pareto curve is shown in Figure 9 as a continuous black line which is obtained by allowing unfulfilled demand (i.e. not considering a fixed required amount). It can be seen that positive NPVs can be achieved by reducing the MA production.

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Environmental Considerations into Strategic and Tactical Planning

(a)

(b)

(c )

(d)

29

Figure 8. a,b,c,d. Different SC configurations obtained from the optimization of each end-point indicator, (a) Human Health, (b) Ecosystem quality, (c ) Climate change and (d) resources

In order to explicitly consider the conflict between environmental and economic issues, here the overall impact indicator has been optimized against NPV for different production

30

José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner

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amounts. Results obtained in this way draw a clear picture of the problem, which is basic for a more objective selection among the different alternatives. As it can be observed (see Figure 8 and 9), the multi-objective optimization results in a set of Pareto solutions, connecting lines do not represent solutions, and only the vertices of the curve are feasible SC alternatives. Within this set of non-dominated solutions the decision maker must select one. The stake holder‘s selected solution will depend on the weights that he/she subjectively assigns to each of the objectives (i.e., NPV and Impact2002+). Several multi-attribute decision analysis (MADA) techniques are available for this purpose, for a review of these techniques the reader is referred to the work of Seppälä et al. (2002). With regards to the effect of interest rate on the optimal SC configuration, an analysis was performed by increasing gradually the annual interest rate from 0% to 40%, while optimizing the NPV. The obtained results are shown in Figure 10. Figure 10 shows that for interest rates lower than 7.5% one SC structure is found. This SC is based on the installation of benzene and butane based production technologies and is similar to the one shown in Figure 8d. For values of interest rate greater than 7.5% the optimal NPV SC is based on the production of MA from benzene only and has the same structure as the one shown in Figure 3. It is worth emphasizing that in this case increases in the interest rate will render solutions that prioritize early cash flows rather than end of project ones.

Figure 9. Iso-production/sales curves for different production amounts based a per-centage of best NPV sales value. Continuous line shows Pareto frontier for overall envi-ronmental impact vs. NPV

Environmental Considerations into Strategic and Tactical Planning

31

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Figure 10. Net present value optimization results for different values of interest rate

4.1.1. CO2 emission trading considerations In order to take into account CO2 emissions, values for maximum free emissions caps must be available. One possible way of assessing such value is to take the best available technology (BAT) in terms of CO2 emissions. Chen and Shonnard (2004) have studied both MA production schemes finding through simulation optimum flow sheets (see Table 12). Given that their data does not consider steam co-production, the BAT value has been increased accordingly (32%), in order to be comparable to the one reported by EcoinventV1.3 (2006). It has been found that producing MA from butane has the lowest CO2 emissions and will be used to set the free emission quota available. Tier 1, Tier 2 and Tier 3 CO2 emissions were retrieved from EcoinventV1.3 (2006). In the economic formulation it is considered that CO2 emissions credits are bought at the end of each year in order to cope with CO2 emissions that exceed the maximum allowed considered using the BAT. The trading cost and price of emission rights is considered as US$23 which is a proxy of the values currently found in the trading market. Table 12. CO2 emissions associated to the production of 1 kg of MA (EcoinventV1.3, 2006), and BAT data (MaxCO2t) adopted from Chen and Shonnard (2004).

BAT Tier 2 CO2 emissions [kg] Tier 1 CO2 emissions [kg] Tier 2 CO2 emissions [kg] Tier 3 CO2 emissions [kg]

MA Technology 1 Benzene based 3.41 1.80 2.05 3.53

MA Technology 2 n-Butane based 3.02 3.87 4.38 4.93

32

José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner

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Figure 11. Emissions allocation along the SC for the maximum NPV configuration, the minimum overall impact configuration, and minimum emissions

It is noteworthy that the optimal SC configuration considering the emissions trading scheme remains equal to the one obtained when optimizing NPV without this consideration (Figure 3) independently of the free emissions cap and the emission right price. Let us recall that the minimum overall environmental impact is achieved by installing butane based technologies, while the most profitable is based on benzene as feedstock. The CO2 emission allocation along the SC is depicted in Figure 11 for the maximum NPV, minimum overall impact, and minimum CO2 emissions network configurations, optimized taking into account the CO2 trading scheme. The least CO2 pollutant configuration is based on benzene technology. It can be observed from this figure that the optimal overall impact configuration (butane based) is the one that emits more CO2, most of it coming from the MA production. Under the trading scheme this configuration would be strongly penalized. As aforementioned, it was expected that regulatory pressures would lead to a conversion of benzene- to butanebased plants since benzene is considered to be more environmental harmful. Actually, benzene based SCs show greater overall impact (see Table 8 and 10), being human health their more impacting damage category due to benzene‘s carcinogenicity. However, a CO2 trading emission scheme as the one modeled in the case study will not cause benzene based production to move towards butane; on the contrary, it can be a factor leading to change butane based into benzene based MA production.

4.1.2. Product and raw material subsidies From the results found from single objective optimization of NPV and Impact 2002+, it was found that an IRR of nearly 100% is associated to a MA production SC based on

Environmental Considerations into Strategic and Tactical Planning

33

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benzene, while production based on butane is the most environmentally friendly but is not profitable (see Table 8). Another possible way of solving this issue, instead of taxes on CO 2, is to have a government subsidy on the production of MA based on butane. This subsidy could be of different forms which can be grasped from the distribution of cost in Figure 6. In this sense the possible options are (i) increase of MA selling price, (ii) a decrease in the cost of production of MA and (iii) decrease of butane and MA related transportation costs. Points (i) and (ii) are similar, in the sense that both are based on the kg of MA produced. Figure 12 shows the change in the IRR value for the SC based on butane when increasing the subsidy per kg of MA produced. Table 13 shows the MA government subsidies results for different IRR values.

Figure 12. IRR values for different amount of government subsidy based on MA production

Table 13. Current and possible MA prices and production government subsidies IRR [%] -31.1% 0.0% 25.0% 99.1%

MA subsidized price [$/kg] 1.672 1.753 1.835 2.142

Operating cost subsidy [$/kg] 0.000 0.081 0.163 0.470

34

José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner Table 14. MA and n-butane transportation cost with and without government subsidies IRR [%]

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-31.1% 0.0% 25.0% 99.1%

Butane subsidy [$/kg·km] 0 6.17E-05 1.27E-04 3.89E-04

Butane Transport Cost [$/kg·km] 4.25E-04 3.63E-04 2.98E-04 3.56E-05

MA subsidy [$/kg·km] 0 2.28E-04 4.69E-04 1.43E-03

MA Transport Cost [$/kg·km] 2.75E-04 4.73E-05 -1.94E-04 -1.16E-03

Figure 13. IRR values for different amount of government subsidy based on transports of MA and butane

In the case of transportation costs associated to MA and n-butane, Table 14 and Figure 13 show the obtained results. The analysis was performed considering one single transport being subsidized, and it is found that a subsidy on butane transportation is more efficient than one on MA. However in both cases in order to make the butane based SC equally profitable than the benzene one, government subsidies are bigger than the actual transportation cost (negative values in Table 14 indicate a higher subsidy than the cost). On the contrary in the case of a subsidy on MA production or sale price, a subsidy of 0.538 €/kg of butane (being it as sales price or operating cost reduction) will make the butane based SC as profitable as the one based on benzene.

Environmental Considerations into Strategic and Tactical Planning

35

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5. CONCLUSION This chapter presents an approach for designing and planning environmentally friendly and profitable SC. The model consists of a multi-period MILP that accounts for the multiobjective optimization of economic and environmental interventions. The model considered the long-term strategic decisions (e.g., installation of plants, selection of suppliers, manufacturing sites, and distribution centers) with the mid-term planning for SCs. Each endpoint damage categories was considered as an objective function in order to avoid the subjectivity associated with their aggregation into an overall environmental impact indicator, showing the various SC possibilities obtained for each indicator. The Impact2002+ metric was adopted as a measure of overall environmental impact. Moreover, joint consideration of end point damages and trading schemes enables the proposed approach to support (i) assessment of current regulatory policies and (ii) definition of more adequate policy parameters (e.g., free emissions allowance cap for each industry, emissions trading price, subsidies). A maleic anhydride SC case study is presented where two potential technologies are available. Two problems were solved, a first approach that did not consider CO2 trading scheme and a second one (see subsection 2.2) that took it into account. We have shown the possibility of tackling such problems with ease. A SC for MA production based on butane was found to be more environmentally friendly than one based on benzene. In this sense the current model allowed for possible selection between obtained optimal solutions. Most of the works related to SC and environmental issues consider a fixed production/demand; it was demonstrated that such constraint leads to dominated solutions. By allowing unsatisfied demand, the actual Pareto curve was obtained. Raw material production was found to be the most important contributor to overall environmental impact, while transportation and electricity consumption were the least important. This clearly shows that the current model allows for selection of improvement actions and the necessity for an approach with visibility of the whole SC. Recall the environmental impact potential significant dependence on ―purchase decisions which cannot be assessed without a SC approach. Additionally, it was determined by using the optimization model that the production process was the activity that emits the most CO2. Additionally, the model may help to discover interesting facts. For example, it turns out that the CO2 trading scheme will favor benzene-based over butane-based production. The results obtained for this specific case study question the suitability of a single CO2 trading scheme applicability to every industry sector: different regulatory schemes may be required in different industrial scenarios. Current regulations merely consider climate change damage which certainly is a very important factor but other aspects such as human health, ecosystem quality and abiotic resources usage should be also considered so that effective industrial changes regarding the environment are induced. In this sense the utilization of a multiobjective optimization for each damage category has shown to be helpful at discovering insights regarding how different policies will affect SC strategic and tactical decisions. We believe that one of the main achievements of this work is not building and solving a complex SC-environmental model, instead it is to emphasize the dangers related to deploying CO2 emission related policies in isolation from other pollution related issues. Also, it has been shown how this type of model can be used to determine subsidies policies in order to actually

36

José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner

drive industry towards more environmental practices. On the other hand, it is important to point out that environmental metrics for the interpretation of life cycle inventories involve determining aggregated measures. Usually, normalizing factors are used to determine the weight of each damage factor (climate change, human health, resources depletion, ecosystem quality) in the overall measure which may favor different solutions. When this type of analysis is performed for the selection among different design alternatives, which will be active during a long time horizon, a careful sensitivity/uncertainty analysis related to the application of these normalizing factors is required. Such analysis can be done by using a multi-criteria optimization that accounts for end-point damage categories as presented in this chapter. Obviously, nowadays the environmental impact associated with SC decisions at all levels is of high significance. However, approaches that address the environmental impact evaluation at the operational level (scheduling and distribution) are scarce. On the other hand, as stated by Papageorgiou (2009), there is an increasing interest in reverse logistics and closed loop SCs mainly because they are expected to diminish firms‘ environmental burden. Notwithstanding, most of the approaches developed so far do not assess the environmental reward or impact of such kind of operations (Fleischmann et al., 2001; Schultmann et al., 2003; Amaro & Barbosa-Póvoa, 2008). Further work should be focused on the consideration of uncertainty, which is an important factor that may influence the decisions regarding trading schemes. Another potential extension is to analyze how decisions related to the short-term may contribute to reduce environmental burdens.

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ACKNOWLEDGMENTS Financial support received from the Agencia de Gestió d‘Ajuts Universitaris i de Recerca (AGAUR) from Generalitat de Catalunya and Fons Social Europeu (EU), through FI grants and European Community (projects PRISM-MRTN-CT-2004-512233 and ECOPHOS-INCOCT-2005-013359) is fully appreciated. Besides, financial support from Xartap (I0898) and ToleranT (DPI2006-05673) projects with FEDER (EU) associated grant is gratefully acknowledged.

NOTATION Indices

e f, f i j s t, t

suppliers facility locations tasks equipment technology materials (states) planning periods

Environmental Considerations into Strategic and Tactical Planning

a g w

r l

(Continued) mid point environmental impact categories end point environmental impact categories possible waste treatment sinks considered reports for environmental compliance considered environmental liabilities

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Sets

Ag

set of midpoint environmental interventions that are combined into endpoint damage factors g

Erm

set of suppliers e that provide raw materials

Eˆ prod

set of suppliers e that provide production services

Etr

set of suppliers e that provide transportation services

Fe

set of locations f where supplier e is placed

FP Ij

set of materials s that are final products

Je

technology j that is available at supplier e

J f

technology j that can be installed at location f

Ji

technologies that can perform task i

Mkt RM Sup

set of market locations

TL

set of periods when the emissions trading is executed

Ts

set of tasks producing material s

Ts

set of tasks consuming material s

Tr

set of distribution tasks

set of tasks i that can be performed in technology j

set of materials s that are raw materials set of supplier locations

Parameters

Asft

maximum availability of raw material s in period t in location

Demsft

demand of product s at market f in period t

f co

Costt

2

distance ff 

emissions right cost in period t distance from location f to location f 

37

38

José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner

FCFJ jft I ftJ

(Continued) fixed cost per unit of technology j capacity at location f in period t investment required to establish a processing facility in location f in period t

MaxCO2t

free allowance emissions cap at period t

NormFg

normalizing factor of damage category g

Pricesft

price of product s at market f in period t

co

Pricet

2

PriceWT w WT wt

emissions right price in period t price for residues treatment to sink w

Flow

Mass flow of residues to treatment sink w at period t

FreqOccrt

frequency of occurrence of report r during period t

CostDocr

cost for the generation of the required documents r

FreqLiabilitylt

frequency of occurrence of liability l during period t

CostFinel

cost associated to the expected liability l

Price Jjft

investment required per unit of technology j capacity increased

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at facility f in period t

rate  sij

discount rate mass fraction of task i for production of material s in equipment j

 sij

mass fraction of task i for consumption of material s in equipment j

 jf

minimum utilization rate of technology j capacity that is allowed at location f

 ag ijff  efftr t ut1  ijfet

ut 2  sfet

g end-point damage characterization factor for environmental intervention a capacity utilization rate of technology j by task i whose origin is location f and destination location f  unitary transportation costs from location f to location f  during period t unitary cost associated with task i performed in equipment j from location f and payable to external supplier e during period t unitary cost associated with handling the inventory of material s in location f and payable to external supplier e during period t

Environmental Considerations into Strategic and Tactical Planning (Continued) unitary cost of raw material s offered by external supplier e in period t a environmental category impact CF for task i performed using technology j receiving materials from node f and delivering it

 est  ijff a

at node f  T  ija

a environmental category impact CF for the transportation of a mass unit of material over a length unit Binary Variables 1 if technology j is

V jft

installed at location f in period t , 0 otherwise Continuous Variables co2 amount of emissions extra rights Buyt bought in period t normalized endpoint damage g for DamC gft

location f in period t

FAssett

normalized endpoint damage g along the whole SC economic value of purchases executed in period t to supplier e economic value of sales executed in period t investment on fixed assets in period t

FCostt

fixed cost in period t

Fjft

total capacity of technology j during

DamC gSC

EPurchet

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ESalest

period t at location f capacity increment of technology j at

FE jft

location f during period t

ICaft

midpoint a environmental impact associated to site f which rises from activities in period t

Impact 2002 f

total environmental impact for site f

2002 Impactoverall

co

Nett

2

total environmental impact for the whole SC Net income due to emissions trading in period t

39

40

José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner (Continued) Net cost associated to type 2 and 3

Nettenv

t

CosttWT

CosttCompliance CosttEnvLiabilities

NPV Pijff t

environmental costs in trading period Environmental type 2 cost related to waste treatment for period t Environmental type 2 cost related to environmental compliance for period t Environmental type 3 cost related to possible environmental liabilities for period t net present value

activity magnitude of task i in equipment j in period t whose origin is location f and destination location

f

Profitt Purchetpr rm et

Purch

Purchettr co2

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Salest

Salessff t S sft

profit achieved in period t amount of money payable to supplier

e in period t associated with production activities amount of money payable to supplier e in period t associated with consumption of raw materials amount of money payable to supplier e in period t associated with consumption of transport services amount of emissions rights sold in period t amount of product s sold from location f in market f  in period t amount of stock of material s at location f in period t

Superscripts

L U

lower bound upper bound

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Alexander, B., Barton, G., Petrie, J. & Romagnoli, J. (2000). Process synthesis and optimization tools for environmental design: methodology and structure. Computers and Chemical Engineering, 24, 1195-1200. Amaro, A. C. S. & Barbosa-Póvoa, A. P. F. D. (2008). ―Planning and scheduling of industrial supply chains with reverse flows: A real pharmaceutical case study.‖ Computers & Chemical Engineering, 32, 2606-2625. Azapagic, A. (1999). Life cycle assessment and its application to process selection, design and optimisation. Chemical Engineering Journal, 73, 1-21. Azapagic, A. & Clift, R. (1999). The application of life cycle assessment to process optimisation. Computers and Chemical Engineering, 23, 1509-1526. Bauman, H. & Tillman, A. M. (2004). The Hitch Hiker‘s Guide to LCA. Student litteratur AB, Lund Sweden. Bare, J. C, G. A., Norris, D. W., Pennington, & McKone, T. (2003). ―TRACI, The Tool for the Reduction and Assessment of Chemical and Other Environmental Impacts.‖ Journal of Industrial Ecology, 6, no. 3-4, 49-78. Bartelmus, P. (2002). Environmental accounting and material flow analysis, In A Handbook of Industrial Ecology, Edward Elgar, Ch. 14, 165-176. Brennan, D. (2007). Life-Cycle Evaluation of Chemical processing plants, In: Environmentally Conscious materials and Chemical processing, New York: John Wiley and Sons, Inc., Vol. 1, Ch. 3, 59-88. Brooke, A., Kendrik, D., Meeraus, A., Raman, R. & Rosenthal, R. E. (1998). GAMS - A User‘s Guide. GAMS Development Corporation, Washington. Butner, K., Geuder, D. & Hittner, J. (2008). Mastering carbon management: Balancing tradeoffs to optimize supply chain efficiencies. IBM Institute for Business Value GBE03011USEN-00. Chen, H. & Shonnard, D. R. (2004). Systematic framework for environmentally conscious chemical process design: Early and detailed design stages. Industrial & Engineering Chemistry Research, 43, 535-552. Chakraborty, A., Colberg, R. & Linninger, A. (2003). ―Plant-Wide Waste Management. 3. Long-Term Operation and Investment Planning under Uncertainty.‖ Industrial & Engineering Chemistry Research, 42, 4772-4788. Chakraborty, A., Malcolm, A., Colberg, R. & Linninger, A. (2004). ―Optimal waste reduction and investment planning under uncertainty.‖ Computers & Chemical Engineering, 28, 1145-1156. Constable, D. J., Jimenez-Gonzalez, C. & Lapkin, A. (2009). Process metrics In: Green Chemistry Metrics: Measuring and Monitoring Sustainable Processes, John Wiley and Sons, Inc., Ch. 6, 228-247. Domenech, X., Ayllon, J. A., Peral, J. & Rieradevall, J. (2002). How green is a chemical reaction? , application of lca to green chemistry. Environmental Science and Technology, 36, 5517-5520. Emblemsvag, J. (2003). Life-Cycle Costing, using Activity-Based Costing and Monte Carlo Methods to manage Future Costs and Risks. John Wiley & Sons, Inc., EcoinventV1.3, (2006). The ecoinvent database v1.3. Tech. rep., Swiss Centre for Life Cycle Inventories.

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T., Felthouse, J., Burnett, B., Horrell, M. Mummey, & Y. Kuo, (Eds.), April 26, 2001. Kirk Othmer Online. Wiley, Ch. Maleic Anhydride, Maleic Acid And Fumaric Acid, 1-58, http://www.huntsman.com/performance. Finnveden, G., Hauschild, M. Z., Ekvall, T., Guinee, J., Heijungs, R., Hellweg, S., Koehler, A., Pennington, D. & Suh, S. (2009). Recent developments in Life Cycle Assessment, Journal of Environmental Management, 91(1), 1-21. Fleischmann, M., Beullens, P., Bloemhof-Ruwaard, J. M. & vanWassenhove, L. N. (2001). ―The impact of product recovery on logistics network design.‖ Production and Operations Management, 10, 156-173. Freeman, H., Harten, T., Springer, J., Randall, P., Curran, M. & Stone, K. (1992). Industrial pollution prevention: A critical review. Journal of the air and waste management association, 42, 617-656. Gasparatos, A., M el Haram, & Horner, M. (2008). ―A critical review of reductionist approaches for assessing the progress towards sustainability.‖ Environmental Impact Assessment Review, 286-311. Goedkoop, M. & Spriensma, R. (2001). The eco-indicator 99: A damage oriented methods for life cycle impact assessment, methodology report. Tech. rep., Pré Consultants B.V., Amersfoort, The Netherlands. Guillén-Gosálbez, G., Caballero, J. A. & Jimenez, L. (2008). Application of life cycle assessment to the structural optimization of process flowsheets. Industrial & Engineering Chemistry Research, 47, 777-789. Guinee, J., Gorree, M., Heijungs, R., Huppes, G., Kleijn, R., de Konig, A., van Oers, L., Sleeswijk, A., Suh, S., de Haes, H. U., de Brujin, H., van Duin, R., Huijbregts, M., Lindeijer, E., Roorda, A., van-der Ven, B. & Weidema, B. (2001). Life cycle assessment. An operational guide to the ISO standards Part 3: Scientific Background. Ministry of Housing, Spatial Planning and the Environment (VROM) and Centre of Environmental Science - Leiden University (CML). Hart, S. L. (1997). Beyond greening: Strategies for a sustainable world. Harvard Business Review, 75, 66-76. Hauschild, M. & Potting, J. (2004). Spatial differentiation in life cycle impact assessment – the EDIP-2003 methodology. Guidelines from the Danish EPA. The Danish ministry of the Environment. Hertwig, T., Xu, A., Nagy, A., Pike, R., Hopper, J. & Yaws, C. (2002). ―A prototype system for economic, environmental and sustainable optimization of a chemical complex.‖ Clean Technologies and Environmental Policy, 3, 363-370. Heijungs, R. & Suh, S. (2002). The Computational Structure of Life Cycle Assessment. Kluwer Academic Publishers, Dordrecht The Netherlands. Hoeffer, E. (1999). The worst is over. New Steel, 15, 48-51. Hugo, A. & Pistikopoulos, E. (2005). Environmentally conscious long-range planning and design of supply chain networks. Journal of Cleaner Production, 13, 1471-1491. Humbert, S., Margni, M. & Jolliet, O. (2005). October 2005. Impact 2002+: User guide draft for version 2.1. Tech. rep., Industrial Ecology & Life Cycle Systems Group, GECOS, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland. ILOG-Optimization, (2008). Ilog cplex 10.0. Tech. rep., ILOG Optimization. ISO14040, (1997). Environmental management - life cycle assessment - principles and framework. Tech. rep., ISO.

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Khor, C. S., Madhuranthakam, C. & Elkamel, A. (2007). Waste Reduction for Chemical Plant Operations, In: Environmentally Conscious materials and Chemical processing, New York: John Wiley and Sons, Inc., Vol. 1, Ch. 4, 89-123. Klassen, R. D. & Greis, N. P. (1993). Managing environmental improvement through product and process innovation: Implications of environmental life cycle assessment. Industrial and Environmental Crisis Quarterly, 7, 293-318. Klassen, R. D. & Johnson, P. F. (2004). Understanding Supply Chains: Concepts, Critiques & Futures. Oxford University Press, Oxford, UK, Ch. The Green Supply Chain, 229-251. Klöpffer, W. & Rippen, G. (1992). Life cycle analysis and ecological balance: Methodological approaches to assessment of environmental aspects of products. Environmental international, 18, 55-61. Kondili, E., Pantelides, C. C. & Sargent, R. W. (1993). A general algorithm for short term scheduling of batch operations. Computers & Chemical Engineering, 17, 211-227. Laínez, J., Kopanos, G., Espuña, A. & Puigjaner, L. (2009). Flexible design-planning of supply chain networks. AIChE Journal. Laínez, J. M., Guillén-Gozálbez, G., Badell, M., Espuña, A. & Puigjaner, L. (2007). Enhancing corporate value in the optimal design of chemical supply chains. Industrial and Engineering Chemistry Research, 46, 7739-7757. Matthews, H. S., Hendrickson, C. & Weber, C. (2008). The importance of carbon footprint estimation boundaries. Environmental Science & Technology, 42, 5839-5842. Mele, F., Espuña, A. & Puigjaner, L. (2005). Environmental impact considerations into supply chain management based on life-cycle assessment. Innovation by Life Cycle Management LCM 2005 International Conference. Mele, F., Hernandez, M. R. & Bandoni, A. (2008). Optimal strategic planning of the bioethanol industry supply chain with environmental considerations. In: M., Ierapetritou, M. Bassett, & S. Pistikopoulos, (Eds.), Proceedings Foundations of Computer-Aided Process Operations (FOCAPO 2008). CACHE-AIChE-Informs, CACHE Corp, 517-520. Papageorgiou, L. G. (2009). ―Supply chain optimization for the process industries: advances and opportunities.‖ Computers & Chemical Engineering, 33, 1931-1938. Pennington, D., Margni, M., Amman, C. & Jolliet, O. (2005). Multimedia fate and human intake modeling: Spatial versus non-spatial insights for chemical emissions in western europe. Environmental Science and Technology, 39, 1119-1128. PRe-Consultants-bv, (2008). Simapro 7.1.6. Tech. rep., PRe-Consultants-bv. Puigjaner, L. & Guillén, G. (2008). Towards an integrated framework for supply chain management in the batch chemical process industry. Computers and Chemical Engineering, 32, 650-670. Seppälä, J., Basson, L. & Norris, G. A. (2002). Decision analysis frameworks for life-cycle impact assessment. Journal of Industrial Ecology, 5(4), 45-68. K. Sinclair-Rosselot, & D. T. Allen, Eds. (2002). Environmental Cost Accounting In: Green Engineering: Environmentally Conscious Design Of Chemical Processes, Prentice Hall PTR, New Jersey, Ch. 12, 397-416. Singh, A., Lou, H., Yaws, C., Hopper, J. & Pike, R. (2007). ―Environmental impact assessment of different design schemes of an industrial ecosystem.‖ Resources, Conservation and Recycling, 51, 294-313. Srivastava, S. K. (2007). Green supply chain management: A state of the art literature review. Int. J. Manag. Rev., 9, 53-80.

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José Miguel Laínez, Aarón David Bojarski and Luis Puigjaner

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Statnikov, R. B. & Matusov, J. B. (1995). Multicriteria Optimization and Engineering. Chapman and Hall, New York. Steen, B. (1999). ―A systematic approach to environmental priority strategies in product development (EPS). Version 2000 - General system characteristics, CPM report, 1999, 4.‖ Technical report, Centre for Environmental Assessment of Products and Material Systems (CPM), Chalmers University of Technology, Technical Environmental Planning, Göteborg, Sweden. Stefanis, S., Livingston, A. & Pistikopoulos, E. (1995). Minimizing the environmental impact of process plants: A process systems methodology. Computers and Chemical Engineering, 19, S39-S44. Stern, N. (2006). Stern review on the economics of climate change. HM Treasury, London, UK, http://www.sternreview.org.uk/. Schultmann, F., Engels, B. & Rentz, O. (2003). ―Closed-loop supply chains for spent batteries.‖ Interfaces, 33, 57-71. USEPA, (Ed.), October 1980. AP 42, Fifth Edition, Volume I. US Environmental Protection Agency, Ch. Chapter 6: Organic Chemical Process Industry, 6.14-1,6.14-5, http://www.epa.gov/ttn/chief/ap42/ch06/final/c06s14.pdf. Xu, A., Indala, S., A Hertwig, T., W Pike, R., F Knopf, C., L Yaws, C. & R Hopper, J. (2005). ―Development and integration of new processes consuming carbon dioxide in multi-plant chemical production complexes.‖ Clean Technologies and Environmental Policy, 7, 97-115. Young, D. M. & Cabezas, H. (1999. Designing sustainable processes with simulation: the waste reduction (war) algorithm. Computers and Chemical Engineering, 23, 1477-1491. Young, T. (2008). The beginners‘ guide to the uk‘s carbon trading schemes. Business Green, http://www.businessgreen.com/business–green/analysis/2224230/. Weissenrieder, F. (1998). ―Value Based Management: Economic Value Added or Cash Value Added?‖ Technical report, Department of Economics, Gothenburg University, Sweden.

In: Environmental Planning Editor: Rebecca D. Newton

ISBN: 978-1-61728-654-4 © 2011 Nova Science Publishers, Inc.

Chapter 2

THE LINKS BETWEEN THE ENVIRONMENTAL REGULATION AND COMPETITIVENESS: THE CASE OF THE AGRICULTURE SECTOR IN ANDALUCÍA

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Francesco Testa1, Natalia Marzia Gusmerotti1,3 and Fabio Iraldo1,2 1. Sant‘Anna School of Advanced Studies, Pisa, Italy 2. IEFE – Institute for Environmental and Energy Policy and Economics, Bocconi University, Milan, Italy 3. Coldiretti –National Confederation of Farmers, Rome, Italy

ABSTRACT In general, the effects of environmental regulation and market incentives on society can redistribute income streams and can have an impact on the standard of living. These effects are also often analyzed in relation to the concept of ―competitiveness‖. Literature and empirics on competitiveness focuses on price and cost developments of production factors and other parameters that can potentially affect economic growth, market shares and other performances of companies in the targeted sectors. After a brief description of the main findings emerging in literature on the different ways of defining and measuring the effects of environmental regulation on market forces and on the relationship between environment and competitiveness, we focus on the role of the policy maker in Andalucía Region, describing the effect of water regulation and planning on the environment as well as on the competitiveness of the firms. The case studies was carried out according to the following structure, including a general background information and a detailed analysis of the environmental, in particular water, policy issues most affecting industries: water resources (hydrological,

46

Francesco Testa, Natalia Marzia Gusmerotti and Fabio Iraldo geographical, climatic, ecological situation), water policy framework and description of policy instruments (focus on water pricing, regulation of point sources, water abstraction, best environmental practices), qualitative and quantitative assessment of effects on competitiveness. The study aims at demonstrating how and the extent to which the policy maker can, by a stringent environmental regulation and planning, improve the quality of local environment and provide competitive opportunities to the firms.

Keywords: water policy, competitiveness, resource efficiency, agriculture

1. THEORETICAL FRAMEWORK ON THE RELATIONSHIP BETWEEN THE ENVIRONMENTAL REGULATION AND COMPETITIVENESS

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In general, the effects of environmental regulation and market incentives on society can redistribute income streams and can have an impact on the standard of living. These effects are also often analyzed in relation to the concept of ―competitiveness‖. Literature and empirics on competitiveness focus on price and cost developments of production factors and other parameters that can potentially affect economic growth, market shares and other performances of companies in the targeted sectors. This following definition of competitiveness, provided by the European Commission (EC, 2008), helps to identify a first relevant impact of environmental policies on market performance: ―their capability to raise costs for companies and sectors operating within an industry.‖ Environmental policies and, especially, regulation can create costs for industries through four different channels: 





A limit to water consumption or to air emissions is able to affect the resource ―productivity‖, or to induce the search for substitutive inputs (such as other forms of energy for cooling the production plants) or alternative production technologies. A tax or levy, usually imposed on a production input (water or energy) or a service (waste or water treatment) directly increases variable costs (or the company chooses to sustain the costs of pollution abatement as a means to avoid the levy, i.e.: fix costs for the investment in technologies and the connected variable costs). Taxes on water or air emissions, in fact, have proved to effectively encourage increases in environmental expenditures by polluters. Symmetrically, incentives and subsidies can be applied as economic instruments for environmental policies, either from domestic sources or from the EU‘s structural funds. The adoption of a ―Best Available Technique‖ (e.g.: suggested by a dedicated Bref document) may entail additional costs, depending on the nature of the policy measure, e.g.: companies in a sector may have to invest in ―end-of-pipe‖ equipment, and switch resources from production to monitoring and/or reporting of emissions, for example. On the one hand, they will face costs if the measure requires processoriented investment that makes existing equipment obsolete before the end of its

The Links between the Environmental Regulation and Competitiveness

47

useful life, because the newly required technology cannot be added onto the existing equipment. On the other hand, modern technology can also avoid cost, especially in the use phase (less energy for heating and cooling).

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From a cost perspective, an increase in the fixed or variable costs of a production input is likely to lead to a deterioration of the competitive performance. More specifically in those cases where environmental policy reduces the possibility to use a particular input, decreases productivity and/or increases the price of the output. Economic literature emphasizes that the above costs will have effects on profitability, prices, demand dynamics, innovation and productivity and investment decisions of the affected industries. A first interpretation for these effects is provided by the so-called ―structuralist‖ approach. This approach focuses mostly on the effects on the market forces caused by the characteristics of the sector ―structure‖ of costs and of the market. This approach is also known in literature as the ―structure-behaviour-performance‖ approach. According to this approach, the extent and the negative/positive outcome of these environmental policies effects depend to a large extent on (i) how the affected companies (industries) finance abatement technologies (additional borrowing on capital markets, price increases, cuts in dividends, cost savings, cuts in other expenditures such as R&D budgets, …), and (ii) market structures (price elasticity of demand, degree of exposure to international competition, …) (Gollop and Robert, 1983; Letchumanan and Kodama, 2000; Antweiler et al., 2001; Gray and Shadbegian, 2003; He, 2006). Such environmental policies may have long-term effects on productivity even if they reduce the resources devoted to ―traditional‖ research and innovation: if a company diverts resources from research and innovation to environmental expenditure, then the immediate impact on the costs is zero, but the lower level of spending on research and innovation will have adverse impacts on the company over time. The ―structuralist‖ approach identifies two kinds of final consequences on market dynamics: 



A worsened performance of an industry, due to the implementation of an environmental policy or regulation, measured by its growth parameters (sales, turnover, ecc.); A significant change in the structure of the industry (companies shutting down or moving to the so-called ―pollution heavens‖) or in the market structure (market shares shifting to industries operating in other contexts - e.g.: competitor sectors, countries or regions).

A second interpretation of the impacts of environmental regulation on market forces and competitiveness can be referred to the so-called ―Porter hypothesis‖. According to Porter (Porter and van der Linde, 1995), the effects of environmental policies could be rather different from what is often supposed; in particular, any loss of competitiveness will be shortlived in terms of lost output, with a longer term boost to output due to enhanced productivity effects. The competitiveness of an industry is essentially based on the capabilities of its companies to exploit and optimize the resources available. Environmental regulation, therefore, can bring to a better and most effective use of the resource and improve its ―productivity‖ (Gabel and Sinclair-Desgagné, 1993; Porter and van der Linde, 1995; Sinclair-

48

Francesco Testa, Natalia Marzia Gusmerotti and Fabio Iraldo

Desgagné, 1999). The effects of environmental policies on market forces are therefore measured in a dynamic way, relying on parameters such as ―resource productivity‖ (e.g.: valued added per unit of final output, average unitary cost, etc.) or innovation capabilities (e.g.: investments in R&D, ecc.). Moreover, by optimizing the use of a scarce resource such as energy or water, an industry can make it more available in the future, guaranteeing a higher sustainability to its production and, therefore, its business continuity (Brunnermeier and Cohen, 2003; Popp, 2006; Leiter at al., 2009). A third and more recent interpretation on the impacts of environmental policies on market dynamics is proposed by the so-called ―Resource-Based View‖. According to this approach, competitiveness and success of companies and products depend on the quality and quantity of the resources available and by the ability of companies/industries to optimize their use (Fouts and Russo, 1997). This approach is an evolution of the Porter‘s approach, as it enlarges the typologies of resources that the companies and industries can rely on. The Resource-Based View identifies five kinds of resources (Grant, 1991):     

Financial and economic resources (as in the ―structuralist approach‖); Physical resources (as in the Porter‘s model); Human resources (and their competence / know-how); Technical (considering innovation capabilities); Intangibles (e.g.: reputational, managerial, organizational,…).

This approach emphasizes that, while the first kind of resources (financial and economic) can be influenced negatively by the effects of environmental regulation described above, at least in the short run, all the other kinds can benefit from their application, especially if we consider them in dynamic terms. For example:

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





a policy can improve the capability of an industry to use a lower quantity of physical resource per unit of product (i.e.: increase productivity) or, by way of water saving techniques or substitution with other inputs, can guarantee a higher availability of the resource in the future or even prevent a rise in costs due to future scarcity. as concerns human resources, there are non-monetary economic impacts reducing the pollution negative effects on health and, therefore, tending over time to lead to a workforce that is more productive (because it is healthier). even more significant can be the positive effects on technical resources of a regulation, by stimulating new technology development and improving the innovation capacities of the companies and of the whole industry. Taxes, clean technologies and even well-designed regulatory instruments (i.e.: limits) generally encourage companies to seek innovative solutions that otherwise would remain unexplored.

Intangibles assets can also be improved by an environmental policy, insofar as it stimulates the adoption of good practices by the industry, that are able to provide immaterial and sometimes even non-monetary benefits (such as a better reputation and image on the market, a higher level of compliance with legislation, etc.).

The Links between the Environmental Regulation and Competitiveness

49

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1.1. Definitions and Measurements of Competitiveness The variety of perspectives and levels of analysis at which the concept of competitiveness may be considered complicates the formulation of an univocal definition of competitiveness both at a theoretical and political level. This is corroborated by the analysis of the main definitions of competitiveness - provided by the most important institutions at the European and the international level - where the authors have found a number of different perspectives on competitiveness and significant differences in the emphasis of certain elements of competitiveness. The definition provided by the European Commission in its annual Competitiveness Report (European Commission, 2008) mainly aims at proposing an analytical framework to assess the impact of policies – including environmental policies – on competitiveness. This definition stresses the importance of the so called ―domestic factors‖ as dominant determinants of competitiveness. The definition of OECD of a nation‘s competitiveness emphasizes the ability of a country to produce goods and services which meet the test of international markets, while simultaneously maintaining and expanding the real incomes of its people over the long term1 (OECD, 2003). A third ―institutional‖ definition of competitiveness has been provided by the World Economic Forum. The World Economic Forum considers the level of productivity of a country as a key element to determine the competitiveness of a nation. It defines the competitiveness as ―the collection of factors, policies and institutions which determine the level of productivity of a country and that determine the level of prosperity that can be attained by an economy‖ (World Economic Forum – Global Competitiveness Report, 2007) By analyzing the different definitions of competitiveness provided by scholars, institutions and practitioners, it is possible to set a common ―ground‖: competitiveness is generally defined as ―The ability of an ‗entity‘ – a country, a region, an industry, a firm – to produce products or services of a superior quality and/or at lower costs than other entities that act in the same economic context (i.e. a competition ―arena‖, such as a market or a sector)‖. The ability of an ―entity‖ to prevail on its competitors is determined and/or influenced by the capacity to use its own resource‘s endowment more efficient and effective in order to obtain a better performance. Starting from this ―common ground‖, a deep understanding of the concept of competitiveness needs to provide answers to three major questions: 1. Who is the entity that competes with others? 2. What is the ―context‖ in which this entity competes with its competitors? 3. What are the drivers and factors that enable this entity to perform better than its competitors?

1

An OECD paper (2003) states that ―Competitiveness is primarily a matter of being able to produce goods that are either cheaper or better than those produced by other firms‖.

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50

Francesco Testa, Natalia Marzia Gusmerotti and Fabio Iraldo

Competitiveness from Entities’ Perspective The first question refers to the ―entities‖ that are the relevant actors in the competition ―arena‖. Literature distinguishes three basic typologies of actors: i) a single firm or plant, ii) a cluster of firms, i.e. an industry, a sector, a branch or a local productive system (e.g. an industrial district), and iii) a territorial context (i.e. a country or a region). At the firm level, competitiveness implies that companies are able to produce goods and services more efficiently and/or effectively than their competitors. A strong competitive performance is achieved by relying on some ―competitive factors‖, often with a particular focus on process productivity and the efficient use and/or access to strategic inputs. Jenkins (1998) states that, ―a firm is competitive if it can produce products or services of a superior quality or at lower costs than its domestic and international competitors. It is therefore synonymous of a firm‘s long-run profit performance and its ability to compensate its employees and provide superior returns to its owners‖. A recent paper for the International Energy Agency defines competitiveness at the firm level as ―the ability to maintain and/or to expand [a] market position based on its cost structure‖ (Reinaud, 2005). At the sectoral level, competitiveness implies that competitive factors are activated and used by different ―clusters‖ of companies (e.g. all the companies operating in similar industrial sectors in different countries) to realize a better performance in the relevant market (local and/or international markets). In this case, the competitive performance is measured by aggregating the performance of the single firms operating in the same cluster. This level is related to the previous one, but not totally overlapping: in fact, a competitive industry can be composed by a high number of competitive firms, but also by some low-performing firms. At the territorial level (country or region), the concept of competitiveness is not limited to a market perspective, but is also related to the ―standard of living‖ within a certain geographical area. This relation makes that competitiveness as such cannot be considered a zero-sum game, as one country‘s or region‘s gain does not necessarily come at the expense of the other. Moreover, competitiveness of a country or region is the result of a wide range of drivers and performances at the regional, sector, firm and plant levels, and the interactions thereof with a number of institutional and social factors. It is therefore that competitiveness at the territorial level cannot be considered as the mere ―sum‖ of the previous levels (i.e. firm/plant and sector level). Dimensions of Competitiveness The second question refers to the ―dimension‖ of competitiveness. At least three dimensions: international, national and local competitiveness can be distinguished. At the international level, competitiveness refers to the success with which an entity (i.e. a country/region, a sector/industry, a firm/plant) competes against overseas counterparts. The most important and widely-used definition of international competitiveness are those provided by the OECD and the EC: 

―The degree to which (a country) under free and fair market conditions, produce goods and services which meet the tests of international markets, while simultaneously maintaining and expanding the real incomes of its people over the longer term‖ (OECD, 2003);

The Links between the Environmental Regulation and Competitiveness 

51

―Competitiveness is understood to mean high and rising standards of living of a nation with the lowest possible level of involuntary unemployment, on a sustainable basis‖ (European Commission, 2008).

At the national level, literature focuses on the measures of competitiveness, such as levels and growth of Gross Domestic Product or Gross National Product (SQW, 2006), GDP per capita (Esty et al., 1991) and international trade flows (Florax et al., 2001). In the view of most authors, the fundaments of national competitiveness rest on the efficiency with which resources are allocated and used at micro level (i.e. at sectoral and/or firm level). Finally, the assumption of the local competitiveness perspective implies the consideration of a series of factors related to the characteristics of a territory/region, going beyond the behavior of local economic actors. Most of all, there are two factors based on theories that point out the relevance and impact of the link between territorial localization and competitiveness, which appears to be crucial. The first is that economic, entrepreneurial and technological activities tend to agglomerate at certain places, leading to patterns of regional and local specialization. The second is that the competitive performance and development of a firm seems to be determined - to a considerable extent - by the conditions that prevail in its environment, and that the conditions in the immediate proximity – in the local milieu - seem to be particularly important (O‘Sullivan, 1984; Iraldo, 2002) for competitive performance.

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Key Variables of Competitiveness The third question refers to the analysis of the key variables affecting competitiveness as well as the ways to measure them. As mentioned above, the variety of definitions of competitiveness provided by scholars and institutions according to the different possible levels of analysis runs parallel to the existence of many approaches and indicators aimed at measuring competitiveness. In an attempt to structure existing approaches, two major approaches may be distinguished:  

The first one tries to investigate the drivers of the competitiveness (e.g. the resource productivity at firm level, the degree of internationalization at sector level). The second approach focuses on the external effects of the competitive success (e.g. the market performance measured by market share; the turnover growth rate; the financial performance measured by ROI or EBTIDA at firm level; the welfare of a nation measured by GDP per capita).

According to our framework of analysis, competitiveness can be measured at: the macro level (territorial: international/national); the meso level (cluster: sectoral/industry/district) and the micro level (plant/firm). a) At the macro level, measurements of competitiveness aim at describing how successfully a country or a region (made up of different sectors and many firms) competes with counterparts in other countries. As mentioned above, the most common indicators to compare competitiveness between countries are Gross Domestic Product (GDP) and Gross National Product (GNP) (SQW, 2006), GDP per capita (Esty et al., 2001) and international trade flows (Florax et al., 2001). The first

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52

Francesco Testa, Natalia Marzia Gusmerotti and Fabio Iraldo three indicators focus on the effect of competitiveness on the ―standard of living‖ of citizens, while the fourth indicator is similar to those used for sectors and industries as it basically underlines the ability of a country to tackle the international competition. Indicators aimed at measuring competitiveness at this level rely on the fact that a country can be gauged competitive compared to other countries if it consistently exports goods earlier than others do (Rose, 1997; Feenstra and Rose, 1997; Depperu, 2006). b) Measurements of competitiveness at the industry level especially refer to the ability of specific industries to compete for market shares with businesses operating in the same sector but located in other countries or regions. Most studies use trade (e.g. net exports), investment flows and market shares as proxies or indicators of sectoral competitiveness (OECD, 2003). Other studies seek to consider the drivers of trade competitiveness at the sectoral level, such as the Total Factor Productivity and/or proxy measures of innovative capacity (mainly R&D expenditure and patent applications) (Jaffe and Palmer, 1997). The different localization usually affects the availability of production factors and inputs, including natural resources (Peterson, 2003). Some authors (Iraldo, 2002; Cainelli and Zoboli 2004) focus on the competitive advantage obtained by firms operating in a local system of production (as an industrial district or regional cluster). Finally, financial measurements such as operating profit and Earnings Before Interest, Tax, Depreciation and Amortisation (EBITDA), even if rarely, are also used in the literature as a measure of sectoral competitiveness (Carbon Trust, 2004). c) At the level of firms/plants, competitiveness indicators relate to various aspects, such as the ability to sustain market shares, to sustain independent existence on the market or to sustain ―normal‖ levels of profitability and returns. At the firm level, productivity is the key variable, simply defined as the ―measure of output per unit of input‖. Productivity aims at measuring the efficiency with which production is carried out; in other words, the ratio between the outputs and inputs that make production possible (raw materials, labour, capital etc). Many studies identify as an optimal measure of productivity the Total Factor Productivity, that is a synthetic measure of how firms are organized, structured, use technology and are managed (for instance see: Jaffe and Palmer, 1997; Dofour, Lanoie and Patry, 1998; Berman and Bui, 2001).

2. THE EFFECT OF WATER POLICIES ON COMPETITIVE PERFORMANCE Water resource is a strategic input for several industrial sector as well as its quality and availability influence the standard of living of human being. In some cases this uses can enter into competition. In fact, a variety of industrial processes strongly relies on ground water extraction and/ or releases contaminated wastewater and this can negative influence water availability. In order to guarantee the coexistence between private and public interest the policy makers started to regulate several aspects concerning water resources, from the setting of

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The Links between the Environmental Regulation and Competitiveness

53

quality standards for surface and ground waters to quantitative and qualitative limits to wastewater effluents. Several policy instruments can be used. Many developed countries (i.e. States of European Union) have been implemented a command and control approach in their water policies: the water quality regulation is always based on a effluent standard scheme and a water quality status. For instance, Canada, Japan and USA adopted a total pollution load regulation (TPLR). The policy makers usually adopt also economic instruments. An industrial activity may, both in the case of sample and in discharge, pay a tariff and rely on ―external‖ service, or ―internalize‖ activities of water sample and effluent purification, paying sampling and discharging royalties. The level of tariff may strongly vary because it could be affected by site-specific conditions. For instance, a low tariff may be due to several factors. On the one hand, in some areas, the water may be abundant, close to the use and with good quality. The costs are low and, consequently, the price may be low. On the other hand, the price may be low due to the fact that the users cover only a part of the costs and the remainder costs are covered by other methods (i.e. general taxation, etc.). In contrast to tariffs, where merely the public water supply system is considered, charges deal with direct abstractions and direct discharges, where the public system is not always involved. Sewerage and sewage disposal and the pollution side of water use must be considered in addition to abstractions. An abstraction charge is the amount of money charged for the direct abstraction of water from ground or surface water. Abstraction charges exist in all sectors (households, industry, agriculture) to a varying extent depending on the different countries. Mostly though they are important for industry and agriculture. These charges can have an explicit environmental purpose and the proceeds can therefore be turned over to environmental agencies or environmental funds. A pollution charge is a charge on discharges according to their quality. There are large differences in applied charging regimes. The differences are in design of the schemes: coverage (pollutants), formula for calculating total tax burden, revenues. Charge schemes may be linked to other economic instruments, for example difficulties in assessing diffuse pollution agriculture sector: application of taxes on pesticides and fertilizers. In general the main competitive factors that can be influenced by water policies or measure the extent to which the policies affect the competitiveness, are the following:         

Production value (or turnover) Value added at factor costs Total cost of production (supply of goods and services) Expenditure/Investments in RandD Water prices Water purification tariffs Quantity of water abstracted or withdrawn) Environmental expenditure (and/or investments) Water-related environmental expenditures

54

Francesco Testa, Natalia Marzia Gusmerotti and Fabio Iraldo

Basing on the availability of data at sector level, we provide an overview of the effect of water policies on performance of different sectors in some developed countries. The first indicator selected for this analysis is the ―water productivity‖, i.e.: the water abstracted compared to the valued added created by a sector (or its opposite ratio: the value added created per unit of water abstracted). The reasons for selecting this indicator is twofold: 



on one side, the value added is the most appropriate variable to measure competitiveness, insofar as it reports the real value created by the activity created by a sector ―at factor costs‖ (i.e.: subtracting by the production value the costs of intermediate goods and service that are acquired from the supply chain and, therefore, the value created by other auxiliary sectors). Where the value added was not available, we used the production value. on the other side, the water abstracted is a key variable to measure the ―water intensity‖ of a sector, that represents the most appropriate proxy of the impact on water consumption (use of the resource) and of the water discharge (pollution). Moreover the water abstracted for most of the sectors is the most reliable estimation of the quantity of water discharged.

Industrial water productivity

Industrial water productivity

Recycling water ratio 140

90% 80%

120

70% 100

60%

80

50%

60

40% 30%

40

20% 20

10%

Source: UNESCO (2006). Figure 1. Industrial water productivity.

na C hi

A U S

ly

C an ad a

Ita

an y G er m

pa in S

A

us tra

lia

0%

U K

Ja pa n

0

Water recycling ratio (%)

Water productivity (US$ / m3)

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The Industrial Water Productivity (IWP) is used to measure the economic importance of water of the industrial sector in the analyzed countries: it is the ratio between the Industrial Value Added and the volume of water abstracted from the environment. Analyzing the data, three groups of efficiency can be distinguished: industrial sectors with an high level of water productivity (more than 50 US$/m3) as in Japan, industrial sectors with a medium level of water productivity as in UK, Australia, Germany, Italy and Spain, and sectors with a low level of water productivity as in Canada, US and China

The Links between the Environmental Regulation and Competitiveness

55

Irrigation water productivity 40

Water productivity (US$/m3)

35 30 25 20 15 10 5

lia Au st ra

Sp ai n

ly Ita

Ja pa n

Ca na da

an y G er m

US A

UK

Ch i

na

0

Source: UNESCO (2006).

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Figure 2. Agricultural water productivity.

Based on the available data (see Figure 1), the IWP seems to be firstly correlated to the Water Recycling Ratio: the choice to increasing the rate of recycled water into the industrial processes is generally a consequence of the need to reducing the pollution load of water discharged into water bodies. Another explanation for the high water productivity, to a lower degree, is the water-saving measures implemented by many sectors in some countries. This is partially correlated to the water policies implemented in the different countries. For example, in the EU countries the level of the tariffs applied on water discharges have been a stimulus to increase the water productivity. The low level of water prices, on the opposite, are a weak stimulus to water productivity In order to provide a complete picture of the water productivity indicator, we also propose an overview of the agricultural sector. The Irrigation Water Productivity (IrWP) is similar to the IWP used for industry: it is the ratio between the Gross Value Added for the agricultural sector and the volume of water abstracted from the environment. The difference of this indicator is more limited as a range: from 2 US$/m3 in Australia to a maximum of about 37 US$/m3 in China (Figure 2). As for the industrial sector, also for agriculture we can see how some countries like China, the UK and the USA are able to provide a higher value per liter of water abstracted. This is an indirect evidence of the higher competitive performance of the agricultural sector in these countries in using water. Finally, we analyze two of the most relevant explanatory variables to explain the effect of water policies on competitiveness, both relating to water-induced costs. First of all, we deal with the price of water. Water pricing is a measure used to control or reduce water demand by different users. The EU Water Framework Directive requires

56

Francesco Testa, Natalia Marzia Gusmerotti and Fabio Iraldo

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Member States to ensure, by 2010, that water-pricing policies provide adequate incentives to use water resources efficiently and to recover the true costs of water services in an equitable manner. Most countries are progressing towards water pricing systems. Nonetheless, quantifying the effects of water pricing is complex due to the lack of reliable and comparable data, and the combined effects of other water demand measures. Water charges are based on different policies, depending on the different availability of water resources (at national or regional level). This complexity relates to the different concepts included in water bills (tariff structures and charging methods), and to the different national water management systems. In order to analyze these effects we focused on the incidence of the water cost on total cost of production. This indicator shows the extent to which the cost of water affects the cost structure of the industrial sector. Figure 3 shows that in some EU countries the water pricing policies have affected the cost structure of the sector more than in others: for instance, in Netherlands and in Sweden the cost of water is more than 5% of total cost of production; while in countries where the water pricing policies were implemented more recently, as in Hungary and Poland, the incidence of water cost on total cost of production does not achieve 3%. In general terms, though, we can state that the price of water is still too low (especially if compared with the cost of other production inputs, such as energy) to really affect the cost function of a sector, and therefore its cost-based competitiveness. An additional indicator that we can use to estimate the weight of water policies on competitiveness is the expenditures of wastewater management, collected according to the Environmental Protection Expenditure Accounts (EPEA) standard. The data available, limited to EU countries, show that the impact of wastewater expenditures on the gross value added is very limited (Figure 4).

Source: Our elaboration on Eurostat data. Figure 3. Incidence of water cost on total cost of production.

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57

Wastewater Expenditures / Gross Value Added (2004) 1,40% 1,20% 1,00% 0,80% 0,60% 0,40% 0,20% n.a.

n.a.

n.a.

n.a.

n.a.

0,00% Italy

Germany

UK

Spain

Japan

Australia

Canada

USA

China

Source: Eurostat, 2008. n.a.: not available.

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Figure 4. Incidence of wastewater expenditures on gross value added of the industrial sector.

Past studies of the water pricing and industrial competitiveness (ECOTEC, 1996; Hitchens et al, 1998; Popovici, 2001) showed a significant correlation of the costs of freshwater and wastewater treatment with the number of initiatives to reduce water use and pollution. It also showed the absence of clear links between average productivity and costs, suggesting that low costs are not necessary to achieving international competitiveness. A study of the competitiveness of industry found that water-intensive industries, such as oxygenated water production, caustic soda and paper production, could be affected by an increase of the raw water price. Another study estimated the impact of full water supply cost recovery on different economic sectors in Cohesion Fund countries (Greece, Spain, Portugal and Ireland); full cost recovery would increase costs by 1.6 to 3.5% of the food and drink sector‘s turnover, but only from 1.1 to 1.4% for the pulp and paper industry, and from 0.3 to 0.4% for the chemical industry. Thus, the total costs of water account for a low share of total industrial turnover. Therefore, the risk of loss of competitiveness is negligible for all but the most water-intensive industries.

3. THE CASE STUDY: THE EFFECT OF WATER POLICIES ON AGRICULTURE SECTOR PERFORMANCE IN ANDALUCIA 3.1. Objectives and Applied Methodology The purpose of the case study is to verify to what extent the theories on the links between environment and competitiveness apply in practice. The case study provides a detailed analysis specifying more precisely the extent to which the current policies affect the agriculture sector in Andalucia. It is mainly based on literature research mostly web based, analysis of public available data from private, non governmental and public sources, on

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Francesco Testa, Natalia Marzia Gusmerotti and Fabio Iraldo

agriculture sector and firm reporting and on interviews conducted with selected key local actors. The case studies was carried out according to the following structure: geographical description of the region; a detailed analysis of the environmental impact of the investigate sector, water resources (hydrological, geographical, climatic, ecological situation), water policy framework and description of policy instruments (focus on water pricing, regulation of point sources, water abstraction, best environmental practices), qualitative and quantitative assessment of effects on competitiveness.

3.2. Geographical Description

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Andalucía is one the 17 Comunidades Autonomas in Spain, located in the extreme southest of European Union. It is strategically located and may be described as a vast triangular plain of 87,561 km2 (which is 17% of the Spanish territory). Andalusia is between two seas of continent and separated from North Africa by the Straits of Gibraltar, length 15 kilometers Due to this geographical situation, Andalusia has a Mediterranean climate, characterized by irregular rainfall – both over time and across space – and long hot summers with a high evapotranspiration. The wealth of landscapes has as result a wide climatic variety: cordilleras with abundant rainfalls, areas of extreme aridity, snowy mountains, valleys characterized by torrid summers, sunny coasts. Moreover, in some areas of Granada and Almeria Province, one hour driving is sufficient to go from a tropical climate to a desert.Even though there are this climatic variety, the common element of the region is a strong Mediterranean character and an intense insolation. As a matter of fact, Andalucía is the most sunny region of Spain and the majority of its territory has more than 2.800 hours of sun in a year. In general the summers are dry and hot while during the winters the majority of rainfalls are concentrated.

Figure 5. Map of Andalucia.

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59

Table 1. Rainfalls and Temperature in Andalucia (2007) Rainfall 2007 City

Total

Almeria Cadiz Cordoba Granada Huelva Jaen Malaga Sevilla

250,4 413,4 473,2 311,7 292,7 378,0 342,6 415,1

Deviation form the standard +51,7 -133,6 -173,8 -87,4 -144,5 -83,8 -163,0 -130,5

Avarage Temperature 2007 (C°) Avarage Deviation form the standard 18,8 +0 17,6 -0,9 17,2 -0,4 14,5 -1 17,5 -0,5 16,1 -0,6 18,6 0,5 18,0 -0,7

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Source: Consejeria de Medio Ambiente and Ministeri de Medio Ambiente, 2008.

Source: Instituto de Estadística de Andalucía. 2008. Figure 6. Trend of Population in Andalucia 1970-2007.

The rainfalls area scarce and irregular, with a wide variation from year to year. The yearly mean changes from 250 mm in the arid areas of Almeria, to 500-700 mm in the Guadalquivir valley and to more than 800 mm in the mountain areas, characterized by Atlantic influences, the westside of Sierra Morena and Sierras Béticas of Cadice and Malaga. Here, Grazalema area is the most rainy of Spain. The table below depicts the rainfalls and the temperature registered in main towns of Andalucia in 2007. As the table shows clearly, the year 2007 was an year quite dry and cold respect to the standard. Andalucia Region with 8.177.805 habitants is the most populous Comunidaded Autonomas in Spain. In Andalucia the 18% of Spanish population lives, more than in Madrid Region (14%) and Cataluña (16%).

60

Francesco Testa, Natalia Marzia Gusmerotti and Fabio Iraldo Table 2. Land use in Andalucia (thousands of m2) 1998

1999

2000

2001

2002

2003

2004

2005

Urban land

1.448.519

1.490.669

1.516.744

1.574.658

1.624.341

1.685.323

1.748.518

1.867.378

% constructed

59,44%

59,48%

60,02%

60,73%

61,27%

61,29%

60,02%

60,50%

Consejeria de Medio Ambiente de Andalucia, 2008.

Source: Instituto de Estadistica de Andalucia , 2002.

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Figure 7. Trend of irrigated land, 1954- 2000.

The resident population of the region increased by 2.000.000 (34,5%) between 1970 and 2007, with a yearly growth ratio that, in last years, is permanently over 1%. The growth registered in last decade is less high than in the Spain. In fact, from 1999 to 2008 the population in Spain increased by 14% while in Andalucia increased by 11%. The population density strongly varies between the Provinces. The index changes from 49,14 hab/km2 in Province of Huelva to 207,64 hab/km2 in Province of Malaga. Analyzing the table 3 we can see that the increasing of resident population is not homogeneous. In the east coast the population density increased more than 75% from 1970 to 2007 (Malaga and Almerìa) while in the central area the population only just increased (Granada, + 8%) or reduced (Jean, -0,5%). Referring to the land use in Andalucia, the Region is characterized by a development phase particularly focused on the east coast. On the whole the urban land increased of 28,9% from 1998 to 2005, more than 400 km2, most of which (60,5%) were used for constructions. From the analysis of land use from 1956 to 2003 important changing emerge. In detail, about the agriculture sector, the decrease of not irrigated land highlights that this practice has falling in disuse in favour of the constructed land and irrigated land that increase.

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61

Source: Consejeria de Agricultura y Pesca. Junta de Andalucia. Figure 8. Trend of main indexes of economic performance, 2000-06.

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3.3. The Agriculture Sector and its Impacts on Environment Agriculture is the major land use in Andalucía with just over 3 million hectares under agricultural management, equal to 35,8% of whole territory of Andalucía. The Mediterranean climate strongly influences the differentiated characteristics of the agriculture in Andalucia. The greater importance of the agriculture than breeding and the prevalence of permanent growing (principally olive) respect to yearly growing, are just caused by the Mediterranean climatic conditions. The diversity of the production and of environmental conditions represent another key feature of agriculture in Andalucia. The main cultivations are the olive (more than 1,5 million of hectares) and fruit and vegetable products, most of all in greenhouse intensive growing systems. In this climatic conditions, where the period when the photosynthetic activity is maximum coincides with the lower presence of rainfalls, the irrigation plays a key role. As a consequence, the irrigated agriculture that is just the 18% of the total farmland, produce more than 50% of total production of the sector. In economic terms, the agricultural production in 2006, had a worth equal to 8.689,8 M€, while, in the same period, the agriculture yield was equal to 7.227 M€, and the Gross Value Added (GVA) achieved the value of 6.758,5 M€. From 2000 to 2006, the area of farmland in Andalucía has reduced of 10,8% while the agriculture yield has increased of approximately 12%. In the same period the value of production, referred to whole agro-industry has decreased of 0.8% while the GVA was substantially constant. The people employed in the agriculture sector increased of 1,4% from 2000 to 2006, even if it decreased of 6,1% between 2005 and 2006. The male workforce decreased of 5,5% while

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female workforce increased of 48,7%. Referring to the last year of the analyzed period, both male and female workforce in agriculture sector has decreased of 6%. According to Consejeria del Empleo de la Junta de Andalucía, 9 of 200 total fatal accident registered in Andalucía referred to the agricultural sector. Moreover the number of fatal accident decreased of 62% in the period 2000-06.

Source: Consejeria de Agricultura y Pesca. Junta de Andalucia. Comitè Andaluz del Agricultura Ecologica. Associacion Agraria del Jovenes Agricultores (ASAJA).

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Figure 9. Agriculture land tilled using sustainable techniques.

Source: Consejeria de Agricultura y Pesca. Junta de Andalucia. Figure 10. Land subjected to an integrated cultivation (2006).

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Source: Anuario de estadistica de Andalucia. Instituto de Estadistica de Andalucia. Cuentas economicas de la agricultura. Metodologia SEC-95.

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Figure 11. GDP per resource consumption unit: farmland and water.

Figure 12. GDP per resource consumption unit: consumption of fertilizers and phytosanitary products.

An important aspect to stress is the continuous growth of land dedicated to organic agriculture: between 2000 and 2006 the agriculture land tilled by low environmental impact increased of 653% (from 69.042 ha to 519.910 ha); in the last year – 2005/06 – this increasing was of 28,9%. These numbers are much more relevant if we consider the reduction the area of tilled land in Andalucía. In fact, in the 2006 the biological agriculture represents the 16,6% of total farmland while the use of integrated production characterizes the 8,2% of total farmland.

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Figure 13. Sustainability of agricolture in Andalucia. 2000-2006.

In detail, the farmland where are used methods of integrated production covers 258.427 ha in the 2006, achieving an increasing of 930% respect to 2000 year. Only between 2005 and 2006 the increase was of 58,8%. Today many agriculture areas have furnished of specific Regulation of integrated production such as rice, cotton, courgette and grapes. Referring to the level of resource productivity of agriculture sector in Andalucia during the period 2000-2006, the trend is quite positive. Analyzing the relationship between the economic performance, measured by GVA, and the use of natural resources, as the land, consumption of fertilizers and phytosanitary products, an increase of 18% emerges during the period 2000-2006. Referring to water consumption, the absence of data referring to the period 2005-06 does not allow a similar analysis. However, we can register that water consumptiom has increased from 2000 to 2003 (+8,5%) , while in last year (2002-2003) there was a string decrease (-16,5%). Summarizing, we can observe that between 2005 and 2006 there was an increase of economic growth of agricolture sector (value of production: +0,6%, agriculture yield: +11,1%) and a slight decrease of GVA (-0,8%). The workforce of the sector decreases of 6,1%. Referring to the environmental sustainability of the sector, we can register the beginning of de-coupling process between economic growing and environmental impact: in fact, the consumption of fertilizers decreases of 8,1% while the use of phytosanitary products increases just slightly (+2%). Referring to use of water resource, the absence of updated data does not allow a deep analysis on the sector trend. Anyway we have to uderline that recently, many public authorithies have put in practice several actions for promoting irrigation methods mainly sustainable.

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3.4. Water Resources 3.4.1. Institutional and Legal Settings Over the last 150 years, water has constituted a central issue of the political debate in Spain. The first Water Law, devoted to codify systematically the, until that moment. disperse water rules, was passed in 1866: in it, the institution of the hydraulic public domain was clearly set up, although only concerning surface waters. After 1976, during the democratic transition, two main changes took place in the field of water policy: first, the reformation of the State, from a strongly centralized model to a semifederal model (Estado de las Autonomias), in which water related issues are shared by the central government (inter-regional river basins authorities, public works of general interest, water transfers between river basins, basic environmental legislation and economic planning) and the regional governments (intraregional river basins, municipal water supply, flood defenses in urban areas, regional and land use planning). Second, in 1985, a new Water Law was passed, with two main new features: the public domain was extended to ground waters and planning (at national and river basin level) was set up as a function under which all activities affecting water had to be developed. The legislative framework of water supply in Andalucia is defined essentially for complying with the Directive 2000/60/CE: the Real Decreto 1/2001 has approved the updated text of the Water Law. Referring to the autonomy level, we underline that the Household Water Supply Regulation in Andalucia, who is pioneer and unique in Spain, represents a milestone for guarantying the respect of water users rights. This Regulation has introduced the obligation of administering for the involved organization, a standard system for measurement and invoicing and the definition of a control system. In the 2004 the publication of Real Decreto 2130/2004, has transferred the competence on water resources management from the Administración General del Estado to the Comunidad Autónoma de Andalucía. Moreover, the next year, the Andalusian Water Agency was established as an autonomous organ subordinate to the Regional Ministry of Environment to coordinate and exercise the competencies of the Regional Government of Andalusia regarding water resources. In 2005 and 2006, the transfer of powers over the coastal catchments that discharge into the Mediterranean and the Andalusian Atlantic coasts became effective. In 2007 the transfer of competencies on water issues to the Andalucía Region was reinforced by the transfer of the waters of Guadalquivir that flows entirely in the Andalucía territory. The setting of the Agency, in 2005, occurred during the process of adaptation to the European Water Framework Directive (Directive 2000/60/EC), which constitutes a new concept in water management in which primary objectives are respect for the environment and public involvement. In order to adapt to the new Directive, as well as to any other environmental law, in Spain, the Water Program (Programa AGUA - Programa de Actuaciones para la Gestión y la Utilización del Agua) has been defined. The Program is designed in a simply way in order to let the citizens understand better the intentions of the Government. Besides the Program it is important to emphasize the function of the Integrated Water Information System (Sistema Integrado de Información del Agua - SIA), that collect all the available information on water resources.

