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Suhaib A. Bandh Editor
Strategizing Agricultural Management for Climate Change Mitigation and Adaptation
Strategizing Agricultural Management for Climate Change Mitigation and Adaptation
Suhaib A. Bandh Editor
Strategizing Agricultural Management for Climate Change Mitigation and Adaptation
Editor Suhaib A. Bandh Department of Higher Education Government of Jammu and Kashmir Srinagar, India
ISBN 978-3-031-32788-9 ISBN 978-3-031-32789-6 (eBook) https://doi.org/10.1007/978-3-031-32789-6 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Dedicated To Prof. Azra N. Kamili
Preface
Agriculture is a sector that is deeply affected by climate change. As the world’s population continues to grow and the demand for food increases, climate change will pose significant challenges to the sustainability of agricultural systems. Improvements in agriculture over the past 50 years have made it feasible to meet the food, feed, and fiber needs of the world’s largest human population. However, due to widespread urbanization, severe land degradation, and climate change, it is difficult to keep the supply for the ever-increasing human population. Given its negative impact on agricultural output, the latter is arguably the greatest food security danger of the twenty-first century. Agricultural output has been significantly impacted by global climate change, and agriculture is also a major contributor to climate change by raising atmospheric greenhouse gas concentrations. To strike a healthy balance between agricultural output and associated climate effects, there has never been a greater need for innovative approaches to agricultural technology and management. To meet the challenges of maintaining the continuous rise in agricultural production, bolstering the resilience of crop production to climate change, and guaranteeing success in climate change mitigation, adjustments in agriculture management are necessary. However, the success of agricultural management-based adaptation and mitigation of climate change, demands the development of straightforward, economical, and highly flexible approaches. As a result, planning for agricultural administration is crucial for dealing with climate change. A significant increase in the input from the scientific community in this research area would play a key role in understanding how strategizing agricultural management can help in adapting to climate change and mitigating its effects on agricultural production. With careful planning and innovative techniques, we can turn agriculture into a solution rather than a problem. By adopting sustainable farming methods like agroforestry, crop rotation, cover cropping, and reducing tillage intensity, farmers can sequester carbon in the soil while improving their yields and increasing resilience against extreme weather events. Furthermore, promoting local food systems that reduce transportation emissions and supporting regenerative farming practices that prioritize biodiversity conservation can help mitigate the negative impacts of agriculture on the environment. Improving water management through measures like vii
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conservation agriculture can have a significant impact on mitigating climate change in agriculture. These strategies are achievable and can be implemented across a wide range of agricultural landscapes to mitigate the impacts of climate change. While these measures might require investments in technologies and training, they are feasible and have the potential to deliver benefits to both the environment and the farmers. Therefore, such approaches will be needed to address the challenges that climate change presents to the agricultural sector, ensuring its continued productivity in the future. Pulwama, India
Suhaib A. Bandh
Acknowledgements
If every project has its secret inspiration or at least its one motivation, here that is the PEACE of my life.
In the name of Allah, the Most Gracious, the Most Merciful. May the praise of Allah, in the highest of assemblies, and His peace, safety and security, both in this world and the next, be on Prophet Mohammad (peace be upon Him), the best of humankind, the most respectable personality for whom Allah created the whole universe and the seal of the Prophets and Messengers. I am highly thankful to Allah, who provided me with the courage and guidance to undertake and complete this project with his great mercy and benevolence. First and foremost, I would like to thank all my teachers who held my finger to tread the learning path and enabled me to compile a book. I deeply thank them for the advice and encouragement, which guided my personal and professional development. Publication of a research article, review article or book requires the efforts of many people besides the authors. I wish to express my special appreciation to Springer’s editorial and production staff including Herbert Moses and Henry Rodgers for their excellent and efficient work. In particular, I would like to thank Aaron Schiller, Senior Editor Springer Nature, for his unwavering confidence in me. They were there whenever needed and they supervised the production of this project with commendable attention to all its minute and vivid details. Inevitably, a book of this type relies heavily on previously published work. I want to thank all the copyright holders for granting permission to publish original diagrams and data. My special thanks go to Keith McNeill, Vincent Happy Ogwugwa, Mahroz Hussain, Abdullah Kavini Rad, Dr. Muhammad Irfan, Charles Anukwonke, Vahid Karimi, Dr. Muhammad Ziaul Hoque, Naser Valizadeh, Pritha Datta, Elame Fouad, and Dr. Muhammad Adil for their valuable contributions to this book. I wish to extend my appreciation to all the people who assisted me individually in completing this project. I am extremely grateful to all the reviewers who provided their timely inputs to improve the quality of the chapters. My special thanks are due to all those who have directly or indirectly worked for the successful completion of this project. Finally,
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but most importantly, I wish to extend my appreciation to my family for their patience and encouragement during the period of its compilation. I owe a debt of gratitude to all of them for their patient forbearance and unwavering support. Pulwama, India
Suhaib A. Bandh
Contents
1 Nitrogen Fertilizer Application Techniques to Reduce Nitrous Oxide Emissions ������������������������������������������������������������������������ 1 Vincent Happy Ogwugwa and Suhaib A. Bandh 2 Rice Production Technologies in Reducing Methane Gas Emissions for Sustainable Environment���������������������������������������� 11 Hamna Bashir, Irshad Bibi, Nabeel Khan Niazi, Abdul Qadeer, Shumaila Zaman, Ayesha Farzand, Muhammad Mahroz Hussain, and Muhammad Ashir Hameed 3 Manure Management to Reduce Methane Emissions�������������������������� 29 Abdullah Kaviani Rad, Hassan Etesami, Angelika Astaikina, and Rostislav Streletskii 4 Crop Residue Incorporation to Enhance Soil Health in the Rice–Wheat System���������������������������������������������������������������������� 47 Hamna Bashir, Waqas Mohy-Ud-Din, Zahoor Mujdded Choudary, Muhammad Mahroz Hussain, and Muhammad Ashir Hameed 5 Promoting Energy Crops to Replace Fossil Fuel Use �������������������������� 69 Muhammad Irfan, Liu Xianhua, Asia Shauket, Muhammad Jafir, Adeel Ahmad, Samina Jam Nazeer Ahmad, and Jam Nazeer Ahmad 6 Changes in the Agriculture Sector That Are Essential to Mitigate and Adapt to Climate Changes ������������������������������������������ 89 Enohetta B. Tambe, Charles C. Anukwonke, Iheoma E. Mbuka-Nwosu, and Chinedu I. Abazu 7 Adaptation and Maladaptation to Climate Change: Farmers’ Perceptions������������������������������������������������������������������������������ 113 Vahid Karimi, Masoud Bijani, Zeynab Hallaj, Naser Valizadeh, Negin Fallah Haghighi, and Mandana Karimi
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8 Farmers’ Perception of Climate Change in Climatically Vulnerable Ecosystem of Bangladesh���������������������������������������������������� 133 Foyez Ahmed Prodhan, Muhammad Ziaul Hoque, Md. Safiul Islam Afrad, Md. Enamul Haque, Minhaz Ahmed, Md. Humayun Kabir, Md. Sadekur Rahman, and Naima Sultana 9 Pest and Disease Management Under Changing Climate�������������������� 149 Yaser Biniaz, Naser Valizadeh, Farshad Hemmati, and Alireza Afsharifar 10 C limate Change Adaptation Through Agroforestry: Empirical Evidence from Indian Eastern Himalayan Foothills���������� 167 Pritha Datta and Bhagirath Behera 11 Policy Framework to Introduce Climate-Smart Agriculture�������������� 183 Fatemeh Fathi, Naser Valizadeh, Samira Esfandyari Bayat, and Khadijeh Bazrafkan 12 Technological and Managerial Innovation in Agriculture to Ensure Food Security Under Climate Change���������������������������������� 207 Fouad Elame, Hayat Lionboui, and Mohammed Behnassi 13 Oyster Farming and a Worldwide Referendum on Global Carbon Fee-and-Dividend���������������������������������������������������������������������� 221 Keith McNeill 14 Climate Change Impact Modeling on Citrus Yield������������������������������ 233 Fouad Elame, Youssef Chebli, Hallam Jamal, and Lionboui Hayat 15 Impact of Climate Change on Environmental Fate and Ecological Effects of Pesticides�������������������������������������������������������� 247 Muhammad Adil, Ghazanfar Abbas, Rabia Naeem Khan, and Faheem Abbas Index������������������������������������������������������������������������������������������������������������������ 265
Chapter 1
Nitrogen Fertilizer Application Techniques to Reduce Nitrous Oxide Emissions Vincent Happy Ogwugwa and Suhaib A. Bandh
Abstract Mankind has developed a technique to generate synthetic reactive nitrogen, which serves as a fertilizer to enhance food production. However, once reactive nitrogen molecules are formed, they become highly mobile and can persist in the environment for extended periods, leading to various negative consequences. One such consequence is the increased emission of nitrous oxide (N2O), a long-lived radiatively active greenhouse gas (GHG) with a molecular heat trapping effect approximately 310 times stronger than other gases, posing a significant environmental challenge. To address this issue, optimizing nitrogen (N) fertilization becomes crucial. The goal is to match the supply of nitrogen from fertilizers with the crop’s demand, thereby reducing excess soil nitrogen. By achieving this balance, the production of soil N2O can also be minimized. Several strategies can be employed to achieve this, such as using slow-release fertilizers that gradually release nutrients into the soil. Additionally, the use of chemical urease inhibitors (UI) and nitrification inhibitors (NI) can slow down the conversion of urea to NH4+, further reducing nitrogen loss. Another effective approach is to adopt a split application method, where fertilizer is applied multiple times throughout the crop cycle. This strategy aims to synchronize fertilizer application with the rapid nitrogen demand of the plants, thereby minimizing N2O emissions. Furthermore, foliar nitrogen fertilizer application can be employed, allowing the active absorption of nitrogen into the interior of the leaf blade through plasmodesmata, hydrophilic pores in the waxy cuticle of the leaf surface, and stomata distributed on the leaf surface. These mechanisms enable the efficient absorption of available nutrients. Moreover, the application of nanotechnology offers a promising solution by reducing the reactivity of nutrient inputs into the agricultural system without compromising productivity, holding a great potential for sustainable agriculture. Keywords Fertilizer application · N2O emission · Agriculture and nutrient V. H. Ogwugwa (*) Department of Microbiology, University of Lagos, Lagos, Nigeria S. A. Bandh Department of Higher Education, Government of Jammu and Kashmir, Srinagar, India © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 S. A. Bandh (ed.), Strategizing Agricultural Management for Climate Change Mitigation and Adaptation, https://doi.org/10.1007/978-3-031-32789-6_1
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1 Introduction In 2015, the UN outlined 17 Sustainable Development Goals (SDGs) (Wang et al., 2022). According to studies, there may be links between various aims that are unbreakable, consistent, etc. Goal 2 focuses on agricultural productivity, which aims to end world hunger. Nitrogen fertilizer is a crucial agricultural input for grain growth, but it also has many negative environmental effects (Shakoor et al., 2021). Excess nitrogen fertilizer use may cause significant nitrogen losses, which contribute to eutrophication of freshwater and atmospheric pollution, which is very unfavorable for mitigating climate change, maintaining ecosystem health, and improving water quality. Too little nitrogen fertilizer use may result in low yields, which makes it very unfavorable for ending poverty and hunger, and improving human health. The secret to encouraging the implementation of SDGs related to nitrogen fertilizer is to optimize the application of nitrogen fertilizer (Bai & Gao, 2021). It is well established that nitrogen (N) has a significant influence in biodiversity loss, air pollution (through NOx and NH3 emissions and indirectly on O3), and climate change (via N2O emissions and aerosols and indirectly on CO2, CH4, and O3 emissions). As a result of their strong connections to food security, N use and climate change are two highly essential concerns to take into account (Maaz et al., 2021). Since 1980, China’s grain production has increased by about 70%, and it has also grown to be one of the world’s top emitters of greenhouse gases (GHGs) due to a threefold increase in the usage of N fertilizer in agriculture (Liu et al., 2021). Due to the fast-rising fertilizer N use since 1980, the effects of N fertilizer use on crop output, greenhouse gas (GHG) emissions, and climate change will become more and more significant (Bandh et al., 2021; Bandh, 2022a). The cycling of nitrogen in terrestrial ecosystems may be accelerated by climate change, particularly climatic warming. As a result of fertilizer application, additional N2O and other GHG gases may be released from both croplands and nonarable soils, thus accelerating the rate of climate change (Lan et al., 2021). Additionally, carbon (C) sequestration in terrestrial ecosystems may be impacted by N cycling; this must be considered when forecasting future CO2 uptake. Therefore, it is important to take climate change seriously, especially in emerging economies, and to consider the relationship between N fertilizer application, GHG emissions, and climate change (Shakoor et al., 2021).
2 History of Fertilizer Application Since hundreds of years ago, organic and mineral fertilizers have been applied to grasslands (Ashekuzzaman et al., 2021). Paddock manuring is the most notable instance of the use of organic fertilizer, and it has been done in many areas for millennia. The movement of nutrients by livestock on pasture forms the basis of paddock manuring (Garcia et al., 2021). Small transportable enclosures are used to
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house livestock that grazes on pasture during the day. The majority of the nutrients ingested by animals in other pastures are released as feces and urine at night inside this enclosure. The enclosure is advanced to the sections that need fertilizing after a set amount of time, often 1 week. To take advantage of the fertilizer’s impact on biomass output and fodder quality in later years, such fertilized regions were traditionally most frequently employed for haymaking (Ashekuzzaman et al., 2021 Garcia et al., 2021). Humans have been known to transport and apply nutrients in numerous areas of Europe for ages. For instance, throughout the seventeenth and twentieth centuries, hay was transported from subalpine grasslands down the valleys across a distance of 10–15 km in the Giant Mountains (Krkonoe, Riesengebirge) situated in the borderland between the Czech Republic and Poland. This hay was fed to the cows and goats maintained in the valleys’ cow huts. In close proximity to the farm homes, the grassland or arable land received an application of the organic fertilizer nutrients derived from that hay. As a result, grasslands at lower altitudes saw an increase in biomass output, while grasslands in the subalpine vegetation zone experienced nutrient depletion.
3 Effects of N Fertilizer Use on the Environment The effects of nitrogen fertilizer use on water and air pollution have drawn more attention recently (Martínez-Dalmau et al., 2021). These environmental worries are valid and will become more significant in the coming years. Numerous nations have enacted restrictions on fertilizer use, and further initiatives to do so are likely. In locations where manure and N fertilizer are currently used at rather high levels, such interventions might be necessary. However, the low rates of use combined with increasing population pressure on the limited land resources in the majority of the developing world force expanded fertilizer use to fulfill rising food needs (Kim et al., 2021).
3.1 Emissions Generated by Fertilizer Application 3.1.1 Nitrous Oxide Nitrous oxide (N2O), despite being largely inactive in the troposphere, absorbs infrared light (de Vries, 2021). In the stratosphere, it can also photochemically break down to create nitric oxide, which can interact with ozone. Since roughly 1960, the concentration of N2O has been observed at an increasing rate. Currently, the atmosphere’s N2O concentrations are rising at a rate of roughly 0.3% per year (Cao et al., 2021). There are around 1500 Tg (1012 g/Terra gram) of N2O in the atmosphere. Nearly 90% of the emissions come from soils via biologically driven
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nitrification and denitrification processes. In each of these processes, N2O emission might be seen as a leakage of intermediate products (Wei et al., 2022). While soils play a significant role in the production of N2O, they also act as a sink. The formation of N2O from nitrification is a topic of significant research because worries about N2O as an atmospheric pollutant have increased recently (Ge et al., 2021). The N2O emissions are extremely variable as a result of this process, which is to be expected given the wide range of variables influencing the reaction, such as oxygen availability, water content, temperature, soil pH, organic matter, and the presence of plants. Emissions are typically proportional to the amount of nitrifiable nitrogen in the soil. 3.1.2 Nitric Oxide and Nitrous Oxide Though they are regarded to not be as significant in absorbing light energy as N2O, nitric oxide and nitrous oxide (together referred to as NOx) are involved in significant atmospheric processes (Han et al., 2021). Ozone (O3) and hydroxyl radicals are created when NO oxidizes CH4 and CO at levels that are high enough (>10 ppt). The primary purifying component in the troposphere is hydroxyl radicals. Ozone (O3) and hydroxyl radicals may both experience net losses due to lower NO concentrations. According to Han et al. (2021), NOx can destroy ozone, especially in the stratosphere, and NO2 forms nitric acid when it combines with hydroxyl ions in a photochemically stimulated reaction. Estimates of emissions are primarily based on laboratory studies, and the production of NOx from soils has not been explored to the same extent as N2O. The processes of nitrification, denitrification, chemo denitrification, and perhaps photolysis of nitrite are used to create the gases (Harris et al., 2021). The primary contributors seem to be nitrification mechanisms. Although it is impossible to make judgments about how much N fertilizers contribute to NOx emissions, it is most certainly true; the absolute amounts, however, are quite unpredictable.
4 Climate Change and Its Impact due to Release of Greenhouse Gases (GHGs) According to the United Nations Framework Convention on Climate Change (UNFCCC), climate change has affected food security and human health in many regions and has been a global issue. One of the main causes of climate change, according to experts, is rising worldwide GHG emissions (Oreggioni et al., 2021). As a result, the UN gave the subject of climate change high priority and included it as one of the SDGs. It must work to create a resource-conserving, environmentally friendly society and strengthen the nation’s ability to reduce GHG emissions.
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5 Nitrogen Fertilizer Application Techniques to Reduce Nitrous Oxide Emissions In order to maximize both economic and ecological needs, increasing N fertilizer use efficiency through novel methods and technology is a challenge. By using specialized application methods, such as applying NH4-dominated fertilizer, as well as novel fertilizer technologies, such as coating or the use of nitrification and urease inhibitors, it is possible for farmers to utilize less split N applications (Aliyu et al., 2021). These methods therefore attempt to reduce unproductive N losses and, consequently, negative environmental effects brought on by NO3 leaching and/or gaseous N losses while increasing productivity through an optimized fertilizer usage rate.
5.1 Precision Agriculture (Site-Specific Application) Precision agriculture (PA) technology has advanced quickly over the past few decades, particularly with regard to arable crops, with the aim of facilitating the handling of production tools and resources in an economically viable and sustainable manner through site-specific management. PA could be defined more broadly as the application of information technology across the board in agriculture (Nyaga et al., 2021). The accurate calculation of the necessary N substitution after harvest on a per-plot basis is one method for handling recycled N in farms in an environmentally beneficial manner. It is necessary to periodically check the soil’s nutrient level due to the unequal distribution of nutrients throughout farms. Such a method, nevertheless, does not currently take field heterogeneity into account. Although the challenge of applying fertilizer precisely to farms is not new, the spatial component is now more widely acknowledged as site-specific application technology advances quickly. Site-specific slurry application is seen as a significant contribution to environmentally friendly and efficient nutrient use on grassland when done in accordance with the best practice for nutrient management (Bandh, 2022b).
5.2 Use of Nitrification Inhibitors (NI) The biological nitrification and denitrification processes are the primary sources of N2O in soils. As a non-obligate intermediate during autotrophic nitrification, the hydroxylamine oxidoreductase (HAO) in aerobic soil compartments produces the gas N2O during the oxidation of hydroxylamine. As the first stage of nitrification, NH4’s transformation into NO2 is slowed down by nitrification inhibitors (NI) (Wang et al., 2021). By preserving the immobile NH4 in the soil for a set amount of time, this delay lowers the quantity of NO3 that can be readily leached under specific
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conditions. Additionally, NIs lessen the internal N mineralization of the soil, reducing the possibility of soil NO3 surpluses that could be lost.
5.3 Use of Urease Inhibitor (UI) One of the most popular nitrogen fertilizers is urea, which makes up more than half of the annual consumption of chemical nitrogen fertilizers. Urea is hydrolyzed when applied to soil, and the NH3 that results from this process can be volatilized, resulting in significant financial loss and environmental pollution. Urease inhibitor prolongs the duration that urea diffuses at fertilizer application sites by delaying the water dissolution of urea (Klimczyk et al., 2021). This will decrease the density of NH4+ and NH3 in the soil and lessen the amount of ammonia lost through volatilization. After 30 years of development, there are more than 100 different types of urease inhibitors. The predominant varieties include humic acid, quinines, acidamide, polyacid, polyphenol, etc.
5.4 Slow-Release/Controlled-Release Fertilizer The mismatch between the needs of crops and the frequency and intensity with which fertilizer releases its nutrients is one of the causes of low fertilizer use efficiency. By adjusting the water solubility of regular fertilizer, slow-release/ controlled-release fertilizer is created. By enhancing the fertilizer, itself, which aligns the release time and intensity with the needs of crops, the nitrogen release is effectively controlled or postponed (Dong et al., 2021). This technique can balance the supply of nutrients with the demand from crops, thereby increasing the yield. It is thought to be the simplest and fastest approach to reduce fertilizer loss and its release of gaseous chemicals into the environment. Slow-release fertilizer mainly delays the release of the nutrients and extends the fertilizer effect period. Slow- release fertilizer combines acceleration and delay of the nutrient release from the fertilizers; it can control the speed of nutrient supply.
5.5 Biofertilizer Biofertilizers are useful, living microbes. These include bacterial phosphate solubilizers like Pseudomonas and Bacillus, as well as blue green algae, Rhizobium, Azotobacter, Azotospirillum, and fungal mycorrhizae. Organic matter is broken down by microorganisms into simple chemicals that give plants vital nutrients, raise soil fertility, preserve the soil’s natural habitat, and boost crop output. The successful application of biofertilizers depends on the preparation, storage, and application
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process. Short shelf life, temperature sensitivity, and storage desiccation issues are drawbacks in use (Sun et al., 2021). The potential for covering biofertilizer preparations with polymeric nanoparticles to produce formulations resistant to desiccation has been explored. One method for storing and distributing microorganisms through liquid formulations is the water-in-oil emulsion. The oil prevents the water from evaporating by trapping it around the bacteria. For microorganisms that are susceptible to desiccation, this is very beneficial. By adding chemicals to the oil and/or aqueous phases, water-in-oil emulsions also enhance cell viability and release kinetics. However, one of the main concerns is sedimentation during storage. By thickening the oil phase during storage, hydrophobic silica nanoparticles decreased cell sedimentation and increased cell survival.
5.6 Application of Nanotechnology in Delivery of Fertilizer Massive volumes of fertilizer in the form of urea, nitrate, or phosphate compounds, as well as ammonium salts, have significantly enhanced food production, but they also have many negative impacts on the good soil microflora. Due to runoff, the majority of fertilizers are not accessible to plants and may result in environmental damage if used in excess. This issue can be resolved with nanomaterial-coated fertilizers (Rakhimol et al., 2021). As nanoparticles retain the fertilizer more tightly from the plant due to their higher surface tension than ordinary surfaces, nanomaterials may help slow down the release of fertilizers. Additionally, nanocoatings shield bigger particles’ surfaces. In order to limit nutrient losses and undesired nutrient interactions with microbes, water, and air, nanofertilizers balance the release of fertilizer nitrogen and phosphorus with the uptake of the plant (Singh et al., 2021). Utilizing nanofertilizer will increase the plants’ ability to absorb nutrients from the soil. After nutrient absorption by fungi or bacteria, nanosilica-encapsulated nanofertilizer can form a binary layer on the cell wall, preventing infections and enhancing plant growth under high temperature and humidity as well as disease resistance. Due to silicon dioxide nanoparticles’ ability to enhance seedling growth and root development, silicon-based fertilizers are used to promote plant resilience.
6 Conclusions and Future Perspectives We looked at current approaches for applying nitrogen fertilizer to cut down on nitrous oxide emissions. Nitrous oxide emissions can be reduced by using nitrification inhibitors, urease inhibitors, site-specific applications, slow-release/controlled- release fertilizer, biofertilizer, and nanotechnology in fertilizer delivery. However, it is important to consider the potential trade-off with higher direct emissions. Although anaerobic digestion has proven successful in lowering NH3 and N2O emissions, more study is required to determine the effects of off-farm inputs.
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Injection is preferred on well-drained soil, whereas surface spreading followed by quick assimilation is preferred on damp soil. Appropriate manure application methods can reduce direct and indirect N2O emissions. The timing of manure application prevents excessive N2O fluxes and decreases NO3 leaching. In general, N2O emissions can be reduced by applying only as much manure as is necessary to meet the N requirements of the crop. Application rate is also crucial. In tests, nitrification inhibitors can lower direct and indirect N2O emissions; however, it is not apparent if this mitigation is economically viable at the farm size. Therefore, additional investigation is required.