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The Regional Government of Andalusia has embraced this philosophy of efficiency and modernization in water management in such a way that the present and future water resource needs of the productive and domestic supply sectors are guaranteed, taking into account the respect for the environment as a point of reference. Participation takes on special importance with the creation of a Water Commission in which, all involved sectors will have a voice and, for the first time, a vote. Actually the Government of Andalucía is going to approve a water law that should collect the proposals of farmers and irrigators. The origin of this discussion lies on the Andalucia Water Agreement that represent the unanimous will of the Parliament of Andalucia. The aim of this agreement is to carry out a programmatic document that can realize the new necessitates of Andalucia society on water resources and contribute to guarantee its quality and sustainability. One of the main aim of the Agreement is just the elaboration of a water law that regulate the prevention against the flooding, the groundwater management, and the regulation of new water uses.

3.4.2. The Management of Water Resources During the development of western countries, water management was characterized by the construction of enormous infrastructures, initially, for human consumption, both for urban areas and agriculture, and then for industrial consumption included energy production. In some areas in the southern Europe, where water availability was traditionally scarce, the economic development has been limited till recent periods, when the capability of constructing infrastructure remarkably improved. First of all, the water management in dry areas of Europe aimed at balancing the water supply (scarce and very discontinuous) and demand (continuous and significantly growing). This situation increased the intensity of the exploitation and so the percentage of drawn volume respect to the available resources. For example in Andalucia this index reaches the significant value of 38%, much higher than the average value in western countries (11%) and also higher than value registered in Spain. So, in Andalucia, water availability is a problem more accentuated than in other part of Europe and Spain. The Region is characterized by a scarce and temporarily inconstant water availability (745 m per habitant per year respect to 1406 m in Spain). Therefore, water is a key element of environment and economic development, because its correct management is essential for keeping the ecological equilibrium and for the sustainability of human activities carried out in the Region. The hydrographical network of Andalucía consists of five river basins: the Guadalquivir basin, the Guadiana basin and the Guadalete-Barbate basin, each flowing into the Atlantic Ocean; and the South and the Segura basins flowing into the Mediterranean Sea. The data, in table below, shows the size of the basins and the amount of water that they provide (note that the Guadiana basin is split into two parts): the first column gives the total size of each basin (in km2). Some basins (in particular Guadiana I and Segura), however, are essentially outside Andalusia; the second column gives the size of each basin within Andalusia, and the third column the percentage of the total Andalusian territory that they cover. With 59%, the Guadalquivir basin is clearly the largest within Andalucía. The fourth and fifth column show how much water (in billion litres per year) is provided by each of the basins. Note that 73% of this is surface water, while 27% is from underground reservoirs.

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Table 3. Water resources Basin Surface (in km2) Basin Guadalquivir Guadalete/Barbate South Guadiana I Guadiana II Segura Total

Total 57.104 6.365 17.820 53.067 6.871 18.870 160.097

In Andalusia 51.477 6.365 17.820 3.248 6.871 1.780 87.561

% 59 7 20 4 8 2 100

Resources (in billion liters per year) Surface Sub terrean 2.255 437 358 85 414 630 1 6 275 60 1 5 3304 1223

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Source: Consejeria de Medio Ambiente 2004.

Source: Consejeria de Medio Ambiente, 2008. Figure 14. Water demand in the basins in Andalucía, 2007.

The economic development of Andalusia has induced an increase in the demand for water over time. In its turn, this has led to a stronger pressure on the scarce water resources. The agricultural sector absorbs 90% of the available water resources due to the very large amount of irrigated land. According to Lopez-Fuster and Montoro (2002), Spain ranks third in the world and first in Europe, in terms of irrigated land. Andalusia covers 23,3% of the Spanish irrigated land (Consejería de Agricultura y Pesca, 1999). This is a very high percentage if we take into account that Andalusia is the most arid region in the country and the one with the most serious problems of water shortages. The problems are further aggravated because the existing irrigation systems are rather old and only few hi-tech systems that save water are used. Irrigation by gravity is still the system that is used most widely in the region (44,9%).

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According to official data published by Government of Andalucía, the water consumption in the Region is caused by agriculture for 77,6%, domestic use for 14,5%, industry for 2,8%; while in Spain this relation is different (agriculture 72,4%, domestic use 11,9%, industry 14,6%). The table below shows in detail water demand in the basins in Andalucia.

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Table 4. Aspects of water use at sectoral level

Source: Agencia de Medio Ambiente, 1996.

Referring to the main water consumers, as well as agriculture, the tourism has become one of the important drivers of the region. The tourist activities require a lot of water, especially in summer, which conflicts with the use in the agricultural sector. In facts. together with the agricultural activities, tourism has risen the demand for water to such an extent that the coastal areas are mostly irrigated with underground water. As a consequence, the intrusion of salty sea water takes place, which raises the problems due to overexploitation even further.

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Next to the agricultural sector, also the manufacturing sector has undergone a large development. This occurred mainly in the Guadalquivir river basin – which holds in particular for the food and agricultural products sector, which consumes a considerable amount of water (Velázquez, 2005) – and around the major cities and the main harbours of the region. The tables below shows some aspects of water use at sectoral level. The first column gives the vector w with sectoral water consumption (in billion liters). It shows that 90% of all the water consumption takes place in the agricultural sectors (1-6). Manufacturing (sectors 719) and services (sectors 20-25) account for 5% of the water consumption. The second column gives the vector x with sectoral production (in million euros). It follows that agriculture accounts for only 8% of the total output, manufacturing for 34%, and services for 58%. So, almost all water is consumed by sectors that are responsible only for a minor share in the output. The third column gives the vector y with direct water input coefficients. They are defined as i i i y = w/x and describe the water consumption (in litres) per euro of production. On average this coefficient is 53, but note that there is an extreme variance across sectors. In particular citrus fruits (sector 3) and cereals and legumes (sector 1) require an enormous amount of water per euro output. Also the other four agricultural sectors are well above average. Consequently, the manufacturing and service sectors must have coefficients much smaller than average. We see that only three manufacturing sectors (metallurgy, 9; chemicals and plastics, 11; and paper, printing and publishing, 18) and one service sector (hotel and catering, 22) consume more than 5 litre per euro production.

Source: Consejeria de Medio Ambiente, 2008. Figure 15. Trend of percentage of depurated wastewater.

Although cereals and legumes (sector 1) has a very high direct water input coefficient and absorbs more than 25% of all the water, a large part of its products are sold to the food

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processing sector (14). So, indirectly, the food products contain a considerable amount of water, because this sector requires cereals and legumes as its inputs. Another important issue about the water management refers to the depuration system of wastewater. The recently approved National Plan on Water Quality 2007-2015, will guarantee to close the water circle both constructing new depuration plants and improving and modernizing the obsolete ones. These interventions will assure a further improving of depuration system in Andalucía that has already gotten relevant results as depicted by the following figure. Actually, in Andalucia, the main depuration plants are located in the priority areas (i.e sensitive areas, urban agglomeration, tourist areas on the coast) and an effective net of little equipments have been installed for serving the other areas The next step is to extend this system and reach also the little town and villages that actually are not served.

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3.5 Water Policies and Competitiveness 3.5.1. Overview of the Effects of the Water Policies on the Competitiveness of the Different Sectors in the Region In Spain, over the last century, water scarcity has been addressed mainly by hydraulic infrastructure. Modern behavior has been characterized by a general acceptance and expectation of unlimited water abundance, thereby disregarding projects costs and water use efficiency. This has transformed the traditional culture which helped the population to coexist with the irregularity and scarcity in a semi-arid area and has contributed to make the water related conflicts more acute. The present major and general issue consist in re-creating a culture which involves managing water as an irregular and scarce resource, in which the scarcity is determined not only by physical reasons, but mainly by its social, economic and ecological costs. Consequently, the long tradition of supply management should be integrated into the broader approach of demand management. According to this need, the present system of permits is rather flexible: water rights granted to specific user, for specific objective. Institutional change also involves correcting this situation to allow for voluntary transfer of water rights between users. Those transfers can be temporal or permanent and should be supervised by River Basin Authorities. Another important issue is the intense controversy over the revision of the financial and economic regulatory system of water as an instrument for the rationalization of its use and management. Since the beginning of this century, the financial and economic regulation of water has been in line with a water policy based on the flexibility of supply. Reforms introduced by the 1985 Water Act, apart from their incomplete implementation, have proved to be insufficient to accomplish this task. The charges and rates fixed in the Water Act have proven to be complicated to apply and difficult to collect as well as manifestly insufficient to cover the amortization costs of investment and of the exploitation costs of the hydraulic systems. The financial and economic regulatory system defined by the Act maintains the two basic characteristics of the previous

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situation, i.e. the compensatory character with respect to the State investments and the subsidization of costs. All this despite its original aim to revise the old system. The financial outcome of the abovementioned charges and rates still represents a subsidy of the order of 40% of total investment. These payments only cover 45% of the total water used for irrigation and urban and industrial supply and 4% of all the water used in hydroelectric generation. The remainder of the users does not make use of the hydraulic works financed by the State and are, therefore, exempt from these rates and charges as there is no payment required for water extraction at source. There is a general agreement that the incorporation of the value and the cost of water as a resource into the price paid by the user is a fundamental condition from the perspective of either its correct allocation (economic efficiency) or of the need to reduce the level of structural intervention. But serious concern arises regarding the effects on irrigation of this full cost recovery approach. The marginal productivity of water in Spain is very different among regions: it is lower in irrigation farming in the northern half of Spain, with a minimum of 35 0,15€/m3 in Aragon and is higher towards the south with a maximum of 0,6€/m3 in Murcia. (Del Moral 2000). These productivity figures set the context far the debate of the effects that an increase of the water price would have on the competitiveness of Spanish irrigation farming. The competitiveness of Spanish large scale irrigation crops (cereals, oil-bearing crops, industrial and animal fodder crops --together they account for 65% of total irrigated land) depends to a large extent on the low cost of water. If the cost of water were to increase substantially, they would not be able to compete. This would be particularly the case for irrigation crops with high energy inputs. On the other hand, irrigated agriculture using groundwater resources already frequently bears costs that are higher than those foreseen for surface water, in case of full supply costs passed to the users. Therefore, it is important to take into consideration the territorial location of those areas, which already suffer from aquifer overexploitation and saline intrusion and in which the only application of economic criteria will not contribute to salve environmental problems, nor to the sustainable use of the resources. So a differential policy must be established according to the different areas within the country, based upon the expected irrigation profits, depopulation risks, the degree of competition for water in different sectors and the environmental aspects. Moreover, just the 53% of water distribution infrastructure for agricultural use are efficient while the 47% is obsolete or works inefficiently. The situation is not uniform: for instance the 50% of water infrastructure in Granada province is in a bad plight while in Huelva and Jaén provinces the 70% infrastructure work efficiently (Camara de Cuentas de Andalucia, 1999). In any case, it is fundamental that the agriculture sector improve and modernize the irrigation equipment and infrastructure. Although, in last years, a modernization process was started and an increase of efficiency achieved (Consejeria de Medio Ambiente, 2007). Moreover, it is necessary a technical and productive restructuring of the irrigated areas, that are characterized by a low efficiency and a high water consumption. That is because the potentiality of agriculture is strictly linked to the water saving and recovery. In general, because the debit water balance causes serious problems of overexploitation and impoverishment of groundwater, it is necessary a policy focused on water improvement

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and savings, the investigation in hydraulic technologies for groundwater recharging, desalination of sea water, and, finally, on a system allowing the water transfer from a basin to the other and from the mountain to the coast. Also the measures for reusing the purified wastewater represent an important action for water saving. Even if this instrument does not determine a significance increasing of water availability, in some areas of the region, it can contribute to reduce the water deficit and support the activity of productive systems. For further information about the water management in agriculture sector in Andalucia we refer to an interesting article (Velasquez et all., 2006) that analyze the effects that an increase in the price of the water delivered to the agriculture sector to promote the conservation of this resource would have on the efficiency of the consumption of water and the possible sectorial reallocation of water to the remaining productive sectors. The methodology is a computable general equilibrium model (CGE), who has been modified to introduce the variations in the water price that is analyzed by means of the introduction of a tariff on the production structure.

3.5.2. The Local Water Policies and Their Impact on Agriculture Competitiveness As we above mentioned, the agriculture sector is the main user of water in Andalucia Region. Referring to the adopted measures at local level it is important to state beforehand that the Community Agricultural Policy has integrated the environment and sustainable development into the sector planning, defining objectives also regarding to water resources. It is self-evident that some agricultural practices have a significant impact on the environment and food safety, promotes the fertilizer and chemicals concentration in the soil and water, and the soil erosion. In any case, the positive contribution of agriculture on the environmental improvement as the defense and conservation landscape, habitat and genetic diversity, has to be recognized as well. The Environmental Administration of Andalucia, in the Environmental Plan 2004-2010, has set up some measures for the integration of sustainability issue into the socio-economic development of agriculture sector. As a consequence, the main strategic plan of Administration of Andalucia for reducing the environmental impacts of agriculture does not focus a single impact category as the water consumption but refers the agriculture system as a whole. In particular it provides measures for training on irrigation practices, the activation of assistance systems for water savings, integrated and organic production, for supporting the modernization of irrigation infrastructures, the wastewater recovery, the desalinization techniques. One of the main strategic action is the introduction of sustainability criteria in the agricultural production process. In this direction, as we have seen in the previous sections, the year 2006 was characterized by the increase of organic and integrated agriculture and the support to extensive agriculture (Consejeria de Agricultura y Pesca de la Junta de Andalucia) An important step in this direction refers the approval of the Strategic Plan of rice sector in Andalucia (2008-2011), whose aim is to improve the infrastructure, the sustainability of growing and transformation and trading process. As a consequence, as ASAJA-Sevilla states, the agriculture sector has keeping on improving the efficiency of water use by means of teledetection techniques and the participation to initiatives as PREVINFO (Strategy for a preventive forest management of fire risk).

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According to the Sustainability Report in Andalusia 2008, the agriculture sector is characterized by an increase of demand of food product and the intensification of exploitation processes; this determine an overuse of water resources. The indentified actions at local level refers principally the new technologies of resource production transformation and saving, the increase of organic and integrated agriculture, the increase of water use efficiency and a better environmental awareness of agricultural firms. In detail, the instruments for changing the agriculture in Andalucia are in:   



European and National policies for sustainable agriculture, CAP, and for rural development; Planning instruments as Organic Agriculture Plan in Andalucia 2007-2013, the Rural Development Program 2007-2013, and the Strategic Plano of rice sector 2008-2011; Planning instruments for developing new production technologies as the Innovation and Modernization Plan in Andalusia 2005-2010 and the RD and Innovation Plan 2007-2013; The projects and initiatives for the integration of sustainability criteria into production process at agricultural level.

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At regional level, other relevant instruments are, moreover, the Strategy for a Sustainable Development and the Action Plan for Climate 2007-2012, whose importance depends on its crucial effects that has for agricultural activities. Focusing on organic agriculture, in 2000, the Andalusian Organic Farming Plan (AOFP) was developed for a six year period (2000-2006) and endowed with 93.8 M€, following the example of other European countries‘ plans. The AOFP has tried to address the most urgent needs of organic sector and it has been developed by the Andalusian Government. The focus was on structuring the sector at a regional level and promoting forward movement in regions by participatory activities with main stakeholders. Targets have been: Economic and social objectives 

 

Integrating production and local consumption of Andalusian organic products by promoting farmers agreements and linking organic to food health in more vulnerable sectors (children, old people and sick people). Developing the organic food chain by consolidating the product offer, processing products and increasing added value and diversity of those products. Promoting small enterprises, family farms and conservation of traditional high quality food.

Production objectives 

Giving more autonomy to organic farming by using and producing local inputs.

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Francesco Testa, Natalia Marzia Gusmerotti and Fabio Iraldo Environmental objectives 

Promoting the role of organic farming ability to preserve protected natural areas (e.g. natural parks) and including it into environment conservation plans in Andalusia that comply with national and international regulations (water conservation Directives, Natura 2000, KYOTO Protocol, etc).

The instrument used to develop organic farming has been the AOFP, structured as 10 main objectives and 38 measures. These measures range from direct subsidies to organic farms to promotion of internal market, education and research. The main actions in 2005 have been: 

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

Natural Parks in Andalusia - In Andalusian natural parks there are 129,200 hectares certified as organic (General Directorate of Organic Farming, 2005), 35% of organic land area. Most of this is pasture and dehesa (Mediterranean forest system associating Querqus sp. with arable crops) for livestock systems, olive trees, fruits and dry fruits. The General Directorate of Organic Farming began a project in eight Natural Parks: Sierra Nevada, Sierra de Cazorla, Segura y la Villas, Sierra Mágina, Sierras Subbéticas, Sierra de las Nieves, Sierra de Aracena y Picos de Aroche, Sierra Norte y Alcornocales. After studying production capacities and resources of these areas, we have designed a project to improve agrarian systems combining both productive and conservation activities. Organic Nourishment in Schools - This ambitious project began in October 2005 and it was designed for nearly 3,000 students. It has involved four local farmers groups who have arranged to supply 16 primary education institutions, five nurseries and one old people‘s home with their produce. The amount of food needed for all students during a whole school period was 249,120 kg, including dairy products, meat, cereals, fruit and vegetables and others. The project has been very successful and next year will be expanded to several hospitals and some more schools.

In order to adapt European regulations to Andalusian reality and to organic sector demands, it was developed, in a participatory way, a local regulation for organic aquaculture and national organic wine principles. Moreover, public aids have been given to farmers and industries. Agri-environmental measures (European funds) in 2004 included 3,334 farmer‘s renewals (5.283.943 M€). New applicants included 780 in agriculture and 253 in animal farms (131,454 € and 301,465 € respectively), (General Directorate of Organic Farming, 2005) The first announcement of organic processing industry aids was made this year with a 1.379.915€ budget to fund 30% of investments. The remaining 70% (4.708.000€) was paid by the private sector. It also includes promotion of farmers‘ associations and marketing initiatives. There were 86 applications but the budget was insufficient for all, so most of them will apply again next year. An example of coordination of measures for both conventional and organic farming was the development of the first regulation for the official treatment against Bactrocera oleae (an olive tree pest) using organic methods.

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Source: Consejeria de Agricultura Y Pesca, 2008. Figure 16. Evolution of land used for organic agriculture in Andalucia and % of organic agriculture respect to total farmland, 1993-2007.

Table 5. Cost of water and productivity Promotion (%) Cost of Water Superficial Residual Underground Public Private (€/m3) 40 0 58 85 15 598 64 0 35 49 51 148 78 0 21 49 51 140 77 1 20 89 11 143 40 59 70 30 256 69 5 24 82 18 100 44 0 55 75 25 184 68 1 31 65 35 161 Source of water (%)

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Irrigated land Province (1000 ha) Almería 64,462 Cádiz 47,533 Córdoba 83,638 Granada 119,438 Huelva 31,217 Jaén 189,023 Málaga 52,744 Sevilla 226,048

Productivity (€/ha) 3,8 0,71 0,38 1,07 2,31 0,8 0,97 0,39

Source: Consejeria de Agricultura Y Pesca, 2008.

Summarizing, these policies have absolutely contributed to the growing level of Andalusian organic production in a decisive way (See the previous paragraph for detailed data), improving the competitiveness of firms measured by the economic performance and also improving the efficiency in use of some natural resources as the water.

CONCLUSIONS The study demonstrates that the agriculture and agro-industry sector represent one of the main drivers of regional economy and, in the meanwhile, the biggest water users, in particular for irrigation. This practice (that is most of all concentrated in some areas and is affected by climatic conditions) does still utilize low efficient equipment on an environmental perspective. On the one hand, the irrigated land has the highest productivity and its surface is, in fact, increased in the last years; on the other hand, the organic and integrated agriculture, that, basically, need a more rational water use, has also strongly increased.

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Consequently the regulation and planning framework, as well as the action carried out by all stakeholders, focus on the efficiency in water use, that is strongly linked to technological and infrastructural investments. Even if the choice on growing products should be considered. Moreover, the incentives system, also in CAP and Rural development framework, is also oriented, not only towards water use efficiency and environmental training but also the adoption of a sustainable agriculture. Nevertheless, the development of regional economy does not appear to want to renounce the agriculture productivity, caused by its strategic role in local economy. In this framework, we have to wait for the effect of actual economic and food situation, that reveals worrying crisis signals, as well as the next reform of Community Agricultural Policy, in order to understand the real orientation of the sectoral development policies. It is important, anyway, to highlight that also in the traditional agriculture the trend is towards the sustainability. Moreover, the debate on tariffs system is ongoing, as demonstrated by recent studies that propose to correct the overexploitation of water resources at a low cost, in particular in the agricultural sector. The data on water cost and water productivity for agricultural use underline as this direction could be correct. In fact, in the province that apply a high cost of water the productivity of water used for irrigation is strongly high. For all these reasons, the regional agricultural economy could be a case of extreme interested for studying the effects of water policies on competitiveness also in the next years.

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REFERENCES Antweiler W., Copeland B.R., Taylor M.S, Is free trade good for the environment? American Economic Review 91 (4) (2001), pp. 877–908 Berman E., Bui LTM, Environmental regulation and productivity: evidence from oil refineries, The Review of Economics and Statistics 83 (3), (2001), pp. 498-510 Brunnermeier S.B., Cohen M.A., ―Determinants of environmental innovation in US manufacturing industries‖, Journal of Environmental Economics and Management 45, (2003), pp. 278-293. Cainelli, G. Zoboli, R., eds, The Evolution of Industrial Districts: Changing governance, Innovation and Internationalisation of Local Capitalism in Italy, Contributions to Economics, Physica, Heidelberg (2004), New-York Consejeria de Medio Ambiente de la Junta de Andalucía, Medio Ambiente en Andalucía. Informe 2007, 2008 , available from: www.juntadeandalucia.es Consejeria de Medio Ambiente de la Junta de Andalucía, Medio Ambiente en Andalucía. Informe 1998, 1999 ; available from: www.juntadeandalucia.es Depperu D., La competitività internazionale delle imprese – determinanti, misure, percorsi di successo, (2006)ed. Il Sole 24Ore, Milano. Dietzenbacher E., Velázquez E., Virtual water and water trade in Andalusia. A study by means of an input-output model, Working Paper 06.06, Universidad Pablo de Olavide, Departamento de Economía, 2006, available from: http://ideas.repec.org/p/pab/wpaper/ 06.06.html

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Dufour C., Lanoie P., Patry M., Regulation and Productivity, Journal of Productivity Analysis 9 (1998), pp. 233-247 ECOTEC.. The Application of the Polluter Pays Principle in Cohesion Fund Countries (1996), Birmingham: ECOTEC. EOI - Escuela de Negocios, Observatorio Ambiental de Andalucía, Informe de sostenibilidad en Andalucia 2008, (2007) EOI; Esty D.C., Porter M.E., Ranking National Environmental Regulation and Performance: A Leading Indicator of Future Competitiveness?‖ in M.E. Porter, J.D. Sachs, P.K. Cornelius, J.W. McAuthur, and K. Schwab, eds. The Global Competitiveness Report 2001-2002 (2002). Oxford: Oxford University Press. European Commission, Communication from the Commission on the European Competitiveness Report 2008, Brussels: European Community; 2008 (COM 774 final) Feenstra RC, Rose AK. Putting Things in Order: Patterns of Trade Dynamics and Growth, NBER Working Paper No 5975 (1997), National Bureau of Economic Research, Inc.. Florax R., Mulatu A., Withagen C., Environmental Regulation and Competitiveness, Tinbergen Institute Discussion Paper (2001), T1 039/3. Gabel, L.H., Sinclair-Dresgagné, B.. Managerial incentives and Environmental Compliance, Journal of Environmental Economics and Management 24(1993): pp. 940-955 Gollop, F.M.. Roberts M.J, Environmental Regulations and Productivity Growth: The Case of Fossil-fuelled Electric Power Generation, Journal of Political Economy 91(4) (1983), pp. 654-674. Grant RM., The resource-based theory of competitive advantage, California Management Review 33(3) (1991), pp. 114-135. Gray, W., Shadbegian, R.. Plant vintage, technology, and environmental regulation, Journal of Environmental Economics and Management 46 (2003): 384–402. He J. Pollution haven hypothesis and environmental impacts of foreign direct investment: The case of industrial emission of sulphur dioxide (SO2) in Chinese provinces, Ecological Economics 60 (2006), pp 228–245 Hitchens D, Birnie E, Cottica A, McGowan A, Triebswetter U. The Firm, Competitiveness, and Environmental Regulations: A Study of the European Food Processing Industries. (1998) Dublin: European Foundation for the Improvement of Living and Working Conditions. Iraldo F. (2002), Ambiente, Impresa e Distretti Industriali – gestione delle relazioni interorganizzative e ruolo degli stakeholder, Franco Angeli, Milano. Jaffe AB, Palmer K. Environmental Regulation And Innovation: A Panel Data Study, The Review of Economics and Statistics 79 (1997) MIT Press, pp 610-619. Jenkins R., Environmental Regulation and International Competitiveness: A Review of Literature and Some European Evidence, United Nations University Institute for New Technologies. (1998) Leiter AM, Parolini A, Winner H. Environmental Regulation and Investment: Evidence from European Industries, Working Papers 2009-04 (2009), Faculty of Economics and Statistics, University of Innsbruck Letchumanan R., Kodama F. Reconciling the conflict between the ‗pollution-haven‘ hypothesis and an emerging trajectory of international technology transfer. Research Policy 29 (2000), pp. 59–79.

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Moral L. del: Institutional Framework of Water Management in Spain: Strengths and Weaknesses for coping with Environmental Risk and New Social Goals, Quaderni di Geografia, nº 19, Universidad de Padua (Italia), 1999, pp. 33-44. Moral L. del (ed.), P. van der Werff, K. Bakker, J.Handmer, Global trends and water policy in Spain, in Water International, International Water Resources Association, September 2003, vol. 28, no. 3, pp. 358-366. OECD Environmental Taxes and Competitiveness: An Overview of the Issues, Policy Options and Research Needs(2003), Paris O‘Sullivan P., Economia e Territorio, Il Mulino (1984), Bologna Peterson S. The EU Emission Trading Scheme and its Competitiveness Effects for European Business: Results from the CGE Model DART, (2003)Kiel Institute for World Economics. Popovici, M., Water pricing and the competitiveness of enterprises in Romania. In: Pricing, Water, Economics, Environment and Society, 185–193. (2001) Brussels: European Commission Popp D. International innovation and diffusion of air pollution control Technologies: the effects of NOX and SO2 regulation in the US, Japan, and Germany, Journal of Environmental Economics and Management 51(1) (2006), pp. 46-71. Porter M. E., van der Linde C. Green and Competitive: Ending the Stalemate‖, Harvard Business Review, September/October (1995), pp. 120-134. Reinaud J. Industrial Competitiveness under the European Union Emission Trading Scheme, International Energy Agency, Information Paper, February (2005 Rose A K. Dynamic Measures of Competitiveness: Are the Geese Still Flying in Formation?, FRBSF - Federal Reserve Bank of San Francisco (1997) SQW Limited, Exploring the relationship between environmental regulation and competitiveness : a literature review – a research report completed for the Department for the Environment, Food and Rural Affairs (2006), SQW Limited. Sinclair-Dresgagné B. Remarks on Environmental Regulation, Firm Behaviour and Innovation, Scientific Series 99s-20, (1999), Montreal, Cirano. Velasquez E., Cardenete , M. A., Hewings, G.J.D., Water Price And Water Sectoras Reallocation In Andalusia. A Computable General Equilibrium Approach, in Revista Estudios de Economía Aplicada, 24, (2006), 1043-1060 World Economic Forum Growth Competitiveness Report (2007) http://www.weforum.org/

In: Environmental Planning Editor: Rebecca D. Newton

ISBN: 978-1-61728-654-4 © 2011 Nova Science Publishers, Inc.

Chapter 3

ENHANCING ENVIRONMENTAL PLANNING THROUGH THE USE OF THE THERMODYNAMIC QUANTITY EXERGY Marc A. Rosen* Engineering and Applied Science, University of Ontario Institute of Technology, Oshawa, Ontario, Canada

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ABSTRACT Environmental planning takes into consideration many factors, one of which sometimes is thermodynamics. The justification for including thermodynamics in such activities is that efforts to improve understanding of and to reduce environmental impact often can be enhanced by combining thermodynamics with environmental disciplines. Most such assessments consider thermodynamics in terms of energy. Recent research has suggested that environmental impact is better understood and reduced using the thermodynamic quantity exergy. An important justification for this statement is that energy often is not a measure of the potential for environmental impact, whereas exergy has attributes of such a measure. Consequently, exergy may be able to provide a meaningful and useful tool in environmental planning. Here, we summarize existing analysis techniques that integrate exergy environmental factors, e.g. environomics, exergy-based life cycle analysis and exergy-based ecological indicators. Correlations between exergy and environmental parameters are identified using thermodynamic and environmental data, and utilized to demonstrate that exergy factors into environmental improvement. As the objectives of most exergy-based methods include improving understanding of environmental impact and ultimately reducing it through use of appropriate environmental improvement measures, the links to environmental planning have become increasingly evident and important. Several applications are considered, including the use of exergy for different environments and ecosystems to help predict and improve their wellbeing and thereby enhance environmental planning initiatives.

* Corresponding author: Email: [email protected], Tel: 905/721-8668, Fax: 905/721-3370.

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1. INTRODUCTION Environmental and ecological impacts are important considerations in environmental planning. Such considerations are also important in other areas such as the analysis, design and optimization of technologies. The latter activities often utilize techniques that combine technical disciplines like thermodynamics, usually in terms of energy, with environmental and ecological disciplines. Hence, environmental planning activities that incorporate thermodynamic factors often do so in terms of energy, which is based on the first law of thermodynamics. Energy generally is not an indicator of environmental or ecological impact potential. However, the second law of thermodynamics has been suggested to have significant implications for environmental and ecological quality and impact, and thus to be of benefit for environmental planning. The thermodynamic quantity exergy, in particular, stems from the second law of thermodynamics and has been suggested to provide an indicator of the potential for environmental or ecological impact and to help understand and assess the wellness of ecological systems (Szargut et al., 2002; Szargut, 2005; Jorgensen, 2000; Jorgensen and Fath, 2004), environmental impact (Sciubba, 1999; Tribus and McIrivne, 1971; Rosen and Dincer, 1997, 1999; Gunnewiek and Rosen, 1998; Rosen, 2002), non-renewable resource depletion (Szargut et al., 2002) and sustainable development (Dincer and Rosen, 2007). Consequently, environmental and ecological assessments and planning may be better performed utilizing exergy rather than or with energy. Several exergy-based environmental and ecological analysis techniques exist, including environomics, exergy-based industrial ecology and exergy life cycle assessment. These methods usually assist in determining appropriate allocations of resources for environmentally responsible design and operation, and environmental and ecological impacts. Exergy-based environmental and ecological techniques determine a system‘s exergy as well as its inputs and outputs, and can improve designs. Exergy thus has an important role in sustainability efforts (Dincer and Rosen, 2007). Accounting for nature‘s contribution to industrial activity is important in determining its impact and sustainability. Planning based on assessments that ignore nature significant deteriorate the ability of ecosystems to provide the goods and services needed for human activity. Understanding these issues is not straightforward, as local, regional and global ecological integrity is complex to understand, assess and maintain, despite being an important consideration in efforts to restore the environment and protect human health (Kay and Regier, 2000). Such efforts require ecological model development, including estimation of parameters and selection of a model structure based on ecological system properties, and involve challenges that are continually being investigated (Jorgensen et al., 1995). In this article, we discuss relations between exergy, environment and ecology as well as analysis techniques based on them and their potential use in environmental planning. Exergy management is illustrated in Figure 1 as one of the many factors in environmental planning.

Enhancing Environmental Planning through the Use of the Thermodynamic… 81

Environment al planning

Public sector urban and rural planning

Environment al and ecological protection

Sustainable development

Economic development

Socioeconom ic advancement

Exergy management

Figure 1. Exergy management and other factors in environmental planning

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2. EXERGY The performance and efficiency of industrial systems can be described with thermodynamics. Conventional thermodynamic analysis is based primarily on the principle of energy conservation, which is embodied in the first law of thermodynamics. An energy analysis of a process or system accounts for energy exiting (with products and wastes) and entering and usually determines efficiencies as energy ratios. But energy efficiencies do not always assess how nearly performance approaches ideality and are consequently often misleading. Also, factors which cause performance to deviate from ideality and thus introduce thermodynamic losses are often not properly described with energy analysis. For example, energy analysis can locate the principal inefficiencies wrongly in a system and assess a state of technological efficiency different than actually exists. Exergy analysis, which is based on second law of thermodynamics, circumvents these concerns (Dincer and Rosen, 2007; Gaggioli, 1983; Moran and Shapiro, 2007; Kestin, 1980; Moran, 1989; Kotas, 1995). The exergy of an energy or material quantity is a measure of its usefulness or quality, and a key difference between energy and exergy is that exergy can be consumed while energy is conserved. Exergy efficiencies provide an actual measure of how nearly performance approaches ideality, and identifies properly the causes, locations and magnitudes of inefficiencies. In particular, exergy indicates theoretical limitations, demonstrating that real systems can not conserve exergy and that only a portion of the input exergy can be recovered due to practical limitations. Its illuminating and rational basis allows exergy analysis to assist in improving and optimizing designs. Increasing application and recognition of the usefulness of exergy methods by those in industry, government and academia has been observed in recent years, with applications reported in such areas as electricity generation, cogeneration, heating, thermal energy storage, and chemical and metallurgical processes, and countries (Dincer and Rosen, 2007; Szargut, 2005; Sato, 2005).

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Exergy is evaluated with respect to a reference environment, whose intensive properties partly determine the exergy of a flow or system. The reference environment is in theory in stable equilibrium, with a constant intensive state (temperature pressure, chemical potentials) and all parts at rest relative to one another. The reference environment acts as an infinite system, and is a sink and source for heat and materials, but chemical reactions do not occur between the environmental components. The exergy of the reference environment is zero, as is the exergy of a flow or system in equilibrium with it. The reference environment may or may not simulate the natural environment, but when it does exergy analyses can be used to assess not just thermodynamic losses and efficiencies, but also potential and actual environmental impacts (e.g., for waste emissions). Extending the reference environment to the natural environment is a important consideration in enhancing the ability of exergy methods to assess and improve environmental and ecological systems and aid environmental planning. Reference environment models compromise the theoretical requirements of the reference environment and the actual behavior of the natural environment, and include process-dependent models that contain only components that participate in the process, equilibrium and constrained-equilibrium models which ―blend‖ of some subsystem of the natural environment in an equilibrium or constrained-equilibrium condition, referencesubstance models in which a ―reference substance‖ is selected for every chemical element and assigned zero exergy, and natural-environment-subsystem models. The latter model simulates realistically subsystems of the natural environment, while the others often do not resemble the natural environment.

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3. EXERGY AND ECOLOGY Exergy is considered by many to be useful in understanding and managing ecological systems. Exergy provides a useful optic because ordered ecosystems have high exergy and disordered systems low exergy. Jorgensen and Svirezhev (2004) interpret the laws of thermodynamics in an ecosystem context, using Prigogine's far-from-equilibrium thermodynamics to explain ecosystem reactions to perturbations. They feel exergy explains ecosystem reactions and growth patterns, and utilize exergy to describe the trophic chain, reactions of ecological networks and ecosystem health. Thermodynamics suggests that ecosystems seek to maximize exergy dissipation by maximizing internal exergy storage as biomass, biodiversity and complex trophical networks. Also, human activity can decrease ecosystem exergy by decreasing biomass or internal complexity, and can convert ordered self-producing ecosystems (e.g. marine estuaries and grasslands) with their resource accumulations (e.g., arable soils and mineral deposits) into damaged and disordered ecosystems (e.g., eroded farmlands and depleted fisheries). Nielsen (2000) considers a hierarchy of embedded systems for ecosystems to facilitate thermodynamics applications, and illustrates the approach for an aquatic food chain with recycling via bacterial action. Also, Salthe (2005) applied to nature the concept of energy quality. On a more fundamental level, exergy has been linked to the evolution of life, with Jorgensen (2007a) determining that exergy density and exergy flow rate are good descriptors for evolution.

Enhancing Environmental Planning through the Use of the Thermodynamic… 83

3.1. Exergy-Based Ecological Indicators Exergy has been used widely in ecological models, especially for aquatic ecosystems (Jorgensen, 1992b, 2002a). Marques et al. (1998) propose exergy as a holistic ecosystem indicator, while Mauersberger (1995) suggests that entropy is a controlling factor for complex ecological processes. Ecosystems have been hypothesized to develop according to increases in four system attributes: ascendency, storage of exergy, ability to dissipate external gradients in exergy, and network aggradation. Ulanowicz et al. (2006) reconcile the attributes of ecosystems by considering exergy, information and aggradation. The exergy for organisms has been studied, including the applicability of genome size in exergy calculations (Debeljak, 2002) and the utilization of nuclear DNA in the determining the exergy of biomass organisms (Fonseca et al., 2000). Ecological exergy is often viewed as a system-oriented development indicator, and thus may have a role in environmental planning.

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Structural changes: Ecological structural changes appear to be accompanied by increased exergy (Jorgensen, 1988). Bendoricchio and Jorgensen (1997) provide a rationale for applying exergy as goal function, and exergy has been applied in structural-dynamical modeling (Nielsen, 1990). Jorgensen et al. (2002) suggest that an exergy index can be used with ecosystem models to determine which structures prevail for given environmental circumstances, with the structure having the highest exergy prevailing. Exergy also is a measure of the information level of communities, and Park et al. (2001) implemented artificial neural networks in patterning and predicting exergy by utilizing the capabilities of such networks for information extraction and self-organization. Ecological processes: Exergy efficiencies for ecological processes can be determined in numerous ways. Zhou et al. (1996) propose evaluation methods for different types of exergy in living systems, considering the relevant physical-chemical and physiological-ecological processes. Exergy balances for animal and plant life can be constructed with this method, leading to four ecological exergy efficiency indices. Although exergy analysis has been extended for life cycle and sustainability evaluations of industrial processes, such extensions neglect the role of ecosystems in sustaining industrial activity (Hau and Bakshi, 2004). Maturity: Exergy has been suggested as a measure of ecosystem maturity, partly from a ranking of aquatic ecosystems on the basis of several of Odum‘s attributes of ecosystem maturity (Christensen, 1995). A comparison with rankings based on various ecosystem goal functions shows that maturity exhibits a strong negative correlation with relative ascendency, and thus a strong positive correlation with system overhead, a possible measure of ecosystem stability. Extremal principles and optimization: Ecological indices provide information about aspects of ecosystem behavior, often assuming ecosystems are optimizing exergy. Exergy has been considered as a constrained optimizing function in a structural dynamical model, and tested on biomanipulation of the phytoplankton community in a shallow lake (Nielsen, 1995). The shift in composition in a macrophyte society can be understood using exergy (Nielsen, 1997), and four types of exergy (traditional exergy, internal exergy, structural or modern exergy, normalized exergy) have been proposed as goal functions in ecosystem development

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and optimization. A dynamic structural model able to describe the observed changes in phytoplankton biomass and diversity was developed and tested to determine if it behaves according to the hypothesis that ecosystem reactions strive to maximize exergy under prevailing conditions (Jorgensen and Padisak, 1996). Extremal principles or ecological orientors or goal functions are commonly used today in theoretical ecology. Exergy and ascendency are two widely accepted goal functions, which Ray (2006) optimized in an aquatic ecosystem. Fath and Cabezas (2004) contrasted two ecological indices (exergy and Fisher Information) and their potential as ecological goal functions by comparing the indices on a ten-compartment food web model undergoing five perturbation scenarios. Buffering capacity and constraints: Exergy has been argued to be tied to ecological constraints (Jorgensen, 1992a) and to relate to the buffering capacity of ecological systems (Jorgensen, 1982).

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Dissipation: Biological dissipation occurs during respiration, excretion, egestion, natural and predatory mortality and other activities. Dissipation manifests itself as exergy destruction and involves degradation from more to less organized states, affecting the formation of structures, growth and development. Straskraba et al. (1999) suggest that trophic pyramids and ecological efficiencies account for dissipation, and that environmental concerns can be explained as a dissipation-driven entropy challenges. Mandal et al. (2007) examined thermodynamic properties in an ecological model shifting from ordered to chaotic for three species (phytoplankton, zooplankton, fish), as well as the exergy of systems at the edge of oscillation before entering the chaotic situation, suggesting that the equilibrium of an ecosystem may gradually become chaotic Biodiversity: Ecosystems often adapt when faced with external changes, e.g. new species take over if present ones are unable to cope with changes. The use of exergy as goal function provides ecosystem models with the flexibility of real ecosystems and in some ways is a translation of Darwinian selection into thermodynamics (Jorgensen, 1992c). Benthic eutrophication often gives rise to qualitative changes in marine and estuarine ecosystems, such as shifts in primary producers. Exergy has been applied in structural dynamic models of shallow lakes (Marques et al., 1997) with exergy optimised during ecosystem development so that an ecosystem self organises towards a state of an optimal configuration of exergy. Exergy constitutes a system characteristic that expresses the natural tendencies of ecosystems to evolve and a good ecological indicator of ecosystem health. The ecological significance of exergy was also tested against biodiversity, an important characteristic of ecosystem structure, by examining spatial and temporal relations between exergy and biodiversity along an estuarine gradient of eutrophication (Marques et al., 1997). Although biodiversity interpretations are somewhat subjective, exergy and specific exergy have been suggested as suitable alternative goal functions in ecological models and holistic ecological indicators of ecosystems integrity. Holling proposed a four-phase conceptual model of ecosystem dynamics as a guide for evaluating the impact of climate change on biodiversity, a measure of species richness and heterogeneity, with exergy used in one approach (Hansell and Bass, 1998).

Enhancing Environmental Planning through the Use of the Thermodynamic… 85 Health and quality: Exergy and specific exergy of macrophytes have been tested as an integrated index to assess ecosystem health in coastal lagoons, considering 244 seaweed and seagrass species common to Mediterranean coastal lagoons and 71 sites in coastal lagoons of Southern France (Austoni et al., 2007). Exergy and structural exergy, trophic state index, diversity index and phytoplankton buffer capacity all were considered as measures to assess ecosystem health for a shallow eutrophic lake in China (Xu, 1996). It is often necessary to calculate the exergy for organisms, and thir exergy can be estimated as the product of the biomass concentration and a weighting factor that accounts for the information carried by the organisms (Jorgensen, 2002a; Eichler and Sankoff, 2003). Jorgensen et al. (2005) describe several indirect methods to determine weighting factors, accounting for age of the organisms, number of cell types, minimum DNA content and ratio of non-coding genes to total number of genes (Mattick, 2003). Chemical exergy may provide a unified objective indicator for water quality, avoiding the subjective characteristics of conventional indicators, while the adaptability of chemical exergy-based indicators for water quality was evaluated for 72 rivers and 24 lakes (Chen and Ji, 2007). By extension, exergy may provide a unified measure of water quality and pollution (Huang et al., 2007).

3.2. Eco-Exergy and Emergy

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Eco-exergy and emergy are both exergy-based quantities used in assessing ecosystems. Eco-exergy: Eco-exergyis a modified form of exergy which measures a system‘s deviation from chemical equilibrium. The two main differences between exergy and ecoexergy are that eco-exergy uses a changed reference state which is more useful for ecological applications, and accounts for the contribution of information exergy. When shifting from macroscopic to microscopic information storage, the exergy contribution due to information is as much as three orders of magnitude greater than conventional exergy for complex living systems (Susani et al., 2006). Jorgensen (2006) proposes as ecological indicators for ecosystem development and health 1) eco-exergy, 2) specific eco-exergy, which is the ratio of eco-exergy to biomass, and 3) ecological buffer capacities. He shows that attributes for ecosystem development and descriptors of ecosystem health are accounted for by growth of biomass, network and information. Although ecosystems are complex, some eco-exergy indices have been reported, e.g., detritus (Jorgensen and Nielsen, 2007). Eco-exergy and exergy destruction have been utilized to describe the development of an aquatic ecosystem. Jorgensen (2007b) determined the respiration rate and stored eco-exergy for 26 aquatic ecosystems, while Odum (1969) demonstrated that the respiration rate peaks for a given type of aquatic ecosystem. The eco-exergy storage in an ecosystem has been used for assessing terrestrial ecosystems and support the ―Ecological Law of Thermodynamics‖ (Jorgensen et al., 2000; Jorgensen, 2002b; Jorgensen and Svirezhev, 2004). Emergy: Emergy, the solar energy required directly and indirectly to generate a flow or storage, has been proposed as an objective function for ecosystems. Emergy is not a state property, as it accounts for the history, time and processes that have occurred prior to the

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present state of the system. The emergy approach allows assessments of self-organizing systems such as ecosystems and the biosphere (Bastianoni and Marchettini, 1997). Emergy analysis is a thermodynamic method from systems ecology. Emergy accounts for energy quality using a transformity factor, which is found from an ecological network as the number of solar equivalents needed to construct a given organism. Both exergy and emergy analyses seek to represent the behavior of physical systems with cumulative energy input/output methods over space and time. But emergy analysis focuses on energy and resource flows for ecosystems, while exergy analysis provides insights like quantified irreversibilities and the matching of inputs and end-uses (Sciubba and Ulgiati, 2005). Further, energy-based emergy differs from exergy-based emergy Bastianoni et al. (2007). Emergy and transformity can be written as a function of exergy alone, using partial efficiencies of the processes involved in a production system starting with solar energy and ending with a final product. Exergy and emergy assessments have been compared for ethanol production from corn, with both methods yielding a set of performance indicators (Sciubba and Ulgiati, 2005). Exergy calculations for higher organisms based only on traditional thermodynamics do not account for organization. Alternative approaches have been suggested based on the thermodynamic information of genes and on the cost of free energy for an ecological network. The latter method is theoretically less sound because it does not consider the increase of information due to evolution. While reflecting some of the differences between emergy and exergy, the results for the two methods are of the same order of magnitude (Jorgensen et al., 1995). Emergy and exergy can be considered complementary objective functions, with both able to describe self-organizing systems like ecosystems (Bastianoni and Marchettini, 1997). Ecological extremal principles can be integrated for such quantities exergy, emergy, power and ascendancy (Patten, 1995). Some methods integrate exergy and emergy, e.g., Jorgensen et al. (2004) have evaluated the emergy and exergy of genetic information and its biological carriers. The chemical exergy of genes is determined using detritus as the reference environment, and the emergy used to construct and maintain biological organisms is evaluated using average global emergy input to the biosphere. Emergy-exergy ratios for genes and solar transformities for biomass are determined with generalized data for populations of organisms from bacteria to large mammals. The emergy required to generate the genetic information in the biosphere today has been estimated (Jorgensen et al., 2004). The relation between the emergy costs of gene maintenance and the solar transformity of biomass suggests that the emergy costs of maintaining a biological carrier increases faster than the information carried as the complexity of the information carrier increases. The emergy-exergy ratio for a flow provides the concentration of solar energy equivalent (emergy) required to maintain or create a unit of organization (exergy) (Bastianoni and Marchettini, 1997), and measures how efficiently a system organizes or maintains its complexity, providing the environmental cost for the production of a unit of organization. The emergy-exergy ratio for three coastal lagoons, two built to purify sewage, was fiybd to be lowest for the natural ecosystem and highest for the waste pond; the ratio decreases over time for the control and the waste ponds, implying these organize via natural selection. It was subsequently found that maximum emergy and maximum exergy principles in ecosystems both have practical validity and should be applied in sequence, with emergy maximization preceding exergy maximization (Bastianoni et al., 2006).

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3.3. Environmental Planning Based on Exergy and Ecology The relations between exergy and ecology discussed in this section can be incorporated into environmental planning. Exergy-based ecological indicators for ecological processes, like structural changes, maturity, buffering capacity, dissipation, biodiversity, health and quality, all provide useful information for understanding and managing ecosystems. Ecoexergy provides a useful measure and indicator for ecosystem development and health. Emergy also provides an objective function that describe self-organizing systems like ecosystems. Methods to plan and manage environmental systems usually are best informed when they take into consideration all available information, including exergy and ecology relations.

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4. EXERGY AND ENVIRONMENT Increasing exergy efficiency reduces environmental impact by reducing requirements for energy resources and emissions. But relations between exergy and the environment can reveal further underlying fundamental patterns affecting environment changes. Exergy is linked to environmental impact since it is a measure of the departure of the state of a system from that of the environment (Ayres et al., 1998; Berthiaume et al., 2001; Creyts and Carey, 1997; Gunnewiek and Rosen, 1998; Frangopoulos and von Spakovsky, 1993; Rosen and Dincer, 1997, 1999; Dincer and Rosen, 2007; Sciubba, 1999; Wall and Gong, 2001; Baumgärtner and de Swaan Arons, 2003; Jorgensen and Svirezhev, 2004). Exergy is a measure of potential of a substance to cause change, so the exergy of an emission can provide a measure of the potential of the emission to change or impact the environment. The exergy of an emission is zero only when it is in equilibrium with the environment and thus benign. Thus exergy may be, or provide the basis for, an effective indicator of the potential environmental impact of an emission, which can be utilized in environmental planning. Decades ago it was suggested that exergy analyses of natural processes on Earth could provide a foundation for ecologically sound planning (Tribus and McIrvine, 1971) and that exergy could be part of air-pollution rating (Reistad, 1970), and applications of exergy in environmental impact have since increased (Ayres et al., 1998; Berthiaume et al., 2001 ; Creyts and Carey, 1997; Gunnewiek and Rosen, 1998; Frangopoulos and von Spakovsky, 1993; Rosen and Dincer, 1997, 1999; Dincer and Rosen, 2007; Sciubba, 1999; Wall and Gong, 2001; Baumgärtner and de Swaan Arons, 2003; Jorgensen and Svirezhev, 2004; Connelly and Koshland, 1997, 2001a, 2001b, 2008). Exergy also can assist in allocating emissions reasonably among the outputs of multi-product systems (e,g, cogeneration). Emissions allocation proportionally to the exergy of the outputs can provide a fair approach, which helps attribute appropriately the causes of environmental damage.

4.1. Exergy-Based Environmental Methods Several exergy-based environmental methods have evolved, which may be incorporated in environmental planning.

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Reducing industrial emissions via increased exergy efficiency: Insights provided by exergy analysis are important in identifying where improvement efficiency potential lies and generating policy advice on sustainability (Hammond, 2004). An approach for improving energy systems design that considers the process (including exergy), the environment and economics has been developed (Giannantoni et al., 2005) . An evaluation method has been proposed for the environmental sustainability of industrial processes that uses exergy analysis to combine different material and energy streams and uses a life cycle approach (Yi et al., 2004).

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Cumulative exergy consumption: The environmental impact of industrial processes can be assessed via the exergy consumption accumulated over processes. Szargut et al. (2002) suggest that the cumulative consumption of non-renewable exergy provides a measure of the depletion of non-renewable natural resources. Industrial cumulative exergy consumption evaluates the exergy of all natural resources consumed by economic sectors. The cumulative exergy consumption approach has been used for the treatment of emissions (Zhu et al., 2005). Cumulative exergy consumption has been extended to ecological cumulative exergy consumption so as to incorporate the contribution of ecosystems (Hau and Bakshi, 2004). Ecological cumulative exergy consumption accounts for the exergy consumed in ecological systems in producing natural resources. Industrial and ecological cumulative exergy consumptions in the U. S. in 1997 were determined by evaluating flows of cumulative exergy in 488 sectors (Ukidwe and Bakshi, 2007). A generalization of the approach in resource analysis and ecological evaluation has been developed based on embodied exergy, i.e. the cosmic exergy consumed directly or indirectly in creating or sustaining a commodity or service (Chen, 2006). Extended exergy accounting: Extended exergy accounting facilitates assessments of a complex system by determining the cost of a commodity based on its resource-base equivalent value and includes equivalent exergy flows for labor, capital and environmental remediation (Sciubba, 2004). The method has been used to evaluate environmental externalities and suggested for forming pollution policies (Sciubba, 2001b). Exergy and industrial ecology: Industrial ecology is an approach to designing industrial systems that seeks improved environmental performance by balancing industrial activity and environmental stewardship and by making industrial systems behave more like ecosystems, where energy and materials are entirely recycled (Graedel, 1996). Industrial ecology can beneficially incorporate exergy (Connelly and Koshland, 2001a, 2001b; Dewulf and Van Langenhove, 2002; Dincer and Rosen, 2005). Zvolinschi et al. (2005) apply exergy sustainability indicators as a tool in industrial ecology, while Kay (2002) treats systems of varying complexity, accounting for exergy flows and considering applications in industrial ecology. Exergy and life cycle analysis: Life cycle assessment (LCA) is a technique for preventing pollution and improving environmental management and performance in which the entire life cycle is considered (ISO, 1997). LCA can be extended by considering exergy to exergetic LCA (Granovskii et al., 2006, 2007). Exergetic LCA extends the objectives of LCA

Enhancing Environmental Planning through the Use of the Thermodynamic… 89 to considering exergy flows and destructions and options for reducing exergy destructions and increasing exergy efficiency. Exergy and ecological footprint and environomics: Exergy has been integrated into ecological footprint and environomics assessment methods. The aggregate indicator ecological footprint has been extended to embodied exergy ecological footprint, which shows the ecological overshoot of ecological systems (Chen and Chen, 2007). Environomics simultaneously accounts for energy, exergy, economic and environmental factors when analyzing energy systems (Frangopoulos and von Spakovsky, 1993). Other methods: Exergy analysis has been applied to eco-industrial systems, providing indicators of resource-utilization efficiency and environmental-impact potential based on exergy and identifying relations to industrial ecology (Li et al., 2006). For biological production systems like agriculture, indicators have been developed based on ecosystem thermodynamics, in part by measuring the capacity of an ecosystem to dissipate solar exergy (Wagendorp et al., 2006). Attempts have been made to convert exergy‘s linkages with pollution and dispersion into a reliable tool on which policy decisions can be based. Design for environment methods focus primarily on subjective ranking techniques, but can incorporate exergy analysis to provide less subjective metrics (Connelly and Koshland, 1997, 2001a, 2001b, 2008).

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4.2. Environmental Planning using Exergy and Its Role as an Environmental Indicator Several types of environmental impact are predictable using exergy as an environmental indicator. First, the exergy associated with wastes (especially chemical exergy) emitted to the environment represents in some ways a potential to cause change, which can harm the environment. Exergy accounts for the fact that not all types of emissions pose equal risks. Exergy emissions can also interfere with the net input of exergy via solar radiation to the Earth, and contribute to global warming. Second, the degradation of resources found in nature destroys their exergy and is a form of environmental damage. For instance, combustion reduces order as does the release of a pure substance like carbon dioxide into the atmosphere and its subsequent mixing and dilution. Third, a form of environmental damage is associated with the creation of chaos or disorder, which is represented by a state of low exergy (or high entropy). A low-exergy system (e.g., carbon dioxide mixed in the atmosphere) is more disordered than one of high exergy (e.g., carbon dioxide in a tank). The difference between the exergy values of a system in ordered and disordered states is a measure of the work required to re-order the system. The above points suggest a role for exergy in environmental planning. Evaluating alternative device options often involves comparisons of their emissions. Existing methods are usually subjective and often based on energy, yet energy itself does not seem to provide a good indicator of the environmental impact. Exergy is a more objective indicator for potential environmental impact. Emissions only possess exergy when in disequilibrium with the environment.

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5. EXTENSIONS TO ECONOMICS AND ENVIRONMENTAL PLANNING The ties between exergy, environment and ecology can be extended to economics, and thus made more relevant to environmental planning. For instance, exergy‘s potential as an indicator of environmental impact can be incorporated in exergy-based economic assessments and environmental impact costs and protection can be included in exergy-based economic analyses. By extending exergy and economics to account for environmental effects, techniques can developed that minimize life cycle costs while reducing environmental effects. Several researchers have investigated exergy and environmental economics (Edgerton, 1982). Sciubba (2005) has also proposed exergoeconomics as a thermodynamic foundation for rational resource use. Ayres (1998) links economics and the second law in what he refers to as ecothermodynamics and suggests that exergy has strong implications on economic growth theory. Sciubba (2001a, 2003, 2004) extends exergy accounting and thermoeconomics with environmental factors to improve the analysis and design of energy processes and systems, and proposes Extended Exergy Accounting as a cost analysis method for energy systems using a resource-based quantifier (extended exergy). Environmental remediation costs are taken into account by determining the equivalent cumulative exergy expenditure required to achieve zero impact. Lazzaretto and Toffolo (2004) show how energy-system designs can be optimized using separate objectives relating to energy (and exergy), economics and the environment. An environmental impact objective function is expressed in cost terms by weighting carbon dioxide and nitrogen oxide emissions according to their unit damage costs. Tonon et al. (2006) propose a comprehensive analysis method based on energy, exergy, economic and environmental factors. Emissions are considered and performance indicators developed that help assess possible areas of improvement. A thermoeconomic method to increase the efficient use of exergy resources based on a carbon exergy tax is proposed (Santarelli, 2004). To obtain exergy-based indicators of sustainable development, Ferrari et al. (2001) integrate thermodynamics and economics. Exergy also has been applied to the economy to develop a model for sustainable development at the macro-economic level by combining resource depletion with pollution to reduce degradation losses (Honkasalo, 1998). Exergy-based economics have been linked to ecology. For instance, a method for performance evaluation under maximum ecological and maximum economic conditions is proposed, where the ecological function is represented by the power output divided by the entropy generation rate and the economic function by the power output divided by the total cost (Tyagi et al., 2007). Also, an ecological economics perspective of economic development and environmental protection is provided by Rees (2003). Ecological economics interprets the environment-economy relation in terms of exergy, which views economic activity as a dissipative (exergy consuming process. Pristine ecosystems are typically observed to be ordered and have high exergy while damaged ecosystems are disordered and have low exergy. Rees notes that the ascendance of humanity has consistently been accompanied by an accelerating rate of ecological degradation, and observes that economic development unavoidably conflicts with environmental protection. Environmental planning can be made more comprehensive and meaningful if it utilizes the extension to economics of the links between exergy, environment and ecology. The use of exergy measures as indicators of environmental or ecological impact along exergy-based

Enhancing Environmental Planning through the Use of the Thermodynamic… 91 economic assessments and environmental impact costs can inform planning, thereby allowing rational decisions that manage the environment advantageously.

6. APPLICATIONS OF EXERGY IN ECOLOGY AND ENVIRONMENT

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A breakdown is presented in Figure 2 of the many factors involved exergy management in environmental planning, as discussed in the previous sections. Numerous applications of these exergy methods to ecosystems and other environmental systems have been reported that serve to demonstrate some of the potential uses of the methods in environmental planning. Some of these applications are discussed in this section.

Figure 2. Breakdown of factors involved exergy management in environmental planning

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6.1. Exergy and Ecology Applications

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Exergy-based ecological models and methods have been applied to various ecosystems, particularly aquatic. The stresses in ecosystems from pollution have made it important to have meaningful indicators for assessing the effects of pollution in those communities. Exergybased indicators of ecosystem integrity facilitate detection and evaluation of environmental responses to pollution, mitigation of the harmful impacts and effective ecosystem management.

6.1.1. Lakes, lagoons and seas Applying exergy in the ecological modelling of a lake environment has demonstrated that exergy can act as an object function in ecological models for lakes and reservoirs, an ecological indicator for the development and evolution of lake ecosystems and a component of structural dynamic models that account for ecosystem changes (Zhang and Wang, 1998). Additional support for exergy being an object function in lake models was provided by an examination for a generic lake of the exergetic response to changes in phytoplankton growth parameters and species composition, with exergy used as a measure of the build-up of biological structure of a natural lake ecosystem (Salomonsen and Jensen, 1996). Xu (1997) applied exergy and structural exergy as ecological indicators to assess the development state of the ecosystem of Lake Chao, a eutrophic in China, and the restoration of riparian wetlands and macrophytes in Lake Chao. It was observed that macrophyte restoration could decrease phytoplaniton biomass and increase fish biomass, exergy, structural exergy, zooplankton/phytoplankton ratio and transparency, implying that macrophyte restoration can purify lake water, regulate lake biological structure and control eutrophication (Xu et al., 1999). Ludovisi and Poletti (1999) also applied exergy and structural exergy as ecological indicators for the development state of homogeneous lake ecosystems. Exergy and structural exergy were used to assess the aquatic ecosystem consisting of the mesocosms and microcosms of Lake Baikal (Silow and Oh In-Hye, 2004). That work supported the use of structural exergy as a measure of ecosystem health in that it was observed that the structural exergy of the communities decreased after the addition of allochtonous compounds (peptone, diesel oil) to the mesocosms, the addition of toxicants to the microcosms, and discharges from Baikal Pulp and Paper, which polluted the area (based on the exergy contents for benthos in polluted and unaffected regions). Exergy and structural exergy were demonstrated to be feasible ecological indicators of system-level responses of lake ecosystems to chemical stresses via tests of the system-level responses of experimental lake ecosystems to three chemical stresses: acidification, copper and pesticide contamination were determined (Xu et al., 2002). Large changes occurred in some instances, indicating the ecosystems were seriously contaminated by the chemical stressors while small changes were observed at other times suggesting the lake ecosystems were not significantly impacted. The observed changes in exergy and structural exergy were consistent with expectations of reduced food chains, resource-use efficiency, stability, information and exergy in stressed aquatic ecosystems. Also, the pelagic trophic food chain in Lago Maggiore, Switzerland was examined from 1978-1992 in part by determining the exergy content in the food chain (de Bernardi and Jorgensen, 1998). The approach helped better describe functioning mechanisms for the food chain, predict the most significant factors

Enhancing Environmental Planning through the Use of the Thermodynamic… 93

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affecting ecosystem function, estimate the efficiency of the food chain in utilizing available resources and verify ecological models. For the Mar Menor lagoon, a Mediterranean coastal lagoon in south-eastern Spain, the exergy index and specific exergy provided useful information on community structure when applied as ecological indicators of organically enriched regions in the lagoon (Salas et al., 2005). These indicators were suggested to be insufficient alone to act as comprehensive ecological indicators because exergy and specific exergy did not distinguish levels of organic enrichment or the effects of all types of pollution. Based on examinations of the communities in the sandy and muddy bottoms of the North Adriatic Sea, exergy has been cited as a useful indicator for integrating the underlying recovery processes of benthic communities after disturbances, based on an application of exergy as an ecosystem indicator during the recovery of marine benthic communities (Libralato et al., 2006). The complex dynamics that occur in a disturbed community during recovery processes are usually difficult to assess with conventional indices, but exergy as a measure of the departure of a system from equilibrium has been proposed as a useful ecological indicator in this context. A controlled trawl fishing haul was the disturbance, and the local exergy storage of the benthic community was used and exergy was estimated with data for trophic groups, coding genes of broad taxonomical groups and genome size. Local exergy content decreased in disturbed areas, peaking in sandy and muddy bottom one month after the disturbance and subsequently increasing to the reference or surrounding level. This result is consistent with the dynamics of exergy storage during the development of systems. As anticipated, the dynamics of exergy in the two habitats differed. The results may be extendable to biological systems (Libralato et al., 2006).

6.1.2. Macroinvertebrate communities and plants Reis and Miguel (2006) reported an exergy balance of green leaves and Park et al. (2006) used self-organizing maps to pattern the exergy of benthic macroinvertebrate communities. The latter work utilized data for 650 sites in the Netherlands including 855 species. The exergy was calculated using biomass data for five trophic functional groups: carnivores, detritivores, detritivore–herbivores, herbivores and omnivores. The response of the exergy of the different trophic groups varied with ecosystem characteristics, suggesting that patterning changes of exergy is effective for evaluating ecosystems, and exergy can act as an effective ecological indicator.

6.2. Exergy and Environment Applications Methods integrating exergy and the environment have been applied to a wide range of devices, systems and processes, including heating, cooling, power generation, cogeneration, chemical processing, separation and fuels production. These applications of exergy methods are directly transferrable to environmental planning.

6.2.1. Heating and cooling Exergy assessments including environmental factors have been reported for a variety of thermal processes related to heating and cooling, including psychrometric devices, heat

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pumps, drying systems, thermal storage technologies and cryogenic devices (Dincer and Rosen, 2007; Rosen and Dincer, 2002). In an exergy-based economic optimization of the geometry of a precooling air reheater for air conditioning, Jassim et al. (2005) optimized the total cost function based on the optimum heat transfer area and the total irreversibilities. An assessment has also been undertaken of cold thermal energy storage system using a glycol working fluid (Bakan et al., 2008). EXCEM analysis (Rosen and Dincer, 2003), an exergybased method that simultaneously considers cost, energy and mass, has been applied to such processes as a greenhouse heating system using a solar-assisted ground-source heat pump (Ozgener and Hepbasli, 2005), ground-source heat pump systems for building applications (Ozgener et al., 2005) and geothermal district heating (Ozgener et al., 2007).

6.2.2. Power generation and cogeneration Numerous exergy-based environmental assessments have been reported for electrical power generation and processes that simultaneously produce multiple products. The latter include cogeneration of electricity and heat (i.e. combined heat and power) as well as trigeneration of electricity, heat and cold. A complex Brayton cycle for power generation was investigated considering ecological and economic conditions (Tyagi et al., 2007). The ecological function was defined as the ratio of power output to entropy generation rate and the economic function as the ratio of power output to total cost. The cycle was optimized by adjusting several operating conditions, including cycle temperatures and reheat and intercooling pressure ratios. Values were determined of turbine outlet temperature and several pressure ratios at which the cycle is maximized in terms of the ecological and economic objectives while minimizing the entropy generation rate. Also, exergy and environmental analyses have been reported of the power plants in transportation systems like aircraft (Rosen and Etele, 2004) and automobiles (Daniel and Rosen, 2002). Rosen and Ao (2008a, b) used exergy to assess air pollution levels from a smokestack. Furthermore, a combined power plant consisting of a solid oxide fuel cell and gas turbine was assessed using a thermoeconomic method based on a carbon exergy tax that directed at increasing the efficient use of exergy resources (Santarelli, 2004). Also, hydroelectric and thermoelectric power generation processes were analyzed with a comprehensive method based on exergetic and economic parameters as well as environmental emissions (Tonon et al., 2006). A photovoltaic-hydrogen system for residential buildings was also assessed (Santarelli and Macagno, 2004). Methods for extending exergy accounting and thermoeconomics with environmental factors were applied to gas turbine-based cogeneration to optimize the design (Sciubba, 2001a, 2003). An exergy-based efficiency analysis of a cogeneration and district energy system, with environmental benefits, was also reported (Rosen et al., 2005). 6.2.3. Chemical processes Some processes for chemical and fuel processing and separation have been investigated with exergy-based environmental methods to improve understanding and designs. For example, an analysis method based on exergetic, economic, environmental and other parameters has been applied to bioethanol production (Tonon et al., 2006). Also, an exergetic evaluation of the renewability of a biofuel has been carried out by Berthiaume et al. (2001). An exergetic environmental assessment of life cycle emissions for various automobiles and

Enhancing Environmental Planning through the Use of the Thermodynamic… 95 fuels, which focused on emissions, was reported (Daniel and Rosen, 2002). Also, the exergy of the emissions for two energy conversion technologies, considering their potentials for environmental impact, were compared and contrasted (Crane et al., 1992).

6.3. Contributions of Applications to Environmental Planning The applications of exergy methods to ecosystems and other environmental systems show their potential uses in environmental planning. The results demonstrate how exergy based methods can provide useful information that guide decisions, and that exergy-based environmental or ecological parameters can act as objective functions or constraints in planning exercises.

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7. ILLUSTRATIVE EXAMPLE The exergy-based ecology and environmental analyses and concepts discussed in this article are demonstrated through an illustrative example, which considers the correlation of exergy with other environmental-impact indicators. Specifically, the exergy of waste emissions is compared to other selected measures to assess or control the potential environmental impact of emissions, including air emission limits established by the government of Ontario, Canada, and two quantifications of ―environmental costs‖ for emissions from fossil fuel combustion. These comparisons, based on a previous analysis (Gunnewiek and Rosen, 1998), help identify trends and patterns that may permit the exergy of a substance to be a useful indicator of potential environmental impact and consequently to be a tool for establishing emission limits that are rationally based rather than formulated by trial and error. Air pollution limits in Ontario are covered by the provincial Environmental Protection Act. That legislation aims to ensure environmental conditions such that human health and the ecosystem of the Earth are not endangered. In Ontario, the Ministry of the Environment develops and implements environmental legislation for industry. Allowable air emission limits (i.e., pollutant mass per air volume averaged over a specified time), which must be achieved prior to discharge, are listed for numerous substances. Point of Impingement (POI) air emission limits are determined considering the best available pollution control technology. The potential of a substance to impact the environment is evaluated by ten parameters:        

transport, persistence bioaccumulation, acute lethality sub-lethal effects on mammals, sub-lethal effects on plants, sub-lethal effects on non-mammalian animals, teratogenicity,

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A. Marc Rosen Table 1. Environmental pollution costs for selected pollutants Pollutant Particulates* CO NOx SO2 CH4 Volatile organic compounds CO2

Environmental pollution cost ($/kg pollutant) 4.95 4.46 3.50 3.19 1.17 0.54 0.036

* Includes heavy metals such as lead, cadmium, nickel, chromium, copper, manganese and vanadium.

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 

mutagenicity/genotoxictiy, and carcinogenicity.

Two methods for developing environmental costs for air emissions are considered. In the first method, the cost is considered of removing pollutants from the waste stream prior to discharge to the environment, for air emissions from fossil fuel combustion. This cost can be related to the exergy of the pollution, and is referred to as the Removal Pollution Cost (RPC). The removal cost for a waste emission is evaluated as the total fuel cost per unit fuel exergy multiplied by the chemical exergy per unit fuel exergy, and divided by the exergy efficiency of the pollution removal process. The exergy efficiencies for removing pollutants from waste streams vary. Some sources indicate that exergy efficiencies are below 5% when removal involves mechanical separation. For simplicity, exergy efficiencies of 1% for all pollutants are used here. In the second method, environmental costs of pollutant, referred to here as Environmental Pollution Costs (EPCs), are estimated. Such work is most advanced for atmospheric emissions from fossil fuel combustion. Environmental costs for some emissions have been estimated for Canada (see Table 1). Values for EPCs are based on quantitative and qualitative evaluations of the cost to correct or compensate for environmental damage, and/or to prevent a harmful emission. Environmental pollution cost values in Table 1 are reported in 2006 Canadian dollars; these costs are based on values from 1990, with an adjustment applied to the dollar values to account for inflation in Canada between 1990 and 2006 as measured by the Consumer Price Index for all products. Statistics Canada reports the adjustment factor as 1.401, which represents a 40.06% increase over the 16 year period or an average annual inflation rate of 2.13%. Preliminary relations have been discerned for POI air emission limits, standard chemical exergies, RPCs and EPCs. Environmental Pollution Cost appears to increase with increasing standard chemical, and to increase at a decreasing rate with increasing percentage of pollution emission exergy. The two measures considered here for the environmental cost of pollutants (RPC and EPC), although based on different principles, are of the same order of magnitude for a given pollutant. The RPC methodology is based on a theoretical concept, while the EPC methodology relies on subjective interpretations of environmental impact data. Thus, exergybased measures for environmental impact may provide a foundation for rational environmental indicators and tools. Environmental Pollution Cost and Removal Pollution

Enhancing Environmental Planning through the Use of the Thermodynamic… 97 Cost are two different types of indicators, among the many existing and possible ones. EPC and RPC provide good examples for comparisons with exergy as indicators of environmental impact, since they are founded on different rationales. EPC is the environmental cost of a pollutant, based on such factors as the societal cost to compensation for environmental damage and to prevent a harmful emission. RPC is the cost of removing a pollutant from a waste stream prior to discharge into the environment. The illustrative example shows that exergy-based ecology and environmental concepts can form part of environmental planning, with respect to measures to assess or control the potential environmental impact of emissions. The correlations of exergy of waste emissions with other environmental-impact indicators (government air emission limits and two quantifications of environmental costs for hydrocarbon combustion emissions) suggest that the exergy of a substance may provide a useful indicator of potential environmental impact and consequently to be a tool for rationally establishing emission limits in environmental planning.

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8. CLOSING REMARKS Exergy exhibits many interesting and useful relations with ecology and the environment. Exergy-based relations can provide a foundation for exergy-based ecological and environmental methods, which are useful in analysis, comparison and improvement activities. By integrating thermodynamics with ecology and environment concepts, the methods can help achieve advantageous designs, accounting for observations that environmental and ecological health may be better based on exergy. More generally, it appears that environmentally successful systems may be configured so as to balance appropriately exergybased economic and environmental and ecological factors. The merits of exergy analysis over the more conventional energy analysis are highlighted from a thermodynamic perspective and also from a combined thermodynamic and environmental/ecological perspective. It is emphasized that analogous relations between energy and ecology and the environment differ in important ways and in general are not useful and sometimes are misleading. For instance, it is shown that exergy, but not energy, is often a measure of the potential for ecological and environmental impact, and that exergybased ecological and environmental indicators are meaningful and merit further investigation. It is hoped that this article helps raise awareness and appreciation of the merits of exergy analysis and exergy-based environmental and ecological methods. The applications discussed suggest that exergy should factor into environmental planning, including environmental remediation and ecological management. Furthermore, the illustrative example considered demonstrates how the insights gained via exergy can assist in integrating thermodynamics into environmental planning, especially by exploiting the correlations with environmental and ecological parameters.

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Acknowledgments Financial support for this work was provided by the Natural Sciences and Engineering Research Council of Canada and is greatly appreciated, as are the contributions to elements of the work reported here over many years by many colleagues including Frank Hooper, David Scott, Ibrahim Dincer, Yongan Ao, Lowy Gunnewiek and Mikhail Granowskii.

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Enhancing Environmental Planning through the Use of the Thermodynamic…101 Jorgensen, S. E. (2002b). Integration of Ecosystem Theories: A Pattern, 3rd ed. Dordrecht, The Netherlands: Kluwer Academic. Jorgensen, S. E. (2006). Application of holistic thermodynamic indicators. Ecological Indicators, 6(1), 24-29. Jorgensen, S. E. (2007a). Evolution and exergy. Ecological Modelling, 203, 490-494. Jorgensen, S. E. (2007b). Description of aquatic ecosystem's development by eco-exergy and exergy destruction. Ecological Modelling, 204, 22-28. Jorgensen, S. E. & Fath, B. D. (2004). Application of thermodynamic principles in ecology. Ecological Complexity, 1, 267-280. Jorgensen, S. E., Ladegaard, N., Debeljak, M. & Marques, J. C. (2005). Calculations of exergy for organisms. Ecological Modelling, 85, 165-175. Jorgensen, S. E., Marques, J. & Nielsen, S. N. (2002). Structural changes in an estuary, described by models and using exergy as orientor. Ecological Modelling, 158, 233-240. Jorgensen, S. E. & Nielsen, S. N. (2007). Application of exergy as thermodynamic indicator in ecology. Energy, 32, 673-685. Jorgensen, S. E., Nielsen, S. N. & Mejer, H. (1995). Emergy, environ, exergy and ecological modelling. Ecological Modelling, 77, 99-109. Jorgensen, S. E., Odum, H. T. & Brown, M. T. (2004). Emergy and exergy stored in genetic information. Ecological Modelling, 178, 11-16. Jorgensen, S. E. & Padisak, J. (1996). Does the intermediate disturbance hypothesis comply with thermodynamics? Hydrobiologia, 323, 9-21. Jorgensen, S. E., Patten, B. C. & Straskraba, M. (2000). Ecosystems emerging: 4. Growth. Ecological Modelling, 126, 249-284. Jorgensen, S. E. & Svirezhev, Y. M. (2004). Towards a Thermodynamic Theory for Ecological Systems. New York: Elsevier. Kay, J. (2002). On complexity theory, exergy, and industrial ecology: Some implications for construction ecology. In C., Kibert, J. Sendzimir, & B. Guy, (Eds.), Construction Ecology: Nature as a Basis for Green Buildings, (72-107). London: Spon Press. Kay, J. & Regier, H. (2000). Uncertainty, complexity, and ecological integrity. In P., Crabbé, A., Holland, L. Ryszkowski, & L. Westra, (Eds.), Implementing Ecological Integrity: Restoring Regional and Global Environment and Human Health (NATO Science Series IV: Earth and Environmental Sciences, Vol. 1, 121-156). Dordrecht: Kluwer Academic Publishers. Kestin, J. (1980). Availability: The concept and associated terminology. Energy-The International Journal, 5, 679-692. Kotas, T. J. (1995). The Exergy Method of Thermal Plant Analysis (reprint ed.). Malabar, Florida: Krieger. Lazzaretto, A. & Toffolo, A. (2004). Energy, economy and environment as objectives in multi-criterion optimization of thermal systems design. Energy, 29, 1139-1157. Li, Y., Shanying, H., Dingjiang, C. & Dawei, Z. (2006). Exergy analysis on eco-industrial systems. Science in China Series B: Chemistry, 49, 281-288. Libralato, S., Torricelli, P. & Pranovi, F. (2006). Exergy as ecosystem indicator: An application to the recovery process of marine benthic communities. Ecological Modelling, 192, 571-585.

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Enhancing Environmental Planning through the Use of the Thermodynamic…103 Park, Y. S., Lek, S., Scardi, M., Verdonschot, P. F. M. & Jorgensen, S. E. (2006). Patterning exergy of benthic macroinvertebrate communities using self-organizing maps. Ecological Modelling, 195, 105-113. Patten, B. C. (1995). Network integration of ecological extremal principles: Exergy, emergy, power, ascendancy, and indirect effects. Ecological Modelling, 79, 75-84. Ray, S. (2006). Extremal principles with special emphasis on exergy and ascendency: The modern approach in theoretical ecology. Journal of Biological Systems, 14(2), 255-273. Rees, W. E. (2003). Economic development and environmental protection: An ecological economics perspective. Environmental Monitoring and Assessment, 86(1-2), 29-45. Reis, A. H. & Miguel, A. F. (2006). Analysis of the exergy balance of green leaves. International Journal of Exergy, 3(3), 231-238. Reistad, G. M. (1970). Availability: Concepts and Applications, Ph.D. dissertation, Univ. of Wisconsin, Madison. Rosen, M. A. (2002). Can exergy help us understand and address environmental concerns? Exergy, An International Journal, 2, 214-217. Rosen, M. A. & Ao, Y. (2008a). Using exergy to assess air pollution levels from a smokestack - Part 1: Methodology. International Journal of Exergy, 5, 375-387. Rosen, M. A. & Ao, Y. (2008b). Using exergy to assess air pollution levels from a smokestack - Part 2: Illustration and methodology extension. International Journal of Exergy, 5, 388-399. Rosen, M. A. & Dincer, I. (1997). On exergy and environmental impact. International Journal of Energy Research, 21, 643-654. Rosen, M. A. & Dincer, I. (1999). Exergy analysis of waste emissions. International Journal of Energy Research, 23, 1153-1163. Rosen, M. A. & Dincer, I. (2002). Energy and exergy analyses of thermal energy storage systems. In Thermal Energy Storage: Systems and Applications (Chapter 10, 411-510). London: Wiley. Rosen, M. A. & Dincer, I. (2003). Exergy-cost-energy-mass analysis of thermal systems and processes. Energy Conversion and Management, 44, 1633-1651. Rosen, M. A. & Etele, J. (2004). Aerospace systems and exergy analysis: Applications and methodology development needs. Int. J. Exergy, 1, 411-425. Rosen, M. A., Le, M. N. & Dincer, I. (2005). Efficiency analysis of a cogeneration and district energy system. Applied Thermal Engineering, 25, 147-159. Salas, F., Marcos, C., Pérez-Ruzafa, A. & Marques, J. C. (2005). Application of the exergy index as ecological indicator of organically enrichment areas in the Mar Menor lagoon (south-eastern Spain). Energy, 30, 2505-2522. Salomonsen, J. & Jensen, J. J. (1996). Use of a lake model to examine exergy response to changes in phytoplankton growth parameters and species composition. Ecological Modelling, 87, 41-49. Salthe, S. N. (2005). Energy and semiotics: The second law and the origin of life. Cosmos and History: The Journal of Natural and Social Philosophy, 1, 128-145. Santarelli, M. G. L. (2004). Carbon exergy tax: A thermo-economic method to increase the efficient use of exergy resources. Energy Policy, 32, 413-427. Santarelli, M. & Macagno, S. A. (2004). A thermoeconomic analysis of a PV-hydrogen system feeding the energy requests of a residential building in an isolated valley of the Alps. Energy Conversion and Management, 45, 427-451.

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In: Environmental Planning Editor: Rebecca D. Newton

ISBN: 978-1-61728-654-4 © 2011 Nova Science Publishers, Inc.

Chapter 4

ENVIRONMENTAL PLANNING INPUTS BY THE FOREST SECTOR: THE SCALE FACTOR, THE CONNECTION PLANNING-MANAGEMENT AND THE RELATIONS WITH OTHER PLANNING SECTORS IN ITALY Sebastiano Cullotta and G. Federico Maetzke Dipartimento di Colture Arboree, Università degli Studi di Palermo, Palermo, Italy

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ABSTRACT In the twentieth-century, Italy, as well as many other densely populated European countries, has been characterized by a progressive reduction of the forest cover, especially in the Southern Mediterranean regions. Generally, the mountain areas developed a forest-based economy, especially in the Northeast Alps and in the Mediterranean Apennine inner mountains. Several distinctions must be taken into account, for example, with regard to ownership of the woods. On the Alps, generally the forests are municipal, community or private properties. In the Mediterranean Apennines inner areas there are many wide state-owned forests, followed by municipal properties, while the private property is, on average, less diffuse. In the recent past, after the destruction and the intensive exploitation, mainly due to the two world wars, reconstitution by reforestation or improvement of the existing woods has been diffusely realized. The most recent period has been characterized by the acknowledgment of the necessity of a more sustainable use of lands and, at the same time, by the evolution of programming and management tools at different scale levels. From continental to local levels, passing through national and sub-national, the planning actions run from a list of main program points to a detailed indication of specific management practices. Nevertheless the core of forest management remained based on the management plan of the local level only, often grounded with classical schemes, with shallow planning at upper and intermediate levels. In this work a critical analysis of current programming and management tools adopted in

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Sebastiano Cullotta and G. Federico Maetzke Italy at different levels is carried out. In the same way, the authors attempt to highlight the relations with other planning tools involved in environmental management (landscape plan, town plan, protected areas plan, etc…). Starting from the foregoing assumptions, which characterized the management approach during the last fifty years, differentiation elements, between the more flexible and integrated forest-environmental planning and management applied in the Alpine environment and the traditional, classical forest management in the Mediterranean Apennine environment, could be pointed out. The classical reference models, mostly strongly anchored to a dominant economic view, have not always applied in reality, because they are based on rigid and pre-arranged schemes of management planning..

Keywords: Forest management planning; management tools, sylvicultural practices, Sustainable Forest Management, Environmental governance.

1. INTRODUCTION

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Some Foreword and the Aim of the Work Foresters today have opportunities and great challenges to deal with. New perspectives in governance and in the practice of sylviculture are opening, following the generalized new approach towards environmental, landscape and forest planning. The matter is being able to overtake old concepts and develop new tools to manage our natural heritage. Two facts are relevant to think about. First is the increasing social awareness of the role played by the forest and the other natural and semi-natural lands in the destiny of mankind. This requires that politicians and managers must share decisions with inhabitants and stakeholders and adopt an effective policy and planning of any action in the environment. In the second place, there is the importance of adopting a holistic approach, required by the consciousness of the complexity of the relationships existing in every biological system we try to manage and address toward our utilities. International processes have brought a growing interest to the forest management planning sector and to its relations with the management moment, by the Sustainable Forest Management (SFM). Italy, as participant in the pan-European program of the Ministerial Conference on the Protection of Forest in Europe (MCPFE) (MCPFE 2003, Rametsteiner and Mayer 2004), has adopted the concept of SFM as defined in the Strasbourg (1990), Helsinki (1993), Lisbon (1998) and Vienna (2003) resolution. In particular the Helsinki H1 1993 resolution (MCPFE 1993) state that ―Forest management should be based on periodically updated plans or programs at local, regional or national levels, as well as for ownership units, when appropriate and on forest surveys, assessments of ecological impact and on scientific knowledge and practical experience‖. Moreover, the Forestry Strategy of the European Union and the Agenda 2000 Programme update and underline the importance of national and subnational forest programmes as a basis for the allocation of European Union Structural Funds. More recently, these concepts have also been expressed and reiterated by the ―EU Forest Action Plan‖ (Commission European Communities 2006), with the aim of reviewing the existing regulations in the EU context to promote greater cooperation among the various

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political areas that influence forest activities. Among its political objectives, the Forest Action Plan emphasizes the need for developing plans at different scale and sustainable forest management of the forests through an important participatory and diffuse approach in order to integrate the forest policies that exist at all levels (Marchetti and Mariano 2006). On these bases, at the international level, forest resources are viewed as an issue that transcends national boundaries and the National Forest Programmes (NFPs), resulting from these processes, as the forest governance tool to define and develop at national level in order to achieve SFM (UNFF 2002). This work is aimed to give a critical picture of the set of rules and tools in force in Italy at the moment, in the forestry planning and management sectors. Moreover, both the mutual relationships with other environmental and land planning instruments and some new perspective will be analyzed.

2. FOREST FACTS AS BACKGROUND Diffusion and Importance of Forest in Italy, Brief History of Forest Distribution and of Forest Acts in Italy

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The present asset of forest in Italy is the result of the history and the needs of a densely populated country. In the two last centuries the wood area suffered firstly a reduction, followed by an expansion in the last sixty years (ISAFA 1985; MIPAAF 2007). The high human pressure on the forest and the huge request for wood during the XIX and the first fifties of the XX century caused a wide reduction of the forest covered areas. The reduction of the forest area can be imputed to several main causes (Iovino et al., 2009):  the rapid growth of the population, that doubled between 1770 and 1900;  the issuing of the 1877 forest law, that bound forest areas over the ―chestnut line‖ (approximately 800 m a.s.l.) leaving free to cultivation the underlying territories;  the growth of the railway network, that grew from 8 km in 1840 to 15.787 km in 1900, and 21.000 km in 1930;  the repeal of fief properties in the Southern area of the country;  the confiscation and sale of the Church's properties after the unity of Italy in 1860;  the rapid development of industries, frequently distributed near the forests in order to minimize the cost of the energy supply. The result of such an attack to the forest patrimony was the reduction of about 2 million hectares (Sereni, 1961): in 1909 the total amount of woods in Italy was estimated about 3,600 million hectares (Agnoletti, 2005). Moreover, there was also a deep change in the features of the remaining Italian forests: the reduction of complexity and structures, the diffusion of coppice stands: as a result, a lower quality and carrying capacity of habitats. During the first half of the last century, the abandonment of mountain area (Braudel 2002; FAO database) and a wide work of reafforestation rose to an increment of the wood surface up to 5.5 million hectares. The urban migration after the second world war and the natural expansion of the

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forest in the abandoned pasture and ex-cultivated lands strengthened this trend up to the 9 million hectares inventoried in the last national forest inventory (MIPAAF 2007). The current state of forest resources in Italy is particularly complex. Briefly, the main features can be summarized as follows (Cullotta and Maetzke, 2009):  

 





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

altitude distribution that ranges from the Mediterranean level to alpine forests with marked differences in geopedological and climatic situations; a very rich and highly diversified structural and sylvicultural composition, that encompasses an enormous reservoir of biodiversity with respect to the entire European continent and the Mediterranean basin; a fragmented and articulated ownership, public 32.4% (among state, provinces, majorities) and private 63.5% (MIPAAF 2007); considerable fragmentation of habitats with high levels of naturalness and other protected national and regional areas, and hence a greater need for the creation and implementation of an adequate and connected national ecological network; a reduction of the mean amount of wood mass harvested annually (currently approximately 106 m3/year), that, while shows a general spare of the forests increment, prove also a considerable decrease in sylvicultural applications (generally not only for economic/financial purposes); sensible differences between the North area and Central-South areas: the alpine regions have deeply rooted forest based economies and forestry traditions, actually more efficient standards and greater interest in managing forests with forest planning tools (Bovio 1999, Del Favero et al. 1999); the Central Apennine and Mediterranean are areas with less deeply-rooted management traditions and hence less efficient regulatory frameworks and tools; high frequency and risk of wild fires in some South and Northwest region (e.g. Sicily and Sardinia, Liguria, respectively).

The planning and managing tools in Italy had a complex history too. It started from a simplified state centralist approach adopted after the unity of the country, when in 1877 the first forest law was issued. This law, as previously said, mainly regarding the hydro-geologic protection, bound the use of mountain forest area not allowing the change of land use of forest land, but had not any care for protecting or bonding the forests below ―the chestnut line‖ altitude limit, leaving those territories free to the deforestation and tillage for agriculture. Moreover, the law set up rules for reafforestation and especially instituted the expropriation of private lands for public utility reafforestation, and instituted the Provincial Framework of Forest Police, literally ―General instructions and forest police rules‖, a set of local rules defined by apposite committees. The 1877 law was early and strongly criticized by politician, experts and people, mainly because of its faults in managing and improving the economy of rural and mountain areas. Despite of the admitted defects, it needs near half a century to adopt another fundamental law on forest issues and forest planning. In 1923 it was enacted the Royal Decree Law. no. 3267: this one too remained substantially unchanged and effective for more than half a century. It focused again on the creation of hydro-geological restrictions. In so doing, 89% of the forests were primarily subject to the hydrological bond. As in the former law, changes in land use

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were prohibited, and specific management practices were imposed, favoring the reafforestation of mountain territories and providing economic support to majorities and private forest owners. Moreover this law stated the compulsory of planning activities. In this regard, the law entered in detail regarding the management of forest. It dealt with the regulation of sylvicultural activities on private and public property through the creation of Forest Economic Management Plan (Piano Economico or Piano di Assestamento Forestale). Despite this, the basic role attributed to the forest resources was economic, the forest was still considered as a wood mine, in which take materials for human utility. In absence of a Management Plan, forest have to be managed respecting the above cited provincial forest rules. Italian post second world war Constitution, enacted in 1948, provided the regional autonomy with regards to many issues, encompassing environmental and forest matter. Even so, the decentralization process took place in the 1970s (D.P.R. no. 11 of 1972 and no. 616 of 1977), giving the primary responsibility for forest issues to the regional-administrative level (see Fig.1). This process prevented the formulation of a desirable new National Forest Law and created difficulties in finding common patterns for nationwide forest policies, so the 1923 law remained in force up to the new regional acts. An heterogeneous framework was created among the Italian regions: some focused their policy on expanding the forest areas and protecting the forest environment, while other regions stressed the economic role of the forests and implemented assistance programs for forest owners and enterprises (Cullotta and Maetzke, 2009). After the decentralization, the state properties were passed to the regional authority, all but national parks, national and bio-genetic reserves. To the State remained also the task to coordinate the frameworks of regional acts. Some further state acts were significant in environment and forest planning. In 1985 with the Landscape Act (no. 431) the forests were transferred under the jurisdiction of the Ministry for the Environment. A new nature-oriented forest management was imposed; only cultivation cutting was allowed as insofar as it was useful for the care of the forest ecosystem, in all forest but plantations. After this, some specific legislation was passed to assure the correct allocation of the public funds to this economic sector, up to the National Forest Programme (Law no. 752 of 1986). Following the above cited approach, in 2001, the Decree Law n.227 assigned the Ministry for the Environment and Landscape Protection and the Ministry of Agricultural and Forest Policies the task of issuing guidelines in order to give a framework for the regions to draft and revise their specific Regional Forest Programmes. These programs must hold on the protection, conservation and development of the forests in their respective areas. However, there were no provisions for the creation of any National Forest Program, and planning was committed to the regional governments. Recently, on 16 June 2005, a Decree Law has been issued by the Minister for the Environment regarding guidelines of forest planning. With a considerable change of approach, in respect to the classic forest management, this act draws the planning tools considered necessary for achieving fully SFM (Sustainable Forest Management), stressing the importance of the knowledge of forests: ‖a good knowledge of the area in general and of the forest in particular, and of forest planning at the various levels (regional, sub-regional and above all local) are strategic.‖ The plans must be multipurpose and extend over long time periods in order to support and accomplish the commitments made with respect to the international community concerning SFM. That same Decree Law assigns to the regions the task of ascertaining the status, condition and characteristics of their respective forest resources with respect to the national and regional

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economic programs, and the overall environmental situation with specific reference to the conservation of biodiversity. At this point forest laws and regulations at the regional level have been developed adopting different approaches, as previously stated. And more with regard to this, it was increasingly clear that the planning chain was not fully functional. It lacked some step, especially between the regional planning (general) and the management (local, operative) level. The need for graduated scale planning became increasingly significant in terms of forest resource management among various geographic levels and over time, according to the criteria defined by the SFM. There was also a de facto need for constant updating of the operational plans.

3. PLANNING AND FOREST MANAGEMENT TOOLS IN ITALY: THE SCALE FACTOR

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3.1. International Processes on Forest Planning and Its Definition Forest planning is the technical-political activity with the goal of rationalizing the relationship between man and the forest (Bovio et al. 2004). Forest planning is the activity that organizes and rationalizes management on the basis of multi-functional criteria, and it has multiple goals. There are many approaches to land use and management planning that typically involve different classifications according to the level of analysis. Most land planning in Europe, as well as many other countries, is done on a ‗micro-scale‘; it deals with highly localized issues at the farmer/estate level (Mitchell et al. 2004). In the past, given the interest in the forest‘s productive capacity, and considering the wake effect1 as efficient, for a long time in Italy (up to the 1980s), forest planning focused on management as per the Local Forest Economic Plan (LFP) or Forest Production Management Plan (FAP) (‖Piano di Assestamento Forestale‖) (Cullotta and Maetzke 2009). At more general levels the forest planning consisted essentially of national laws. Since then, there have been significant developments in the views of the man-forest relationship, and in the concept and interest in the forest‘s multi-functional role. Recent national and regional regulations and legislation confirm this. Sustainable management of environmental resources cannot be achieved solely through use of micro-scale analysis and management. Such an approach would ignore the larger scale environmental factors within which any activity should be constrained (Burnett and Blaschke 2003, Mitchell et al. 2004). Natural resource management should be a hierarchical process ranging from large regions with broad goals (e.g. NFPs) to small areas with specific operational aspects (Church et al. 2000). Land management policies should initially be developed for the upper levels of the hierarchy, and then be scaled down to the local levels, taking in account the feedback.

1

This is the assumption that a forest - which is managed functionally to maximize wood production - is also capable of fulfilling its other inherent functions such as hydro-geological protection, recreational use, environmental values, etc. (various sources, including Patrone, 1940)

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Pulzl and Rametsteiner (2002) observed that forest governance, through forest planning tools, can be distinguished in three categories, expressions of different environmental governance approaches: Anarchical governance, in which involved actors follow a ―horizontal logic‖ without giving much attention to others; Hierarchical governance, that follows a ―vertical logic‖ of interaction between actors; Heterarchical governance, that is inspired by co-operative and deliberative ideas.

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3.2. A Critical Analysis of Current Programming and Management Tools Adopted in Italy at Different Levels Hereinafter an analysis of different forest planning tools currently defined in Italy is reported in conceptual and structural terms and their hierarchical organization (vertical logic) in relations to the scale level is highlighted. Thus, forest planning tools are related to their geographic and territorial value. It is possible to identify several planning levels, with the single goal of creating tools that are organic, mutually related and coherent with each other. The following table (Table 1) provides a hierarchical summary of five different levels to which the concept of forest planning in Italy can be linked (Cullotta and Maetzke, 2009). It goes from the first, most general level – the national – to the fifth which is estate-property management via the regional and sub-regional (territorial2) levels (Figure 1) to structure and anchor the general strategies compatibly with the specific regional, sub-regional and local situations. A functional hierarchy of decision-making among these levels is usually insured but not achieved in every case. For instance, Regional Forest Programmes (RFPs) are usually negotiated and drafted after the upper level of NFP definitions, probably under the effects of the EU Forestry Strategy that identified the tools for implementing international commitments, principles and recommendations in these two levels. However, disconnections occur when scaling down to the local level. Currently, due to the lack of linkage between local technical authorities and policy makers, in Italy many local forest plans are not well linked to the higher level, sub-regional or regional forest governance tools. There seems to be quite a clear gap between the national-regional levels on one side and the sub-regional-local levels on the other side. Similar considerations can be applied to the European context (Hogl 2002).

2

The sub-regional level can be identified by the term territorial. However, it is important to point out that in Italy a ―territorial‖ planning level is not necessarily linked to a well-defined area – it is in between the regional (higher) and estate (lower) levels. More legalistic-administrative terms for this intermediate geographic level, that is territorial, could be Provincial – District – County. Obviously these terms are applied differently in other countries. For these reasons we have opted for the term ―territorial‖ in the sense of a physical-geographic space.

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Sebastiano Cullotta and G. Federico Maetzke Table 1. Hierarchical hypothesis of the Italian forest planning system in existence and under development (after Cullotta and Maetzke 2009)

Level 1

Geographic reference National

Competence Forest policy

2

Regional*

Forest policy

3

Provincial*

Application of the local forest policy

4

District

5

Local / Farmer /Estate

Contextualization of local framework of forest policy Contextualization and technical application of local forest policy

Tools

Source of information

National Forest Programme (NFP) Regulatory framework of forest policy Regulatory framework of forest policy Regional Forest Programme (RFP) (other sectorial tools: PSR, etc. ) (see Figure 2) Provincial Forest Policy Prescriptions (PMPF) Provincial framework of forest policy Territorial Forest Plan (TFP)

National Forest Inventory (NFI) Regional Forest Inventory (RFI), Regional Forest Map, data synthesis DB of upper level data synthesis DB of following level

Forest Reorganization Plan (FRP) Forest Management Plan (FMP) Forest Production Management Plan (FAP) Forest Cultivation Plan (CFP) etc…

Thematic maps (land uses, forest types, management units, etc…) Local and detailed data inventory, Detailed thematic maps, Management unit assessment

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* Regional: Administrative Regions of Italy (see Figure 1and 3); Provincial: Administrative Provinces of Italy

Figure 1. Geographic levels and forest planning tools in Italy (after Cullotta and Maetzke 2009)

3.2.1. Forest planning at national level: The National Forest Programme (NFP) and its importance for the European and international policies As previously noted, international developments in forest policy towards a holistic view (that is also horizontal and vertical) of forest and environmental resources consider the NFP as the tool for implementing the SFM (UNFF 2002) (see Figure 8), as set forth in the UNCED Forest Principles and Helsinki H1 Resolution. NFPs have become a central topic at the panEuropean level in the last decade. In particular, the MCPFE devotes specific attention to the

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planning process and defines the NFP as a method for inter-sectorial and iterative planning, implementation, monitoring and evaluation at national and/or regional level aimed at achieving sustainable resource utilization. The documents also pinpoint the need for a participatory and inter-sectorial approach (this was also set forth in the ―Forest Action Plan‖) as well as the importance of making the planning process a permanent institution in order to be able to achieve long-term goals. This, however, is something that still remains to be done in Italy, as well as in other European countries. Few years ago, at the European level a COST Action, named E19 – ―National forest programmes in a European context‖ (Gluck and Humphreys 2002), was conducted to highlight the importance of this national tool in forest planning (Figure 2). The aim of this action was to contribute to political processes, at international levels, dealing with forest resource planning, for a more common definition and organization of a NFP. COST E19 identified four main fundamentals to be analyzed for the realization of a NFP (Gluck and Humphreys 2002), in accordance with the forest planning principles of Agenda 21 (United Nations 1992):

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1) 2) 3) 4)

Public participation, Holistic and intersectorial co-ordination, Decentralization, Long term iterative and adaptive planning.

In particular, ―decentralization‖ refers to the importance of geographic-level coordination among actors who can contribute to the creation of different scale forest planning tools. As an example, in 1988 Italy devised its first National Forest Programme (NFP) (MAF 1988), that was approved by the Inter-ministerial Committee for Economic Planning (CIPE) in December 1987. This was a ten-year plan (from 1988 to 1997) and it was the first national document that granted autonomy to the forest sector and separated it from agriculturefarming.

UK, United Kingdom; CZ, Czech Republic; BE, Belgium; LT, Lithuania; IE, Ireland; ES, Spain; FI, Finland; NO, Norway; DE, Germany; DK, Denmark; HU, Hungary; CH, Switzerland; GR, Greece. Figure 2. NFP processes lunched in same European countries after the Rio 1992 Declaration (after Zimmermann and Mauderli 2001; COST Action E-19 – working document, modified)

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The Italian NFP, based on the current concept of SFM, was a detailed document on the most important forestry issues on the whole and it outlined guidelines for solutions to problems. Unfortunately the NFP did not become operational because of uncertainties concerning the institutional relationships between the central government and the administrative Regions: responsibilities and roles were not clearly defined, and funding was insufficient (Corrado and Merlo, 1999); as well as observed in many other European countries (Zimmermann and Mauderli 2001). Currently, the new Italian NFP should be drafted as soon as possible, and on the basis of the new National Forest Inventory (Inventario Nazionale delle Foreste e dei Serbatoi di Carbonio - INFC) (De Natale et al. 2005, MIPAAF 2007) in order to make up for the existing time gap (various authors – AA.VV. 1999, Ciancio and Nocentini 2001; Bagnaresi et al. 2000). Recently, only a Framework Program of Forest Sector (Programma Quradro per il Sistema Forestale – PQSF, MIPAAF 2008) was carried out at national level. The last National Forest Inventory, with its high level of acquired information on the forest resources, will make it possible to draft the new NFP in accordance with the current EU guidelines. As an operational tool for coordinating forest policy, the NFP is a summary of the guidelines for implementing the policy and development lines established at the European and International levels (Shannon 2002). In relation to the Italian situation it serves as a link among the respective regional tools since the issue is one of regional responsibility. It is also a tool for financial planning since it coordinates the application of EU grants.

Figure 3. Administrative division of Europe at sub-national level. Some administrative denomination are: Comunidad Autonoma in Spain; Region in France; Regione in Italy; Land in Germany; Division in United Kindom; Lan in Sweden; Oblast in Bulgaria and Ukraine; Kraj in Czech Republic and Slovakia; Judet in Romania; Il in Turkey.

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3.2.2. The sub-national level of forest planning: Regional and territorial At the Regional (i.e. Administrative Regions in Italy - different sub-national administrative divisions of many European countries must be interpreted: Region, Regione, Land, Comunidad Autonoma, Division, Province, Canton, District, etc.) level (Figure 3; see also Figure 1 and Table 1) the Public administration sets forth the guidelines for environmental and forest policy, the economic-financial strategies (e.g. PSR –

Piano di Sviluppo Rurale - Rural Development Plan, Figure 9 and Table 1) and the organization models for the forest administration in a long-term programmatic document, the Regional Forest Programme (RFP). According to Hyttinen (in Michaelsen et al. 2000), a RFP should include the following points:

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a) overall description of forest related facts and issues, b) regional development needs and objectives (broken down according to production and timber use, biodiversity and conservation, employment, industrial activities), c) measures to be taken to reach the objectives, d) assessment of economic and environmental impacts. Moreover, the operational RFP and various sub-regional planning tools play important roles in the drafting of the NFP. The regional level plans provide specific features, issues and objectives to take into account when drafting the new NFP. Therefore, the picture concerning RFPs in Italy is quite mixed, due to the autonomy of each administrative regions (Figure 1). Many regions are still lacking a RFP. Some regions are working on them and they should be ready in a short time. Generally, RFPs are more diffused in the Alpine and Northern Italy, while some Mediterranean regions in Southern Italy are still lacking. To the point, following the creation of the first NFP in 1988, only a few regions complied quickly by drafting their own RFP: Emilia Romagna, Lombardy, Tuscany, Umbria (Corrado and Merlo 1999) and Trentino-Alto Adige. Recently, Liguria, Molise, Sicily and Sardinia have created their respective RFPs, while Emilia-Romagna, Lombardy, Trentino-Alto Adige and Tuscany have prepared new, updated editions. There is also a certain amount of heterogeneity in the drafting and contents of the existing RFPs. However, in line with the most recent trends the RFPs are being drafted on the basis of the data contained in the Forest Information System (specifically, the Forest Inventory) and the Regional Forest Map – fundamental planning tools that all the Italian regions want to acquire, and other forest planning tools that exist on a regional level (Figure 4). These tools require to regional Authorities the use of GIS data format in order to continuously update and improve the regional upper level DB. The Territorial level (Provincial/District – see Fig.1 and Note 2) of planning level has the objective to produce a set of guidelines for forest planning, The Territorial Forest Plan (TFP – in Italy named ―Piano Forestale di Indirizzo Territoriale‖ or ―Piano Forestale Territoriale‖ or ―Piano Territoriale Forestale‖) (IPLA 2004, Bovio et al. 2004), must be drafted for homogeneous forest districts (concerning management aims and goals), into which the regional surface can be uniformly divided (Figure 5). The planning guidelines include the entire range of the forests‘ multiple-functions as well as those of other forest resources (preforest areas; pastures and the most important natural environments with close ties to the forest; main agronomic landscape context; property; land system; hydro-geological conditions; road system; fauna; fires; social-economic aspects – IPLA 2004) and identify the management guidelines and most important threshold parameters (Figure 6) in order to

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guarantee full forest sustainability (SFM) in line with the main international criteria (MCPFE, Forest Action Plan, etc.). The importance of territorial planning is that it would force the local administrators (e.g. municipalities) of a given forest area to create a platform of cohesion with respect to an asset – the forest – that would otherwise be considered and managed in a fragmented way regardless of a univocal and indispensable territorial-level environmental strategy (Figure 7). All this is only possible if there is a strong partnership among all the communities in a given area (and only if this address to appropriate incentives and regulations). The public participation in environmental decision-making, namely in the forest sector, is a focal point for a wider diffusion of operative programme and planning tools, as put in evidence by different international processes (Aarhus Convention 1998; various MCPFE Resolutions; European Landscape Convention 2000; EU Forest Action Plan 2006; etc.). In Italy, from the legislative and methodological standpoint this level of territorial/provincial/district planning does not yet have a clear, well defined regulatory framework on either the national or regional level. Moreover, at the national level, the debate concerning a standardized definition and structure of the TFP is still open (Bianchi 2004, Bianchi et al. 2006). Currently only the Piemonte Region (NW Italy) has produced a TFP for their entire area (Figure 5 and 6), dividing the Region into 47 sub-areas (homogeneous Territorial Forest Units) (IPLA 2004). Anyway, at now there isn't a common share of this approach, both in scientific and in administrative ambit, nor a clear definition of the term ―territorial‖ meaning, and this severely limits the opportunity of planning at this important level.

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Regional Forest Map

Regional Forest Programme Guidelines

Other specific tools at regional level (Agriculture/Rural development; Landscape; Fauna; Protected areas; etc…)

Regional Forest Inventory

Regional Firefighting Programme

Regional Forest Programme

Figure 4. Forest Information System and other most important forest planning tools at regional level, useful for the draw of a RFP

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Figure 5. The Territorial Forest Plan (TFP): geographic division in territorial areas (Forest District), macro-relations among different planning levels and aims of the planning ( after IPLA 2004; modified). (RFP – Regional Forest Programme; LFP – Local Forest Plan)

Figure 6. Structure and components of a Territorial Forest Plan (TFP) (after IPLA 2004; modified)

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Figure 7. Landscape mosaic, with highly fragmented forest properties (darker patches). In a such situation it will be compulsory to boot an associate forest management. (Administrative Province of Urbino, Marche Region – Central Italian Apennines, picture from Google Earth 2007)

3.2.3. The Local Forest Planning (LFPs): The proliferation of plans and tools This is the management level that leads to the direct, practical application of sylvicultural and management techniques in the specific forest stand (Table 1). The various planning tools at this level (Table 1, Figure 1), which can generically labeled Local Forest Plans (LFPs), consist of the Forest Management Plan, the Forest Production Management Plan, the Forest Reorganization Plan, and, with more specific aims, the Forest Cultivation Plan and the Forest Felling Plan. Even in the case of estate-level planning the situation varies significantly from region to region throughout Italy (Alpine area; Northern sub-Mediterranean; Central-Southern Mediterranean). For example, operational management plans are widespread in several Northern Italian regions with longer forestry traditions such as Trentino-Alto Adige, Veneto, Friuli-Venezia Giulia and Emilia-Romagna. However, in Southern Italy, with the exception of Campania, the drafting and application of forest plans is much more sporadic – even in spite of the vast tracts of publicly owned lands. Thus, if the historic Forest Production Management Plan (FAP) is recognized in all the Italian regions, other local forest planning tools are quite distinct (Local Forest Plan sensu IPLA 2004) (see Table 2). Almost all of these local forest planning tools are based on detailed and systematically acquired data concerning structural, compositional and functional aspects, that are needed in order to develop specific indications for forest management over the duration of the plan. Due to the lack of adequate incentives, and the low income from sylvicultural activities in many Italian regions, this highly diversified situation could last for a long time. However, the provisions of the recent Forest Action Plan enhance existing community tools with specific actions aimed at supporting the popularization, technical consulting and the drafting of the LFPs. In this regard, in order to

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reduce costs, especially in small areas, the possibility of stimulating associated management of forest resources is of considerable interest (Del Favero et al. 1998, Solari et al. 2000). This issue is both important and current; it has been clearly addressed by the Forest Action Plan: Action ―Improving long-term competitiveness‖ – Key-action 5 ―Foster the cooperation between forest owners and enhance education and training in forestry‖ (Commission of European Communities 2006). A synthesis of fundamental local management tools are hereinafter reported in table 2, with focal information of the functional role of each one. Table 2. Plans and tools of the Local Forest Planning (LFP) Tools Forest Reorganization Plan (FRP)

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Forest Management Plan (FMP)

Objective To favour forming association among the forest owners in an entire municipality, or within a park. Standard requirements are set forth which establish the rules regarding felling periods, intervals and methods for specific forest compositional-structural categories (Del Favero et al. 1998) A more structured, flexible and open planning tool comparing to the traditional and solely economicfinancial aims of the FAP. The FMP identifies and coordinates the long-term technical- operational management of the estate and sets down also the administrative management guidelines.

Forest Production Management Plan (FAP)

It is the operational management tool for implementing sylvicultural methods in the given estate over time. It defines the spatial and temporal distribution of technical management practices. It is the historical FLP in Italy (starting from legal Acts of 1877 and 1923), with the main aim to favour the productive function of a forest stand.

Forest Cultivation Plan (FCP)

This is a plan that specifically focuses on cultivation practices, not taking in account the intended uses of the forest products and resources as in a management plan. It defines specific procedures for: a) tending young forests; b) restoring the function – in terms of biological efficiency – of degraded forests. Specific guidelines concerning cultivation treatments, thinning, etc., are provided. This is a basic forest management tool: its purpose is to regulate the distribution and extent of cuttings over time. Usually it is one of the required component of the FAP.

Forest Felling Plan (FFP)

Diffusion Diffused in NE administrative regions of Italy (Veneto; FiuliVenezia Giulia) Much must be done for the diffusion of these plans. For example most of the Italian protected areas are still lacking FMPs (Marchetti et al. 2005). For a long time these documents were the main tool for forest planning and even today they are the basic tools that are acquainted throughout the entire Country. Used in some North East regions for local planning

Frequently used for coppice forest stands, under a regular felling regime.

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4. ENVIRONMENTAL, LAND USE AND FOREST PLANNING TOOLS: MUTUAL RELATIONSHIP

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The Relations with Other Planning Tools (Rural Development Plan, Landscape Plan, Town Plan, Protected Areas Plan, etc…) In the above reported homogeneous and coherent hierarchical logic of forest planning tools, it is also essential that they dialogue horizontally with all the planning tools that are available and/or operational. It means the necessity to highlights the importance of an intersectorial and harmonic relational framework among planning tools for forest and other sectors of environmental/land-use planning: Landscape programmes and plans; Agriculture/Rural development tools; Urban planning; Hydrogeological land protection; regional programmes on Energy use and development; Protected areas/Nature conservation tools; etc. Following the Principles at the Agenda 21 - chapter 11, principles for forestry planning: co-operation, co-ordination, decentralization of decision-making, inter-sectoral co-ordination, reviewing (United Nations, 1992) - the necessity to draw inter-sectoral connections among tools that have common interest in environmental resource uses was expressed. For example, the COST Action E19, analyzing the basic frame of a NFP (the most important forest planning tool at national level), indicate among the main fundamental points the necessity of an ―Holistic and intersectorial co-ordination‖ (Gluck and Humphreys 2002). This fundamental or basic principle can be viewed as an expression of the ―heterarchical governance mode‖ (Pulzl and Rametsteiner 2002), that, updating, we can define as a: ―a cooperative and deliberative idea that follows a horizontal logic, trying to give attention to others‖. In other words a horizontal way of governance with the aim to find links and synergies among sectors, for the sustainable use of environmental resources (water, air, agriculture, forestry, etc.). In the way of implementing international commitments to enhance sustainable forest management, Pulzl and Rametsteiner (2002) underlined the shift from the hierarchical to the heterarchical mode of governance that can be found in natural resource governance. Comparing the two different approaches (see Figure 8): the hierarchical mode (vertical logic) focus primarily on the forestry sector despite its stated aim of being inter-sectoral; viceversa, the intersectorial approach prove to be the more appropriate holistic mode of governance for solving forest problems (heterarchical in a synergistic horizontal logic). The inter-sectorial coordination among different planning tools seem to be strongly influenced by the scale level. For instance in Italy, at a more general level (e.g. Regional, National) the connections and ―considerations‖ between the forest and other sectors can be more easily underlined (Table 3); while become quite absent at more detailed level (i.e. Local). An example of attempt at combine vertical and horizontal parallels between forestry tools and specific plans and programmes of other sectors is shown in Figure 9 for the study-case of Italy (Cullotta and Maetzke 2009). Actually, however, true integration of all these tools is not always achieved. This gap or incomplete co-ordination of forest planning tools and the other territorial and land planning instruments seems to be common to several European countries (e.g. Spain – Montiel and Galiana 2005).

Environmental Planning Inputs by the Forest Sector: The Scale Factor…

Hierarchical

Heterarchical

mode of governace

mode of governace

“Vertical logic” of governace

“Horizontal and Vertical logic” of governace

Developed in tropical countries in the 1980s

Developed in western countries in the 1990s

Representative planning tool: “Tropical Forest Action Plan” (TFAP)

Representative planning tool: “National Forest Programme” (NFP)

Main aim: slow the rate of deforestation in developing countries

Achieve the SFM in all countries

Intersectorial relations: any, or only between forestry and agriculture

holistic mode of governance with intersectorial relations

123

Figure 8. Schematic comparison between ―hierarchical‖ and ―heterarchical‖ mode of forest governance (after Pulzl and Rametsteiner 2002; modified)

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Table 3. Presence/absence of a real connection (integration) in planning between the forestry and the other sectors of environmental resource use in Italy

Forest planning at scale levels  National Regional Territorial Local





Landscape

Agriculture/ Rural development

/ / / NO

YES YES YES/NO NO

Other sectors of environmental planning    Hydrogeological

Energy

/ YES

/ /

NO

NO





Protected areas/Nature conservation

Urbantown plans

Others ……

YES YES YES/NO YES

NO NO NO NO

According to the same criterion further tools of other sectors of territorial planning could be included in Figure 9. For instance some regional governments (Administrative Regions in Italy) have produced planning tools to place in an intermediate position between the forest sector and others: the ―Mountain Regional Plan‖ (―Programma Regionale per la Montagna‖ or ―Piano di Indirizzo per la Montagna‖), the ―Regional Plan for Environmental Action‖ (―Piano Regionale di Azione Ambientale‖), the ―Management Plans for Reserves and Nature 2000 sites‖ (―Programma or Piano di Indirizzo per le Aree Protette e dei Siti Natura 2000‖), the ―Regional Energy Plan‖ (―Piano Energetico Regionale‖), etc.. In creating new tools or updating existing ones, today Plans and Programmes seem to be more open in their inter analysis and structure to other sectors.

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Figure 9. Hierarchy of forest planning tools in Italy and correlation with some other important specific regional and subregional planning instruments. (planning tools that impact the forest and other areas are shown in the boxes with crosshatched backgrounds) (after Cullotta and Maetzke 2009)

As and example it is indicative in Italy that a quite recent RFP, namely that one of the Sardinia Region (Central Mediterranean Basin), changed the classical RFP name, titled ―Regional Forest-Environmental Programme‖ (―Piano Forestale Ambientale Regionale‖) (REGIONE AUTONOMA SARDEGNA 2007). In particular it put in evidence the importance of inter-relations with other tools of regional level as: the Rural Development Plan, the Regional Landscape Plan, the Regional Hunting Faunistic Plan, the Regional Energy Plan, and the Water Safeguard Plan.

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5. FROM FOREST PLANNING TO MANAGEMENT: THE REAL EFFECT OF PLANNING TOOLS ON FOREST MANAGEMENT AS CURRENTLY APPLIED

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The management approach during the last fifty years, differentiation elements and limits between the more flexible and integrated forest-environmental planning and management applied in alpine environment and the traditional, classical forest management in mediterranean apennine environment The above discussed evolution of planning is a quite recent history, and the main tools of management, largely applied at operational level, remained the management plan (FAP – Table 2), that was for a long time the unique having legal validity. The evolution of approach had a fallout especially in the region where the economy was traditionally based on forest and wood products, like in the North East regions on the Alps. In Central and South Italy a new approach to forestry needed a longer time and isn't yet fully achieved. In order to enlighten the contact elements and the difference in the real management that had been applied between North and South Italy during the last fifty years from the the immediate post WWII up to now, it's necessary to analyze the assumptions at the base of the forest activity, as far as the evolution of the cultural approach to the forest management. Moreover, it is necessary to take into account the social and economic history of the inner mountain population. In the Northern alpine region the connection between the man and the forest is traditionally strong and has a long time based roots. It was historically balanced respecting the needs of the wood and satisfying the utilities requested by the human communities. From the second half of '800 to the post WWII period, as in the rest of Italy and in many other European countries, there was an over-exploitation of woods that lasted until the fifties of the last century. It resulted in a general degradation and simplification of the woods structure and composition. From that period up to now a long phase of renaturation and cultivation of the forest followed. It was actually supported by the awareness of the importance of woods in the communities economy, as far as the strength of an ancient tradition, still living. At present the socially acquired awareness of the environmental and social-cultural utilities of forest, that are progressively overtaking the productive aspects, is growing in every part of communities, locally and all over the country. With regards to the management, in brief, the ancient German traditional schemes of sylviculture and management (Farcy, 2004), based on a financial approach and realized with even-aged woods, short production cycles, clear cutting and replanting, were abandoned, rediscovering and restoring the uneven-aged cultivation of woods, following the mot "wood growths on wood" (or ―close-to-nature‖) (Schutz 1999). It means leaving the "financial" sylviculture and management and adopting a "near nature" approach. It appears obvious that this changing approach would result in a deep change in structural and managing assets of forest. The management and planning activities changed in methods and in the way they have applied. The formal, hard schemes of drawing plan, for a long time adopted and widely diffused, left the place to a more flexible approach to the planning activity. As first (Wolinsky, 2008) management plans were adopted for all the public owned forests. With regards to the operative management, the selective cutting sylviculture based on uneven aged stands (Figure 10) was largely adopted and the "control method" was supported by

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technicians and public managers. This method, (in a very short synthesis) conceived by the french forester A. Gournaud at the end of 18th century, is based on a continuous inventory of the unevenaged managed forest and the exploitation of only a part of the real increment of forest: the inventories reveal, time to time, the effectiveness of cultivation cutting adopted, and the sustainability of exploitation. At the same time a gradual reduction of the exploitation of logs allowed a significant increment of the growing stock in forests, especially the public owned. From the cultivation point of view there was a significant passage in the way of regenerating forest from planting towards the natural regeneration supported by sylviculture. As previously stated, it allowed a progressive differentiation in composition and structures, enhancing the diversity and resilience of woods. But the matter wasn't only a change in planning and forest management but, above all, a widespread change of the approach to the forestry both in professionals and in citizens, that are even aware of the importance of forest. It also reflected the growing importance of tourism and leisure activities in mountain areas, that became a pillar of the alpine economy. With regards to the planning, two new tools have been adopted. Recently it is discussed the necessity of a mid-level planning tool, the ―Territorial plan‖, as above mentioned (Figure 6 and 7). The need of a intermediate planning tool useful to overtaking the firm-estate level the strict local management plan that is limited to the operative viewpoint - was evident due the lack of a general consideration of social-economic and environmental at the territorial/district level. While in Italy there isn't a clear definition of this level, as previously discussed, some authorities in the North and in the alpine regions adopted the territorial plans at province-district (sensu administrative province) level. This allows the stakeholders consultation and decision sharing between municipalities, and, overall, allows a widespread consideration of economics and conservations programs of forest on a wider area. At this level, and at the management plan level too, another tools, the ―forest types‖ approach have been developed and adopted (Del Favero 2001). Forest types are a classification (typology) and analysis of forest composition (trees, shrubs and grasses species) and structures (distribution and competition of trees in the vertical and the horizontal space) that matches the scientific approach with the practical knowledge (Del Favero 1992; Cullotta e Marchetti 2007), in order to enlighten similarities, ecological mechanism and devices to drive the human activities and interaction with the forest in order to realize SFM. In the Central and South Italy, where forest tradition is generally poor, woods have been over exploited for centuries, with a widespread simplification of wood system, a large diffusion of coppices and even-aged forest. The public owned forest have been managed, from the second half of the '800 up to the sixties of the last century by applying almost schematic plans, based on even-aged cultivation, shelter-wood cutting, or coppices, (Figure 11) especially for the beech forest, the most diffused mountain forest type on the Apennine Central-South mountains. A synthetic analysis of the plans drawn for those forest reveals rigid schemes, repetitive technical approach and, worst, a limited consideration of forest ecological needs, frequently put after the human, almost productive interests. This was a consequence of the deep rooted idea that a forest managed in an effective way to maximize the production must be efficient in every other aspect and functionality, the so called - and previously cited - ―wake effect‖ of the German management school origin. Consequently, this often resulted in a diffuse not application of the prescription of plans, mainly caused by difficulties in the real application of

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the prescription itself, in front of unexpected response of forest to the human intervention, e.g. the lack of regeneration or phyto-sanitary problems. With the same approach, the management of white fir forests, diffused as well in the Apennine chain, was based on clear cutting and plantation.

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Figure 10. Selective cutting marks in a unevenaged common spruce stand (East Italian Alps) (photo Maetzke)

Figure 11. A typical mountain beech old-coppice, currently not managed (Sicily, Central Mediterranean Basin) (Photo Cullotta)

The described situation remained substantially unchanged until the second half of the last century, when, in pursuance of the post WWII Italian Constitution, the forest matter passed to

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the regional authorities, that recently have issued the regional forest plans, as discussed in paragraph 2, the current situation draw a panorama of different approach to the forestry between the Regions. The majority of them have a Forest Regional Plan (PFR) drawn and adopted, while many regions there lack of management plan, and forest are managed only respecting the provincial generic prescriptions. As far as it's concerned with the private owners properties, often managed without any plan, both coppices and high forest. Nevertheless, some examples could be interesting to demonstrate a different approach to sylviculture. For instance, in some mountain pine high forest, in Calabria and in Sicily, the group selection cutting was adopted, irregularly spread creating small gaps in the crown tissue, let say 40 -100 m2. (Iovino et al., 2009). It allows to exploit 40 to 70 trees per hectare, corresponding to 60 -100 cubic meter of commercial wood, with a repetition each 10 years. The matter is that by this way the growing stock of forest remains always over a mean value of 300 – 350 cubic meters per hectare. This value is considered, in a new approach to sylviculture that will be later discussed, the minimum required for the SFM in mountain pine forest, in order to save the regeneration capability, the forest ecological functionality, the soil protection. The forest evolves towards unevenaged structure, quite complex and dynamically stable, naturally regenerated with a low impact and low cost human felling and tending. This approach to sylviculture recalls the ancient methods adopted in traditional forestry, revaluing the local knowledge, that allowed a long time balance, only recently disrupted, between human benefits and forest efficiency.

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6. NEW PERSPECTIVE IN FOREST MANAGEMENT AND PLANNING The classical reference models, mostly strongly anchored to a dominant economic view, have not always applied in the reality, because they are based on rigid and pre-arranged schemes of management. A new perspective in sylviculture and the need for new management tools: the forest as a complex system In the previous paragraph some problems of forest management in Italy have been enlightened, especially with regards to the Central-South regions. The classical approach that characterized the majority of plans was aimed to enhance the productive (in a broad sense) aspects, also overtaking the cultivation needs of forests. And it often caused the inapplicability of plans it selves. In the meantime a new approach to forestry grew between foresters and public opinion too, as already mentioned. The role of forests in the environment and the man-forest relationship are clearly reconsidered: this entails the necessity to adopt new tools and systems, shared with stakeholders and effective in order to manage forests resources in a sustainable way: SFM is largely discussed and several issues have been addressed and tentatively applied in many countries. Conceiving of the forest as a system is obvious for foresters and biologists. The self organisation of the complex of trees, fauna, shrubs, herbs, microfauna in the soil and so on is well recognised. But the relationship between all these components, man included, are highly complicated and not all clearly understood - and consequently not manageable with a direct cause-effect approach. The matter is to understand that the forest is a complex, self-

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organising system, that react against - or better consequently – to any human action and intervention, e.g. cutting, clearing, plantation. It means that any human action causes a feedback by the forest. This fact implies some basic assumptions:

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understand that any action must be planned taking into account the past cultivation (or self evolution) history of each forest, each stand, and being aware that the actual action will be the base for the future ones, sylviculture must be approached considering the time scale factor: trees species have a life that spans over centuries, even if the man manage them in shorter cycle in order to take wood and services for a short term utilities, managing forest is anyway a trials and errors activities: plans must be revised each 5-10 years in order to analyze and correct the programs depending from forest feedback, verified by monitoring the results of any intervention, SFM, especially at the management plan level, must not be limited to consider trees and sylvicultural aspects, but must take into account the various other aspects of the forest environment in broad sense, e.g. fauna and game management, touristic opportunities, funds necessities, logging and raw wood selling. On the base of these assumptions, shared on international level (e.g. Franklin et al. 2002; Schutz 1999), a―systemic approach‖ or ―holistic approach‖ has been developed in Italy by a foresters group especially in the University o Florence, (Ciancio and Nocentini, 1996, 1997, Ciancio, 2009), that bases the ―systemic sylviculture‖ on the continuous, capillary spread and cautious felling; something similar at international level has been proposed by some other Authors (e.g. ―Sylviculture based on natural dynamics‖ (Bergeron and Harley, 1997). The feedback of the forest must be checked periodically in order to correct the actions and achieve the expected results. The main target of this approach is to enhance the ecological functionality of the forest as system. No predetermined felling schemes are adopted (―Strict regulation and sylviculture norms should be avoided...‖ Bergeron and Harley, 1997), but the interventions follow the forest needs, in order to support natural, diffused regeneration of trees. In a such way the woods tend to form mixed unevenaged stands, that are more resilient and form ecologically well balanced system in their environment. Another pillar of this approach is to put some limits to keep to in the minimum stock that must be left in every forest type after each exploitation. The stock level depends on the characters of the species forming the wood. For instance, heliophile species requires a minimum stock of 100 -150 cubic meters per hectare, while in the shade tolerant species (sciaphile) forests a greater minimum stock of 300 -350 cubic meters per hectare must remain after each exploitation. The limits have to be defined for each forest when drawing plans. Planning and managing tools developed following these guidelines have the target – and when applied, result - in an increase of species diversity and structure complexity, stand stock growth, successful of natural regeneration. Moreover, a great care is focused on managing specific issues, as the conservation of habitats, the deadwood and its food chain, the conservation and care of ancient, monumental trees. There are many new things in this approach, so synthetically above exposed, more than such a glance can reveal. But the core matter is to change the way to cope with the problems of the man-forest relationship, from a pure wood exploitation towards a harmonic

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cohabitation and a functional exchange of services and respect of the forest needs. And this last, paraphrasing Aldo Leopold (1933), is a good forest policy, a good forest economy.

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7. CONCLUSION In the recent past a new approach to forestry is increasing between foresters and naturalists, following the awareness of the importance of forests with regards to their uncountable utilities and role in the environment. In consequence of this, the classical tools of forest governance have been overtaken: it needs to find new more flexible tools, based on the effective knowledge acquired from national and regional inventories, thematic maps and GIS opportunities. In Italy, after a long period of stasis, following the decentralization of the forest matter from the state to the regional administrative authorities in the second half of the last century, a new asset of the whole sector is going on. Regional Forest Plans have been drawn, regional laws enacted. The forest sector is no more a closed off matter for foresters, nor an isolated, remote part of territories to be managed with their own rules. There is a growing need to harmonize the forest planning tools with other parallel sector tools, in an Hierarchical and Heterarchical logic: (i.e. vertical and horizontal) by establishing mutual controls and links with towns and environmental plans at different levels, for the true achieving of SFM and SEM (Sustainable Environmental Management). A gap in the planning and management stood out, due to the need for a middle-size plan at territorial level, between the regional and forest management plan. Tentative plans at this level have been drafted in some regions both in an experimental and an effective way, but there still isn't a common shared and legally valid definition of these plans, nor a clear idea of the meaning of ―territorial‖ in terms of effective surface between regions. In the mean time the management plans are changing their objective: from a main wood production target toward the cultivation of forests aimed to enhance their ecological functionality, as factor of stability and, as a result, effectiveness of the multiple services to human society. This process, as demonstrated by several study cases, entailed the rediscovering of traditional knowledge of forest practices previously adopted, for centuries, by the mountain people. Adopting traditional methods resulted also in a wider stakeholders agreement and in diversity improvement. Nonetheless, many problems remain unsolved. For instance, in order to popularize and spread the necessity of planning in Central and Southern Italy, as well as in other European countries, it is compulsory to improve technical assistance both to public and private owners. A great opportunity, in regard to this, is offered by the European Community Forest Acts, that plans to assign contributions to enhance technical professional assistance for management plan drawing and application. In Italy those funds are channeled by the Regional Programs for rural development. Another problem—still not handled by regional plans—is the fragmentation of property. This strongly hinders the management of private property woods, often divided in very small estates, so that the costs of planning cannot be faced with respect to the importance of the

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assets. In respect to this also, the above cited Forest Acts assigns funds to promote small land owners pooling. Planning and management activities in Italy are going towards a progressive enhancement and effectiveness, even if this process is still beginning and not yet fully shared. European Community acts are leading toward a common platform for planning and managing the environmental matter: this will contribute to developing common shared regulations.