References Aliyu, G., Luo, J., Di, H. J., Liu, D., Yuan, J., Chen, Z., He, T., & Ding, W. (2021). Yield- scaled nitrous oxide emissions from nitrogen-fertilized croplands in China: A meta-analysis of contrasting mitigation scenarios. Pedosphere, 31(2), 231–242. https://doi.org/10.1016/ S1002-0160(20)60074-1 Ashekuzzaman, S. M., Forrestal, P., Richards, K. G., Daly, K., & Fenton, O. (2021). Grassland phosphorus and nitrogen fertiliser replacement value of dairy processing dewatered sludge. Sustainable Production and Consumption, 25, 363–373. https://doi.org/10.1016/j. spc.2020.11.017 Bai, Y., & Gao, J. (2021). Optimization of the nitrogen fertilizer schedule of maize under drip irrigation in Jilin, China, based on DSSAT and GA. Agricultural Water Management, 244, 106555. https://doi.org/10.1016/j.agwat.2020.106555 Bandh, S. A. (2022a). Climate change: The social and scientific construct (1st ed.). Springer. https://doi.org/10.1007/978-3-030-86290-9 Bandh, S. A. (2022b). Sustainable agriculture: Technological progressions and transitions (1st ed.). Springer. https://doi.org/10.1007/978-3-030-83066-3 Bandh, S. A., Shafi, S., Peerzada, M., Rehman, T., Bashir, S., Wani, S. A., & Dar, R. (2021). Multidimensional analysis of global climate change: A review. Environmental Science and Pollution Research International, 28(20), 24872–24888. https://doi.org/10.1007/ s11356-021-13139-7 Cao, Y., Wang, R., Peng, J., Liu, K., Chen, W., Wang, G., & Gao, X. (2021). Humidity enhanced N2O photoacoustic sensor with a 4.53 μm quantum cascade laser and Kalman filter. Photoacoustics, 24, 100303. https://doi.org/10.1016/j.pacs.2021.100303 de Vries, W. (2021). Impacts of nitrogen emissions on ecosystems and human health: A mini review. Current Opinion in Environmental Science and Health, 21. https://doi.org/10.1016/j. coesh.2021.100249 Dong, D., Li, J., Ying, S., Wu, J., Han, X., Teng, Y., Zhou, M., Ren, Y., & Jiang, P. (2021). Mitigation of methane emission in a rice paddy field amended with biochar-based slow-release fertilizer. Science of the Total Environment, 792, 148460. https://doi.org/10.1016/j.scitotenv.2021.148460 Garcia, J. S., Anderson, K. E., Guard, J. Y., Gast, R. K., & Jones, D. R. (2021). Impact of organic dairy cattle manure on environmental and egg microbiology of organic free-range laying hens. Journal of Applied Poultry Research, 30(4). https://doi.org/10.1016/j.japr.2021.100189 Ge, P., Chen, M., Cui, Y., & Nie, D. (2021). The research progress of the influence of agricultural activities on atmospheric environment in recent ten years: A review. Atmosphere, 12(5). https:// doi.org/10.3390/atmos12050635 Han, Z., Wang, J., Xu, P., Li, Z., Liu, S., & Zou, J. (2021). Differential responses of soil nitrogen- oxide emissions to organic substitution for synthetic fertilizer and biochar amendment in a subtropical tea plantation. GCB Bioenergy, 13(8), 1260–1274. https://doi.org/10.1111/gcbb.12842
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Harris, E., Diaz-Pines, E., Stoll, E., Schloter, M., Schulz, S., Duffner, C., Li, K., Moore, K. L., Ingrisch, J., Reinthaler, D., Zechmeister-Boltenstern, S., Glatzel, S., Brüggemann, N., & Bahn, M. (2021). Denitrifying pathways dominate nitrous oxide emissions from managed grassland during drought and rewetting. Science Advances, 7(6). https://doi.org/10.1126/sciadv.abb7118 Kim, D.-G., Grieco, E., Bombelli, A., Hickman, J. E., & Sanz-Cobena, A. (2021). Challenges and opportunities for enhancing food security and greenhouse gas mitigation in smallholder farming in sub-Saharan Africa. A review. Food Security, 13(2), 457–476. https://doi.org/10.1007/ s12571-021-01149-9 Klimczyk, M., Siczek, A., & Schimmelpfennig, L. (2021). Improving the efficiency of urea-based fertilization leading to reduction in ammonia emission. Science of the Total Environment, 771, 145483. https://doi.org/10.1016/j.scitotenv.2021.145483 Lan, T., Zhang, H., Han, Y., Deng, O., Tang, X., Luo, L., Zeng, J., Chen, G., Wang, C., & Gao, X. (2021). Regulating CH4, N2O, and NO emissions from an alkaline paddy field under rice–wheat rotation with controlled release N fertilizer. Environmental Science and Pollution Research International, 28(14), 18246–18259. https://doi.org/10.1007/s11356-020-11846-1 Liu, Y., Ge, T., van Groenigen, K. J., Yang, Y., Wang, P., Cheng, K., Zhu, Z., Wang, J., Li, Y., Guggenberger, G., Sardans, J., Penuelas, J., Wu, J., & Kuzyakov, Y. (2021). Rice paddy soils are a quantitatively important carbon store according to a global synthesis. Communications Earth and Environment, 2(1). https://doi.org/10.1038/s43247-021-00229-0 Maaz, T. M., Sapkota, T. B., Eagle, A. J., Kantar, M. B., Bruulsema, T. W., & Majumdar, K. (2021). Meta-analysis of yield and nitrous oxide outcomes for nitrogen management in agriculture. Global Change Biology, 27(11), 2343–2360. https://doi.org/10.1111/gcb.15588 Martínez-Dalmau, J., Berbel, J., & Ordóñez-Fernández, R. (2021). Nitrogen fertilization. A review of the risks associated with the inefficiency of its use and policy responses. Sustainability, 13(10). https://doi.org/10.3390/su13105625 Nyaga, J. M., Onyango, C. M., Wetterlind, J., & Söderström, M. (2021). Precision agriculture research in sub-Saharan Africa countries: A systematic map. Precision Agriculture, 22(4), 1217–1236. https://doi.org/10.1007/s11119-020-09780-w Oreggioni, G. D., Ferraio, M., Crippa, M., Muntean, M., Schaaf, E., Guizzardi, D., Solazzo, E., Duerr, M., Perry, M., & Vignati, E. (2021). Climate change in a changing world: Socio- economic and technological transitions, regulatory frameworks and trends on global greenhouse gas emissions from EDGAR v.5.0. Global Environmental Change, 70, 102350. https:// doi.org/10.1016/j.gloenvcha.2021.102350 Rakhimol, K. R., Thomas, S., & Nandakumar Kalarikkal, J. K. (2021). Nanotechnology in controlled-release fertilizers. In F. B. Lewu, T. Volova, & R. K. R. Sabu Thomas (Eds.), Controlled release fertilizers for sustainable agriculture (pp. 169–181). Academic. https://doi. org/10.1016/B978-0-12-819555-0.00010-8 Shakoor, A., Shahzad, S. M., Chatterjee, N., Arif, M. S., Farooq, T. H., Altaf, M. M., Tufail, M. A., Dar, A. A., & Mehmood, T. (2021). Nitrous oxide emission from agricultural soils: Application of animal manure or biochar? A global meta-analysis. Journal of Environmental Management, 285, 112170. https://doi.org/10.1016/j.jenvman.2021.112170 Singh, S. K., Patra, A., Verma, Y., Chattopadhyay, A., Rakshit, A., & Kumar, S. (2021). Potential and risk of nanotechnology application in agriculture vis-à-vis nanomicronutrient fertilizers. In A. Rakshit, S. Singh, P. Abhilash, & A. Biswas (Eds.), Soil science: Fundamentals to recent advances. Springer. https://doi.org/10.1007/978-981-16-0917-6_26 Sun, H., Zhang, Y., Yang, Y., Chen, Y., Jeyakumar, P., Shao, Q., Zhou, Y., Ma, M., Zhu, R., Qian, Q., Fan, Y., Xiang, S., Zhai, N., Li, Y., Zhao, Q., & Wang, H. (2021). Effect of biofertilizer and wheat straw biochar application on nitrous oxide emission and ammonia volatilization from paddy soil. Environmental Pollution, 275, 116640. https://doi.org/10.1016/j. envpol.2021.116640 Wang, X., Bai, J., Xie, T., Wang, W., Zhang, G., Yin, S., & Wang, D. (2021). Effects of biological nitrification inhibitors on nitrogen use efficiency and greenhouse gas emissions in
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a gricultural soils: A review. Ecotoxicology and Environmental Safety, 220, 112338. https://doi. org/10.1016/j.ecoenv.2021.112338 Wang, Y., Lu, Y., Yuan, J., & He, G. (2022). Evaluating the risks of nitrogen fertilizer-related grain production processes to ecosystem health in China. Resources, Conservation and Recycling, 177. https://doi.org/10.1016/j.resconrec.2021.105982 Wei, Z., Shan, J., Well, R., Yan, X., & Senbayram, M. (2022). Land use conversion and soil moisture affect the magnitude and pattern of soil-borne N2, NO, and N2O emissions. Geoderma, 407, 115568. https://doi.org/10.1016/j.geoderma.2021.115568
Chapter 2
Rice Production Technologies in Reducing Methane Gas Emissions for Sustainable Environment Hamna Bashir, Irshad Bibi, Nabeel Khan Niazi, Abdul Qadeer, Shumaila Zaman, Ayesha Farzand, Muhammad Mahroz Hussain, and Muhammad Ashir Hameed Abstract Agriculture is the primary contributor for greenhouse gas (GHG), with rice being a driver to global warming due to large number of GHGs emissions, having importance as a staple food for more than half of the world’s population. Global rice demand to fulfil hunger requirement will enhance GHG emissions due to its cultivation under paddy rice conditions that have detrimental effects on the environment results in more GHGs. Agriculture is the major contributor for CH4 emission under paddy soils, which have increased by methanogen activity resulting in CH4 production, a major end product in the anaerobic food chain (CH4-producing bacteria). Because anaerobic conditions enhance the performance of methanogens, which leads to the utilization of organic carbon and its conversion into CH4 through a process called methanogenesis, anaerobic conditions are the biochemical routes of CH4 generation. Therefore, it is in dire need of time to study the impacts of the paddy rice system and possible alternative ways to develop critical understanding to mitigate CH4. In this chapter, production technologies and importance of rice as a staple food were elucidated. Furthermore, the impacts of different production technologies to mitigate CH4 production was also discussed critically. However, future research directions and major research gaps have been identified. Keywords Rice · Alternate wetting and drying · Methanogens · Global warming · Production technologies
H. Bashir · I. Bibi · N. K. Niazi · A. Qadeer · S. Zaman · A. Farzand Institute of Soil and Environmental Sciences, University of Agriculture Faisalabad, Faisalabad, Pakistan M. M. Hussain (*) · M. A. Hameed Institute of Soil and Environmental Sciences, University of Agriculture Faisalabad, Faisalabad, Pakistan HAM Organics (PVT) Limited, Punjab, Pakistan © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 S. A. Bandh (ed.), Strategizing Agricultural Management for Climate Change Mitigation and Adaptation, https://doi.org/10.1007/978-3-031-32789-6_2
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1 Introduction The atmosphere is chemically changed over time due to the energy production by fossil fuels as they emit greenhouse gases (GHGs) via manufacturing, transportation, conversion, and combustion. Of all GHGs about 16% is methane, making it a significant greenhouse gas (Hussain et al., 2021a, c). Despite being steady for millennia, the amount of methane in the atmosphere has recently increased ~2-fold. In the absence of oxygen, decomposition of organic molecules causes methane formation with microbes that acts as a major climate change driver (Din et al., 2022). It is emancipated from natural and artificial sources, with natural resources causing 40% of the global methane emissions (Table 2.1), but 60% of these are caused by human activities (Linquist et al., 2012). Rice is probably one of the most important grains, as it is consumed by more than 50% of the population globally (Hussain et al., 2021b). Globally, paddy fields account for about 11% of the world’s farmland, or 153 million hectares (Wang et al., 2012). In the next 20 years, demand for rice is expected to grow by 24%, with more pressure from developing countries to fulfil hunger requirements, being a staple food (Van Nguyen & Ferrero, 2006). In addition, paddy fields play an important role in the production of CH4 and N2O and potential sources or sinks of carbon dioxide. Paddy fields provide roughly 30% of all agricultural CH4 emissions worldwide and 11% of all agricultural N2O emissions (Linquist et al., 2012). The CH4 emissions from paddy fields are mainly caused by microbial decomposition and the combustion of plant debris and humus (Smith et al., 2008). The organic decomposition in watered rice crops leads to methane formation, protonation, and transportation (Le Mer & Roger, 2001; Malla et al., 2022; Bandh et al., 2021, 2023). For sustainable and profitable rice systems, technologies and methods to offset greenhouse gas emissions need to be developed. In paddy fields, GHG production is primarily based on farming practices, but adjustments in management systems have mitigation potential. Often a practice may be exposed to more than one gas, sometimes through opposing processes, so the net benefit depends on the cumulative effect of implementation on all gases (Schils et al., 2005). Table 2.1 Major methane (CH4) emission contributors Agriculture (50.63%) Manure management Rice cultivation Enteric fermentation Other
Waste (20.61%) Landfilling of solid waste Use of solvent and others Waste combustion
Industry (0.10%) Silicone carbide production Mineral products
Energy (28.65%) Coal mining activities
Metal production
Wastewater
Iron and steel production Chemical production
Stationary and mobile combustion Biomass combustion
Natural gas and oil systems
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2 Greenhouse Gas Emission Mechanisms 2.1 CH4 Emissions and Production Methane is one of the end products of anaerobic food webs in paddy soils due to the action of methanogens. Methane is produced by anaerobic conditions which is a biochemical method, as fermentative conditions invigorate the output of methanogens that results in the harvesting and conversion of organic carbon into CH4 through the methanogenesis process (Flynn & Smith, 2010). Due to a range of biological activities, the redox potential of the rice soil was greatly reduced after being flooded for a long time (Fig. 2.1). During flooding, methanogenic substrates are mainly produced by degradation of soil organic compounds. Labile carbon, which is not taken up by plants, is normally liberated to the soil, where it is rarely transformed by methanogens into CH4 (Epule et al., 2011). Three primary processes allow CH4 to be released after methanogenesis. The dissolved CH4 gas diffusion, boiling loss (discharge of air bubbles mediated via agricultural reforms or soil fauna), and plant transport to roots via the process of diffusion and transformation of aerial tissue and gaseous CH4 in the cortex that consequently liberates CH4 in the atmosphere thru plant micropores are some of these pathways. Previous studies have reported that more than 90% of the CH4 in temperate paddy fields is emitted from rice plants (Guo & Zhou, 2007). Nevertheless, growing tropical rice can also lead to substantial methane emissions, especially in
Fig. 2.1 Factors affecting methane emissions from rice field
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early seasons when there are high organic amendment applications (van der Gon, 2000).
3 Agriculture Annual agricultural methane emissions are estimated at over 3135.7 Mt CO2 eq. This makes the agricultural sector a large contributor of methane emissions, caused from human non-point sources. Or we can say that 50.63% of all methane emissions that are caused by human activities mainly comes from agricultural practices. Enteric fermentation is the source of 59.84% of all methane emissions, followed by rice farming, other agricultural pursuits, and waste management. The change in the percentage of emissions from farms is greater than the change in the percentage of emissions from other happenings. Since 2000, these emissions have drastically grown. Moreover, 15.47% of the emissions in this category are produced in China (Bandh, 2022a, b).
3.1 Source Agricultural methane emissions are caused through manure management, enteric fermentation, rice cultivation, and other agricultural practices. The fermentation of food by microorganisms in the digestive system of animals is termed enteric fermentation (Li et al., 2021). A by-product of this process is methane, which is produced by the animals’ respiration. Farm animals such as cattle, goats, buffalo, camels, and sheep are the main source of methane emissions in this sector. Methane is also produced by enteric fermentation in other domesticated nonruminants, such as pigs and horses; however, emissions vary greatly from animal to animal. Total methane emissions from these sources are inversely correlated with the number of animals, with feed type, quantity, and quality having the most effects. When manure is stored or processed in lagoons, ponds, or pits, the decomposition process leads to anaerobic conditions and methane emissions (Bundhoo et al., 2016). The amount of methane produced by manure depends on the storage method, the ambient temperature, and the composition of the manure. Higher methane emissions are also feasible in environments with higher room temperature and humidity. In addition, the feces composition is directly related to the species of the animals and their diet (Bundhoo et al., 2016). Therefore, the combination of these variables affects the actual methane emissions caused via manure management. Methane is produced by the breakdown of oxygen-poor organic molecules in flooded paddy fields. When paddy fields are flooded, the decomposition of organic matter consumes oxygen in the soil and water gradually. A variety of factors can affect the amount of methane produced by paddy fields, including the amount of organic matter present, labile C pool, soil microbiota, and water management (Vaghefi et al.,
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2016). Open combustion of biomass, savannah burning, agricultural waste burning, and open sweltering after deforestation are examples of sources of agricultural methane emissions. Cropping options to reduce GHG emissions while adjusting irrigation patterns and farming practices, managing organic additives and fertilizers, selecting appropriate varieties, and applying cropping systems can all help in reducing greenhouse gas emissions from paddy fields. In the following sections, the detail of all of these, as well as options and possibilities in different agroclimatic scenarios, will be discussed.
4 Management of CH4 via Irrigation Regime Changes One of the most important factors affecting greenhouse gas emissions is the management of water resources during rice cultivation. Several water management practices compared to conventional flooded rice, various midseason drainage intervals, alternate soil wetting and drying, erratic irrigation, and meticulous irrigation have been shown to cause reduction in GHG emissions. These techniques can be used in a variety of soil and climate conditions without affecting crop yield. Summer Drainage Midseason drainage is a separate period of irrigation in the agricultural growing season that is halted. To avoid tillering and reduce unproductive tiller numbers, a short drainage period of 5–20 days is usually performed before the maximum tillering phase; the duration is determined by locally accepted traditional practice. Methane emissions could increase when soil aeration begins due to the release of CH4 trapped in the soil, followed by a sustained decrease in emissions even if the field is flooded again. The efficacy of midseason drainage to reduce CH4 varied significantly (15–59%) due to the additional water available to re-flood the rice soil. Seasonal drainage improves the soil oxidation state and uptake of nitrogen (Shiratori et al., 2007). It is achieved due to the decrease in the level of water sprayed, as the total water level reduction translates into a reduction in CH4 emissions. Because oxygenation of the soil creates aerobic conditions that are not conducive to methanogen activity, Wassmann et al. (2000b) found that seasonal drainage lowered CH4 discharge by 43%. Timed and controlled midseason drainage seems to be the main approach to achieve a net reduction in GHG emissions (Wassmann et al., 2000a). Numerous studies have shown that it works for paddy fields based on total greenhouse gas emissions. Methane (CH4) and N2O emissions advocates midseason drainage as the most effective method for reducing greenhouse gas emissions, as it produces a 27% lower global warming potential (GWP) than typical flooding. According to Zou et al., the GWPs (CH4 and N2O) of midseason drainage are 42% and 72% lower, respectively, than typical floods. Because the length and timing of the drainage season have such a large impact on greenhouse gas emissions, this management approach can be upgraded to further reduce emissions.
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Alternate Wetting and Drying Irrigations Desiccating and re-flooding a rice field repeatedly is the technique of “alternating wetness.” The time between dried and moist conditions does not seem to be long enough to allow the soil to change from aerobic to anaerobic conditions, in contrast to midseason drainage (Wassmann & Aulakh, 2000). Although alternating soaking and drying minimized CH4 emissions, the N2O emissions from this system varied widely. Methane can be oxidized and prevented by drainage and the resulting aerobic conditions of soil. According to Katayanagi et al. (2016), alternating paddy and drying conditions can lessen CH4 emissions by 73% as compared to conventional flooded rice. Correct watering is carried out according to the physiological parameters of the different growth phases of the plants. However, it can minimize the frequency of alternating wet and dry environments, thereby reducing N2O and CH4 production and emissions. However, more research is needed to overcome the N2O offset in this strategy. Drainage Patterns Intermittent drainage is defined as alternating periods of unrestricted drainage and watering. It improves the oxidative conditions in the soil by improving root activity and soil-bearing capacity and lowering anaerobic water input. It increases the aerobic surface area of the soil while reducing CH4 production by improving oxygen transport. According to Yagi et al. (1996), sporadic drainage can reduce CH4 emissions up to 44% as compared to conventional flooding. According to Adhya et al. (2000), alternating drainage can reduce CH4 emissions by 15% compared to continuous flooding. In paddy fields, different water regimes lead to significant changes in N2O emissions (Zou et al., 2005). However, Ye et al. (2013) found that intermittent irrigation produced GWP (CH4 and N2O) 34% and 54% lower than flooding, respectively. Irrigation Control Controlling irrigation has also been shown to lower net greenhouse gas emissions from uprooted flooded rice (Hou et al., 2012). Similar to water management techniques employed in rice-intensive systems, after replanting rice seedlings throughout the rice production period in the absence of floods, the soil of flooded paddy fields stays dry (60–80%) (Liu et al., 2015). Comparing paddy fields irrigated with control irrigation with paddy fields irrigated with conventional flood irrigation, Yang et al. (2014) found a 79% decline in CH4 emissions, a 10% increase in N2O emissions, and a 67% reduction in GWP. According to Hou et al. (2016), this irrigation system produced 27% less GWP (CH4 and N2O) than conventional flooding. Additionally, contrary to irrigated rice, Yan et al. (2021) and some writers testified that constant wet, water-saving irrigation and deep irrigation (10-cm water depth) generate greenhouse gas emissions, particularly CH4. Cultivated Genotypes Changes in soil characteristics, like soil temperature, porosity, soil moisture, etc., and biochemical activities have a significant effect on greenhouse gas emissions
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from paddy fields due to tillage (Wu et al., 2013). By aerating the soil and physically rupturing soil aggregates to liberate protected organic carbon components, soil disturbance brought on by tillage can be intensified (Bilen et al., 2022). Tillage enhances soil carbon oxidation to carbon dioxide by enhancing soil aeration, increasing crop residue-soil contact, and bare aggregate preservation of soil orgainc matter (SOM) to microbial strike (Khaliq et al., 2013). Reducing tillage and soil degradation in rice-dependent farming processes can reduce greenhouse gas emissions. Guo and Zhou (2007) reported that no-till (NT) following the harvest of spring wheat produced lower CO2 fluxes than regular tillage (CT). That is why NT paddy fields generate a less amount of CH4 as compared to CT paddy fields due to a number of factors (Li et al., 2013). Compared to CT, Sakai et al. (2007) observed a 43% decrease in rice fields in Japan’s Northern Territory’s seasonal cumulative CH4 emissions. Ghimire et al. (2017) found that with rice-wheat cropping systems, lowering the tillage frequency dramatically reduced CH4 fluxes. The rise in soil bulk density, which results in a lower volume of macropores and a reduction in the decay of humus, is what causes the drop in CH4 emissions below LT. In a dry agricultural setting, Omonode et al. (2007) discovered that NT-caused soil top hardening prevented CH4 from entering the soil for oxidation, resulting in a reduction in CH4 absorption in the soil. Similarly, increasing soil compaction may extend CH4 transport pathways, limiting CH4 emissions into the atmosphere or through rice crops, or CH4 transfer to the rhizosphere (Bassett et al., 2005).
5 Management of Organic Additives In rice fields, organic additives have a significant impact on greenhouse gas emissions. In general, adding the organic materials such as straw or organic fertilizers leads to an increase in CH4 emissions, the extent of which varies depending on the quantity, quality, and programing of application (Naser et al., 2007). In addition, organic supplements produce freely available nitrogen pools in the soil, thereby increasing N2O emissions (Tao et al., 2015). In fact, there is selected conflicting data showing that high straw improvement reduces N2O emissions from paddy fields, which can be attributed to N immobilization (Kreye et al., 2007). Understanding this relationship presents complex challenges that need to be addressed depending on the ecological situation.
5.1 Straw/Residue Management Arable farming always generates large amounts of straw and other field waste. As organic fertilizer use decreases, rice paddies are increasingly relying on straw recycling to offset carbon losses from tillage and harvesting. Although straw burning
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accelerates farmers’ seedbed preparation and reduces the hazard of nitrogen fixation during the decomposition of residues with higher C/N ratios, incomplete C incineration releases significant amounts of greenhouse gases and reduces air standards (Hussain et al., 2015). In addition, nitrogen oxides and further burning of natural chemicals contribute to the formation of tropospheric ozone. Rice straw contains a variety of organic components, including cellulose, lipids, hemicellulose, lignin, proteins, etc., and each component’s contribution to increasing the CH4 emission rate varies. The CH4 discharge levels are most delicate for handling of straw in the soil. Bugna et al. (1996) observed that off-season CH4 discharge rates from fresh straw were higher than those from straw incorporated into rice fields. In a field study conducted in Zhejiang Province, China, Deininger et al. (2000) reported that timely straw bedding at the onset of winter fallow reduced GHG emissions by 11% in comparison to traditional spring straw bedding methods. Similarly, Wassmann et al. (2000b) demonstrated that remnant absorption under the uncultivated phase (60 days before rice sowing) had advantages over traditional pre-sowing treatment in terms of GHG emissions and crop production. In comparison to straw wrapping, removing straw reduced emissions of all three gases, suggesting that eliminating the use of straw in paddy fields could also be a beneficial approach. Koga and Tajima (2011) discovered that straw removal treatment had lower CH4 and CO2 emissions than straw recirculation treatment. In the addition of straw according to Bhattacharyya et al. (2013) CH4 emissions increased by 108% and N2O emissions decreased up to 21% as related to manure plots. It also promotes soil carbon sequestration, but its effect on CH4 growth is such that the GHG benefits of reducing N2O emissions or increasing soil carbon sequestration are hardly outweighed. Because the decomposition of straw promotes the growth of methanogens, most of the CH4 is produced in flooded environments as straw decomposes. In rice fields, Zschornack et al. (2011) found that surface reservation of straw can reduce CH4 and N2O emissions by 69% and 81%, respectively, in contrast to straw integration. In rice-wheat cropping systems, the integration of wheat straw resulted in more emissions than rice straw. From an economic and environmental point of view, wheat straw mulch, whether partial or complete, is still beneficial. Besides having a smaller effect on N2O emissions, mulching also significantly lowered CH4 emissions compared to capture (Ma et al., 2009).
5.2 Biochar Enrichment Biochar is a carbon-rich by-product that results from the anaerobic pyrolysis of waste biomass at high temperatures (Hussain et al., 2021a, 2022; Warnock et al., 2007). The highly permeable structure of biochar, the finely grained C content, and the enhanced surface make it a suitable soil additive for carbon sequestration (Güereña et al., 2013). Use of biochar from pyrolysis of crop straw can raise carbon sequestration up to 22% and lower GHG emissions up to 35% in relation to plots without biochar. N2O emission from rice fields is more effective at higher biochar
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concentrations (Shan et al., 2013). Liu et al. (2012) similarly documented large reductions in GHG emissions through the use of biochar.
5.3 Selection of Rice Varieties Choosing the right variety has been recognized as a viable way to reduce greenhouse gas emissions, i.e., CH4 in rice soil. Rice cultivars (and their relatives) form an extremely diverse crop (De Leon & Carpena, 1995), having greater than 90,000 attainments in the IRRI gene pool, each with unique morphophysiological traits and environmental adaptations, and there are more than 90,000 accessions in the gene pool (Price et al., 1999). In addition, the GWP of rice varieties varies greatly. Several researches carried out in controlled and natural settings (Hussain et al. 2015) demonstrated the diversity of rice cultivars and varieties in relation to the CH4 emission. Differences in CH4 emissions between varieties are related to differences in CH4 liberation, oxidation, and transport capacity (Jiang et al., 2013). The threshold for soil Eh is known to be 150 mV, which mainly controls the CH4 production rate in rice soils (Yu & Patrick, 2004). Han et al. (2022) showed that soil Eh is regulated by root respiration and exudation, aboveground biomass, and the growth state of the rice plant during the rice planting season. All of these factors are frequently listed as anticipated characteristics for the development of CH4 budgets in paddy fields (Ding et al., 2004). The ability of rice soils to generate and release CH4 is directly impacted by the dynamic fluctuations in soil Eh and the changes in these parameters. Rice plants have variable CH4 oxidation and differential O2 diffusion into the rhizosphere through the aerenchyma due to changes in cultivar gas conductance connected to the release of O2 in the rhizosphere (Huang et al., 2021). Concentration gradients, diffusivity, internal aerenchyma structure, canopy density, root biomass, root pattern, overall biomass, and metabolic activity all affect how quickly gases move through the tissue (Aulakh et al., 2002). In order to sustain aerobic metabolism, a well-developed respiratory tissue system makes sure that oxygen is available to the rhizosphere. This also limits the possibility of potentially hazardous chemicals to enter plant roots through oxidation (Armstrong et al., 1994). This promotes CH4 oxidation, which lowers atmospheric emissions of the gas (Neue et al., 1997). Additionally, driven by concentration and/or pressure gradients, it serves as a conduit for CH4 to reach the atmosphere from the rhizosphere. Zheng et al. (2014) reported that super-rice CH4 emissions were much lower than conventional rice and claimed that oxidation rather than production was the main reason for the reduction in CH4 emissions. With more robust root systems, rice varieties can deliver more oxygen to the soil, improve environmental resilience, and promote yields. Zheng et al. (2014) also observed that the root oxidation activity of super-rice before topping and at the topping stage was much higher than that of standard rice seed. The aerenchyma of rice plants, which supplies root exudates and/or dead root cells as substrates for methanogens and methanotrophs, also controls the transfer of
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CH4 and O2 (Kerdchoechuen, 2005). Different rice varieties produce different amounts and types of root exudates, which are a breakdown of recently expelled organic materials in rice roots (Aulakh et al., 2002). Crop transport is responsible for the majority of CH4 emissions and Jiang et al. (2013) supported this theory and suggested that rice variety selection has great potential for reducing CH4 emissions. Cultivation practices can mask seasonal variations in species-specific CH4 emissions (Barman & Mitra, 2019) and can be influenced by cultivation strategies. Komatsu et al. (2009) reported that rice cultivars reaped at 3 months release less CH4 than cultivars harvested at 4 months, indicating that a shorter growing season is a clear factor for choosing low-emitting cultivars. A promising solution to lower greenhouse gas emissions from rice soils appears to be choosing rice cultivars with low CH4 emissions and increased resource utilization order. Prior to cultivar evaluation, it is necessary to look at the mechanisms causing exudate and aerenchyma impacts in the field.
6 Changing Planting Practices 6.1 Rice No-Till Technology Direct rice (DSR), which can minimize greenhouse gas emissions and adapt to climate hazards, has been acknowledged as a promising alternative to traditional puddle transplant rice (TPR), which is a substantial source of greenhouse gas (GHG) emissions (Lip et al., 2014). Farooq et al. (2011) asserted that DSR is thought to be a water-retaining method that can dramatically lower greenhouse gas emissions, notably CH4 emissions, without lowering agricultural yields. They assert that the primary causes of the decrease in CH4 generation and emissions in DSR compared to TPR are less soil modification and shorter flooding durations. Wassmann et al. (2004) found that midseason drainage of DSR fields can reduce CH4 emissions by up to 50%. The reduction in CH4 fluxes, however, may be counterbalanced by an increase in N2O emissions from dry DSRs due to changes in water status (Zheng et al., 2014). Jiao et al. (2006) reported that N2O production at DSR increased as the redox potential approached 250 mV. To limit CH4 and N2O emissions, they recommend controlling the water supply to keep the soil’s redox potential in the midrange (100–200 mV). Since the critical soil redox potential for N2O formation has been determined to be 250 mV, this range is sufficient to inhibit CH4 synthesis and promote the reduction of N2O to N2 (Jiao et al., 2006). The DSR system reduces N2O emissions, but because of its lower GWP, it offers a more promising growth regime. Kumar et al. (2019) discovered that DSR had a 53% lower average GWP than TPR for the three greenhouse gases (CO2, CH4, and N2O). According to Ahmad et al. (2009) with the NT approach in paddy fields, the GWP of DSR may be further decreased. Wang et al. (2017) also reported that DSR cropping systems have the efficiency to significantly lower greenhouse
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gas emissions from paddy fields. Due to lower GWP and high productivity, DSR cultivation systems can result in reduced CH4 and N2O emissions per rice yield unit. However, more extensive research, including simultaneous measurement of greenhouse gases under the influence of water management, agriculture, fertilizers, and more, is needed to recommend more appropriate DSR production options while reducing environmental concerns.