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REFERENCES A. A. V. V. (1999). Mozione Finale. In: II Congresso Nazionale di Selvicoltura ―Per il miglioramento e la conservazione dei boschi italiani‖: vol. I ( XI-XIII). Venezia, Italy: Direzione Generale Risorse For. Montane Idriche - Accademia It. Sc. Forestali Consulta Naz. Foreste Legno. Agnoletti, M. (2005). Osservazioni sulle dinamiche dei boschi e del paesaggio forestale italiano tra 1862 e la fine del secolo XX. Società e storia, XXVIII, 108, 377-396. Bergeron, Y. & Harley, B. (1997). Basing silviculture on natural ecosystem dynamics: an approach applied to the southern boreal mixedwood forest of Quebec. Forest Ecology and Management, 92, 235-242. Bagnaresi, U., Ciancio, O. & Pettenella, D. (2000). Il settore forestale italiano: linee guida e strumenti di politica forestale. CNEL - Consiglio Nazionale dell‘Economia e del Lavoro. Bianchi, M. (2004). Il progetto ―Ri.selv.Italia‖: programma comune di ricerca sulla selvicoltura in Italia. Forest@, 1 (2), 109-111. [online] URL: http://www.sisef.it/ Bianchi, M., Cantiani, P. & Ferretti, F. (2006). Criteri per la raccolta e organizzazione dei dati e per l‘informatizzazione delle procedure per la pianificazione e gestione forestale. Annali Istituto Sperimentale Selvicoltura, 32, 9-24. Bovio, G. (1999). Problemi e prospettive della selvicoltura – Alpi Centro-Occidentali. II Congresso Nazionale di Selvicoltura ―Per il miglioramento e la conservazione dei boschi italiani‖, Venezia, Vol. II, 43-78. Bovio, G., Ceccato, R., Francesetti, A. & Marzano, R. (2004). La Pianificazione Forestale Territoriale - stato dell‘arte e prospettive di sviluppo. Progetto Riselvitalia, Sottoprogetto 4.2 - Sistemi informativi di supporto per la gestione forestale. Milano. Braudel, F. (2002). Civiltà e imperi del Mediterraneo nell‘età di Filippo II. Turin, vol. 1, Einaudi, 692. Burnett, C. & Blaschke, T. (2003). A multi-scale segmentation/object relationship modelling methodology for landscape analysis. Ecological Modelling, 168, 233-249. Church, R. L., Murray, A. T., Figueroa, M. A. & Barber, K. H. (2000). Support system development for forest ecosystem management. European Journal of Operational Research, 121, 247-258. Ciancio, O. (2009). Quale selvicoltura nel XXI secolo? Atti del Terzo Congresso Nazionale di Selvicoltura. Taormina (ME). Accademia Italiana di Scienze Forestali, Firenze, 3-39. Ciancio, O. & Nocentini, S. (1996). Systemic silviculture: scientific and technical consequences. La selvicoltura sistemica: conseguenze scientifiche e tecniche. L‘Italia Forestale e Montana, 51(2), 112-130.

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IPLA, (2004). La pianificazione silvo-pastorale in Piemonte: Norme tecniche per i Piani Forestali Territoriali - Indirizzi metodologici per i Piani Forestali Aziendali. Torino, Regione Piemonte, Settore Politiche Forestali (CD-Room). ISAFA/MAF, (1985). Inventario Forestale Nazionale 1985. Sintesi metodologica e risultati. Ministero Agricoltura e Foreste, Istituto Sperimentale per l‘Assestamento Forestale e l‘Alpicoltura, Trento. Hogl, K. (2002). Patterns of multi-level co-ordination for NFP-processes: learning from problems and success stories of European policy-making. Forest Policy and Economics, 4, 301-312. Leopold, A. (1933). The conservation ethic. Journal of Forestry. MAF, (1988). Piano Forestale Nazionale. Gazzetta Ufficiale. 7 marzo 1988. Marchetti, M., Cullotta, S. & Di Marzio, P. (2005). I sistemi di Aree Protette in Italia e il loro contributo alla conservazione forestale. L‘Italia Forestale e Montana (Italian Journal of Forest and Mountain Environments), LX, 559-581. Marchetti, M. & Mariano, A. (2006). Alcune considerazioni sulla valutazione della consistenza e dello stato delle risorse forestali secondo le organizzazioni internazionali di settore. Forest@, 3 (3), 351-366. [online] URL: http://www.sisef.it/ MCPFE, (1993). Resolution H1 – General Guidelines for the Sustainable Management of Forests in Europe. Second Ministerial Conference on the Protection of Forests in Europe, Helsinky, Finland. MCPFE, (2003). State of Europe‘s forests 2003—the MCPFE report on sustainable forest management in Europe. In: Ministerial Conference on the Protection of Forests in Europe, Liaison Unit Vienna and UNECE/FAO Michaelsen, T., Ljungmann, L., El-Lakany, M.H., Hyttinen, P., Giesen, K., Kaiser, M. & Von Zitzewitz, E. (2000). Hot spot in the field: National Forest Programmes – a new instrument within old conflicts of the forestry sector. Forest Policy and Economics, 1, 95106. Mitchell, N., Espie, P. & Hankin, R. (2004). Rational landscape decision-making: the use of meso-scale climatic analysis to promote sustainable land management. Landscape and Urban Planning, 67, 131-140. MIPAAF, (2007). Inventario Nazionale delle Foreste e dei Serbatoi di Carbonio INFC – Le stime di superficie (Prima Parte). MIPAAF – Corpo Forestale dello Stato, ISAFA, Trento. 413. MIPAAF, (2008). Programma Quadro per il Settore Forestale. MIPAAF, MATTM, CFS, INEA, ISMEA, Conferenza Stato-Regioni e P.A. 130. Montiel, C. & Galiana, L. (2005). Forest policy and land planning policy in Spain: a regional approach. Forest Policy and Economics, 7, 131-142. Patrone, G. (1940). Assestamento forestale. Ed. Coppini, Firenze. Pulzl, H. & Rametsteiner, E. (2002). Grounding international modes of governance into National Forest Programmes. Forest Policy and Economics, 4, 259-268. Rametsteiner, E. & Mayer, P. (2004). Sustainable forest management and Pan-European forest policy. Ecological Bulletin, 51, 51-57. REGIONE AUTONOMA SARDEGNA, (2007). Piano Forestale Ambientale Regionale. Regione Autonoma Sardegna, Assessorato della Difesa dell‘Ambiente. 316. Sereni, E. (1961). Storia del Paesaggio Agrario Italiano, Laterza, Bari.

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Schutz, J. Ph. (1999). Close-to-nature silviculture: is this concept compatible with species diversity? Forestry, 72, 361-368. Shannon, M. (2002). Understanding collaboration as deliberative communication, organizational form and emergent institution. In: Gislerud O, Neven I. (eds.) National Forest Programmes in a European Context. EFI Proceedings, 44, 7-26. V. Solari, (Ed.), Del Favero, R., Bortoli, P.L., Bolzon, P., Giuriceo, A. & D‘orlando, M. C. (2000). Progetti di riqualificazione forestale e ambientale e piani integrati particolareggiati. Udine, Regione Autonoma Friuli-Venezia Giulia, Direzione regionale delle foreste, 95. UNFF - United Nations Forum on Forests (2002). Report of the Secretary General on National Forest Programmes, New York (EyCN.18y2002y4). UNITED NATIONS, (1992). Agenda 21, Ch. 11. Combating Deforestation. United Nations Conference on the Environment and Development. Rio de Janeiro. Wolynski, A. (2005). Sviluppi recenti dell'assestamento forestale in Italia settentrionale. SAFE-Infoblatt, 19, 6-7. Zimmermann, W. & Mauderli, U. (2001). ―National Forest Programs in European Countries.‖ http://www.metla.fi/eu/cost/e19/papers. htm (November 28, 2004).

In: Environmental Planning Editor: Rebecca D. Newton

ISBN: 978-1-61728-654-4 © 2011 Nova Science Publishers, Inc.

Chapter 5

OPERATIONS RESEARCH METHODS IN PRODUCTION MANAGEMENT WITH ENVIRONMENTAL CONSTRAINTS Marius Rădulescu, Constanta Zoie Rădulescu and Gheorghiţă Zbăganu

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1

Institute of Mathematical Statistics and Applied Mathematics, Casa Academiei Romane, Calea 13 Septembrie nr.13, RO-050711, Bucharest 5, ROMANIA 2 National Institute for Research and Development in Informatics, 8-10 Averescu Avenue, RO-011455, Bucharest 1, ROMANIA 3 Faculty of Mathematics and Computer Science, University of Bucharest, Academiei 14, RO-010014, Bucharest 1, ROMANIA

ABSTRACT Economic growth is frequently considered to be in conflict with sustainable development and environmental quality. With increasingly stringent environmental regulations, there is a growing need for efficient production planning models that take into account the trade-off between return and environmental costs and therefore reduce the penalties paid for overcoming the pollution levels. This chapter surveys partially the current state of the literature in operations research approaches to production management in the presence of environmental constraints. A special attention is paid to the application of portfolio theory and to loss function theory to production planning models with environmental constraints. Our research has been focusing in the area of pollution prevention, consequently the models can be considered sustainable production planning models.



Corresponding author: Email: [email protected]

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Keywords: multiple objective programming, production planning, environmental constraints, pollutant emission, crop planning, portfolio theory, loss function theory.

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1. INTRODUCTION Economic growth is frequently considered to be in conflict with sustainable development and environmental quality. In the last decades environmental considerations are increasingly playing an important part in our lives. Research activity directed toward environmental issues in production management has gained a great interest since the early 1990s. Various strategies have been developed to mitigate the effects of pollution. Unfortunately, these strategies are expensive to implement and may take years to have the desired effect. The pollution levels have increased very much in amount and toxicity in the last decades. People recognize that the solution to the pollution problem is pollution prevention, rather than clean up or control, although the alternative approach of source reduction may be a good starting point to the prevention process. With increasingly stringent environmental regulations, there is a growing need for efficient production planning models that take into account the trade-off between return and environmental costs and therefore reduce the penalties paid for overcoming the pollution levels. This chapter surveys partially the current state of the literature in operations research approaches to production management in the presence of environmental constraints. A special attention is paid to the application of portfolio theory and to loss function theory to production planning models with environmental constraints. Several multiobjective programming models for industrial and agricultural production are formulated. Some of them are in continuous variables and others are in discrete variables. The two multiobjective models for the industrial production planning are illustrated with practical examples from the textile industry. A binary multiobjective model for crop planning under uncertainty in the presence of production quotas is presented in the fifth paragraph of the chapter. It uses loss functions and several target production quotas. Starting from the multiple objective programming model, one formulates several single objective models. We analyze losses associated to the optimal production plans that try to comply to the target production quotas versus various parameters of the average loss minimization model.

2. A SURVEY OF RESEARCH IN MATHEMATICAL MODELING FOR ENVIRONMENT PROTECTION Industrial production consists in the transformation of material resources with the participation of human beings. It is a process in which natural resources are processed or manufactured into products for consumer or re-processing purposes, in which natural resources are needed for the processing or manufacturing of products. Therefore, consumption of natural resources is a necessary condition for industrial production. Solid, liquid, gas and other wastes resulting from industrial production are bound to affect the natural environment and thus environmental changes are another inevitable result of industrial production. There is a limit to either the degree of consumption of resources, or to that of

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Operations Research Methods in Production Management with Environmental… 137 environmental change (pollution and destruction in particular) that may be tolerated. Excessive resource consumption and environmental destruction not only make industrial production unsustainable, but also destroy the basic conditions for humanity‘s survival. Today the industrial development implies a colossal consumption of resources and a great impact on the environment. Therefore mankind‘s industrial development is challenged more severely by resource and by environmental constraints. In the 21st century, resource and environmental problems are becoming even more serious. This situation is challenging: the mankind must maintain a sustainable development and achieve its socioeconomic development goals despite of the severe resource and environmental constraints. The concept of sustainable development supposes harmonization or simultaneous realization of the objectives connected to economic growth, environment quality and social progress. An important factor that determines the economic growth is the industrial development. Pollution prevention is one of the most serious challenges that are currently facing the industry. At present the majority of the industrial enterprises make production plans that pollute the environment. After that they apply different methods for cleaning up the environment. The pollution prevention seems to be the most appropriate policy the industrial enterprises must adopt. The clean up or control and the approach of source reduction may be a start to the prevention process. With increasingly stringent environmental regulations, there is a growing need for efficient production planning models that take into account the trade-off between return and environmental costs and therefore reduce the penalties paid for overcoming the pollution levels. The importance of the problems connected with environment protection and pollution prevention represent a stimulus for the research in mathematical modeling of production processes and manufacturing systems. Production planning is a complicated task that requires cooperation among multiple functional units in any organization. In order to design an efficient production planning system, a good understanding of the environment in terms of customers, products and manufacturing processes is necessary. Although such planning exists in the company, it is often incorrectly structured due to the presence of multiple conflicting objectives. The primary difficulty in modern decision analysis is the treatment of multiple conflicting objectives. A formal decision analysis that is capable of handling multiple conflicting goals through the use of priorities may be a new frontier of management science. Application and potential use of models is the central theme of this survey. Issues for future research are presented at the end and an extensive list of publications is provided in the references at the end of the chapter. The enterprise managers become more and more aware of the potential benefits of the integrated production-planning decision support systems (DSS). Reiborn (1999) has shown that, in the long run, the investments in systems for environment management are smaller than the benefits of the firms. The importance of the problems connected with environment protection and pollution prevention is a stimulus for research in mathematical modeling of production processes. There are many papers dealing with various mathematical models of production systems and related sustainable technologies (Bloemhof et al., 1995), (Chakraborty et al., 2004), (Cheng et al., 2003), (Clarke, 1987), (Daniel et al., 1997), (Dohin and Kaios, 1995), (Grauer et al., 1984), (Klassen and McLaughlin, 1999), (Klassen and Whybark, 1999), (Lemathe and Balakrishnan, 2005), (Linninger et al., 2000), (Melnyk et al., 1999), (Nijkamp and Van den

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138

Marius Rădulescu, Constanta Zoie Rădulescu and Gheorghiţă Zbăganu

Bergh, 1997), (Penkuhn et al., 1997), (Qiu et al., 2001), ( Radulescu et al. 2009), (ReVelle, 2000), (Ulhoi, 1995), (Wirl, 1991), (Wirl et al. 1987), (Wu and Chang 2004, 2005). Interesting references, environmental standards and several mathematical models can be found in (Klassen and Whybark, 1999). A rich list of references concerning papers on sustainable production technologies is given in (Radulescu et al. 2009). At present „ green manufacturing‖ is an objective which must be adopted by all industries with a view to reducing the environmental impact of product and production processes (Blanchard and Fabrycky 2006). In (Melnyk et al., 1999) and (Steven and Lemathe, 1996) the authors suggest the integration of output related material and energy flows such as waste, sewage and pollutants into bills of materials. This integration refers to the coefficients that characterize different operating procedures. A great number of decisions about industrial production are made under uncertainty. Uncertainty governs the market price of industrial products, the price of raw materials and energy, the attempts of the firms to comply with environmental constraints etc. Mathematical modeling of the decision problems under uncertainty is much more difficult than that of the deterministic decision problems. Decision problems under uncertainty generate difficult large scale optimization problems. Often these problems are complicated by the presence of integer decision variables which are used to model the logical restrictions or cardinality restrictions. Their complexity degree increases very much when several periods are taken into account (multiperiod models). Operating in a changing and uncertain environment, firms must make strategic and operational decisions while trying to satisfy many conflicting goals. For example, in order to maximize expected profit and minimize risk, they must periodically decide when and by how much to expand capacity and even more often how much to produce, all in the face of unknown future demands, available technology, and so on. We refer to this class of problem as multi-objective decision processes under uncertainty. The interested reader may find several decision making models for the industrial production which take into consideration the uncertainty in the following papers (Chakraborty et al., 2004), (Cheng et al., 2003), (Ierapetritou et al., 1996), (Linninger et al., 2000), (Wu and Chang 2004, 2005). An overview on the problems connected with optimization in the presence of uncertainty may be found in (Sahinidis, 2004).

3. FORMULATION OF A MULTIOBJECTIVE MODEL IN CONTINUOUS VARIABLE In what follows a sustainable production plan means a production plan that satisfies suitable environmental constraints. We shall formulate several optimal production planning models that take into account various environmental constraints. A general multiobjective stochastic programming problem is formulated where the objective functions are the expected return of the production plan and the penalties for the case when the cumulative effect of each emission overcomes some environmental levels. The manager tries to find a production plan that maximize the expected return, minimize the pollution penalties and satisfies the environmental constraints.

Operations Research Methods in Production Management with Environmental… 139 Suppose that an industrial firm has the possibility to manufacture the products P1 , P2 ,…,

Pn . Here by a product we understand not only the product, but the product together its

production technology. Let ,K, P  be a probability space and ci :   R   R  , i = 1,2,..., n. Suppose that c i  , S  :   R  are random variables for every i = 1,2,..., n and S  R  . If the manager invests the sum S in the manufacture of product i then he will obtain a return equal to c i  , S . A unit of the product Pi is defined as an amount of the product Pi for which the manager invested one monetary unit, say one euro. The manufacture of a product generates none, one or several pollution emissions F1 , F2 ,…, Fm and requires p resources

R1 , R 2 ,..., R p . We denote by bij the amount of pollution emission F j per unit of product

Pi and by cik the amount of resource Rk required per unit of product Pi . Denote by rk the maximum availability of resource Rk . Since bij depends on several random factors, including the conditions of the experiment in which the measurement of it is performed, we shall consider that bij is a random variable. Consequently we shall suppose that all bij :   R  are random variables (measurable functions).

bij are random variables because

repeated measurements of the same quantity yield slightly different values. In practice the uncertainty on the result may arise from many possible sources. Some of them are: human error, environmental conditions, sampling process, incomplete definition, matrix effects and interferences, uncertainties of masses and volumetric equipment, reference values, approximations and assumptions incorporated in the measurement method and procedure, and random variation. There are two kinds of errors: sampling errors and non-sampling errors. The sampling errors are associated with the process of selecting a sample. Non-sampling errors can be defined as errors arising during the course of all survey activities other than sampling. In our chapter we consider only random errors. The firm manager has a sum M of money that desires to invest in the manufacture of the products P1 , P2 ,…, Pn such that to obtain a maximum expected return and a minimum risk

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T

T

for the pollution of the environment. In this chapter the pollution risk is measured by the penalties paid by the manager for the environment pollution. We denote by d j1 the desirable or target pollution level for the pollutant emission F j . We denote by d j 2 the alarm level of pollution for the pollutant emission F j . We denote by d j 3 the maximum acceptable limit of pollution for the pollutant emission

F j . Of course

0  d j1  d j 2  d j 3 for every j = 1, 2,..., m. A small overcome of the level

d j1

represents no danger for the environment. It represents only a warning that the pollution process had already began. A small overcome of the level d j 2 represents a warning that the pollution process may have consequences for the environment.

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140

An overcome of the level d j 3 is a warning that the pollution process had already produced bad consequences for the environment and urgent measures must be taken in order to stop the process. We denote by  js the admissible risk degree for overcoming the desirable risk level d js s = 1, 2, 3. Let x  x1 , x 2 ,..., x n  be the fabrication plan of the manager. This means that the manager wishes to use the sum xi in order to manufacture the product Pi , i =1,2,...,n. If a is a real number we denote by a  the positive part of a, that is:

a   max a,0

a a 2

We consider two approaches to the measure of the environmental risk. A first approach is based on the assumption that the environmental penalty is proportional to the expected amount of pollutant that overcomes the pollution level. Consequently it is equal to

 n  a js   E bij xi  d js   i 1  We denote by a js the proportionality factor from the environmental penalty and by

 

E bij the expected value of the random variable bij . In this case the overall environmental Copyright © 2010. Nova Science Publishers, Incorporated. All rights reserved.

penalty is  n  a bij xi  d js   js   E  s 1 j 1  i 1  3

m

(3.1)

The idea of considering a desirable pollution level and environmental penalties proportional to the amount of pollutant that overcome the pollution level goes back to (Qiu et al., 2001). In a city the value of the above level is supposed to be fixed by the city environmental protection department. It strongly depends by the degree of industrial pollution in the city. The value of this level may decrease in a polluted city and increase in a low polluted city. A second approach is based on the assumption that the environmental penalty is proportional to the probability that the amount of pollutant overcomes the pollution levels. In this case the overall environmental penalty will be equal to 3

m

 a s 2 j 1

js

 n  m  n  P  bij xi  d js    a j1   E bij xi  d j1   i 1  j 1  i 1 

(3.2)

Operations Research Methods in Production Management with Environmental… 141 The manager must take into account environmental constraints. We shall define two types of environmental constraints: Mean type environmental constraints These types of constraints impose some bounds on the expected amount of pollutant emissions as e.g.,

 Eb x n

i 1

ij

i

 d j4

j  1,2,...,m

(3.3)

Here we denote by d j 4 a number smaller or equal than d j 3 , which is a measure of the aversion against a polluted environment. The smaller is d j 4 , the cleaner is the environment. We shall denote by E1 the set of all nonnegative vectors x  x1 , x 2 ,..., x n  that satisfy constraints (3.3). Safety-first type environmental constraints: These types of constraints impose some bounds on the probability that the pollutant emissions overcome the pollution levels as e.g.,

 n  P  bij xi  d js    js  i 1 

j  1,2,...,m

s  2,3

(3.4)

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We denote by E 2 the set of all nonnegative vectors x  x1 , x 2 ,..., x n  that satisfy the constraints (3.4). From the mathematical point of view no relation can be established between safety-first and mean type environmental constraints. The advantage of mean type environmental constraints is that they are easily to be checked. The drawback of the safety-first type environmental constraints is that checking them is time consuming. However the engineers that manage the production process feel that the safety-first environmental constraints capture more accurately the pollution risk than the expected value environmental constraints. In order to use efficiently the available funds, the manager tries to find a fabrication plan x  x1 , x2 ,..., xn  yielding a maximum return, minimizing the overcome of the pollution levels and allowing him to comply with environmental restrictions. In order to find such a plan the manager must solve the following stochastic multiobjective programming problems ( q  1,2):

142

Marius Rădulescu, Constanta Zoie Rădulescu and Gheorghiţă Zbăganu   n  max  E  ci  , xi      i 1   n  min   E bij xi  d j1  j  1,2,..., m;   i 1  (SBB1qB)   n  min P  bij xi  d js  j  1,2,..., m; s  2,3   i 1  n  x M i  i 1  x  E q n  cik xi  rk k  1,2,..., p  i 1

There are several approaches allowing to reduce this problem to single objective programming problems. A common approach is to consider the objective function n  3 m  n  m  n  f1 x  E  ci  , xi    a js P  bij xi  d js    a j1   E bij xi  d j1   i 1  s 2 j 1  i 1  j 1  i 1 

and to maximize f1 subject to the set of feasible solutions of problem (S1p). Two other approaches are presented in the next section. B

B

B

B

3.1. The Maximum Expected Return Problem

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In the maximum expected return problem the manager tries to maximize the expected return taking into account the following restrictions: the production plans satisfy the environmental conditions (3.3) or (3.4), that is x  E q where q=1 or q=2. the sum invested in the fabrication plan is equal to M. for all k  1,2,..., p the total amount of resource Rk required by the fabrication plan is less or equal than rk    n  max  E  ci  , xi      i 1   n (Qq(M))  xi  M  i 1 x  E q  n   cik xi  rk k  1,2,..., p  i 1 B

B

Operations Research Methods in Production Management with Environmental… 143 Problem (Qq(M)) is a stochastic parametric programming problem. The user parameter M is the sum invested by the manager for producing the fabrication plan x. An important problem for the manager is to find the range of parameter M. Denote by M1q the optimal value of the optimization problem: B

B

B

B

 n  max  xi   i 1  (Aq)  x  E  q n  cik xi  rk  i 1 B

B

k  1,2,..., p

In order that the set of feasible solutions of problem (Qq(M)) be nonempty, the manager must choose the parameter M in the interval [0, M 1q ] . B

B

3.2. The Minimum Pollution Risk Problem with Environmental Constraints In the minimum pollution risk problem the manager tries to minimize a linear combination (with positive coefficients) of the probabilities of overcoming the pollution levels and of the positive part of the difference between the expected amount of pollutant emission and the desirable pollution level, taking into account the following restrictions:

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the production plans satisfy the environmental conditions (3.1) or (3.2), that is x  Eq where q=1 or q=2. the expected return is greater than a given level W. the sum invested in fabrication plan is equal to M.   3 m   n  m  n   min  a js P  bij xi  d js    a j1   E bij xi  d j1    i 1  j 1  i 1    s 2 j 1  x  E q (P1q(M,W,a))  n     E  ci  , xi   W    i 1 n  xi  M  i 1 n  cik xi  rk k  1,2,..., p  i 1 B

B

The problem P1q(M,W,a) is a stochastic parametric programming problem. The user parameter M is the sum of money invested by the manager for producing the fabrication plan x. The parameter a stands for the m  3 matrix a js . The coefficients a js are positive. B

B

 

Marius Rădulescu, Constanta Zoie Rădulescu and Gheorghiţă Zbăganu

144

Their signification is connected with the penalties (charges) paid by the manager for the pollution emission. W is a lower bound for the return desired by the manager. An important problem for the manager is to find the ranges of parameters M and W. Denote by M1q the optimal value of the problem (A1q). The range of parameter M is the interval [0, M 1q ] . Suppose that the manager make a choice for the parameter M in the B

B

B

B

interval [0, M 1q ] . In order to determine a range of variation for the parameter W we shall consider the following two optimization problems:    n  min  E  ci  , xi      i 1  n (B1q)  xi  M  i 1 x  E q  n   cik xi  rk k  1,2,..., p  i 1 B

B

and    n  max  E  ci  , xi      i 1  n (B2q)  x  M i  i 1 x  E q  n  cik xi  rk k  1,2,..., p  i 1

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B

B

Denote by W1q and W2 q the optimal values of the objective functions of problems (B1q) B

B

and (B2q). In order that the set of feasible solutions be nonempty, the manager must choose the parameter W in the interval [W1q ,W2 q ] . B

B

There are several approaches in order to solve the above optimization problems. One approach require the specification of the probability distributions of the random vectors b j  b1 j , b2 j ,..., bnj , j = 1, 2,..., m. The special case when the random vectors b j have a





multivariate normal distribution is of interest. Another approach is to treat the sample variables as an empirical distribution. The result of the optimization is valid as long as the empirical distribution accurately represents the true underlying distribution. A common method used in to solve the problems obtained as a result of this approach is based on heuristic algorithms and computer simulation.

Operations Research Methods in Production Management with Environmental… 145

3.3. The Minimum Pollution Risk Problem with Mean Type Environmental Constraints In this section we shall study the minimum pollution risk problem when the pollution risk is defined by equation (3.1). The manager tries to minimize a linear combination (with positive coefficients) of the positive part of the difference between the expected amount of pollutant emissions and the pollution levels, taking into account the following restrictions: the expected amount of pollutant emission for each pollutant emission F j is smaller than

d j 3 , the maximum acceptable limit of pollution for the pollutant emission F j . the expected return is greater than a given level W. the sum invested in the fabrication plan is equal to M. for all k  1,2,..., p the total amount of resource Rk required by the fabrication plan is less or equal than rk    3 m  n   min   a js   E bij xi  d js       s 1 j 1  i 1 x  E 1 (P2(M,W,a))  n     E  ci  , xi   W    i 1 n  xi  M  i 1 n  cik xi  rk k  1,2 ,..., p  i 1

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B

B

The Problem (P2(M,W,a)) is a nonlinear deterministic parametric programming problem. The user parameter M is the sum of money invested by the manager for producing the fabrication plan x, while parameter a stands for the m  3 matrix a js . The coefficients a js B

B

 

are positive. Their meaning is connected with the penalties (charges) paid by the manager for the pollution emission. W is a lower bound for the return desired by the manager. An important problem for the manager is to find the ranges of parameters M and W. Denote by M2 the optimal value of the problem (A2). The range of parameter M is the interval 0, M 2  . Suppose that the manager make a choice for the parameter M in the interval B

B

B

B

0, M 2  .

In order to determine a range for the parameter W we shall consider the following two optimization problems:

Marius Rădulescu, Constanta Zoie Rădulescu and Gheorghiţă Zbăganu

146

  n  min  E  c i  , x i      i 1  n (C1)  x  M i  i 1  x  E1 n k  1,2,..., p  c ik x i  rk  i 1 B

B

and   n  max  E  c i  , x i      i 1  n (C2)  x  M i  i 1  x  E1 n k  1,2,..., p  c ik x i  rk  i 1 B

B

Denote by W1 and W2 the optimal values of the objective functions of problems (C1) B

B

and (C2). In order that the set of feasible solutions be nonempty, the manager must choose the parameter W in the interval W1 ,W2 . B

B

In the case when the profit functions are linear, that is there exist the nonnegative random variables q i :   R  such that ci , s   q i s , s > 0,    , the (P2(M,W,a)) model B

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is equivalent to the linear programming model:   3 m  min  a js y js    s 1 j 1  n  E bij xi  d js  y js j  1,2,..., m; s  1,2  i 1 n  E bij xi  d j 4 j  1,2,..., m;  i 1 n   E qi xi  W  i 1 n  xi  M  i 1 n  cik xi  rk k  1,2,..., p  i 1  xi  0, y js  0, i  1,2,..., n; j  1,2,..., m, s  1,2  

B

Operations Research Methods in Production Management with Environmental… 147 The decision variables in the above model are the vectors x  x1 , x 2 ,..., x n  and

y s   y s1 , y s 2 ,..., y sm  , s=1,2.

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3.4. Numerical Results The textile industry uses vast amounts of water, energy and chemicals. Dyes and auxiliary chemicals used in textile mills have hard environmental influences. Textile processing generates many waste streams, including water-based effluent as well as air emissions, solid wastes, and hazardous wastes. Textile manufacturing is one of the largest producers of wastewater. On average, approximately 160 liters of water are required to produce 1 kg of textile product. Textile also is a chemically intensive industry and therefore the waste wastewater from textile processing contains processing bath residues from preparation, dyeing, finishing, slashing and other operations. These residues can cause damage to the environment. State authorities and local municipalities have begun to target the textile industry to clean up the wastewater that is being discharged from the textile mills and to apply technologies that prevent pollution. In order to maximize pollution prevention it is necessary to apply production plans which maximize the return and minimize the pollution of the environment. In what follows we shall apply some of our models (the maximum return models) in order to obtain optimal production plans for a firm from textile industry. Consider a textile firm. Its manager wants to find a fabrication plan for 10 products that maximize the return and complies with environmental constraints related to water pollution. Two kinds of environmental constraints are considered: mean type and safety-first type. The mean type environmental constraints are defined by the upper limits for the expected value of pollutants that is by the vector d 4  d j 4  .

 

The safety-first type environmental constraints are defined by the vectors ε s   js ,

d s  d js  , s = 2, 3 where  js are the admissible risk degrees and d js are the pollution levels. We recall that a production plan satisfies these constraints if the probabilities that the cumulative effect of the polluting emissions overcome the pollution levels are smaller than the admissible risk degrees for overcoming the pollution risk levels d js . In our numerical example we put  j 2  0.05 ,  j 3  0.01 , j=1,2,3,4. Let M be the sum invested in fabrication plan. Suppose that M=100000 euros. We shall consider that the amount of the resources is sufficiently large and the return functions ci  ,  are linear, that is ci  , S  = qi S for all    , S  0 , i=1,2,...,10. For water consider the pollution indicators: In the above table the alarm levels and the maximum admissible levels are taken from the Romanian normative for wasted water NTPA 002/2005. The manager intends to make a production plan starting from a set of 10 products. Here by a product we understand a textile product together the technology it is produced. There are classical technologies which usually generate a higher level of pollution and sustainable (ecological, clean or green) technologies

Marius Rădulescu, Constanta Zoie Rădulescu and Gheorghiţă Zbăganu

148

that generate a lower level of pollution. Some of the well known sustainable technologies that are applied in the textile industry are those based on enzymes and membranes. Table 3.1. Pollution indicators Nr. crt. 1 2 3 4

Pollution indicators CCO-Cr Suspended solid CBO5 Biodegradable detergent

Unit measure

Target level 175 74 40 0.00

Mg O2/l Mg/l Mg O2/l Mg/l

Alarm level 350 245 210 17.5

Maximum admissible level 500 350 300 25

Table 3.2. Products and technologies Nr. crt.

1

2 3

4

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5 6 7 8 9 10

Name of the product and technology

Product cotton woven 100% Ecological technology with the Bactosal ARL enzyme Product cotton woven 100% Classical technology Product dyed woven Technology with direct dyes (classical) Product dyed woven Technology with reactive dyes (eco) Product printed fabrics Classical technology Product printed fabrics Print by transfer technology Product dyed cotton yarn Classical technology Product dyed cotton yarn Enzyme technology Product dyed fabrics Classical technology Product mercerized fabrics Classical technology

Rate of return

Optimal production plan

0.20

with mean type constraints 19463

with safety-first type constraints 23537

0.25

0.0

0.0

0.15

0.0

0.0

0.25

35235

34245

0.14

0.0

0.0

0.15

0.0

2304

0.25

0.0

0.0

0.12

10067

10023

0.18

0.0

0.0

0.14

35233

29891

The list of the 10 products is presented in table 3.2. Consider the 10 textile products and the matrix of expected unit emission outputs. The entries of matrix from table 3.3 are the expected values of the random variables bij. The ranges of the bij samples are at most  5% around the expected value of bij. The safety-first environmental constraints are approximated with cardinality constraints that are defined with the help of the empirical distributions of the random variables that describe the cumulative effect of the polluting emissions. B

B

B

B

B

B

Operations Research Methods in Production Management with Environmental… 149 This approach transforms the maximum return problem with safety-first environmental constraints in a combinatorial optimization problem that is difficult to be solved. In order to solve this problem we used a Premium solver (which is an upgrade of the Standard Microsoft Excel Solver) that uses genetic and evolutionary algorithms. The solution of the optimization problem is displayed in the last column of table 3.2. An analysis of the optimal production plan for the problem with mean type constraints shows that it contains 3 products, that is the products 1,4 and 8, that are manufactured using ecological technologies. One can easily see that the optimal production plan for the problem with safety-first type constraints contains 4 products, that is the products 1,4,6 and 8, that are manufactured using ecological technologies. Table 3.3. The matrix of expected unit emission outputs Nr. crt. Pollution indicator 1 2 3 4

Prod01

1.25 0.70 0.75 0.05

Prod02 Prod03

0,95 0,77 0.64 0.05

0.75 0.76 0.58 0.08

Prod04 Prod05 Prod06 Prod07 Prod08 Prod09 Prod10

0.61 0.50 0.46 0.06

1.14 0.95 0.80 0.06

1.00 0.70 0.70 0.06

0.97 0.82 0,60 0.07

0.78 0.63 0.52 0.05

1.00 0.50 0.81 0.07

1.20 0.92 0.68 0.04

Table 3.4. Pollution load for the optimum production plan

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Nr. Crt. 1 2 3 4

Pollution indicators

CCO-Cr Suspended solid CBO5 Biodegradable detergent

Upper limits for the expected value of pollutants Vector dj4 100000 70000 60000 5000

Pollution load for the optimum production plan with mean type constraints 97868 70000 60000 5000

In any case the optimal production plan contains at least three products that are manufactured using ecological technologies and at least 65% of the funds are invested in such products. An analysis of table 3.4 shows that the pollution load corresponding to the optimum production plan with mean type constraints is maximal for the pollution indicators 2,3 and 4, and it is close to the upper limit for the first pollution indicator.

4. FORMULATION OF A MULTIOBJECTIVE MODEL IN DISCRETE VARIABLES We shall formulate several discrete production planning models that take into account several environmental constraints. These models are discrete versions of the continuous variable models from the preceding paragraph. A general multi-objective programming problem is formulated in which the objective functions are the expected return of the

150

Marius Rădulescu, Constanta Zoie Rădulescu and Gheorghiţă Zbăganu

production plan and the penalties for the case when the cumulative effect of each emission overcome some environmental levels and the financial risk of the production plan. The manager tries to find a production plan that maximize the expected return of it, minimize the pollution penalties and satisfies the environmental constraints. Suppose that an industrial enterprise has the possibility to manufacture products of types T1 , T2 ,…, Tn . For all i=1,2,...,n, denote by ci the selling price of a product of type Ti . Note that all ci are random variables. The manufacture of a product generates none, one or several pollution emissions F1 , F2 ,…, Fm and requires p resources R 1, R2 ,..., R p . Denote by bij the amount of pollution emission F j when is manufactured a product of type Ti and by cik the amount of resource Rk required for manufacturing a product of type

Ti . Denote by rk the maximum availability of resource Rk . Note that bij and cik are nonnegative numbers. The enterprise manager wants to invest a sum M of money in the range M 1 , M 2  in order to manufacture products of types T1 , T2 ,…, Tn . He desires to obtain a fabrication plan x  x1 , x 2 ,..., x n  that gives him a maximum expected return, a minimum

risk for the environment pollution and a minimum financial risk. In the present chapter the pollution risk is measured by the penalties paid by the manager for the environment pollution. Denote by d j1 the desirable or target pollution level for the pollutant emission F j . Denote by d j 2 the alarm level of pollution for the pollutant emission

F j . Denote by d j 3 the maximum acceptable limit of pollution for the pollutant emission F j .

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Of course 0  d j1  d j 2  d j 3 for every j = 1, 2,..., m. A small overcome of the level d j1 represent no danger for the environment. It represents only a warning that the pollution process had already began. A small overcome of the level d j 2 represent a warning that the pollution process may have consequences for the environment. An overcome of the level d j 3 represents a warning that the pollution process had already produced bad consequences for the environment and urgent measures must be taken in order to stop the process. Let x  x1 , x 2 ,..., x n  be the fabrication plan of the manager. Here xi represents the number of products of type Ti , i =1,2,...,n. Denote by pi the production cost of a product of type Ti and by q i a minimum quantity of products of type Ti that should be produced. Of course pi are positive real numbers and q i are natural numbers for all i =1,2,...,n. The production cost for the fabrication plan x  x1 , x 2 ,..., x n  is equal to

n

 p x . We shall i i

i 1

call q  q1 , q2 ,..., qn  the vector of demand. If a is a real number we shall denote by a  the positive part of a, that is:

a   maxa ,0  

a a 2

Operations Research Methods in Production Management with Environmental… 151 We shall consider that, the environmental penalty paid in the case the fabrication plan x  x1 , x2 ,..., xn  is applied is proportional to the amount of pollutant that overcomes the pollution level. Consequently in the case of pollutant emission F j and pollution level d js it is equal to

 n  a js  bij xi  d js   i 1 



We denoted by a js the proportionality factor from the environmental penalty. The overall environmental penalty will be in this case 2

 n  a js  bij xi  d js  j 1  i 1  m



f1 x 

s 1



(4.1)

The idea of considering a desirable pollution level and environmental penalties proportional to the amount of pollutant that overcome the pollution level goes back to [20]. The manager must take into account environmental constraints. In our chapter we shall consider constraints that impose some bounds on the expected amount of pollutant emissions: n

b x

ij i

 d j 4 j  1,2,...,m

(4.2.)

i 1

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Here we denoted by d j 4 a number smaller or equal than d j 3 . It measures the aversion against a polluted environment. The smaller is d j 4 , the cleaner will be the environment. We shall denote by E1 the set of all nonnegative vectors x  x1 , x 2 ,..., x n  having integer components that satisfy: the inequalities xi  q i for all i, the environmental constraints (2) and the resource constraints n

c

ik xi

 rk

k  1,2,..., p

(4.3)

i 1

Denote by  ij the covariance of the random variables ci and c j . Let C   ij  be the covariance matrix. We shall define the financial risk of the production plan x as the variance of the its return

n

c x

i i

. One can easily see that

i 1

 n  Var  ci xi    i 1 



n

n

  i 1 j 1

ij xi x j

 xT Cx

152

Marius Rădulescu, Constanta Zoie Rădulescu and Gheorghiţă Zbăganu

In order to use efficiently the sum available, the manager tries to find a fabrication plan x  x1 , x2 ,..., xn  such that it will bring a maximum return, it will minimize the overcome of the pollution levels and the financial risk and it will allow him to comply with environmental restrictions. In order to find such a plan the manager must solve the following multiobjective programming problem:   n  max  E ci   pi xi    i 1   n min b x  d  s  1,2; j  1,2,..., m; js  (S)   i 1 ij i   n n      ij xi x j  min    i 1 j 1    n M 1  pi xi  M 2 , x  E1  i 1





 

There are several approaches for reducing the above problem to single objective programming problems. Two of them are presented in the following.

4.1. A Minimum Financial Risk Model

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In the minimum financial risk problems the manager tries to minimize the financial risk taking into account the following restrictions: the production plans satisfy the environmental and resource conditions (4.2) and (4.3), that is x  E1 . the sum M invested in the fabrication plan is in the range M 1 , M 2 .

the expected return of the production plan is greater than a given value W. The model is the following:   n n  min   ij xi x j      i 1 j 1    f1 x     n  Eci   pi xi  W  i 1  n M 1  pi xi  M 2 , x  E1  i 1







Operations Research Methods in Production Management with Environmental… 153 Here W is the parameter that controls the expected return of the production plan and  is the parameter that controls monetarily the penalties paid for pollution.

4.2. A Maximum Expected Return Model In the maximum expected return problem the manager tries to maximize the expected net return taking into account the following restrictions: the production plans satisfy the environmental and resource conditions (4.2) and (4.3), that is x  E1 . the sum M invested in the fabrication plan is in the range M 1 , M 2 . the financial risk is smaller than a given value 

  n  max Eci   pi xi  f1 x    i 1   n n  (Q)   ij xi x j    i 1 j 1  n M  pi xi  M 2 , x  E1  1 i 1







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The problem (Q) is a single objective parametric programming problem.

4.3. Numerical Results In the following we shall analyze a numerical example for the minimum financial risk problem in discrete variables. Consider a textile firm. Its manager wants to find a fabrication plan for 12 types of products that will minimize the financial risk. The manager wants to control the amount of penalties paid for the pollution and the return. He wants to find a fabrication plan such that the sum of pollution penalties is lower than  =500 euros and the expected return is greater than W=300 euros. The manager agrees that the sum invested in the fabrication plan lies between 1800 euros and 3500 euros. We shall consider that the amount of the resources available for the production plan is sufficiently large. For water consider the following pollution indicators: In the second column of table 4.3. is displayed the vector p. Its components represent the production cost for products of types displayed in the first column. In our example the unit measure for the components of vector p are euros/meter. The third column contains the vector q, the vector of demand. The fourth column of table 4.3 contains the optimal fabrication plan that is the components of the decision vector x.

154

Marius Rădulescu, Constanta Zoie Rădulescu and Gheorghiţă Zbăganu Table 4.1. Pollution indicators

Nr. crt. 1 2 3 4

Pollution indicators CCO-Cr Suspended solid CBO5 Ammonia nitrogen (NH4)

Unit measure mg O2/l mg/l mg O2/l mg/l

Target level 175 74 40 1.2

Alarm level 350 210 210 21

Maximum admissible level 500 300 300 30

Table 4.2. The matrix (bij) of expected emission outputs Product

CCO-Cr

T01 T02 T03 T04 T05 T06 T07 T08 T09 T10 T11 T12

1 0.5 0.04 0.02 0.01 0.06 0.1 0.4 0.3 0.4 0.04 0.3

Suspended solid 0.02 0.01 0.03 0.06 0.03 0.1 0.1 0 0.1 0 0.03 0.1

CBO5 0.02 0 0.02 0.02 0.05 0.03 0.7 0.3 0.1 0.5 0.02 0.1

Ammonia nitrogen (NH4) 0 0.01 0.01 0.01 0 0.01 0.01 0.02 0.01 0 0.01 0.01

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Table 4.3. Vector of optimal fabrication plan versus vector of demand Product T01 T02 T03 T04 T05 T06 T07 T08 T09 T10 T11 T12

Vector p

Vector q

Optimal fabrication plan

3,70 3,30 3,90 1,50 5,40 2,80 2,50 5,40 7,50 2,70 1,90 3,50

15 25 45 15 20 55 55 37 25 15 12 10

79 27 100 15 100 55 55 37 25 15 12 10

.

Operations Research Methods in Production Management with Environmental… 155

5. FORMULATION OF A BINARY MULTIOBJECTIVE MODEL FOR CROP PLANNING IN AGRICULTURE The last decades witnessed an increasing interest in sustainable agriculture and a rapid progress in reaching it. Several environmental regulations were introduced in the Common Agricultural Policy (CAP) of European Union. As a result several agricultural subsidies were introduced and various development programs were implemented. The production quotas were introduced in the Common Agricultural Policy of the European Union in order to protect the environment, to prevent the exhaustion of agricultural resources and to ensure farmers a stable income. In the present paragraph we shall develop several crop planning models based on loss functions. These kinds of models are used when optimal production plans are desired and target production quotas are involved. Agricultural production under or above the quota targets receive penalizations, therefore it is discouraged. In the next subparagraph we present a brief introduction in the theory of loss functions. In the third subparagraph is formulated a 0-1 multiple objective programming model for crop planning under uncertainty in the presence of production quotas. It uses loss functions and several target production quotas. Starting from the multiple objective programming model, one formulates several single objective models. We analyze losses associated to the optimal production plans that try to comply to the target production quotas versus various parameters of the average loss minimization model.

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5.1. Loss Functions The notion of loss function occurs in various domains as: the theory of statistical decisions, the actuarial theory, learning theory, pattern recognition, time series, quality theory. The domains where loss functions apply include: economics, finance, engineering, health, agriculture and environment. In statistics a loss function represents the loss (cost in money or loss in utility in some other sense) associated with an estimate being "wrong" (different from either a desired or a true value) as a function of a measure of the degree of wrongness (generally the difference between the estimated value and the true or desired value.) The notion of loss function is complementary to the notion of utility function which suggests the benefit and satisfaction. If u is an utility function then k – u is the loss, where k is an arbitrary constant. The prediction of future events and their evolution is a very difficult task. The majority of methods for obtaining predictions are based on statistics and probability theory. Usually loss functions are used for obtaining predictions. When a performance criterion is defined one could study the problem of finding an optimal prediction. A prediction process postulates a probability distribution, defines a loss function, computes the prediction that minimizes the expected losses predicted by the probability model. Eventually some unknown parameters may be estimated. Both theory and practice connected to prediction making is more complicated than the sketch presented above.

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156

Marius Rădulescu, Constanta Zoie Rădulescu and Gheorghiţă Zbăganu

In practice there exist a great number of loss functions. Research workers that want to make predictions have a great problem when they want to choose the appropriate loss function. A method usually chosen for making predictions is based on results of previous predictions. Thus starting from a family of loss functions that depends on a multidimensional parameter one looks for the parameters of the loss function that is consistent with the past predictions. In applications often are used classical quadratic loss functions. The main reason for that this is that the theory for this class of functions is very well developed. Applications of quadratic loss functions may be found in quality theory. A quadratic loss function has been suggested by Taguchi in measuring the loss due to imperfect product quality (cost of acceptance). However there exist loss functions that are not quadratic. The theory of this class of functions was only partly developed. Under some circumstances overestimation could be penalized more than underestimations. These and other factors can be incorporated into the loss function. There is a great demand from the applicative domains for the development of theory of various classes of loss functions. An important class of loss functions is the class of unimodal loss functions. Some interesting studies about this class of functions may be found in (Zbaganu, 2006). Applications of loss functions to investments can be found in (Kulkarni and Prybutok, 2004). Some books that represent good references for the theory of loss functions are (Berger, 1993), (Clements and Hendry 1998), (Cameron and Trivedi, 2005), (Granger C.W.J. and Paul Newbold, 1977), (DeGroot, 2005). In the literature there are several approaches about loss functions. A general definition of loss functions is presented in the following. Let (E,E) be a measurable space. A loss function on E is any measurable function L : E²→ [0,∞] with the property that L(x,x) =0. We shall often denote Lx(y) the mapping y →L(x,y). Let (Ω,K, P) be a probability space and X : Ω→E be a random variable. Let h:E→ [0,∞] be defined by h X  y   EL X , y  , y  E . The optimal predictor of X defined by L is an element AL ( X )  E with the property that hX (AL (X))  hX (y) for every y E The following notation is usually: AL (X) = argmin hX . Under some hypotheses the number exists and it is unique (see (Zbaganu, 2006)). Another approach on loss functions, which we shall use in our paper is the following. Consider a family of random variables X   :   R ,    , and a loss function L : R 2  R  . We propose to solve the problem: min EL X λ , y  : λ  

Examples of loss functions: 1. Quadratic loss function: La ( s, t )  a t  s  , s, t  R . 2

2. Absolute loss function La ( s, t )  a t  s , s, t  R

Operations Research Methods in Production Management with Environmental… 157 3. Linlin loss function

  a s  t if s  t La ,b s, t      b s  t if t  s One can easily see that

L a , b s , t  

ab ba s  t  st  2 2

Here a,b are nonnegative parameters. 4. LINEX loss function

La s, t   exp as  t   as  t   1  Here where a is a known parameter and a  0. Exhaustive motivations to use the LINEX loss function are presented in (Varian, 1974) and (Zellner, 1986). These examples shows that loss function influences the choice of the predictor. Each predictor has its own interpretation. Quadratic loss function penalizes large deviations of the predictor t from ―true‖ value of the parameter. Absolute loss is more tolerant to large deviations.

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5.2. Crop Planning Models for Sustainable Agriculture In the following is formulated a 0-1 integer programming model with multiple objectives for crop planning in agriculture. The model takes into account weather risks and market risks. Input data include historical land productivities data for various crops and soil types. Some special cases of the model are discussed. Consider a farm which has an agricultural land divided into several plots. Let P1 , P2 ,..., Pm be the plots from the farm‘s land. We consider that if a plot is cultivated then it is cultivated with the same crop. Also we consider that the soil quality of a plot is homogeneous. Denote by S j the area of the plot Pj , j=1, 2,..., m. We consider that the farmer have a contract for delivery some fixed quantities of various crops. These quantities can be considered crop target quotas. Agricultural production under these quotas may be subject to contractual penalizations. Agricultural production over the quota targets can be sold by the farmers on the free market (local markets or international markets). Unfortunately on the free market does not exist minimum prices. We consider that the farmer have to choose a crop plan from n crops C1 , C 2 ,..., C n , that is to make an allocation of crops to plots.

Marius Rădulescu, Constanta Zoie Rădulescu and Gheorghiţă Zbăganu

158

Consider the probability space , K, P  . Denote I  1,2,..., n, J  1,2,..., m . For every

i  I , j  J we define the random variables cij :   R  and bi :   R  . c ij are called the plot productivity functions and bi are called the market price functions. cij represents the quantity of crop C i that can be produced on an area of one hectare of plot Pj and bi represent the market price for a quantity of one tone of crop C i . For every i  I , j  J , denote by: aij the cultivation cost for one ha of the plot Pj with crop C i

x ij - the decision variable that takes the value 1 if the crop C i is cultivated on plot Pj and takes value zero if the crop C i is not cultivated on the plot Pj .

M 1 , M 2  the range for the sum of money available for investment Q1i the target quota for crop C i (contractual level) Q2i the inferior bound for the expected yield of crop C i necessary to be obtained

The yield of crop C i obtained from the plot Pj when the land allocation decisions are

given by the matrix x  x ij , is

equal to x ij S j c ij . The yield of crop C i is equal to

m

 c  S j 1

ij

j

xij , i  I . The cultivation

cost when the land allocation x  x ij  of crops to plots is applied is equal to

n

m

 a i 1 j 1

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The restrictions

n

x i 1

ij

ij

S j xij .

 1 , j  J show that every plot is cultivated with at most one crop.

The return (respectively the expected return) obtained when the decision matrix x is used is n

m

equal to  , x   bi cij S j xij (respectively) i 1 j 1

For every i,   I , j ,   J , denote  ij

 Eb c S x .  E b c b c   E b c  E b c  . n

m

i 1 j 1

i ij

j

ij

i ij  

 

i ij

n

m

n

m

Then the variance of the return is equal to Var  , x    ij xij x S j S  . The i 1 j 1  1  1

variance of the return has the meaning of financial risk. The farmer intends to obtain optimal production plans that minimize the expected loss of the allocation minimize the financial risk maximize the expected return. Let Li , i  I be loss functions associated to crops. The overall expected loss for the

 

allocation x  x ij is equal to

Operations Research Methods in Production Management with Environmental… 159

  m  E  Li   cij  S j x ij , Q1i  .    j 1 According to the above requirements the multiobjective programming model for the crop planning is the following:   n   m   min  E  Li   c ij  S j x ij , Q1i     i 1   j 1    min Var  , x   n m  n m  max    E bi c ij S j x ij    a ij S j x ij     i 1 j 1  i 1 j 1  m   E c ij S j x ij  Q 2i , i  I  j 1 n m  M 1    a ij S j x ij  M 2 i 1 j 1  n  x ij  1, for every j  J ,  i 1  x  0,1, i  I , j  J  ij 

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Starting from the above multiobjective programming problem we formulate four single objective problems. The first one is the expected loss minimization model:     n   m  min  E  Li   c ij  S j x ij , Q1i        i 1   j 1       Var   , x    n m n m   E bi c ij S j x ij    a ij S j x ij  W  i 1 j 1 i 1 j 1 m   E c ij S j x ij  Q2i , i  I  j 1 n m  M 1    a ij S j x ij  M 2 i 1 j 1  n  x ij  1, for every j  J ,  i 1  x  0,1, i  I , j  J ij  

 

In the frame of this model the farmer wants to find an optimal allocation x  x ij that minimize the overall expected loss in the presence of the following restrictions:

Marius Rădulescu, Constanta Zoie Rădulescu and Gheorghiţă Zbăganu

160    

the financial risk is smaller than a given level  the expected net return is greater than a given level W the expected quantities of crops are greater than some given levels Q2i , i  I the total tillage cost is in the range M 1 , M 2  .

The user parameters of the model are:

 , W, M 1 , M 2 and the parameters of the loss

functions. Denote by V the set of all allocations

x  x ij 

that satisfy the following restrictions:

m  E cij S j x ij  Q2i , i  I  j 1 n m  M 1   a ij S j xij  M 2 i 1 j 1  n  x ij  1, for every j  J ,  i 1  x  0,1, i  I , j  J  ij

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The expected return maximization model is formulated as follows: n m  n m    max E b c S x    i ij j ij  aij S j xij  i 1 j 1  i 1 j 1   n  m    E  Li   cij  S j xij , Q1i     i 1   j 1   Var  , x    x V

The formulation of the financial risk minimization model is the following:

min Var  , x  n m  E  L  c  S x , Q     i   ij j ij 1i   i 1   j 1   n m n m  E bi cij S j xij   aij S j xij  W i 1 j 1  i 1 j 1 x V

Operations Research Methods in Production Management with Environmental… 161 The loss-return-risk tradeoff model is formulated as follows:

min  Var  , x   Lx   Rx  n m  E  L  c  S x , Q       i ij j ij 1i    i 1    j 1  n m n m   E bi cij S j xij   a ij S j xij  W i 1 j 1  i 1 j 1 x V where

 ,  ,  are nonnegative coefficients.

We

n   m  Lx   E  Li   cij  S j xij , Q1i  , i 1    j 1

denoted

Rx   E bi cij S j xij   aij S j xij n

m

n

i 1 j 1

m

.

i 1 j 1

5.3. Numerical Results In the following we shall study a numerical example for the expected loss minimization model. We shall consider a farmer that have contracts to deliver n=5 crops: C1 =wheat (W), C 2

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= barley (B), C 3 =corn (C), C 4 =soybean (S) and C 5 =sunflower (F). He wants to cultivate these crops on m=10 plots. We shall choose the loss functions Li to be of linlin type. Denote by  i the loss coefficient of Li when the quantity of crop C i is under the target quota Q1i . Denote by  i the loss coefficient of Li when the quantity of crop C i is over the target quota Q1i .   s  t if s  t Then one can write L s, t    i i    i s  t if t  s

In our numerical example we shall put

 1 =23 euro/tone,  2 =9 euro/tone,  3 =5

euro/tone,

 4 =8 euro/tone,  5 =7 euro/tone,  1 =27 euro/tone,  2 =15 euro/tone,  3 =10

euro/tone,

 4 =4 euro/tone,  5 =10 euro/tone.

The user parameters are:   

M

M

2 the budget limits 1 and the lower limit for the expected return (the number W) the upper limit for the financial risk (the number  )

Marius Rădulescu, Constanta Zoie Rădulescu and Gheorghiţă Zbăganu

162

Consider the following values for the user parameters

M 1  0 euro, M 2  30000 euros, W=10 euros,   10 10 euros2. The input data are represented by:

 



the matrix A  a ij of the cultivation costs



the three-dimensional matrix C  c ijt



data of land productivities for crops the matrix B  bit  whose entries are represented by the historical market prices



for crops the vector Q1  Q1i  of the target quotas for crops (contractual levels)

  whose entries are represented by historical



the vector Q 2  Q2i  of the inferior bounds for the expected yield of crops



the vector S of areas of plots

The crop quotas in tone are presented in the table below. The surfaces of plots are S 1 =9.5 ha, S 2 =15.5 ha, S 3 =12.4 ha, S 4 =11.9 ha, S 5 =10.2 ha, S 6 =9.5 ha, S 7 =13.1 ha, S 8 =12.7 ha, S 9 =10.4 ha, S 10 =14.2 ha.

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The decision variable is the allocation matrix x  xij  whose entries are 0 and 1.

Starting from the input data we compute the sample variance of the return and the sample mean for the overall loss and for the crops quantities. We construct a dual model of the initial model in which variances and means are replaced with sample variances and sample means. Starting from historical data we made computer simulations with GAMS for various subperiods of the period 1990-2005. Table 5.2 contains simulation results for these. In the column optimal value are displayed the optimal values of expected loss for the corresponding periods. Table 5.1. Crop quotas Crop

Q1i

Q 2i

Wheat

63

60

Corn

46

40

Barley

62

60

Soybean

32

30

Sunflower

30

30

Operations Research Methods in Production Management with Environmental… 163 Table 5.2. Simulation results for various periods Period 2000-2005 1999-2005 1998-2005 1997-2005 1996-2005 1995-2005 1994-2005 1993-2005 1992-2005 1991-2005 1990-2005

Opt.. value 685,51 625,47 608,48 685,51 575,98 1013,1 539,35 554,75 813,47 1002,8 574,39

1

2

3

4

5

6

7

F F

B B B F B C B B F

W W W C W S W W S F

W W W F W

C C S W C W C

F F F S S

S S C S S F S S W W W

W F C F F B W W

W W B B S

C C C

S F W S F

8

S F S C S B S

9

10

S S F B F W

B

F S B

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6. CONCLUSION Currently industrial firms are facing several challenges: market competition, continuous trend of increasing pollution charges, resources conservation fees etc. The purpose of the present chapter is to present various strategies based on portfolio theory and loss function theory that are intended for prevention of pollution and the exhaustion of natural resources. The chapter presents several production planning models under uncertainty that take into account both the economic and environmental problems. The models can be considered pollution prevention models. The production planning problems are multiobjective programming problems. The models presented in third and fourth paragraphs are based on portfolio theory. Here the portfolios are represented by sustainable production plans and environmental constraints are represented by several pollution levels. Applications of the models are made to the optimization of a production planning in a textile plant. The fifth paragraph contains a multiobjective model for crop planning in the presence of crop target quotas. Crop quotas can be motivated by contractual levels or by environmental constraints. They contribute to the prevention of the exhaustion of agricultural resources. The multiobjective model for crop planning is based on portfolio theory and on loss function theory. Here portfolios are represented by crop plans. In all above mentioned models ranges of the user parameters are determined. This facilitates the integration of our optimization models in environmental management decision support systems.

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Operations Research Methods in Production Management with Environmental… 165 [22] Penkuhn, T., Spengler, Th., Püchert, H. & Rentz, O. (1997). Environmental integrated production planning for the ammonia synthesis, European Journal of Operational Research, 97(2), 327-336. [23] Qiu, Z., Prato, T. & McCamley, F. (2001). Evaluating environmental risks using safetyfirst constraints. American J. of Agricultural Economics, 83, 402-413. [24] Rădulescu, M., Rădulescu, S. & Rădulescu, C. Z. (2006). Optimal production planning in a firm subject to environmental constraints, Proc. 5th MATHMOD Vienna, (I. Troch, F. Breitenecker, eds.), Discrete Modelling and Planning, 70, 4.1 -4.9. ISBN 3-90160830-3. [25] Rădulescu, M. & Rădulescu, C. Z. (2006). A model for agricultural production planning which includes weather risks, market risks and environmental risks, in vol. 2, ―Research Excellence - favorable prerequisite for the development of the Romanian space research‖, Braşov 2006, 1.4-27, pg. 1-8. 2006. Editura Printech. ISBN 973-718552-8, ISBN 973-718-553-6. [26] Rădulescu, M. & Rădulescu, C. Z. (2007). ―Decision Support Tools For A Sustainable Agriculture‖, Proc. EFITA 2007, (Conference and the World Congress on Computers in Agriculture) "Environmental and rural sustainability through ICT‖, Editor C. Parker, Glasgow Caledonian University, CDROM pg. 1-6, Glasgow, Great Britain, 2007. ISBN-10:1-905866-10-0, ISBN-13: 978-1-905866-10-6, http:// www. efita. net/ apps/ accesbase/dbsommaire [27] Rădulescu, M. & Rădulescu, C. Z. (2007). ―Crop planning under risk and environmental constraints‖, Proc. 6th EUROSIM Congress on Modelling and Simulation, Editors: B., Zupancic, R. Karba, & S. Blazic, pg. 334, vol. 2, CDROM pg. 1-6, Ljubljana, Slovenia, 2007. ISBN 13: 978-3-901608-32-2. [28] Rădulescu, M. & Rădulescu, C. Z. (2007). A multiobjective programming model for production planning under environmental constraints Proc. IFAC/IEEE 4th Conference on management and control of production and logistics, MCPL 2007, Editors: O., Bologa, I. Dumitrache, & F. G. Filip, pg. 771-776, Sibiu, Romania, 2007. ISBN 978973-739-481-1. [29] Rădulescu, M. & Rădulescu, C. Z. (2007). Optimal decisions for crop planning under risk, Conference Excellence Research-a way to E.R.A., Brasov, Editors: Nicolae Vasiliu and Lanyi Szabolcs, Editura Tehnică, pg. 28.1-28.6., ISSN 1843-5904. [30] Rădulescu, M. & Rădulescu, C. Z. (2008). Discrete models for production planning under environmental constraints, Proc. 12th WSEAS International Conference on COMPUTERS, Heraklion, Greece, (2008), pg. 1091-1096. WSEAS Press. ISSN: 17905109, ISBN: 978-960-6766-85-5. [31] Rădulescu, C. Z. & Rădulescu, M. (2008). A multidimensional data model for environment protection, Proc. 12th WSEAS International Conference on COMPUTERS, Heraklion, Greece, 2008, (2008), pg. 1101-1106. WSEAS Press. ISSN: 1790-5109, ISBN: 978-960-6766-85-5. [32] Rădulescu, M., Rădulescu, C. Z. & Filip, F. (2008). Sustainable production planning models, Proc. Romanian Academy, vol. 9, no. 2, 149-156. [33] Rădulescu, M., Rădulescu, C. Z. & Zbaganu, G. h. (2008). Crop Planning in the Presence of Production Quotas (Invited Paper), Editors: A. David Al-Dabass, Orsoni, Proc. Tenth International Conference on Computer Modeling and Simulation (uksim

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Marius Rădulescu, Constanta Zoie Rădulescu and Gheorghiţă Zbăganu 2008), 549-554, ISBN 0-7695-3114-8, http: //doi. ieeecomputersociety. org/ 10. 1109/UKSIM.2008.40 Rădulescu, M., Rădulescu, S. & Rădulescu, C. Z. (2009). Sustainable production technologies which take into account environmental constraints, European Journal of Operational Research, vol. 193, no. 3, 730-740. Reiborn, C. A., Joyner, B. E. & Logan, J. W. (1990). ISO 1400 and the bottom line. Quality Progress, 11, 89-93. ReVelle, C. (2000). Research challenges in environmental management. European Journal of Operational Research, 121, 218-231. Sahinidis, N. V. (2004). Optimization under uncertainty: state-of-the-art and opportunities, Computers & Chemical Engineering, 28, 971-983. Steven, M. & Letmathe, P. (1996). Umweltstücklisten als Datengrundlage für umweltorientierte PPS – systeme. In: Albach, Dyckhoff (Eds.), Betriebliches Umweltmanagement (ZfB – Ergänzungsheft 2/96), Gabler: Wiesbaden, 165-183. Ulhoi, J. P. (1995). Corporate environmental and resource management: In search of a new managerial paradigm. European Journal of Operational Research, 80, 2-5. Varian, H. R. (1974). A Bayesian approach to real estate assessment, in: Studies in Bayesian Econometrics and Statistics, edited by A. Zellner, & J. B. Kadane, NorthHolland, 195-208. Wirl, F. (1991). Evaluation of management strategies under environmental constraints. European Journal of Operational Research, 55, 191-200. Wirl, F., Infanger, G. & Unterwurzacher, E. (1987). Planning of production under environmental constraints. Engineering costs and production economics, 12, 299-305. Wu, C. C. & Chang, N. B. (2003). Global strategy for optimizing textile dyeing manufacturing process via GA-based grey nonlinear integer programming. Computers & Chemical Engineering, 27, 833-854. Wu, C. C. & Chang, N. B. (2004). Corporate optimal production planning with varying environmental costs: A grey compromise programming approach, European Journal of Operational Research, 155, 68-95. Zbaganu, G. h. (2006). Loss functions, lottery evaluation and premium principles, Math. Reports, Bucharest. 8(58), No. 3, 343-383. Zellner, A. (1986). Bayesian estimation and prediction using asymmetric loss functions, J. Amer. Statist. Assoc, 81, 446-451.

In: Environmental Planning Editor: Rebecca D. Newton

ISBN: 978-1-61728-654-4 © 2011 Nova Science Publishers, Inc.

Chapter 6

POLICY ANALYTICAL CAPACITY IN THE ENVIRONMENTAL SECTOR: SURVEY RESULTS FROM CANADA Michael Howlett12 and Sima Joshi-Koop2 1

Lee Kuan Yew School of Public Policy National University of Singapore 469C Bukit Timah Road Singapore 259772 2 Department of Political Science Simon Fraser University Burnaby BC Canada V5A 1S6

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INTRODUCTION Governments and increasingly, non-governmental actors in Canada and elsewhere are being asked to design effective long-term policy measures for climate change adaptation and mitigation. Whether they have the necessary kinds of resources to successfully do so, through the use of enhanced evidence-based analytical techniques, remains unknown. This is due in large part because work on the behaviour and behavioural characteristics of in-house policy analysts in supplying advice to government, let alone those working outside it, is exceedingly rare (Nelson 1989; Aberbach and Roclanan 1989; Wollmann 1989; Thompson and Yessian 1992; Radin 1992; Boston et al. 1996; Bushnell 1991; Binz-Scharf et al. 2008). In most countries empirical data on almost every aspect of policy analysis in government are lacking (Dunn 2004; Patton and Sawicki 1993; MacRae and Whittington 1997). This is despite the common assertion made by policy scholars that governance regimes are often to blame when resource management fails (Pahl-Wostl 2009). Given the significance of public sector analysts in the policy advice system of government, studies of their activities, behaviour, and impact are required if our understanding of policy capacity for climate change mitigation and adaptation is to be informed. As Beem (2009: 498) has written, ―government officials can help define, frame, implement, and enforce new conceptualizations of what is good and/or appropriate policy.‖ And their potential influence over public policy is not limited to the domestic realm either: through their framing of domestic policy and

168

Michael Howlett and Sima Joshi-Koop

interaction with other governments and non-governmental actors, public policy bureaucracies can affect the expectations of other jurisdictions and can help cultivate a policy discourse subsequently informing policy development and implementation elsewhere (Beem 2009). Because civil servants are crucial policy actors when it comes to designing and implementing systems to respond to climate change, it is important that we understand what they do and how they do it. Here, we will investigate education levels and training, day-today policy activities, sources and types of information collected and use of analytical tools and methods to determine the policy analytical capacity of sub-national governments in Canada on environmental policy issues. The first section of this chapter will introduce the concept of evidence-based decision-making and its importance to environmental policy capacity, before turning to the results of a national survey of Canadian provincial environmental policy analysts.

EVIDENCE-BASED DECISION MAKING AND ENVIRONMENTAL POLICY CAPACITY

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Governments in Canada have moved beyond climate change mitigation efforts to those dealing with climate change adaptation. That is, they have moved from proposing only incremental changes to the status quo to attempting to grapple with the major socio-economic, political and technological challenges and changes required to adapt to a new post-global warming environment. Adapting to climate change in Canada requires Canadian governments to have the capacity to design and implement policies capable of dealing with long-term problems. Policy capacity can be understood as: a loose concept which covers the whole gamut of issues associated with the government‘s arrangements to review, formulate and implement policies within its jurisdiction. It obviously includes the nature and quality of the resources available for these purposes – whether in the public service or beyond – and the practices and procedures by which these resources are mobilized and used (Fellegi 1996: 6).

While governments seek to develop high policy capacity across a variety of policy areas, climate change adaptation poses significant additional policy design and implementation challenges, since policies must be multi-level and multi-sectoral in nature given the crosssectoral and international character of climate change issues. Responsive policy-making on climate change issues thus requires both sophisticated policy analysis as well as an institutional structure which allows problems to be dealt with on a multi-level and multisectoral basis (Howlett and Rayner 2006; Weber et al 2007). In this context, evidence based or ―evidence-informed‖ policy-making represents a recent effort on the part of government (Nutley, Walter, and Davies 2007; Pawson 2006; Sanderson 2006) to bolster policy capacity and enhance the possibility of policy success by improving the amount and type of information processed in public policy decision-making, as well as the methods used in its assessment (Morgan and Henrion 1990; Nilsson et al. 2008). It is expected that enhancing the information basis of policy decisions will improve the results

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Policy Analytical Capacity in the Environmental Sector: Survey Results… 169 flowing from their implementation, while iterative monitoring and evaluation of results in the field will allow errors to be caught and corrected. Through a process of theoretically informed empirical analysis, governments can better learn from experience and both avoid repeating the errors of the past as well as better apply new techniques to the resolution of old and new problems (Sanderson 2000; May 1992; Bennett and Howlett 1992; March 1981, 1994). Simply put, it is argued that the more relevant, usable information decision makers have their disposal, the better the decisions they will make. In order to make decisions based on evidence however, policy actors, particularly government actors, need to have the analytical capability to collect appropriate data and make it useable in the course of policy-making activities. While policy capacity can be thought of as extending beyond analysis to include the actual administrative capacity of a government to undertake the day-to-day activities involved in policy implementation (Painter and Pierre 2005; Peters 1996), policy analytical capacity is a more focused concept related to knowledge acquisition and utilization in policy processes (Adams 2004; Leeuw 1991; Lynn 1978; MacRae 1991; Radaelli 1995). It refers to the amount of basic research a government can conduct or access, its ability to apply statistical methods, applied research methods, and advanced modelling techniques to this data and employ analytical techniques such as environmental scanning, trends analysis, and forecasting methods in order to gauge broad public opinion and attitudes, as well as those of interest groups and other major policy players, and to anticipate future policy impacts (O‘Connor, Roos, and Vickers-Willis 2007; Preskill and Boyle 2008). It also involves the ability to communicate policy-related messages to interested parties and stakeholders and includes ―a department‘s capacity to articulate its medium- and long- term priorities‖ (Fellegi 1996: 19) and to integrate information into the decision-making stage of the policy process.1 As such, a significant factor affecting the ability of policy-makers to engage at all in evidence-based policy-making pertains to the level of both governmental and nongovernmental actors‘ policy analytical capacity. Enhancing policy analytical capacity is an essential precondition for the adoption of evidence-based policy-making and through its application, the improvement of policy outcomes, a point often ignored or downplayed in the literature on the subject. The policy functions outlined in Table 1 call for either a highly trained, and hence expensive, workforce that has far-seeing and future-oriented management and excellent information collection and data processing capacities, as well as the opportunity for employees to strengthen their skills and expertise (O‘Connor, Roos, and Vickers-Willis 2007) or the ability to outsource policy research to similarly qualified personnel in private or semipublic organizations such as universities, think tanks, research institutes and consultancies (Boston 1994). It also requires sufficient vertical and horizontal coordination between participating organizations to ensure that research being undertaken is relevant and timely. ―Boundary-spanning‖ links between governmental and non-governmental organizations are also critical (Weible 2008). As George Anderson has noted, ―a healthy policy-research community outside government can play a vital role in enriching public understanding and 1

The willingness of policy-makers to use the information generated in the way it was intended to be used, of course, is not always present. On the ‗‗strategic‘‘ and ‗‗argumentative‘‘ versus ‗‗evaluative‘‘ uses of research and analysis, see D. Whiteman (1985) and R. Landry, M. Lamari, and N. Amara (2003).

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debate of policy issues, and it serves as a natural complement to policy capacity within government‖ (1996: 486). In sum, if evidence-based policy-making is to be achieved, policy actors require the ability to collect and aggregate information in order to effectively develop medium- and longterm projections, proposals for, and evaluations of future government activities. Organizations both inside and outside of governments thus require a level of human, financial, network and knowledge resources enabling them to perform the tasks associated with managing and implementing an evidence-based policy process. Without this they might only marshal these resources in particular areas, resulting in a ―lumpy‖ set of departmental or agency competences in which some agencies are able to plan and prioritize over the long-term while others focus on shorter-term issues or, if evenly distributed, may only be able to react to short- or medium- term political, economic or other challenges and imperatives occurring in their policy environments (Voyer 2007). Whether or not, and to what degree, government and non-governmental policy actors in a policy analytical community have the capacity to actually fulfil these tasks remains an important and largely unanswered empirical question in the study of evidence-based policymaking in many sectors, including that of the enviroment (Turnpenny et al. 2008; Wollmann 1989). Studies of the actual behaviour and job performance of policy analysts, for example, have constantly challenged the view often put forward in academic texts that policy analysis is all about the neutral, competent and objective performance of tasks associated with the application and use of a small suite of technical policy analytical tools on the part of governmental or non-governmentally based analysts (Boardman et al. 2001; Boston 1994; Durning and Osama 1994; Patton and Sawicki 1993). This raises to the fore the questions What do environmental policy analysts actually do in government? Are their training and resources appropriate to allow them to meet contemporary governance challenges such as designing effective policies for climate change adaptation?

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Table 1. Aspects of political analytical capacity Components Environmental scanning, trends analysis and forecasting methods Theoretical research Statistics, applied research and modeling Evaluation of the means of meeting targets/goals Consultation and managing relations Program design, implementation monitoring and evaluation Department‘s capacity to articulate its medium and long term priorities Policy analytical resources - Quantity and quality of employees; annual departmental reports; budgets

Policy Analytical Capacity in the Environmental Sector: Survey Results… 171

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METHODS Canadian studies of policy analysts have traditionally focused almost exclusively at the federal level (Voyer 2007; Prince 1979; Prince and Chenier 1980; Hollander and Prince 1993) despite the fact that the provinces control many important areas of social, economic, and political life including most resource and environmental portfolios. This situation only began to change in 2006-2007 with studies of non-governmental policy analysts (Dobuzinskis Howlett and Laycock 2007) and of regional and central policy analysts employed in the federal civil service (Wellstead, et al, 2007). Given Canada's decentralized federal system of government however, approximately half of the more than ten thousand bureaucratic policy analysts employed in the country are working at the sub-national level in the civil services of the ten provinces and three territories. Information on analytical activities and the supply of policy advice remains extremely rudimentary at this level, generally collected from personal reflections and anecdotes of former analysts and managers, or from a small number of single-province interviews or surveys (McArthur 2007; Rasmussen 1999; Singleton 2001; Hicks and Watson 2007; Policy Excellence Initiative 2007). To address this gap, a survey of policy analysts employed by provincial civil services was carried out in November and December of 2008 using an online commercial software service. It involved the completion of a 64-item questionnaire by more than 1,200 provincial and territorial civil servants situated in seven jurisdictions. Mailing lists for the survey were compiled wherever possible from publicly available sources such as online government telephone directories, using keyword searches for terms such as "policy analyst" appearing in job titles or descriptions. In some cases additional names were added to lists from hard-copy sources such as government organization manuals. In other cases lists or additional names were provided by provincial public service commissions, who also checked initial lists for completeness and accuracy. From 2,846 valid email addresses in seven jurisdictions, 1,258 valid survey completions were gathered for a total response rate of 44.2%. The data collected from the survey allowed the first profile of Canadian provincial public servants to be constructed and from within that profile, the profiles of particular policy sectors to be drawn. Here we focus on the experience of the 203 policy analysts who work predominantly on environmental policy issues. Evaluated against analysts in five other policy sectors (health, social welfare, education, industry/trade, and finance), we can assess both the absolute and relative analytical capacities of Canadian sub-national governments on environmental policy issues. Data were divided into five topic areas: Demographic Characteristics and Job Experience; Education and Training; Day-to-Day Duties; and Techniques and Data Employed. Combined, these provide the basis for the first large-scale empirical analysis of the background and activities of sub-national government policy analysts.

WHO ARE PROVINCIAL ENVIRONMENTAL POLICY ANALYSTS? Basic demographic data were collected on provincial environmental policy analysts in terms of characteristics such as gender and age. The responses revealed that general

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provincial analysts are predominantly (58.4%) female, and fairly young, 70% being under 50 years of age. Environmental policy analysts are even younger than non-environmental policy analysts; nearly half (47.9%) being under 40 years of age. Additional questions revealed that provincial environmental policy analysts also tend to have come to their present career path and positions fairly recently. Over 40% of provincial analysts being involved in professional policy analytical activities for five years or less (Table 1). Over 55% had also been in their present organizations for less than five years, including 15% for less than one year. This contrasts sharply with the federal situation described by Wellstead et al. (2007) where a majority of analysts are male and a sizable number have been in their positions for over 20 years. These analysts also do not expect to stay very long in their current positions, with more than half expecting to stay less than five additional years. This pattern accords closely with Meltsner's (1975) observation that the typical policy analyst believes he or she is upwardly mobile and "believes he (sic) is a short-timer, so he does not worry about maintaining the agency or conserving its jurisdiction" (p. 117), and instead is able to be more "problemfocused" in orientation and approach. Table 2. Length of time, environmental policy analysts

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Employed as a professional policy analyst Frequency Percent Valid 00-01 years 01-05 years 05-09 years 10-14 years 15-19 years 20 or more Total

14 73 39 18 22 28 194

Employed in present organization

Expected to remain in present position

Frequency

Percent

Frequency

Percent

30 80 24 13 20 28 195

15.4 41.0 12.3 6.7 10.3 14.4 100.0

20 93 33 26 8 11 191

10.5 48.7 17.3 13.6 4.2 5.8 100.0

7.2 37.6 20.1 9.3 11.3 14.4 100.0

Table 3. Education, environmental policy analysts

Valid High School College or Technical University Graduate or Professional Total

Frequency

Percent

1 19 67 107 195

1.0 9.7 34.3 54.9 100.0

Policy Analytical Capacity in the Environmental Sector: Survey Results… 173

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Table 4. Degree subject area, environmental policy analysts

Environmental Studies Natural Sciences Geography Natural Resource Management Planning Political Science Public Administration Economics Public Policy Business Management Engineering Law Other Social Sciences History Humanities or Fine Arts English Education Sociology Computer Science Languages or Linguistics Communications or Journalism Medicine Other Health Sciences Other Arts or Humanities Total

N 72 50 39 33 23 22 14 13 13 12 10 10 10 9 7 5 3 3 2 2 2 1 1 0 356

Percent 20.2 14.0 11.0 9.3 6.5 6.2 3.9 3.7 3.7 3.4 2.8 2.8 2.8 2.5 2.0 1.4 0.8 0.8 0.6 0.6 0.6 0.3 0.3 0.0 100.0

A second set of questions examined the background education and training of provincial environmental policy analysts. Table 3 highlights the generally very high level of formal education attained by environmental policy analysts in provincial governments: 54.9% having had some graduate or professional education and 89.2% holding a university degree. Provincial environmental policy analysts‘ study area of expertise were quite varied, as indicated in Table 4. The five leading degree fields were environmental studies, natural sciences, geography, natural resource management, and planning, which together account for 61% of degrees held by environmental policy analysts. The next five most prevalent degrees boast a policy, research, or management orientation (political science, public administration, economics, public policy, and business management) and together accounted for another 20.9% of degrees. As for previous work experience, provincial environmental policy analysts have varied backgrounds but tend to be recruited from within the provincial government (28%), the notfor-profit sector (16%), or academia (13%). 11% claim experience in the federal government, 6% in other provincial governments, and just 5% in foreign governments (see Table 4). Compared with analysts across other sectors, environmental policy analysts have less

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experience outside of government and less experience in foreign governments (see Howlett 2009). Table 5. Previous work experience, environmental policy analysts

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Academia Municipal government department or agency Aboriginal government Non-for-profit sector Private sector Other provincial government department or agency in your current province Department or agency in another provincial government Federal government Department or agency in another country Total

N 42 33 1 54 39 91

Percent 12.7 10.0 0.3 16.4 11.8 27.6

18 37 15 330

5.5 11.2 4.5 100.0

While provincial environmental policy analysts possess diverse work experience and high academic credentials, it is not clear if this experience has adequately prepared them to conduct evidence-based decision-making. In particular, provincial environmental policy analysts have had little training in formal policy analysis, in terms of both post-secondary education coursework and post-employment training. As Table 6 shows, 41% of analysts have never taken a policy-specific course at the post-secondary level and 68% have taken two or fewer policy-related courses. Moreover, 65% of analysts have never completed a postsecondary course specifically dealing with formal policy analysis or evaluation (see Table 7) and more than half of provincial analysts (52%) have never completed any formal professional training on these subjects (see Table 8). Finally, as Table 9 reveals, the most common form of post-employment training is attendance at policy-related conferences, workshops, or forums, typically passive forums for learning. Only 10% of provincial analysts cited completion of policy courses with government-run or sponsored training institutes. Table 6. Environmental policy analysts, number of post-secondary policy courses completed

Valid 0 1 2 3+ Total

Frequency

Percent

Cumulative Percent

77 21 30 61 189

40.7 11.1 15.9 32.3 100.0

40.7 51.9 67.7 100.00

Policy Analytical Capacity in the Environmental Sector: Survey Results… 175 Table 7. Environmental Policy Analysts, Completion of Post-Secondary Policy Analysis Courses. Frequency Valid No Yes Total

124 67 191

Percent 64.9 35.1 100.0

Table 8. Environmental policy analysts, completion of formal internal training courses

Valid No Yes Total

Frequency

Percent

100 91 191

52.4 47.6 100.0

Table 9. Environmental policy analysts, sources of post-employment training

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Attended policy related conferences Attended policy workshops or forums Completed public administration, political science, economics or other policy-relevant courses at a university or college Completed policy courses with the Canada School of Public Service or any other government-run or government-sponsored training institute Total

N 130 155

Percent 66.7 79.5

46

23.6

20

10.3

195

100.0

POLICY ANALYTICAL CAPACITY IN PRACTICE How does Canada shape up with regard to environmental policy analytical capacity? In this section, we seek to assess the extent to which provincial environmental policy analysts explicitly engage in evidence-based policymaking. The survey results present a picture of a somewhat ―lumpy‖ or uneven distribution of policy analytical capacity, supporting previous anecdotal results (Bakvis 2000; Dobuzinskis, Howlett, and Laycock 2007). That is, policy capacity, as perceived by provincial policy analysts varies markedly by sector, with high policy capacity being reported by only 29.4% of analysts in the health sector compared with 51.1% of analysts in the finance sector, usually considered to possess the highest capacity given its subject matter and access to analytical resources within government (see Table 10). Table 10 reveals that 48% of environmental policy analysts report high departmental policy capacity. While this may speak favourably of analytical capacity in the sector vis-à-vis others, several caveats are worth mentioning. First, the spread of responses on this survey question suggest strong variability within the sector itself. While environmental analysts are

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second most likely to cite strong departmental capacity, they are also the second most likely sector to cite weak departmental capacity (21%). Two, in absolute terms, more than half of environmental policy analysts do not rate their department‘s capacity to address policy issues positively. Three, while environmental departments may have strong internal capacity, on issues that cut across organizational boundaries, like climate change, it is the capacity of government as a whole that is of prime importance. When policy capacity is examined at this governmental level (rather than departmental level) and over time, as in Table 11, it is no longer clear that environmental analysts enjoy high organizational capacity vis-à-vis peers in other sectors. Here we posit that the variability of departmental capacity as well as the challenges of horizontal coordination, lead to an overall diminished capacity to address environmental issues compared with other policy issues. Indeed, in Table 11, analysts in the environmental sector are most likely to state that the policy capacity of the government has been declining, followed by analysts in trade, education, and social welfare. Table 12 also clarifies that 33% of respondents from the environmental sector believe that much of the existing policy capacity exists outside of government, compared with 25% of respondents from all other sectors.

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Table 10. Department Policy Capacity, by sector

Sector Environment Social Welfare Health Education Trade Finance Total

Policy-making capacity rating of one‘s department or agency, by % of respondents Low Moderate High 21.4 31.0 47.7 19.2 34.9 45.9 25.3 45.2 29.4 19.3 40.4 40.3 17.5 43.8 36.9 11.5 37.5 51.1 19.8 37.9 42.2

Table 11. Government Policy Capacity by Sector

Sector Environment Social Welfare Health Education Trade Finance Average

Responses to the statement that ―there seems to be less governmental capacity to analyze policy options than there used to be‖ Percent who Percent who disagree agree 15.6 48.2 21.1 43.2 20.5 37.7 23.4 43.3 22.2 47.8 28.3 33.3 21.0 43.0

Policy Analytical Capacity in the Environmental Sector: Survey Results… 177 Table 12. Policy Capacity outside Government

Environmental Policy Analysts Non-Environmental Policy Analysts Total

Much of the existing policy capacity is outside the formal structures of government Disagree Neutral Agree 29.6% 37.8% 32.6% 39.5% 35.5% 25.0% 38.4% 35.8% 25.9%

This is not surprising given that the policy issues that environmental policy analysts deal with appear to be more complex than in other sectors. Displayed in Table 13, environmental policy analysts are more likely than their non-environmental counterparts to deal with issues that necessitate long term thinking, require significant technical expertise and interorganizational coordination, operate at a national or international level, and lack clear, simple solutions. Further, 54% of analysts in the environmental sector work on a weekly basis on issues for which data is also not immediately available. Table 13. Nature of Issues Dealt with on a Weekly Basis

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... for which data is not immediately available Environment Health Social Development Education Industry and Trade Finance Total

54.1 50.2 55.8

Percentage of respondents who weekly deal with issues ... ... that require .... that require ... that lack a ... that require coordination coordination single, clear, specialist or across regions with other simple technical levels of solution knowledge government 44.0 33.7 66.7 69.0 32.5 16.6 63.3 41.2 40.0 24.9 63.0 52.1

45.8 58.3

22.3 27.2

17.6 29.0

47.1 62.6

37.4 59.9

49.5 52.6

17.3 32.5

20.9 24.1

59.2 61.6

61.9 61.9

Table 14. Prevalence of Networks

Environment Social Welfare Health Education Industry and Trade Finance Total

Respondents who agree that their policy-related work increasingly involves networks of people N Percent 135 71.5 121 57.9 95 67.4 61 57.5 85 67.0 53 58.9 550 63.8

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The supply of external knowledge and expertise to meet this enhanced demand is also generally low, if we take policy analysts networking behaviour as a cue. Table 14 shows that on the one hand, environmental policy analysts are most likely of all analysts to engage in networking, with 72% of environment policy analysts agreeing that their policy related work increasingly involves networks of people. Table 15. Types of evidence used in policy work, by sector

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Scientific findings Professional advice Information from other governments Personal experience Government platforms Consultants reports Academic research Industry-provided information Non-governmental organization-provided information Budget and cost data Personal opinion Evaluation results Think-tank findings Survey data

Percent of respondents who frequently use type of evidence Environmental NonPolicy environmental Analysts policy analysts 47.7 34.8 47.1 41.8 45.2 49.3 44.8 41.5 43.7 25.6 38.8 39.1 38.5 45.7 33.1 35.4 26.3 31.6 23.9 23.9 19.4 15.7 12.2

33.8 18.1 23.9 23.6 19.8

Table 16. Use of evidence informed methods (EIM), by sector

Environment Welfare Health Education Trade Finance

Percent of respondents who ―often‖ or ―always‖ feel... ...evidence ...they can ...encouraged ...required ...provided informs access by managers to use EIM with support decisioninformation to use EIM in in policy and making and data policy work work resources to relevant to use EIMs in their policy policy work work 33.0 32.6 28.0 33.0 10.2 52.4 31.7 48.3 52.4 22.9 60.0 48.2 54.0 60.0 31.7 51.4 44.9 49.5 51.4 30.7 42.9 37.7 37.8 42.9 16.8 43.2 38.7 36.3 43.2 25.0

Policy Analytical Capacity in the Environmental Sector: Survey Results… 179 We can also see from Table 16, however, that environmental policy analysts are more likely to use scientific findings, professional advice, advice from other governments, and government platforms in their work than analysts in other sectors. However, they are less likely to rely on survey data, think-tank findings, evaluation results, budget and cost data, and evidence from NGOs, industry groups, and academia. To the extent that environmental policy issues are typically complex, demanding sophisticated knowledge and expertise and high levels of collaboration and coordination across groups in society, the underuse of evidence from non-state actors may be undermining policy analytical capacity in this sector. Table 17 further reveals that support for, and prevalence of, evidence-informed policy research and development is strongest in the health sector and weakest in the environmental sector. Environment policy analysts are the least likely to use an evidence-informed method or feel that evidence is used to inform decision-making processes. The difference across sectors is significant. Whereas 33% of analysts in the environmental sector report frequent use of evidence-based methods, 60% of analysts in health, 52% of analysts in social welfare and 51% of analysts in education report frequent use of evidence-based methods. Only 10% of environment policy analysts are routinely provided with the appropriate resources to implement evidence-based methods, a figure that is almost three times less than peers in the health and education sectors.

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Table 17. Types of policy analytical techniques used in policy work, by sector

Brainstorming Consultation Check lists Risk analysis Expert judgements Scenario analysis Cost-benefit analysis Environmental impact assessment Focus Groups Cost-effectiveness analysis Probability trees Problem-mapping Financial impact analysis Robustness or sensitivity analysis Sophisticated modelling Social network diagrams Free-form gaming Preference scaling Monte Carlo techniques

Environment 89.7 77.3 66.5 63.1 58.6 54.2 53.2 49.8

Welfare 85.7 71.3 62.6 60.4 42.4 51.3 58.7 29.6

Health 90.3 74.0 60.4 63.0 53.9 53.9 51.9 28.6

Education 85.8 75.8 58.3 51.7 42.5 51.7 51.7 18.3

Trade 87.2 69.9 62.4 63.9 60.2 60.2 61.7 24.1

Finance 80.0 62.0 57.0 71.0 46.0 59.0 63.0 21.0

43.3 36.5

48.3 46.5

38.3 49.4

44.2 40.0

30.1 39.1

29.0 52.0

36.0 30.0 29.1

20.0 35.2 41.7

29.2 31.8 40.9

10.8 24.3 39.2

28.6 33.1 42.9

30.0 26.0 71.0

16.7

11.3

11.7

17.5

24.8

27.0

11.3 10.8

10.4 6.1

11.0 10.4

15.0 8.3

17.3 9.8

19.0 4.0

8.4 6.9 3.0

5.2 6.1 0.4

5.8 10.4 1.3

3.3 7.5 2.5

6.8 7.0 2.3

5.0 7.3 4.0

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Michael Howlett and Sima Joshi-Koop Table 18. Scope of Policy Issues

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Environment Welfare Health Education Trade Finance Total

% of respondents who deal with type of issue weekly Immediate Short- Medium- LongOn-going & Urgent term term term 62.1 53.8 47.7 51.0 51.9 68.2 62.3 49.1 41.3 39.4 66 57.5 57.0 54.4 48.0 68.5 63.0 42.5 42.6 38.0 73.3 61.1 47.7 50.7 47.0 60.5 60.4 41.7 36.4 30.2 66.5 59.4 48.1 46.6 43.3

In sum, though analysts in the environmental sector would clearly benefit from an evidence-based approach to decision making given the types of policy issues they deal with and demands on their sector, they are also the least likely of analysts across all sectors to first, seek out evidence from other jurisdictions and second, utilize it in decision making processes. Given weak support for evidence-informed methods across most departments (the exception being health), the types of analytical techniques used by provincial policy analysts to make policy decisions, summarized in Table 17 above, should not come as a surprise. As it shows, provincial policy analysts across all sectors are more likely to use informal analytical techniques in their work. ―Consultation‖ and ―brainstorming‖ are the main analytic techniques used in the environmental policy sector. Environmental policy analysts, in particular, are more likely to use ―professional advice‖ and ―personal experience‖ as main evidentiary sources over ―scientific findings‖, ―academic research‖, or ―survey data‖. While this pattern goes against the instructions and admonitions of many textbooks, it is in keeping with the findings of many utilization studies which have found a distinct preference for the use of "simple" tools vs. complex ones on the part of both the producers and consumers of policy analysis (Sabatier 1978; Nilsson et al. 2008). The problem here is one noted by Dolowitz (2009: 317) that simple analytical tools translate into ―simpler forms of learning; often little more than the emulation of the ideas and rhetoric used within other political systems.‖ Indeed, as Table 17 demonstrates, a more complex analytical tool, modelling, is conducted by less than a fifth of analysts across the sectors and is an even less popular analytical method in the environment, welfare, and health sectors. Analysts in the environmental sector are the most likely of analysts in all sectors to use consultation and checklists to make decisions. In general, analysts across sectors appear to favour informal and unsystematic techniques to make policy decisions rather than more sophisticated formal analytical tools, limiting the potential for knowledge updating to occur. The types of policy issues provincial policy analysts are working on may help to explain why governments have made limited use of analytical techniques in decision making processes. Indeed, across all sectors, immediate, urgent, and short-term work dominate the day-to-day and week-to-week work agenda of policy analysts (see Table 19). As Table 18 shows, just over half of environmental policy analysts report working on a weekly basis on issues that are ongoing for more than a year, about the same proportion as report working on a weekly basis on long, medium, and short-term issues. However, sixtytwo percent also report working on a weekly basis on issues and problems that demand

Policy Analytical Capacity in the Environmental Sector: Survey Results… 181 immediate attention (i.e., "firefighting"). Environmental policy analysts are less likely to deal with urgent issues than counterparts in trade (73%), education (69%), and welfare sectors (68%); nonetheless, these types of issues remain the most common issues to consume their day-to-day work. While the prevalence of short-term work within provincial governments is often decried in the existing literature on the subject (Gregory and Lonti 2008), it can also be considered to be a primary "raison d'etre" of the policy bureaucracy. As Hawke (1993) put it:

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Fire-fighting is part of the job of any manager and is especially prominent in the public service because of the pressures on ministers. It is worth remembering that a key reason for having departmental policy advice agencies rather than distinct contracts for each piece of policy development is the desirability of immediate and unplanned access to informed advice (p. 64) [italics added].

However, given that environmental policy issues lack simple solutions and require greater coordination and technical knowledge than other policy issues (refer to Table 13), the degree to which ‗policy firefighting‘ comprises the policy activities of environmental policy analysts is highly problematic. Efforts – such as the Policy Excellence Initiative in Nova Scotia, the Knowledge and Information Services initiative in British Columbia, the Policy Innovation and Leadership project in Ontario, as well as cabinet-level initiatives in Yukon, Manitoba, Newfoundland and Labrador, and Alberta – are underway in many jurisdictions to systematically grapple with the short term focus of policy in the absence of strong policy analytical capacity and promote evidence-informed policy-making (Ontario, Executive Research Group 1999; Hicks and Watson 2007; Manitoba, Office of the Auditor General 2001; Nova Scotia, Policy Excellent Initiative 2007). This study cannot comment on the success of these initiatives, many of which have only recently been established; nonetheless, the survey results presented here underline the importance of action to invigorate policy capacity in the environmental sector given the limited application of formal analytical methods, minor use of external (nongovernmental) sources of evidence and lack of evidence based decision-making in provincial policy development around environmental issues.

CONCLUSION Our main argument here is that it cannot simply be assumed that governments have the capacity to address policy issues in the absence of information about the organization, resources, and activities of their civil services. In particular, we have chosen to focus here on the analytical policy capacity of sub-national governments in Canada. By developing a profile of environmental provincial policy analysts, we can better assess the prospects of governments to resolve complex policy issues in their sector. Here we find that environmental provincial analysts, like their federal and provincial counterparts in all sectors, are highly educated, relatively young ad mobile. However, they do not tend to have a great deal of formal training in policy analysis and work on a relatively small number of issue areas, often on a "fire-fighting" basis. Their short-term orientation, relative inexperience, high levels of job mobility, and lack of training in formal policy analytical techniques sets them apart from

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their national counterparts (see Wellstead et al 2009) and has significant implications for policy design and efficacy in multi-level states. More accurate assessments of policy analytical activities in government, especially those governments operating within multilevel governance frameworks have much to contribute in terms of clarifying the policy capacity of government actors on environmental policy issues. In terms of the present study, the weak policy capacity and short-term analytical focus found among most of the major actors involved in Canadian government-based poicy analysis is very problematic in the context of successfully dealing with the challenges of complex contemporary policy challenges. In particular it appears ill-suited to the development of the ongoing and long-term solutions required to deal with problems like climate change adaptation.

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WORKS CITED Aberbach, J. D. & Rockman, B. A. (1989). On the Rise, Transformation and Decline of Analysis in the US Government. Governance, 2(3), 293-314. Adams, D. (2004). ―Usable Knowledge in Public Policy.‖ Australian Journal of Public Administration, 63(1) March, 29-42. Anderson, George. (1996). ―The New Focus on the Policy Capacity of the Federal Government.‖ Canadian Public Administration, 39(4), 469-88. Bakvis, Herman. (1997). ―Advising the Executive: Think tanks, Consultants, Political Staff and Kitchen Cabinets.‖ In The Hollow Crown: Countervailing Trends in Core Executives, edited by P., Weller, H. Bakvis, & R. A. W. Rhodes, New York: St. Martin‘s Press. (2000). ―Rebuilding Policy Capacity in the Era of the Fiscal Dividend: A Report from Canada.‖ Governance, 13(1), 71-103. Beem, Betsi. (2009). Leaders in Thinking, Laggards in Attention? Bureaucratic Engagement in International Arenas. The Policy Studies Journal, 37(3), 497-519. Bennett, Colin, J. & Michael Howlett, (1992). ―The Lessons of Learning: Reconciling Theories of Policy Learning and Policy Change.‖ Policy Sciences, 25(3), 275-294. Binz-Scharf, M. C., Lazer, D. & Mergel, I. (2008). ―Searching for Answers: Networks of Practice among Public Administrators.‖ Harvard Kennedy School Faculty Research Workshop Papers RWP08-Q46. Boardman, Anthony, E., David Greenberg, Aidan Vining, and David Weimer (eds.). (2001). Cost- Benefit Analysis: Concepts and Practice. Upper Saddle River, N.J.: Prentice Hall. Boston, Jonathan, (1994). ―Purchasing Policy Advice: The Limits of Contracting Out.‖ Governance, 7(1), 1-30. Boston, Jonathan, John Martin, June Pallot, & Pat Walsh, (1996). Public Management: The New Zealand Model. Auckland: Oxford University Press. Bushnell, P. (1991). ―Policy Advice: Planning for Performance.‖ Public Sector, 14(1), 14-16. Davies, P. (2004). ―Is Evidence-based Government Possible?‖ Jerry Lee Lecture presented to the 4th Annual Campbell Collaboration Colloquium, 19 February 2004,Washington, D.C.

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Policy Analytical Capacity in the Environmental Sector: Survey Results… 183 Dobuzinskis, Laurent, Michael Howlett, & David Laycock, (eds.). (2007). Policy Analysis in Canada: The State of the Art. Toronto: University of Toronto Press. Dolowitz, David, P. (2009). ―Learning by Observing: Surveying the International Arena.‖ Politics & Policy, 37(3), 317-334. Dunn, W. (2004). Public Policy Analysis: An Introduction. Upper Saddle River, NJ: Pearson/Prentice Hall. Durning, Dan, & Will Osama. (1994). ―Policy Analysts‘ Roles and Value Orientations: An Empirical Investigation using Q Methodology.‖ Journal of Policy Analysis and Management, 13(4), 629-57. Fellegi, Ivan. (1996). Strengthening our Policy Capacity. Report of the Deputy Ministers Task Force. Ottawa: Supply and Services Canada. Gregory, R. & Lonti, Z. (2008). ―Chasing Shadows? Performance Measurement of Policy Advice in New Zealand Government Departments.‖ Public Administration, 86(3), 83756. Hawke, G. R. (1993). Improving Policy Advice. Wellington, New Zealand: Institute of Policy Studies. Hicks, Ron, & Peter Watson. (2007). Policy Capacity: Strengthening the Public Service‘s Support to Elected Officials. Edmonton: Queen‘s Printer. Hollander, Marcus, J. & Michael, Prince, J. (1993). ―Analytical Units in Federal and Provincial Governments: Origins, Functions and Suggestions for Effectiveness.‖ Canadian Public Administration, 36(2), Summer, 190-224. Howlett, Michael, & Jeremy Rayner. (2006). ‖Globalization and Governance Capacity: Explaining Divergence in National Forest Programs as Instances of "Next-Generation" Regulation in Canada and Europe.‖ Governance, 19(2), 251-275. Howlett, Michael, & Evert Lindquist. (2004). ―Policy Analysis and Governance: Analytical and Policy Styles in Canada.‖ Journal of Comparative Policy Analysis, 6(3), 225-49. Howlett, Michael, M. Ramesh, & Anthony Perl. (2009). Studying Public Policy: Policy Cycles and Policy Subsystems (3rd ed.). Toronto: Oxford University Press. Howlett, Michael. (2009). ―Policy Advice in Multi-Level Governance Systems: Sub-National Policy Analysts and Analysis‖ International Review of Public Administration, 13(3), 116. Howlett, Michael. (2000). ―Beyond Legalism? Policy Ideas, Implementation Styles and Emulation-Based Convergence in Canadian and U.S. Environmental Policy‖ Journal of Public Policy, 20, 305-329 Landry, R., Lamari, M. & Amara, N. (2003). ―The Extent and Determinants of the Utilization of University Research in Government Agencies.‖ Public Administration Review, 63(2), 192-205. Leeuw, F. L. (1991). ―Policy Theories, Knowledge Utilization, and Evaluation.‖ Knowledge and Policy, 4(3), 73-91. Lynn Jr., L. (1978). Knowledge and Policy: The Uncertain Connection. Washington, D.C.: National Academy of Sciences. MacRae Jr., D. (1991). ―Policy Analysis and Knowledge Use.‖ Knowledge and Policy, 4(3), 27-40. MacRae, D. & Whittington, D. (1997). Expert Advice for Policy Choice: Analysis and Discourse. Washington DC: Georgetown University Press.

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March, J. G. (1981). ―Decision making perspective: Decisions in organizations and theories of choice.‖ In Perspectives on Organization Design and Behaviour, edited by A. H. van de Ven, & W. F. Joyce, New York:Wiley. (1994). A Primer on Decision-Making: How Decisions Happen. New York: Free Press. May, P. J. (1992). ―Policy learning and failure.‖ Journal of Public Policy, 12(4), 331-54. McArthur, Doug, (2007). ―Policy Analysis in Provincial Governments in Canada: From PPBS to Network Management.‖ In Policy Analysis in Canada: The State of the Art, edited by Laurent Dobuzinskis, Michael Howlett, and David Laycock. Toronto: University of Toronto Press. Meltsner, A. J. (1976). Policy Analysts in the Bureaucracy. Berkeley, CA: University ofCalifornia Press. (1975). Bureaucratic Policy Analysis. Policy Analysis, 1(1), 115-31. Morgan, M. G. & Henrion, M. (1990). Uncertainty: A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis. Cambridge: Cambridge University Press. Nelson, R. H. (1989). The Office of Policy Analysis in the Department of the Interior. Journal of Policy Analysis and Management, 8(3), 395-410. New Zealand. State Services Commission. (1999). Essential Ingredients: Improving the Quality of Policy Advice. Wellington: Crown Copyright. Nilsson, Måns, Andrew Jordan, John Turnpenny, Julia Hertin, Bjorn Nykvist, and Duncan Russel. (2008). ―The Use and Non-use of Policy Appraisal Tools in Public Policy Making: An Analysis of Three European Countries and the European Union.‖ Policy Sciences, 41(4), December, 335-55. Nova Scotia. Policy Excellence Initiative. (2007). Policy Excellence and the Nova Scotia Public Service. Halifax: Policy Advisory Council and Treasury and Policy Board. Nutley, Sandra, M. Isabel Walter, & Huw, Davies, T. O. (2007). Using Evidence: How Research Can Inform Public Services, Bristol, U.K.: Policy Press. O‘Connor, Alan, Goran Roos, & Tony Vickers-Willis. (2007). ―Evaluating an Australian Public Policy Organization‘s Innovation Capacity.‖ European Journal of Innovation Management, 10(4), 532-58. Ontario. Executive Research Group. (1999). Investing in Policy: Report on Other Jurisdictions and Organizations. Toronto: Ministry of the Environment. Painter, M. & Pierre, J. (2005). Challenges to State Policy Capacity: Global Trends and Comparative Perspectives. London: Palgrave Macmillan. Patton, Carl, V. & David, Sawicki, S. (1993). Basic Methods of Policy Analysis and Planning. Englewood Cliffs, N.J.: Prentice Hall. Pahl-Wostl, Claudia. (2009). ―A Conceptual Framework for Analysing Adaptive Capacity and Multi-level Learning Processes in Resource Governance Regimes‖ Global Environmental Change, 9, 354-365. Pawson, Ray. (2006). Evidence-Based Policy: A Realist Perspective. London: Sage Publications. (2002). ―Evidence-based Policy: In Search of a Method?‖ Evaluation, 8(2), 157-81. Peters, B. Guy, (1996). The Policy Capacity of Government. Ottawa: Canadian Centre for Management Development. Preskill, Hallie, & Shanelle Boyle. (2008). ―A Multidisciplinary Model of Evaluation Capacity Building.‖ American Journal of Evaluation, 29(4), 443-59.

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Policy Analytical Capacity in the Environmental Sector: Survey Results… 185 Prince, Michael, J. (1979). ―Policy Advisory Groups in Government Departments.‖ In Public Policy in Canada: Organization, Process, Management, edited by G. Bruce Doern, & Peter Aucoin. Toronto: Gage. (2007). ―Soft Craft, Hard Choices, Altered Context: Reflections on 25 Years of Policy Advice in Canada.‖ In Policy Analysis in Canada: The State of the Art, edited by Laurent Dobuzinskis, Michael Howlett, and David Laycock. Toronto: University of Toronto Press. Prince, Michael, J. & Chenier, John (1980). ―The Rise and Fall of Policy Planning and Research Units.‖ Canadian Public Administration, 22(4), 536-50. Radaelli, C. M. (1995). ―The Role of Knowledge in the Policy Process.‖ Journal of European Public Policy, 2(2), 159-83. Radin, Beryl, A. (2000). Beyond Machiavelli: Policy Analysis Comes of Age. Washington, D.C.: Georgetown University Press. Radin, Beryl, A. & Boase, Joan, P. (2000). ―Federalism, Political Structure, and Public Policy in the United States and Canada.‖ Journal of Comparative Policy Analysis, 2(1), 65-90. Radin Beryl, A. (1992). Policy Analysis in the Office of the Assistant Secretary for Planning and Evaluation in the HEW/HHS: Institutionalization and the Second Generation. In Organizations for Policy Analysis: Helping Government Think. Edited by C. H. Weiss, (144-60). London: Sage Publications. Rasmussen, Ken. (1999). ―Policy Eapacity in Saskatchewan: Strengthening the Equilibrium.‖ Canadian Public Administration, 42(3), 331-48. Sabatier, Paul. (1987). ―Knowledge, Policy-Oriented Learning, and Policy Change.‖ Knowledge: Creation, Diffusion, Utilization, 8(4), 649-692. Sanderson, I. (2006). ―Complexity, ‗Practical Rationality‘ and Evidence-based Policy Making.‖ Policy and Politics, 34(1), 115-32. (2002). ―Evaluation, Policy Learning and Evidence-based Policy Making.‖ Public Administration, 80(1), 1-22. Thompson, P. R. & Yessian, M. R. (1992). Policy Analysis in the Office of Inspector General, U.S. Department of Health and Human Services. In Organizations for Policy Analysis, Helping Governments Think. Edited by C. H. Weiss, London: Sage Publications. Turnpenny, John, Måns Nilsson, Duncan Russel, Andrew Jordan, Julia Hertin, & Bjorn Nykvist. (2008). ―Why is Integrating Policy Assessment so Hard? A Comparative Analysis of the Institutional Capacity and Constraints.‖ Journal of Environmental Planning and Management, 51(6), 759-75. Voyer, Jean-Pierre. (2007). ―Policy Analysis in the Federal Government: Building the Forward-Looking Policy Research Capacity.‖ In Policy Analysis in Canada: The State of the Art, edited by Laurent Dobuzinskis, Michael Howlett, and David Laycock. Toronto: University of Toronto Press. Weible, Christopher, M. (2008). ―Expert-based Information and Policy Subsystems: A Review and Synthesis.‖ Policy Studies Journal, 36(4), November, 615-35. Weimer, David L. & Aidan, R. Vining, (1999). Policy Analysis: Concepts and Practice. New Jersey: Prentice Hall. Weller, Patrick, & Bronwyn Stevens. (1998). ―Evaluating Policy Advice: The Australian Experience.‖ Public Administration, 76(3), 579-89.

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Wellstead, A., Stedman, R. & Lindquist, E. (2007). ―Beyond the National Capital Region: Federal Regional Policy Capacity.‖ In Report Prepared for the Treasury Board Secretariat of Canada. Ottawa: Public Works and Government Services Canada. Wollmann, Hellmut, (1989). ―Policy Analysis in West Germany's Federal Government: A Case of Unfinished Governmental and Administrative Modernization?‖ Governance, 2(3), 233-66.

In: Environmental Planning Editor: Rebecca D. Newton

ISBN: 978-1-61728-654-4 © 2011 Nova Science Publishers, Inc.

Chapter 7

GOVERNANCE AND PUBLIC PARTICIPATION IN THE NETWORK SOCIETY Greg Hampton* Academic Services Division, University of Wollongong, New South Wales, Australia

ABSTRACT

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The public participation movement in planning and policy development is regarded as anachronistic in the network society. Politicians, administrators and citizens deliberate together to perform governance. In the network society co-governance is carried out jointly and politicians need to become adept at meta-governance in order to maintain representative democracy. Meta-governance – regulating the self-regulated – is important in facilitating co-governance. This can be achieved through modifying public participation methodology to include politicians and administrators and making use of modes of communication which are prevalent in the network society.

Public Participation in the Network Society This chapter is concerned with the work on public participation and consultation which has mushroomed in the literature in the last 20 years. This work on public participation has been particularly prevalent in the area of environmental policy development and planning (Webler, Kastenholz, & Renn, 1995). My argument is that this work is limited because it does not ensure that any work done with various publics is necessarily incorporated in the decision-making process. There has been a distinction made between public participation and public consultation in that the former addresses some form of participation in decision-making and the latter is usually in the guise of finding out how the public will react to a proposal (Roberts, 1998). The processes that are followed to engage in public policy making do not necessarily incorporate the public's *

Corresponding author: Email: [email protected], Phone: +61 2 4221 3446 Facsimile: +61 2 4221 3769 Fellow, Australian Center for Science, Innovation and Society, University of Melbourne, Victoria, Australia.

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Greg Hampton preference. On the other hand participatory policy making has a tradition of incorporating public preferences into the actual decision-making. This work and how it relates to the public participation movement is outlined in Hampton (2009a, p.43).

GOVERNANCE AND PUBLIC PARTICIPATION IN THE NETWORK SOCIETY In this essay I suggest that the public participation movement is anachronistic in the network society, which is characterized by the processes of what has come to be called cogovernance and meta-governance. Public managers and politicians work together with lay citizens from the outset to develop policy and planning proposals. I will outline the operation of co-governance and its applicability to current society and how meta-governance is important for the maintenance of representative democracy. I will also make some suggestions as to how social learning occurs in the network society and how various procedures can be used to distil the tacit knowledge of lay citizens and how this can be juxtaposed with explicit expert knowledge brought to bear on local conditions. The role of narrative policy analysis in this process will be explicated. I will discuss how the methods of public participation can be adopted and adapted for use in co-governance.

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Public Participation in Society In the last 40 years there has been an increasing recognition of the need for public participation in decision-making. This has evolved from simple consultation which assesses public preferences to sophisticated citizen panels which allow the opportunity for selected participants to deliberate in detail on a particular proposal or plan (Altman & Petkus, 1994; Kathlene & Martin, 1991). The level of participation which is afforded in such a process has been described within typologies such as Arnstein's ladder (Arnstein, 1969) and the Spectrum, propagated by the International Association of Public Participation (IAP2, 2010). I have outlined in detail how this process of public participation can be enhanced through the methods of participatory policy analysis (Hampton, 2009a) which stress the need for lay input in decision-making. The outcomes of these processes may or may not be incorporated in the final decision making process. This might be enhanced through the type of policy analysis and planning which is engaged in but it is still up to the whims of the public administrator or politician.

Decision Making and Inclusion of the Public In Creighton‘s (2005) model of public participation, the process starts with decision analysis. Whether to involve the public in decision-making is the subject of the analysis of the decision scenario and whether it is expedient to do so. Creighton's first step in decision analysis is simply to decide who should be involved. He provides examples such as people or organizational units who will be affected by the decision or those who understand how decisions fit together. The next step is to clarify who will make the decision and find out what will influence the decision from the perspective of the decision

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maker. This is particularly important when there are multiple organisations involved in the decision-making. It may be important to clarify the values involved in the decision in order to consult the public about the right issue. The next step is clarifying the problem being resolved. This entails gathering multiple perspectives on the issue at hand from different parts of the organization. The stages of the decision-making process need to be defined and when and how the public need to be consulted. It is important to identify institutional constraints that could influence the public participation process. When these steps have been completed it is possible to decide whether and what level of public participation is required. Involvement may require "informing the public; procedural public participation; collaborative problemsolving; developing agreements." (Creighton, 2005, p.43). It is important to establish what kind of participation is being provided by an organization otherwise misunderstandings will occur. When a decision scenario requires expression of a public‘s preferences and deliberation on alternative viewpoints then public involvement is warranted. It is important that in this process the views of proponents are openly expressed. As Guttman and Thompson (1996, p.3) argue in favour of democracy ―citizens should try to accommodate the moral convictions of their opponents to the greatest extent possible, without compromising their own moral convictions‖.

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The Network Society In the last 15 years there has been considerable work done on the concept of a network society. The network society is characterized by individuals linked locally and globally with high connectedness between units with lower density and lower inclusiveness (Yang & Bergrud, 2008). This requires public managers to develop skills in networking, negotiation, collaboration and deliberation. For example the operation of the network society and the need for involvement in governance is demonstrated by Healy et al. (2003) who discuss the networks involved in a regeneration on the city of Newcastle in the United kingdom. There was limited interaction amongst networks in the city and stakeholders relied on traditional hierarchies. This eventually resulted in public protests about the council‘s inadequate public consultation. They considered concepts of knowledge in constructivist terms. There were significant differences in the frames of reference used to construe the city regeneration. There was a learning dynamic which was promoted by the regeneration project. Citizen engagement has required a new set of skills for administrators in a post bureaucratic world (Hillier & Van Wezemael, 2008). They are now required to network, facilitate, collaborate and negotiate and bring together a multitude of heterogeneous voices. Policy making is participatory and informed by and negotiated with stakeholders who might be lay citizens or businesspeople. It is important that this policy is created using resources of the local political landscape. There is now a myriad of institutions which promote public engagement and citizen participation through deliberative flora. Hillier and Van Wezemael (2008) are interested in working with the disorderly aspect of a multitude of networks. They look at whether collaborative civic engagement actually leads to different outcomes than non collaborative processes. They outline how dealing with a network might be more expedient in

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developing a political solution to a planning problem however it might not engage with citizens who do not actively participate in that network. Policy making creates a sense of community and meaningful political participation in the network society (Hajer, 2003). It is grappling with public policy that creates the widely politically diverse network society. In the network society networks develop out of engaging with political issues that concern the community. Interest in political action defines the networks which become very diverse in orientation. Also in a network society citizens do not automatically respect hierarchical rules and policies. Hajer outlines how discourse analysis can be utilized in explicating how the network society is involved in policy analysis. Various methodologies have been developed to foster participation in policy development within the network society. Lukensmyer and Hasselblad Torres (2008) describe how their mode of citizen engagement, AmericaSpeaks, organizes citizens in large collectivities within town meetings, and enables them to participate in policy development. The process involves citizens deliberating in small facilitated groups and using information technology to assess and communicate their views to a wider group of up to four thousand people. It is possible for politicians and administrators to interact in these settings. Lukensmyer and Hasselblad Torres also describe how websites on the Internet can be used to implement community development and disaster management thereby enabling the broader network society to develop policy solutions of its own.

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Inter-Organizational Networks Some of the work on the network society has focused on the relations between organizations which characterize the way in which people now work within the network society. Vigoda-Gadot (2008) argues that a major challenge for public administration in the coming years is to create administrators that are appreciative of participatory democracy and willing to join with the private sector to advance the public good. Greater collaboration with the private sector and with publics is required so that a more inclusive collaboration is developed for public administration. This requires an understanding of businesses and the private sector and citizens, communities and the third sector or civic society, which is citizens who are part of larger groups that are more formal. An understanding of collaboration is also required at the political-national and international level, organisational level and communal level. Government and public administrators coordinate the actions of other social players at the political national level. At the organisational level business processes are utilised for the community good. Public administration and business management are assumed to support grassroots activities of citizens and civic society. Sharing of knowledge is critical for this collaboration to succeed. Vigoda-Gadot suggests an integrative collaboration between academic and practitioners, reform of public administration and grassroots initiatives which develop a civic culture. Collaborative networks should be distinguished from social networks which focus on nodes of social relationships (Agranoff, 2006). They are comprised of representatives of disparate organisations. They focus on developing inter-organisational solutions to problems that cannot be solved by single organisations. Inter-organisational network management shares a place alongside other forms of inter-organisational management and managers do the

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bulk of their work within an organisational hierarchy. One of the benefits of interorganisational networks is the sharing of information and procedures and the development of interagency agreements. Usually networks have some form of board of management which is elected by network members. They also create structures and rules and strategies which fit their inter-organizational needs. Networks have different forms including informational, developmental, outreach and action functions. Collaborative decisions are the result of mutual learning and they represent agreements between organizations. The network is not necessarily responsible for their implementation. Mutual learning involves looking into a problem and figuring out how to solve it, and this requires all parties to engage in joint learning and a brokered consensus. This can be fostered by group discussion, exchange of ideas, political negotiation of sensitive areas, data driven agreements and mutual respect amongst partners. Knowledge management is important to this process so that explicit and tacit knowledge is bought together. Power structures are still evident in networks and credence and power are given to those with specialised knowledge and skill. There are costs to network collaboration and these stem from protracted decision making process and pre-existing policies. Agranoff concludes that networks have altered the boundaries within which states operate but networks are still dependent on resources which states control.

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Decision-Making in the Network Society Deliberative and discursive democratic theory (Dryzek, 1990, 2002) extols the benefits of having the public involved in decision-making. In addition, work on the network society suggests that traditional analysis of societal processes is outmoded (Agranoff & Yidiz, 2007). The current policy sector manager deals with decision-making within a public managed network which extends beyond the bounds of the public organisation. This requires an understanding of societal processes and network governance. Decision-making in this context requires consideration of people who may not necessarily be part of the government hierarchy but are members of associated networks of the profit and not for profit sectors. Decisionmaking requires an understanding of the diverse viewpoints within a network and an ability to work with network members as partners rather than members of a hierarchy. This requires consensus building and problem solving. Decision-making is made in a more mutual manner. Publicly managed networks involve many stakeholders who must be collaborated with. Network management involves such activities as activating, brokering and facilitating interaction which creates strategic consensus building. There is a mutual learning process amongst the members involved in a network. Negotiations amongst network members require thorough understanding of one another's interests and differences. Agranoff and Yadiz categorise networks according to the types of decisions that they make. They distinguish between informational, developmental, outreach and action networks. Network decision processes are characterised by joint learning leading to brokered consensus. Public network members come together on a voluntary basis and share participation in decisions. Agranoff and Yadiz (2007) stress the learning environment factors involved in network decision making by virtue of partners following principles of civic discourse. The effectiveness of a network lies in the pattern of relationships that are established amongst its members.

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Governance of Networks Networks might involve at a horizontal level local government, townships, financial institutions, businesses and private-public partnerships. In a vertical field they might involve state or federal government agencies. Agranoff and McGuire (2001) found that 1% of cities had nine partners and 90% had at least one partner. They argue for a shift to the social production model which assumes that society is not coherent but a loose system of institutional arrangements. Effort is expended on developing enough cooperation to get things done. Network management has led to greater complexity in governance. It has also led to a diminution of governments so that they are no longer at the centre of policy processes. They argue that the democratic role of government should not be lost in network complexity and that governance is critical in intergovernmental network management. Agranoff and McGuire (2001) state that networks are multi-organizational arrangements for solving problems that cannot be done by single organizations. Public managed networks are typically led by government representatives. Activating the right players is critical in network management as it is important to involve the right people in a sequence of actions. Framing involves establishing the operating rules of the network and realigning the perceptions of these rules by the network members. It might involve looking at a problem differently. Mobilizing organizations and aligning them to a common cause is required. The network manager needs to synthesize the network by creating favourable interaction amongst members. Social capital is people working inter-organizationally and is essential for members of disparate organizations. Networks provide greater flexibility for all manner of organizational requirements. This is achieved by bypassing procedures, which may be seen as necessary in hierarchies. Democratic governance might be facilitated by the operation of a network. Decision making in a network might be more effective because it involves stakeholders and clients. Such decisions might meet the test that they deliver policy outcomes that are consistent with a multiplicity of societal interests. They might be based on a broader range of information and multiple perspectives. The synergy that develops between interest groups might lead to the creation of alternatives that would not otherwise have been considered.

Co-Governance of Networks Agger, Sorenson and Torfino (2008, p.17) recommend that network governance be regulated by agonistic respect when dealing with conflict. They suggest transforming "citizens and stakeholders from demanding receivers of governance to responsible coproducers of governance". They outline the various impediments that exist in societies to limit democracy such as fragmentation caused by growing individualism and postmaterialist values and suggest that new forms of coordination bring public and private actors together to jointly solve problems. Wicked problems also hamper governance in that they require specialised knowledge for developing solutions and the cooperation of large numbers of stakeholders often in conflict. Horizontal policy problems can only be solved through coordination of public and private actors. They suggest that elected representatives are captured by political elites and the interest groups and voters treated as customers who are communicated with through market research processes. They suggest that we have a plurality

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of demoi that must be connected through participatory governance. A governance network is characterized by independent yet autonomous actors engaged in governance based on negotiated interaction. Effective governance is enhanced by the production of responsive policy through continuous negotiation and democratic ownership and empowered participation. Democratic governance is deepened by an ongoing dialogue between politicians and citizens and bureaucrats and the stimulation of public debate. This is quite at odds with traditional views of government in which citizen participation would be regarded as inappropriate. Within this process we can expect there to be debate amongst stakeholders with agonistic respect for differences in opinion. The opinion of stakeholders can be expected to be treated with respect by other stakeholders. Booher (2008) argues that collaborative governance requires joint problem solving, broad public participation and sharing of regulatory responsibility. He discusses the concept of collaborative complex adaptive networks which can create pathways to democracy through emerging networks structured around common identities and based on collaboration and mutual learning. This view relies on replacing aggregative and adversarial democracy with the processes of deliberative democracy. These processes require that all participants are free to speak and be heard respectfully, they have equal opportunity to speak, that the outcomes of such deliberation promote equality and autonomy and that communication promotes understanding and reasoning. Such processes are recognised as being vulnerable to manipulation by powerful interests, which might marginalise the inarticulate or those who are vulnerable. Traditional democracy is regarded as having failed to inform the public about areas of civic interest and to involve the public in decision making. Deliberative democracy is the posited alternative which provides freedom to speak and air a view which is understood and respected. Having citizens maintain cognitive grasp and emotional stability while considering civic issues is a challenge which can be facilitated by processes of collaborative planning. These processes encourage open ended, respectful dialogue which encourages different ways of knowing such as story telling and role playing. This process commences with assessment of stakeholder knowledge, their readiness to collaborate and who should be involved. The stakeholders are then involved in designing how they should be convened and involved. Booher (2008) adds to deliberative democracy with deliberative planning practice. Booher focusses on long term face-to-face dialogue in deliberative democracy which seeks agreement on policy and plans. He suggests that dialogue meetings be professionally facilitated rather than chaired in order to promote dialogue. The process begins with assessment of stakeholders‘ and relevant others‘ knowledge about the topic and relationships and power dynamics amongst stakeholders and willingness to collaborate and the method of doing so. The process then continues with organising and convening the deliberative process with the agreement of all stakeholders. The stakeholders might be convened in sub-groups during this phase dependent on the purpose being pursued. There is a pedagogical aspect to this phase in that stakeholders learn how to communicate and collaborate. In the third phase of joint fact finding, groups develop a common understanding of issues and creation of new options. This phase is typically not included in deliberative democracy and might lead to mutual sharing of knowledge particularly from indigenous participants. In the fourth phase of deliberation and negotiation stakeholders engage with one another in order to solve the problem. Bargaining and trade-offs are only resorted to if mutually beneficial solutions are

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not derived. In the final phase of implementation stakeholders work together and modify the planned solution if necessary. Booher argues that civic engagement in democracy is true participation in policy deliberation through the many networks of interest spread across geography. The principles of collaborative planning guide the interactions of participants in this process within this system of networks. This is different to competitive democracy and deliberative democracy and includes perspectives from each movement. It is not aggregative and adversarial but instead is collaborative within clusters of networks which deal with particular issues. There are also sub-networks of stakeholders which have their own processes. The system of networks is in constant transition and may connect hundreds or thousands of people. There are agents within policy networks which evolve procedures and norms of collaboration and planning, which become heuristics for local interaction, which gradually spread to wider networks. These heuristics determine how people can work together despite their differences. These networks may ultimately influence political institutions. Politicians are less likely to ignore the voices of various networks when they are of one voice. Administrative agencies and interest groups can educate leaders on collaborative planning within complex adaptive networks. When the ability to build and maintain networks is equitably distributed across citizens then there will be democracy with civil engagement which allows people to rule themselves.

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Meta-Governance of Networks Agger, Sorenson and Torfino (2008) argue that contemporary governance is carried out as meta-governance -- the regulation of self-regulation. The governed become co-governors. The role of the politician and public administrator becomes one of meta-governor who governs self-regulating actors. They suggest a distinction between hands-off and hands-on meta-governance. The former is carried out at a distance through the formulation of overall political goals and political objectives, the allocation of an amount of resources that self regulating actors can govern, through the establishment of rules of self governance and through the construction of hegemonic storylines that give meaning to actions of the selfregulating actors. Meta-governors participate in the network and directly influence policy outcomes produced by the network according to the procedural rules and norms defined by the network. Agger, Sorenson and Torfino (2008) suggest that hands-on interaction between meta-governors and self regulating networks is important for performing meta-governance. While politicians tend to engage in hands off meta-governance public administrators engage in hands on meta-governance. However if politicians interacted directly with citizens and stakeholders they might find a plurality of powerful channels of influence. This requires citizens and stakeholders to become active co-producers of public governance through selfregulated governance techniques rather than just demanding consumers. They stand to gain considerable influence on the problem definitions of policy proposals; better governance proposals through a pooling of information and resources; more feasible policy expectations in the light of available resources and a sense of ownership and shared understanding and mutual trust with public authorities. This may result in greater collective benefits. Relatively unskilled and less resourceful publics and stakeholders will benefit from network participation. They also stand to lose from cooptation thereby losing a capacity to criticise and protest against unsatisfactory policy. They argue that antagonistic clashes in an agonistic

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democracy are a necessary part of political life in a network. Conflicting partners in a network need to be seen as adversaries who engage with one another in respectful contestation rather than as enemies. Governance of networks needs to be characterized as developing and cultivating agonistic respect where political struggles are democratized.

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Meta- Governance and Representative Democracy Sorensen (2006) argues that democracy is being diminished by the burgeoning metagoverning role of politicians. She perceives this role as limited as meta-governance is exercised by public administrators at a cost to democracy. Sorenson suggests how politicians can perform a role of meta- governance so that democracy is enhanced. In governance a multitude of actors interact to govern society. Meta-governance provides a means of coordinated governance in a politically fragmented society composed of self-governing networks and institutions. It provides a means of managing complexity and plurality. Sorenson discusses how storytelling is a forceful means of influencing self-governing actors without interfering directly in their strategic actions. She discusses how meta-governance is a threat to the position of government and how politicians and administrators are in a good position to facilitate meta- governance because they have access to administrative and political resources. In order to restructure representative democracy so that it is viable under conditions of governance citizens must control the decision-making process through elected politicians, there must be plurality for individuals and groups, there must be political equality amongst citizens and citizens must be linked together in community. Self governance contributes to the participatory skills of citizens by giving them direct access to governance processes. On the other hand there is the possibility that those who are more competent in dealing with government processes will dominate self governance. Sorenson suggests that it is important for elected politicians to have dominance in meta-governance so that it becomes a means of politicians governing society. Sorenson suggests that politicians have a central role in networks that produce meta-governance. She sees it as problematic that politicians have been ostensibly sidelined in the exercise of meta- governance. Sorenson conducted interviews with Dutch politicians, which found that they saw themselves as meta- governing and left the details of governance to stakeholders. Sorenson concludes that the metagovernance of self-governing networks and institutions has dire consequences for representative democracy. Self-governing actors are making important governance decisions and are not being democratically regulated through meta- governance. Democratically elected politicians are becoming part of a network of decision makers. Elected politicians should take a leading role in meta- governance which promotes efficient and democratic self governance rather than being marginalized which is at the cost of representative democracy. Sorenson suggests the formulation of a new political role for politicians which develops competence in meta-governance and empirical research which highlights the obstacles to the development of such a role.

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Social Learning in the Network Society Agranoff (2008) coins the term, the conductive organisation, which connects with a myriad of stakeholders, citizens and organisations which make up the network. External publics are not only service recipients but partners in joint collaborative efforts. Deliberation in these circumstances becomes a collective enterprise where administrators and publics learn together in attaining a common goal. Tacit knowledge can be explored through stakeholder consultations. Codified knowledge can be shared between agencies and publics through project reports and policy documents. In this shift the place of government and its role in governance should not be downplayed. In the conductive organisation information is calibrated and collaboratively implemented.

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The Facilitation of Social Learning in the Network Society The network society is dependent upon the development of authentic dialogue amongst stakeholders. This requires discussion traversing uncharted territory and people being able to question the status quo and challenge assumptions (Innes & Booher, 2003). Authentic dialogue requires diversity and interdependence amongst stakeholders. All interests need to be engaged in the discourse in order to achieve communicative rationality. This ensures that assumptions are challenged. Diversity of stakeholders ensures creativity. A realization that stakeholders are interdependent enhances problem-solving. It leads to the development of a shared mission. A result of authentic dialogue amongst diverse, interdependent stakeholders is reciprocity, relationships, learning and creativity. In developing reciprocity stakeholders find a narrative of the future which appeals to all of them. They find that they can make modifications to their own actions which are of little cost to themselves but of considerable benefit to others. The development of new relationships is a consequence of collaborative dialogue which may not otherwise have occurred. Stakeholders might learn what issues mean to each other while continuing to disagree. A respectful dialogue changes how interests are expressed. For learning to occur participants must be engaged in the process. Learning was an activity in which participants jointly created a shared a story and solution which would be acceptable to the public they were a part of. This often involved considerable creativity in the development of alternative scenarios and shared meanings and new heuristics which guide their action.

The Use of Public Participation Methodology in the Practice of Co-Governance and Meta-Governance Methods of participation, such as panels and focus groups could include politicians and administrators as participants. This will require a modification of the mode of facilitation so that politicians and administrators do not dominate proceedings. This requires a change in administrators‘ and politicians‘ attitudes towards the importance of their contributions within these methods of discussion and deliberation. It requires a recognition of the change in status afforded by the network society. Politicians and administrators are seen as equal participants. This may require some recognition that formal status is less important in the network society

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whereas competence or knowledge of local conditions in an area of implementation is more important. It also requires citizens to be more forthright in their contributions in such deliberation and to be less in awe of elected politicians, if that is the case. Komatsuzitki and Schachter (2008) point out the importance of understanding cultural mores in considering citizens‘ willingness to engage in participation. They note that Japanese citizens might be unwilling to participate with public officials because of the respect afforded to them due to their qualifications. A change in the function of such consultation and deliberation is required so that it is seen as the central method of policy development rather than a peripheral activity. The role of the politician and administrator in such activities is one of participant and contributor. This is an important aspect of the implementation of hands on meta- governance and co-governance. It requires politicians, administrators and citizens to reflect jointly on the processes of co-governance and for all to practice agonistic respect for differing views. Edelenbos et al (2010) discuss how Council representatives and politicians in the Netherlands were reluctant to accede their power and responsibility in managing Council functions. They did participate as auditors in the process but were reluctant to directly participate in discussions. Although this role is not as participative as preferred in the network society it did mean that discussions with citizens were conveyed to the wider Council. Professionals found that the interaction with citizens was not compatible with their perceived role and were reluctant to participate in the interactive process. This was further in evidence in their reluctance to have discussions with citizens incorporated in a final policy document. The professionals were reluctant to have the uncertainties of the lay discussion included in the final document which they wanted to retain a certain professionalism. Edelenbos et al conclude that only the political interface was maintained in the process. The executive, policy and professional interfaces were difficult to maintain. The executive interface was marred by electoral processes and the illness of an executive. In the process it was apparent that professionals, experts and civil servants, had difficulty with direct democracy however this was not the case with politicians who were more prepared to engage with citizens in cogovernance. Rowe and Frewer (2000) discuss a number of public participation methods, some of which are amenable to joint deliberation and useful for co-governance and meta- governance. For example, in a citizen panel, where scientists and other experts give evidence to and are examined by the panel, politicians and administrators would also take part in this process as equal participants. This would allow for joint discussion and questioning of the evidence presented so that citizen views and politicians‘ and administrators‘ views are discussed in the same venue rather than citizens‘ views being treated as an after thought. This form of deliberation might lead to joint development of ideas for politicians, administrators and citizens. The result would be a more creative and comprehensive view on the part of all participants. When participants share their diverse views they will come to consider and recognize the benefits of one another's perspectives. This will be more productive than politicians and public administrators having their own private consultations and deliberations with experts. The combination of these perspectives will lead to the development of new ideas and solutions which may not otherwise have been contemplated without this juxtaposition of differing viewpoints. This process will require a swallowing of pride on the part of politicians and administrators and that is the nature of the network society. Public hearings, inquiries and consensus conferences could be adapted in a similar manner.