7 Conclusions Rising rice consumption and future population increase have sparked worries about stabilizing greenhouse gas emissions in order to reduce predicted global climate change. Here, we give a thorough evaluation of rice crop management techniques effective in lowering greenhouse gas emissions in conjunction with recent data. We are unable to cover all gases in each segment due to data constraints, but we have looked into the viability and potential of several alternative practices based on the GWP of greenhouse gases, especially CH4 and N2O. We discovered that crop administration practices can lessen the expected global climate change caused by rice farming. For example, the reduction potentials of intermittent irrigation, midseason drainage, and regulated irrigation systems for CH4 and N2O were 27–64%, 34–54%, and 27–67%, respectively, compared to standard flood irrigation. The introduction of NT and conservation tillage practices as an alternative to conventional farming is effective for GHG reduction and C-smart farming because they reduce overall GHG emissions. Rice fields can potentially reduce greenhouse gas emissions if straw is managed through surface retention or mulching and biochar/compost is produced on behalf of being burned or incorporated. The use of fermented organic fertilizers is also a possible reduction strategy. Adjusting fertilization to the needs of plants, precise positioning, replacing urea with ammonium sulfate, adding potassium fertilizer, and using nitrification inhibitors are effective measures to reduce greenhouse gas emissions. In this context, the selection of varieties with lower CH4 emissions and improved resource use efficiency also represents an important opportunity. DSR also appears to be the most promising cultivation method and the most suitable option for TPR in terms of GWP. It is anticipated that using all of these suggested strategies to cut greenhouse gas emissions will either preserve rice yields or at the very minimal enhance aid usage ability in the absence of lowering productivity. But for these techniques to be effective, all social, economic, educational, and political barriers must be eliminated. In order to build site-specific mitigation measures, future research might concentrate on confirming the viability of these techniques in various geographic locations and under other circumstances. Combining geographic data, production and greenhouse gas emission models, and socioeconomic data might also be beneficial. Finding cultivars with fewer greenhouse gas emissions may be done using GIS data. Finding the GWP of various agricultural systems is crucial. The GWP should ideally be determined using a standardized procedure. There is a growing understanding that other aspects need to be taken into account
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when discussing global climate change and agriculture, such as cultural significance, supply of ecosystem assistance, food protection, and human health. We hope that our efforts will be of use in the future, as their practical consequences will inspire and guide future research. With regard to food security, any future proposals to prevent catastrophic climate change should take this into account. Acknowledgements Authors thank the Higher Education Commission, Pakistan, for awarding fellowship under International Research Support Initiative Program (IRSIP) Muhammad Mahroz Hussain No. 1-8/HEC/HRD/2020/10831 and to the Environmental Biogeochemistry Laboratory, University of Agriculture Faisalabad, Pakistan. Author also want to thank UKRI-GCRF South Asian Nitrogen Hub for providing the funding source.
References Adhya, T. K., Bharati, K., Mohanty, S. R., Ramakrishnan, B., Rao, V. R., Sethunathan, N., & Wassmann, R. (2000). Methane emission from rice fields at Cuttack, India. Nutrient Cycling in Agroecosystems, 58(1/3), 95–105. https://doi.org/10.1023/A:1009886317629 Ahmad, S., Li, C., Dai, G., Zhan, M., Wang, J., Pan, S., & Cao, C. (2009). Greenhouse gas emission from direct seeding paddy field under different rice tillage systems in central China. Soil and Tillage Research, 106(1), 54–61. https://doi.org/10.1016/j.still.2009.09.005 Armstrong, W., Brändle, R., & Jackson, M. B. (1994). Mechanisms of flood tolerance in plants. Acta Botanica Neerlandica, 43(4), 307–358. https://doi.org/10.1111/j.1438-8677.1994. tb00756.x Aulakh, M. S., Wassmann, R., & Rennenberg, H. (2002). Methane transport capacity of twenty- two rice cultivars from five major Asian rice-growing countries. Agriculture, Ecosystems and Environment, 91(1–3), 59–71. https://doi.org/10.1016/S0167-8809(01)00260-2 Bandh, S. A. (2022a). Climate change: The social and scientific construct (1st ed.). Springer. https://doi.org/10.1007/978-3-030-86290-9 Bandh, S. A. (2022b). Sustainable agriculture: Technological progressions and transitions (1st ed.). Springer. https://doi.org/10.1007/978-3-030-83066-3 Bandh, S. A., Shafi, S., Peerzada, M., Rehman, T., Bashir, S., Wani, S. A., & Dar, R. (2021). Multidimensional analysis of global climate change: A review. Environmental Science and Pollution Research International, 28(20), 24872–24888. https://doi.org/10.1007/ s11356-021-13139-7 Bandh, S. A., Malla, F. A., Qayoom, I., Mohi-ud-Din, H., Butt, A. K., Altaf, A., Wani, S. A., Betts, R., Truong, T. H., Pham, N. D. K., Cao, D. N., & Ahmed, S. F. (2023). Importance of blue carbon in mitigating climate change and plastic/microplastic pollution and promoting circular economy. Sustainability, 15(3), 2682. https://doi.org/10.3390/su15032682 Barman, M., & Mitra, A. (2019). Temporal relationship between emitted and endogenous floral scent volatiles in summer- and winter-blooming Jasminum species. Physiologia Plantarum, 166(4), 946–959. https://doi.org/10.1111/ppl.12849 Bassett, I. E., Simcock, R. C., & Mitchell, N. D. (2005). Consequences of soil compaction for seedling establishment: Implications for natural regeneration and restoration. Austral Ecology, 30(8), 827–833. https://doi.org/10.1111/j.1442-9993.2005.01525.x Bhattacharyya, P., Nayak, A. K., Mohanty, S., Tripathi, R., Shahid, M., Kumar, A., Raja, R., Panda, B. B., Roy, K. S., Neogi, S., Dash, P. K., Shukla, A. K., & Rao, K. S. (2013). Greenhouse gas emission in relation to labile soil C, N pools and functional microbial diversity as influenced by 39 years long-term fertilizer management in tropical rice. Soil and Tillage Research, 129, 93–105. https://doi.org/10.1016/j.still.2013.01.014
2 Rice Production Technologies in Reducing Methane Gas Emissions for Sustainable…
23
Bilen, S., Jacinthe, P.-A., Shrestha, R., Jagadamma, S., Nakajima, T., Kendall, J. R. A., Doohan, T., Lal, R., & Dick, W. (2022). Greenhouse gas fluxes in a no-tillage chronosequence in Central Ohio. Soil and Tillage Research, 218, 105313. https://doi.org/10.1016/j.still.2021.105313 Bugna, G. C., Chanton, J. P., Cable, J. E., Burnett, W. C., & Cable, P. H. (1996). The importance of groundwater discharge to the methane budgets of nearshore and continental shelf waters of the northeastern Gulf of Mexico. Geochimica et Cosmochimica Acta, 60(23), 4735–4746. https:// doi.org/10.1016/S0016-7037(96)00290-6 Bundhoo, Z. M. A., Mauthoor, S., & Mohee, R. (2016). Potential of biogas production from biomass and waste materials in the Small Island Developing State of Mauritius. Renewable and Sustainable Energy Reviews, 56, 1087–1100. https://doi.org/10.1016/j.rser.2015.12.026 De Leon, J., & Carpena, A. (1995). Pedigree-based genetic diversity analysis of improved rice (Oryza sativa L.) varieties in The Philippines. Philippine Journal of Crop Science (Philippines), 20, 1–12. Deininger, A., Tamm, M., Krause, R., & Sonnenberg, H. (2000). SE—Structures and environment: penetration resistance and water-holding capacity of differently conditioned straw for deep litter housing systems. Journal of Agricultural Engineering Research, 77(3), 335–342. https:// doi.org/10.1006/jaer.2000.0606 Din, M. S. U., Mubeen, M., Hussain, S., Ahmad, A., Hussain, N., Ali, M. A., & Nasim, W. (2022). World nations priorities on climate change and food security. In Building Climate Resilience in Agriculture (365–384). Springer, Cham. https://doi.org/10.1007/978-3-030-79408-8_22 Ding, W., Cai, Z., & Wang, D. (2004). Preliminary budget of methane emissions from natural wetlands in China. Atmospheric Environment, 38(5), 751–759. https://doi.org/10.1016/j. atmosenv.2003.10.016 Epule, E. T., Peng, C., & Mafany, N. M. (2011). Methane emissions from paddy rice fields: Strategies towards achieving a win-win sustainability scenario between rice production and methane emission reduction. Journal of Sustainable Development, 4(6), 188. https://doi. org/10.5539/jsd.v4n6p188 Farooq, M., Siddique, K. H. M., Rehman, H., Aziz, T., Lee, D.-J., & Wahid, A. (2011). Rice direct seeding: Experiences, challenges and opportunities. Soil and Tillage Research, 111(2), 87–98. https://doi.org/10.1016/j.still.2010.10.008 Flynn, H. C., & Smith, P. (2010). Greenhouse gas budgets of crop production: Current and likely future trends. International Fertilizer Industry Association. Ghimire, R., Lamichhane, S., Acharya, B. S., Bista, P., & Sainju, U. M. (2017). Tillage, crop residue, and nutrient management effects on soil organic carbon in rice-based cropping systems: A review. Journal of Integrative Agriculture, 16(1), 1–15. https://doi.org/10.1016/ S2095-3119(16)61337-0 Güereña, D., Lehmann, J., Hanley, K., Enders, A., Hyland, C., & Riha, S. (2013). Nitrogen dynamics following field application of biochar in a temperate North American maize-based production system. Plant and Soil, 365(1–2), 239–254. https://doi.org/10.1007/s11104-012-1383-4 Guo, J., & Zhou, C. (2007). Greenhouse gas emissions and mitigation measures in Chinese agroecosystems. Agricultural and Forest Meteorology, 142(2–4), 270–277. https://doi.org/10.1016/j. agrformet.2006.03.029 Han, L., Chen, L., Li, D., Ji, Y., Feng, Y., Feng, Y., & Yang, Z. (2022). Influence of polyethylene terephthalate microplastic and biochar co-existence on paddy soil bacterial community structure and greenhouse gas emission. Environmental Pollution, 292(B), 118386. https://doi. org/10.1016/j.envpol.2021.118386 Hou, H., Peng, S., Xu, J., Yang, S., & Mao, Z. (2012). Seasonal variations of CH4 and N2O emissions in response to water management of paddy fields located in Southeast China. Chemosphere, 89(7), 884–892. https://doi.org/10.1016/j.chemosphere.2012.04.066 Hou, H., Yang, S., Wang, F., Li, D., & Xu, J. (2016). Controlled irrigation mitigates the annual integrative global warming potential of methane and nitrous oxide from the rice–winter wheat rotation systems in Southeast China. Ecological Engineering, 86, 239–246. https://doi. org/10.1016/j.ecoleng.2015.11.022
24
H. Bashir et al.
Huang, C., Chen, X., Liu, L., Zhang, H., Yuan, B., & Li, Y. (2021). The influence of opening shape of obstacles on explosion characteristics of premixed methane–air with concentration gradients. Process Safety and Environmental Protection, 150, 305–313. https://doi. org/10.1016/j.psep.2021.04.028 Hussain, S., Peng, S., Fahad, S., Khaliq, A., Huang, J., Cui, K., & Nie, L. (2015). Rice management interventions to mitigate greenhouse gas emissions: A review. Environmental Science and Pollution Research International, 22(5), 3342–3360. https://doi.org/10.1007/ s11356-014-3760-4 Hussain, M., Farooqi, Z., Mohy-Ud-Din, W., Younas, F., Shahzad, M., Ghani, M., Ayub, M., & Qadeer, A. (2021a). Application of bioremediation as sustainable approach to remediate heavy metal and pesticide polluted environments. Plant and Environment, 1, 62–92. Hussain, M. M., Bibi, I., Niazi, N. K., Shahid, M., Iqbal, J., Shakoor, M. B., Ahmad, A., Shah, N. S., Bhattacharya, P., Mao, K., Bundschuh, J., Ok, Y. S., & Zhang, H. (2021b). Arsenic biogeochemical cycling in paddy soil-rice system: Interaction with various factors, amendments and mineral nutrients. Science of the Total Environment, 773, 145040. https://doi.org/10.1016/j. scitotenv.2021.145040 Hussain, M. M., Zur Farooqi, R. F., & Din, W. M. U. (2021c). Role of microorganisms as climate engineers: Mitigation and adaptations to climate change. In J. A. Parray, S. A. Bandh, & N. Shameem (Eds.), Climate change and microbes: Impacts and vulnerability. 1. Apple Academic Press. Hussain, M. M., Mohy-Ud-Din, W., Younas, F., Niazi, N. K., Bibi, I., Yang, X., Rasheed, F., & Biochar, F. Z. U. R. (2022). A game changer for sustainable agriculture. Journal of Sustainable Agriculture, 143–157. Springer. Jiang, Y., Wang, L.-l., Yan, X.-j., Tian, Y.-l., Deng, A.-x., & Zhang, W.-j. (2013). Super rice cropping will enhance rice yield and reduce CH4 emission: A case study in Nanjing, China. Rice Science, 20(6), 427–433. https://doi.org/10.1016/S1672-6308(13)60157-2 Jiao, Z., Hou, A., Shi, Y., Huang, G., Wang, Y., & Chen, X. (2006). Water management influencing methane and nitrous oxide emissions from rice field in relation to soil redox and microbial community. Communications in Soil Science and Plant Analysis, 37(13–14), 1889–1903. https://doi.org/10.1080/00103620600767124 Katayanagi, N., Fumoto, T., Hayano, M., Takata, Y., Kuwagata, T., Shirato, Y., Sawano, S., Kajiura, M., Sudo, S., Ishigooka, Y., & Yagi, K. (2016). Development of a method for estimating total CH4 emission from rice paddies in Japan using the DNDC-Rice model. Science of the Total Environment, 547, 429–440. https://doi.org/10.1016/j.scitotenv.2015.12.149 Kerdchoechuen, O. (2005). Methane emission in four rice varieties as related to sugars and organic acids of roots and root exudates and biomass yield. Agriculture, Ecosystems and Environment, 108(2), 155–163. https://doi.org/10.1016/j.agee.2005.01.004 Khaliq, A., Matloob, A., Ihsan, M. Z., Abbas, R. N., Aslam, Z., & Rasool, F. (2013). Supplementing herbicides with manual weeding improves weed control efficiency, growth and yield of direct seeded rice. International Journal of Agriculture and Biology, 15, 191–199. Koga, N., & Tajima, R. (2011). Assessing energy efficiencies and greenhouse gas emissions under bioethanol-oriented paddy rice production in northern Japan. Journal of Environmental Management, 92(3), 967–973. https://doi.org/10.1016/j.jenvman.2010.11.008 Komatsu, G., Arzhannikov, S. G., Gillespie, A. R., Burke, R. M., Miyamoto, H., & Baker, V. R. (2009). Quaternary paleolake formation and cataclysmic flooding along the upper Yenisei River. Geomorphology, 104(3–4), 143–164. https://doi.org/10.1016/j.geomorph.2008.08.009 Kreye, C., Dittert, K., Zheng, X., Zhang, X., Lin, S., Tao, H., & Sattelmacher, B. (2007). Fluxes of methane and nitrous oxide in water-saving rice production in North China. Nutrient Cycling in Agroecosystems, 77(3), 293–304. https://doi.org/10.1007/s10705-006-9068-0 Kumar, A., Nayak, A. K., Das, B. S., Panigrahi, N., Dasgupta, P., Mohanty, S., Kumar, U., Panneerselvam, P., & Pathak, H. (2019). Effects of water deficit stress on agronomic and physiological responses of rice and greenhouse gas emission from rice soil under elevated atmo-
2 Rice Production Technologies in Reducing Methane Gas Emissions for Sustainable…
25
spheric CO2. Science of the Total Environment, 650(2), 2032–2050. https://doi.org/10.1016/j. scitotenv.2018.09.332 Le Mer, J., & Roger, P. (2001). Production, oxidation, emission and consumption of methane by soils: A review. European Journal of Soil Biology, 37(1), 25–50. https://doi.org/10.1016/ S1164-5563(01)01067-6 Li, C., Zhang, Z., Guo, L., Cai, M., & Cao, C. (2013). Emissions of CH4 and CO2 from double rice cropping systems under varying tillage and seeding methods. Atmospheric Environment, 80, 438–444. https://doi.org/10.1016/j.atmosenv.2013.08.027 Li, Y., Meng, Z., Xu, Y., Shi, Q., Ma, Y., Aung, M., Cheng, Y., & Zhu, W. (2021). Interactions between anaerobic fungi and methanogens in the rumen and their biotechnological potential in biogas production from lignocellulosic materials. Microorganisms, 9(1), 190. https://doi. org/10.3390/microorganisms9010190 Linquist, B. A., Adviento-Borbe, M. A., Pittelkow, C. M., van Kessel, C., & van Groenigen, K. J. (2012). Fertilizer management practices and greenhouse gas emissions from rice systems: A quantitative review and analysis. Field Crops Research, 135, 10–21. https://doi. org/10.1016/j.fcr.2012.06.007 Lip, G. Y., Kongnakorn, T., Phatak, H., Kuznik, A., Lanitis, T., Liu, L. Z., Iloeje, U., Hernandez, L., & Dorian, P. (2014). Cost-effectiveness of apixaban versus other new oral anticoagulants for stroke prevention in atrial fibrillation. Clinical Therapeutics, 36(2), 192–210.e20. https:// doi.org/10.1016/j.clinthera.2013.12.011 Liu, X.-y., Qu, J.-j., Li, L.-q., Zhang, A.-f., Jufeng, Z., Zheng, J.-w., & Pan, G.-x. (2012). Can biochar amendment be an ecological engineering technology to depress N2O emission in rice paddies?—A cross site field experiment from South China. Ecological Engineering, 42, 168–173. https://doi.org/10.1016/j.ecoleng.2012.01.016 Liu, H., Hussain, S., Zheng, M., Peng, S., Huang, J., Cui, K., & Nie, L. (2015). Dry direct-seeded rice as an alternative to transplanted-flooded rice in Central China. Agronomy for Sustainable Development, 35(1), 285–294. https://doi.org/10.1007/s13593-014-0239-0 Ma, J., Ma, E., Xu, H., Yagi, K., & Cai, Z. (2009). Wheat straw management affects CH4 and N2O emissions from rice fields. Soil Biology and Biochemistry, 41(5), 1022–1028. https://doi. org/10.1016/j.soilbio.2009.01.024 Malla, F. A., Mushtaq, A., Bandh, S. A., Qayoom, I., Ho-ang, A. T., & Shahid-e-Murtaza. (2022). Understanding climate change: Scientific opinion and public perspective. In S. A. Bandh (Ed.), Climate change: The social and scientific construct. Springer Nature Publishing. https://link. springer.com/chapter/10.1007/978-3-030-86290-9_1 Naser, H. M., Nagata, O., Tamura, S., & Hatano, R. (2007). Methane emissions from five paddy fields with different amounts of rice straw application in Central Hokkaido, Japan. Soil Science and Plant Nutrition, 53(1), 95–101. https://doi.org/10.1111/j.1747-0765.2007.00105.x Neue, H. U., Wassmann, R., Kludze, H. K., Bujun, W., & Lantin, R. S. (1997). Factors and processes controlling methane emissions from rice fields. Nutrient Cycling in Agroecosystems, 49(1/3), 111–117. https://doi.org/10.1023/A:1009714526204 Omonode, R. A., Vyn, T. J., Smith, D. R., Hegymegi, P., & Gál, A. (2007). Soil carbon dioxide and methane fluxes from long-term tillage systems in continuous corn and corn–soybean rotations. Soil and Tillage Research, 95(1–2), 182–195. doi:https://doi.org/10.1016/j. still.2006.12.004, 182. Price, A., Steele, K., Townend, J., Gorham, J., Audebert, A., Jones, M., & Courtois, B. (1999). Mapping root and shoot traits in rice: Experience in UK, IRRI and WARDA. In Genetic improvement of rice for water-limited environments (pp. 257–273). International Rice Research Institute. Sakai, S., Imachi, H., Sekiguchi, Y., Ohashi, A., Harada, H., & Kamagata, Y. (2007). Isolation of key methanogens for global methane emission from rice paddy fields: A novel isolate affiliated with the clone cluster rice cluster I. Applied and Environmental Microbiology, 73(13), 4326–4331. https://doi.org/10.1128/AEM.03008-06
26
H. Bashir et al.
Schils, R. L. M., Verhagen, A., Aarts, H. F. M., & Šebek, L. B. J. (2005). A farm level approach to define successful mitigation strategies for GHG emissions from ruminant livestock systems. Nutrient Cycling in Agroecosystems, 71(2), 163–175. https://doi.org/10.1007/ s10705-004-2212-9 Shan, Q., Wang, Y., Chen, K., Liang, Z., Li, J., Zhang, Y., Zhang, K., Liu, J., Voytas, D. F., Zheng, X., Zhang, Y., & Gao, C. (2013). Rapid and efficient gene modification in rice and Brachypodium using TALENs. Molecular Plant, 6(4), 1365–1368. https://doi.org/10.1093/mp/sss162 Shiratori, Y., Watanabe, H., Furukawa, Y., Tsuruta, H., & Inubushi, K. (2007). Effectiveness of a subsurface drainage system in poorly drained paddy fields on reduction of methane emissions. Soil Science and Plant Nutrition, 53(4), 387–400. https://doi. org/10.1111/j.1747-0765.2007.00171.x Smith, P., Fang, C., Dawson, J. J. C., & Moncrieff, J. B. (2008). Impact of global warming on soil organic carbon. Advances in Agronomy, 97, 1–43. https://doi.org/10.1016/ S0065-2113(07)00001-6 Tao, R., Liang, Y., Wakelin, S. A., & Chu, G. (2015). Supplementing chemical fertilizer with an organic component increases soil biological function and quality. Applied Soil Ecology, 96, 42–51. https://doi.org/10.1016/j.apsoil.2015.07.009 Vaghefi, N., Shamsudin, M. N., Radam, A., & Rahim, K. A. (2016). Impact of climate change on food security in Malaysia: Economic and policy adjustments for rice industry. Journal of Integrative Environmental Sciences, 13(1), 19–35. https://doi.org/10.1080/1943815X.2015.1112292 van der Gon, H. D. (2000). Changes in CH4 emission from rice fields from 1960 to 1990s: 1. Impacts of modern rice technology. Global Biogeochemical Cycles, 14(1), 61–72. https://doi. org/10.1029/1999GB900096 Van Nguyen, N., & Ferrero, A. (2006). Meeting the challenges of global rice production. Paddy and Water Environment, 4(1), 1–9. https://doi.org/10.1007/s10333-005-0031-5. Springer. Wang, J., Zhang, X., Xiong, Z., Khalil, M. A. K., Zhao, X., Xie, Y., & Xing, G. (2012). Methane emissions from a rice agroecosystem in South China: Effects of water regime, straw incorporation and nitrogen fertilizer. Nutrient Cycling in Agroecosystems, 93(1), 103–112. https://doi. org/10.1007/s10705-012-9503-3 Wang, W., Peng, S., Liu, H., Tao, Y., Huang, J., Cui, K., & Nie, L. (2017). The possibility of replacing puddled transplanted flooded rice with dry seeded rice in Central China: A review. Field Crops Research, 214, 310–320. https://doi.org/10.1016/j.fcr.2017.09.028 Warnock, D. D., Lehmann, J., Kuyper, T. W., & Rillig, M. C. (2007). Mycorrhizal responses to biochar in soil–concepts and mechanisms. Plant and Soil, 300(1–2), 9–20. https://doi.org/10.1007/ s11104-007-9391-5 Wassmann, R., & Aulakh, M. S. (2000). The role of rice plants in regulating mechanisms of methane missions. Biology and Fertility of Soils, 31(1), 20–29. https://doi.org/10.1007/s003740050619 Wassmann, R., Buendia, L. V., Lantin, R. S., Bueno, C. S., Lubigan, L. A., Umali, A., Nocon, N. N., Javellana, A. M., & Neue, H. U. (2000a). Mechanisms of crop management impact on methane emissions from rice fields in los Baños, Philippines. Nutrient Cycling in Agroecosystems, 58(1/3), 107–119. https://doi.org/10.1023/A:1009838401699 Wassmann, R., Lantin, R. S., Neue, H. U., Buendia, L. V., Corton, T. M., & Lu, Y. (2000b). Characterization of methane emissions from rice fields in Asia. III. Mitigation options and future research needs. Nutrient Cycling in Agroecosystems, 58(1/3), 23–36. https://doi.org/1 0.1023/A:1009874014903 Wassmann, R., Hien, N. X., Hoanh, C. T., & Tuong, T. P. (2004). Sea level rise affecting the Vietnamese Mekong Delta: Water elevation in the flood season and implications for rice production. Climatic Change, 66(1/2), 89–107. https://doi.org/10.1023/ B:CLIM.0000043144.69736.b7 Wu, G., Li, L., Ahmad, S., Chen, X., & Pan, X. (2013). A dynamic model for vulnerability assessment of regional water resources in arid areas: A case study of Bayingolin, China. Water Resources Management, 27(8), 3085–3101. https://doi.org/10.1007/s11269-013-0334-z
2 Rice Production Technologies in Reducing Methane Gas Emissions for Sustainable…
27
Yagi, K., Tsuruta, H., Kanda, K., & Minami, K. (1996). Effect of water management on methane emission from a Japanese rice paddy field: Automated methane monitoring. Global Biogeochemical Cycles, 10(2), 255–267. https://doi.org/10.1029/96GB00517 Yan, Q., Xu, Y., Chen, L., Cao, Z., Shao, Y., Xu, Y., Yu, Y., Fang, C., Zhu, Z., Feng, G., & Chen, M. (2021). Irrigation with secondary municipal-treated wastewater: Potential effects, accumulation of typical antibiotics and grain quality responses in rice (Oryza sativa L.). Journal of Hazardous Materials, 410, 124655. https://doi.org/10.1016/j.jhazmat.2020.124655 Yang, G., Chen, H., Wu, N., Tian, J., Peng, C., Zhu, Q., Zhu, D., He, Y., Zheng, Q., & Zhang, C. (2014). Effects of soil warming, rainfall reduction and water table level on CH4 emissions from the Zoige peatland in China. Soil Biology and Biochemistry, 78, 83–89. https://doi. org/10.1016/j.soilbio.2014.07.013 Ye, Y., Liang, X., Chen, Y., Liu, J., Gu, J., Guo, R., & Li, L. (2013). Alternate wetting and drying irrigation and controlled-release nitrogen fertilizer in late-season rice. Effects on dry matter accumulation, yield, water and nitrogen use. Field Crops Research, 144, 212–224. https://doi. org/10.1016/j.fcr.2012.12.003 Yu, K., & Patrick, W. H. (2004). Redox window with minimum global warming potential contribution from rice soils. Soil Science Society of America Journal, 68(6), 2086–2091. https://doi. org/10.2136/sssaj2004.2086 Zheng, H., Huang, H., Yao, L., Liu, J., He, H., & Tang, J. (2014). Impacts of rice varieties and management on yield-scaled greenhouse gas emissions from rice fields in China: A meta-analysis. Biogeosciences, 11(13), 3685–3693. https://doi.org/10.5194/bg-11-3685-2014 Zou, J., Huang, Y., Jiang, J., Zheng, X., & Sass, R. L. (2005). A 3-year field measurement of methane and nitrous oxide emissions from rice paddies in China: Effects of water regime, crop residue, and fertilizer application. Global Biogeochemical Cycles, 19(2), n/a–n/a. https://doi. org/10.1029/2004GB002401 Zschornack, T., Bayer, C., Zanatta, J. A., Vieira, F. C. B., & Anghinoni, I. (2011). Mitigation of methane and nitrous oxide emissions from flood-irrigated rice by no incorporation of winter crop residues into the soil. Revista Brasileira de Ciência do Solo, 35(2), 623–634. https://doi. org/10.1590/S0100-06832011000200031
Chapter 3
Manure Management to Reduce Methane Emissions Abdullah Kaviani Rad, Hassan Etesami, Angelika Astaikina, and Rostislav Streletskii
Abstract As a result of human activities, the production of greenhouse gases into the atmosphere has increased in the past few hundred years, which has contributed to the phenomenon of climate change. As the emissions of methane, a significant greenhouse gas, have risen tremendously in recent years, especially from the agricultural sector, numerous studies have been undertaken to find efficient methods for reducing these emissions. A major focus of this chapter is on reducing the amount of methane emitted from livestock production, particularly animal waste, and offers biological alternatives that include the use of biofertilizers and biochar, the microbial conversion of methane, genetic modification, and biogas production. It is also suggested that precision agriculture (PA) policies and digital innovations, such as the Internet of Things (IoT), unmanned aerial vehicle (UAV), and robotic systems, be implemented to carefully monitor the application of manure to farms. Furthermore, government economic plans, such as offering financial assistance to farmers to minimize greenhouse gas emissions, which can be beneficial in lowering methane emissions. Although several strategies have been recommended to decrease greenhouse gas emissions, there has been no discernible shift in atmospheric methane concentrations; this would suggest that regulations such as PA on farms are not being carried out effectively. Climate change and global warming will worsen over the next few decades if no urgent action is taken to reduce greenhouse gas emissions.