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Focus groups could be readily set up to include politicians and administrators. This somewhat contradicts the view that participants in focus groups are representative of the population who might be randomly selected, but this method has become such a popular tool in public participation that this variation seems warranted. The politicians and administrators could form a stimulus to discussion in the focus group. The benefits of this change to methods are that the lay citizen is included in the policy deliberation from the beginning. This change in format might be more readily be considered to be a forum which utilises the discussion methods and analytical methods of focus groups (Morgan & Krueger, 1998; Puchta & Potter, 2004). The AmericaSpeaks method of engagement of Lukensmyer and Hasselblad Torres (2008) can readily accommodate the participation of politicians and administrators. They can present their views to a large town meeting through the use of information and communication technology and assess the views of citizens and interact with citizens through the use of such technology. One issue of concern is how to motivate citizens to participate in policy deliberation. Do we rely on the highly motivated citizen to volunteer for participation in such deliberation or do we randomly select citizens to participate? It is likely that only the highly motivated citizen with a particular political view will volunteer to participate in co-governance. Citizens could be required to participate in policy deliberation as they do in jury duty. Such moves might not be popular but they go some way towards developing an educated citizenry. Participation in the AmericanSpeaks method of engagement may generate a momentum of interest amongst citizens because of the breadth and depth of interaction it affords. These modifications to public participation methodologies and new innovations such as America Speaks enable the implementation of co-governance and meta- governance and its benefits, as outlined by Agger, Sorenson and Torfino (2008). To involve citizens in this way in policy development enables them to become designers rather than consumers of policy. Such joint deliberation enables policy development to be more reliably aligned with citizen preferences and administrators means of implementing policy. It is important that metagovernance does not lead to a diminution of representative democracy. This requires facilitators of joint deliberation to be mindful of the role of politicians in representative democracy and to design deliberation in a way which maintains that position - it enables them to be co-designers of policy. This might go some way towards facilitating the inclusion of politicians within such a joint deliberative process if their role is recognized and maintained within the process.

Characteristics of Lay Knowledge in Participatory Technology Assessment The work of Chilvers (2008) provides principles on which to base participatory appraisal of technology and the environment which could form the basis of formulating deliberation carried out jointly by politicians, administrators and citizens. Chilvers‘ (2008) principles of effective participatory appraisal, which are relevant to joint deliberation, are that in the framing stage of appraisal process citizens and politicians should be engaged in shaping and guiding scientific analysis conducted during the process. They should also be involved in scientific assessment and evaluation when the science is particularly contentious or uncertain. The scientific analysis should also be responsive to the

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issues and concerns raised by the participants. Above all it should support deliberation and be accessible to all participants. It should strive to make assumptions explicit. I have explored dimensions of creating a deliberative forum in which lay citizens uncover the apparent facticity of expert knowledge provided to them (Hampton, 2009b). Chilvers‘ (2008) principles of appraisal were used to guide the presentation of information and analysis of participant responses. With regard to effective use of scientific analysis Chilvers suggests that it supports deliberation and be accessible to participants, responding in an iterative fashion. This project focused on representing alternative viewpoints; exploring uncertainties and exposing underlying assumptions. We found that participants in a technology appraisal exercise often engaged in reification of expert knowledge but when encouraged to do so would question and ironize the information that was provided to them as expert knowledge.

Participatory Inquiry in the Development of Joint Deliberation and Co-Governance

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Another methodological process which could be readily adapted for use in joint deliberation and co-governance is that of Participatory Inquiry. As formulated by Frank Fischer (1999) this method provides a forum within which politicians, administrators and citizens can deliberate on technological issues. Participatory inquiry involves citizens doing their own research and is similar to what scientists formulate according to their methodological procedures. The technicalities of such procedures are simplified for use by politicians, administrators and citizens. That they are working together on collecting evidence to support or diminish proposals means that they will formulate solutions to problems as they develop rather than having arguments and controversy towards the end of a policy development process.

Narrative Policy Analysis and the Network Society A policy development process which is relevant to the promotion of joint deliberation and co-governance is Narrative Policy Analysis (Roe, 1994). This method provides a means of eliciting dominant narratives in a controversy and juxtaposing them with counter narratives which are usually expressed by citizens. Meta-narratives are derived in this process and often lead to a rapprochement between dominant and counter narratives. I argue that the tacit knowledge of citizens is expressed through their counter narratives which need to be explicated so that citizens are comprehensively aware of their viewpoints. As narratives are a common means by which people express themselves there is often the opportunity to make explicit the tacit knowledge which is expressed in such narratives. Within this interchange of knowledge between politicians, administrators, experts and citizens there will be varying degrees of structure and explicitness of knowledge. On the one hand expert knowledge is likely to be systematic and explicit; lay knowledge on the other hand is likely to be tacit and uncoordinated. It is an important part of meta-governance for the administrator or facilitator of proceedings within policy deliberation to uncover and elicit tacit lay knowledge.

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As the formulation of meta-narratives is based on the expression of dominant narratives of politicians, bureaucrats and experts and the joint expression of counter narratives, often by citizens, it represents a systematic form of collecting joint and diverse narratives which are expressed in a technological and environmental controversy. The various commentators that have been reviewed often refer to the narrative form of communication in the network society and this mode of policy analysis gives recognition to this form of communication. I have outlined in Hampton (2009a) how this form of policy analysis relates to public participation theory and practice.

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Applying Joint Deliberation to Technological Developments Several case studies of technological development and environmental controversy are reported and the way in which joint deliberation could have been incorporated in the process is discussed. The drinking water program established by Sydney Water (1992) was designed to improve the overall quality of potable water supplied in the Sydney region. The process was marred in the Illawarra region by controversy over the need for water quality improvement and social and environmental objections to the siting of a water treatment plant. The water utility organization embarked on a systematic community consultation program to assess the question of whether the community wanted water treatment and what type of treatment they wanted. There were opportunities for the organization to be more involved in the public deliberation. They did attend focus group forums in the later stage of the consultation process but it might have been more constructive to involve them in the early stage of deliberation so that the options for water treatment were jointly considered and developed. The Illawarra wastewater strategy (Technology and Environmental Strategies Research Group, 1997) could have benefited from early joint deliberation about options for treating wastewater. The water utility developed a social survey for community preferences for treatment options. I argue that the options for treatment were not particularly positive about tertiary treatment and the community voted for secondary treatment perhaps because of this bias in the survey. Further stakeholder consultation with interest groups led to a preference for tertiary treatment and the development of this option. It might have been preferable to engage with these interest groups jointly when the options were being developed and incorporate their preferences into the process. The recycled waste water exploration in the Toowoomba region would have benefited from joint deliberation early on in the process. This might have led to less controversy within the community and the joint seeking of options for a solution to the problem of potable water supply (Smith, 2006). Because of the urgency of fulfilling government requirements the public was not given much opportunity to deliberate on information about water reuse. The marketing strategies utilized by the local Council mitigated against joint deliberation and fostered differences of opinion amongst protagonists (Hampton, 2009a). In these cases expert knowledge was given primacy and was the first source of knowledge to be considered. Such expert knowledge has been showing to contain value orientations and does not uphold the objective reality that it is purported to (Fischer, 2000). On the contrary a joint deliberation process would give equal recognition to lay and expert sources of knowledge.

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REFERENCES Agger, A., Sorensen, E., & Torfino, J. (2008). It takes two to tango: when public and private actors interact. In K. Yang & E. Bergrud (Eds.), Civic engagement in a network society (pp. 15-40). Charlotte North Carolina: Information Age Publishing. Agranoff, R. (2006). Inside collaborative networks: Ten lessons for public managers. Public Administration Review, 66, 56-65. Agranoff, R. (2008). Conductive public organizations in networks: collaborative management and civic engagement. In K. Yang & E. Bergrud (Eds.), Civic engagement in a network society (pp. 85-110). Charlotte North Carolina: Information Age Publishing. Agranoff, R., & McGuire, M. (2001). Big questions in public network management research. Journal of Public Administration Research and Theory, 11(3), 295-326. Agranoff, R., & Yidiz, M. (2007). Decision making in public management networks. In G. Morcol (Ed.), Handbook of decision making (pp. 319-345). London: Taylor and Francis. Altman, J. A., & Petkus, E. (1994). Toward a stakeholder-based policy process: An application of the social marketing perspective to environmental policy development. Policy Sciences, 27, 37-51. Arnstein, S. R. (1969). A Ladder of Citizen Participation. Journal of the American Institute of Planners, 35, 216-224. Booher, D. E. (2008). Civic engagement as collaborative complex adaptive networks. In K. Yang & E. Bergrud (Eds.), Civic engagement in a network society (pp. 111-148). Charlotte, North Carolina: Information Age Publishing. Chilvers, J. (2008). Deliberating Competence: Theoretical and Practitioner Perspectives on Effective Participatory Appraisal Practice. Science Technology & Human Values, 33(3), 421-451. Creighton, J. L. (2005). The public participation handbook: making better decisions through citizen involvement. San Francisco: Jossey-Bass Inc. Dryzek, J. S. (1990). Discursive democracy: politics, policy, and political science. Cambridge: Cambridge University press. Dryzek, J. S. (2002). Deliberative democracy and beyond: liberals, critics, contestation. Oxford: Oxford University press. Edelenbos, J., van Schie, N., & Gerrits, L. (2010). Organizing interfaces between government institutions and interactive governance. Policy Sciences, 43(1), 73-94. Fischer, F. (1999). Technological deliberation in a democratic society: the case for participatory inquiry. Science and Public Policy, 26(5), 294-302. Fischer, F. (2000). Citizens, Experts and the Environment: The Politics of Local Knowledge. Durham NC: Duke University Press. Guttman, A., & Thompson, D. (1996). Democracy and disagreement. Cambridge: Harvard University Press. Hajer, M. A. (2003). A frame in the fields: policy making and the reinvention of politics. In M. A. Hajer & H. Wagenaar (Eds.), Deliberative policy analysis: understanding governance in the network society (pp. 88-110). Cambridge: Cambridge University Press. Hampton, G. (2009a). Narrative policy analysis and the integration of public involvement in decision making. Policy Sciences, 42(3), 227-242. Hampton, G. (2009b). The perception of the facticity of expert knowledge in public engagement. Submiited for publication.

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Healey, P., de Magalhaes, C., Madanipour, A., & Pendlebury, J. (2003). Place, identity and local politics: analyzing initiatives in deliberative governance. In M. A. Hajer & H. Wagenaar (Eds.), Deliberative policy analysis: understanding governance in the network society (pp. 60-87). Cambridge: Cambridge press. Hillier, J., & Van Wezemael, J. (2008). Tracing the disorderly real: performing civic engagement in a complex world. In K. Yang & E. Bergrud (Eds.), Civic engagement in a network society (pp. 149-185). Charlotte, North Carolina: Information Age Publishing. IAP2. (2010). Public Participation Spectrum, fromhttp://www.iap2.org/associations/4748 /files/spectrum.pdf Innes, E., & Booher, D. E. (2003). Collaborative policy making: governance through dialogue. In M. A. Hajer & H. Wagennar (Eds.), Deliberative policy analysis: understanding governance in the network society (pp. 33-59). Cambridge: Cambridge University Press. Kathlene, L., & Martin, J. A. (1991). Enhancing Citizen Participation: Panel Designs, Perspectives and Planning. Journal of Policy Analysis and Management, 10(1), 46-63. Komatsuzitki, S., & Schachter, H. (2008). A comparative study of citizen engagement in the infrastructure planning in Japan and the United States: a look at legal frameworks and two successful cases. In K. Yang & E. Bergrud (Eds.), Civic engagement in a network society (pp. 187-205). Charlotte, North Carolina: Information Age Publishing. Lukensmyer, C. J., & Hasselblad Torres, L. (2008). Citizensourcing: citizen participation in a network nation. In K. Yang & E. Bergrud (Eds.), Civic engagement in a network society (pp. 207-233). Charlotte, North Carolina: Information Age Publishing. Morgan, D. L., & Krueger, R. A. (1998). The focus group kit. California: Sage. Puchta, C., & Potter, J. (2004). Focus groups practice. London: Sage. Roberts, R. (1998). Public involvement in environmental impact assessment: Moving to a "Newthink. The Journal of Public Participation, 4(1), 39-62. Roe, E. M. (1994). Narrative Policy Analysis: Theory and Practice. Durham, NC: Duke University Press. Rowe, G., & Frewer, L. J. (2000). Public Participation Methods: a Framework for Evaluation. Science, Technology and Human Values, 25(1), 3-29. Smith, A. (2006). Lies, damn lies and recycled water. Retrieved 4/4/08, 2008, from http://www.blogtoowoomba.com/entry.php?w=toowoombawatervote&e_id=236 Sorensen, E. (2006). Metagovernance - The changing role of politicians in processes of democratic governance. American Review of Public Administration, 36(1), 98-114. Sydney-Water. (1992). Drinking water program, 1992-1998 Sydney: Sydney Water. Technology and Environmental Strategies Research Group. (1997). Sydney Water Customers' Views on the Illawarra Wastewater Strategy. Wollongong: University of Wollongong. Vigod-Gadot, E. (2008). Collaboration management in public administration. In K. Yang & E. Bergrud (Eds.), Civic engagement in a network society (pp. 41-64). Charlotte, North Carolina: Information Age Publishing. Webler, T., Kastenholz, H., & Renn, O. (1995). Public participation in impact assessment: a social learning perspective. Environment Impact Assessment Review, 15, 443-463. Yang, K., & Bergrud, E. (2008). Civic engagement in a network society. In K. Yang & E. Bergrud (Eds.), Civic engagement in a network society (pp. 1-15). Charlotte, North Carolina: Information Age Publishing.

In: Environmental Planning Editor: Rebecca D. Newton

ISBN: 978-1-61728-654-4 © 2011 Nova Science Publishers, Inc.

Chapter 8

INDUSTRIAL ECOLOGY IN THE PLANNING AND MANAGEMENT OF INDUSTRIAL PARKS M.C. Ruiz* Transport and Projects Technology and Processes Department, School of Industrial and Telecommunication Engineers, University of Cantabria, Spain

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ABSTRACT The planning and design of an industrial area is quite a complicated process, due to the large number of agents involved. It is also a long process due to the scope of the action itself: selection and design of the location, design of the physical infrastructures, of the industrial installations and buildings, construction, operation and design of the management systems and disassembly-dismounting. Integration of the environmental variable throughout all the design stages is essential in order to ensure that it works over time and that it coexists with the environment where the estate is located. In this chapter we analyse the concept and the types of sustainable industrial areas (Eco-Industrial Parks, EIPs). Application of industrial ecology is the main strategy supporting change towards a new development model, based on a sustainable economy. Depending on the applicable geographical scale, there are different types of EIPs. Thus arise new opportunities for seeking alternative strategies and solutions for making use of resources, minimising negative environmental impact and maximising financial profits. However, developing an industrial area of this nature requires a large amount of coordination between all the agents involved. The types of organisms and current management forms and trends are summarised. The roles, opportunities and risks to be assumed by the organisms involved in the development of EIPs are established based on this framework The manager or coordinator is an important figure throughout the operational life of the estate, as a feasible combination of companies must be managed and infrastructures and competitive services must be maintained.

Key words: industrial ecology, EIPs, sustainability, agents, management * Corresponding author: E-mail: [email protected].

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1. INTRODUCTION

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The term industrial area refers to the idea of more or less intensive clustering of industrial activities with shared infrastructures in a certain territory (Trinder et al. 1993, Walcott 2009). The definition of a typology of industrial areas can be as diverse as areas exist, thus any classification that is made could be incomplete. In practice, the typology of productive spaces can be formed based on the consideration of one or several of the following features: predominant use or uses depending on the type of activity (basic or mixed industrial and special activities), area size and plot subdivision. This type of clustering represents a large part of the economic strategy followed by many countries since 1970, especially the more developed countries, where their planning and development are an essential part of the urban and territorial planning programs (Smith 1971). Nonetheless, there is a significant environmental risk, because industrial parks concentrate all of the environmental problems of each one of the companies that are located there, in a relatively small area, to which we must add the impact caused by their infrastructures and services. The lack of environmental management mechanisms may cause impact from the generation of waste, atmosphere and water pollution and safety conditions in a relatively small space, which may also interfere with the neighbouring urban, tourist or recreational areas. The current environmental legislation framework focuses on individual activities, which hinders its application to the industrial area system. This is partly due to the difficulty in establishing regulations that are applicable to all cases, because each park is different. This situation could be solved by means of industrial park self-government, and the consequent freedom of environmental self-regulation, depending on the degree of competitiveness that businesses may achieve. However, the essential element for improvement resides in the lifecycle perspective during the planning and design stages of new projects (Thabrewa et al. 2009, Pennington et al. 2007). Therefore, we should identify and address each of the lifecycle stages of an industrial area, in depth: Location selection. Analysis of the localisation factors of influence and application of the techniques for assessment and selection of the optimal location. Planning of the area and the physical infrastructures. Zoning and use of the land, precise delimitation of accesses and dimensioning suitable to the infrastructures required for the area to function, water and energy supply, sewage facilities, public lighting, waste collection… Design of the buildings. Selection of the type of industrial buildings to be installed, their orientation, building materials and development of the ancillary installations required for the business operations. Construction. Performance of the civil engineering works, which include the buildings and infrastructures required for the future companies that will locate to the industrial area to operate.

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Operation and management. Stage at which the companies located in the industrial area operate generating products and services; maintenance operations and improvement of the installations are also carried out to guarantee their competitiveness. Disassembly and dismantling. End of the lifecycle, when the location is vacated of the industrial installations so that it may be used for other purposes. Throughout this lifecycle a negative environmental impact is generated, which must be reduced by means of new planning, design and management methods that are capable of conceiving industrial areas as socio-economic development elements that are in equilibrium with their surroundings. The emerging concept of sustainable industrial area should therefore be based on each and every one of the stages of its lifecycle. The planning and zoning stage has already been addressed in previous papers (Fernández & Ruiz 2009). The operation and management stage is the longest of the lifecycle and its design entails a higher efficiency in the consumption of resources and a lower generated impact on the surroundings, especially and with priority through the creation of cooperation networks of businesses for the exchange of materials and energy. In this chapter we present industrial ecology as the main strategy supporting change towards a new development model, based on a sustainable economy. Nevertheless, the process is complex and requires the participation and coordination of the different organisms involved in the development and management of these areas. Within this context new opportunities and risks are emerging. Industrial ecology Green design

Pollution prevention

Green design

Pollution prevention

Lifecycle analysis Lifecycle analysis

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Ecoefficiency

Environmen tal Management System

In dustry

Ecoefficiency

Trans port

Cons umer

Trans port

Cons umer

Pr oduct

Raw materials

Pr oduct

Raw materials

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Natural resources

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Waste

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Life cycle analysis Ecoefficiency

In dustry

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Environmen tal Management System Pr oduct

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Pollution prevention

Green design

Lifecycle analysis Ecoefficiency

In dustry

Raw materials Cons umer

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Figure 1 Perspective of the relationship between sustainability strategies. Figure 1. Perspective of the relationship between sustainability strategies

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2. SUSTAINABILITY AND DESIGN OF INDUSTRIAL PARKS 2.1. Sustainability Strategies Based on Industrial Ecology

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Since the energy crisis of 1971, many are the events that have conditioned international politics and have provided the essential impulse to begin the process of change towards a new model of sustainable development (WCE 1987). The 1992 Rio de Janeiro summit was the milestone after which many states and even the European Union began to define and apply plans to achieve equilibrium between economic, social and environmental interests. The achievement of this goal has led to the creation of a variety of strategies that affect processes or products (Munier 2005): pollution prevention, eco-efficiency, lifecycle analysis, green design, environmental management systems and industrial ecology. Figure 1 shows the relationship between these sustainability strategies, with a systemic focus. Industrial ecology has come to represent a broad set of concepts within which the remaining strategies are contained, its aim being to guide the transformation of the current industrial systems towards a sustainable basis. Industrial ecology theory presents the search for interactions between industrial activity and its environmental and urban surroundings, where the different production processes are considered as dependent and interrelated elements. The main goal is to encourage symbiosis between human activities situated in a certain area through the exchange of materials and energy, use of the know-how contained within the activities, development of shared installations or initiatives (O‘Rourke et al. 1996, Graedel & Allenby 2003). This transformation requires changing the linear productionconsumption model towards a closed-cycle model, similar to the cyclic flows of natural ecosystems (Lowe & Evans 1995). Industrial ecosystems and sustainable industrial parks represent, for some industrial ecologists, a key strategy for implementing industrial ecology (Côte & Hall 1995).

2.2. The Concept of Sustainable Industrial Park (Eco-Industrial Park, EIP) The planning and design of EIPs has become especially relevant over the last decade (Côté & Cohen-Rosenthal 1998, Gibss & Deutz 2005). The most common concept is based on the creation of materials and energy exchange networks. Martin et al. (1996) resort to the definition given by the United States Environmental Protection Agency (USEPA) to describe an EIP as: A community of manufacturing and services businesses that seek to enhance environmental and economic performance through collaboration in environmental management and reuse of materials. By working together, the community of businesses seeks a collective benefit that is greater than the sum of individual benefits each company would realise by only optimising its individual performance.

Other authors (Lowe et al. 1996, Oh & Kim 2005), also include in their definitions additional elements of industrial ecology that relate to the creation of a community identity, design and rehabilitation of infrastructures and buildings and pollution prevention:

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A community of manufacturing and service businesses seeking enhanced environmental and economic performance through collaboration in managing environmental and resource issues including energy, water... Improvement of the environmental and economic performance includes the design and rehabilitation of the park‘s infrastructures and buildings, pollution prevention and energy efficiency. Industrial community in which the neighbours, manufacturing industries and services companies all share a feeling of belonging to a community and basic resources (information, materials, pollution prevention infrastructures) to maximise economic and social benefit and, at the same time reduce their environmental impact. Achievement of these goals requires the design and use of technologies that are efficient in the use of resources, energy and recycling of waste. This also implies the creation of a cultural identity, environmental design of the buildings and construction of symbiotic industrial networks

A common theme in these different statements is the economic and environmental benefit resulting from cooperation between the organisms involved in the performance of a sustainable industrial area. This cooperation entails the shared use of infrastructures, services, information and the creation of exchange networks that are aimed at closing materials cycles throughout the chain. The entire life cycle is taken into consideration, from the extraction of raw materials to the consumption of the product and its disposal. With the creation of these networks EIPs seek to imitate the efficiencies of natural ecosystems in achieving a more sustainable consumption and production, thus attaining a reduction in the amounts of waste generated and the conversion of by-products into reusable resources and products (Erkman 2003, Fiksel 2003). The localisation and integration of organisations that can use each of the waste products is essential, given that the loss of energy and materials at different points throughout the production/consumption/recycling/reuse cycle are unavoidable.

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3. TYPES AND DEVELOPMENT STAGES OF EIPS The typology of EIPs is defined, partly, by spatial and organisational elements. Considering the distance between the companies forming part of the network and the boundaries within which the exchange of resources take place, Tudor et al. (2007) have produced a summary of terms used in the literature to define these networks of companies: Eco-Industrial Network, Eco-Industrial Park, Eco-Industrial Development, Networked EcoIndustrial Parks, Integrated Eco-Industrial Parks, Industrial Ecosystems and Industrial Symbiosis. In spite of the variety of terms, they all relate the clustering of companies to an increase of environmental, social and economic benefits. Based on a detailed analysis of experiences contained in the scientific literature and on the taxonomy of types of exchange of materials carried out by Chertow (2004), Fernández (2009) proposes a classification based on the geographic scale. A distinction is made between the local and regional scaled EIPs. Despite the fact that there is no distance limit that defines the change from local to regional scale, we can consider that 3 km is the distance between companies for a local scale. The entities that participate in the exchanges vary depending on whether they are traditional parks, individual enterprises or EIPs.

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Figure 2. Local scale applicable to the concept of EIP

3.1. Local Scale The local scale comprises all those situations in which the physical distance between companies is small. The possible options can be conceived through the design or redesign of pre-existing areas. In general, rehabilitation will achieve less environmental and economic benefits than designing a new area that starts from scratch based on the principles of industrial ecology. These strategies are applicable to companies or firms, localised companies and companies not localised in an area defined as industrial park, Figure 2.

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Company. Companies that can recycle water, co-generate steam and electricity, use gas emissions and re-process waste products and materials, can considerably reduce their operating costs. However, there are limitations regarding the degree and quality of waste and by-products that affect recovery costs. Although the measures employed may at times be partial, large plants such as refineries and electrical plants provide good opportunities for applying industrial ecology at firm or factory level. This is the case of the Corporation EBARA in Fujisawa (http://www.ebara.co.jp). Localised companies. The group of companies located in a defined and delimited area is the next stage in the evolution of industrial parks. Development of new synergies is stimulated and so the added value of the company individually and of the collective group of businesses increases. Within this type of parks we in turn find a further four types depending on the strategy applied (Figure 3): by-product exchange, recovery of resources and recycling, green design around a specific theme and combination of industrial, commercial and residential uses. Some examples of this type of industrial parks are the eco-industrial park Guitang Group in China (Zhu & Côte 2004) or the Phillips Eco-Enterprise Centre in the United States (Gibbs & Deutz 2007). Non-Localised companies. These are industrial activities of a very diverse nature, mainly small and medium businesses, which are concentrated over more or less extensive areas. The separation between the companies is dictated by the economic feasibility of the shared services and usually does not exceed 3 km. Although the environmental and economic benefits increase with the geographical scale, the difficulties in their creation increase as well, given the need to coordinate the rising number of organisms involved. An example of this type of park is Kalundborg in Denmark (Lowe & Evans, 1995).

Industrial Ecology in the Planning and Management of Industrial Parks

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Figure 3. Strategies applied by companies located in an industrial area

Figure 4. Regional scale applicable to the concept of EIP

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3.2. Regional Scale The regional scale affects the systems of eco-industrial networks whose distance between companies exceeds 3 km. The national and global scope is included within these limits. As shown in Figure 4, this system represents the development at a macro level of strategic linkages or alliances between eco-parks, classical industrial parks and/or individual companies through metropolitan regions or even global network structures, thus boosting both environmental and business actions (Lowe 2001). This system emerges where industries actively seek opportunities for linkages and relationships that promote synergies through networks and spatial association. Inter-connected parks are not only a market or exchange system, they can be designed to boost synergies between industries that will allow reprocessing of products and waste. These synergies stimulate the creation of new industries, which will contribute to the diversity or expansion of existing industrial activities or groups. There are many more opportunities for the application of industrial activities in the larger areas, as it is more probable that there is a greater variety of activities and, therefore, also the possibility of establishing a greater number of synergies. One of the main drawbacks of the eco-industrial networks is the increase in risks. These risks are derived from the strong dependence created between the different companies that make up the synergies. Network design requires a careful planning process that will make the system strong. Two examples of eco-industrial networks are Singapore‘s Jurong Island (Yang & Lay 2004) and Kola Peninsula Mining-Industrial Complex in Russia (Salmi 2007).

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3.3. Summary of Features Pursuant to the Geographical Scale Application of the industrial ecology principles in the development of EIPs generates a series of advantages and disadvantages in the different scales of application. The main features are summarised in Table 1. The possibilities for creation of synergies increase in proportion to the geographical size, because the number of companies involved is larger and therefore the possibilities for establishing exchanges are also higher. This requires an increase in awareness on the principles and benefits of industrial ecology, thus facilitating collaboration between the different organisms involved in the development and performance of these areas of economic activity. There are more opportunities for creation of networks between companies in the EIP, as well as between EIPs and the community, higher economies of scale are obtained as the result of an extensive network of organisms, connectivity between different organisms increases and absolute production capacity rises regarding the base resources and skills that can be found in this environment. On the other hand, this creation of synergies increases dependence between the network members. A high degree of dependence leads to company vulnerability. Changes in a company‘s production process can lead to new by-products and waste and the consequent modification to the raw materials supply chain. The search for new suppliers may lead to costs that are too high for company feasibility. The risks and costs associated with by-product and waste transactions also increase, thus leading to further difficulties in management activities. Lastly, a greater distance between companies also impairs the use of communal

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services and infrastructures, which does not allow cost-sharing. Likewise, innovation in other areas such as architecture or new technologies is more difficult.

3.4. Development Situation at an International Level The situation and evolution of experiences in these industrial eco-systems has been compiled in several scientific works over the last decade (Côté & Cohen-Rosenthal 1998, Lambert & Boons 2002, Gibbs 2005, Korhonena & Snäkin 2005, Gibbs & Deutz 2007). Figure 5 summarises an approximate percentage distribution of eco-industrial parks around the world (from 110 documented eco-parks). The main areas where these initiatives are concentrated are Western Europe (United Kingdom, The Netherlands, France), North America and Eastern Asia (China, Japan, The Philippines), coinciding with the most developed countries and those in economic expansion.

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Table 1. Features of the different scales of application of sustainable industrial areas

Figure 5. Distribution of Eco-Industrial Parks (EIPs) by continents

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North America. The concept of EIP was mainly applied to pre-existing industrial areas or to the rehabilitation of urban areas. In order to achieve the development of these parks they have sought to establish exchange networks for waste, water and energy. Most of them are characterised by having an electric centre, steam and electricity generation centre or cogeneration centre that is intended to act as the centre of the park, supplying electricity or steam to the other industries in order to optimise energy use. The industrial activities are quite varied: by-product recovery, compost manufacturing, recycling of different products, tire processing, chemical industries, fertiliser manufacturing, energy industries, steel manufacturing, automobile industry, oil refineries, development of technologies that are more environmentally friendly, food processing, electronic and electrical component manufacturing.

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Europe. The nature and concept of EIPs is varied. Part of them are built around the development of environmental technologies, development of renewable energies, recycling and reuse of waste, as well as providing environmental education. A second type of industrial park is that combining the development of environmental technologies with services companies (advisory service, engineering, feasibility studies, lab analyses…). A third type is the product of applying industrial ecology principles to pre-existing industrial areas. There is a wide variety of production activities (chemical, textile, mining, biotechnology industries; manufacturing of plastic, paper, electronic and electrical components, cars, construction materials, pharmaceutical products, pipes, storage tanks; processing of food products) that coexist in the same industrial area. Within this group of industrial parks we should highlight the industrial symbiosis in the Styrian Recycling Network (Austria) and especially The Symbiosis Institute (Denmark), commonly known as Kalundborg eco-park. However, development of newly created sustainable industrial parks is an initiative that has still not achieved the expected rate of success in its implementation. Asia. There are many initiatives in the development of industrial ecology principles, located mainly in China, Japan, India and Thailand and materialised both in local EIPs and in eco-industrial networks and eco-cities. The Fujisawa eco-park is the main initiative in Japan. It was built on a pre-existing industrial area, where there are plans for integrating residential areas in the future. The main goal is to achieve zero emissions. Eco-city projects came about in Japan as consequence of a waste treatment crisis (Lowe 2001). The aim of these initiatives is to involve both the industries and the community in waste management, which is beneficial to the local economy. This project has government economic and technological support and the only condition required from participating enterprises is that they apply programmes to reduce energy use and promote recycling. These projects also promote the development of high technology applied to environmental management. There are several eco-city projects and each one is different. Some of them try to develop eco-parks or by-product exchanges at a regional level, whereas others focus on technologies for recycling. Regardless of the geographical scale of application, the feature that is common to most of the documented experiences is the building of networks for exchange of materials and energy between companies. Furthermore, this formulation has been applied mainly in pre-existing industrial areas instead of new developments. The main reason put forth for this is the

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excessive difficulty in deciding on the optimal combination of companies that are to be situated in a certain industrial area based on the creation of these exchange networks. Therefore, aside from exceptional cases of EIPs that were planned as an end in themselves, most of the experiences are based on rehabilitation and transforming the existing industrial systems into eco-industrial systems. The detailed information provided by certain specific cases of EIPs also shows that they have been a solution in situations of economic crisis, by promoting the industrial base, or as a solution to environmental problems for reducing pollution rates.

4. ORGANISMS INVOLVED AND MANAGEMENT OF EIPS

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4.1. Organisms Involved The development and performance of any type of industrial area requires the participation and collaboration of different organisms that are internal and external to the community where it is situated. The industrial area community is comprised of the social, environmental and economic system where it is located. This community is the source of the labour required for the area to work; it may also be a source of resources, and is the one most affected by the environmental impact of the new industrial park at a local level. Regarding the organisms external to the community, these are companies that establish relationships with the industrial park members to promote exchanges of resources, services and information that are beneficial to both parties. The internal organisms of the community where the area is installed and their main goals are: Administration. The goals may include reduction of the unemployment rate, increase of income from taxes or improvement of local environmental conditions. The Administration may work from the central, autonomous and local levels. Population. The aims include achieving good working, education and income conditions and improvement of environmental quality. The workers offer their labour and skills to attain these aims. Other companies. Their aim is to establish relations with the industrial area, the result of which will allow them to obtain mutual benefit in the exchange of goods and services. Industrial area. The aim varies depending on the perspective of the companies that make up the industrial area, of the developer or the manager. When the developer‘s function is limited to the development and marketing of the plots, his main aim is economic benefit. However, in the case of companies and managers, their aim may be, in addition to socioeconomic benefits, to attain an equilibrium with the surrounding area that guarantees a better quality of life for the population and feasibility and future growth of the industrial area. In order to achieve these aims the infrastructures, buildings and services of the park must be designed efficiently by the companies that are installed, developers and managers. The developers and managers of the industrial area may be public or private.

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Table 4. Functions of the organisms involved in the development of an EIP ORGANISM FUNCTIONS Community where the industrial area is installed Administration. Definition of the performance objectives of the industrial area. Establishment of environmental standards for the industrial area‘s operation (limits on noise, smoke, dust, smells, vibration, lighting…). Search for industries suited to be located within the industrial area. Development of strategies for financing the industrial area. Increase of efficiency in land use, administrative procedures and development of environmental laws that increase flexibility for carrying out by-product exchanges. Financing of technological development and transfer programmes, in addition to providing the technical training required for their correct use. Industrial area. Developer Choice of location that will maximise the economic and environmental benefits of the industrial area. Design of infrastructures within the industrial area that cater to the needs of the companies for specialised services. Design of industrial services that offer the necessary flexibility to allow the park to grow and evolve. Design of buildings that maximise energy and materials efficiency. Use of construction practises that are environmentally-friendly. Manager Guarantee the park‘s future feasibility. Management of the design and process development. Maintain relationships between companies. Manage the park‘s property and maintenance of the shared infrastructures and services. Companies Cost-profit analysis of the location within a sustainable industrial area. Selection of the companies to establish relationships with. Search for the most suitable technologies. Marketing activities towards clients and the general public on belonging to a sustainable industrial area. Population. Offer their labour, skills and cooperation. Other Establish cooperation relationships with the different organisms of the companies. community (administration, industrial area, population and other businesses). Clients from outside the community who establish relationships with the community.

Collaboration and coordination of the organisms is the predominant feature in the planning of EIPs. Table 4 summarises the functions and responsibilities entailed in addressing a strategy of this type for the organisms involved. Prior experiences have proven the essential role of Universities and Technological Centres as active agents in the design and simulation of proposals and in bringing together the interests of all the parties involved. For example, the Management Faculty of the University of Dalhousie (Halifax) studied the Burnside Industrial Park (Dartmouth) to develop the principles, guidelines and strategies for its rehabilitation into an eco-industrial park (Côte & Hall 1995, Peck and Associates & Dalhousie University 1997). Other examples are the cases of the Environmental and Political Studies Department of the University of Utrecht (Lowe 2001), Industrial Ecology Centre of the University of Yale (Harper & Graedel 2004) or the Eco-planning and Development Institute of the University of Technology of Dalian (Zhu & Côte 2004).

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4.2. Forms of Management Areas given over to industrial parks usually offer services of public lighting, waste collection, water, electricity and telephone outlets on the different plots available. Once the park is built and the different plots have been sold or partially or fully rented, companies begin their activities. The park operations entail that in time maintenance of the infrastructures is required in order to guarantee the correct performance of the different businesses located there. However, it is quite common that by then the developer company has already become disassociated from the park. This situation leads to management being non-existent and the companies installed in these parks are not very competitive as opposed to others that do have all of the basic infrastructures and even additional services. Diversity and quality of the services has become an essential requirement for modern parks. Additional services, which until recently had been implemented in a fashion parallel to their growth, have become today an important part of the package offered by industrial locations. The services offered in a modern industrial area could be classified in a first category of general communal services, a second category of optional services (advanced telecommunications, personalized maintenance, labour and legal advisory, leisure, bank services, logistics…) and a third emerging type of service for parks that are governed by industrial ecology principles. These services comprise environmental information systems, communal infrastructures and sustainable park management. The provision and maintenance of these complementary services become an important requirement for the park to be attractive as an area for a company to locate to. The organism in charge of management is an essential figure for promoting relations between the enterprises and improving their competitiveness. Therefore different management forms are presented and summarised in Figure 6. In the United States and in Europe the most common management forms are private and public-private. However, private management in all of its forms has gained substantially in importance in recent years. In the particular case of Spain, the implementation of management organisms in industrial areas is quite poor. In the cases where there is a managing organism, it is usually public or public-private. Although the creation of partnerships comprising the companies located in the industrial area is a growing initiative, its implementation is still rare, and is limited solely to parks of a certain size.

Figure 6. Management options for industrial areas

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5. BENEFITS AND LIMITATIONS OF EIPS Planning and development of an eco-park requires an in-depth study of the system and area of influence in each case. In general, however, a series of benefits and limitations can be identified (Lowe & Evans 1995, Tudor et al. 2007).

5.1. Benefits The advantages can be classified as benefits for the industry, environment and society. Benefits to Industry. An eco-industrial park offers the opportunity to decrease production costs through increased materials and energy efficiency, waste recycling and elimination of practices that incur regulatory penalties. Increased efficiency may also enable park members to produce more competitive products. In addition, the costs in which companies incur individually (costs for infrastructure, research and development and the cost of design and maintenance of sophisticated information systems) can also be shared between all of the companies in the park. The added value of the projects increases for developers and for the companies managing the park.

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Benefits to the environment. This planning model of industrial park represents the establishment of sustainable development principles. Its own dynamics promotes innovation in systems for pollution prevention, energy efficiency, resource recovery and other environmental management technologies. Furthermore, and what may be the most important point, is that each park will serve as a working model for future eco-parks and other environmentally friendly forms of operation. Benefits to society. Eco-industrial parks offer governments a laboratory for creation of policy and regulations that are more effective for the environment, while less burdensome to businesses. If joint operations between companies are achieved, this would make parks a powerful tool for economic development. At the same time, communities can benefit from the new jobs created in industrial plants that are much more environmentally friendly.

5.2. Limitations The hurdles and limitations that have to be overcome refer to issues of coordination and communication between the organisms involved, technological factors, system fragility, financing capacity and definition framework. Coordination and communication. The complex structure and the agents involved in the EIPs lead to difficulties in communication and coordination. These difficulties are mainly due to the fact that companies are separate entities, with different management and personnel structures, therefore their company values are different, as well as the way in which their employees relate and communicate. Among companies competition also prevails over

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cooperation, because they perceive the latter as a high increase in costs. On the other hand, industrial areas are conceived as isolated areas, not accessible to the public, which hinders cooperation between companies and the social environment that surrounds them. Technological limitations. The establishment of materials and energy exchange networks may be greatly hindered by technological factors. The creation of symbiotic networks requires production processes of a modular design, which would allow improvements in the different stages of obtaining the product without having to modify the whole process. On the other hand, the production processes implemented by the companies were not designed with the capacity to absorb the waste and energies from other processes, which hugely complicates the creation of exchanges. Potential fragility of the system. The potential fragility of EIPs also hinders their development. A small industrial network is vulnerable to any company leaving or seeking other places for its materials/ products, which could affect the functioning of the entire chain. One possible strategy to deal with this fragility could be diversification regarding suppliers and resources, so that the system could adapt quicker to the changes. In fact, a diverse system with a strong inter-sector cooperation is more sustainable. However, it might be quite complicated to achieve a large diversity because conflicts in values, preferences, interests and needs may arise, as well as an increase in transaction costs.

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Market uncertainty. The closing of cycles (materials and energy) may be affected by fluctuations in the entry price or by its substitute or by changes in the markets, entries to the industrial process or in production/purifying technologies. The political climate and the lack of guarantees that demand for a specific product will remain constant over time may also be decisive factors. Financing capacity. The differences between developed and developing countries, regarding availability of resources and economic-environmental policies have an impact on the development of EIPs. For example, developing countries, due to their financial limitations, have tended to partner with agencies such as the UNDP (United Nations Development Programme) and UNEP (United Nations Environmental Programme) to develop their EIPs. Access to financing is obviously an important aspect in the starting up and continuity of EIPs. Legislation also tends to vary from country to country, and this is the case of the countries signing the Kyoto Protocol on climate change. Consequently, environmental strategies and incentives aimed at changing resource management also vary from country to country. Having the necessary legal instruments as well as political support are important aspects in the creation of the optimal climate for development of EIPs. We can thus conclude that the EIP models should be adapted to each country. Responsibility and awareness. Lastly, the lack of precise definitions that mark what industrial development is and the functions proper to the different organisms involved are restrictive aspects, as well as the lack of knowledge on the potential of industrial ecology and of technologies, practices and management systems that should be implemented in the planning, development, management and operation stages of EIPs.

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If these barriers and limitations are to be overcome, joint efforts between the industry and its environs must be made, so that all of the organisms participating in the development and operation of an EIP are fully integrated. At present there is limited knowledge on these concepts, as well as a certain dislike of the idea of establishing exchanges between companies and commercial or residential areas, therefore it is necessary to work on showing companies and the general public the many advantages of this new concept of industrial park. Lastly, it is important to highlight that although it is possible to learn from the development of other industrial ecosystems, each one has its own particularities regarding social, economic, cultural and ecological aspects that are not easily extrapolated.

6. CONCLUSION We can conclude that industrial ecology is the motivating discipline of a new model of industrial park. International experiences show the economic and environmental benefits obtained on the different geographic scales of application. However, changes towards a new development model are not easy and they require a firm commitment based on knowledge and joint work of all the agents involved. Planning and design of eco-industrial parks and transformation of the existing ones entail the development of new management models based on organization and cooperation. Administrations, developer organisms and managers of industrial parks currently face the challenge of joining forces to seek new formulas that make this possible. This is a basic and essential element to promote companies‘ competitiveness through the exchange of material resources, energy and information between the businesses comprised in the industrial area system.

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REFERENCES Chertow, M. R. (2004). Industrial Symbiosis. Encyclopedia of Energy, 3, 407-415. Côté, R. P. & Cohen-Rosenthal, E. (1998). Designing eco-industrial parks: a synthesis of some experiences. Journal of Cleaner Production, 6, 181-188. Côte, R. P. & Hall, J. (1995). Industrial parks as ecosystems. Journal of Cleaner Production, 3, 41-46. Erkman, S. (2003). Perspectives on Industrial Ecology. In D. Bourg, & S. Erkman, (Eds.), Perspectives on Industrial Ecology, (338-342). Sheffield, UK: Greenleaf Publishing Limited. Fernández, I. & Ruiz, M. C. (2009). Descriptive model and evaluation system to locate sustainable industrial areas. Journal of Cleaner Production, 17, 87-100. Fernández, I. (2009). Desarrollo de un modelo de localización y contribución al diseño de la operación de áreas industriales sostenibles. PhD. Thesis, Transport and Projects Technology and Processes Department, University of Cantabria, Spain. Fiksel, J. (2003). Designing Resilient, Sustainable Systems. Environmental Science & Technology, 37, 5330-5339. Gibbs, D. & Deutz, P. (2005). Implementing industrial ecology? Planning for eco-industrial parks in the USA. Geoforum, 36, 452-464

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Gibbs, D. & Deutz, P. (2007). Reflections on implementing industrial ecology through ecoindustrial park development. Journal of Cleaner Production, 15, 1683-1695. Graedel, T. E. & Allenby, B. R. (2003). Industrial Ecology. New Jersey: Prentice Hall. Harper, E. M. & Graedel, T. E. (2004). Industrial ecology: a teenager‘s progress. Technology in Society, 26, 433-445. Korhonena, J. & Snäkin, J. (2005). Analysing the evolution of industrial ecosystems: concepts and application. Ecological Economics, 52, 169-186. Lambert, A. J. D. & Boons, F. A. (2002). Eco-industrial parks: stimulating sustainable development in mixed industrial parks. Technovation, 22, 471-484. Lowe, E. A. & Evans, L. K. (1995). Industrial ecology and industrial ecosystems. Journal of Cleaner Production, 3, 47-53. Lowe, E. A. (2001). Eco-industrial park handbook for Asian Developing Countries. http://indigodev.com/ADBHBdownloads.html Lowe, E. A., Moran, S. & Holmes, D. (1996). Fieldbook for the development of ecoIndustrial parks. Oakland, CA: Indigo Development. Martin, S. A., Weitz, K. A., Cushman, R. A., Sharma, A., Lindrooth, R. C. & Moran, S. R. (1996). Eco-industrial parks: a case study and analysis of economic, environmental, technical and regulatory issues. North Carolina, USA: Research Triangle Institute. Munier, N. (2005). Introduction to Sustainability: road to a better future. Dordrecht: Springer. Oh, D. S. & Kim, K. B. (2005). Eco-industrial park design: a Daedeok Technovalley case study. Habitat International, 28, 268-284. O‘Rourke, D., Connelly, L. & Koshland, C. (1996). Industrial Ecology: A Critical Review. International Journal of Environment and Pollution, 6, 89-112. Peck and Associates & Dalhousie University (1997). Promoting eco-industrial park development: exploring challenges, drivers and opportunities for progress in Canada. A report for Environment Canada and Industry, Canada, Ottawa. Pennington, D., Wolf, M. Aa., Bersani, R. & Pretato, U. (2007). Overcoming barriers to the broader implementation of life cycle thinking in business and public administration– Preface. International Journal of Life Cycle Assessment, 12, 459-460. Salmi, O. (2007). Eco-efficiency and industrial symbiosis - a counterfactual analysis of a mining community. Journal of Cleaner Production, 15, 1696-1705. Smith, D. (1971). Industrial location: an economic geographical analysis. New York: John Wiley & Sons. Thabrewa, L., Wiekb, A. & Riesa, R. (2009). Environmental decision making in multistakeholder contexts: applicability of life cycle thinking in development planning and implementation. Journal of Cleaner Production, 17, 67-76. Trinder, B., Fohl, A. & Shayt, D. H. (1993). The Blackwell Encyclopedia of Industrial Archaeology. Oxford: Blackwell Publishers. Tudor, T., Adam, E. & Bates, M. (2007). Drivers and limitations for the successful development and functioning of EIPs (eco-industrial parks): a literature review. Ecological Economics, 61, 199-207. Walcott, S. M. (2009). International Encyclopedia of Human Geography, 408-412. WCE, World Commission on Environment, (1987). Our Common Future. The Brutland Report. Oxford: Oxford University Press.

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Yang, P. P. & Lay, O. B. (2004). Applying ecosystem concepts to the planning of industrial areas: a case study of Singapore‘s Jurong Island. Journal of Cleaner Production, 12, 1011-1023. Zhu, Q. & Côte, R. P. (2004). Integrating green supply chain management into an embryonic eco-industrial development: a case study of the Guitang Group. Journal of Cleaner Production, 12, 1025-1035.

In: Environmental Planning Editor: Rebecca D. Newton

ISBN: 978-1-61728-654-4 © 2011 Nova Science Publishers, Inc.

Chapter 9

DEVELOPING A DROUGHT PLANNING EVALUATION SYSTEM IN THE UNITED STATES Mark Svoboda and Zhenghong Tang* 1

National Drought Mitigation Center, School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE, U.S.A. 2 College of Architecture, University of Nebraska-Lincoln, Lincoln, NE, U.S.A. 68588-0105

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1. INTRODUCTION Drought is a normal part of the climate cycle, affecting every climate regime on the planet. Drought indicates a special period in which an unusual moisture scarcity causes a serious hydrological imbalance. Drought is related to the timing and effectiveness of the rains, high temperature, high wind, and low humidity. The typical impacts of drought may include dry lands, low or empty water-supply reservoirs, low groundwater levels (dried up wells), crop damage, and ensuing environmental degradation. In the United States, drought accounts for losses in the billions of dollars. In fact, a FEMA (1995) report estimates the average annual losses due to drought at $6-8 billion, on a par with hurricanes, making these the two most costly hazards impacting our country. Drought often affects several sectors (agriculture, recreation and tourism, energy, forestry, and others) at the same time and typically impacts large areas and many people. These impacts serve as indicators of our vulnerability and risk during extended periods of rainfall deficits. Our vulnerability to drought is affected by (among other factors) population growth and shifts, urbanization and sprawl, demographic characteristics, technology, water use trends, government policy, social behavior, and environmental awareness. These factors are continually changing, and society‘s vulnerability to drought can increase or decrease in response to these changes. Although drought is a natural hazard, society can reduce its *

Corresponding author: Phone: Email: [email protected] , (402) 472-9281; Fax: (402) 472-3806.

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vulnerability and therefore lessen the risks associated with drought episodes. The impacts of drought, like those of other natural hazards, can be reduced through mitigation and preparedness. Planning ahead in an attempt to mitigate drought gives decision makers the chance to relieve the most suffering at the least expense. Reacting to drought in ―crisis mode‖ decreases self-reliance and increases dependence on government and donors (Wilhite and Pulwarty, 2005). As a proof of concept approach, this paper looks into the process of comparing and evaluating state drought plans within the United States. The idea of evaluating (scoring) drought plans may be new, but similar methods have been applied to other hazards and in other planning fields, such as the environmental and urban/rural planning sectors (Baer 1997; Berke 2000; Brody 2003; Tang et al. 2008). Even so, the planning profession itself has developed relatively few criteria for evaluating the quality of plans, so plan quality is difficult to define (Baer 1997). Now, and in a changing climate with changing vulnerabilities, Brody (2003) aptly notes that planners must be flexible, adapting and planning for changing conditions by gearing their efforts more toward uncertainty and surprise. Thus, the purpose of this paper is to assess the potential transferability of evaluation techniques in other fields and hazards to the evaluation of drought plans in the United States.

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2. THE CURRENT STATE OF DROUGHT PLANNING One of the core missions of the U.S. National Drought Mitigation Center (NDMC) is to assist various entities in developing drought plans. Drought preparedness plans promote a more proactive risk management approach to drought management. They help people reduce their vulnerability to drought and dependence on emergency assistance from governments and international aid organizations. The process of developing a plan will identify vulnerable areas, population groups, and economic and environmental sectors. The process also seeks to identify data and informational gaps and research and institutional needs. Ultimately, preparedness plans will improve coordination and integration within and between levels of government; procedures for monitoring, assessing, and responding to water shortages; information flow to primary users; and efficiency of resource allocation. The goals of these plans are to reduce water shortage impacts, personal hardships, and conflicts between water and other natural resource users. These plans should promote self-reliance by systematically addressing issues of principal concern to the region or nation in question (Wilhite et al., 2005). The complexity of drought impacts requires a preventive, anticipatory approach to risk reduction. How can governments reduce their vulnerability to drought? The first steps involve the formulation of a drought policy with clearly stated objectives and the development of a preparedness plan that lays out a strategy to achieve these objectives. In 1983, only three states had drought plans. Progress since that time has brought the total to 37, with the latest efforts focused on developing drought plans that are more proactive, or ―mitigative‖, in nature (as noted in blue in the figure below). Drought preparedness plans contain three critical components: (1) a comprehensive early warning system, (2) risk and impact assessment procedures, and (3) mitigation and response strategies (Wilhite et al.,2005). These components complement one another and represent an integrated approach

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that addresses both short- and long-term management and mitigation issues. More details on the specific indicator criteria will be described in the following section.

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3. EVALUATION METHODS AND CRITERIA In the mid-1990s, scholars identified a series of indicators for quantitatively assessing plan quality (Berke et al. 1997). Berke (1998) highlights the role of state growth management in reducing natural hazards risks. Similar frameworks are used to measure the quality of natural hazard planning on a local scale (Berke et al. 1996; Godschalk et al. 1999). Burby et al. (1999, 2000) further proposed the creation of hazard-resilient communities through landuse planning. These studies in the middle and late 1990s have greatly advanced our understanding on plan quality of natural hazard elements and provide an insight on the influence factors on hazard management plan quality (Baer 1997; Burby and Dalton 1994; Berke 1995; Berke and French 1994; Berke et al. 1996; Berke et al. 1997; Burby et al. 1997; Godschalk et al. 1998). However, no research has been done to evaluate drought planning quality. This study uses the following framework to evaluate drought planning quality.

3.1. Scoring This study adopted and applied a modified scoring system based on a 0-5 (with 5 being the highest score) scale following the examples of readings and case studies. The drought

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plan criteria chosen below were taken and modified from Wilhite et al.‘s (2000) 10-Step Drought Planning Process, a methodology designed to serve as a checklist for planners interested in developing a state drought plan. The respective strengths and weaknesses of the state plans evaluated were used to assign evaluation scores to each criterion. The criteria chosen are described below. All criteria have been assigned equal weights with each parameter worth a maximum score of 5 and a minimum of 0 (assigned in the case of no mention at all of said criteria). Each plan is evaluated subjectively to determine what indicators (criteria) have been integrated (or at least mentioned/considered in the plan‘s language) into the respective drought plans. The study is only aimed at evaluating those states that already have a plan and not those that are currently developing one.

3.2. Evaluation Criteria Most of the evaluation criteria below have been taken from Wilhite et al. (2000) and have been modified, or added to, for the purposes of this paper. The full descriptions of most of these criteria can be found on the National Drought Mitigation Center‘s website (from Wilhite) at drought.unl.edu. The criteria chosen for this exercise are:

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3.2.1. Have a plan The most fundamental criterion is whether the state has a drought plan. If not, the score assigned would be ―0‖. Full credit and a score of ―5‖ is given regardless of whether the plan is response oriented or mitigative in nature. 3.2.2. Have a mitigation plan Additional credit is given to those states that have completed a plan that is proactive and mitigative in nature. A score of ―5‖ will be given if the state‘s drought plan is considered to be a mitigation plan as determined by the National Drought Mitigation Center (2009) in their ―Status of State Drought Plans‖ assessment, found at http://drought.unledu/mitigate/ status. htm. Response plans, multi-hazard plans containing a drought component, or other operational plans (such as water plans) can receive partial scoring credit if mitigation wording or future risk assessment or mitigation actions are at least mentioned or considered. 3.2.3. Drought task force A key political leader initiates the drought planning or oversight process through appointment of a drought task force. The task force has two purposes. First, it supervises and coordinates development of the plan. Second, after the plan is developed and during times of drought when the plan is activated, the task force coordinates actions, implements mitigation and response programs, and makes policy recommendations to the appropriate political leader(s). The task force should reflect the multidisciplinary nature of drought and its impacts, and it should include appropriate representatives of government agencies (provincial, federal) and universities where appropriate expertise is available. Environmental and public interest groups and others from the private sector can be included as appropriate. The task force should include a public information official who is familiar with local media‘s needs and

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preferences and a public participation practitioner who can help establish a process that includes and accommodates both well-funded and disadvantaged stakeholder and interest groups.

3.2.4. Purpose and objectives The general purpose and objectives for the drought plan should be clearly stated. Government officials should consider many questions as they define the purpose of the plan:

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Purpose and role of government in drought mitigation and response efforts Scope of the plan Most drought-prone areas of the state or nation Historical impacts of drought Historical responses to drought Most vulnerable economic and social sectors Role of the plan in resolving conflict between water users and other vulnerable groups during periods of shortage Current trends (e.g., land and water use, population growth) that may increase or decrease vulnerability and conflicts in the future Resources (human and economic) the government is willing to commit to the planning process Legal and social implications of the plan Principal environmental concerns caused by drought The plan should be aimed at providing government with an effective and systematic means of assessing drought conditions, developing mitigation actions and programs to reduce risk in advance of drought, and developing response options that minimize economic stress, environmental losses, and social hardships during drought. The plan should also identify specific objectives that support the purpose of the plan. Drought plan objectives will vary within and between countries and should reflect the unique physical, environmental, socioeconomic, and political characteristics of the region in question. For a provincial, state, or regional plan, objectives that should be considered include the following: Collect and analyze drought-related information in a timely and systematic manner. Establish criteria for declaring drought emergencies and triggering various mitigation and response activities. Provide an organizational structure and delivery system that ensures information flow between and within levels of government. Define the duties and responsibilities of all agencies with respect to drought. Maintain a current inventory of government programs used in assessing and responding to drought emergencies.

3.2.5. Stakeholder participation Social, economic, and environmental values often clash as competition for scarce water resources intensifies. Therefore, it is essential for task force members to identify all citizen

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groups (stakeholders) that have a stake in drought planning and understand their interests. These groups must be involved early and continuously for fair representation and effective drought management and planning. Discussing concerns early in the process gives participants a chance to develop an understanding of one another‘s various viewpoints and generate collaborative solutions. Although the level of involvement of these groups will vary notably from location to location, the power of public interest groups in policy making is considerable. In fact, these groups are likely to impede progress in the development of plans if they are not included in the process. The task force should also protect the interests of stakeholders who may lack the financial resources to serve as their own advocates. One way to facilitate public participation is to establish a citizens‘ advisory council as a permanent feature of the drought plan, to help the task force keep information flowing and resolve conflicts between stakeholders.

3.2.6. Resources inventory and risk assessment An inventory of natural, biological, and human resources, including the identification of constraints that may impede the planning process, may need to be initiated by the task force. In many cases, provincial and federal agencies already possess considerable information about natural and biological resources. It is important to determine the vulnerability of these resources to periods of water shortage that result from drought. The most obvious natural resource of importance is water: its location, accessibility, and quality. Biological resources refer to the quantity and quality of grasslands or rangelands, forests, wildlife, and so forth. Human resources include the labor needed to develop water resources, lay pipeline, haul water and livestock feed, process citizen complaints, provide technical assistance, and direct citizens to available services. In drought planning, making the transition from crisis to risk management is difficult because, historically, little has been done to understand and address the risks associated with drought. To solve this problem, areas of high risk should be identified, as should actions that can be taken to reduce those risks before a drought occurs. Risk is defined by both the exposure of a location to the drought hazard and the vulnerability of that location to periods of drought-induced water shortages (Blaikie et al., 1994). Drought is a natural event; it is important to define the exposure (i.e., frequency of drought of various intensities and durations) of various parts of the state or region to the drought hazard. Some areas are likely to be more at risk than others. Vulnerability, on the other hand, is affected by social factors such as population growth and migration trends, urbanization, changes in land use, government policies, water use trends, diversity of economic base, and cultural composition. 3.2.7. Identify research and data gaps and needs As research and data needs and gaps in institutional responsibility become apparent during the drought planning process, the drought task force should compile a list of those deficiencies and make recommendations to the appropriate person, or government body, on how to remedy them. For example, the monitoring committee may recommend establishing an automated weather station network or initiating research on the development of a climate or water supply index to help monitor water supplies and trigger specific actions by state government.

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3.2.8. Dissemination and education If the public has been engaged throughout the process of establishing a drought plan, there may already be better-than-normal awareness of drought and drought planning by the time the plan is in place. During drought, the task force should work with public information professionals to keep the public well informed of the status of water supplies, whether conditions are approaching ―trigger points‖ that will lead to requests for voluntary or mandatory use restrictions, and how victims of drought can access assistance. All pertinent information should be posted on the drought task force‘s website so that the public can get information directly from the task force without having to rely on mass media. A broad-based education program to raise awareness of short- and long-term water supply issues will help ensure that people know how to respond to drought when it occurs and that drought planning and awareness does not lose ground during non-drought years.

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3.2.9. Coordination and implementation The drought plan should have three primary components: (1) monitoring, early warning, and prediction; (2) risk and impact assessment; and (3) mitigation and response. A committee should be established to focus on the first two of these needs; the drought task force can in most instances carry out the mitigation and response function. The committees will have their own tasks and goals, but well-established communication and information flow between committees and the task force is necessary to ensure effective planning. Plans must clearly define agency/entity roles and responsibilities in order to ensure good communication and smoother implementation during a drought crisis. Plans will be evaluated with an eye on assessing how the above factors are integrated within the plan. 3.2.10. Evaluation and revision of the plan Periodic testing, evaluation, and updating of the drought plan are essential to keeping the plan responsive to local, state, provincial, or national needs. Two modes of evaluation (ongoing and post-drought) are needed to maximize the effectiveness of the system. To ensure an unbiased appraisal, governments may wish to place the responsibility for evaluating drought and societal response to it in the hands of nongovernmental organizations such as universities or specialized research institutes.

4. CASE STUDIES From the 37 state drought plans in place, we chose 4 to initially test the scoring system. In choosing the plans, the goal was to choose one plan that is a traditional response, or operating, plan. Two of the plans are mitigation plans, as determined by the NDMC, and the fourth plan is one that delegates planning authority to the local level. The plans were also chosen based on geographic location to account for different drought characteristics and planning methods in the East, Southeast, Southwest, and Great Plains. The states chosen were Nebraska (mitigation plan), New Mexico (mitigation plan), Florida (delegated to local authorities) and Connecticut (response plan). All of these plans can be found on-line at http://drought.unl.edu/plan/stateplans.htm.

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5. RESULTS AND CONCLUSIONS The results of the evaluation exercise below (Table 1) show the comparison of the drought plans according to the evaluation criteria outlined above. As expected, the mitigation oriented plans in New Mexico (48 out of 50) and Nebraska (39) graded the highest using this evaluation scheme. However, a high score does not necessarily indicate a complete plan. For example, Nebraska‘s plan does not provide any real backing for evaluation or revision, and little attention is given to research and data needs. New Mexico does stand out by far as having the most complete plan of those evaluated. Many states have used the New Mexico plan as a model to emulate in many regards. It had very few weaknesses when analyzed with the 10 criteria chosen for this study. Perhaps a survey tool or more thorough research would reveal some weaknesses, but this plan was well thought out and, according to a quick review of their website, it is still being used and implemented as of early 2010. Connecticut and Florida both scored 34 out of a possible 50. This is not surprising given the operational response-oriented nature of the plan in Connecticut, which is much more geared toward water supply and demand. In the case of Florida, planning for drought is delegated to the local authorities (usually water oriented) who are in charge of managing their water resources during times of drought. To their credit, both Florida and Connecticut mention the need for future mitigative actions and risk assessments. As outlined in the scoring criteria, partial credit is given for considering these criteria even though these two state plans are clearly oriented more toward response activities. Incidentally, these same two states also score lower marks in the area of resources inventory and risk assessment. Again, this type of activity is more mitigative in nature, and it illustrates what ultimately sets states with a proactive, mitigative approach apart from states that don‘t take such an approach. The recent trend in drought planning over the past decade or so has been more focused on mitigation planning, and this is the approach the NDMC recommends to the states we work with. This study only looked into a few of the many potential drought plan indicator criteria given the time constraints of undertaking a more thorough research approach. Further research might include a thorough review of all state drought plans or a more detailed look into state drought mitigation, response, and monitoring efforts. Such studies could help document what works best in the drought planning arena, and they would fill a unique research niche.

6. POLICY RECOMMENDATIONS From the results of these four state drought plan quality evaluations, this paper provides the following policy recommendations. First, state-level drought management agencies need to improve the factual basis of drought plans. One of the important functions in drought plans is to identify potential drought risk areas if they are to plan appropriately for the future. State drought planning should provide timely and systematic data collection, data analysis, and data dissemination of drought-related information. It is important for state-level drought management agencies to identify and designate drought-affected areas of the state. The drought-affected areas provide the factual base for drought management decision makers to trigger the phasing in and out of

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various drought risk assessment and drought response activities by inter-organizational agencies during times of drought. The state-level drought plan should include a vehicle for the timely and accurate reporting and/or assessment of drought impacts on agriculture, tourism, industry, wildlife, and human health. Table 1. Comparison of state drought plans utilizing evaluation criteria DROUGHT PLAN

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Have a Drought Plan Mitigation Plan Task Force Purpose & Objectives Stakeholder Participation Resources Inventory and Risk Assessment Research and Data Needs Dissemination and Education Coordination and Implementation Evaluation and Revision Total Score

New Mexico

Nebraska

Florida

Connecticut

5 5 5 5 5

5 2 4 5 4

5 5 5 5 5

5 2 3 5 2

5

2

5

2

1

2

4

4

4

5

5

4

3 1 39

4 1 34

4 5 48

4 3 34

Second, state agencies should commit appropriate resources and practical objectives to their drought preparedness, response, mitigation, and recovery plans. Drought plans need adequate drought awareness and a strong commitment by the public and decision makers in supporting drought preparedness. Increasing drought awareness and recognition of drought as a natural hazard among the multiple local jurisdictions is an effective way to reduce drought risk. The goals and objectives for drought management should be clear and applicable. Third, inter-organizational coordination for drought planning and monitoring is extremely important because droughts are slow onset in nature, relatively longer in duration, and typically impact larger spatial regions, and they do little in the way of structural damage when compared to other natural hazards. The state drought plan needs to define a process aimed at guiding multiple state-level agencies to better coordinate their drought-related activities. The successfully integrated drought plan can coordinate the monitoring, communication, risk assessment, vulnerability assessment, and preparedness activities for successively dealing with more severe drought stages. The state drought plan also needs to identify the primary responsibilities of the state and local entities for managing drought-related activities. In addition, it is important to promote effective mobilization of public and private resources in managing drought mitigation efforts. An effective drought plan should hinge on communication among multiple agencies and water suppliers and the timely dissemination of clear and succinct drought information to decision makers, the media, and the general public. Fourth, more effective policies, tools, and strategies should be introduced into state-level drought planning. The state agencies should adopt some regulatory policies (e.g., land use

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permits, special zoning, buffers, building ordinances, hazard reviews, or specific drought legislation) to help mitigate drought hazards. The state agencies should also adopt some incentives (e.g., tax abatement, density bonus, low-interest loans, voluntary community groups, or drought insurance) to mitigate the drought hazard. The drought plans should establish and pursue a series of effective policies to remove management obstacles toward the equitable allocation of water during shortages and to provide incentives to encourage water conservation. Lastly, drought plans should specify drought implementation, monitoring, and updating mechanisms and timelines. Drought plans need to clearly specify the appropriate personnel and financial resources, and responsibilities, to ensure that drought planning implementation can be realized operationally on the ground. Drought plans should set up a series of procedures aimed at evaluating and updating the plan on a continuous cycle in order to keep the plan updated and responsive to a state and its constituents‘ needs. In summary, this study is just a starting point to further develop a drought planning evaluation system in the United States. The ultimate value of the rating system is not just in comparing between plans, but is intended for individual states or entities to use in developing or evaluating their own plans with a goal of using the system to ultimately help them better their plans. Also, a good plan in terms of a rating on paper doesn‘t ensure or equate to a good plan in terms of operations. Having a good plan does provide an entity with the opportunity to use that plan or improve on that plan in the future. In the end, it is still up to the entity to follow and use the plan as well as update it on a regular basis. Future study will extend the scope from state-level drought plans to local jurisdictions‘ drought plans.

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REFERENCES Baer, W. C. (1997). General plan evaluation criteria: An approach to making better plans. J. Am. Plan. Assoc., 63(3), 329-344. Berke, P. (1995). Evaluation environmental plan quality: The case of planning for sustainable development in New Zealand. J. Environ. Plan. Manage., 37(2), 155-169. Berke, P. & French, S. (1994). The influence of state planning mandates on local plan quality. J. Plan. Educ. Res., 13, 237-250. Berke, P., Roenigk, D., Kaiser, E. & Burby, R. (1996). Enhancing plan quality: Evaluation the role of the state planning mandates for natural hazard mitigation. J. Environ. Plan. Manage., 39, 79-96. Berke, P., Dixon, J. & Ericksen, N. (1997). Coercive and cooperative intergovernmental mandates: A comparative analysis of Florida and New Zealand environmental plans. Environ. Plan. B-Plan. Des., 24, 451-468. Berke, P. R. (1998). Reducing natural hazard risks through state growth management. J. Am. Plan. Assoc., 64(1), 76-87. Berke, P. R. (2000). Are we planning for sustainable development? J. Am. Plan. Assoc., 66(1), 21-33. Blaikie, P., Cannon, T., Davis, I. & Wisner, B. (1994). At Risk: Natural Hazards, People‘s Vulnerability, and Disasters. Routledge, London, United Kingdom.

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Brody, S. (2003). Are we learning to make better plans? A longitudinal analysis of plan quality associated with natural hazards. J. Plan. Educ. Res., 23(2), 191-201. Burby, R. J. & Dalton, L. (1994). Plans can matter! The role of land use plans and state planning mandates in limiting the development of hazardous areas. Public Adm. Rev., 54(3), 229-237. Burby, R. J., Beatley, T., Berke, P. R., Deyle, R. E., French, S. P., Godschalk, D. R., Kaiser, E. J., Kartez, J. D., May, P. J., Olshansky, R., Paterson, R. G. & Platt, R. H. (1999). Unleashing the power of planning to create disaster-resistant communities. J. Am. Plan. Assoc., 65(3), 247-258. Burby, R. J., Deyle, R. E., Godschalk, D. R. & Olshansky, R. B. (2000). Creating hazard resilient communities through land-use planning. Nat. Hazards Rev., 1(2), 99-106. Burby, R. J., May, P., Berke, P., Dalton, L., French, S. & Kaiser, E. (1997). Making Governments Plan: State Experiments in Managing Land Use. Johns Hopkins Univ. Press, Baltimore, Maryland. FEMA. (1995). National Mitigation Strategy. Federal Emergency Management Agency, Washington, D.C. Godschalk, D. R., Beatley, T., Berke, P., Brower, D. J. & Kaiser, E. J. (1999). Natural Hazard Mitigation. Island Press, Washington, D.C. Godschalk, D. R., Kaiser, E. & Berke, P. (1998). Integrating hazard mitigation and local landuse planning. In Cooperating with Nature: Confronting Natural Hazards with Land-use Planning for Sustainable Communities. R.J. Burby, ed. John Henry Press, Washington, D.C., 85-118. NDMC. (2009). National Drought Mitigation Center website: http://drought.unl.edu. Tang, Z., Lindell, M. K., Prater, C. S. & Brody, S. D. (2008). Measuring tsunami planning capacity on U.S. Pacific Coast. Natural Hazards Review, 9(2), 91-100. Wilhite, D. A., Hayes, M. J., Knutson, C. & Smith, K. H. (2000). Planning for drought: Moving from crisis to risk management. J. Am. Water Res. Assoc., 36(4), 697-710. Wilhite, D. A., Hayes, M. J. & Knutson, C. L. (2005). Drought preparedness planning: Building institutional capacity. In: Drought and Water Crisis: Science, Technology, and Management Issues, D. A. Wilhite, (ed.). CRC Press (Taylor and Francis), New York, 93-135. Wilhite, D. A. & Pulwarty, R. (2005). Lessons learned and the road ahead. In: Drought and Water Crisis: Science, Technology, and Management Issues, D. A. Wilhite, (ed.). CRC Press (Taylor and Francis), New York, 389-398.

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In: Environmental Planning Editors: Rebecca D. Newton

ISBN: 978-1-61728-654-4 © 2011 Nova Science Publishers, Inc.

Chapter 10

MARINE SPATIAL PLANNING: IDENTIFYING THE CRITICAL ELEMENTS FOR SUCCESS Fanny Douvere* and Charles Ehler

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1. INTRODUCTION Human use of ocean space is rapidly expanding – a trend primarily driven by the quest for cleaner energy, food security, and the effects of climate change. Offshore renewable energy in Europe could provide 15% of its total energy demand in 20 years1. In the US, offshore wind is moving forward in Massachusetts and Rhode Island 1. While climate change is opening the Arctic ocean to new (and often contentious) proposals for economic development 2, ocean warming is likely to alter the distributions and critical habitats of fish and protected species, such as polar bears or narwhals. Further, proponents of offshore aquaculture are seeking places to meet the rising global demand for healthy seafood in the face of declining stocks of wild fish. Simultaneously, more traditional uses like recreational and commercial fishing, shipping and oil and gas extraction continue to expand their footprint in a recovering global economy 3. Around the globe, governments increasingly recognize that without more comprehensive and proactive management, the health of ocean resources will continue to decline. Without strong support for the sustainable use of ocean spaces rich in natural resources (wind, waves, oil, fish), opportunities for energy and food security, jobs, and income will remain unexplored. Without protection for ecologically critical places, conflicts between human activities and nature are inevitable, resulting in crucial natural services reduced or lost entirely. Marine spatial planning (MSP) is a pragmatic approach that can help achieve

* Corresponding author: UNESCO, Programme Specialist, 7, place de Fontenoy, 75352 Paris. Phone: +33 1 4568 1562. Email: [email protected] 1 The European Wind Energy Association estimates that 15,000 offshore wind turbines, each generating 10MW could supply about one-sixth of Europe's current energy demand by 2030; another sixth would be supplied by 75,000 onshore turbines, each generating 2MW. Available at: www.no-fuel.org/index.php?id=241

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ecological, economic and social objectives simultaneously by placing the spatial and temporal heterogeneity of the ocean at the heart of a legally authorized decision-making process 4. Both the United States and the United Kingdom have recently taken major steps to allow the development of MSP in their respective marine areas. On 9 December 2009, U.S. President Barack Obama launched a draft framework for effective coastal and marine spatial planning that aims at addressing conservation, economic activity, user conflict, and sustainable use of the U.S. ocean, coastal and Great Lakes resources 5. The draft framework could result in new authority (which is expected in the short run to take the form of a Presidential executive order) that will allow the development of a nation-wide system for MSP. A month earlier, the United Kingdom passed a Marine and Coastal Access Act that will profoundly change the way its marine areas are used 6. MSP (shortened in the UK to 'marine planning') is proposed as one of the main tools to deliver the aims of the Act. While new to some, almost a dozen other countries2 have already developed some form of MSP, starting in the 1970s in Australia’s Great Barrier Reef Marine Park 7. Recent examples, particularly in Northwest Europe, are strengthening the multiple-objective approach toward MSP while other countries, including China 8 explore innovative ways for financing MSP. Despite the fact that many governments already employ MSP, little guidance is available that illustrates how MSP can deliver successful results. Countries that currently consider, develop, or apply MSP are doing so on an ad hoc basis, each with different time frames, costs, and results. Most professionals and government officials responsible for the planning and management of marine areas and their natural resources usually have scientific or technical training in areas such as ecology, biology, oceanography, or engineering, among others. Few have been trained as professional marine planners and managers. Consequently, many professionals who want or have to develop MSP in their country wind up "learning on the job" and tend to "re-invent the wheel" over and over. This practice is often very expensive and an inefficient way to do business. A lack of understanding about MSP and what it entails, makes it also difficult for governments to define what MSP is really about and what is essential in making sure their efforts will actually lead to the suggested outcomes described in a variety of MSP definitions. The latter is particularly important now, as many confusing and conflicting viewpoints about the true nature of MSP begin to emerge.

2. MARINE SPATIAL PLANNING: FIVE ESSENTIAL CHARACTERISTICS Many advocate MSP as a promising way to achieve simultaneously social, economic, and ecological objectives by means of a more rational and scientifically-based organization of the use of ocean space. Its supporters emphasize the potential of MSP to resolve conflicts among offshore uses and between uses and the environment and stress its marked departure from single-sector management that is currently applied, but largely unsuccessful, in achieving integrated management of our oceans. 2 Countries that are exploring, designing, or implementing MSP include Belgium, Germany, The Netherlands, United Kingdom, Poland, Sweden, Norway, Australia, the United States (Commonwealth of Massachusetts), Canada and China.

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Although various MSP initiatives are still in an early stage and will only over time demonstrate how effective they really are, some initial lessons can be drawn from these experiences. When analyzing - and to some extent comparing - MSP initiatives, for example, it is possible to identify at least some important characteristics. In the context of this research, five essential characteristics of MSP were identified. They include (a) adaptation; (b) participation; (c) ecosystem-based; (d) integration; and (e) future-orientated. Although most of these characteristics are common to many other public management approaches, their value and importance is still little – if at all – considered in the context of MSP. This might be caused by the fact that MSP is a relatively young field of expertise but could also be the result of MSP being largely developed and inspired from within the marine and environmental community without many contributions from more traditional planning experts. The characteristics described in this article have been selected on the basis of a brief review of literature of planning and management practices. More importantly, they are derived from analysis of various MSP practices currently in place in different countries. The analysis included field trips to a number of offices responsible for MSP in the Netherlands, Germany, Massachusetts (United States of America), Australia and Canada. Additionally, the characteristics are partly based on the outcomes of three review meetings that were held with expert groups of marine scientists and MSP practitioners between March 2008-April 2009. They were further refined through two regional ‗fine-tuning‘ meetings, held in the Commonwealth of Massachusetts in the United States of America (from 13-17 October 2008) and Ha Noi/Ha Long Bay in Vietnam (from 1-8 April 2009)3. The sections below describe each of the characteristics and illustrate why they are critical to the development and implementation of MSP. The section concludes that even though these characteristics are in place, MSP fails without a clear, legal authority for both its planning and implementation stages.

2.1. Adaptation The phrase marine spatial planning is misleading since MSP really is part of a management process in which planning, implementation, and adaptation are all equally important components. In general, planning without implementation is sterile, implementation without planning is a recipe for failure. Integrated coastal zone management (ICZM), for example, as any other form of public management, is typically described as a process that goes through a number of stages 9. Cicin-Sain and Knecht 10 define six stages of the ICZM process, including (a) issue identification and assessment; (b) program planning and preparation; (c) formal adoption and funding; (d) implementation; (e) operation; and (f) evaluation. They further emphasize the importance of having ICZM efforts moving progressively beyond planning into implementation, enforcement and evaluation. Similar to ICZM, MSP aims at achieving multiple objectives and overcoming current fragmentation that results from single-sector management and should similarly be conducted as a management

3 For more information see the Marine Spatial Planning Initiative of the Intergovernmental Oceanographic Commission, United Nations Educational, Scientific, and Cultural Organization at: ioc3.unesco.org/marinesp

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process rather than a one-time plan. The following steps are relevant to the development of MSP as a management process 11: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

Identifying need and establishing authority Obtaining financial support Organizing the process through pre-planning Organizing stakeholder participation Defining and analyzing existing conditions Defining and analyzing future conditions Preparing and approving the marine spatial plan Implementing and enforcing the marine spatial plan Monitoring and evaluating performance of the marine spatial plan Adapting the marine spatial planning process

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These steps are not simply a linear process that moves sequentially from step to step. Many feedback loops should be built into the process. For example, goals and objectives identified early in the planning process are likely to be modified as costs and benefits of different management measures are identified later in the planning process. Analysis of existing and future conditions will change as new information is identified and incorporated in the planning process. Gaining understanding about whether or not the measures taken to implement a marine spatial plan lead to the anticipated results is only possible through monitoring and evaluation of the marine spatial plan. Eventually, adapting the marine spatial plans consistent with the monitoring results leads to the potential to identify new research needs and sets the basis for a new round of MSP planning, implementation, monitoring, etc. (Figure 1).

Source: Ehler and Douvere, 2009. Figure 1. The Adaptive Marine Spatial Planning Cycle

While well established in many other planning and management contexts 12, the ‗planning-implementation-adaptation‘ cycle is infrequently applied to the development of

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MSP. Neglecting an adaptive approach to MSP, however, is likely to limit its capacity to achieve successful and sustainable results over time. MSP practice in Belgium and Germany, for example, illustrates that a one-time plan is unlikely to deliver the anticipated outcomes in the long run. Both governments have opted for the development of a ‗Master Plan‘ (in 2005 and 2009, respectively) - a one-time plan that addresses both economic development and environmental protection, but without any explicit provisions or time frame to adapt the spatial plan to changing circumstances. Change, however, is inevitable and is partly a result of uncertainty or a lack of information both about the functioning of marine ecosystems in space and time and the effectiveness of management measures taken to protect it. Technological improvements such as remote sensing, geographic information systems (GIS), global positioning systems (GPS), and underwater autonomous systems, are rapidly making spatial data more accessible and sophisticated. In Belgium, improved techniques for the valuation of ecological and biological marine areas 13 were developed after the initial Master plan was implemented. These new techniques would allow, for example, better informed and more science-based choices and trade-offs about the future use of the marine environment. Without a concrete framework to adapt initial marine spatial plans, it is difficult to incorporate such new techniques and information into the decisionmaking processes. Further, new political or economic conditions can also call for revisions of the marine spatial plan consistent with modified priorities. For example, climate change might modify the location of important biological and ecological areas over the next 50-100 years or require alternative methods for coastal adaptation. As described below, the Netherlands has recently started its second round of MSP by adapting its existing plan to changing circumstances and newly acquired information. An adaptive approach to MSP in the Netherlands, for instance (the Integrated Management Plan for the North Sea 2015 included the requirement for revision every five years), has allowed the effects of sea-level rise to be dealt with proactively through, among others measures, the designation of an exclusive sand extraction zone for beach nourishment to help protect the low-lying country from coastal erosion and flooding in the future. Without any specific provisions – ideally incorporated in MSP legislation – that require the revision within certain time frames (for example, revision and adaptation of the Massachusetts Ocean Management Plan is required by law at least every five years) 13, marine spatial plans either are not adapted at all, or at best, get adapted on the wings of government officials willing to undertake the task. The lack of an adaptive approach to MSP means that marine spatial plans get outdated very quickly and entirely forego the proactive decision-making power they could have when designed properly.

2.2. Ecosystem-Based Approach As proposed by a variety of authors, MSP is a means to alter the declining health of marine ecosystems and maintain key ecosystem services upon which all life, including humans, ultimately depend 15,16,17,18,19. To do this effectively, however, MSP needs to reflect ecosystem patterns and processes at appropriate spatial and temporal scales 15. Plans need to address fundamental topographic, oceanographic, and ecological conditions enabling

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identification and protection of the most ecologically and economically valuable places. This is not a simple task, and many plans have not addressed this issue adequately. During the past seven years, Australia (outside the Great Barrier Reef) has used an ecosystem-based approach to develop marine bioregional plans for its entire exclusive economic zone on the basis of its Environment Protection and Biodiversity Conservation Act of 1999 20. It first used an integrated marine regionalization of all Australian waters to define ecosystem boundaries for five large marine regions 21. Marine planners recently have completed marine bioregional profiles, containing information on biophysical and economic characteristics, key ecological features, and protected species and places that will form the basis for the actual marine spatial plans. Final marine bioregional plans will be completed in 2012. All marine spatial plans in the North Sea, as developed by Germany, the Netherlands and Belgium, currently incorporate spatial and temporal management measures to protect valuable ecological and biological places. However, ecosystem patterns and processes are often not consistent with administrative boundaries. Experiences with trans-boundary protected areas in the North Sea, for example, show that an ecosystem approach should be an essential characteristic of MSP. Most importantly, it would help prevent that MSP remains confined to the limits of administrative and political boundaries that do not reflect the true nature of ecosystem features, and hence prevent MSP to achieve its anticipated ecological objectives. Following a two-day workshop of academic, governmental and non-governmental representatives, Foley et al. (2010) concluded that MSP should be underpinned by four basic ecosystem principles to enable MSP to achieve ecosystem-based management. These principles include the maintenance of (a) native species diversity; (b) habitat diversity and heterogeneity; (c) populations of key species; and (d) connectivity among ecological attributes. Additionally, both the context of the ocean ecosystem and uncertainty should be addressed in conjunction with the principles to ensure MSP 'adequately addresses the spatial and temporal variability and non-linearity that characterize all ecosystems' 15 Their research further stipulates that these principles should provide for the scientific foundation of the MSP process, inform the definition of goals for MSP, and be translated into the operational decisions of MSP.

2.3. Integration MSP addresses multiple objectives and integrates a wide range of uses and issues. Ideally, a marine spatial plan should include all important economic sectors and environmental concerns in the management area. Integration across all sectors is important to ensure that unregulated uses do not undermine the effective performance of the plan. Some countries, however, have been more successful than others in meeting this challenge. One good example is Norway‘s Barents Sea plan, where all key economic activities—oil and gas development, fisheries, and marine transport— have been integrated with nature conservation objectives 22. A driving issue for the development of MSP in this area was the proposed expansion of oil and gas extraction into areas critical to seabirds, polar bears, whales, and fisheries. Between 2002-2005, the plan development was led by the Norwegian Ministry of the Environment, in cooperation with the representatives from all other relevant ministries,

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and included four extensive environmental impact assessments that studied the impact of fisheries, shipping, and oil extraction as well as pressures coming from outside the planning area. To achieve an integrated plan, a shipping lane was moved (in cooperation with the International Maritime Organization) to decrease pollution risks, trawling was limited in sensitive areas, while other ecologically valuable areas were closed to oil and gas exploration and some marine protected areas and fishery closure areas were extended to protect key life history stages of important species or critical ecological processes 23. The resulting plan has been implemented through existing authorities. The existing management authority for fisheries, for instance, remains responsible for fisheries management, but now has to make its decisions consistent with the Barents Sea management plan (Figure 2). One potential shortcoming of the plan though is the lack of international cooperation with its neighboring country Russia. Such trans-boundary cooperation would allow the plan to cover the entire Barents Sea ecosystem 23. Effective marine spatial plans indeed require more than integration across economic sectors and individual ocean uses. To be effective, marine spatial plans also need consistency with adjacent planning areas in which other management frameworks might be in place, as well as across state, federal-state, and international boundaries. The primary reason for such consistency is that impacts and effects from adjacent areas might greatly impact the marine area for which the marine spatial plan is in place and consequently undermine its effectiveness entirely. Consistency across adjacent areas and their applicable management frameworks allows that such potential exogenous threats can be address and dealt with properly. Few countries have made their marine spatial plans consistent with their policies and plans in the coastal zone, estuaries and rivers. In Europe, coastal zones, estuaries, and rivers have separate management regimes, and are dealt with through ICZM and the Water Framework Directive 24 respectively. Again, the Dutch approach to MSP is unique. Since late 2009, Dutch marine spatial plans for the North Sea do not stand by themselves any longer but are now embedded in the National Waterplan 25 for the Netherlands that covers all waters under the jurisdiction of the nation. A huge benefit of this approach is that upstream sources of pollution, for example, that affect the marine spatial planning area, can be identified and dealt with through other management bodies. Additionally, in their quest for an efficient use of marine space, priorities are set for the country as a whole and are only translated to the marine environment if that is the place where they can be best addressed. Consistency across boundaries is also rarely considered because timing of MSP development is often out of phase across borders. In the United States, two states, Massachusetts 26 and Rhode Island 27, are developing integrated marine plans without initial consultation across their adjoining marine borders. Considering that their marine spatial plans cover 0-3 nautical miles, it is obvious that cross-boundary cooperation is indispensable to achieve MSP at a scale meaningful from an ecosystem perspective. The United States draft framework for coastal and marine spatial planning calls for a regional approach to MSP that is likely to change the way states cooperate with each other and the federal government that is responsible for MSP in all US waters beyond three nautical miles (up to 200 nautical miles) 5.

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Source: Royal Norwegian Ministry of the Environment, 2006. Figure 2. Marine Spatial Planning in the Barents Sea, Norway.

In Europe, Belgium and The Netherlands also developed their initial marine spatial plans without transnational consultation. To the contrary, the guiding principle from Germany‘s 2004 Federal legislation 28 is ―development that meets social and economic demands consistent with sustainable ecological functions‖. Authority for MSP in the German territorial sea (0-12 nmi) lies with the three coastal states, each of which have developed spatial plans for their waters in the Baltic and North Seas. The German federal government is

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responsible for MSP in the exclusive economic zone and must develop its plans consistent with those in the territorial sea. Germany is one of the few countries that also aims at consistency across international boundaries. To this end, it conducted a formal consultation round with its neighboring countries, Poland and The Netherlands, for its respective marine spatial plans for the Baltic and North Sea. Informal consultations with government officials in the Netherlands are now working toward the identification of inconsistencies in their respective marine spatial plans and are trying to find ways to address them. Key issues that have emerged include compatibility between shipping and other uses, primarily wind energy, and consistency among the national plans for nature conservation. Considering and consulting neighboring countries early on in the MSP process would help avoid future problems that often would require additional resources to fix. Through its Marine Strategy 29, Maritime Policy 30 and Roadmap for MSP 31, as well as through a number of large-scale research projects, the European Commission is providing national states with tools and incentives to move toward a better consistency among national marine spatial plans.

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2.4. Participation MSP requires stakeholder involvement in the design, implementation, and evaluation of the entire MSP process. Involving key stakeholders in the development of MSP is essential for a number of reasons. Among these, the most important is because MSP aims to achieve multiple objectives (social, economic and ecological) and should therefore reflect as many expectations, opportunities or conflicts occurring in the MSP area. Stakeholders are individuals, groups, or organizations that are (or will be) affected, involved or interested (positively or negatively) by MSP actions. The scope and extent of stakeholder involvement differs greatly from country to country and is often culturally influenced. The level of stakeholder involvement will also largely depend on the political or legal requirements for participation that already exist in a particular country. The United States of America, for example, has a long tradition of consulting stakeholders for almost any public form of planning and management. When developing its marine spatial plan in 2009, the Commonwealth of Massachusetts engaged the general public and ocean user groups substantially from the onset of the planning process. In addition to public access through an Ocean Advisory Committee and a Science Advisory Council, the state held 18 public ―listening sessions‖ and conducted 66 interviews with stakeholder groups, that were also used to explore data availability for planning 26. Stakeholders were also extensively involved during the MSP plan revision for the Great Barrier Reef from 19982003. The Great Barrier Reef Marine Park organized several formal opportunities for the general public to provide written comments, initially prior to development of the marine spatial plan and subsequently commenting on the draft plan. Over these two phases, the Authority received over 30,000 written public submissions that led to substantial changes to the final marine spatial plan in comparison to its draft versions 32. In European examples, stakeholder involvement is often limited to a one-time comment period once a draft plan has been designed by government officials. Although stakeholders are more and more consulted in light of gaining access to better and more detailed knowledge and information, no formal processes are in place yet to include stakeholders in the early phases of MSP, similar to those

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of Massachusetts or the Great Barrier Reef. Although these plans are still too immature to derive conclusions related to the real success of stakeholder involvement, it can be expected that thorough stakeholder participation is better able to reflect the multiple perspectives on the planning area and therefore might encourage ‗ownership‘ of the spatial plan, engender trust in the process and eventually stimulate voluntary compliance with its rules and regulations.

2.5. Future-Orientation

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As with any other planning effort, MSP should be a future-oriented activity 33. Marine places without any visible problems or conflicts today can look very different in another ten or twenty years. One of the purposes of MSP is to help anticipate such conflicts and allow them to be dealt with before they become problems. To this end, MSP can help to envision a desirable future and enable proactive decision-making in the short run to move toward what is desired in the long run. Consequently, MSP should not be limited to defining and analyzing only existing conditions and maintaining the status quo, but should reveal possible alternative futures of how the MSP area could look in another 10, 15, or 20 years. Developing alternative spatial scenarios is important because they can: a) Visualize how the area will look if present trends continue without new management interventions; b) Illustrate the spatial and temporal consequences of implementing certain goals and objectives. It can, for example, help in estimating the required marine space to build, for example, 100 offshore wind turbines in the management area and help identify their implications upon other uses and/or the marine environment; c) Help anticipate potential future opportunities, conflicts or compatibilities for the area that can guide pro-active decision-making; and d) Determine the desired direction the management area should develop and help select the spatial management measures needed to get there. The development of alternative spatial scenarios is well established in land-use planning. From 2003-2005, the Belgian research initiative, ―Toward a spatial structure plan for sustainable management of the North Sea‖ 34 applied such land-use planning methods to the marine environment. The project illustrated that despite the different contexts of land versus water, these techniques could relatively easily be applied to MSP. The project resulted in the creation of six alternative spatial scenarios, each emphasizing a different set of goals and objectives and identified the significance and spatial implications of each scenario for the different functions and activities in the Belgian part of the North Sea. One of the most important lessons that can be derived from this research initiative is the fundamentally different skills needed to induce a future-orientated, pro-active approach to MSP. Although the project started with an initial ‗stock-take‘ of the area based on available scientific information organized and analyzed through geographic information system (GIS) technology, neither were useful in the design of spatial scenarios. While science tends to disaggregate data to analyze conditions and look at the past in an attempt to understand the present more precisely, spatial planners are more likely to synthesize information and patterns

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that - instead of trying to be precise - help forecast a desirable future and create alternative spatial use scenarios upon which pro-active decision-making can be based (Figure 3). The development of future spatial use scenarios for MSP clearly demand the skills of spatial planners.

Source: Maes F. et al. 2005.

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Figure 3. From GIS maps to patters and trends

Unfortunately, few marine spatial plans have so far identified and evaluated alternative spatial scenarios or visions for the future. It is, in fact, difficult to overstate how little a futureoriented approach is recognized in the actual practice of MSP. One counter-example exists in The Netherlands. The central goal of the Dutch marine spatial plan is the creation of an ocean that is safe (limiting shipping accidents and reduction of climate change effect), healthy (good water quality and biodiversity conservation) and productive (economic return from oil and gas, wind energy, fishing, and sand extraction). To achieve these goals, the Dutch government prepared three alternative spatial scenarios for a time horizon of 10 years (base year 2005; target year 2015). As a first step, for each activity (including wind energy, a high government priority) in the management area an estimate was made of (a) what economic developments can be expected; (b) what policy developments can be expected; (c) what technical or operational developments can be expected; (c) what are the spatial requirements until 2015; and (d) what are the spatial requirements after 2015? Secondly, the analysis included an economic valuation (both direct and indirect) for each activity in relation to its demand for ocean space. The economic value was estimated in terms of economic return, added value to the general economy, and employment. On the basis of this information, the three spatial scenarios were developed, each indicating a different level of expected growth, e.g., maximum growth, medium growth, and minimum growth. Thirdly, the spatial and temporal implications of each growth scenario were visualized in maps. These maps further contained information on expected policy developments and estimated technological improvements. By visualizing these scenarios, it was possible to anticipate what opportunities or conflicts could occur when certain objectives (set through the political process) would be implemented. It also allowed

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drawing initial conclusions about a desired future for the Dutch part of the North Sea. The spatial scenarios were developed through close cooperation with all relevant agencies and steered by an interagency ‗Board of Directors‘. The estimates for the human uses were mainly developed in cooperation with the sectors themselves. The economic valuations were largely based on economic and financial statistics, historic prices or products, international trade trends and forecasts, and expert opinions 35,36.

Source: Ministerie van Verkeer en Waterstaat, the Netherlands, 2009. Figure 4. Dutch policy priorities for the protection and economic development of the North Sea

Additionally to this work, a State Advisory Committee (Delta Commission) advised the Dutch Government on measures to protect the low-lying country against effects of climate change in the long term 37. Alternative sea level rise (SLR) scenarios were developed. For the year 2050, relative SLR could be 20-40cm (including 5 cm subsidence of the bottom), in 2100 the maximum plausible SLR could be 1.30m. The Dutch government decided to integrate the SLR into the National Water Plan, and protect the coast through beach nourishment, equal to the actual SLR (acknowledging the maximum SLR as a safety strategy albeit not actually planning for it). Further, the Dutch government intends to explicitly offer

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space for additional sand extraction for coastal and flood protection measures by reserving space between the 20-m depth contour and the 12-mile zone. The latter is included as a ―preferred sand extraction zone‖ in the National Water Plan 38. Together, these initiatives now allow the Dutch government to select policy priorities and management measures that actively support protection of the most valuable and fragile places of the marine environment and simultaneously steer the sustainable development of economic use, including oil and gas, fisheries and sand extraction. In addition, it provides them with a vision for the future that preserves areas in case they are needed to protect the country from the effects of climate change (Figure 4).

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3. A CLEAR LEGAL AUTHORITY FOR MSP Although an explicit legal basis for MSP was not available in all countries at the time they began, success in achieving a multi-objective MSP outcome depends on authority that requires all agencies to act consistently with the approved marine spatial plan. Although this may sound obvious, MSP legislation is often drafted in ways that makes a biased MSP outcome inevitable or discontinues MSP once a first plan is in place. The authority to conduct MSP should be established before the planning process begins, through modifying existing legislation, establishing new legislation, or administrative action that enables a multiple-objective outcome involving all agencies and stakeholders in an inclusive, transparent process. Most countries have relied on existing legislation. For example both Germany 28 and The Netherlands 39 extended their national land use planning acts into their exclusive economic zone (EEZ) in 2004 and 2008 respectively. Australia used its national biodiversity legislation to cover its entire EEZ and Belgium relied on its existing legislation for the protection of the marine environment. The United Kingdom and Sweden are currently developing and implementing new legislation. In 2002 a marine stewardship report by the government of the UK outlined a new approach to managing marine activities, including MSP 40. The Labour Party‘s 2005 manifesto committed ―through a Marine Act, ...[to] introduce a new framework for the seas, based on marine spatial planning, that balances conservation, energy, and resource needs.‖ 41. In 2006, a Marine Bill was introduced that included a UK-wide system for MSP, establishment of conservation zones, and establishment of a Marine Management Organization (MMO) that would develop marine spatial plans, streamline permitting, and reduce administrative costs to both government and marine users. The Marine and Coastal Access Bill was introduced in December 2008 and passed at the end of 2009. The formation of a new MMO to develop marine spatial plans is a unique approach in Europe, though it has been done previously in Australia‘s Great Barrier Reef in 1975 42. In other countries marine spatial plans are primarily developed and implemented through existing institutions and agencies. Work is underway on an integrated marine policy for Sweden and new legislation will likely be presented in 2010. A preparatory Inquiry proposed that the National Board of Housing, Building and Planning be given overall responsibility for planning Sweden‘s sea areas, and specific responsibility for MSP in the exclusive economic zone. Regional agencies would be responsible for MSP within 12nmi 43.

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4. MARINE SPATIAL PLANNING: WHAT IS IT NOT?

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Although the rapidly evolving interest for MSP can only be welcomed, debates about it are unfortunately becoming increasingly mis-directed. Of these, the biggest flaw is the misconception that MSP is synonymous with 'ocean zoning'. It is not. For many years, countries have designated special ocean zones for a variety of purposes, including fisheries closures, protected areas, sand and gravel mining, offshore oil drilling, maritime traffic routes and separation schemes, dredged disposal areas, among others. To date, however, most zoning has been done on a sector-by-sector basis, without much consideration of its effects on other sectors or the marine ecosystem. Some authors 44 now promote 'comprehensive ocean zoning' as a means to achieve more integrated, ecosystem-based management of the ocean. Their arguments - although often inspired on recent thinking in the field of MSP - miss an important point.

Source: Ehler and Douvere, 2009. Figure 5. The relationship between zoning and marine spatial planning

Zoning is a well-established tool in European and United States land-use planning systems, and is essentially practiced to separate uses that are perceived to be incompatible 45. Indeed, in the marine environment, zoning is a way to separate conflicts and encourage compatible uses. As illustrated in the figure below, a zoning map will usually form part of a

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marine spatial plan as a principal management measure for its implementation (Figure 5). Contrary to what zoning supporters proclaim, however, a fixed zoning plan alone cannot deliver social, economic, and ecological in an integrated, ecosystem context – particularly not in a multi-dimensional ocean that is continuously changing both spatially and temporally. In fact, who would want vast ocean spaces entirely zoned for all different uses or non-uses? The crucial point that proponents of ocean zoning miss is that MSP is much more than the mere separation of conflicts and the allocation of ocean space to specific uses or objectives. As illustrated above, MSP not only documents the present or deals with current conflicts but, also, focuses on extrapolating trends and creating spatial scenarios that allow the visualization of how a desirable future could look in another 10, 20, 30 years. This, together with the continuous and adaptive nature of MSP, is what permits governments to be proactive in their decision-making and help estimate what measures are needed today to preserve and protect ecosystem goods and services for future generations. None of this is possible through an ocean zoning plan that is seldom more than a reflection of the existing status quo and prevailing powers at the time. Additionally, MSP is also often confused with single-sector spatial plans for wind energy or marine protected areas. Both are spatially explicit tools and could form part of marine spatial plan, but again, they are not equal to a MSP process whose aim it is to achieve multiple objectives, and not only economic development or nature conservation. Of course, the variety of terms currently used to refer to MSP does not help avoid the confusion. Maritime spatial planning (European Union), marine planning (United Kingdom), coastal and marine spatial planning (United States), for example, are all used interchangeably throughout the MSP literature. Nevertheless, it has to be noted that despite the different terminology, all terms tend to aim at a more integrated management of ocean space in response to the failures of the current piece-meal approach.

5. CONCLUSION Despite the fact that many governments are currently embarking on MSP, little guidance is available that illustrates how MSP can deliver successful results. Although various MSP initiatives are still in an early stage and will only over time demonstrate how effective they really will be, some initial lessons can be drawn from these experiences. Clear authority is needed before starting any MSP process—without authority, marine spatial plans are likely be ineffective in achieving their multiple goals and objectives. All sectors, including fisheries and oil and gas development, should be fully integrated in the MSP process. Allowing any important sector to opt out of the planning process easily leads to problems when the use of ocean space has been agreed upon and the excluded (or uninvolved) sector is not operating consistently with the approved spatial plan. Once a legal basis is in place, other characteristics are critical to the development of MSP. First, MSP is dynamic and should focus on the future, not simply document present conditions. Second, profound and unforeseen changes are inevitable in both ocean ecosystems and ocean industries and could not be dealt with through a one-time plan. Instead, plans should be adaptive as these changes could significantly alter where, when, and how we use the ocean in the future. Third, as MSP is proposed as a means to alter the declining health of

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marine ecosystems, it should reflect ecosystem patterns and processes at appropriate spatial and temporal scales or, in other words, induce an ecosystem approach. Fourth, the multiple objective nature of MSP requires integration across a wide range of uses and issues not only within the planning area, but also in adjacent areas (across state, federal-state, and international) where both land-based or offshore activities could greatly influence the quality of the marine area and hence undermine the effectiveness of the marine spatial plan entirely. Finally, MSP should reflect as many expectations, opportunities, or conflicts occurring in the marine area and to that end involve stakeholders at all levels of its development and implementation. Understanding these characteristics of MSP is of critical importance as more and more governments become convinced of its benefits and are developing new legal and policy arrangements to enable its application. Not only does it prevent new MSP professionals from ―re-inventing the wheel‖ each time over again, it helps avoid misleading interpretations about MSP taking root and eventually derailing the further successful development and implementation of MSP worldwide.

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Daley B. 2009. State draws zones for coast wind farms. The Boston Globe. UNESCO. 2009. Climate change and Arctic sustainable development: scientific, social, cultural and educational challenges. Report and recommendations. Paris, France. [3] Mouawad J. 2009. Oil industry sets a brisk pace of new discoveries. New York Times, 23 September 2009 [4] Crowder L., Norse E. 2008. Essential ecological insights for marine ecosystem-based management and marine spatial planning. Marine Policy 32:772-778 [5] The White House Council on Environmental Quality. 2009. Interim Framework for Effective Coastal and Marine Spatial Planning. Interagency Policy Task Force. United States of America [6] Department for Environment, Food and Rural Affairs. 2009. Coastal and Marine Access Act. Available at: http://www.defra.gov.uk/environment/marine/legislation/index.htm [7] Lawrence D., Kenchington R., Woodley S. 2002. The Great Barrier Reef. Finding the right balance. Melbourne University Press, Victoria, Australia [8] Li H. 2006. The impacts and implications of the legal framework for sea use planning and management in China. Ocean and Coastal Management 49:717-726 [9] Kay R. and Alder J. 2006. Coastal Planning and Management. Taylor & Francis, London, United Kingdom [10] Cicin-Sain B. and Knecht R. 1998. Integrated Coastal and Ocean Management. Concepts and Practices. Island Press. Washington DC. United States [11] Ehler C. and Douvere F. 2009. Marine spatial planning: A step-by-step approach. Intergovernmental Oceanographic Commission and Man and the Biosphere Programme. IOC Manual and Guides. UNESCO, Paris. [12] Lein J. 2003. Integrated Environmental Planning. Blackwell Publishing, Oxford, United Kingdom.

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[13] Derous S, Verfailie E, Van Lancker V, Courtens W, Stienen E, Hostens K, Moulaert I, Hillewaert H, Mees J, Deneudt K, Deckers P, Cuvelier D, Vincx M and Degraer S. 2007. A biological valuation map of the Belgian part of the North Sea: BWZee. Biology Department, University of Ghent, Belgium [14] Commonwealth of Massachusetts. 2008. Oceans Act. Available at: http://www.mass.gov/czm/oceanmanagement/oceans_act/index.htm [15] Foley M. et al. 2010. Guiding ecological Principles for marine spatial planning. Marine Policy (in press) [16] Douvere F. 2008. The importance of marine spatial planning in advancing ecosystembased sea use management. Marine Policy 32:762-771. [17] Halpern B, McLeod K, Rosenberg A, Crowder L. 2008. Managing for cumulative impacts in ecosystem-based management through ocean zoning. Ocean & Coastal Management 51:203-211. [18] Ekebom J, Jäänheimo J, and Reker J. (eds.) 2008. Towards marine spatial planning in the Baltic Sea. Balance Technical Summary Report 4/4 [19] Young O, Oshrenko G, Ekstrom J, Crowder L, Wislon J, Day J, Douvere F, Ehler C, McLeod K, Halpern B, Peach R. 2007. Solving the crisis in ocean governance. Placebased management of marine ecosystems. Environment 49:21-30 [20] Commonwealth of Australia. 1999. Environment and Biodiversity Protection Act. Australia. [21] Commonwealth of Australia. Department of the Environment and Heritage. 2006. A Guide to the Integrated Marine and Coastal Regionalisation of Australia Version 4.0., Canberra, Australia. [22] Royal Norwegian Ministry of the Environment. 2006. Integrated management of the marine environment of the Barents Sea and the sea areas off the Lofoten Islands. Norway. [23] Olsen E, Gjosaeter H, Rottingen I, Dommasnes A, Fossum P, Sandberg P. 2007. The Norwegian ecosystem-based management plan for the Barents Sea. ICES Journal of Marine Science 64 :599-602. [24] Directive 2000/60/EC of 23 October 2000 of the European Parliament and of the Council of the European Union establishing a framework for Community action in the field of water policy. OJ L 327, 22 December 2000 [25] Ministerie van Verkeer en Waterstaat, Ministerie van Volkshuisvesting, Ruimtelijke Ordening en Milieubeheer en het Ministerie van Landbouw, Natuur en Voedselkwaliteit. Nationaal Waterplan 2009-2015. The Netherlands. [26] Commonwealth of Massachusetts. 2009. Massachusetts Ocean Management Plan. Volume 1 and 2. Boston, Massachusetts. [27] Rhode Island Coastal Resources Management Council. 2009. The ocean special area management plan (SAMP). Providence, Rhode Island. [28] Raumordnungsgezetz (ROG) vom 18 August 1997 (BGB1. IS. 2081, 2102), zuletzt geändert durch Artikel 10 des Gesetzes vom 9 Dezember 2006 [29] Commission of the European Communities, 2005. Proposal for a Directive of the European Parliament and of the Council establishing a Framework for Community Action in the field of Marine Environmental Policy (Marine Strategy Directive). COM (2005)505 final, Brussels.

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[30] Commission of the European Communities, 2006. Green Paper: Towards a Future Maritime Policy for the Union: a European Vision for the Oceans and Seas. COM (2006)275 final, Brussels. [31] Commission of the European Communities, 2008. Roadmap for Maritime Spatial Planning: Achieving Common Principles in the EU. COM(2008)791 final [32] Day J. 2009. Great Barrier Reef Marine Park Authority (personal communication). Australia. [33] Lein J. 2003. Integrated Environmental Planning. Blackwell Publishing, Oxford, United Kingdom. [34] Maes F., et al. 2005. A Flood of Space. Towards a spatial structure plan for sustainable management of the North Sea. Belgian Science Policy. [35] Ministerie van Verkeer en Waterstaat. 2008. Verkenning van de economische en ruimtelijke ontwikkelingen op de Noordzee. The Netherlands. [36] Ministerie van Verkeer en Waterstaat. 2008. Pre-policy document North Sea. The Netherlands. [37] Kabat P. 2009. Dutch Coasts in transition. Nature Geoscience 2;450-452. [38] Ministerie van Verkeer en Waterstaat, Ministerie van Volkshuisvesting, Ruimtelijke Ordening en Milieubeheer en het Ministerie van Landbouw, Natuur en Voedselkwaliteit. Nationaal Waterplan 2009-2015. The Netherlands. [39] Ministry of Housing, Spatial Planning and the Environment. 1965. The Spatial Planning Act. The Netherlands. [40] Department of Environment, Food, and Rural Affairs. Safeguarding our seas. A strategy for conservation and sustainable development of our marine environment (London, 2002). [41] Labour Party. Manifesto. 2005. London, United Kingdom [42] Great Barrier Reef Marine Park Act. 1975. (http://www.gbrmpa.gov.au) [43] Enander G, Nilsson T, Dahlander J and Vrede K. 2008. Better management of the marine environment. Final report developed for the Swedish government, Sweden. [44] Agardy T. 2010. Ocean Zoning: Making Marine Management More Effective. Earthscan Pubns Ltd. United States. (in press) [45] Smith H. 1993. The Citizen‘s guide to planning. Planners Press. American Planning Association, Chicago, Washington.

In: Environmental Planning Editors: Rebecca D. Newton

ISBN: 978-1-61728-654-4 © 2011 Nova Science Publishers, Inc.

Chapter 11

A COMPREHENSIVE APPROACH FOR PARTICIPATORY LAND USE PLANNING IN AREAS AFFECTED BY DESERTIFICATION OF THE EUROPEAN MEDITERRANEAN REGION Luis Recatalá Boix* and Juan Sánchez Díaz Department of Land-Use Planning, CIDE-Centro de Investigaciones sobre Desertificación (CSIC, Universitat de València, Generalitat Valenciana), Apartado Oficial, C/ Camí de la Marjal (Valencia), Spain

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ABSTRACT This chapter deals with the application of a comprehensive approach for participatory land-use planning in the Valencian region (east of Spain), a representative area of the European Mediterranean region. In this region, land-use conflicts and environmental issues have emerged rapidly as a consequence of the intensification of agrarian activity and the expansion of industrial-urban uses that occurred in recent decades. These environmental issues increase the risk of desertification in extensive areas of the region. Several relevant land-use plans were developed in accordance with information from the relevant stakeholders identified in the region, using the Land Use Planning Information System (LUPIS) as a spatial decision support system. LUPIS facilitates the generation of alternative land-use plans by adjusting the relative importance attributed by multiple stakeholders to preference and avoidance guidelines. From these plans, a possible consensus plan is proposed to address the land use conflicts between agrarian uses, industrial-urban activity and conservation, and to mitigate natural resource degradation caused by intensive agriculture and expansion of industrial-urban uses. Given that the land-use conflicts and environmental issues characterising the study

* Department of Land-Use Planning, CIDE-Centro de Investigaciones sobre Desertificación (CSIC, Universitat de València, Generalitat Valenciana),Apartado Oficial, C/ Camí de la Marjal S/N,46470Albal (Valencia), Spain, *Corresponding author: Email: [email protected], Tel: + 34961220540. Fax: + 34961270967

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Luis Recatalá Boix and Juan Sánchez Diaz area are similar to those identified in the European Mediterranean Region, it follows that the approach can be extended to areas affected by desertification of this region.

Keywords: Land-use planning, stakeholders, LUPIS, Valencian Region, European Mediterranean Region

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INTRODUCTION The European Mediterranean Region includes all countries or parts of countries having a Mediterranean type of climate and neighboring the Mediterranean Sea but not necessarily adjacent to it (Le Houerou, 1990). This region covers Portugal, Spain (except the northern part of the country), the southeast part of France and most parts of Italy and Greece (Joffre et al., 1995). Apart from the climate, these countries have a common land use and development pattern. Over recent decades, the land-use pattern of the European Mediterranean Region has seen an intensification of agrarian activity and an expansion of industrial-urban uses (including tourism) (Coccocsis, 1991; Sánchez, 1991; OSE, 2006). The Valencian region, located in the eastern part of Spain, is a representative example of a European Mediterranean area where land use conflicts and environmental issues have emerged rapidly. Land use conflicts concern two main land uses: agrarian uses (including agriculture and forestry) and industrial-urban uses (including tourism), which also compete with conservation (Cendrero et al., 1990; Recatalá, 1995; 2009). Environmental issues refer to surface and underground water pollution (Benet, 1991; Morell, 1991), soil pollution (Andreu, 1991),erosion (Rubio, 1991; Sanroque, 1991), soil salinization (Llorca, 1991; De Paz et al., 2004), landscape deterioration (Peñin and Jaen, 1991) and degradation of areas of high conservation value (De Felipe and Vizcaino, 1991). These environmental issues have led to an increase in the risk of desertification in extensive areas of the region (Pérez-Trejo, 1992; Rubio 1995; Rubio et al., 1998; Sánchez et al., 2009). In fact, the Valencian Mediterranean region was already included as an area of high desertification risk in the first World Map of Desertification Risk (FAO/UNESCO and WMO 1977). Participatory and comprehensive land use planning is recognised by the United Nations Convention to combat desertification (UNCCD, 1994) as a useful approach to minimise land degradation. Therefore, participatory and comprehensive land-use planning is needed for solving land-use conflicts and controlling land degradation in an area environmentally sensitive. The aim of this chapter is twofold: (1) apply a comprehensive and participatory approach for land use planning to prepare and evaluate a set of land use plans according to the particular perspective of each of the three kinds of stakeholders operating in the region, including farmers, industrial-urban developers and conservationists; and (2) propose a consensus plan on the basis of mutual agreements between stakeholders, using a spatial decision support system.

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METHODOLOGY

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The approach integrates three methods: (1) method for assessing land capability of mapping units; (2) method for assessing the resource quality of mapping units; and (3) method for assessing environmental impacts on mapping units (Figure 1). In this context, a mapping unit is a parcel of land that is homogeneous for natural resources and environmental processes on which an allocation decision is made. The land capability method (Figure 1, green part) allows establishing the potentiality of mapping units to allocate certain land uses taking into account their resource requirements and the resource base of the unit. Based on the requirements to implement a land use an exclusion index and a capacity index are defined for each land use. An exclusion index integrates resource parameters that do not permit a particular land use. For instance, the exclusion index for irrigation crops includes, among others, the slope as an exclusion parameter. When slope is greater than 5 % in a mapping unit then the index achieves a value that means that irrigation crops can not be allocated in that mapping unit. On the other hand, a capacity index integrates resource parameters that have different meaning to implement a land use depending on the value achieved in a mapping unit but never excludes the land use. For instance, the soil content of organic matter is one of the parameters in the capacity index for irrigation crops. The greater the soil content of organic matter the better the potentiality of a mapping unit to allocate irrigation crops. A detailed description and discussion of this land capability method can be found in Recatalá and Sánchez (2001a).

Figure 1. Methodology for participatory land-use planning.

The resource quality method (Figure 1, yellow part) allows assessing the merit of a mapping unit to be protected taking into account the quality of its ecosystem components

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(soil, vegetation, fauna and landscape). Each ecosystem component is evaluated through quality attributes based on their ecological functions. Soil quality is evaluated by means of four quality attributes: soil erodibility, degree of proximity to equilibrium with environmental conditions (ecological value), natural fertility and rarity (or singularity). As an example figure 2 show the criteria, attributes, parameters and soil characteristics to assess soil quality and figure 3 shows the operations that have to be made to classify and evaluate the soil quality through the attributes. Table 1 specifies the classes of the reference systems to assess soil quality of non-singular soils trough soil erodibility, ecological value and natural fertility. A more detailed description of this procedure can be found in Recatalá and Sánchez (1993) and Recatalá (1993). Both vegetation and fauna quality are evaluated through five quality attributes: ecological value, complexity, naturalness, stability and singularity as specified in Recatalá (2005). Landscape here refers to the visual image of a mapping unit. Landscape quality is evaluated through four quality attributes: intrinsic visual quality, intrinsic visual fragility, extrinsic visual quality and extrinsic visual fragility. Intrinsic visual quality refers to the value of a landscape to be preserved for its structure and it is assessed taking into account several landscape components such as relief, altitude, unevenness, lithology, waterbodies, land-use, type of vegetation and human constructions (Figure 4). Intrinsic visual fragility refers to the vulnerability of the landscape of a mapping unit to be visually degraded by a human influence. Extrinsic visual quality and fragility include the consideration of the effect on the visual quality and fragility in the landscape of a mapping unit by those surrounding it within the same visual basin. These four quality elements are combined to obtain the landscape quality of a mapping unit following the procedure specified in Recatalá and Sánchez (2001b). Finally, the resource quality of a mapping unit results from the integration of the quality of its ecosystem components as follows:

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EQu = wc x vic

(1)

n where, EQu = value of resource quality of mapping unit u. We = weight given to ecosystem component e. viu = quality value of ecosystem component e. n = number of ecosystem components. A more detailed description of this integration procedure can be found in Recatalá (1995). The environmental impact assessment method (Figure 1, red part) allows assessing the global or aggregated effect of land uses on mapping units taking into account the quality and vulnerability of natural resources. This method takes into account the resource quality of soil, vegetation, fauna and landscape, which are assessed as specified above. In addition, it also takes into account the vulnerability of soil to pollution, the vulnerability of aquifer to pollution and the soil loss by water erosion that are three relevant resource degradation processes in the European Mediterranean region. Soil vulnerability to pollution is evaluated through the structure and characteristics of horizons in the profile of each soil as specified in Recatalá and Sánchez (1997). Aquifer vulnerability to pollution is evaluated through lithology (permeability), soil (organic matter content, texture, structure and soil depth), climate

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(rainfall) and topography (slope) as specified in Recatalá and Sánchez (1998a). Soil erosion by water is evaluated by means of a weighting-rating method that takes into account the erosivity of rainfall, the erosionability of soil and lithology, the slope, the type of vegetation, the erosive morphologies and the type of soil conservation practices in a mapping unit as specified in Recatalá and Sánchez (1998b). Finally, the global impact of a land use on a mapping unit results from the integration of the quality and the vulnerability of its resources as follows:

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GIum=  Wr x (RQf – RQi) + Wsvp x SVP + Wavp x AVP + We x (RE – PE) n where,

(2)

GIum = Global impact of land use u on mapping unit m. Wr = weights given to resource components (soil, vegetation, fauna and landscape) depending on the type of land use being implemented in mapping unit m. RQf = Estimated resource quality of component i after the implementation of a land use on mapping unit m. RQi = Evaluated resource quality of component i before the implementation of a land use on mapping unit m. n = number of resource components. Wsvp = weight given to soil pollution vulnerability depending on the type of land use being implemented in mapping unit m. Wavp = weight given to aquifer pollution vulnerability depending on the type of land use being implemented in mapping unit m. We = weight given to soil erosion depending on the type of land use being implemented in mapping unit m. SVP = Soil pollution vulnerability in mapping unit m. AVP = Aquifer pollution vulnerability in mapping unit m. RE = Potential soil erosion in mapping unit m. PE = Present soil erosion in mapping unit m. A more detailed description of the operations (rating, weighting and integration) of this procedure can be found in Recatalá (1995). Application of these three methods (land capability, resource quality and global impact) in an area results in a map for each land use that shows the mapping units where the land use is excluded and those ones having the better conditions to implement it considering both the capability and the global impact associated to the land use. These maps are the starting points to propose alternative land use plans trough decision criteria according to the perspectives of the stakeholders identified in the area. From these land use plans a consensus plan can be proposed trough negotiation between the stakeholders (Figure 1, blue part). In order to increase the effectiveness of the process of decision making a spatial decision support system can be used. Particularly, in this chapter the LUPIS system (see next section) has been used to carry out the planning exercise showed below.

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Figure 2. Criteria, attributes, parameters and soil characteristics for assessing soil quality.

Figure 3. Procedure for classifying and assessing soil quality through soil erodibility, ecological value and natural fertility.

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Table 1. Classes of the reference systems defined to assess soil quality of non-singular soilsa Criteria Erodibility Classes Very High K > 0.45

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High

0.45 > K > 0.35

Ecological Value

Natural Fertility

* Soils having a mollic A horizon; lacking salic and fluvic properties * Soils developed on sandstone; having an argic B horizon * Soils which are coarser than sandy loam to a depth of at least 100 cm of the surface; lacking fluvic and/or salic properties * Soils showing gleyic properties within 50 cm of the surface under natural conditions; lacking fluvic properties * Soils having salic properties under natural conditions; lacking fluvic properties * Soils developed on limestone, having an argic B horizon; lacking a mollic A horizon * Soils developed on sandstone; having a cambic B horizon

* Soils with a loamy texture within first 50 cm; no modifiers apply (which means that the soil pH-water is between 6-7.5; the cation exchange capacity is greater than 7 cmol kg-1 within the upper 20 cm; the electrical conductivity is lesser than 2 dS m-1; soil is not saturated within 60 cm of the surface for more than 60 days each year).

Moderate 0.35 > K >0.25

* Soils developed on limestone or unconsolidated materials; having a cambic B horizon; lacking a mollic A horizon; lacking a B argic horizon; lacking gleyic, salic and fluvic properties * Soils developed on limestone or unconsolidated materials; having a calcic horizon, a petrocalcic horizon or soft powdery lime within 125 cm of the surface; lacking a mollic A horizon, lacking salic, gleyic and fluvic properties

Low

* Soils developed on limestone or unconsolidated materials, lacking a mollic A horizon, a cambic B horizon, an argic B horizon; lacking salic, gleyic and fluvic properties * Soils showing fluvic properties

0.25 > K >0.15

Very Low K < 0.15

a

* Soils which are limited in depth by continuos hard rock or a continuos cemented layer within 30 cm of the surface, lacking a mollic A horizon * Soils in which human activities have resulted in profound modifications of the original soil characteristics (e.g. humaninduced saline soils)

* Soils with a loamy texture within first 50 cm; soil pH-water is between 7.5-8.5; no other modifiers apply * Soils with a loamy texture within first 20 cm and a clayey texture from 20 to 50 cm; no modifiers apply * Soils with a loamy texture within first 20 cm and a clayey texture from 20 to 50 cm; soil pH-water is between 7.5-8.5; no other modifiers apply * Soils with a loamy texture within first 20 cm and a lithic contact between 20 and 50 cm of the surface; soil pH-water is between 68.5; no other modifiers apply * Soils with a clayey texture within first 50 cm; soil pH-water is between 6-8.5; no other modifiers apply * Soils with an electrical conductivity between 2 and 4 dS m-1 within first 100 cm *Soils with a sandy texture within first 50 cm; with an effective cation exchange capacity of less than 7 cmol kg-1 within the upper 20 cm; soil pH-water is between 6-8.5; no other modifiers apply * Soils with a sandy texture within first 20 cm and a clayey texture from 20 to 50 cm; with an effective cation exchange capacity of less than 7 cmol kg-1 within the upper 20 cm; soil pH-water is between 6-8.5; no other modifiers apply * Soils saturated within 60 cm of the surface for more than 60 days each year * Soils with an electrical conductivity between 4 and 8 dS m-1 within first 100 cm * Soils with a lithic contact between 20 cm and the surface * Soils saturated within 60 cm of the surface most of the year * Soils exceeding 8 dS m-1 electrical conductivity within first 100 cm * Soils having a content of exchangeable sodium in excess of 15% of the cation exchange capacity; soil pH-water is greater than 8.5

There is no necessarily relationship between columns. For instance, soils of high ecological value are not necessarily of high natural fertility.

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Figure 4. Method for assessing landscape quality through four quality attributes: intrinsic visual quality, intrinsic visual fragility, extrinsic visual quality and extrinsic visual fragility.

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THE LUPIS SPATIAL DECISON SUPPORT SYSTEM LUPIS (Land Use Planning and Information System) is a microcomputer-based spatial decision support system developed at CSIRO (Commonwealth Scientific and Industrial Research Organisation) in Australia for carrying out comprehensive land use planning. LUPIS has proven to be an appropriate instrument for comprehensive land use planning at regional level (e.g. Cocks 1984; Yapp et al., 1986; Ive et al., 1989; Braithwaite et al., 1993; Cocks et al., 1995; Recatalá, 1995; Rodríguez, 1995; Ive, 1997; Recatalá et al., 2000; Recatalá and Zinck, 2008). In this research, LUPIS was used to formalize the planning process, handle diverging group interests and design options leading to agreements between contending stakeholders. Central of LUPIS is the premise that land use planning should be issue-driven (Ive, 1992). An issue is a statement of some stakeholder perspective that should be considered when allocating land. LUPIS requires a response to each issue in the form of one or more resource allocation policies (Cocks et al., 1986) which seek to identify, in principle, the preferred resource requirements for the relevant uses. As a consequence, competing land uses are allocated as far as possible in accordance with their preferred resource requirements, conditional upon the resource base of the area and the stakeholders‘ demands.

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More details on the LUPIS capabilities can be found in Ive and Cocks (1988), Ive (1992) and Cocks and Ive (1996).

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THE PLANNING EXERCISE In the LUPIS context a planning exercise implies identification of land-use conflicts and environmental issues, identification of competing stakeholders, formulation of land-use policies, preparation of a base map and data and generation of land-use plans. Land-use conflicts involve agrarian uses vs. industrial-urban uses vs. conservation uses, and environmental issues refer to surface and underground water pollution, soil and air pollution, soil erosion and salinisation, landscape degradation and deterioration of areas of high conservation value. Three types of stakeholders compete for the appropriation of the land resources in the regional context: farmers, industrial-urban developers and conservationists. Farmers promote intensive agriculture (irrigation crops) for commercial purposes, mainly in the coastal zone where the most productive soils and the best resource conditions (e.g. high water availability) are found. Dry land uses are preferred in areas having low or even null water availability, but if such areas have high accessibility then intensive wood production becomes an alternative. Extensive wood production is preferred in highly accessible areas with tree vegetation. Industrial-urban developers promote development of houses, infrastructures and tourism facilities (e.g. hotels, shops and commercial zones). Conservationists seek the conservation of native ecosystems; promote afforestation to control soil erosion on degraded areas and to restrict agrarian activity and urban-industrial development to areas of low vulnerability to environmental degradation. Taking into account the diverse and contrasting perspectives of the three stakeholders, twenty-two policies were formulated in response to the land-use conflicts and environmental issues identified in the study area. The purpose of such policies was to establish the resource requirements of each land use. Policies were grouped as imperative (exclusion and commitment policies) and indicative (preference and avoidance policies) policies (Cocks et al., 1986). Imperative policies state how a particular mapping unit will be used (a commitment policy) or must not be used (an exclusion policy). Indicative policies suggest how a particular mapping unit should (a preference policy) or should not (an avoidance policy) be used. The complete set of policies used in the exercise is presented in table 2. Policy rating consists in evaluating the relative attractiveness of a map unit for the land use referred to in a policy in terms of the policy‘s resource requirements. It is a number between 0 and 1, representing the extent to which the selection of a particular land use on a particular map unit satisfies a particular policy. The LUPIS system operates with user-defined rules to calculate policy ratings from the data items for each map unit. The methodology described above was considered in order to define the rules to calculate policy ratings. A policy vote provides a mechanism for adjusting the relative importance attributed to an indicative policy during the plan-making process. Policies considered more important by a stakeholder and therefore warranting a higher policy achievement are likely to receive a higher vote than those that are considered less important. Policy votes mark the final user input required to generate a plan.

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Luis Recatalá Boix and Juan Sánchez Diaz Table 2. Set of policies used for land-use planning in Valencia

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Exclusion Policies 1. EXCLUDE IRRIGATION (from mapping units unsuitable for irrigation)

Commitment Policies 1. COMMIT URBANUSES (to mapping units currently urbanised)

Preference Policies Avoidance Policies 1. ENCOURAGE 1. AVOID IRRIGATION IRRIGATION (on AND INDUSTRIALmapping units which are of URBAN USES (on high capability for mapping units which are of irrigation) high vulnerability to underground water pollution) 2. EXCLUDE DRY 2. COMMIT NON- USE 2. ENCOURAGE DRY 2. AVOID IRRIGATION LAND USES (from (to mapping units that are LAND USES (on mapping AND INDUSTRIALmapping units unsuitable waterbeds and streams) units which are of high URBAN USES (on for dry land uses) capability for dry land mapping units which are of uses) high vulnerability to soil pollution) 3. EXCLUDE 3. ENCOURAGE 3. AVOID DRY LAND INTENSIVE WOOD INTENSIVE WOOD USES, INDUSTRIALPRODUCTION (from PRODUCTION (on URBAN USES AND mapping units unsuitable mapping units which are of WOOD PRODUCTION for intensive wood high capability for (on mapping units which production) intensive wood production)are of high potential soil erosion) 4. EXCLUDE 4. ENCOURAGE 4. AVOID INDUSTRIALEXTENSIVE WOOD EXTENSIVE WOOD URBAN USES (on PRODUCTION (from PRODUCTION (on mapping units which are of mapping units unsuitable mapping units which are of high landscape quality) for extensive wood high capability for production) extensive wood production) 5. EXCLUDE 5. ENCORAGE 5. AVOID IRRIGATION, INDUSTRIAL-URBAN INDUSTRIAL-URBAN DRY LAND USES, USES (from mapping units USES (on mapping units WOOD PRODUCTION unsuitable for industrialwhich are of high AND INDUSTRIALurban uses) capability for industrial- URBAN USES (on urban uses) mapping units which are of high conservation value) 6. EXCLUDE 6. ENCOURAGE AFFORESTATION (from INDUSTRIAL-URBAN mapping units unsuitable USES(on mapping units for afforestation) which are highly urbanised 7. ENCOURAGE AFFORESTATION (on mapping units which are of high capability for afforestation) 8. ENCOURAGE NATURAL REGENERATION (on mapping units which are of high capability for natural regeneration) 9. ENCOURAGE PROTECTION (on mapping units which are of high capability for protection)

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A base map at a scale of 1:200 000 corresponding to the study area (Figure 5) was developed from the Geoscientific Map of the province of Valencia (Diputación Provincial de Valencia, Universitat de València and Universidad de Cantabria, 1986). The study area contains 271 morphodynamic units defined on the basis of climate, geomorphology, lithology, soils, vegetation and active processes (e.g. soil erosion) by using an integrated mapping method (Cendrero et al., 1980; Diaz de Teran, 1985; Cendrero et al., 1990). Morphodynamic units were adopted as mapping units and data items attributed to them. To operationalise the set of allocation policies, 23 data items were selected. These data items referred to: lithology, soil, surface water, underground water, topography, vegetation, landscape, soil erosion, slide risk, flood risk, road accessibility and building activity.

Figure 5. (a) Location of the study area in Spain. (b) Base map of the study area. (Recatalá et al., 2000).

In the plan generation phase, preference and avoidance policies are voted first, on a scale of 0 to 10, in an attempt to achieve the stakeholder expectations. By selectively assigning

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votes to the preference/avoidance policy set, land use plans were developed giving emphasis to either agrarian or industrial-urban uses which showed the opportunities for accommodating these uses in areas of high capability and low vulnerability. In addition, the stakeholder representatives also agreed to emphasise conservation uses in both land-use plans. As the stakeholders had different objectives, the plans showed significant discrepancies of land use allocation, calling for an effort of compatibilization to generate a common plan suitable to address current and potential land use conflicts and environmental issues. While recognizing that all stakeholder priorities could not be simultaneously achieved, it was agreed by stakeholder representatives to jointly emphasize the preference/avoidance policies after having completed negotiations leading to a consensus. The study team scoped the exercise drawing upon information received from stakeholder representatives. A more detailed description of the planning exercise can be found in Recatalá (1995) and Recatalá et al. (2000).