A. K. Rad (*) Department of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz, Iran H. Etesami Department of Soil Science, University of Tehran, Tehran, Iran A. Astaikina Eurasian Center for Food Security, Lomonosov Moscow State University, Moscow, Russia R. Streletskii Soil Science Faculty, Lomonosov Moscow State University, Moscow, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 S. A. Bandh (ed.), Strategizing Agricultural Management for Climate Change Mitigation and Adaptation, https://doi.org/10.1007/978-3-031-32789-6_3
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Keywords Agriculture · Climate change · Global warming · Precision farming · Livestock · Biofertilizer · Organic fertilizers · Biogas
1 Introduction In the past five thousand years, methane (CH4) emissions have risen because of the growing population, rice cultivation in Asia, the subsequent need for more farmland, and the increased use of wood for cooking and heating (Li et al., 2009). Considering that CH4 is a greenhouse gas (GHG) emitted by both natural and anthropogenic systems, the analysis of its emissions in various spatial and temporal dimensions is of paramount importance (VanderZaag et al., 2014; Yusuf et al., 2012). The CO2 concentration in the atmosphere has increased by 33% since 1750, while the CH4 concentration has increased by 75%. The global warming potential (GWP) of CH4 is 25 times that of CO2, and it contributes to approximately 20% of the greenhouse effect (Dalal et al., 2008). Methane levels in the atmosphere began to rise in 2007 following a period of nearly zero growth for seven years, and from 2014 to 2018, the global level of CH4 was approximately two times that in 2007 (Fletcher & Schaefer, 2019). Figure 3.1a illustrates the trend of growing methane emissions from 1990 to 2019. In recent years, methane has been subject to extensive research because of its disastrous effects on global warming and the chemistry of the atmosphere (Yusuf et al., 2012). Agriculture, the energy sector, and the waste management industry are the three most significant contributors to human resources of GHGs (Fig. 3.1b). CH4 emissions are highest in the agricultural industry, energy, and finally the waste management sector. Dalal et al. (2008) pinpointed intestinal fermentation in ruminant animals (59%), fossil fuel power generation (24%), and
Biomass (3%) Agriculture (manure) ( 4%)
Stationary and mobile sources (1%) Enteric fermentation (29%)
Coal mining (6%) Global Methane Emissions Other Ag sources (7%)
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1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
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Oil and Gas (20%) Landfaills (11%)
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Fig. 3.1 Global statistics regarding methane emissions during 1990–2019 (a) and its sources (b). (Adapted from IGSD (2016) and World Bank (2020))
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landfills and domestic sewage (15%) as the major sources of CH4 in Australia. The emissions of gases that contribute to global warming in the European Union are largely attributable to agriculture (De Cara et al., 2005). At the same time, agricultural production is impacted by GHGs. Methane and nitrogen oxide (N2O) emissions were shown to be negatively associated with agricultural GDP in China (Rehman et al., 2020). As a major subsector of the agricultural industry, the livestock sector is a primary source of the GHGs ammonia, CH4, and N2O (Hou et al., 2015). Ruminants release CH4 through enteric fermentation (Ramin & Huhtanen, 2013). Anaerobic fermentation is used by the microbial communities in ruminants to decompose food. Approximately 30% of all CH4 released into the atmosphere derives from livestock such as cattle, sheep, and goats (Black et al., 2021). Animal manure is among the key agricultural inputs that have been used to boost soil fertility by supplying N, P, K, S, Ca, Mg, and Na, as well as other microelements including Fe, Mn, Cu, and Zn. It also enhances organic matter in the soil and exchangeable cations, as well as soil aggregate durability, soil physical properties, soil infiltration, moisture retention, and resistance to cracking (Bayu et al., 2005). In spite of the fact that animal manure contributes to soil fertility, it is estimated that cattle dung adds approximately 240 million metric tons of methane to the atmosphere annually (Tauseef et al., 2013). Approximately 14.5% of anthropogenic greenhouse gas emissions worldwide are attributed to livestock production, which represents 7.1 gigatons of CO2-equivalent annually. Manufacturing and processing animal feed, as well as enteric fermentation of ruminants, are the two leading causes of environmental pollution, each contributing 45% and 39%, respectively, to total emissions (FAO, 2022). It has been estimated that approximately 40% of total human GHG emissions results from ruminant enteric fermentation and animal dung, and this percentage is likely to increase dramatically in the coming decades (Key & Tallard, 2012; Lassey, 2008). As a result, it is critical to take steps to reduce the gases emitted by livestock (Black et al., 2021). The reduction of livestock’s contribution to global CH4 emissions has been addressed through a variety of biological and political approaches. For instance, from an economic viewpoint, Hynes et al. (2009) reported that it would be feasible to reduce GHG emissions if subsidies were presented to growers based on the CH4 reduction program in Ireland. It is well demonstrated that the application of biodigesters in crop fields is an effective method for lowering GHG emissions and generating green energy (Flesch et al., 2011). In a study conducted by Jeffery et al. (2016), the application of biochar in paddy and acidic soils was suggested as a technique to lower CH4 emissions. Methanotrophic bacteria bioconversion of CH4 into microbial compounds has been proven to be a cost-effective and ecologically acceptable method (Cantera et al., 2018). Pickering et al. (2015) examined the possibility of genetically modifying ruminants in order to reduce CH4. This gas is an abundant and inexpensive carbon feedstock that has the potential to be bioconverted into beneficial industrial products through the use of methanotrophs (Hwang et al., 2018). Ruminant CH4 production is influenced by factors such as consumption level, food type, and feed quality; therefore, modifying ruminant diets can be influential (Broucek, 2014; Haque, 2018).
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Despite the benefits of the aforementioned options, climate regulations, notably those geared toward reducing CH4 emissions, do not appear to have significantly changed the upward trend of global GHG emissions (Jackson et al., 2020). Methane emissions from the livestock and fossil fuel sectors in the United States have been reported by Miller et al. (2013) to be higher than those reported by the Environmental Protection Agency (EPA) and the Emissions Database for Global Atmospheric Research (EDGAR). According to the results calculated by Höglund-Isaksson et al. (2020), approximately 7.7 Pg of CH4 is expected to be released into the atmosphere between 2020 and 2050, and it is difficult to eliminate this gas using current technological solutions. Consequently, strategies to combat CH4 and the resulting global warming are urgently needed in order to maintain agricultural sustainability and food security (Reay et al., 2018). It has been determined that a prompt decrease in CH4 significantly increases the probability of keeping global warming under 1.5 °C, as determined by Collins et al. (2018). The objective of this chapter is to present an overview of some practical methods to alleviate CH4 emissions from agronomic systems within the framework of different mechanical and biological approaches.
2 Biological Approach 2.1 Alternative Fertilizers to Animal Manure There are a number of steps that can be taken in order to reduce the amount of methane gas released into the atmosphere, such as the substitution of animal manure for bio-fertilizers and other forms of organic fertilizers that have been processed or combining animal manure with organic fertilizer. Additionally, it has been demonstrated that mineral fertilizers, which are commonly used by farmers on agricultural land such as paddies, may also affect the concentration of CH4 in agricultural soils (Malyan et al., 2016). In rice paddies, nitrogen fertilizers applied in the form of urea may significantly increase CH4 due to a reduction in redox potential and a change in soil pH, which stimulate methanogenesis (Wang et al., 1993). According to Malyan et al. (2016), the opposite effect was observed after fertilization with ammonium sulfate, ammonium thiosulfate, and single superphosphate (SSP). The reduction of CH4 emissions associated with the use of mineral fertilizers has been found to be associated with a reduction in CH4 emissions as a result of the inhibition of methanogens, which would affect the soil community structure (Bodelier 2011). Therefore, using biofertilizers instead of animal fertilizers can reduce the negative effects of using these fertilizers. In addition to being highly potent, biofertilizers have the advantage of being environmentally friendly as compared to conventional inorganic fertilizers (Rad et al., 2022a). The use of other organic fertilizers (soil organic amendments), such as compost, vermicompost, and biochar (a carbon-rich material produced during the pyrolysis process), can also reduce the negative effects of animal manure (e.g., a reduction in CH4 emissions). For instance, Agnihotri et al.
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(1999) demonstrated that the composting of cow dung and leaves decreased CH4 fluxes on rice fields. In addition to reducing CH4, the application of biochar as a fertilizer in rice paddies has been shown to significantly reduce GHG emissions (Pandey et al., 2014; Zhang et al., 2010). Upon adding biochar to soil, the following changes were observed: (1) the number of methanotrophic proteobacteria increased, and (2) the ratio of methanogens to methanotrophs decreased. Molecular analysis, on the other hand, demonstrated that the inhibition of methanogenic archaeal growth was not associated with a decrease in CH4 concentration when biochar was present. A comparison of the positive effects of biofertilizer and organic fertilizers is presented in Fig. 3.2. Biofertilizers, such as diazotrophs (Azotobacter, Ochrobactrum anthropi, and Azospirillum), plant growth-promoting rhizobacteria (PGPR), purple non-sulfur bacteria (PNSB), cyanobacteria, and a water fern named Azolla, are widely used in rice cultivation in Southeast Asia. A study conducted by Pingak et al. (2014) recognized that inorganic fertilizer was combined with methanotrophic bacteria, diazotrophic bacteria, Ochrobactrum anthropi, Azotobacter, and Azospirillum to reduce GHG emissions as well as increase rice yield and growth. By stimulating root growth and hair growth, these bacterial isolates enhanced O2 diffusion in flooded soils (Bhardwaj et al., 2014). A higher rate of plant growth was obtained by purple non-sulfur bacteria (PNSB) under anoxic salt stress conditions than by methanogens (Kantha et al., 2015). In this context, Kantha et al. (2015) demonstrated that PNSB Rhodopseudomonas palustris strains TN114, PP803, and TK103 were effective biofertilizers in paddy fields by increasing rice yield and reducing CH4 emissions. Two types of rice fields were studied: organic paddy fields and saline paddy fields. According to the findings of this study, purple non-sulfur bacteria were found
CH4 Flux
Inorganic fertilizers
Organic fertilizer Biofertilizer Biochar
Microbial communities degradation
Improving microbial communities
Fig. 3.2 CH4 emissions and soil microbial communities are affected by biofertilizers and organic fertilizers
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to increase grain yields over controls, and only strain TN114 was found to increase rice yields in organic paddy fields. An earlier study showed that Rhodopseudomonas palustris strains, particularly strain PP803, prevented salt from adversely impacting rice seedlings and inhibited CO2 and CH4 emissions. Azolla (aquatic pteridophyte) and the cyanobacteria Anabaena azollae (Nostocaceae family) are important for reducing atmospheric carbon and fixing nitrogen in paddy soil ecosystems (Ali et al., 2014). Moreover, a study by Prasanna et al. (2002) indicated that active oxidation of CH4 by cyanobacteria and/or Azolla microphylla resulted in a reduction in the emission of this GHG from rice paddies. As part of this laboratory study, seven strains of cyanobacteria were evaluated for their ability to reduce CH4 concentrations in rice soil samples. In the presence of the Synechocystis sp., the CH4 concentration decreased by 10–20 times compared to the control without the addition of cyanobacteria, demonstrating the maximum effectiveness. Using silicate fertilizer in combination with urea and A. azollae in paddy soil, Ali et al. (2014) reported a reduction in the maximum level of seasonal CH4 flux by 12%. The experiment evaluated the effectiveness of five complexes of soil amendments: (1) urea + rice straw compost, (2) urea + rice straw compost + silicate fertilizer, (3) urea + sesbania biomass + silicate fertilizer, (4) urea + azolla biomass + cyanobacterial mixture + silicate fertilizer, and (5) urea + cattle manure compost + silicate fertilizer. The A. azollae-treated plots showed the lowest CH4 flux of the three treatments during both rice-growing seasons. Malyan et al. (2021) observed a similar reduction in CH4 production when blue-green algae and Azolla were applied as rice biofertilizers. As a result, Azolla and cyanobacteria can reduce CH4 flux in two ways: (i) actively or directly oxidizing CH4 in hydromorphic soils and (ii) increasing the soil redox potential (Eh) and, consequently, decreasing CH4 production in rice soil. Additionally, the application of Azolla, Methylobacterium oryzae, and blue-green algae can also reduce the emission of N2O into the atmosphere.
2.2 Biogas Production A series of strategies have been devised under the Kyoto Protocol since 1997, including one that is known as the Clean Development Mechanism (CDM), which is intended to reduce emissions of GHGs (Yacob et al., 2005). Solar, wind, and biomass energy sources have emerged as sources of renewable energy (RE) that have improved the sustainability and environmental quality of the energy market (Ishikawa et al., 2021). In terms of heat and power generation, biomass energy production is extremely useful and reduces GHGs (Ahmed et al., 2017). As a clean energy source, biogas is produced by anaerobic treatment of biomass feedstock such as manure, sewage sludge, and food waste in a digester (Fig. 3.3) (Mathieu Dumont et al., 2013; Li et al., 2019). In addition to containing 50–70% CH4 and 30–50% CO2, as well as a limited number of other gases, biogas has a heating value of 21–24 MJ.m−3. The number of biogas plants in India and China has been approximately 4 million and 27 million since the 1970s, respectively. Generally, manure
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Electricity Biogas Animal manure, Sewage sludge, Weeds, Industrial wastes, Agricultural crops and residues
Biomethane Heat
Livestock bedding Digestate
Fertilizer Compost
Fig. 3.3 Applications of biogas production from biomass sources. (Adapted from Rabii et al. (2019))
management systems are installed in rural areas and are fueled by livestock manure (Bond & Templeton, 2011). By reducing global CH4, manure management systems can significantly reduce GHG emissions (Martinez et al., 2003; Xiaohong et al., 2011). Approximately 978–1776 kg of CO2 would be reduced annually if fermentation is applied in cow ranches based on a survey by Marañón et al. (2011). Moreover, biogas can eliminate solid waste. According to research conducted by Baldé et al. (2016), biogas generation was able to eliminate 62% of the volatile solid waste (VS) input within two years. Kivaisi and Rubindamayugi (1996) estimated that Tanzania produces 468,100 tons of organic matter annually, including coffee residue, sisal, sugar, and grain wastes. Methane generation was calculated to be 400 m−3/ton for sisal pulp, 400 m−3/ton for sisal industrial wastewater, and 650 m−3/ton for Robusta coffee waste. The potential substitution of fossil fuels by biogas may lower annual CO2 by approximately one million tons. By processing wastes with the anaerobic digestion system, annual CH4 emissions can be decreased to roughly 189 million m−3. Consequently, the production of biogas can contribute to the management of water and soil pollution, the mitigation of GHGs, and the development of RE (Wang & Calderon, 2012). Different-sized digesters produce biogas, which can be utilized for the simultaneous generation of heat and power in boilers or as biofuel for diesel engines (Börjesson & Berglund, 2006). In recent years, biogas processing has become crucial for replacing natural gas and supplying fuel for CNG automobiles (Makaruk et al., 2010; Subramanian et al., 2013). Adding organic matter to the soil after digestion in the digester is beneficial as an organic fertilizer because, according to a study carried out in Hangzhou (China) by Lu et al. (2000), CH4 in paddy fields where digested residues from a biogas plant were added to the soil was reduced. It was between 10% and 16% less than farms that directly received pig manure. Landfills and animal ranches can be regarded as biogas reactors that, in addition to meeting the energy demands of on-site operations, are also capable of boosting the electricity network (Karapidakis et al., 2010). Zamorano et al. (2007) evaluated a municipal waste landfill in southern Spain and observed that it was capable of producing
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250–550 N m−3/h of CH4 at a concentration of 45%, which could be used to generate nearly 4,500,000 kWh yearly. Biogas obtained from public garbage has high concentrations of aromatic hydrocarbons, siloxanes, and some halogenated hydrocarbons. In addition, the biogas produced from food waste is rich in sulfur-containing compounds such as H2S and SO2 (Li et al., 2019). Considering its commercial implications, biogas can potentially produce CH4 and N2O. Although upgrading biogas to biomethane can improve air quality and reduce GHGs, CH4 loss is still a significant environmental and economic challenge for biogas (Paolini et al., 2018). Due to the fact that CH4 is 25 times more potent than CO2, even minor biogas leaks have a substantial influence on global warming (Mathieu Dumont et al., 2013). Recently, the environmental and economic effects of CH4 loss from biogas power plants have been addressed (Kvist & Aryal, 2019). Minimizing CH4 leaks from biogas sites is also crucial for maintaining efficiency (Börjesson & Berglund, 2006). According to one estimate, CH4 losses from biogas plants in the United Kingdom amounted to up to 3.8% of total emissions (Bakkaloglu et al., 2021). Scheutz and Fredenslund (2019) assessed 23 biogas reactors and determined that CH4 loss rates varied from 0.4% to 14.9%. Meyer-Aurich et al. (2012) revealed that GHG emissions resulting from the utilization of energy crop wastes or CH4 leaks from reservoirs can neutralize the advantages of biogas. The second challenge associated with the anaerobic digestion process is the absence of appropriate optimization conditions. The effectiveness of biogas production is influenced by variables such as feedstock selection, storage tanks, thermal energy use, and ambient conditions (Meyer-Aurich et al., 2012). According to research conducted by Reinelt and Liebetrau (2020), monitoring a biogas plant reveals that the rate of CH4 emission is dependent on a number of factors. Some of these factors include shifts in the ambient temperature, the ability to use heat and combined power, and the effectiveness of gasholders. In addition to operational conditions such as tank filling level and substrate type, Hrad et al. (2015) demonstrated that weather conditions such as wind speed and solar radiation also influence CH4 flux. Muha et al. (2015) created a CH4 estimation model based on data from 21 biogas reactors in Germany and found that CH4 production efficiency is highly reliant on factors such as hydraulic retention time (HRT), digestate removal rate from the tank, and mixing ratio. Ruile et al. (2015) similarly documented a substantial correlation between CH4 output and HRT. Biogas contains a variety of gases, including H2S, which is hazardous and harms the pipelines and generators of an anaerobic digestion system. Andriamanohiarisoamanana et al. (2018) observed that the addition of waste iron powder (WIP) at a rate of 2 g L−1 reduced H2S by 93%. In addition, it had no adverse influence on the anaerobic digestion process. According to Farghali et al. (2020), direct mixing of WIP with cow dung is a feasible and cost- effective method for H2S removal and biogas purification since, in their investigation, adding 100 mg, 500 mg, and 1000 mg L−1 of WIP enhanced CH4 production by 99.36%. Presented herein are two methods that can be used in order to quantify the CH4 emissions from biogas plants: (i) an on-site measurement approach and (ii) a remote
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sensing approach. As a result of a summation of the calculated rates between both approaches, it is evident that there is a large difference between the results of both approaches (Fredenslund et al., 2018). As a result of using remote sensing techniques to estimate CH4 losses at a power plant in Rhineland-Palatinate, Germany, it was found that the average CH4 loss rate was 2.8 grams per second, which accounted for 4% of the total biomass produced at the plant (Groth et al., 2015). As part of the process of improving the biogas industry in the future, operational support networks need to be strengthened (Bond & Templeton, 2011). There is no doubt that cities, along with farms and industries, contribute significantly to GHG emissions (~70%), but fewer efforts have been put into reducing CH4 flux from cities in comparison to other sources. It has been concluded that in order to deal with CH4 in general, it is necessary to invest in research and development efforts, implement new reduction schemes, and conduct accurate and continuous monitoring of the amount of this gas in the atmosphere (Hopkins et al., 2016).
3 Precision Agriculture Approach There are a number of negative impacts associated with the uncontrolled use of inputs in crop production that include waste of resources, destruction of the environment, as well as substantial financial losses for farmers (Bhattacharyay, 2020). Taking appropriate action is necessary to ensure the long-term viability and optimal performance of the food system. In order for the food system to remain viable, innovative farming methods need to be adopted to combat climate change and food insecurity (Demirbaş, 2018). It has been widely attributed to precision agriculture (PA) as an advanced, all-encompassing, and globally standardized approach to managing agricultural diversity and enhancing productivity (Schellberg et al., 2008). PA contains novel agriculture management strategies that contribute to the aforementioned objectives. A great deal of investment has been made in agricultural research and technology over the past few decades. This has made it apparent that PA is crucial to the achievement of the goals of increased sustainable food production in terms of yields, profits, and reduced environmental fallout. As a result of the new and upgraded technologies that have enabled the collection of data, the food system has become more transparent and safer (Fig. 3.4) (Demirbaş, 2018; Schellberg et al., 2008). By focusing on the proper use of inputs, PA minimizes both the economic costs associated with input preparation and the environmental damage associated with agrochemical residues (Finger et al., 2019; Rad et al., 2022b). It is possible to carry out a wide range of farming operations under the PA strategy, such as soil preparation, planting, irrigation, weed control, spraying, and fertilizing. PA aims to maximize the efficiency of these activities by using a variety of technologies such as GPS, sensors, Internet of Things (IoT), robotics, unmanned aerial vehicles (UAVs), machine learning, and decision support systems (Bhattacharyay, 2020; Shamshiri et al., 2022). The environmental benefits of this approach include reduced soil degradation, water contamination, carbon sequestration, and GHG emissions
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Fig. 3.4 Some of the applicable technologies for fertilizer management in agriculture. (Adapted from Doshi and Varghese (2022))
IoT
Machine Learning
Smart Technologies in Agriculture
Renewable Energy
Data Analytics
Cloud Technology
(Kassam & Brammer, 2016; Malla et al., 2022; Bandh et al., 2021, 2023; Mushtaq et al., 2020). Precise fertilizer management is a useful framework for figuring out how PA might be used to minimize GHG emissions, in particular CH4, from agricultural systems. This recently developed concept integrates agronomic and manure management techniques with advanced technologies in order to improve crop yield (Moshia et al., 2014). Fertilizer management includes the operation of collecting, storing, and warehousing fertilizer, as well as the process of transporting fertilizer to the field and applying it (Kleinman et al., 2017). Numerous studies have shown that proper manure management can have positive effects on the economy and the ecosystem (Niles et al., 2019). Increased profitability, a lower risk of soil pollution from livestock manure, and enhanced crop and livestock yields are all major consequences of efficient management of manure distribution on farms. Morris et al. (1999) developed a GPS-enabled fertilizer spreader with the purpose of avoiding fertilization near water sources and other sensitive areas. By analyzing a fertilizer distributor, Cabot et al. (2006) demonstrated that it is possible to precisely regulate soil nitrogen levels using the instrument. Additionally, remote control technologies such as satellite imagery, UAVs, and IoT have become serviceable and can dramatically improve the above processes in farming (Higgins et al., 2019). Using data from three farms on the Portuguese-Spanish border, Loures et al. (2020) determined that integrating systems such as remotely piloted aircraft systems (RPAS), UAV, and Normalized Vegetation Difference Index (NDVI) can result in significant economic savings, even on small farms (less than 50 ha). Evidently, the effectiveness of PA is contingent on its precise application in analyzing the circumstances and spatial and temporal administration of agriculture activities (Pierce & Nowak, 1999). However, in spite of the growing number of advantages that PA technologies can offer as well as the fact that PA technologies can be widely applied in fields, growers
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still do not employ them (Lindblom et al., 2017). It has been reported that the rate of adoption of PA by farmers at present is extremely low (Higgins et al., 2019), and the reasons for the disparate rates of adoption between and within countries merit further research (Kassam & Brammer, 2016). As Schieffer and Dillon (2013) found in their survey of farmers in western Kentucky, the extra costs associated with implementing PA technologies on farms make them less responsive to policies designed solely to provide financial incentives to reduce pollution. The reluctance to perform PA appears to be caused by a lack of access to specialists, as well as financial and educational limitations (Kitchen et al., 2002). Governments, however, may also contribute to the challenges associated with PA implementation. Kulyasov et al. (2020) addressed the challenges associated with expanding PA in Russia. They concluded that the absence of a regulatory framework for data management and the lack of institutional support for PA were major factors. Stuart et al. (2014) conducted a survey of US corn farmers and found that poor perceptions of climate change, lack of access to advanced technologies, and political and financial restrictions can all prevent the enhancement of nitrogen efficiency. By utilizing educational programs and tax incentives, some of these challenges can be addressed. PA offers economic, social, and ecological advantages that can be enhanced through the enhancement of its technical infrastructure and the adoption of legal frameworks (Finger et al., 2019). As PA is essential for food security, it is imperative to enhance (i) agricultural knowledge and (ii) computer science and information management abilities in order to facilitate its development. Furthermore, a multidisciplinary approach and the collaboration of professionals from other scientific disciplines are required for agriculture’s long-term sustainability (Lindblom et al., 2017). To combat the challenge of global warming and maintain agricultural production, international collaboration is required (Rad et al., 2022c; Zarei & Kaviani Rad, 2020; Parray et al., 2022 Bandh et al., 2022 Bandh, 2022a, b).
4 Conclusions Methane (CH4) is a greenhouse gas that is released into the atmosphere as a result of natural and anthropogenic activities. These include deforestation and biomass burning, rice farming, and livestock production. Due to intestinal fermentation in ruminants and the production of manure, the livestock industry is widely regarded as one of the largest contributors to CH4 emissions. In this chapter, practical methods for reducing the emissions of GHGs from livestock manure were examined. The first efficient biological treatment option was the substitution or combined application of animal dung and biofertilizers such as some PGPRs, fungi, and Azolla. Additionally, biogas reactors can be advantageous for limiting CH4 produced from animal manure if appropriate manufacturing conditions are provided and methane loss is controlled. Measurement and management of manure distribution in the field may be accomplished by utilizing technology such as the IoT, robotics, and UAVs. To prevent further increases in CH4 production in the coming years and the
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subsequent worsening of global warming and climate change, the recommended solutions must be implemented immediately on a global level.