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RESULTS The agrarian plan (Figure 6, a) emphasises the four agrarian-oriented uses and is dominated by irrigation crops. This is a consequence of the policy ratings and votes, and reflects the fact that irrigation crops are the most preferred agrarian activity for the study area because of its profitability. Such land use has been allocated to alluvial and alluvial-colluvial mapping units occurring in the coastal zone, and also to a few mapping units of the intermediate and inland zones. These mapping units are actually of high capability for irrigation crops as they support the most productive soils (Fluvisols, FAO, 1988) and have high water availability. Dry land uses have been allocated to alluvial-colluvial and colluvial mapping units (occurring in the intermediate and inland zones) that are of high or moderate capability for agrarian uses. However, irrigation crops cannot be allocated to them because water is no available and/or other limitations occur (e.g. slope). Intensive wood production has been allocated to mapping units similar to those ones being allocated to dry land uses, but having high road accessibility, reflecting the importance of good accessibility in determining the profitability of intensive wood production. Extensive wood production has been allocated to some inland mapping units having tree vegetation and high road accessibility. The industrial-urban plan (Figure 6, b) includes the coastal zone and some intermediate and inland mapping units being allocated to industrial-urban uses. By their resource conditions (high water availability, high accessibility, infrastructures and flat slope) such mapping units are of high capability for industrial-urban uses. Many of those mapping units were allocated to irrigation crops in the agrarian plan. This illustrates the competition between these land uses for similar land resources (e.g. water). Actually, water is the critical resource causing the conflict. Although both plans generated by using LUPIS separately satisfy the stakeholders‘ perspectives, the implementation of any two plans is no realistic. On the one hand, industrialurban developers would never accept the agrarian plan; and on the other, the industrial-urban plan is obviously no practical (too much area for industrial-urban uses at the expense of agrarian uses). However, such plans show the possibilities for widely accommodating the main land uses, and are the initial reference in search of a consensus plan.

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Figure 6. Land-use maps associated with the plans: (a) agrarian plan, (b) industrial-urban plan, (c) consensus plan (Recatalá et al., 2000).

In the consensus plan (Figure 6, c), it has been possible to accommodate the two main land uses in the study area without undue conflict between them or with conservation despite their preference for similar land resources. To allocate industrial urban uses according to the requirements (criteria) of the additional commitment policy, only five mapping units have been required from irrigation crops. Although these mapping units have high capability for irrigation crops, they also have high level of building activity. The presence of such activity and other attributes (e.g. high accessibility) are sufficient to justify the loss of good agricultural land in favour of industrial-urban uses. A more detailed discussion of the plans generated in the exercise taking into account the policy achievement profiles associated to them can be found in Recatalá (1995) and Recatalá et al. (2000). Thus, the results achieved suggest that it is possible to simultaneously address the land use conflicts and environmental issues of the study area (and of the region) through comprehensive land use planning. For such purpose, the use of the LUPIS system facilitates agreement by contending stakeholders as to how areas of land suitable for competing land

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uses can be resolved, while environmental management strategies for minimising remaining environmental issues can be derived. Unfortunately, there is no widely accepted technical criterion for judging whether the correct allocation of uses has been made in any particular situation (Cocks, 1992; Cocks and Ive, 1996; Zinck, 1996). For instance, the agrarian and industrial-urban plans are both technically correct for the study area in terms of land capability, even though they are unrealistic because of the land use conflict between agrarian and industrial-urban uses remains unsolved. In a democratic pluralist society the pragmatic test of a good decision is the extent to which society collectively accepts the decision as legitimate. Such general acceptance implies that the diverse stakeholders in that decision also accept it as legitimate (Cocks and Ive, 1996). To this end, LUPIS clearly encourages explicitness and transparency by involving multiple stakeholders in the plan-making process, as it has been evidenced in this exercise by generating the consensus plan after having analysed the two main land use plans. Finally, it must be highlighted that the experience gained in this exercise suggests that LUPIS can be used to carry out comprehensive land use planning in other European regions, where the decisions about land use and management are made in a democratic and pluralistic way.

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CONCLUSION Three main kinds of stakeholders compete for the appropriation of the land resources in the study area: farmers, industrial-urban developers and conservationists. On the basis of simulated agreements between stakeholders, selected land uses were allocated to the most suitable map units to solve conflicts between competing land use options. The results achieved suggest that it is possible to simultaneously address land use conflicts and environmental issues through comprehensive land use planning. Given that the land use conflicts and environmental issues of the Valencian region repeat in similar terms over the broader European Mediterranean region, it follows that the approach could be extended to this larger region. The use of the LUPIS decision-support system helped simulate the behaviour of the contending stakeholders in their endeavour to reach agreements about competing land uses with explicitness and transparency. Usually, explicitness and transparency are two desirable system qualities that facilitate successful negotiations (Kwaku Kyem 2004; Janssen et al., 2006). In this study, they supported the generation of a consensus plan that resolved the resource conflicts raised by the particular land use plan of each stakeholder category. LUPIS confirmed to be an appropriate tool to carry out comprehensive land use planning that involves multiple stakeholders in the decision-making process.

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Pons, V. (1991). Contenido y evolución del plomo total en los inceptisoles de la provincia de Valencia. Suelo y planta, 1, 643-651. Recatala, L. (1995). Propuesta Metodologica para Planificacion de los Usos del Territorio y Evaluacion de Impacto Ambiental en el Ambito Mediterraneo Valenciano. Ph. D. Thesis, Universitat de València. Valencia: Servei de Publicacions de la Universitat de València. Recatalá, L. (Dir.) (2009). Indicadores e Índices Integrados en la Agenda 21 Local para la Evaluación de la Calidad Ambiental en Áreas Afectadas por Desertificación del Ámbito Mediterráneo. Valencia: CIDE-Centro de Investigaciones sobre Desertificación, Universitat de València, Fundación Biodiversidad. Recatalá, L. & Sánchez, J. (1993a). Propuesta metodológica de valoración de la calidad ambiental de los suelos para evaluación de impacto ambiental en el ámbito mediterráneo valenciano. In R. Ortiz Silla (Ed.), Problemática Geoambiental y Desarrollo (pp. 727737), Vol. II. Murcia: V Reunión Nacional de Geología Ambiental y Ordenación del Territorio. Recatalá, L. (1993b). Propuesta metodológica de valoración de la calidad ambiental de los suelos para evaluación de impacto ambiental en el ámbito mediterráneo valenciano. In R. Ortiz Silla (Ed.), Problemática Geoambiental y Desarrollo (pp. 533-542), Vol. II. Murcia: V Reunión Nacional de Geología Ambiental y Ordenación del Territorio. Recatalá, L. and Sánchez, J. (1997). Soil pollution vulnerability for environmental impact exercises; a case study. In V. Pawlowsky Glahn (Ed.). Quantitative Methods in Environmental Geosciences (pp. 317-322). Barcelona: CIMNE. Recatalá, L. & Sánchez, J. (1998a). A method to evaluate underground water pollution vulnerability for environmental impact assessment and land use planning. In C.A. Brebbia, J.L. Rubio & J.L. Usó (Eds.), Risk Analysis (pp. 189-198). Southampton, United Kingdom: WIT Press, Computational Mechanics Publications. Recatalá, L. & Sánchez, J. (1998b). A weighting-rating method for evaluating soil erosion in the context of land use planning for the Valencian Mediterranean Region. In A. Rodríguez Rodríguez, C.C. Jiménez Mendoza & M.L. Tejedor Salguero (Eds.), The soil as a strategic resource: degradation processes and conservation measures (pp. 189-200). Logroño: Geoforma Ediciones. Recatalá, L. & Sánchez, J. (2001a). Método de evaluación de la capacidad del territorio para planificación en el ámbito Mediterráneo. Estudios Geográficos, 245, 705-735. Recatalá, L. & Sánchez, J. (2001b). A methodology for assessing landscape quality for environmental impact assessment and land use planning; application to a Mediterranean environment. In V. Rivas & Marchetti (Eds.), Geomorphology and Environmental Impact Assessment (pp. 191-206). Amsterdam: Balkema Publishers. Recatalá, L. & Zinck, J.A. (2008). Land-Use Planning in the Chaco Plain (Burruyacú, Argentina): Part 2: Generating a Consensus Plan to Mitigate Land-Use Conflicts and Minimize Land Degradation. Environmental Management, 42, 200-209. Recatalá, L., Ive, J.R., Baird, I.A., Hamilton, N. & Sánchez, J. (2000). Land Use Planning in the Valencian Mediterranean Region: Using LUPIS to Generate Issue Relevant Plans. Journal of Environmental Management, 59, 169-184. Rodríguez, O. (1995). Land Use Planning in Urban Fringes; A Case Study in Caracas (Venezuela). Ph D Thesis, ITC-International Institute for Aerospace Survey and Earth Sciences. Enschede: ITC.

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Rubio, J.L. (1991). La desertificación del territorio valenciano. In Generalitat Valenciana (Ed.), El Medio Ambiente en la Comunidad Valenciana (Segunda Edición, pp. 188-193). Valencia: Generalitat Valenciana. Rubio, J.L. (1995). Soil erosion effects on burned areas. In R. Fancheti, D. Peter, P. Balabanis & J.L. Rubio (Eds.), Desertification in a European context: Physical and socio-economic aspects. European Commission, ECSC-EC-EAEC. Brussels: European Commission. Rubio, J.L., Recatalá, L. & Andreu, V. (1998). European desertification risk. In C.A. Brebbia, J.L. Rubio & J.L. Usó (Eds.), Risk Analysis (pp. 3-16). Southampton, United Kingdom: WIT Press, Computational Mechanics Publications. Sánchez, J. (1991). Desertification and Changes in Land use, Desertification Hydric Resources in the European Community. STOA Document, European Parliament. Brussels. Sánchez, J., Recatalá, L. & Pastor, A. (2009). La Desertificación y sus consecuencias en el Ámbito Mediterráneo. Capítulo 2. In L. Recatalá (Dir.), Indicadores e Índices Integrados en la Agenda 21 Local para la Evaluación de la Calidad Ambiental en Áreas Afectadas por Desertificación del Ámbito Mediterráneo (pp. 53-78). Valencia: CIDE-Centro de Investigaciones sobre Desertificación, Universitat de València, Fundación Biodiversidad. Sanroque, P. (1991). La erosión del suelo. In Generalitat Valenciana (Ed.), El Medio Ambiente en la Comunidad Valenciana (Segunda Edición, pp. 184-187). Valencia: Generalitat Valenciana. UNCED (1994). United Nations Convention to Combat Desertification in those countries experiencing serious drought and/or desertification, particularly in Africa. United Nations Environment Programme (UNEP). Geneva: Interim Secretariat for the Convention to Combat Desertification (CCD). Yapp, G.A., Wiken, E.B., Gelines, R.R. and Morrison, N.R. (1986). A microcomputer based method for enhanced use of large land data systems in Canada. Landscape and Urban Planning, 13, 169-181. Zinck, J.A. (1996). La información edáfica en la planificación del uso de las tierras y el ordenamiento territorial. In J. Aguilar, A. Martínez & A. Roca (Eds.), Evaluación y Manejo de Suelos, pp. 49-75. Granada: Consejería de Agricultura de la Junta de Andalucía, Sociedad Española de la Ciencia del Suelo, Universidad de Granada.

INDEX

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A abatement, 46, 47, 230 abstraction, viii, 46, 53, 58 Abstraction, 53 access, 50, 169, 175, 178, 181, 195, 227, 241 accessibility, 226, 259, 261, 262, 263 accounting, vii, 1, 2, 4, 5, 6, 40, 85, 88, 90, 94, 97, 98, 104 accuracy, 171 achievement, 206, 259, 263 acid, 9, 20, 21 activity level, 22, 23 adaptability, 85 adaptation, ix, x, 65, 167, 168, 170, 182, 235, 236, 237 additives, 18 adjustment, 96 administrators, x, 118, 187, 189, 190, 194, 195, 196, 197, 198, 199, 200 Africa, 58, 268 age, 85, 171 agencies, 53, 170, 181, 192, 194, 196, 217, 224, 225, 226, 228, 229, 244, 245 aggregation, 34 agricultural sector, 55, 62, 67, 68, 69, 76 agriculture, xi, xii, 46, 53, 55, 57, 60, 61, 63, 64, 66, 68, 69, 71, 72, 73, 74, 75, 76, 89, 110, 115, 122, 132, 155, 157, 221, 229, 251, 252, 259 air emissions, 46, 96, 147 algorithm, 3, 10, 42, 43 alternatives, 4, 22, 29, 35, 192 ammonia, 165 amortization, 70 analytical framework, 49, 99 applications, viii, 52, 74, 79, 81, 82, 85, 87, 88, 91, 93, 94, 95, 97, 102, 110, 156, 266 applied research, 169, 170

appropriate technology, 5 Argentina, 267 Asia, 211, 212 assessment, vii, viii, 1, 3, 4, 7, 8, 12, 34, 40, 41, 42, 46, 58, 80, 88, 89, 94, 99, 100, 102, 104, 114, 117, 166, 168, 179, 193, 199, 202, 204, 222, 224, 226, 227, 228, 229, 235, 254, 267 assessment procedures, 222 assets, 15, 16, 38, 48, 125, 131 assignment, 10 assumptions, ix, 108, 125, 129, 139, 196, 199 atoms, 19 attitudes, 169, 197 attractiveness, 259 Australia, 54, 55, 187, 234, 235, 238, 245, 248, 249, 250, 258, 265 Austria, 212 authorities, 65, 113, 126, 128, 130, 147, 195, 227, 228, 239 authority, 111, 227, 234, 235, 236, 239, 245, 247 authors, ix, 4, 10, 49, 51, 52, 108, 116, 138, 206, 237, 246 automobiles, 94, 99 autonomy, 65, 73, 111, 115, 117, 193 availability, vii, 1, 5, 36, 48, 52, 54, 56, 66, 72, 139, 150, 217, 241, 259, 262 aversion, 141, 151 avoidance, xii, 251, 259, 261 awareness, xi, 2, 73, 97, 108, 125, 130, 210, 217, 221, 227, 229

B background, viii, 45, 171, 173 background information, viii, 45 bacteria, 86 barley, 161 barriers, 218, 219 base year, 243

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270

Index

basic research, 169 batteries, 43 Bayesian estimation, 166 behavior, xi, 51, 70, 82, 83, 86, 221 Belgium, 115, 234, 237, 238, 240, 245, 249 beliefs, 18 benign, 9, 87 benzene, 18, 19, 20, 22, 23, 26, 27, 29, 31, 32, 33, 34 bias, 200 Bible, 132 bioaccumulation, 95 biodiversity, 82, 84, 87, 100, 102, 110, 112, 117, 243, 245 biofuel, 94, 98 biological systems, 93 biomanipulation, 83 biomass, 82, 83, 84, 85, 86, 92, 93, 99 biosphere, 86 biotechnology, 212 biotic, 7 blame, x, 167 bonding, 110 bone, 6 borrowing, 47 bounds, 5, 141, 151, 162, 191 brainstorming, 180 breakdown, 91 break-even, 27 breeding, 61 Britain, 165 buffer, 85 Bulgaria, 116 bureaucracy, 181 business management, 4, 173, 190 by-products, 207, 208, 210

catalyst, 19 catchments, 65 category a, 14, 72 category d, 31 cation, 257 cell, 85, 94, 100 challenges, 80, 84, 108, 137, 163, 166, 168, 170, 176, 182, 219, 248 channels, 4, 46, 194 chaos, 89 character, 58, 71, 168 chemical industry, 12, 57 chemical reactions, 82 children, 73 China, 54, 55, 85, 92, 101, 105, 208, 211, 212, 234, 248 chromium, 96 chromosome, 99 CIA, 12 City, 59 civil servants, x, 168, 171, 197 civil service, 171, 181 classes, 7, 156, 254 classification, 126, 204, 207 cleaning, 137 clients, 192, 214 climate, ix, x, xi, 5, 8, 14, 27, 34, 43, 58, 61, 84, 100, 167, 168, 170, 176, 182, 217, 221, 222, 226, 233, 237, 243, 244, 245, 252, 254, 261 climate change, ix, x, xi, 5, 8, 14, 27, 34, 43, 84, 100, 167, 168, 170, 176, 182, 217, 233, 237, 243, 244, 245 close relationships, 7 closure, 239 clustering, 204, 207 clusters, 50, 194 CO2, vii, 2, 4, 8, 9, 10, 14, 19, 21, 27, 30, 31, 32, 34, 96 coatings, 18 coding, 85, 93, 102 cogeneration, 81, 87, 93, 94, 103 cohesion, 118 coke, 20, 27 collaboration, 134, 179, 189, 190, 191, 193, 194, 206, 207, 210, 213 color, iv combined effect, 56 combustion, 89, 95, 96, 97 commodity, 88 communication, x, 134, 187, 193, 198, 200, 216, 227, 229, 250

C cadmium, 96 Canada, v, ix, x, 53, 54, 79, 95, 96, 98, 167, 168, 171, 175, 181, 182, 183, 184, 185, 186, 219, 234, 235, 268 cancer, 8 CAP, 73, 76, 155 capillary, 129 capital expenditure, 8 capital markets, 47 carbon, 9, 10, 40, 42, 43, 89, 90, 94 carbon dioxide, 43, 89, 90 carcinogenicity, 31, 96 carrier, 86 case study, viii, 2, 18, 19, 24, 31, 34, 40, 57, 98, 102, 132, 219, 220, 267 cash flow, 6, 29

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Index community, ix, 3, 4, 7, 83, 93, 107, 111, 120, 169, 170, 190, 195, 200, 206, 207, 210, 212, 213, 214, 219, 230, 235 community relations, 7 compatibility, 241 compensation, 18, 97 competence, 48, 65, 195, 197 competition, 47, 49, 50, 52, 71, 126, 163, 216, 225, 262 competitive advantage, 2, 52, 77 competitiveness, vii, viii, 2, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 71, 75, 76, 78, 121, 204, 205, 215, 218 competitor, 47 competitors, 49, 50 compilation, 6 complaints, 226 complement, 170, 222 complexity, 56, 82, 86, 88, 101, 108, 109, 129, 132, 138, 192, 195, 222, 254 compliance, 6, 7, 9, 16, 17, 36, 39, 48, 242 components, 2, 82, 119, 128, 151, 153, 212, 222, 227, 235, 253, 254, 255 composition, 83, 92, 100, 103, 110, 125, 126, 226 compost, 212 compounds, 92, 96 computer simulations, 162 concentration, 72, 85, 86 conceptual model, 84 concrete, 237 conditioning, 94, 100 configuration, 23, 26, 29, 31, 84 conflict, ix, 29, 77, 135, 136, 192, 225, 234, 262, 263, 264 confusion, 247 connectivity, 210, 238 consciousness, 108 consensus, xii, 191, 198, 251, 252, 255, 262, 263, 264, 266 conservation, xii, 72, 73, 74, 81, 111, 112, 117, 122, 123, 129, 133, 163, 230, 234, 238, 241, 243, 245, 247, 250, 251, 252, 255, 259, 260, 262, 263, 265, 267 Constitution, 111, 127 construction, x, 66, 101, 194, 203, 207, 212, 214 consulting, 120, 241 consumers, 2, 10, 68, 180, 194, 198 consumption, 7, 9, 19, 20, 21, 24, 34, 37, 39, 46, 54, 63, 64, 66, 68, 69, 71, 72, 73, 88, 98, 99, 104, 105, 136, 137, 205, 206, 207 contamination, 92 continuity, 48, 217 contour, 245

271

control, 2, 8, 9, 10, 53, 55, 65, 78, 86, 92, 95, 97, 102, 125, 136, 137, 153, 165, 171, 191, 195, 259 conversion, 11, 12, 19, 31, 95, 99, 104, 207 cooling, 46, 47, 93 coordination, x, 74, 122, 169, 176, 177, 179, 181, 192, 203, 205, 214, 216, 222, 229 copper, 92, 96 copyright, iv Copyright, iv, 184 corn, 86, 161 correlation, 57, 83, 95, 124 correlations, 97 cost, vii, viii, 2, 4, 6, 7, 9, 14, 15, 16, 17, 18, 19, 22, 24, 26, 30, 32, 33, 36, 37, 38, 39, 45, 46, 47, 48, 50, 53, 56, 57, 71, 76, 86, 88, 90, 94, 96, 103, 104, 109, 128, 134, 150, 153, 155, 156, 158, 160, 178, 179, 195, 196, 211, 216 cost benefit analysis, 6 cost saving, 47 costs, vii, viii, ix, 2, 4, 6, 7, 9, 15, 16, 17, 18, 21, 25, 26, 32, 33, 37, 39, 46, 47, 48, 49, 50, 53, 54, 55, 56, 57, 70, 71, 86, 90, 91, 95, 96, 97, 121, 130, 135, 136, 137, 162, 166, 191, 208, 210, 216, 217, 234, 236, 245 costs of production, 15 cotton, 64, 148 Council of the European Union, 249 coupling, 64 CPU, 21 creativity, 196 credentials, 174 credit, 224, 228 critical analysis, ix, 107 critics, 201 crops, 71, 74, 157, 158, 160, 161, 162, 253, 259, 262, 263 crown, 128 cultivation, 62, 109, 111, 121, 125, 126, 128, 129, 130, 158, 162 culture, 70, 132, 190 current account, vii, 1 customers, 137, 193 cycles, 125, 207, 217 cycling, 99 Czech Republic, 115, 116

D damages, iv, 7, 34 danger, 139, 150 DART, 78 data analysis, 228 data availability, 241 data collection, 228

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272

Index

data processing, 169 database, 20, 40, 109 decentralization, 111, 115, 122, 130 decision makers, xi, 169, 195, 222, 228, 229 decision making, 4, 11, 39, 138, 180, 188, 191, 192, 193, 201, 219, 255 decision-making process, xii, 179, 187, 189, 195, 234, 237, 264 decisions, vii, 1, 2, 4, 5, 6, 7, 10, 11, 12, 25, 34, 35, 47, 89, 91, 95, 108, 138, 155, 158, 165, 168, 169, 180, 189, 191, 192, 195, 201, 238, 239, 264 defects, 110 defense, 72 deficiencies, 226 deficit, 72 definition, 3, 34, 46, 49, 50, 65, 99, 115, 118, 126, 130, 139, 156, 204, 206, 216, 238 deforestation, 110 degradation, xi, xii, 84, 89, 90, 98, 125, 221, 251, 252, 254, 259, 266, 267 degradation process, 254, 267 degraded area, 259 delegates, 227 delivery, 2, 4, 157, 225 democracy, x, 187, 188, 189, 190, 192, 193, 194, 195, 197, 198, 201 demographic characteristics, xi, 221 demographic data, 171 density, 60, 82, 189, 230 Department of Health and Human Services, 185 Department of the Interior, 184 deposits, 82 designers, 198 destination, 6, 11, 37, 39 destiny, 108 destruction, ix, 84, 85, 101, 107, 137 detection, 92 developed countries, 53, 54, 204, 211 developing countries, 217 deviation, 85 differentiation, ix, 41, 108, 125, 126 diffusion, 78, 109, 118, 121, 126, 164 direct cost, 6, 15 direct costs, 6, 15 direct investment, 77 direct measure, 104 disaster, 190, 231 discharges, 9, 53, 55, 92 discipline, 218 discounting, 6 discourse, x, 168, 190, 192, 196 discrete variable, 21, 136, 153 disequilibrium, 89

disorder, 89 disordered systems, 82 dispersion, 89 distribution, vii, viii, 1, 2, 3, 4, 5, 10, 12, 18, 19, 24, 26, 32, 34, 35, 36, 71, 110, 121, 126, 144, 155, 175, 211 district heating, 94, 102 disturbances, 93 diversification, 217 diversity, 61, 72, 73, 84, 85, 126, 129, 130, 134, 196, 210, 217, 226, 238 division, 116, 119 DNA, 83, 85, 99 domestic factors, 49 domestic policy, x, 167 dominance, 195 donors, xi, 222 double counting, 9 draft, 41, 111, 116, 234, 239, 241 drawing, 125, 129, 130, 244, 262 drinking water, 200 drought, vii, xi, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 268 drying, 94 duration, 120, 229 duties, 225 dyeing, 147, 166 dyes, 148 dynamics, 47, 48, 84, 93, 99, 102, 129, 131, 193, 216

E early warning, 222, 227 ecological indicators, viii, 79, 84, 85, 87, 92, 93, 100, 102, 105 ecology, vii, x, 80, 84, 86, 87, 88, 89, 90, 95, 97, 98, 99, 100, 101, 103, 105, 203, 205, 206, 208, 210, 212, 215, 217, 218, 219, 234 economic activity, 90, 210, 234 economic assessment, 90, 91 economic crisis, 213 economic development, xi, 66, 67, 72, 90, 205, 216, 233, 237, 243, 244, 247 economic efficiency, 71 economic growth, viii, 45, 46, 64, 90, 137 economic indicator, 6, 10 economic performance, 2, 4, 14, 61, 64, 75, 206, 207 economic resources, 48 economics, 43, 88, 90, 99, 103, 104, 126, 155, 166, 173, 175 economies of scale, 16, 210 economy, ix, x, xii, 2, 19, 49, 75, 76, 90, 100, 101, 107, 110, 125, 126, 130, 203, 205, 212, 233, 243

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Index ecosystem, 8, 27, 34, 42, 82, 83, 84, 85, 86, 87, 89, 92, 93, 95, 99, 100, 101, 102, 104, 105, 111, 131, 220, 235, 237, 238, 239, 246, 247, 248, 249, 253, 254 ECSC, 268 Education, 171, 172, 173, 176, 177, 178, 179, 180, 229 effluent, 53, 147 effluents, 53 elaboration, 56, 66 elasticity, 47 elasticity of demand, 47 election, 34 electrical conductivity, 257 electricity, 20, 21, 24, 27, 34, 81, 94, 208, 212, 215 email, 171 emission, 4, 5, 7, 9, 10, 14, 17, 30, 31, 34, 77, 87, 95, 96, 97, 136, 138, 139, 143, 144, 145, 148, 149, 150, 151, 154 emotional stability, 193 employees, 50, 169, 170, 216 employment, 117, 174, 175, 243 enemies, 195 energy, viii, xi, xii, 5, 8, 9, 10, 20, 21, 24, 46, 47, 48, 56, 66, 71, 79, 80, 81, 82, 85, 86, 87, 88, 89, 90, 94, 95, 97, 98, 99, 100, 103, 104, 109, 138, 147, 204, 205, 206, 207, 212, 214, 216, 217, 218, 221, 233, 241, 243, 245, 247 energy consumption, 9 energy efficiency, 207, 216 energy emission, 5 energy supply, 109, 204 enforcement, 235 engagement, 189, 190, 194, 198, 201, 202 engineering, 3, 100, 104, 155, 164, 204, 212, 234 entropy, 83, 84, 89, 90, 94 environment, viii, ix, x, 4, 7, 9, 34, 45, 46, 51, 54, 55, 57, 65, 66, 72, 74, 76, 80, 82, 86, 87, 88, 89, 90, 92, 93, 95, 96, 97, 101, 105, 108, 111, 125, 128, 129, 130, 136, 137, 138, 139, 140, 141, 147, 150, 151, 155, 165, 168, 178, 179, 180, 191, 198, 203, 210, 216, 217, 234, 237, 239, 242, 245, 246, 248, 249, 250, 267 environmental awareness, xi, 73, 221 environmental change, 136 environmental conditions, 61, 95, 139, 142, 143, 213, 254 environmental degradation, xi, 221, 259 environmental economics, 90 environmental effects, 90 environmental factors, viii, 79, 89, 90, 93, 94, 112 environmental harm, 31

273

environmental impact, viii, x, 3, 4, 5, 6, 7, 10, 13, 20, 21, 22, 24, 25, 26, 27, 31, 34, 35, 36, 38, 43, 58, 63, 64, 72, 77, 79, 80, 82, 87, 88, 89, 90, 91, 95, 96, 97, 99, 100, 103, 104, 105, 117, 138, 202, 203, 205, 207, 213, 239, 253, 254, 267 environmental influences, 147 environmental issues, vii, xii, 1, 2, 3, 6, 27, 34, 136, 164, 176, 181, 251, 252, 259, 262, 263, 264 environmental policy, x, 47, 48, 168, 170, 171, 172, 173, 174, 175, 177, 178, 179, 180, 181, 182, 187, 201 environmental protection, 90, 103, 140, 237 Environmental Protection Act, 95 Environmental Protection Agency, 43, 206 environmental quality, ix, 98, 135, 136, 213 environmental regulations, ix, 16, 135, 136, 137, 155 environmental resources, 112, 114, 122 environmental standards, 138, 214 environmental sustainability, 64, 88, 105 enzymes, 148 EPA, 41 EPC, 96 equality, 193, 195 equilibrium, 66, 72, 82, 84, 85, 87, 93, 205, 206, 213, 254 equipment, 5, 6, 12, 21, 35, 37, 39, 46, 71, 75, 139 erosion, 72, 237, 252, 254, 261, 268 estimating, 10, 242 ethanol, 4, 86 ethylene, 20 Europe, viii, xi, 2, 20, 66, 67, 108, 112, 116, 132, 133, 183, 211, 212, 215, 233, 234, 239, 240, 245, 265, 266 European Commission, 46, 49, 51, 77, 78, 241, 266, 268 European Community, 35, 77, 130, 131, 268 European Parliament, 249, 268 European policy, 133 European Union, 9, 53, 58, 78, 108, 155, 184, 206, 247, 249 European Union Structural Funds, 108 evapotranspiration, 58 evidence-based policy, 169, 170, 175 evolution, ix, 48, 82, 86, 92, 99, 107, 125, 129, 132, 155, 208, 211, 219 examinations, 93 exclusion, 253, 259 excretion, 84 exercise, 65, 195, 199, 224, 228, 255, 259, 262, 263, 264 expenditures, 7, 8, 46, 47, 53, 56, 57 expertise, 169, 173, 177, 178, 179, 224, 235 experts, 110, 197, 200, 235

274

Index

exploitation, ix, 66, 70, 73, 107, 125, 126, 129 exploration, 200, 239 exports, 52 exposure, 7, 47, 226 external costs, 4, 6, 7 externalities, 4, 6, 88, 104 extinction, 18 extraction, xii, 3, 8, 12, 19, 20, 21, 52, 71, 83, 207, 233, 237, 238, 243, 245

foreign direct investment, 77 forest ecosystem, 111, 131, 132 forest management, ix, 72, 107, 108, 109, 111, 120, 121, 122, 125, 126, 128, 130, 133 forest resources, 109, 110, 111, 116, 117, 121 forests, ix, 107, 109, 110, 111, 117, 121, 125, 126, 127, 128, 129, 130, 132, 133, 226, 265 formal education, 173 formula, 53 fossil, 5, 95, 96 fragility, 216, 217, 254, 258 framing, x, 167, 199 France, v, 45, 85, 116, 211, 248, 252 free energy, 86 free trade, 76 freedom, 193, 204 freshwater, 57 fruits, 69, 74 fuel, 5, 94, 95, 96, 100, 233 functional hierarchy, 113 funding, 116, 235 funds, 15, 46, 53, 74, 111, 129, 130, 131, 141, 149

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F fabrication, 140, 141, 142, 143, 145, 147, 150, 151, 152, 153, 154 facilitators, 198 factor cost, 53, 54 failure, 184, 235 family, 73, 156 family farms, 73 farmers, 66, 73, 74, 155, 157, 252, 259, 264 farmland, 61, 63, 64, 75 farms, 73, 74, 248 faults, 110 fauna, 117, 128, 129, 254, 255 feedback, 112, 129, 236 fertility, 254, 256, 257 fertilizers, 53, 63, 64 finance, 47, 155, 171, 175 financial institutions, 192 financial performance, 51 financial planning, 116 financial resources, 4, 226, 230 financial support, 35, 236 financing, 15, 214, 216, 217, 234 Finland, 115, 133 fires, 110, 117 firms, vii, viii, 1, 9, 10, 35, 45, 46, 49, 50, 51, 52, 73, 75, 137, 138, 163, 208 fish, xi, xii, 84, 92, 233 fisheries, 82, 238, 245, 246, 247 fishing, xii, 93, 233, 243 flexibility, 70, 84, 192, 214 flood, 65, 245, 261 flooding, 66, 237 flora, 189 fluctuations, 217 fluid, 94 focus groups, 196, 198 focusing, vii, ix, 2, 5, 135 food, xi, xii, 57, 69, 72, 73, 74, 76, 82, 84, 92, 99, 129, 212, 233 food products, 70, 212 food safety, 72 forecasting, 169, 170

G gasoline, 20, 22, 27, 100 GDP, 51, 63 GDP per capita, 51 gender, 171 gene, 86 generalization, 88 generation, xii, 2, 17, 37, 71, 81, 90, 93, 94, 98, 204, 212, 251, 259, 261, 264 genes, 85, 86, 93 genetic diversity, 72 genetic information, 86, 101 genome, 83, 93, 99 geography, 173, 194 geology, 265 Germany, 54, 78, 115, 116, 186, 234, 235, 237, 238, 240, 245 Global Competitiveness Report, 49, 77 global demand, xi, 233 global economy, xii, 2, 233 Globalization, 183 glycol, 94, 98 GNP, 51 goal setting, 12 goals, 112, 115, 117, 137, 138, 170, 194, 207, 213, 222, 227, 229, 236, 238, 242, 243, 247 goods and services, 49, 50, 53, 80, 213, 247 governance, x, 76, 108, 109, 113, 122, 123, 130, 133, 167, 170, 182, 187, 188, 189, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 249

Index government, iv, ix, x, xi, xii, 9, 32, 33, 65, 81, 95, 97, 111, 116, 123, 167, 168, 169, 170, 171, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 191, 192, 193, 195, 196, 200, 201, 204, 212, 216, 221, 222, 224, 225, 226, 227, 233, 234, 237, 239, 240, 241, 243, 244, 245, 247, 248, 250 government policy, xi, 171, 221 GPS, 237 grants, 35, 116 grasses, 126 grasslands, 82, 226 grassroots, 190 gravity, 67 Great Britain, 165 Great Lakes, 234 Greece, 57, 115, 165, 252 groundwater, xi, 66, 71, 221 group interests, 258 groups, 10, 54, 74, 93, 169, 179, 190, 192, 193, 194, 195, 196, 198, 200, 202, 210, 222, 224, 225, 226, 230, 235, 241 growth, viii, ix, xi, 45, 46, 47, 51, 60, 63, 64, 82, 84, 85, 90, 92, 103, 109, 129, 135, 136, 137, 213, 215, 221, 223, 225, 226, 230, 243 growth rate, 51 growth theory, 90 guidance, 234, 247 guidelines, xii, 17, 111, 116, 117, 121, 129, 214, 251, 265

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H habitat, 72, 238 habitats, xi, 93, 109, 110, 129, 233 hands, 194, 197, 227 harm, 89 harmonization, 137 hazardous wastes, 147 hazards, vii, xi, 221, 222, 223, 229, 230, 231 health, xii, 5, 6, 7, 8, 27, 31, 34, 48, 73, 80, 82, 84, 85, 87, 92, 95, 97, 104, 155, 171, 175, 179, 180, 229, 233, 237, 247 heat, 7, 82, 93, 94, 102 heat transfer, 94 heating, 47, 81, 93, 102 heavy metals, 96 heterogeneity, xii, 84, 117, 234, 238 HM Treasury, 43 hospitals, 74 hotels, 259 House, 248 households, 53 human activity, 80, 82 human resources, 48, 226

275

humanism, 132 humidity, xi, 221 Hungary, 56, 115 hurricanes, xi, 221 hydrocarbons, 18 hydrogen, 19, 94, 100, 103 hypothesis, 47, 77, 84, 101, 114

I identification, 6, 226, 235, 238, 241, 259 identity, 202, 206, 207 image, 7, 48, 254 impact assessment, vii, 1, 3, 7, 8, 12, 41, 42, 179, 202, 222, 227, 239 Impact Assessment, 41, 202, 267 impacts, vii, viii, xi, 2, 3, 5, 8, 9, 10, 13, 17, 20, 21, 24, 25, 26, 27, 47, 48, 72, 77, 80, 82, 92, 117, 169, 221, 222, 224, 225, 229, 239, 248, 249 implementation, vii, x, 1, 3, 8, 47, 70, 98, 110, 115, 168, 169, 170, 191, 194, 197, 198, 212, 215, 219, 227, 230, 235, 236, 241, 247, 248, 255, 262 in transition, 250 incentives, viii, 45, 46, 56, 76, 77, 118, 120, 217, 230, 241 incidence, 56 inclusion, 198 inclusiveness, 189 income, viii, xii, 15, 17, 38, 45, 46, 120, 155, 213, 233 India, 212 indication, ix, 107 indicators, viii, xi, 8, 14, 20, 51, 52, 79, 84, 85, 86, 87, 88, 89, 90, 92, 93, 95, 96, 97, 99, 100, 101, 102, 105, 147, 148, 149, 153, 154, 221, 223, 224 indices, 13, 83, 85, 93, 99 indigenous, 194 indirect effect, 103 individualism, 192 industrial emissions, 88 industrial location, 215 industrial sectors, 7, 8, 50, 54 industry, 7, 12, 34, 42, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 61, 68, 74, 75, 81, 95, 136, 137, 147, 148, 171, 179, 212, 216, 218, 229, 248 inefficiencies, 81 inefficiency, 98 infinite, 82 inflation, 96 information technology, 190 infrastructure, 66, 70, 71, 72, 202, 216, 266 innovation, 42, 47, 48, 76, 78, 211, 216 insight, 223

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276

Index

institutions, 9, 49, 51, 74, 189, 192, 194, 195, 201, 245 instruments, viii, 9, 46, 48, 53, 58, 73, 109, 122, 124, 217 insurance, 230 integration, 2, 4, 15, 43, 72, 73, 103, 122, 123, 138, 163, 201, 207, 222, 235, 239, 248, 254, 255 integrity, 80, 84, 92, 101 intentions, 65 interaction, x, 113, 126, 168, 189, 191, 192, 193, 194, 197, 198 interactions, 50, 194, 206 interdependence, 196 interest groups, 169, 192, 193, 194, 200, 225, 226 interest rates, 29 interface, 197 internalizing, 6 international trade, 5, 51, 244 internationalization, 51 Internet, 190 interval, 14, 143, 144, 145, 146 intervention, 8, 37, 71, 127, 129 investment, 4, 6, 15, 16, 21, 22, 26, 37, 38, 40, 46, 47, 52, 70, 71, 158, 164 involuntary unemployment, 51 ionizing radiation, 8 Ireland, 57, 115 IRR, 24, 26, 31, 32, 33 isolation, vii, 1, 34 issues, vii, viii, x, xii, 1, 2, 3, 6, 27, 29, 34, 45, 65, 80, 110, 111, 112, 116, 117, 128, 129, 136, 164, 168, 170, 171, 176, 177, 179, 180, 181, 182, 190, 193, 194, 196, 199, 207, 216, 219, 222, 223, 227, 238, 241, 248, 251, 252, 264, 265 Italy, v, viii, ix, 45, 54, 76, 107, 108, 109, 110, 112, 113, 114, 115, 116, 117, 118, 120, 121, 122, 123, 124, 125, 126, 128, 129, 130, 131, 132, 252

J Japan, 53, 54, 78, 202, 211, 212 job mobility, 181 job performance, 170 jobs, xii, 216, 233 Jordan, 184, 185 jurisdiction, 111, 168, 172, 239 justification, viii, 79

K knowledge acquisition, 169 Kola Peninsula, 210

L labor, 6, 16, 88, 226 labour, 52, 213, 214, 215 lakes, 84, 85, 92 land, vii, xii, 7, 8, 60, 61, 62, 63, 64, 65, 67, 71, 74, 75, 109, 110, 112, 114, 117, 122, 131, 133, 157, 158, 162, 204, 214, 223, 225, 226, 229, 231, 242, 245, 246, 248, 251, 252, 253, 254, 255, 258, 259, 260, 262, 263, 264, 265, 266, 267, 268 land use, vii, xii, 7, 60, 61, 65, 75, 110, 112, 114, 214, 226, 229, 231, 245, 251, 252, 253, 254, 255, 258, 259, 260, 262, 263, 264, 265, 266, 267 Land Use Policy, 265 landscape, ix, 72, 108, 117, 131, 133, 189, 252, 254, 255, 258, 259, 260, 261, 267 Landscape, 111, 118, 120, 122, 123, 124, 133, 254, 266, 268 landscapes, 58 land-use, xii, 122, 223, 231, 242, 246, 251, 252, 253, 254, 259, 260, 262, 265 language, 224 laws, 82, 112, 130, 214 learning, 133, 155, 174, 180, 184, 188, 189, 191, 193, 196, 202, 231, 234 learning environment, 191 learning process, 191 Lee Kuan Yew, 167 Legalism, 183 legislation, 9, 17, 48, 65, 95, 111, 112, 204, 230, 237, 240, 245, 248 leisure, 126, 215 life cycle, viii, 3, 35, 40, 41, 42, 79, 80, 83, 88, 90, 94, 99, 100, 104, 207, 219 limestone, 257 line, 27, 29, 70, 109, 110, 117, 118, 166, 227 linear function, 6 linear programming, 146 linearity, 238 linkage, 113 links, vii, viii, 6, 8, 57, 79, 90, 122, 130, 169 liquidity, 15 listening, 241 Lithuania, 115 livestock, 74, 226 loans, 230 local authorities, 227, 228 local government, 192 localization, 51, 52 logging, 129 logistics, 35, 41, 165, 215 loyalty, 7 lying, 237, 244

Index

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M maintenance, 3, 86, 188, 205, 214, 215, 216, 238 major cities, 69 majority, 58, 128, 137, 155, 172 mandates, 230, 231 manganese, 96 manipulation, 193 manufacturing, 2, 3, 5, 6, 8, 9, 10, 22, 23, 27, 34, 69, 76, 136, 137, 138, 147, 150, 166, 206, 207, 212 map unit, 259, 264 mapping, vii, 2, 156, 179, 253, 254, 255, 259, 260, 261, 262, 263 marginal product, 71 marine environment, 237, 239, 242, 245, 246, 249, 250 market, viii, 2, 5, 9, 12, 14, 30, 36, 37, 39, 45, 46, 47, 48, 49, 50, 51, 52, 74, 138, 157, 158, 162, 163, 165, 193, 210 market incentives, viii, 45, 46 market position, 50 market share, viii, 45, 46, 47, 51, 52 market structure, 47 marketing, 74, 201, 213 marketplace, 4 markets, 9, 19, 20, 22, 47, 49, 50, 157, 217 mass media, 227 material resources, 136, 218 matrix, 139, 143, 145, 148, 149, 151, 154, 158, 162 meanings, 196 measurement, 7, 65, 139 measures, viii, ix, 14, 35, 51, 52, 55, 56, 72, 74, 79, 85, 86, 90, 95, 96, 97, 100, 117, 140, 150, 151, 167, 208, 236, 237, 238, 242, 244, 245, 247, 267 meat, 74 media, 41, 224, 227, 229 mediation, 265, 266 Mediterranean, vi, viii, ix, xii, 58, 61, 65, 66, 74, 85, 93, 107, 108, 110, 117, 120, 124, 127, 251, 252, 254, 264, 265, 266, 267 Mediterranean climate, 58, 61 membranes, 148 messages, 169 metallurgy, 69 metals, 8, 96 meter, 128, 153 methodological procedures, 199 methodology, vii, x, 1, 3, 4, 7, 8, 12, 16, 24, 27, 40, 41, 43, 72, 96, 103, 131, 187, 224, 259, 267 Mexico, 227, 228, 229 microcosms, 92 migration, 109, 226 minimum price, 157

277

mining, 212, 219, 246 MIP, 21 missions, 8, 9, 14, 27, 30, 34, 82, 87, 94, 95, 97, 99, 100, 103, 139, 150, 222 mixing, 89 mobility, 181 model, vii, x, 1, 2, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 20, 21, 34, 48, 65, 72, 76, 80, 82, 83, 84, 90, 100, 102, 103, 104, 136, 138, 146, 147, 152, 155, 157, 159, 160, 161, 162, 163, 165, 188, 192, 203, 205, 206, 216, 218, 228 modeling, 5, 7, 8, 10, 15, 21, 42, 83, 102, 137, 138, 164, 170 modelling, 92, 100, 101, 105, 131, 169, 179, 180 models, ix, 4, 5, 8, 11, 13, 15, 82, 83, 84, 92, 93, 100, 101, 108, 117, 128, 135, 136, 137, 138, 147, 149, 155, 163, 165, 217, 218, 265 modernization, 66, 71, 72 moisture, xi, 221 momentum, 198 money, 39, 53, 139, 143, 145, 150, 155, 158 Montana, 131, 132, 133 morale, 7 mortality, 18, 84 mosaic, 120 mountains, ix, 58, 107, 126 movement, x, 15, 73, 187, 188, 194 multidimensional, 156, 165 multidimensional data, 165 mutual respect, 191

N narratives, 199, 200 nation, 49, 51, 202, 222, 225, 234, 239 national parks, 111 native species, 238 NATO, 101 natural hazards, xi, 222, 223, 229, 231 natural resource management, 173 natural resources, xii, 52, 64, 75, 88, 104, 136, 163, 233, 234, 253, 254 natural sciences, 173 natural selection, 86 nature conservation, 238, 241, 247 neglect, 83 negotiation, 189, 191, 193, 194, 255, 266 net exports, 52 Netherlands, 41, 56, 93, 101, 197, 211, 234, 235, 237, 238, 239, 240, 243, 244, 245, 249, 250, 266 New South Wales, 187, 265 New Zealand, 182, 183, 184, 230 NFI, 114 NGOs, 179

278

Index

nickel, 96 nitrification, 8 nitrogen, 90, 154 nodes, vii, 2, 6, 10, 11, 20, 27, 190 noise, 7, 214 normal distribution, 144 North Africa, 58 North America, 211, 212 Norway, 115, 234, 238, 240, 249

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O objective reality, 201 objectives, viii, xii, 29, 65, 72, 73, 74, 79, 88, 90, 94, 101, 109, 117, 137, 157, 194, 214, 222, 225, 229, 234, 235, 236, 238, 241, 242, 243, 247, 262 obligation, 65 observations, 97 obstacles, 196, 230 oceans, 234, 249 OECD, 49, 50, 52, 78 oil, xii, 71, 76, 92, 212, 233, 238, 243, 245, 246, 247 operations research, ix, 135, 136 opportunities, viii, x, xii, 5, 10, 42, 46, 108, 129, 130, 166, 200, 203, 205, 208, 210, 219, 233, 241, 242, 243, 248, 262 opt out, 247 optimization, vii, 1, 3, 4, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 34, 40, 41, 42, 80, 83, 94, 99, 100, 101, 102, 138, 143, 144, 145, 149, 163 order, vii, x, 1, 3, 4, 5, 6, 9, 10, 15, 16, 21, 22, 29, 30, 33, 34, 49, 52, 55, 56, 65, 71, 74, 76, 86, 89, 96, 98, 109, 111, 115, 116, 117, 120, 125, 126, 128, 129, 130, 137, 138, 140, 141, 143, 144, 145, 146, 147, 149, 150, 152, 155, 169, 170, 187, 189, 193,멐195, 196, 203, 212, 213, 215, 227, 230, 234, 255, 259 organ, 65, 86, 112, 168, 190, 198 organic chemicals, 20 organic compounds, 96 organic food, 73 organic matter, 253, 254 organism, 86, 215 orientation, 76, 172, 173, 181, 190, 204 oscillation, 84 output method, 86 outreach, 191 overhead costs, 6 oversight, 224 ownership, ix, 107, 108, 110, 193, 195, 242 oxidation, 8, 18 oxygen, 19 ozone, 7, 8

P Pacific, 231 paradigm, 166 parallel, 51, 130, 215 parameter, 11, 16, 143, 144, 145, 146, 153, 156, 157, 224, 253 parameters, viii, 11, 34, 45, 46, 47, 48, 79, 80, 92, 94, 95, 97, 103, 104, 117, 136, 144, 145, 155, 156, 157, 160, 161, 162, 163, 253, 254, 256 Pareto, 27, 29, 34 Parliament, 66, 249 participatory democracy, 190 partnership, 118 passive, 24, 174 pasture, 74, 110 pastures, 117 pathways, 193 pattern recognition, 155 peers, 176, 179 penalties, ix, 6, 135, 136, 137, 138, 139, 140, 144, 145, 150, 151, 153, 216 perceptions, 192 performance, vii, 1, 2, 4, 5, 14, 41, 46, 47, 49, 50, 51, 54, 55, 61, 64, 75, 81, 86, 88, 90, 155, 164, 170, 206, 207, 210, 213, 214, 215, 236, 238 performance indicator, 2, 14, 86, 90 permeability, 254 permission, iv permit, 15, 95, 253 personal communication, 250 personnel costs, 17 pesticide, 92 Philippines, 211 phytoplankton, 83, 84, 85, 92, 103 planning decisions, 5 plants, 4, 5, 19, 31, 34, 40, 43, 46, 52, 70, 93, 94, 95, 208, 216 plastics, 69 platform, 118, 131 pluralist society, 264 Poland, 56, 99, 234, 241 police, 110 policy instruments, viii, 46, 53, 58 policy makers, 52, 53, 113 policy making, 188, 201, 202, 226 policy options, 176 policy problems, 193 political participation, 190 politics, 201, 202, 206 pollutants, 7, 53, 96, 138, 147, 149 polluters, 46

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Index pollution, ix, 2, 6, 7, 9, 24, 34, 41, 46, 47, 48, 53, 54, 55, 57, 77, 78, 85, 87, 88, 89, 90, 92, 93, 94, 95, 96, 103, 135, 136, 137, 138, 139, 140, 141, 143, 144, 145, 147, 149, 150, 151, 152, 153, 163, 204, 206, 207, 213, 216, 239, 252, 254, 255, 259, 260, 267 polymers, 18 poor, 126, 215 population, xi, 59, 60, 70, 109, 125, 198, 213, 214, 221, 222, 225, 226 population density, 60 population group, 222 population growth, xi, 221, 225, 226 portfolio, ix, 6, 135, 136, 163 portfolios, 163, 171 Portugal, 57, 252 positive correlation, 83 power, 86, 90, 93, 94, 103, 191, 193, 197, 226, 231, 237 power plants, 94 practical knowledge, 126 prediction, 102, 155, 164, 166, 227 preference, xii, 180, 188, 200, 251, 259, 261, 263 preparedness, xi, 222, 229, 231 pre-planning, 236 present value, viii, 2, 30, 39 pressure, 67, 82, 94, 109 prevention, ix, 41, 66, 135, 136, 137, 147, 163, 206, 207, 216 price elasticity, 47 prices, 16, 21, 22, 32, 47, 53, 55, 157, 162, 244 pricing policies, 56 primacy, 201 private sector, 74, 190, 224 probability, 139, 140, 141, 144, 155, 156, 157 probability distribution, 144, 155 probability theory, 155 problem solving, 191, 193 problem-solving, 189, 196 procedural rule, 194 process innovation, 42 producers, 12, 84, 147, 180, 192, 194 product design, 2 production, vii, viii, ix, 1, 2, 5, 6, 10, 11, 12, 13, 15, 16, 18, 19, 20, 21, 22, 23, 24, 26, 27, 29, 30, 31, 32, 33, 34, 36, 37, 39, 43, 45, 46, 47, 48, 52, 53, 54, 56, 57, 61, 63, 64, 66, 69, 72, 73, 74, 75, 86, 89, 93, 94, 100, 112, 117, 125, 126, 130, 135, 136,멐137, 138, 139, 141, 142, 143, 147, 148, 149, 150, 151, 152, 153, 155, 157, 158, 163, 164, 165, 166, 192, 193, 206, 207, 210, 212, 216, 217, 259, 260, 262 production capacity, 5, 27, 210

279

production costs, 16, 216 production quota, 136, 155 production technology, 139 productive capacity, 112 productivity, 46, 47, 48, 49, 50, 51, 52, 54, 55, 57, 64, 71, 75, 76, 158 professionalism, 197 profit, 14, 17, 27, 39, 50, 52, 138, 146, 173, 174, 191, 214 profitability, 47, 52, 262 profits, x, 71, 203 program, ix, 9, 107, 108, 200, 202, 227, 235 programming, ix, 107, 136, 138, 141, 142, 143, 145, 146, 149, 152, 153, 155, 157, 159, 163, 165, 166 project, 6, 17, 18, 29, 74, 181, 189, 196, 199, 212, 242 proliferation, 120 properties, ix, 27, 80, 82, 84, 102, 107, 109, 111, 120, 128, 257 proportionality, 140, 151 prosperity, 49 protected areas, ix, 108, 121, 238, 239, 246, 247 protocol, 10 protocols, 10 prototype, 41 public administration, 173, 175, 190, 202, 219 public domain, 65 public interest, 52, 224, 226 public opinion, 128, 169 public policy, x, 167, 168, 173, 187, 190 public sector, x, 167 public service, 168, 171, 181 pulp, 57 pumps, 94 purification, 53 pyrolysis, 20

Q qualifications, 197 quality improvement, 200 quality of life, 213 quality standards, 53 questioning, 197 quotas, 136, 155, 157, 162, 163

R radiation, 7, 8, 20, 21, 89 rain, 9 rainfall, xi, 58, 221, 255 random errors, 139 range, 41, 50, 55, 74, 93, 117, 143, 144, 145, 150, 152, 153, 158, 160, 192, 238, 248

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280

Index

rate of return, 26 ratings, 259, 262 rationality, 196 raw materials, 2, 3, 4, 5, 6, 7, 9, 15, 19, 20, 22, 26, 36, 39, 52, 138, 207, 210 reactions, 18, 82, 84 real estate, 166 real income, 49, 50 real numbers, 150 reality, ix, 74, 108, 128, 201 reason, 156, 181, 212, 239 reasoning, 193 recall, 31, 147 reciprocity, 196 recognition, 81, 155, 188, 197, 200, 201, 229 recommendations, iv, 113, 224, 226, 228, 248 reconcile, 83 reconciliation, 104 recovery, 41, 57, 71, 72, 93, 101, 208, 212, 216, 229 recovery plan, 229 recovery processes, 93 recreation, xi, 221 recreational areas, 204 recycling, 3, 9, 82, 207, 208, 212, 216 reference system, 254, 257 reflection, 247 regeneration, 126, 127, 128, 129, 189, 260 region, xii, 49, 50, 51, 58, 60, 67, 68, 69, 72, 110, 120, 125, 200, 222, 225, 226, 251, 252, 254, 263, 264 Registry, 9 regulation, vii, viii, 4, 45, 46, 47, 48, 53, 58, 66, 70, 74, 76, 77, 78, 111, 129, 164, 194, 204 regulations, ix, 7, 16, 34, 74, 108, 112, 118, 131, 135, 136, 137, 155, 204, 216, 242 regulatory framework, 110, 118 rehabilitation, 206, 207, 208, 212, 213, 214 relationship, viii, 45, 64, 78, 112, 128, 129, 131, 205, 206, 246, 257 relevance, 51 relief, 254 remediation, 88, 90, 97 remote sensing, 237 renewable energy, xi, 8, 20, 21, 233 replacement, 11 reprocessing, 210 reputation, 48 reserves, 111 residues, 37, 147 resilience, 126 resins, 18 resolution, 108, 169 resource allocation, 222, 258

resource management, x, 112, 166, 167, 173, 217 resources, viii, ix, x, xii, 4, 5, 8, 15, 27, 28, 34, 45, 46, 47, 48, 51, 52, 56, 58, 64, 65, 66, 67, 71, 72, 73, 74, 75, 76, 80, 87, 88, 89, 90, 93, 94, 103, 104, 109, 110, 111, 112, 114, 116, 117, 121, 122, 128, 136, 137, 139, 147, 150, 153, 155, 163, 167, 168, 170, 175, 178, 179, 181, 189, 191, 194, 195, 203, 205, 207, 208, 210, 213, 217, 218, 225, 226, 228, 229, 230, 233, 234, 241, 255, 259, 262, 263, 264 respect, 13, 59, 61, 64, 65, 66, 71, 75, 82, 97, 110, 111, 118, 130, 190, 191, 192, 193, 195, 197, 225 respiration, 84, 85 respiratory, 8 restructuring, 71 returns, 50, 52 revenue, 9, 15 rhetoric, 180 rice, 33, 47, 64, 72, 73, 138, 158 risk, xi, xii, 7, 57, 72, 110, 138, 139, 140, 141, 143, 145, 147, 150, 151, 152, 153, 158, 160, 161, 165, 204, 221, 222, 224, 225, 226, 227, 228, 229, 231, 251, 252, 261, 265, 268 risk assessment, 224, 226, 228, 229 risk management, 222, 226, 231 river basins, 65, 66 role playing, 193 Romania, 78, 116, 165 rural development, 73, 130 Russia, 210, 239

S safety, 72, 141, 147, 148, 149, 165, 204, 244 sales, 5, 8, 12, 15, 22, 27, 29, 33, 38, 47 sample mean, 162 sample variance, 162 sampling, 53, 139 sampling error, 139 satisfaction, 155 savings, 2, 47, 72 scaling, 113, 179 scarcity, xi, 48, 70, 221 scheduling, 11, 12, 35, 40, 42 school, 7, 8, 74, 126 scientific knowledge, 108 scores, 224 sea level, 244 seafood, xi, 233 sea-level rise, 237 search, 46, 166, 206, 210, 262, 266 searches, 171 secondary education, 174 security, xi, xii, 233

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Index selecting, 5, 54, 139 self-organization, 83 self-regulation, 194, 204 semiotics, 103 sensing, 237 sensitivity, 35, 179 separation, 11, 93, 94, 96, 208, 246, 247 sequencing, 12 sewage, 53, 86, 138, 204 shade, 129 shape, 175 shaping, 199 shares, viii, 45, 46, 47, 52, 191 sharing, 2, 126, 191, 193, 194, 211 sharing of responsibility, 2 shelter, 126 short run, 48, 234, 242 shortage, 222, 225, 226 shrubs, 126, 128 signals, 76 simulation, 21, 30, 43, 144, 162, 214 Singapore, 167, 210, 220 skills, 169, 189, 195, 210, 213, 214, 242 Slovakia, 116 smog, 5, 7 smoke, 214 social behavior, xi, 221 social environment, 217 social learning, 188, 202 social network, 190 social relations, 190 social relationships, 190 social welfare, 171, 176, 179 societal cost, 97 sodium, 257 software, 21, 171, 266 soil, 20, 21, 72, 128, 157, 252, 253, 254, 255, 256, 257, 259, 260, 261, 267 soil erosion, 72, 255, 259, 260, 261, 267 soil pollution, 252, 255, 260 solid waste, 99, 147 soybean, 161 space, xi, 58, 86, 113, 126, 139, 156, 157, 165, 204, 233, 234, 237, 239, 242, 243, 245, 247 specialization, 51 species, xi, 18, 84, 85, 92, 93, 100, 103, 126, 129, 134, 233, 238, 239 species richness, 84 spectrum, 202 stability, 83, 92, 130, 193, 254 stakeholder groups, 241

281

stakeholders, xii, 73, 76, 108, 126, 128, 130, 169, 189, 191, 192, 193, 194, 195, 196, 226, 241, 245, 248, 251, 252, 255, 258, 259, 262, 263, 264 standard of living, viii, 45, 46, 50, 52 standards, 41, 51, 53, 110, 138, 214 stasis, 130 state planning, 230, 231 statistics, 155, 244 steel, 212 sterile, 235 stimulus, 55, 137, 198 stock, 39, 126, 128, 129, 242 storage, 16, 81, 82, 83, 85, 93, 94, 98, 103, 212 storytelling, 195 strategic planning, 42 strategies, vii, x, 1, 3, 10, 43, 113, 117, 136, 163, 164, 166, 191, 201, 203, 205, 206, 208, 214, 217, 222, 229, 264 strategy, x, 18, 118, 166, 200, 203, 204, 205, 206, 208, 214, 217, 222, 244, 250 strength, 125 stress, 63, 188, 191, 225, 234 stressors, 92 structural changes, 83, 87, 100 structural funds, 46 structuring, 73 students, 74 subjectivity, 10, 34 subsidization, 71 subsidy, 32, 33, 71 substitution, 48 sugar, 4 sulphur, 77 summer, 68 suppliers, 4, 5, 15, 19, 20, 22, 26, 34, 35, 36, 210, 217, 229 supply, vii, xi, 1, 2, 4, 5, 9, 40, 41, 42, 43, 53, 54, 57, 65, 66, 70, 71, 74, 109, 171, 178, 200, 204, 210, 220, 221, 226, 227, 228, 233 supply chain, vii, 1, 2, 9, 40, 41, 42, 43, 54, 210, 220 surplus, 20, 21 survey, x, 132, 137, 139, 168, 171, 175, 179, 180, 181, 200, 228 survival, 137 sustainability, 4, 17, 41, 48, 64, 66, 72, 73, 76, 80, 83, 88, 100, 105, 118, 126, 165, 203, 205, 206 sustainable development, ix, 72, 80, 90, 99, 104, 135, 136, 137, 206, 216, 219, 230, 245, 248, 250 Sweden, 40, 43, 56, 116, 234, 245, 250 Switzerland, 41, 92, 115 symbiosis, 206, 212, 219 synthesis, 40, 114, 121, 126, 165, 218

282

Index

Copyright © 2010. Nova Science Publishers, Incorporated. All rights reserved.

T Taiwan, 266 tanks, 169, 182, 212 targets, 155, 157, 170 tariff, 53, 56, 72 taxation, 53 taxonomy, 207 TCR, 9 technical assistance, 130, 226 technology transfer, 77 TEG, 20, 21 telecommunications, 215 telephone, 171, 215 temperature, xi, 59, 82, 94, 221 territory, 51, 58, 61, 65, 66, 196, 204 testing, 227 textbooks, 180 texture, 254, 257 Thailand, 212 thermal energy, 81, 94, 98, 103 thermodynamic method, 86 thermodynamic properties, 84, 102 thermodynamics, viii, 79, 80, 81, 82, 84, 86, 89, 90, 97, 98, 101, 104 thinking, 2, 177, 219, 246 thinning, 121 threat, 195 threats, 239 threshold, 117 timber, 117 time constraints, 228 time frame, 234, 237 time periods, 111 time series, 155, 164 timing, xi, 12, 221, 239 tissue, 128 topology, 2, 3, 10 total costs, 57 total energy, xi, 233 total product, 11, 22, 27, 61 total revenue, 15 tourism, xi, 68, 126, 221, 229, 252, 259 toxicity, 8, 136 toxicology, 7 tradable permits, 9 trade, vii, ix, 1, 3, 5, 17, 27, 40, 51, 52, 76, 135, 136, 137, 171, 176, 181, 194, 237, 244 trade-off, vii, ix, 1, 3, 17, 27, 40, 135, 136, 137, 194, 237 trading, vii, 2, 5, 10, 14, 17, 27, 30, 31, 34, 35, 36, 38, 39, 43, 72 tradition, 70, 125, 126, 188, 241

traditional views, 193 traditions, 110, 120 traffic, 246 training, x, 72, 76, 121, 168, 170, 173, 174, 175, 181, 214, 234 trajectory, 77 transaction costs, 217 transactions, 210 transformation, 72, 73, 136, 206, 218 transformations, 265 transition, 65, 194, 226, 250 translation, 10, 13, 84 transparency, 92, 264 transport, 3, 5, 9, 13, 15, 20, 21, 24, 26, 33, 39, 95, 238 transportation, 6, 13, 15, 20, 21, 22, 24, 26, 27, 32, 33, 34, 36, 37, 38, 94 trees, 74, 126, 128, 129, 179 trends, x, xi, 21, 78, 95, 100, 117, 169, 170, 203, 221, 225, 226, 242, 243, 244, 247 trial, 95 trust, 195, 242 tsunami, 231 Turkey, 116 turnover, 47, 51, 53, 57

U Ukraine, 116 uncertainty, xi, 8, 35, 40, 136, 138, 139, 155, 163, 164, 166, 217, 222, 237, 238 unemployment, 51, 213 unemployment rate, 213 UNESCO, 54, 55, 233, 248, 252, 265 uniform, 71 United Kingdom, 115, 211, 230, 234, 245, 247, 248, 250, 267, 268 United Nations, 77, 115, 122, 134, 217, 235, 252, 265, 268 United Nations Development Programme, 217 universities, 169, 224, 227 updating, 112, 122, 123, 180, 227, 230 urban areas, 65, 66, 212 urbanization, xi, 221, 226

V Valencia, 251, 260, 261, 264, 265, 266, 267, 268 valuation, 6, 90, 227, 230, 237, 243, 249 vanadium, 96 variability, 175, 238 variable costs, 46, 47 variables, 10, 18, 21, 51, 55, 136, 138, 139, 144, 146, 147, 148, 150, 151, 153, 156, 157

Index variance, 69, 151, 158, 162 variations, 72 vector, 69, 147, 150, 153, 154, 162 vegetables, 74 vegetation, 254, 255, 259, 261, 262 vehicles, 100 Venezuela, 267 venue, 197 vibration, 214 victims, 227 vision, 245 visions, 243 visualization, 247 voice, 66, 194 voiding, 85 voters, 193 vulnerability, xi, 210, 221, 222, 225, 226, 229, 254, 255, 259, 260, 262, 267

W

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Wales, 187, 265 war, 43, 109, 111 waste, 4, 6, 7, 9, 16, 36, 39, 40, 41, 43, 46, 82, 86, 95, 96, 97, 98, 99, 100, 103, 138, 147, 164, 200, 204, 207, 208, 210, 212, 215, 216, 217 waste heat, 7 waste management, 6, 41, 212 waste treatment, 4, 6, 9, 16, 36, 39, 99, 212 waste water, 200 wastewater, 52, 53, 56, 57, 69, 70, 72, 147, 200 water policy, viii, 46, 58, 65, 70, 78, 249

283

water quality, 53, 85, 98, 100, 200, 243 water resources, viii, 45, 52, 56, 58, 65, 66, 67, 72, 73, 76, 225, 226, 228 water rights, 70 water supplies, 226, 227 wealth, 58 welfare, 51, 171, 176, 179, 180, 181 wellness, 7, 80 wells, xi, 221 Western Europe, 211 wetlands, 92, 105 whales, 238 wheat, 161 White House, 248 wildlife, 226, 229 wind, xi, xii, 221, 233, 234, 241, 242, 243, 247, 248 wind farm, 248 wind turbines, 233, 242 wood, 109, 110, 111, 112, 125, 126, 128, 129, 130, 259, 260, 262 wood products, 125 workers, 156, 213 worry, 172

Y yarn, 148

Z zooplankton, 84, 92