References Agnihotri, S., Kulshreshtha, K., & Singh, S. N. (1999). Mitigation strategy to contain methane emission from rice-fields. Environmental Monitoring and Assessment, 58(1), 95–104. https:// doi.org/10.1023/A:1006081317688 Ahmed, W. A., Aggour, M., & Naciri, M. (2017). Biogas control: Methane production monitoring using Arduino. International Journal of Biotechnology and Bioengineering, 11(2), 130–133. https://doi.org/10.5281/zenodo.1339948 Ali, M. A., Sattar, M. A., Islam, M. N., & Inubushi, K. (2014). Integrated effects of organic, inorganic and biological amendments on methane emission, soil quality and rice productivity in irrigated paddy ecosystem of Bangladesh: Field study of two consecutive rice growing seasons. Plant and Soil, 378(1–2), 239–252. https://doi.org/10.1007/s11104-014-2023-y Andriamanohiarisoamanana, F. J., Shirai, T., Yamashiro, T., Yasui, S., Iwasaki, M., Ihara, I., Nishida, T., Tangtaweewipat, S., & Umetsu, K. (2018). Valorizing waste iron powder in biogas production: Hydrogen sulfide control and process performances. Journal of Environmental Management, 208, 134–141. https://doi.org/10.1016/j.jenvman.2017.12.012 Bakkaloglu, S., Lowry, D., Fisher, R. E., France, J. L., Brunner, D., Chen, H., & Nisbet, E. G. (2021). Quantification of methane emissions from UK biogas plants. Waste Management, 124, 82–93. https://doi.org/10.1016/j.wasman.2021.01.011 Baldé, H., VanderZaag, A. C., Burtt, S. D., Wagner-Riddle, C., Crolla, A., Desjardins, R. L., & MacDonald, D. J. (2016). Methane emissions from digestate at an agricultural biogas plant. Bioresource Technology, 216, 914–922. https://doi.org/10.1016/j.biortech.2016.06.031 Bandh, S. A. (2022a). Climate change: The social and scientific construct (1st ed.). Springer. https://doi.org/10.1007/978-3-030-86290-9 Bandh, S. A. (2022b). Sustainable agriculture: Technological progressions and transitions (1st ed.). Springer. https://doi.org/10.1007/978-3-030-83066-3 Bandh, S. A., Shafi, S., Peerzada, M., Rehman, T., Bashir, S., Wani, S. A., & Dar, R. (2021). Multidimensional analysis of global climate change: A review. Environmental Science and Pollution Research International, 28(20), 24872–24888. https://doi.org/10.1007/ s11356-021-13139-7 Bandh, S. A., Parray, J. A., & Shameem, N. (2022). Climate change and microbial diversity: Advances and challenges (1st ed.). Apple Academic Press. https://www.routledge.com/Climate- Change-a nd-M icrobial-D iversity-A dvances-a nd-C hallenges/Bandh-Parray-S hameem/p/ book/9781774637821 Bandh, S. A., Malla, F. A., Qayoom, I., Mohi-ud-Din, H., Butt, A. K., Altaf, A., Wani, S. A., Betts, R., Truong, T. H., Pham, N. D. K., Cao, D. N., & Ahmed, S. F. (2023). Importance of blue carbon in mitigating climate change and plastic/microplastic pollution and promoting circular economy. Sustainability, 15(3), 2682. https://doi.org/10.3390/su15032682 Bayu, W., Rethman, N. F. G., & Hammes, P. S. (2005). The role of animal manure in sustainable soil fertility management in sub-Saharan Africa: A review. Journal of Sustainable Agriculture, 25(2), 113–136. https://doi.org/10.1300/J064v25n02_09 Bhardwaj, D., Ansari, M. W., Sahoo, R. K., & Tuteja, N. (2014). Biofertilizers function as key player in sustainable agriculture by improving soil fertility, plant tolerance and crop productivity. Microbial Cell Factories, 13(1), 66. https://doi.org/10.1186/1475-2859-13-66 Bhattacharyay, D. (2020). Future of precision agriculture in India. In Protected cultivation and smart agriculture. https://www.researchgate.net/ publication/347511698_Future_of_Precision_Agriculture_in_India
3 Manure Management to Reduce Methane Emissions
41
Black, J. L., Davison, T. M., & Box, I. (2021). Methane emissions from ruminants in Australia: Mitigation potential and applicability of mitigation strategies. Animals (Basel), 11(4). https:// doi.org/10.3390/ani11040951 Bodelier, P. L. E. (2011). Interactions between nitrogenous fertilizers and methane cycling in wetland and upland soils. Current Opinion in Environmental Sustainability, 3(5), 379–388. https:// doi.org/10.1016/j.cosust.2011.06.002 Bond, T., & Templeton, M. R. (2011). History and future of domestic biogas plants in the developing world. Energy for Sustainable Development, 15(4), 347–354. https://doi.org/10.1016/j. esd.2011.09.003 Börjesson, P., & Berglund, M. (2006). Environmental systems analysis of biogas systems—Part I: Fuel-cycle emissions. Biomass and Bioenergy, 30(5), 469–485. https://doi.org/10.1016/j. biombioe.2005.11.014 Broucek, J. (2014). Production of methane emissions from ruminant husbandry: A review. Journal of Environmental Protection, 05(15), 1482–1493. https://doi.org/10.4236/jep.2014.515141 Cabot, P., Pierce, F., Nowak, P., & Karthikeyan, K. (2006). Monitoring and predicting manure application rates using precision conservation technology. Journal of Soil and Water Conservation, 61(5), 282–292. https://www.jswconline.org/content/61/5/282 Cantera, S., Muñoz, R., Lebrero, R., López, J. C., Rodríguez, Y., & García-Encina, P. A. (2018). Technologies for the bioconversion of methane into more valuable products. Current Opinion in Biotechnology, 50, 128–135. https://doi.org/10.1016/j.copbio.2017.12.021 Collins, W. J., Webber, C. P., Cox, P. M., Huntingford, C., Lowe, J., Sitch, S., Chadburn, S. E., Comyn-Platt, E., Harper, A. B., Hayman, G., & Powell, T. (2018). Increased importance of methane reduction for a 1.5 degree target. Environmental Research Letters, 13(5). https://doi. org/10.1088/1748-9326/aab89c Dalal, R. C., Allen, D. E., Livesley, S. J., & Richards, G. (2008). Magnitude and biophysical regulators of methane emission and consumption in the Australian agricultural, forest, and submerged landscapes: A review. Plant and Soil, 309(1–2), 43–76. https://doi.org/10.1007/ s11104-007-9446-7 De Cara, S., Houzé, M., & Jayet, P.-A. (2005). Methane and nitrous oxide emissions from agriculture in the EU: A spatial assessment of sources and abatement costs. Environmental and Resource Economics, 32(4), 551–583. https://doi.org/10.1007/s10640-005-0071-8 Demirbaş, N. (2018). Precision agriculture in terms of food security: Needs for the future. Precision Agriculture, 27. https://www.researchgate.net/publication/328655146_Precision_Agriculture_ in_Terms_of_Food_Security_Needs_for_The_Future Doshi, M., & Varghese, A. (2022). Chapter 12. Smart agriculture using renewable energy and AI-powered IoT. In A. Abraham, S. Dash, J. J. P. C. Rodrigues, B. Acharya, & S. K. Pani (Eds.), AI, edge and IoT-based smart agriculture (pp. 205–225). Academic Press. https://doi. org/10.1016/B978-0-12-823694-9.00028-1 Farghali, M., Andriamanohiarisoamanana, F. J., Ahmed, M. M., Kotb, S., Yamamoto, Y., Iwasaki, M., Yamashiro, T., & Umetsu, K. (2020). Prospects for biogas production and H2S control from the anaerobic digestion of cattle manure: The influence of microscale waste iron powder and iron oxide nanoparticles. Waste Management, 101, 141–149. https://doi.org/10.1016/j. wasman.2019.10.003 Finger, R., Swinton, S. M., El Benni, N., & Walter, A. (2019). Precision farming at the nexus of agricultural production and the environment. Annual Review of Resource Economics, 11(1), 313–335. https://doi.org/10.1146/annurev-resource-100518-093929 Flesch, T. K., Desjardins, R. L., & Worth, D. (2011). Fugitive methane emissions from an agricultural biodigester. Biomass and Bioenergy, 35(9), 3927–3935. https://doi.org/10.1016/j. biombioe.2011.06.009 Fletcher, S. E. M., & Schaefer, H. (2019). Rising methane: A new climate challenge. Science, 364(6444), 932–933. https://doi.org/10.1126/science.aax1828 Food and Agriculture Organization. (2022). Key facts and findings, GHG emissions by livestock. https://www.fao.org/news/story/en/item/197623/icode/. Retrieved July 20, 2022.
42
A. K. Rad et al.
Fredenslund, A. M., Hinge, J., Holmgren, M. A., Rasmussen, S. G., & Scheutz, C. (2018). On-site and ground-based remote sensing measurements of methane emissions from four biogas plants: A comparison study. Bioresource Technology, 270, 88–95. https://doi.org/10.1016/j. biortech.2018.08.080 Groth, A., Maurer, C., Reiser, M., & Kranert, M. (2015). Determination of methane emission rates on a biogas plant using data from laser absorption spectrometry. Bioresource Technology, 178, 359–361. https://doi.org/10.1016/j.biortech.2014.09.112 Haque, M. N. (2018). Dietary manipulation: A sustainable way to mitigate methane emissions from ruminants. Journal of Animal Science and Technology, 60, 15. https://doi.org/10.1186/ s40781-018-0175-7 Higgins, S., Schellberg, J., & Bailey, J. S. (2019). Improving productivity and increasing the efficiency of soil nutrient management on grassland farms in the UK and Ireland using precision agriculture technology. European Journal of Agronomy, 106, 67–74. https://doi.org/10.1016/j. eja.2019.04.001 Höglund-Isaksson, L., Gómez-Sanabria, A., Klimont, Z., Rafaj, P., & Schöpp, W. (2020). Technical potentials and costs for reducing global anthropogenic methane emissions in the 2050 timeframe – Results from the GAINS model. Environmental Research Communications, 2(2). https://doi.org/10.1088/2515-7620/ab7457 Hopkins, F. M., Ehleringer, J. R., Bush, S. E., Duren, R. M., Miller, C. E., Lai, C.-T., Hsu, Y.-K., Carranza, V., & Randerson, J. T. (2016). Mitigation of methane emissions in cities: How new measurements and partnerships can contribute to emissions reduction strategies. Earth’s Future, 4(9), 408–425. https://doi.org/10.1002/2016EF000381 Hou, Y., Velthof, G. L., & Oenema, O. (2015). Mitigation of ammonia, nitrous oxide and methane emissions from manure management chains: A meta-analysis and integrated assessment. Global Change Biology, 21(3), 1293–1312. https://doi.org/10.1111/gcb.12767 Hrad, M., Piringer, M., & Huber-Humer, M. (2015). Determining methane emissions from biogas plants—Operational and meteorological aspects. Bioresource Technology, 191, 234–243. https://doi.org/10.1016/j.biortech.2015.05.016 Hwang, I. Y., Nguyen, A. D., Nguyen, T. T., Nguyen, L. T., Lee, O. K., & Lee, E. Y. (2018). Biological conversion of methane to chemicals and fuels: Technical challenges and issues. Applied Microbiology and Biotechnology, 102(7), 3071–3080. https://doi.org/10.1007/ s00253-018-8842-7 Hynes, S., Morrissey, K., O’Donoghue, C., & Clarke, G. (2009). A spatial micro-simulation analysis of methane emissions from Irish agriculture. Ecological Complexity, 6(2), 135–146. https:// doi.org/10.1016/j.ecocom.2008.10.014 IGSD. (2016). Estimated global anthropogenic methane emissions by source, Retrieved July 17, 2022. https://www.igsd.org/estimated-global-anthropogenic-methane-emissions-by- source-2010/ Ishikawa, S., Connell, N. O., Lechner, R., Hara, R., Kita, H., & Brautsch, M. (2021). Load response of biogas CHP systems in a power grid. Renewable Energy, 170, 12–26. https://doi. org/10.1016/j.renene.2021.01.120 Jackson, R. B., Saunois, M., Bousquet, P., Canadell, J. G., Poulter, B., Stavert, A. R., Bergamaschi, P., Niwa, Y., Segers, A., & Tsuruta, A. (2020). Increasing anthropogenic methane emissions arise equally from agricultural and fossil fuel sources. Environmental Research Letters, 15(7). https://doi.org/10.1088/1748-9326/ab9ed2 Jeffery, S., Verheijen, F. G. A., Kammann, C., & Abalos, D. (2016). Biochar effects on methane emissions from soils: A meta-analysis. Soil Biology and Biochemistry, 101, 251–258. https:// doi.org/10.1016/j.soilbio.2016.07.021 Kantha, T., Kantachote, D., & Klongdee, N. (2015). Potential of biofertilizers from selected Rhodopseudomonas palustris strains to assist rice (Oryza sativa L. subsp. indica) growth under salt stress and to reduce greenhouse gas emissions. Annals of Microbiology, 65(4), 2109–2118. https://doi.org/10.1007/s13213-015-1049-6
3 Manure Management to Reduce Methane Emissions
43
Karapidakis, E. S., Tsave, A. A., Soupios, P. M., & Katsigiannis, Y. A. (2010). Energy efficiency and environmental impact of biogas utilization in landfills. International Journal of Environmental Science and Technology, 7(3), 599–608. https://doi.org/10.1007/BF03326169 Kassam, A., & Brammer, H. (2016). Environmental implications of three modern agricultural practices: Conservation Agriculture, the System of Rice Intensification and Precision Agriculture. International Journal of Environmental Studies, 73(5), 702–718. https://doi.org/1 0.1080/00207233.2016.1185329 Key, N., & Tallard, G. (2012). Mitigating methane emissions from livestock: A global analysis of sectoral policies. Climatic Change, 112(2), 387–414. https://doi.org/10.1007/s10584-011-0206-6 Kitchen, N. R., Snyder, C. J., Franzen, D. W., & Wiebold, W. J. (2002). Educational needs of precision agriculture. Precision Agriculture, 3(4), 341–351. https://doi.org/10.102 3/A:1021588721188 Kivaisi, A. K., & Rubindamayugi, M. S. T. (1996). The potential of agro-industrial residues for production of biogas and electricity in Tanzania. Renewable Energy, 9(1–4), 917–921. https:// doi.org/10.1016/0960-1481(96)88429-1 Kleinman, P. J. A., Buda, A. R., Sharpley, A. N., Khosla, R., Delgado, J., Sassenrath, G., & Mueller, T. (2017). Elements of precision manure management. In Precision conservation (pp. 165–192). https://doi.org/10.2134/agronmonogr59.c9. Kulyasov, N. S., Novik, N. N., Klyukin, N. D., & Charyyarova, G. D. (2020). Precision agriculture in The Russian Federation: Problems and directions in development. IOP Conference Series: Earth and Environmental Science, 548(2), 022090. https://doi.org/10.1088/1755-1315/548/2/022090 Kvist, T., & Aryal, N. (2019). Methane loss from commercially operating biogas upgrading plants. Waste Management, 87, 295–300. https://doi.org/10.1016/j.wasman.2019.02.023 Lassey, K. R. (2008). Livestock methane emission and its perspective in the global methane cycle. Australian Journal of Experimental Agriculture, 48(2). https://doi.org/10.1071/EA07220 Li, X., Dodson, J., Zhou, J., & Zhou, X. (2009). Increases of population and expansion of rice agriculture in Asia, and anthropogenic methane emissions since 5000 BP. Quaternary International, 202(1–2), 41–50. https://doi.org/10.1016/j.quaint.2008.02.009 Li, Y., Alaimo, C. P., Kim, M., Kado, N. Y., Peppers, J., Xue, J., Wan, C., Green, P. G., Zhang, R., Jenkins, B. M., Vogel, C. F. A., Wuertz, S., Young, T. M., & Kleeman, M. J. (2019). Composition and toxicity of biogas produced from different feedstocks in California. Environmental Science and Technology, 53(19), 11569–11579. https://doi.org/10.1021/acs.est.9b03003 Lindblom, J., Lundström, C., Ljung, M., & Jonsson, A. (2017). Promoting sustainable intensification in precision agriculture: Review of decision support systems development and strategies. Precision Agriculture, 18(3), 309–331. https://doi.org/10.1007/s11119-016-9491-4 Loures, L., Chamizo, A., Ferreira, P., Loures, A., Castanho, R., & Panagopoulos, T. (2020). Assessing the effectiveness of precision agriculture management systems in Mediterranean small farms. Sustainability, 12(9). https://doi.org/10.3390/su12093765 Lu, W. F., Chen, W., Duan, B. W., Guo, W. M., Lu, Y., Lantin, R. S., Wassmann, R., & Neue, H. U. (2000). Methane emissions and mitigation options in irrigated rice fields in Southeast China. Nutrient Cycling in Agroecosystems, 58(1/3), 65–73. https://doi.org/10.102 3/A:1009830232650 Makaruk, A., Miltner, M., & Harasek, M. (2010). Membrane biogas upgrading processes for the production of natural gas substitute. Separation and Purification Technology, 74(1), 83–92. https://doi.org/10.1016/j.seppur.2010.05.010 Malla, F. A., Mushtaq, A., Bandh, S. A., Qayoom, I., Ho-ang, A. T., & Shahid-e-Murtaza. (2022). Understanding climate change: Scientific opinion and public perspective. In S. A. Bandh (Ed.), Climate change: The social and scientific construct. Springer Nature Publishing. https://link. springer.com/chapter/10.1007/978-3-030-86290-9_1 Malyan, S. K., Bhatia, A., Kumar, A., Gupta, D. K., Singh, R., Kumar, S. S., Tomer, R., Kumar, O., & Jain, N. (2016). Methane production, oxidation and mitigation: A mechanistic understanding and comprehensive evaluation of influencing factors. Science of the Total Environment, 572, 874–896. https://doi.org/10.1016/j.scitotenv.2016.07.182
44
A. K. Rad et al.
Malyan, S. K., Bhatia, A., Tomer, R., Harit, R. C., Jain, N., Bhowmik, A., & Kaushik, R. (2021). Mitigation of yield-scaled greenhouse gas emissions from irrigated rice through Azolla, Blue- green algae, and plant growth–promoting bacteria. Environmental Science and Pollution Research International, 28(37), 51425–51439. https://doi.org/10.1007/s11356-021-14210-z Marañón, E., Salter, A. M., Castrillón, L., Heaven, S., & Fernández-Nava, Y. (2011). Reducing the environmental impact of methane emissions from dairy farms by anaerobic digestion of cattle waste. Waste Management, 31(8), 1745–1751. https://doi.org/10.1016/j.wasman.2011.03.015 Martinez, J., Guiziou, F., Peu, P., & Gueutier, V. (2003). Influence of treatment techniques for pig slurry on methane emissions during subsequent storage. Biosystems Engineering, 85(3), 347–354. https://doi.org/10.1016/S1537-5110(03)00067-9 Mathieu Dumont, N. L., Luning, L., Yildiz, I., & Koop, K. (2013). Methane emissions in biogas production. In The biogas handbook (pp. 248–266). https://doi.org/10.1533/9780857097415.2.248 . Meyer-Aurich, A., Schattauer, A., Hellebrand, H. J., Klauss, H., Plöchl, M., & Berg, W. (2012). Impact of uncertainties on greenhouse gas mitigation potential of biogas production from agricultural resources. Renewable Energy, 37(1), 277–284. https://doi.org/10.1016/j. renene.2011.06.030 Miller, S. M., Wofsy, S. C., Michalak, A. M., Kort, E. A., Andrews, A. E., Biraud, S. C., Dlugokencky, E. J., Eluszkiewicz, J., Fischer, M. L., Janssens-Maenhout, G., Miller, B. R., Miller, J. B., Montzka, S. A., Nehrkorn, T., & Sweeney, C. (2013). Anthropogenic emissions of methane in the United States. Proceedings of the National Academy of Sciences of the United States of America, 110(50), 20018–20022. https://doi.org/10.1073/pnas.1314392110 Morris, D. K., Ess, D. R., Hawkins, S. E., & Parsons, S. D. (1999). Development of a site-specific application system for liquid animal manures. Applied Engineering in Agriculture, 15(6), 633–638. https://doi.org/10.13031/2013.5829. https://elibrary.asabe.org/abstract.asp?aid=5829 Moshia, M. E., Khosla, R., Longchamps, L., Reich, R., Davis, J. G., & Westfall, D. G. (2014). Precision manure management across site-specific management zones: Grain yield and economic analysis. Agronomy Journal, 106(6), 2146–2156. https://doi.org/10.2134/agronj13.0400 Muha, I., Linke, B., & Wittum, G. (2015). A dynamic model for calculating methane emissions from digestate based on co-digestion of animal manure and biogas crops in full scale German biogas plants. Bioresource Technology, 178, 350–358. https://doi.org/10.1016/j.biortech.2014.08.060 Mushtaq, B., Bandh, S. A., & Shafi, S. (2020). Environmental management: Environmental issues, awareness and abatement (1st ed.). Springer. https://doi.org/10.1007/978-981-15-3813-1 Niles, M. T., Horner, C., Chintala, R., & Tricarico, J. (2019). A review of determinants for dairy farmer decision making on manure management strategies in high-income countries. Environmental Research Letters, 14(5). https://doi.org/10.1088/1748-9326/ab1059 Pandey, A., Mai, V. T., Vu, D. Q., Bui, T. P. L., Mai, T. L. A., Jensen, L. S., & de Neergaard, A. (2014). Organic matter and water management strategies to reduce methane and nitrous oxide emissions from rice paddies in Vietnam. Agriculture, Ecosystems and Environment, 196, 137–146. https://doi.org/10.1016/j.agee.2014.06.010 Paolini, V., Petracchini, F., Segreto, M., Tomassetti, L., Naja, N., & Cecinato, A. (2018). Environmental impact of biogas: A short review of current knowledge. Journal of Environmental Science and Health. Part A, Toxic/Hazardous Substances and Environmental Engineering, 53(10), 899–906. https://doi.org/10.1080/10934529.2018.1459076 Parray, J. A., Bandh, S. A., & Shameem, N. (2022). Climate change and microbes: Impact and vulnerability (1st ed.). Apple Academic Press. https://www.routledge.com/ Climate-C hange-a nd-M icrobes-I mpacts-a nd-Vulnerability/Parray-B andh-S hameem/p/ book/9781774637210 Pickering, N. K., Oddy, V. H., Basarab, J., Cammack, K., Hayes, B., Hegarty, R. S., Lassen, J., McEwan, J. C., Miller, S., Pinares-Patiño, C. S., & de Haas, Y. (2015). Animal board invited review: Genetic possibilities to reduce enteric methane emissions from ruminants. Animal, 9(9), 1431–1440. https://doi.org/10.1017/S1751731115000968
3 Manure Management to Reduce Methane Emissions
45
Pierce, F. J., & Nowak, P. (1999). Aspects of precision agriculture. Advances in Agronomy, 67, 1–85. https://doi.org/10.1016/S0065-2113(08)60513-1 Pingak, G. M. F., Sutanto, H., Akhdiya, A., & Rusmana, I. (2014). Effectivity of methanotrophic bacteria and Ochrobactrum anthropi as biofertilizer and emission reducer of CH4 and N2O in inorganic paddy fields. Journal of Medical and Biological Engineering, 3(3). https://doi. org/10.12720/jomb.3.3.217-221 Prasanna, R., Kumar, V., Kumar, S., Yadav, A. K., Tripathi, U., Singh, A. K., Jain, M. C., Gupta, P., Singh, P. K., & Sethunathan, N. (2002). Methane production in rice soil is inhibited by cyanobacteria. Microbiological Research, 157(1), 1–6. https://doi.org/10.1078/0944-5013-00124 Rabii, A., Aldin, S., Dahman, Y., & Elbeshbishy, E. (2019). A review on anaerobic co-digestion with a focus on the microbial populations and the effect of multi-stage digester configuration. Energies, 12(6). https://doi.org/10.3390/en12061106 Rad, A. K., Zarei, M., Astaikina, A., Streletskii, R., & Etesami, H. (2022a). Chapter 1 - effects of microbial inoculants on growth, yield, and fruit quality under stress conditions. In M. Seymen, E. S. Kurtar, C. Erdinc, & A. Kumar (Eds.), Sustainable Horticulture (pp. 1–38). Academic. https://doi.org/10.1016/B978-0-323-91861-9.00014-8 Rad, A. K., Astaykina, A., Streletskii, R., Afsharyzad, Y., Etesami, H., Zarei, M., & Balasundram, S. K. (2022b). An overview of antibiotic resistance and abiotic stresses affecting antimicrobial resistance in agricultural soils. International Journal of Environmental Research and Public Health, 19(8). https://doi.org/10.3390/ijerph19084666 Rad, A., Zarei, M., Pourghasemi, H. R., & Tiefenbacher, J. P. (2022c). Chapter 27 – The COVID-19 crisis and its consequences for global warming and climate change. In H. R. Pourghasemi (Ed.), Computers in earth and environmental sciences (pp. 377–385). Elsevier. https://doi. org/10.1016/B978-0-323-89861-4.00006-3 Ramin, M., & Huhtanen, P. (2013). Development of equations for predicting methane emissions from ruminants. Journal of Dairy Science, 96(4), 2476–2493. https://doi.org/10.3168/ jds.2012-6095 Reay, D. S., Smith, P., Christensen, T. R., James, R. H., & Clark, H. (2018). Methane and global environmental change. Annual Review of Environment and Resources, 43(1), 165–192. https:// doi.org/10.1146/annurev-environ-102017-030154 Rehman, A., Ma, H., Irfan, M., & Ahmad, M. (2020). Does carbon dioxide, methane, nitrous oxide, and GHG emissions influence the agriculture? Evidence from China. Environmental Science and Pollution Research International, 27(23), 28768–28779. https://doi.org/10.1007/ s11356-020-08912-z Reinelt, T., & Liebetrau, J. (2020). Monitoring and mitigation of methane emissions from pressure relief valves of a biogas plant. Chemical Engineering and Technology, 43(1), 7–18. https://doi. org/10.1002/ceat.201900180 Ruile, S., Schmitz, S., Mönch-Tegeder, M., & Oechsner, H. (2015). Degradation efficiency of agricultural biogas plants—A full-scale study. Bioresource Technology, 178, 341–349. https:// doi.org/10.1016/j.biortech.2014.10.053 Schellberg, J., Hill, M. J., Gerhards, R., Rothmund, M., & Braun, M. (2008). Precision agriculture on grassland: Applications, perspectives and constraints. European Journal of Agronomy, 29(2–3), 59–71. https://doi.org/10.1016/j.eja.2008.05.005 Scheutz, C., & Fredenslund, A. M. (2019). Total methane emission rates and losses from 23 biogas plants. Waste Management, 97, 38–46. https://doi.org/10.1016/j.wasman.2019.07.029 Schieffer, J., & Dillon, C. (2013). Precision agriculture and agro-environmental policy. In J. V. Stafford (Ed.), Precision agriculture 2013 (pp. 755–760). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-778-3_93 Shamshiri, R. R., Balasundram, S. K., Rad, A. K., Sultan, M., & Hameed, I. A. (2022). An overview of soil moisture and salinity sensors for digital agriculture applications. In R. R. Shamshiri & S. Shafian (Eds.), Digital agriculture, methods and applications. IntechOpen. https://doi. org/10.5772/intechopen.103898
46
A. K. Rad et al.
Stuart, D., Schewe, R. L., & McDermott, M. (2014). Reducing nitrogen fertilizer application as a climate change mitigation strategy: Understanding farmer decision-making and potential barriers to change in the US. Land Use Policy, 36, 210–218. https://doi.org/10.1016/j. landusepol.2013.08.011 Subramanian, K. A., Mathad, V. C., Vijay, V. K., & Subbarao, P. M. V. (2013). Comparative evaluation of emission and fuel economy of an automotive spark ignition vehicle fuelled with methane enriched biogas and CNG using chassis dynamometer. Applied Energy, 105, 17–29. https:// doi.org/10.1016/j.apenergy.2012.12.011 Tauseef, S. M., Premalatha, M., Abbasi, T., & Abbasi, S. A. (2013). Methane capture from livestock manure. Journal of Environmental Management, 117, 187–207. https://doi.org/10.1016/j. jenvman.2012.12.022 VanderZaag, A. C., Flesch, T. K., Desjardins, R. L., Baldé, H., & Wright, T. (2014). Measuring methane emissions from two dairy farms: Seasonal and manure-management effects. Agricultural and Forest Meteorology, 194, 259–267. https://doi.org/10.1016/j. agrformet.2014.02.003 Wang, Z., & Calderon, M. M. (2012). Environmental and economic analysis of application of water hyacinth for eutrophic water treatment coupled with biogas production. Journal of Environmental Management, 110, 246–253. https://doi.org/10.1016/j.jenvman.2012.06.031 Wang, Z. P., Lindau, C. W., Delaune, R. D., & Patrick, W. H. (1993). Methane emission and entrapment in flooded rice soils as affected by soil properties. Biology and Fertility of Soils, 16(3), 163–168. https://doi.org/10.1007/BF00361401 World Bank. (2020). Climate watch. GHG emissions. World Resources Institute. Retrieved July 17, 2022. https://data.worldbank.org/indicator/EN.ATM.METH.KT.CE?end=2019&start=199 0&type=shaded&view=chart Xiaohong, Z., Jia, H., & Junxin, C. A. O. (2011). Study on mitigation strategies of methane emission from rice paddies in the implementation of ecological agriculture. Energy Procedia, 5, 2474–2480. https://doi.org/10.1016/j.egypro.2011.03.425 Yacob, S., Hassan, M. A., Shirai, Y., Wakisaka, M., & Subash, S. (2005). Baseline study of methane emission from open digesting tanks of palm oil mill effluent treatment. Chemosphere, 59(11), 1575–1581. https://doi.org/10.1016/j.chemosphere.2004.11.040 Yusuf, R. O., Noor, Z. Z., Abba, A. H., Hassan, M. A. A., & Din, M. F. M. (2012). Methane emission by sectors: A comprehensive review of emission sources and mitigation methods. Renewable and Sustainable Energy Reviews, 16(7), 5059–5070. https://doi.org/10.1016/j. rser.2012.04.008 Zamorano, M., Ignacio Pérez Pérez, J., Aguilar Pavés, I., & Ramos Ridao, Á. (2007). Study of the energy potential of the biogas produced by an urban waste landfill in Southern Spain. Renewable and Sustainable Energy Reviews, 11(5), 909–922. https://doi.org/10.1016/j.rser.2005.05.007 Zarei, M., & Kaviani Rad, A. K. (2020). Covid-19, challenges and recommendations in agriculture. Journal of Botanical Research, 2(1), 12–15. https://doi.org/10.30564/jrb.v2i1.1841 Zhang, A., Cui, L., Pan, G., Li, L., Hussain, Q., Zhang, X., Zheng, J., & Crowley, D. (2010). Effect of biochar amendment on yield and methane and nitrous oxide emissions from a rice paddy from Tai Lake plain, China. Agriculture, Ecosystems and Environment, 139(4), 469–475. https://doi.org/10.1016/j.agee.2010.09.003
Chapter 4
Crop Residue Incorporation to Enhance Soil Health in the Rice–Wheat System Hamna Bashir, Waqas Mohy-Ud-Din, Zahoor Mujdded Choudary, Muhammad Mahroz Hussain, and Muhammad Ashir Hameed
Abstract There has been a fourfold rise in the world population in the past century. To feed the ever-increasing numbers of people, increased agricultural and industrial processes have put further burden on food production. The utilization of crop waste in fields might be regarded as crucial in developing countries. Agricultural soil health is altered for increasing physical, chemical, and biological process owing to the lack of alternative organic amendments. Agricultural residual management techniques in developing countries, i.e., surface retention, integration, and removal, are discussed in this chapter with their benefits and hazards to the agroecosystems based on cereal crops. The health of agricultural soils has deteriorated as a result of increased food production over time. Nutrient cycling and soil quality are influenced due to the various biological, chemical, and physical processes that occur on organic matter that is returned to the soil in the form of crop residues. This chapter will discuss important biological properties like soil microbial biomass and soil biodiversity; physical properties like soil moisture content, soil temperature, soil compaction, and erosion; and chemical properties like soil cation exchange capacity, soil pH, and soil organic carbon. The competitive use between residue retention and yield in mixed crop/livestock systems in developing nations can be a problem. On the other hand, strategies such as intensification and partial retention, as well as nutrient cycling from manures and alternatives to the current functions of livestock such as a mechanized system or insurance, could reduce the pressure on residues in favor of long-term soil quality and health. Keywords Soil health · Physicochemical attributes · Nutrient cycling · Crop residues
H. Bashir · W. Mohy-Ud-Din · Z. M. Choudary · M. M. Hussain (*) · M. A. Hameed Institute of Soil and Environmental Sciences, University of Agriculture Faisalabad, Faisalabad, Pakistan © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 S. A. Bandh (ed.), Strategizing Agricultural Management for Climate Change Mitigation and Adaptation, https://doi.org/10.1007/978-3-031-32789-6_4
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1 Introduction There has been a fourfold rise in the world population. To feed the ever-increasing number of people, increased agricultural and industrial processes have put further tension on the production of food. In the past years, increased food production has caused serious damage on agricultural soil health and quality (Dias et al., 2015; Kareem et al., 2022). In different regions of Africa, Asia, and Latin America, crop yields have decreased significantly due to the increase of soil degradation (Din et al., 2022; Alewell et al., 2020). According to the Food and Agriculture Organization (FAO), soil health is referred to the capability of the soil to function as a living system and fitness for use refers to the quality of soil (Bünemann et al., 2018). A good soil quality has less deterioration and is thus very productive in agriculture production (Eswaran et al., 2019). Soil health has an impact on soil quality, which is crucial for long-term agricultural output. It is important to remember that soil is a living system, which means it contains organisms that perform a variety of functions such as the recycling of nutrients; controlling pests, weeds, and diseases; maintaining symbiosis with roots; improving soil gaseous exchange; and enhancing soil aggregate formation. Soils with high organic matter content are home to thriving soil organisms, which serve as a reservoir for nutrients and moisture (Table 4.1). Organic amendments must be added to the soil regularly to enhance or maintain its organic matter content, which in turn improves soil health (Hussain et al., 2021c; Urra et al., 2019; Parray et al., 2022; Bandh et al., 2022; Bandh, 2022a, b). Crop residue (the remains of harvesting) is the most readily available biomass. Zhou et al. (2016) claim that crop residues are the biggest source of soil organic matter (SOM). Rice (Oryza sativa L.), sorghum (Sorghum bicolor L.), maize (Zea mays L.), and wheat (Triticum aestivum L.) are among the primary cereal crops that produce considerable volumes of agricultural waste (Aula et al., 2019). In 2010 approximately 217 Mha for wheat, 161 Mha for maize, 154 Mha for rice, and 41 Mha for sorghum were harvested across the world (Zuo et al., 2018). Twenty-five percent of maize and wheat crops are sources of calories for the people living in developing countries, which together account for 40% of all food eaten globally (Wijesinha-Bettoni & Mouillé, 2019). Retaining agricultural waste or incorporating it into the soil improves soil quality in several ways (Farooqi et al., 2021). Although small-scale farmers in underdeveloped countries confront a trade-off in controlling agricultural waste, in certain cases, crop residues can be used as biofuel and animal feed, or they can be grazed in crop fields by livestock. There are several ways farmers use to prepare their fields for sowing one of them is burning off crop waste. The
Table 4.1 Essential plant nutrients in soil Nutrient type Primary nutrients Secondary nutrients Macronutrients
Nutrients Nitrogen, phosphorus, and potassium Calcium, magnesium, and sulfur Boron, chlorine, copper, iron, manganese, molybdenum, nickel, and zinc
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long-term environmental and economic advantages of conserving agricultural wastes need a shift in conventional crop residue management. The rice–wheat cropping system (RWS) is one of the most frequently employed cropping systems in India, with around 90% of the land used in the Indo-Gangetic Plains (IGPs) (Singh & Sidhu, 2014). Combine harvesters have made it possible to mechanically harvest more than 75% of the rice land in the northwestern IGPs. Wheat straw is often used by farmers to feed their livestock. Due to its high silica concentration, rice straw is regarded as a poor feed for livestock, making management of huge biomass considerably difficult. The seed drill used to sow wheat is hampered by a swath of loose rice residues left behind by the combine harvester. Farmers burn agricultural leftovers to prevent these issues (90–140 Mt annually). Rice straw can be disposed of by burning, according to the perspective of farmers. Not only does it save money, but it also serves as an excellent form of pest management (Minas et al., 2020). India’s 0.05% greenhouse gas emissions are attributable to the burning of rice straw, according to a study by Bisen and Rahangdale (2017), whose results showed significant loss of biomass and have a negative impact on soil fauna and flora and also in different soil characteristics (Malla et al., 2022; Bandh et al., 2021, 2023; Mushtaq et al., 2020).
2 Crop Residue Impact on Soil Physiochemical Health Crop residue is returned to the soil in the form of organic matter that undergoes different biological, chemical, and physical processes that all work together to influence soil quality and the cycling of nutrients. Soil organic carbon, soil pH, and cation exchange capacity are all affected by residue management (Hussain et al., 2022); physical qualities, e.g. soil compaction and moisture content; and biological properties, e.g., soil biodiversity and microbial biomass (Farooqi et al., 2022). Because increased crop yields leave more agricultural residue after harvest, crop yield findings can be provided in this study because of their contribution to the postharvest residue of crops (Fig. 4.1).
2.1 Structure of Soil The resilience of a system based on crop production, soil erosion, and degradation is strongly influenced by the structure of the soil. Rainfall, tillage, mechanization, and residue management all have an impact on the physical stability of soil organic matter and soil structure (Sithole et al., 2016; Turmel et al., 2015). Soil structure can be improved by crop residues in many ways: by boosting soil aggregation via the organic matter added to topsoil and by avoiding the soil compaction due to raindrops (Almendro-Candel et al., 2018). The structural stability of soil can be calculated by looking at how long soil aggregates can hold together under pressure. The
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Fig. 4.1 Simplified model of plant residue inputs transformed by soil microorganisms. (Reprinted with permission from Turmel et al. (2015))
stability of soil aggregates affects soil porosity, water, gas, nutrient flow in the soil system, and root growth (Almendro-Candel et al., 2018). To keep soil organic matter from decomposing, soil aggregates can create organo-mineral complexes that are incomprehensible to microorganisms (Havlicek & Mitchell, 2014). There are several reasons why soil aggregates are important, but the loss of soil organic matter (SOM) is a major concern, especially in agricultural soils in specific surroundings where SOM is widespread. In mountainous terrains, intense rainfall, and extensively eroded soils, agricultural residues can play an essential role in stabilizing topsoil aggregates. In a 6-year field experiment on sandy loam soil, Bhattacharyya et al. (2012) compared various tillage strategies with the crop remains integrated or left on the topsoil in a lentil-finger millet cycle (Lens esculentus L.–Eleusine coracana L.): no-tillage (NT) and one no-tillage on seasonal basis; conventional tillage (NT–CT) treatments, where residues of the crops were left on the soil surface and had higher water-stable macroaggregates in the surface soil layer (0–5 cm) than year-round conventional tillage (CT–CT); and one-seasonal conventional tiling (CT–NT) treatments, where residues were incorporated. In the NT–CT and NT treatments, higher soil organic carbon (SOC) concentrations were due to the soil compaction. Due to larger crop residual biomass on the surface, the absorption and breakdown of biomass in the absence of tillage resulted in delayed formation of SOC in the surface soil layer, resulting in a more stable aggregate and
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SOC buildup (Prasad et al., 2016). As long as residue remains on the soil surface, NT and seasonal NT–CT techniques are effective for aggregate stability and preserving soil organic carbon in soils that are prone to soil erosion (Bhattacharyya et al., 2012). Better soil aggregate stability was observed when plants retained their residues on the soil surface (Turmel et al., 2015). This might be due to an increase in microbial activity and adhesive agent production caused by organic N from the residues. No-till systems are better at keeping residues on the surface than absorbing them, which can raise soil temperature and lead to increased mineralization of residues (Vanhie et al., 2015). Tillage has the potential to be a more critical element than residue addition in driving aggregate formation. Central China is famous for rice cultivation having clay-loam soil, and also famous for no-tillage practices, it was found that in surface soils under continuous NT, with or without, the crop residues of rape–rice rotation had significantly higher proportions of water-stable aggregates and particulate organic C than in single or continuous CT without residue. When organic materials remained undisturbed, even in the NT, it helped to promote macroaggregate formation and residue retention (Li et al., 2012). Soil aggregate stability has been increased due to the residue retention on topsoil; however, findings in subsoils under tillage regimes with and without residue retention have proven contradictory (Hameed et al., 2021b). No-tillage with or without residue reduced macroaggregate proportions from the 5 to 30 cm layer, but in conventional ways of tilling, the treatments without crop residue increased macroaggregate fractions from 5 to 15 cm to the 5 to 30 cm layer under NT (Bhattacharyya et al., 2012). Chen et al. (2017) reported that there is a rise in the percentage of macroaggregates in the soil plow layer, while others have found no major variations in the subsurface soil layer when using reduced tillage processes (Bhattacharyya et al., 2012). Because external inputs (seed, fertilizer, and pesticides) are applied to this horizon, macroaggregate proportions can vary from soil to soil, but it is apparent that for the better production of the crop, the soil surface layer is very important (Hussain et al., 2021a). Surface organic matter has an important function in safeguarding topsoil aggregates, for the preservation of soil erosion, permitting water penetration, and nutrient retention since it is the soil layer that is more prone to rain and connects the atmosphere to the soil (Menta, 2012). Soil aggregates are protected from raindrop impact by the preservation of surface residue. Dissipating rainfall’s influence and keeping soil aggregates intact are two of the most essential functions of residue cover (Turmel et al., 2015). Irrigation water is becoming limited in the Yaqui Valley in Sonora, Mexico, where surface debris is fed to livestock or tilled into the soil. A study by Verhulst et al. (2011a) found that the soil aggregate stability of the 0–5 cm layer was less in traditionally raised beds and more in permanent raised beds because of the protection provided by the surface residue from raindrop impact. Furthermore, the soil is protected from compaction by leaving residues on the surface. Water infiltration in soil, air movement, and soil porosity are all negatively affected by the compaction of the soil. When soil is compacted, nitrogen availability and crop development can be negatively affected, as well as loss of nutrients via surface runoff (Kaur et al., 2020). Residue management practices, equipment usage,
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experimental plan, and soil texture all influence the impact of agricultural residue on soil compaction (Celik et al., 2017). The compaction of surface soil can rise dramatically over many years of continual NT if no residue is left behind. Runoff and erosion can occur as a result of compaction because of the seal-over and crusting. Soils with zero tillage and burned crop waste showed the greatest penetration resistance in northwest Mexico (Verhulst et al., 2011b). It was shown that infiltration rates under NT were greater when residue was retained on the surface without residue retention as compared to NT. Turmel et al. (2015) demonstrated that surface residue can help prevent soil compaction’s harmful impacts. Under mechanical no-till, in clayey soils, compaction of soil can be a prominent problem. There are subsoils containing gravel and clay with low organic matter content and a potential to crust on the top of alfisols in many locations of Africa where crops like sorghum and maize are produced, making alfisols susceptible to compaction. No-till and residue retention have been proven to be effective methods of minimizing soil compaction in Africa’s humid and subhumid areas (Somasundaram et al., 2020). Penetration resistance and bulk density were reduced in no-till with mulch in tropical alfisol in Ibadan, Nigeria, for example, as compared to no-till without mulch (Fasinmirin & Reichert, 2011). Soil residue retention is critical in no-tillage systems for reducing soil compaction.
2.2 Impact of Crop Residues on Organic Carbon Crop residues increase soil aggregate stability and water retention and also act as a nutrient reservoir. Researchers consider soil organic matter as a good indicator for soil quality and agricultural stability (Wander et al., 2019). Carbon (C) is emitted as CO2 as a result of soil heterotrophic and autotrophic respiration. Although the use of land changes with the passage of time, the disposal of crop residues and digestion process in animal produce more CO2 as compared to human activities (Ali et al., 2019). Different techniques in agriculture disrupt the soil organic carbon pool, which is a significant source of greenhouse gas; carbon losses in soil decrease pressure on long-term crop yield, food security, and soil quality. Agricultural practices can either increase inputs of organic matter or can also delay the rate of breakdown of cellulose to maintain SOC levels (Mitchell et al., 2018). Soil organic matter (SOM) can be categorized in two ways: humus pool and labile pool, both influencing nutrient availability and carbon storage. Humus is resistant to degradation, whereas labile pool is easily degradable by soil microorganisms, resulting in more carbon storage in the soil. The physical and chemical stabilization of this pool ensures its long-term stability (Dheri & Nazir, 2021). Decomposition of crop residue is an important step in the process of humus formation, which results in carbon storage. Retention of crop residues is critical for raising and/or sustaining levels of SOC, although soil type, climate, and management techniques can influence its impact (Turmel et al., 2015). The conservation of mulch ripping residue, as opposed to
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clean ripping with residue eliminated, resulted in increased soil organic carbon in sandy soils in Zimbabwe (Nyakudya & Stroosnijder, 2015). No major changes in soil organic carbon were observed in sandy soil and red clay soil. In addition to influencing breakdown rates, climatic conditions can have an impact on the quantity of SOC that can accumulate with residue remaining on the surface rather than being incorporated. Turmel et al. (2015) found that rain-fed maize cultivation in Apatzingán and Casas Blancas, Mexico, resulted in organic C sequestration for 6 years. Soil organic carbon content in Casas Blancas and Apatzingán was found to be higher with four treatments including minimum tillage, NT with 33% crop residues, 66% crop residues, and 100% crop residues by comparing conservational tillage treatment having disk plowing and disking with 0% crop residue NT. Surface decomposition of crop residue under no-tillage is anticipated to be slower than in normal tillage when they are mixed with soil and come in contact with soil microorganisms (Wang et al., 2020). Soil organic carbon and total nitrogen (N) were greatest when residue was left on the surface rather than incorporated under minimum tillage in Varanasi, India (Turmel et al., 2015). The retention of crop residues in the soil profile can also be influenced by management practices such as surface retention of crop residues or tillage incorporation. Conventional tillage is often blamed for increased decomposition rates, which result in C losses (West & Six, 2007). When soil structure is disturbed and organic matter is redistributed, tillage releases carbon due to surface microbial activity (Sapkota, 2012). This approach, cultivating agricultural soils, has resulted in a 30–50% decrease in pre-cultivation SOC (Bruun et al., 2015). Hijbeek et al. (2017) stated in their meta-analysis of soil carbon case studies quite conflicting results. There was no significant change in soil C stock between zero tillage and conventional tillage in 7 out of the 78 research studies. Understanding decomposition and SOM stabilization is essential for determining the fate of carbon and nutrients via crop waste and other soil amendments, delivered to the soil when selecting appropriate management techniques (Navarro-Pedreño et al., 2021). No-tillage with residue retention has shown a greater SOC content. However, this concentrates C on the soil surface (Luo et al., 2020). According to Zhang et al. (2018), soil tillage affects SOC distribution by integrating residues into the soil and therefore raising SOC in deeper layers. All SOC can be kept in a single layer of soil when the whole soil profile is examined (Powlson et al., 2011). The SOC content was highest in the 0–5 cm soil layer without surface residue for conventional tillage, with incorporated chopped surface residue rotary tillage, and with standing residue for no-tillage in the Northern China Plain silt loam soils (Mert et al., 2018). However, up to 30 cm SOC content decreased with depth. The 5–10 cm deep soil layer had the greatest SOC concentration under conventional tillage with residue treatment. Even while moldboard plowing is often demonstrated to reduce C stocks, conventional tillage with residue treatment increased significantly in this research, illustrating once again the varying influence on SOC induced by crop residue management strategies. Therefore, shallow sampling does not favor no-till methods such as residue retention and provides more accuracy in the evaluation of the effective management strategies of residues on soil organic carbon, sampling the whole
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plow depth (Yang et al., 2013). In addition, when comparing residue surface retention and incorporation outcomes, various parameters (e.g. soil, time, experiment, environment) should be considered (Powlson et al., 2011). There is no doubt that no-till in conservation agriculture with surface residue has its advantages, but it is unclear whether they are better at carbon sequestration than the incorporation of residues or tillage, and soil sampling methods can give better results compared with the direct effect of soil organic carbon storage (Valkama et al., 2020). Experimental studies in temperate areas account for the bulk of the data, and knowledge on this topic is especially scarce in tropic and subtropic regions (Deryng et al., 2014).
2.3 Percentage of Different Bioavailable Micro- and Macronutrients Nitrogen availability can be affected by the addition of agricultural wastes. Nitrogen (N) mineralization may occur when the crop residue of legume having a low C/N ratio is added, but during the breakdown with a high C/N ratio, legume residues partially immobilize N. Increase of soil moisture content and improper fertilizer incorporation and larger denitrification losses may occur from chemical N fertilizers when the crop residues remain on the soil surface (Walsh & Belmont, 2015). There is evidence that retaining residue in the topsoil increases the content of phosphorus (P). There may be movement of phosphorus from lower layers in the soil (Iqbal et al., 2011). The heavily weathered soils and the addition of residues can have an indirect effect on phosphorus availability. Humic compounds and aliphatic acids with low molecular weight generated can block Al oxide adsorption sites during the degradation of agricultural wastes and minimize P adsorption (Johan et al., 2021; Qadir et al., 2021). In general, legumes are more effective because of their higher decomposition rates; this impact depends on the quality of the residue (Abera et al., 2012).
2.4 Crop Residue Effect on Soil pH Soil pH can be affected by crop residue retention because of the relationship between crop residue, chemical composition, and soil characteristics (Turmel et al., 2015). The concentration of nitrogen and alkaline ash in legume crop residues is more likely to affect pH than in wheat crop residues (Butterly et al., 2013). The impact of residue incorporation on soil’s initial pH can be affected due to different soil characteristics including temperature, moisture, and soil organic carbon availability that can pace the residual decomposition (Lehman et al., 2015). The anionic concentration in organic form and the N content in crop residues are connected with changes in pH as a result of crop residue addition (Turmel et al., 2015). Organic anionic
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decomposition consumes H+ ions as a result of soil pH changes; H+ ion is associated with organic ions if the initial soil pH is lower than the pKa value of a weak acid group of organic carbon and vice versa (Adusei-Gyamfi et al., 2019). The ammonification and nitrification process both release and consume H+ throughout the nitrogen mineralization process, resulting in pH shifts in the soil. The overall effect is acidifying due to a state of disequilibrium in the nitrogen cycle. Final soil pH is determined by the reaction balance (Heil et al., 2016). Incorporation vs. surface retention of residue can have an impact on pH in the topsoil layer, although this remains a matter of debate. With the incorporation of crop residues of maize and wheat in topsoil in central Mexico for 5 years, the surface pH was 7.0 and without residues 6.6 and 6.7 when residues are incorporated with tillage (Dendooven et al., 2012). However, results were not significant for subsoils with depths of 5–20 cm. Sombrero and De Benito (2010) observed the comparison between chisel plow minimal tillage and conservation tillage and no-tillage with incorporated residue and para low zone tillage in central Spain. The first two operations lowered the pH than the second two operations. When maize residues were integrated into the soil, Turmel et al. (2015) found a decrease in pH in both treatments. The pH in the 0–10 cm layer was initially 6.7 but declined in the first 3 years of the experimental studies before stabilizing at 5.6 when residues were maintained on the surface and 5.4 when they were integrated into the soil.
3 The Activity of Soil Microbes Soil microbes decompose the organic material that affects soil structure and water and nutrient availability in agroecosystems. The living part of soil organic matter is termed soil microbial biomass (SMB) (Naveen Kumar & Babalad, 2018). Soil quality can be improved and considered a sensitive and valuable indicator due to its role as a source and reservoir of biologically accessible nutrients and as a catalyst for soil aggregation and structure formation (Huera-Lucero et al., 2020). Temperature and moisture in the environment, as well as soil management methods such as residue inputs, can alter SMB (Tiwari et al., 2019). Residue retention stimulates the microbial activity and SMB. Zhang et al. (2016) found that when straw was retained rather than removed, microbial biomass C levels were significantly higher because of increased soil porosity, soil moisture, and decreased temperature of soil due to the residue cover in North China. Soil microbial biomass levels were shown to be greater in experiments conducted in central Mexico when residue was incorporated as opposed to when residue was removed (Verhulst et al., 2011b). Adding of crop residues to the soil warms it and aerates it more quickly, which benefits microorganisms and speeds up decomposition. This results in a larger loss of soil organic carbon (SOC) over time (Thangarajan et al., 2013; Victoria et al., 2012). Experimental studies showed that changes in agricultural residual supply altered the biomass of microorganisms, which is consistent with this finding (Feng et al., 2022; Li et al., 2018). Soil organic carbon has been increased due to the
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incorporation of crop residues and no-till with high temperatures and rainfall, compared to the incorporation of SOC (Chowdhury et al., 2015). Less interaction occurs between soil microorganisms and crops residing on the surface than in humid temperate or humid tropical climates where breakdown rates are high, suggesting the importance of residue preservation on the soil surface rather than incorporating them into the soil. Arbuscular mycorrhizal fungi (AMF) are an example of a fungus that can enhance plant nutrient availability. Symbiotic connections exist between AMF and plant roots, with the AMF obtaining nutrients from the plant and the plant roots receiving phosphate through hyphae (Basu et al., 2018). Additionally, soil particles get aid from the glycoprotein and AMF hyphae for the bonding that results in improving the stability of the aggregates (Bronick & Lal, 2005; Li et al., 2022). Development of mycorrhiza hyphae is adversely affected by tillage practices, and the organic matter addition to soil has been shown to increase AMF growth and spore production (Wei et al., 2019).
4 The Activity of Earthworms Macrofauna, such as earthworms, play a significant role in the soil ecosystem as well. Soil ecosystems can benefit from the long-term benefits of earthworms, which are referred to as ecosystem engineers (Bender et al., 2016). Their biomass directly affects C and N cycles by taking in and storing nutrients, as well as releasing considerable quantities of N via excretion (Mischler et al., 2016). Incorporation of organic matter into the soil affects aggregate stability and C and N cycles through their digestive tracts as well as their middens, casts, and burrows. These stimulate microbial processes like breakdown and mineralization by bringing microorganisms into direct contact with organic materials (Paterson & Sim, 2013). Retention of crop residues and little soil disturbance have been shown to encourage earthworm behavior. Surface crop residues that are left behind after harvest provide food supply and lower the soil temperature, all of which can contribute to an increase in the biomass of earthworms and their populations (Abail & Whalen, 2018). On the other hand, tillage has been demonstrated to have a detrimental effect on several species of earthworms because it destroys their burrows, giving them physical injury and exposing them to the surface for the predator (Briones & Schmidt, 2017). Soil invertebrates, particularly earthworms, show an increase in their population and variety in Tunisia (semiarid region) owing to the improvement of soil characteristics and the absence of disturbance. Tillage can assist endogeic (horizontal-burrowing) earthworms, providing a food supply, if the residue is integrated into the soil, as residue retention can have a varied influence on earthworms (Turmel et al., 2015). The incorporation of residue rather than spreading it on the soil surface might limit their population even with shallow tillage in areas with high populations of anecic (vertical burrowing) earthworms because they remain on the surface and used as a food source (Bertrand et al., 2015).
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Bertrand et al. (2015) also discovered an earthworm population connection between crop and tillage. Under crop field earthworm numbers were low in conventional and reduced tillage treatments, but earthworm numbers were high in all treatments under the grass–clover cycle. Crop residue impact on soil fauna and earthworms might depend upon the plowing depth, incorporation of residues, type of crop residue, quality of residue, frequency of plowing, and crop residue type (Mirzaei et al., 2021; Younas et al., 2021).
5 Methods for Crop Residue Management India’s rice–wheat farming system creates an enormous quantity of agricultural waste, as one would expect. In northwest India, combine harvesters are used to harvest rice–wheat crops, which leave residues. Cattles are the primary consumers of cereal crop residues. Domestic stoves and rice parboiling boilers use rice straw and husk as a fuel. It is more difficult to manage rice straw than wheat straw because of the shorter turnaround time of wheat–rice crops, the lack of appropriate recycling technology, and rice straw’s higher silica content. Incorporation of biochar, baling, mulching, and removing the straw are the management operations available to farmers for profitably managing crop residues. Straw management practices vary depending on the situation.
5.1 Animal Feed from Crop Residues In India, the traditional use of crop waste is to feed it to animals and supplement it with various additives. It is not possible to use crop wastes as a single feed for cattle because of their poor digestion. Rice straw is considered poor feed for animals due to its high silica content. It has low lignin content than other crop straws. It is possible to increase the nutritional content of rice straw by several approaches. Crop residues’ lignocellulose linkages have been weakened and broken down by physical, chemical, and biological treatments (Ginni et al., 2021). As food for livestock, wheat straw is mostly shred into small pieces with a cutting machine. However, this process demands extra time and resources. Because rice straw stems have a lower silica content than leaves, cutting the rice crop as close to the ground as possible improves the digestibility of the straw for livestock. Urea and molasses can be added to the residues, and green fodders including leguminous and nonleguminous crops can be used to meet the nutritional needs of animal feed.
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5.2 Biofuels from Crop Residues Reduced reliance on fossil fuels via the use of biofuels is unquestionably an essential option. This process is critical because ethanol can be used as a fuel extender and octane-enhancing agent in gasoline, or it can be used as a clean fuel in internal combustion engines. Different feedstock (corn cob, rice straw, wheat straw, bagasse, and sawdust) have theoretical ethanol production estimates ranging from 382 to 471 liters per ton of dry matter. Ethanol production from agricultural waste is becoming more and more sophisticated in India. The conversion of crop residues to alcohol has a few limiting steps that need to be improved (Hameed et al., 2021a; Hussain et al., 2021b).
5.3 Biochar from Crop Residues As a realistic technique for sustaining soil health, biochar from crop residues has gained a lot of attention in the few past years. Slow pyrolysis (heating without oxygen) of biomass produces fine-grained charcoal with a high carbon content known as biochar. It has the capacity to store carbon in soil over the long term. Biochar made up to plant biomass is resistant to decomposition by soil microorganisms when it is applied to the soil (Heikkinen et al., 2021; Hussain et al., 2022). Biochar improves water quality via its ability to absorb impurities and minimize greenhouse gases in agricultural areas. It is important to keep in mind that the characteristics of biochar might change depending on the biomass used and the pyrolysis conditions used.
5.4 Incorporation of Crop Residues With the incorporation of crop residues into the soil instead of removing or burning agricultural waste, straw integration enhances soil organic matter, as well as the concentrations of nutrients N, P, and K in soil. Ball et al. (1990) and Christian and Bacon (1991) found that plowing is the most efficient method of incorporating residues into the soil (Farid Eltom et al., 2015). Remaining crop leftovers might be absorbed into the soil partly or entirely depending on the manner of cultivation. It is more difficult to incorporate rice residues into the soil before wheat planting than to incorporate wheat straw into the soil before rice planting. Adding crop residues to the field is a good way of nutrient recycling, but it also immobilizes the soil nutrients temporarily (such as nitrogen), which causes the additional burden of nitrogenous fertilizer use to adjust the high C/N ratio (Turmel et al., 2015). The short-term immobilization of available soil and fertilizer nitrogen by decomposer microbial activity is the source of this
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N deficiency. The length of time depends on the decomposition rate of crop waste, as well as the crop residue quality and the soil environment (Grzyb et al., 2020). Similarly, Upadhyay et al. (2012) stated that in 10, 20, and 40 days of wheat planting, no negative impact was observed on wheat and subsequent rice grain yields from in situ incorporations of rice straw in soil. Addition of rice straw to the wheat crop did not even have any influence on the next year’s rice harvest.
5.5 Surface Mulching from Crop Residues Evaporation of water can be minimized by retaining soil residues on the earth’s surface and is a better option for soil conservation. Soil microbial populations are increased, which in turn improves soil health by increasing organic carbon. Soil health directly affects wheat production (Turmel et al., 2015). Zero-till wheat has been implemented in the rice–wheat system in the northwest IGP. For this, an advanced seed drill has been developed. Sidhu et al. (2007) reported that in conservation agriculture any kind of residue can be used with the Happy Seeder as long as it is spread out evenly before drilling. Wheat grain production was up to 31% higher with rice straw mulch, crop water usage was reduced to 31%, and water use efficiency was up to 25% higher than it would have been without it. The density of root length in lower levels of >0.15 m was 40% higher when mulch was used compared to nomulch, which can be attributable to the increased soil moisture retention in lower layers (Singh & Sidhu, 2014).
6 Conclusions Crop residue significantly increased the quality of soil in Asia, Latin America, and Africa. Surface residue retention typically improves soil health qualities physically, chemically, and biologically, but it has been shown to have detrimental impacts on crop production in specific conditions. Some studies have shown that retaining residue, whether it is absorbed into the soil or left on the top, is more beneficial than completely removing it or incorporating it into intensive tillage operations. When comparing different residue management approaches, it is crucial to consider abiotic parameters like the texture of the soil, regional climate, research length, sample methodologies, and agricultural activities like weed control as well as surface and residue retention vs. assimilation. There are several advantages to incorporating the crop residue rather than mixing it into the soil, including greater topsoil protection against soil loss, erosion, and surface compaction. Soil erosion and rapid decomposition rates in humid tropical environments necessitate promoting residue retention
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on the surface in these situations. Soil is affected by crop residue and is largely dependent on the quality of residues and parameters of the soil. While the influence on SOC and CEC can only be seen on the soil surface, with the incorporation of residues into the soil, the effect can be seen at a larger depth. Sample methods that compare residue management strategies should take this into account. This results in enhanced microbial activity and faster breakdown rates when residue is left in the ground. In addition to stimulating the earthworm population, residue retention has a corresponding impact on earthworm ecology. Crop residue retention has been shown to have adverse impacts in specific situations; however, these cases are rare. It is the most prevalent negative impact of N mobilization that might lower the supply of N to the crop under N limiting conditions. Strip tillage should also be used in colder areas since surface residues reduce the soil’s temperature, which can severely affect the crop’s output. In areas having significant rainfall, excess soil moisture retention can cause waterlogging. On the other hand, leftovers in semiarid locations with little rainfall can act as rain catchers and so accelerate the rate of evaporation. There is an exchange between the use of crop residue incorporation and animal waste for the purpose of soil quality. Crop leftover can be replaced with noncommercial plants used as mulch, or as much as 30–60% or 50–75% of the crop residue can be left on the soil surface, depending on the region’s soils and temperature. Because improved soil quality and moisture retention increase yields in areas where water is available to crops in limited quantities, retaining crop residue can have a positive feedback effect, increasing crop residue that can be used as animal feed. It is possible to further benefit from soil health by retaining leftovers on the surface, but farmers in open range areas prefer to integrate their residues to keep them from being grazed by their neighbors’ livestock. Acknowledgements Authors want to thank the Higher Education Commission, Pakistan, for awarding fellowship under the International Research Support Initiative Program (IRSIP) Muhammad Mahroz Hussain no. 1-8/HEC/HRD/2020/10831, and also to the Environmental Biogeochemistry Laboratory, University of Agriculture Faisalabad, Pakistan.
References Abail, Z., & Whalen, J. K. (2018). Corn residue inputs influence earthworm population dynamics in a no-till corn-soybean rotation. Applied Soil Ecology, 127, 120–128. https://doi.org/10.1016/j. apsoil.2018.03.013 Abera, G., Wolde-Meskel, E., & Bakken, L. R. (2012). Carbon and nitrogen mineralization dynamics in different soils of the tropics amended with legume residues and contrasting soil moisture contents. Biology and Fertility of Soils, 48(1), 51–66. https://doi.org/10.1007/ s00374-011-0607-8 Adusei-Gyamfi, J., Ouddane, B., Rietveld, L., Cornard, J. P., & Criquet, J. (2019). Natural organic matter-cations complexation and its impact on water treatment: A critical review. Water Research, 160, 130–147. https://doi.org/10.1016/j.watres.2019.05.064
4 Crop Residue Incorporation to Enhance Soil Health in the Rice–Wheat System
61
Alewell, C., Ringeval, B., Ballabio, C., Robinson, D. A., Panagos, P., & Borrelli, P. (2020). Global phosphorus shortage will be aggravated by soil erosion. Nature Communications, 11, 1. Ali, M., Saleem, M., Khan, Z., & Watson, I. A. (2019). The use of crop residues for biofuel production. In Biomass, biopolymer-based materials, and bioenergy (pp. 369–395). Elsevier. Almendro-Candel, M. B., Lucas, I. G., Navarro-Pedreño, J., & Zorpas, A. A. (2018). Physical properties of soils affected by the use of agricultural waste. Agricultural Waste and Residues, 2, 9–27. Aula, L., Dhillon, J. S., Omara, P., Wehmeyer, G. B., Freeman, K. W., & Raun, W. R. (2019). World sulfur use efficiency for cereal crops. Agronomy Journal, 111(5), 2485–2492. https:// doi.org/10.2134/agronj2019.02.0095 Bandh, S. A. (2022a). Climate change: The social and scientific construct (1st ed.). Springer. https://doi.org/10.1007/978-3-030-86290-9 Bandh, S. A. (2022b). Sustainable agriculture: Technological progressions and transitions (1st ed.). Springer. https://doi.org/10.1007/978-3-030-83066-3 Bandh, S. A., Shafi, S., Peerzada, M., Rehman, T., Bashir, S., Wani, S. A., & Dar, R. (2021). Multidimensional analysis of global climate change: A review. Environmental Science and Pollution Research International, 28(20), 24872–24888. https://doi.org/10.1007/ s11356-021-13139-7 Bandh, S. A., Parray, J. A., & Shameem, N. (2022). Climate change and microbial diversity: Advances and challenges (1st ed.). Apple Academic Press. https://www.routledge.com/Climate- Change-a nd-M icrobial-D iversity-A dvances-a nd-C hallenges/Bandh-Parray-S hameem/p/ book/9781774637821 Bandh, S. A., Malla, F. A., Qayoom, I., Mohi-ud-Din, H., Butt, A. K., Altaf, A., Wani, S. A., Betts, R., Truong, T. H., Pham, N. D. K., Cao, D. N., & Ahmed, S. F. (2023). Importance of blue carbon in mitigating climate change and plastic/microplastic pollution and promoting circular economy. Sustainability, 15(3), 2682. https://doi.org/10.3390/su15032682 Basu, S., Rabara, R. C., & Negi, S. (2018). AMF: The future prospect for sustainable agriculture. Physiological and Molecular Plant Pathology, 102, 36–45. https://doi.org/10.1016/j. pmpp.2017.11.007 Bender, S. F., Wagg, C., & van der Heijden, M. G. A. (2016). An underground revolution: Biodiversity and soil ecological engineering for agricultural sustainability. Trends in Ecology and Evolution, 31(6), 440–452. https://doi.org/10.1016/j.tree.2016.02.016 Bertrand, M., Barot, S., Blouin, M., Whalen, J., de Oliveira, T., & Roger-Estrade, J. (2015). Earthworm services for cropping systems. A review. Agronomy for Sustainable Development, 35(2), 553–567. https://doi.org/10.1007/s13593-014-0269-7 Bhattacharyya, R., Tuti, M. D., Kundu, S., Bisht, J. K., & Bhatt, J. C. (2012). Conservation tillage impacts on soil aggregation and carbon pools in a sandy clay loam soil of the Indian Himalayas. Soil Science Society of America Journal, 76(2), 617–627. https://doi.org/10.2136/ sssaj2011.0320 Bisen, N., & Rahangdale, C. (2017). Crop residues management option for sustainable soil health in rice-wheat system: A review. International Journal of Chemical Studies, 5, 1038–1042. Briones, M. J. I., & Schmidt, O. (2017). Conventional tillage decreases the abundance and biomass of earthworms and alters their community structure in a global meta-analysis. Global Change Biology, 23(10), 4396–4419. https://doi.org/10.1111/gcb.13744 Bronick, C. J., & Lal, R. (2005). Soil structure and management: A review. Geoderma, 124(1–2), 3–22. https://doi.org/10.1016/j.geoderma.2004.03.005 Bruun, T. B., Elberling, B., de Neergaard, A., & Magid, J. (2015). Organic carbon dynamics in different soil types after conversion of forest to agriculture. Land Degradation and Development, 26(3), 272–283. https://doi.org/10.1002/ldr.2205 Bünemann, E. K., Bongiorno, G., Bai, Z., Creamer, R. E., De Deyn, G., de Goede, R., Fleskens, L., Geissen, V., Kuyper, T. W., Mäder, P., Pulleman, M., Sukkel, W., van Groenigen, J. W., & Brussaard, L. (2018). Soil quality–A critical review. Soil Biology and Biochemistry, 120, 105–125. https://doi.org/10.1016/j.soilbio.2018.01.030
62
H. Bashir et al.
Butterly, C. R., Baldock, J. A., & Tang, C. (2013). The contribution of crop residues to changes in soil pH under field conditions. Plant and Soil, 366(1–2), 185–198. https://doi.org/10.1007/ s11104-012-1422-1 Celik, I., Günal, H., Acar, M., Gök, M., Bereket Barut, Z., & Pamiralan, H. (2017). Long-term tillage and residue management effect on soil compaction and nitrate leaching in a Typic Haploxerert soil. International Journal of Plant Production, 11, 131–149. Chen, Z., Ti, J.-s., & Chen, F. (2017). Soil aggregates response to tillage and residue management in a double paddy rice soil of the Southern China. Nutrient Cycling in Agroecosystems, 109(2), 103–114. https://doi.org/10.1007/s10705-017-9864-8 Chowdhury, S., Farrell, M., Butler, G., & Bolan, N. (2015). Assessing the effect of crop residue removal on soil organic carbon storage and microbial activity in a no-till cropping system. Soil Use and Management, 31(4), 450–460. https://doi.org/10.1111/sum.12215 Dendooven, L., Patiño-Zúñiga, L., Verhulst, N., Luna-Guido, M., Marsch, R., & Govaerts, B. (2012). Global warming potential of agricultural systems with contrasting tillage and residue management in the central highlands of Mexico. Agriculture, Ecosystems and Environment, 152, 50–58. https://doi.org/10.1016/j.agee.2012.02.010 Deryng, D., Conway, D., Ramankutty, N., Price, J., & Warren, R. (2014). Global crop yield response to extreme heat stress under multiple climate change futures. Environmental Research Letters, 9(3), 034011. https://doi.org/10.1088/1748-9326/9/3/034011 Dheri, G. S., & Nazir, G. (2021). A review on carbon pools and sequestration as influenced by long-term management practices in a rice–wheat cropping system. Carbon Management, 12(5), 559–580. https://doi.org/10.1080/17583004.2021.1976674 Dias, T., Dukes, A., & Antunes, P. M. (2015). Accounting for soil biotic effects on soil health and crop productivity in the design of crop rotations. Journal of the Science of Food and Agriculture, 95(3), 447–454. https://doi.org/10.1002/jsfa.6565 Din, W. M. U., Hussain, M. M., & Farooqi, Z. U. R. (2022). Climate change-induced aggravations in microbial populations and processes: Constraints and remediations. In Climate change and microbes (pp. 25–49). Apple Academic Press. Eswaran, H., Lal, R., & Reich, P. (2019). Land degradation: An overview. In Response to land degradation (pp. 20–35). CRC Press. Farid Eltom, A. E., Ding, W., Ding, Q., Tagar, A. A., Talha, Z., & Gamareldawla. (2015). Field investigation of a trash-board, tillage depth and low speed effect on the displacement and burial of straw. CATENA, 133, 385–393. https://doi.org/10.1016/j.catena.2015.05.025 Farooqi, Z. U. R., Hameed, M. A., Mohy-Ud-Din, W., Ali, M. H., Qadir, A., & Hussain, M. M. (2021). Global climate change and microbial ecology: Current scenario and management. In Microbiological activity for soil and plant health management (pp. 285–313). Springer. Farooqi, Z. U. R., Din, W. M. U., & Hussain, M. M. (2022). Microbial responses under climate change scenarios: Adaptation and mitigations. In Climate change and microbial diversity (pp. 1–20). Apple Academic Press. Fasinmirin, J. T., & Reichert, J. M. (2011). Conservation tillage for cassava (Manihot esculenta Crantz) production in the tropics. Soil and Tillage Research, 113(1), 1–10. https://doi. org/10.1016/j.still.2011.01.008 Feng, J., He, K., Zhang, Q., Han, M., & Zhu, B. (2022). Changes in plant inputs alter soil carbon and microbial communities in forest ecosystems. Global Change Biology, 28(10), 3426–3440. https://doi.org/10.1111/gcb.16107 Ginni, G., Kavitha, S., Yukesh Kannah, R., Bhatia, S. K., Adish Kumar, S., Rajkumar, M., Kumar, G., Pugazhendhi, A., Chi, N. T. L., & Rajesh Banu, J. (2021). Valorization of agricultural residues: Different biorefinery routes. Journal of Environmental Chemical Engineering, 9(4), 105435. https://doi.org/10.1016/j.jece.2021.105435 Grzyb, A., Wolna-Maruwka, A., & Niewiadomska, A. (2020). Environmental factors affecting the mineralization of crop residues. Agronomy, 10(12). https://doi.org/10.3390/agronomy10121951
4 Crop Residue Incorporation to Enhance Soil Health in the Rice–Wheat System
63
Hameed, M. A., Farooqi, Z. U. R., Hussain, M. M., & Ayub, M. A. (2021a). PGPR-assisted bioremediation and plant growth: A sustainable approach for crop production using polluted soils. In Plant growth regulators: Signalling under stress conditions (p. 403). Springer. Hameed, M. A., Farooqi, Z. U. R., Younas, F., Din, W. M. U., Hussain, M. M., & Khilji, S. A. (2021b). Microplastic pollution: Sources, fate, impacts and research gaps. Quality of Life, 20, 39–50. Havlicek, E., & Mitchell, E. A. (2014). Soils supporting biodiversity. In Interactions in soil: Promoting plant growth (pp. 27–58). Springer. Heikkinen, J., Ketoja, E., Seppänen, L., Luostarinen, S., Fritze, H., Pennanen, T., Peltoniemi, K., Velmala, S., Hanajik, P., & Regina, K. (2021). Chemical composition controls the decomposition of organic amendments and influences the microbial community structure in agricultural soils. Carbon Management, 12(4), 359–376. https://doi.org/10.1080/17583004.2021.1947386 Heil, J., Vereecken, H., & Brüggemann, N. (2016). A review of chemical reactions of nitrification intermediates and their role in nitrogen cycling and nitrogen trace gas formation in soil. European Journal of Soil Science, 67(1), 23–39. https://doi.org/10.1111/ejss.12306 Hijbeek, R., van Ittersum, M. K., ten Berge, H. F. M., Gort, G., Spiegel, H., & Whitmore, A. P. (2017). Do organic inputs matter–a meta-analysis of additional yield effects for arable crops in Europe. Plant and Soil, 411(1–2), 293–303. https://doi.org/10.1007/s11104-016-3031-x Huera-Lucero, T., Labrador-Moreno, J., Blanco-Salas, J., & Ruiz-Téllez, T. (2020). A framework to incorporate biological soil quality indicators into assessing the sustainability of territories in the Ecuadorian Amazon. Sustainability, 12(7), 3007. https://doi.org/10.3390/su12073007 Hussain, M., Farooqi, Z., Mohy-Ud-Din, W., Younas, F., Shahzad, M., Ghani, M., Ayub, M., & Qadeer, A. (2021a). Application of Bioremediation as sustainable approach to remediate heavy metal and pesticide polluted environments. Plant and Environment, 1, 62–92. Hussain, M. M., Farooqi, Z. U. R., Latif, J., Mubarak, M. U., & Younas, F. (2021b). Bioremediation: A Green Solution to avoid Pollution of the Environment. In Soil bioremediation: An approach towards sustainable technology (pp. 15–40). Wiley-Blackwell. Hussain, M. M., Farooqi, Z. U. R., Rasheed, F., & Din, W. M. U. (2021c). Role of microorganisms as climate engineers: Mitigation and adaptations to climate change. In Climate change and microbes (pp. 1–24). Apple Academic Press. Hussain, M. M., Mohy-Ud-Din, W., Younas, F., Niazi, N. K., Bibi, I., Yang, X., Rasheed, F., & Farooqi, Z. U. R. (2022). Biochar: A game changer for sustainable agriculture. Journal of Sustainable Agriculture, 143–157. Springer. Iqbal, M., Ul-Hassan, A., & van Es, H. M. (2011). Influence of residue management and tillage systems on carbon sequestration and nitrogen, phosphorus, and potassium dynamics of soil and plant and wheat production in semi-arid region. Communications in Soil Science and Plant Analysis, 42(5), 528–547. https://doi.org/10.1080/00103624.2011.546929 Johan, P. D., Ahmed, O. H., Omar, L., & Hasbullah, N. A. (2021). Phosphorus transformation in soils following co-application of charcoal and wood ash. Agronomy, 11(10). https://doi. org/10.3390/agronomy11102010 Kareem, A., Farooqi, Z. U. R., Kalsom, A., Mohy-Ud-Din, W., Hussain, M. M., Raza, M., & Khursheed, M. M. (2022). Organic farming for sustainable soil use, management, food production and climate change mitigation. Journal of Sustainable Agriculture, 39–59. Springer. Kaur, G., Singh, G., Motavalli, P. P., Nelson, K. A., Orlowski, J. M., & Golden, B. R. (2020). Impacts and management strategies for crop production in waterlogged or flooded soils: A review. Agronomy Journal, 112(3), 1475–1501. https://doi.org/10.1002/agj2.20093 Lehman, R. M., Cambardella, C. A., Stott, D. E., Acosta-Martinez, V., Manter, D. K., Buyer, J. S., Maul, J. E., Smith, J. L., Collins, H. P., Halvorson, J. J., Kremer, R., Lundgren, J., Ducey, T., Jin, V., & Karlen, D. (2015). Understanding and enhancing soil biological health: The solution for reversing soil degradation. Sustainability, 7(1), 988–1027. https://doi.org/10.3390/ su7010988
64
H. Bashir et al.
Li, C.-f., Yue, L.-x., Kou, Z.-k., Zhang, Z.-s., Wang, J.-p., & Cao, C.-g. (2012). Short-term effects of conservation management practices on soil labile organic carbon fractions under a rape– rice rotation in central China. Soil and Tillage Research, 119, 31–37. https://doi.org/10.1016/j. still.2011.12.005 Li, J., Wu, X., Gebremikael, M. T., Wu, H., Cai, D., Wang, B., Li, B., Zhang, J., Li, Y., & Xi, J. (2018). Response of soil organic carbon fractions, microbial community composition and carbon mineralization to high-input fertilizer practices under an intensive agricultural system. PLoS One, 13(4), e0195144. https://doi.org/10.1371/journal.pone.0195144 Li, Y., Xu, J., Hu, J., Zhang, T., Wu, X., & Yang, Y. (2022). Arbuscular mycorrhizal fungi and glomalin play a crucial role in soil aggregate stability in Pb-contaminated soil. International Journal of Environmental Research and Public Health, 19(9), 5029. https://doi.org/10.3390/ ijerph19095029 Luo, Y., Iqbal, A., He, L., Zhao, Q., Wei, S., Ali, I., Ullah, S., Yan, B., & Jiang, L. (2020). Long- term no-tillage and straw retention management enhances soil bacterial community diversity and soil properties in Southern China. Agronomy, 10(9), 1233. https://doi.org/10.3390/ agronomy10091233 Malla, F. A., Mushtaq, A., Bandh, S. A., Qayoom, I., Ho-ang, A. T., & Shahid-e-Murtaza. (2022). Understanding climate change: Scientific opinion and public perspective. In S. A. Bandh (Ed.), Climate change: The social and scientific construct. Springer Nature Publishing. https://link. springer.com/chapter/10.1007/978-3-030-86290-9_1 Menta, C. (2012). Soil fauna diversity-function, soil degradation, biological indices, soil restoration. In Biodiversity conservation and utilization in a diverse world (pp. 59–94). InTech. Mert, A., Celik, I., & Günal, H. (2018). Effects of long-term tillage systems on aggregate- associated organic carbon in the eastern Mediterranean region of Turkey. Eurasian Journal of Soil Science, 7, 51–58. Minas, A. M., Mander, S., & McLachlan, C. (2020). How can we engage farmers in bioenergy development? Building a social innovation strategy for rice straw bioenergy in The Philippines and Vietnam. Energy Research and Social Science, 70, 101717. https://doi.org/10.1016/j. erss.2020.101717 Mirzaei, M., Gorji Anari, M., Razavy-Toosi, E., Asadi, H., Moghiseh, E., Saronjic, N., & Rodrigo- Comino, J. (2021). Preliminary effects of crop residue management on soil quality and crop production under different soil management regimes in corn-wheat rotation systems. Agronomy, 11(2), 302. https://doi.org/10.3390/agronomy11020302 Mischler, J., Johnson, P. T., McKenzie, V. J., & Townsend, A. R. (2016). Parasite infection alters nitrogen cycling at the ecosystem scale. Journal of Animal Ecology, 85(3), 817–828. https:// doi.org/10.1111/1365-2656.12505 Mitchell, E., Scheer, C., Rowlings, D., Conant, R. T., Cotrufo, M. F., & Grace, P. (2018). Amount and incorporation of plant residue inputs modify residue stabilisation dynamics in soil organic matter fractions. Agriculture, Ecosystems and Environment, 256, 82–91. https://doi. org/10.1016/j.agee.2017.12.006 Mushtaq, B., Bandh, S. A., & Shafi, S. (2020). Environmental management: Environmental issues, awareness and abatement (1st ed.). Springer. https://doi.org/10.1007/978-981-15-3813-1 Navarro-Pedreño, J., Almendro-Candel, M. B., & Zorpas, A. A. (2021). The increase of soil organic matter reduces global warming, myth or reality? Sci, 3(1), 18. https://doi.org/10.3390/ sci3010018 Naveen Kumar, B. T., & Babalad, H. B. (2018). Soil organic carbon, carbon sequestration, soil microbial biomass carbon and nitrogen and soil enzymatic activity as influenced by conservation agriculture in pigeonpea and soybean intercropping system. International Journal of Current Microbiology and Applied Sciences, 7(3), 323–333. https://doi.org/10.20546/ ijcmas.2018.703.038
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Nyakudya, I. W., & Stroosnijder, L. (2015). Conservation tillage of rainfed maize in semi-arid Zimbabwe: A review. Soil and Tillage Research, 145, 184–197. https://doi.org/10.1016/j. still.2014.09.003 Parray, J. A., Bandh, S. A., & Shameem, N. (2022). Climate change and microbes: Impact and vulnerability (1st ed.). Apple Academic Press. https://www.routledge.com/ Climate-C hange-a nd-M icrobes-I mpacts-a nd-Vulnerability/Parray-B andh-S hameem/p/ book/9781774637210 Paterson, E., & Sim, A. (2013). Soil-specific response functions of organic matter mineralization to the availability of labile carbon. Global Change Biology, 19(5), 1562–1571. https://doi. org/10.1111/gcb.12140 Powlson, D. S., Whitmore, A. P., & Goulding, K. W. T. (2011). Soil carbon sequestration to mitigate climate change: A critical re-examination to identify the true and the false. European Journal of Soil Science, 62(1), 42–55. https://doi.org/10.1111/j.1365-2389.2010.01342.x Prasad, J. V. N. S., Rao, C. S., Srinivas, K., Jyothi, C. N., Venkateswarlu, B., Ramachandrappa, B. K., Dhanapal, G. N., Ravichandra, K., & Mishra, P. K. (2016). Effect of ten years of reduced tillage and recycling of organic matter on crop yields, soil organic carbon and its fractions in alfisols of semi arid tropics of southern India. Soil and Tillage Research, 156, 131–139. https:// doi.org/10.1016/j.still.2015.10.013 Qadir, A., Hameed, M., Bin Zafar, M., Farooqi, Z., Younas, F., Hussain, M., & Mohy-Ud-Din, W. (2021). Phytoremediation of inorganic pollutants: An eco-friendly approach, its types and mechanisms. Plant and Environment, 1, 110–129. Sapkota, T. B. (2012). Conservation tillage impact on soil aggregation, organic matter turnover and biodiversity. In Organic fertilisation, soil quality and human health (pp. 141–160). Springer. Sidhu, H. S., Manpreet-Singh, Humphreys, E., Yadvinder-Singh, Balwinder-Singh, Dhillon, S. S., Blackwell, J., Bector, V., Malkeet-Singh, & Sarbjeet-Singh. (2007). The happy seeder enables direct drilling of wheat into rice stubble. Australian Journal of Experimental Agriculture, 47(7), 844–854. https://doi.org/10.1071/EA06225 Singh, Y., & Sidhu, H. S. (2014). Management of cereal crop residues for sustainable rice-wheat production system in the Indo-Gangetic plains of India. Proceedings of the Indian National Science Academy, 80(1), 95–114. https://doi.org/10.16943/ptinsa/2014/v80i1/55089 Sithole, N. J., Magwaza, L. S., & Mafongoya, P. L. (2016). Conservation agriculture and its impact on soil quality and maize yield: A South African perspective. Soil and Tillage Research, 162, 55–67. https://doi.org/10.1016/j.still.2016.04.014 Somasundaram, J., Sinha, N. K., Dalal, R. C., Lal, R., Mohanty, M., Naorem, A. K., Hati, K. M., Chaudhary, R. S., Biswas, A. K., Patra, A. K., & Chaudhari, S. K. (2020). No-till farming and conservation agriculture in South Asia–issues, challenges, prospects and benefits. Critical Reviews in Plant Sciences, 39(3), 236–279. https://doi.org/10.1080/07352689.2020.1782069 Sombrero, A., & De Benito, A. (2010). Carbon accumulation in soil. Ten-year study of conservation tillage and crop rotation in a semi-arid area of Castile-Leon, Spain. Soil and Tillage Research, 107(2), 64–70. https://doi.org/10.1016/j.still.2010.02.009 Thangarajan, R., Bolan, N. S., Tian, G., Naidu, R., & Kunhikrishnan, A. (2013). Role of organic amendment application on greenhouse gas emission from soil. Science of the Total Environment, 465, 72–96. https://doi.org/10.1016/j.scitotenv.2013.01.031 Tiwari, S., Singh, C., Boudh, S., Rai, P. K., Gupta, V. K., & Singh, J. S. (2019). Land use change: A key ecological disturbance declines soil microbial biomass in dry tropical uplands. Journal of Environmental Management, 242, 1–10. https://doi.org/10.1016/j.jenvman.2019.04.052 Turmel, M.-S., Speratti, A., Baudron, F., Verhulst, N., & Govaerts, B. (2015). Crop residue management and soil health: A systems analysis. Agricultural Systems, 134, 6–16. https://doi. org/10.1016/j.agsy.2014.05.009 Upadhyay, S. K., Singh, J. S., Saxena, A. K., & Singh, D. P. (2012). Impact of PGPR inoculation on growth and antioxidant status of wheat under saline conditions. Plant Biology, 14(4), 605–611. https://doi.org/10.1111/j.1438-8677.2011.00533.x
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H. Bashir et al.
Urra, J., Alkorta, I., & Garbisu, C. (2019). Potential benefits and risks for soil health derived from the use of organic amendments in agriculture. Agronomy, 9(9), 542. https://doi.org/10.3390/ agronomy9090542 Valkama, E., Kunypiyaeva, G., Zhapayev, R., Karabayev, M., Zhusupbekov, E., Perego, A., Schillaci, C., Sacco, D., Moretti, B., Grignani, C., & Acutis, M. (2020). Can conservation agriculture increase soil carbon sequestration? A modelling approach. Geoderma, 369, 114298. https://doi.org/10.1016/j.geoderma.2020.114298 Vanhie, M., Deen, W., Lauzon, J. D., & Hooker, D. C. (2015). Effect of increasing levels of maize (Zea mays L.) residue on no-till soybean (Glycine max Merr.) in Northern production regions: A review. Soil and Tillage Research, 150, 201–210. https://doi.org/10.1016/j.still.2015.01.011 Verhulst, N., Carrillo-García, A., Moeller, C., Trethowan, R., Sayre, K. D., & Govaerts, B. (2011a). Conservation agriculture for wheat-based cropping systems under gravity irrigation: Increasing resilience through improved soil quality. Plant and Soil, 340(1–2), 467–479. https://doi. org/10.1007/s11104-010-0620-y Verhulst, N., Kienle, F., Sayre, K. D., Deckers, J., Raes, D., Limon-Ortega, A., Tijerina-Chavez, L., & Govaerts, B. (2011b). Soil quality as affected by tillage-residue management in a wheat-maize irrigated bed planting system. Plant and Soil, 340(1–2), 453–466. https://doi. org/10.1007/s11104-010-0618-5 Victoria, R., Banwart, S., Black, H., Ingram, J., Joosten, H., Milne, E., Noellemeyer, E., & Baskin, Y. (2012). The benefits of soil carbon. Foresight chapter in UNEP [Yearbook], 2012 (pp. 19–33). Walsh, O. S., & Belmont, K. M. (2015). Improving nitrogen-use efficiency in Idaho crop production. University of Idaho Extension. Wander, M. M., Cihacek, L. J., Coyne, M., Drijber, R. A., Grossman, J. M., Gutknecht, J. L. M., Horwath, W. R., Jagadamma, S., Olk, D. C., Ruark, M., Snapp, S. S., Tiemann, L. K., Weil, R., & Turco, R. F. (2019). Developments in agricultural soil quality and health: Reflections by the research committee on soil organic matter management. Frontiers in Environmental Science, 7, 109. https://doi.org/10.3389/fenvs.2019.00109 Wang, H., Wang, S., Yu, Q., Zhang, Y., Wang, R., Li, J., & Wang, X. (2020). No tillage increases soil organic carbon storage and decreases carbon dioxide emission in the crop residue- returned farming system. Journal of Environmental Management, 261, 110261. https://doi. org/10.1016/j.jenvman.2020.110261 Wei, L., Vosátka, M., Cai, B., Ding, J., Lu, C., Xu, J., Yan, W., Li, Y., & Liu, C. (2019). The role of arbuscular mycorrhiza fungi in the decomposition of fresh residue and soil organic carbon: A mini-review. Soil Science Society of America Journal, 83(3), 511–517. https://doi.org/10.2136/ sssaj2018.05.0205 West, T. O., & Six, J. (2007). Considering the influence of sequestration duration and carbon saturation on estimates of soil carbon capacity. Climatic Change, 80(1–2), 25–41. https://doi. org/10.1007/s10584-006-9173-8 Wijesinha-Bettoni, R., & Mouillé, B. (2019). The contribution of potatoes to global food security, nutrition and healthy diets. American Journal of Potato Research, 96(2), 139–149. https://doi. org/10.1007/s12230-018-09697-1 Yang, X., Drury, C. F., & Wander, M. M. (2013). A wide view of no-tillage practices and soil organic carbon sequestration. Acta Agriculturae Scandinavica, Section B – Soil and Plant Science, 63(6), 523–530. https://doi.org/10.1080/09064710.2013.816363 Younas, F., Mustafa, A., Farooqi, Z. U. R., Wang, X., Younas, S., Mohy-Ud-Din, W., Ashir Hameed, M., Mohsin Abrar, M., Maitlo, A. A., Noreen, S., & Hussain, M. M. (2021). Current and emerging adsorbent technologies for wastewater treatment: Trends, limitations, and environmental implications. Water, 13(2), 215. https://doi.org/10.3390/w13020215 Zhang, H., Zhang, Y., Yan, C., Liu, E., & Chen, B. (2016). Soil nitrogen and its fractions between long-term conventional and no-tillage systems with straw retention in dryland farming in northern China. Geoderma, 269, 138–144. https://doi.org/10.1016/j.geoderma.2016.02.001
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Zhang, Y., Li, X., Gregorich, E. G., McLaughlin, N. B., Zhang, X., Guo, Y., Liang, A., Fan, R., & Sun, B. (2018). No-tillage with continuous maize cropping enhances soil aggregation and organic carbon storage in Northeast China. Geoderma, 330, 204–211. https://doi.org/10.1016/j. geoderma.2018.05.037 Zhou, X., Wu, H., Li, G., & Chen, C. (2016). Short-term contributions of cover crop surface residue return to soil carbon and nitrogen contents in temperate Australia. Environmental Science and Pollution Research International, 23(22), 23175–23183. https://doi.org/10.1007/ s11356-016-7549-5 Zuo, L., Zhang, Z., Carlson, K. M., MacDonald, G. K., Brauman, K. A., Liu, Y., Zhang, W., Zhang, H., Wu, W., Zhao, X., Wang, X., Liu, B., Yi, L., Wen, Q., Liu, F., Xu, J., Hu, S., Sun, F., Gerber, J. S., & West, P. C. (2018). Progress towards sustainable intensification in China challenged by land-use change. Nature Sustainability, 1(6), 304–313. https://doi.org/10.1038/ s41893-018-0076-2
Chapter 5
Promoting Energy Crops to Replace Fossil Fuel Use Muhammad Irfan, Liu Xianhua, Asia Shauket, Muhammad Jafir, Adeel Ahmad, Samina Jam Nazeer Ahmad, and Jam Nazeer Ahmad
Abstract Biomass energy development is a critical component in resolving the energy issue and mitigating the effects of global warming. Renewable energy sources such as biomass can be described as carbon neutral, as they emit only carbon that has been trapped in the plant growth cycle. Biofuel is the only liquid fuel that can be used as an alternative to fossil fuels for transportation. Biofuels have the potential to address future global energy demand. Energy crops referred to as energy farming is another option for agriculture on agricultural lands. In terms of cost and environmental benefits, energy crops for biofuel generation have been studied extensively. Energy is now obtained from commodities including seed crops and some C4 crops, like sweet sorghum, switchgrass, and miscanthus, can grow on infertile terrain and produce substantial amounts of biomass. Energy crops now make up a small percentage of the total energy provided by biomass, but this is expected to change in the next decades. This chapter includes (1) global energy classification, (2) biofuel-producing energy crops, (3) potential contribution of energy crops to replace fossil fuel, (4) conversion technologies and (5) prospects of energy crops.
M. Irfan (*) · L. Xianhua School of Environmental Science and Engineering, Tianjin University, Tianjin, PR China e-mail: [email protected] A. Shauket · S. J. N. Ahmad Department of Botany, University of Agriculture Faisalabad, Faisalabad, Pakistan M. Jafir · J. N. Ahmad Department of Entomology, University of Agriculture Faisalabad, Faisalabad, Pakistan A. Ahmad Institute of Soil and Environmental Science, University of Agriculture Faisalabad, Faisalabad, Pakistan © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 S. A. Bandh (ed.), Strategizing Agricultural Management for Climate Change Mitigation and Adaptation, https://doi.org/10.1007/978-3-031-32789-6_5
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1 Introduction In many debates, climate change and global warming are emphasized as fundamental threats, particularly in this age of globalization where country borders and spatial heterogeneity are being reduced (Usman et al., 2021). It is challenging to put a precise numerical value on the magnitude of fossil fuel subsidies. In 2015, it was predicted that fossil fuel subsidies amounted to $4.7 trillion (6.3%) of the world’s real GDP, and in 2017, it was projected that they would rise to $5.2 trillion (6.5%) (Coady et al., 2019).). In 2016, the G7 leaders issued a call to action, urging all governments to end fossil fuel subsidies by 2025. There are many facets of fossil fuel subsidies that have not been sufficiently studied in the literature, despite the growing quantity of these subsidies around the world and the growing worry about the increase in these subsidies. To name a few of these traits, subsidies for fossil fuels are controversial because of the negative effects they have on the economy and the environment, which have not been adequately addressed (Malla et al., 2022; Bandh et al., 2021, 2023; Mushtaq et al., 2020). The extent of ecological damage was calculated by using the ecological footprint. The current global population of 7.4 billion people is expected to grow to 10 billion in 2055, which could put a strain on the planet’s limited resources. Alternatively, human yearly use of biomass materials is estimated at 72 gigatons, rising to 100 gigatons by 2030 (Usmani et al., 2020). To battle global climate concerns and reduce reliance on fossil fuels, the expansion of the global economy is currently up against a unique challenge in many sectors, including energy, food, and agriculture. There is now a global race to develop commercially viable renewable biofuels from lignocellulosic biomass as a response to rising fuel prices and the release of hazardous gases from the combustion of fossil fuels (Islam et al., 2020). The increased consumption of these nonrenewable resources, however, poses a critical risk to the environment. Using a biorefinery process to convert lignocellulose biomass into marketable industrial bioproducts like renewable energy is a new but exciting area of study (Abraham et al., 2020). Most lignocellulosic biomass comes from forest waste, farm waste, and energy crops that are grown specifically for energy, organic municipal solid waste, and industrial waste (wood, paper, and pulp). To minimize the worldwide environmental impact of energy production and consumption, several renewable energy sources (RES) can be utilized, including the conversion of biomass into usable energy (Roy et al., 2021; Parray et al., 2022; Bandh et al., 2022; Bandh, 2022a, b).
2 Global Energy Classification The global energy classification is based on nonrenewable and renewable energy sources which can be utilized for power generation (Fig. 5.1). The nonrenewable energy sources are crude oil, coal, natural gas, and nuclear. Nonrenewable energy sources are those whose economic worth could not be recovered by natural means
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Fig. 5.1 Flowchart of global energy classification. (Elavarasan, 2019)
at the same level of use. Nonrenewable sources form over billions of years. They are not sustainable (Elavarasan, 2019). Renewable energy sources are currently replacing nonrenewable energy sources since they are abundant and environmentally friendly. Renewable energy sources include solar, wind, geothermal, hydrothermal, and biomass. Countries are currently focusing on renewable energy to lessen the greenhouse gas effect. Additionally, hybrid systems consisting of two system combinations (renewable-nonrenewable) are created to improve output (Guo et al., 2018).
3 Biomass Energy Biomass-based energy is the most promising option for meeting the needs and ensuring a steady supply of eco-friendly energy and fuel because of its high potential and wide applicability. There are numerous approaches that can be taken to effectively utilize biomass resources. One of these is through developing and implementing new biomass technologies that allow for more effective biomass production and utilization. Agricultural biomass includes both the edible parts (oil and simple carbohydrates) and the nonedible parts of crops including stems, leaves, straws, etc. In the biomass context, agriculture-based biomass is a particularly large group (Chandra et al., 2012). Numerous crops can produce starch, cellulose, and oil, while some other crops produce biogas which can be utilized for heat and electricity generation. Landfills produce methane which can be utilized as biofuels that comprise biodiesel, methanol, ethanol, and their derivatives (Demirbaş, 2001). These are types of crops which can be used to create alternative energy sources. Significant incentives exist now to encourage renewable fuel utilization in the transportation
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sector across the globe. Several countries’ energy policies, climate policies, and agricultural policies reportedly offer incentives to promote the continued production and use of biofuels in the future. Carbon dioxide (CO2) levels in the air are going up because fossil fuels are being burned (DGS, 2005; Kamm et al., 2006). This is a big part of what is causing global warming. Concern over climate change on a global scale, which is mostly brought on by the combustion of fossil fuels, is one of the primary motivating factors behind the expansion of the biofuel industry around the world. There is much evidence that greenhouse gas emissions are to blame for the accelerated rate of global warming. The greenhouse effect is exacerbated by carbon dioxide (Rutz & Janssen, 2007). Biofuels can be made from a variety of renewable energy sources, but plant biomass has been seen as particularly promising for decades. This is due to its several positive qualities, including its low cost, negligible impact on the environment, and ample supply. About 14% of the world’s energy needs are met by biomass, making it a major resource for the economy. Additionally, the use of plant biomass has the potential to preserve and improve both ecological and social sustainability, as well as contribute to the stabilization of the incomes of farmers (Zhao et al., 2009). The world’s economy has been growing at a rapid rate recently due to which the demand for energy is increasing. The swift growth of major economies around the world, such as China, the United States, and Europe, is sure to increase the need for energy. It is for this reason that the dissemination of technologies that might fundamentally cut down on carbon emissions is difficult (Li & Zhang, 2017). One of the essential components of business expansion, technological advancement, and economic competitiveness in modern economies is the energy industry (Muntean et al., 2018). An economy that is focused on sustainability will have as some of its priorities the securing of energy supplies and the protection of the environment. Initiatives based on collaboration may have a beneficial effect on the environment (Cherry & Pidgeon, 2018). The demand for fossil fuels will be able to fall because of the development of renewable energy sources (RES). Furthermore, compared to 2005, the number of greenhouse gases emitted will be reduced by one-tenth (Searchinger et al., 2018).
3.1 Bioenergy Market The growth of a sustainable bioenergy market that is supported by bioresources is required to accomplish the goals of protecting the climate and maximizing the efficiency of resources. To equalize the support to produce biofuels, there is a need, as stated by (Zieliński et al., 2019) to look for nonfood biomass. Because of their role in maintaining energy stability, renewable energy sources should be prioritized for research and development to benefit the economy. Their contribution to the savings associated with the import of fossil fuels in 2015 was 15 million euros, and it is projected to be 58 million euros in the year 2030 (Study on the role of technical help in the production of the report on renewable energy for 2016). The use of renewable sources of energy in the EU carries with it significant implications for the region’s
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standing in the race for technological advancement. The European Union (EU) owns 30% of all patents related to energy sources worldwide. However, a significant number of businesses based in the EU struggle to accomplish their sustainable goals. To match the incentives and income mechanisms necessary to drive sustainable solutions, therefore, innovation at the level of the business model is essential (Geissdoerfer et al., 2018; Rashid et al., 2013). It is estimated that most of the world population will prefer to live in urban areas until 2050 (Desa, 2017), which presents a huge problem for policymakers attempting to promote sustainability (Petit-Boix & Leipold, 2018). Greenhouse gas emissions are lower in rural areas, but farmers can afford to make the necessary investments in their fields, especially in cutting- edge equipment that will allow them to boost production on a larger scale. Although the price of agricultural inputs can fluctuate, the demand for food is fixed, so these efforts will not lead to higher revenue, and farmers are being pushed to invest in more efficient technology because of this trend where the marginal revenue from agricultural output is falling (Czyżewski et al., 2019).
4 Agricultural Biofuels The use of renewable energy sources, such as biomass, to generate power is one approach to lessening the global environmental impact of energy production and use (Owusu & Asumadu-Sarkodie, 2016). Biomass is used to make energy in five different ways: growing plants for sugar, starch, cellulose, and oil, burning waste, using anaerobic digesters to make biogas that can be used to make heat or electricity, making gas from landfills, and making biofuels like methanol, biodiesel, ethanol, and their derivatives (Grangeiro et al., 2019). Concern over climate change on a global scale, which is mostly brought on by the combustion of fossil fuels, is one of the primary motivating factors behind the expansion of the biofuel industry around the world. There is much evidence that greenhouse gas emissions are to blame for the accelerated rate of global warming. The greenhouse effect is intensified by carbon dioxide (Prasad et al., 2020). Biofuels can be made from a variety of renewable energy sources, but plant biomass has been seen as particularly promising for decades. This is due to its several positive qualities, including its low cost, negligible impact on the environment, and ample supply. About 14% of the world’s energy needs are met by biomass, making it a major resource for the economy. Plant biomass has the potential to preserve and improve both ecological and social sustainability, as well as to contribute to the stabilization of the incomes of farmers (Bórawski et al., 2019). The use of oils derived from soybeans, canola, corn, rapeseed, and palm oil is generally acknowledged to be among the basic ingredients for biodiesel production. New plant oils, including those made from mustard seeds, peanuts, sunflowers, and cotton seeds, are currently under study (Eryilmaz et al., 2016). When making biodiesel, several different kinds of bio-lipids can be used. Some other crops are hemp, palm oil, mustard, sunflower, and some types of algae used as a replacement for vegetable oil that is not in use and fats obtained from
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animals (Khatib & Yassine, 2019). Only the oils from peanuts, soybeans, palms, sunflowers, safflowers, cottonseeds, and rapeseeds are investigated as possible replacement fuels for diesel vehicles. This is out of more than 350 different oil- producing crops (Eryilmaz et al., 2016).
4.1 Sweet Sorghum, a Source of Ethanol Production Annual C4 sweet sorghum is notable for its high photosynthetic efficiency. It is a plant that produces a lot of biomasses and has a high glucose content. Sucrose (up to 55%) and glucose (up to 3.2%) make up the bulk of their stalks (Diallo et al., 2019). Cellulose accounts for 12.4%, whereas hemicellulose makes up 10.2% of its composition. There are a lot of fermentable sugars in sweet sorghum biomass, so it is commonly thought of as a great starting point for making fermentative hydrogen. When compared to the other “new crops” that are now being studied as potential energy and industrial raw material sources, sweet sorghum appears to have the most promise (Diallo et al., 2019). Today, ethanol and methane are the two most well- known by-products of sweet sorghum fermentation. Assuming an energy yield of 26,500 kJ/kg, the cited research indicated that the energy obtained from ethanol varied between 6500 and 8900 kJkg−1 of dry sorghum biomass and between 1400 and 2700 kJkg−1 from fresh sorghum biomass (Diallo et al., 2019).
4.2 Brassica napus (Rapeseed) Brassica oil crops, which include Brassica napus (rapeseed), is referred to as oilseed rape (Indian mustard). The second highest-yielding oil crop worldwide is rapeseed. This crop is known as the energy crop that receives the greatest land in cultivation in Europe and is grown for the production of fodder, biofuel, and food. Rapeseed oil production made up 14% of oil crop production worldwide and was among the top 14 agricultural products in Europe. The nonedible oil demand is rising around the globe as a result of the growing industrialization of developing nations. Energy is a strategic national concern since petroleum supplies are running out at the same time. Therefore, it is essential to produce clean and effective bioenergy. For a number of reasons, rapeseed is the best crop for the manufacture of biodiesel. This crop produces a large quantity of oil because it has a lot of cellulose. Because of this, it is currently the most popular choice for making biodiesel. It may be the only alternative that can be used directly as a liquid biofuel without any preparation. Firstly, canola/rapeseed has a 40% oil content and can yield a lot of oil per unit of space. Secondly, rapeseed biodiesel has a significantly lower cloud point (a measure of the oil’s propensity to clog filters) and pour point (the temperature at which the liquid turns semisolid and loses its flow properties). Canola biodiesel is
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therefore a better fuel for colder climates because it is converted into gels at a lower temperature than biodiesel made from other feedstocks. Rapeseed is a significant source of biodiesel’s raw materials in temperate climate regions like Europe, where it makes up 50–70% of the fuel. Even if the technique for use is fully developed, there are currently few consistent sources of raw materials available. Therefore, there is a need to develop varieties that are suitable for marginal soils and setting up raw material processing equipment is crucial for the growth of the rapeseed biodiesel in the world (Fu et al., 2016; Popp et al., 2016; Raman et al., 2019; Van Duren et al., 2015).
4.3 Jatropha (Jatropha curcas) There are now cultivations in the southeast, north, and northeast of Brazil where jatropha (Jatropha curcas) is grown to extract its oil, which is then used in the production of biodiesel fuel in the Philippines and Brazil. Similarly, hundreds of initiatives in poor nations promote jatropha oil as an accessible biofuel crop (Rozina et al., 2017). The cake that is left over after pressing the seeds can be used as fertilizer, fuel for vehicles, or even animal feed. Also, digesters can use the whole seed, including the oil, to make biogas. Jatropha curcas, also known as jatropha, and Pongamia pinnata are the two types of raw materials that are now used in production in India (Karanja). Because of the presence of toxins, neither of these plants’ oils should be consumed in any form. Both jatropha and Karanja trees produce oil- rich seeds, with jatropha seeds containing 40% and Karanja seeds containing 33% (Demirbas et al., 2016).
4.4 Palm Oil (Elaeis guineensis) Its scientific name is Elaeis guineensis, which is native to West Africa. It was initially discovered to grow naturally in that region, but it was later farmed as an agricultural commodity once it was discovered there. Since palm oil comes from a tropical perennial plant, it is best grown in lowlands that experience high levels of humidity. As a result, palm oil might be easily cultivated in Malaysia. There is only one trunk on the tree, and it does not have any branches. The tree’s height can reach between 20 and 30 m (Wakil et al., 2015). Each solitary flower is relatively small and consists of three sepals, three petals, and three stamens. The blooms are produced in dense clusters. The leaves have a structure known as pinnate, and their length can range anywhere from 3 to 5 m.
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4.5 Safflower (Carthamus tinctorius L.) To make biodiesel, its seed oil undergoes chemical processing known as the transesterification reaction, which takes place in an atmosphere containing methyl alcohol and sodium hydroxide (NaOH) (Suresh et al., 2018). Safflower, which is a member of the Composite family and can thrive in a variety of climates, is grown in several different regions of the globe. It is an annual plant that resembles a thistle and is herbaceous. The leaves often have many very long and sharp spines on them. The plants can grow up to 150 cm tall and have globular flower heads that bloom in July. The flowers are typically a beautiful yellow, orange, or red color and each flower head on a branch typically has 15–20 seeds in it and can have anywhere from one to five bloom heads (Aydın, 2016).
4.6 Soybean (Glycine max) When it comes to protein and oil, it is indispensable. Major producers include China (7%), Argentina (21%), Brazil (27%), and the United States (33%). Soybeans can also be extracted for protein and oil. This makes them a significant food crop. While the protein is mostly used for animal feed, it is also used in some food products. The oil, on the other hand, is used in a wider variety of food products, animal feed products, and even some industrial uses. One of the primary ingredients in biodiesel is soybean oil. Over 80% of Brazil’s biodiesel comes from soybeans. When compared to the United States (74%), the European Union (16%), and Argentina (100%), it is at the 100% level. Therefore, soy holds great potential as a feedstock for making biodiesel. Soybean oil and protein are in high demand, making genetic breeding for increased yield and quality a pressing concern (André Cremonez et al., 2015).
5 Conversion Technologies The production of a single unit of bioenergy results in carbon dioxide emissions that are 10–20 times fewer than those associated with the production of fossil fuels (Gabrielli et al., 2020). Biochemical technology allows for the breakdown of cellulose into sugars and glycerides, which can then be processed further in biorefineries to produce chemical intermediates, bioethanol, and biodiesel. While the energy input and output ratios are not exactly small, they are also not significant. Many times, fossil fuels are used in the creation of bioenergy carriers. However, this source of energy production accounts for a negligible fraction of the whole. Bioenergy forestry and agriculture systems typically have energy conversion ratios of 1:25 and 1:50, respectively (Schipfer, 2017). There is a diverse selection of bioenergy carriers, ranging from unprocessed agricultural waste to highly refined
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biofuels for transportation. Several factors, such as availability, location of consumers, and the presence or absence of coproducts or benefits, can all have an impact on the objectives of using biomass. Products derived from biomass can be put to a broad variety of different uses (Datta et al., 2019).
5.1 Combustion and Cofiring One of the most common ways in which biomass is transformed is by combustion. It is possible that in the future, as more is learned about the fundamentals of combustion performance and ash behavior, plant dependability and efficiency will improve. Emissions and localized investment costs can be decreased by improving our knowledge of combustion (Ilic et al., 2018). Coffering solid biomass particles with coal, mixing diesel with biodiesel and gasoline with bioethanol, and installing vehicles with flexible fuel engines are all straightforward examples of merging biomass and fossil fuel technologies. Co-using biomass materials in coal-fired boiler systems have advanced rapidly in recent years. Co-firing has been used with a variety of biomass materials and commercially relevant fuels such as lignites, anthracites, bituminous and subbituminous coals, and petroleum coke. Herbaceous and sappy plants, trees, dry and wet farm trash, and energy crops all fall into this category (Nelson et al., 2018).
5.2 Gasification Biomass gasification involves the transformation of organic material into a gas or vapor and a solid. Syngas, in their gaseous form, can be converted into energy or biofuels to their high heating capacity. Char is the solid phase, and it is made up of the inert residue from the biomass and any organic material that was not changed throughout the treatment process. This change happens when some of the carbon in the material being fed is oxidized. This usually happens in the presence of air, steam, oxygen, and carbon dioxide. Many strategies are being investigated to maximize the quantity of biomass utilized to generate energy. One such strategy is the gasification of biomass. As the price of oil continues to skyrocket, so does public concern over the environmental impact of burning fossil fuels, which in turn has sped up research into gasification technology for biomass. Produced at temperatures between 250 and 300 °C, syngas is a gaseous combination of hydrogen, carbon monoxide, carbon dioxide, methane, and heavier hydrocarbons (such as tars) that condense. In addition to syngas, lighter hydrocarbons like ethane and propane are also generated. Besides inert gases like nitrogen, syngas can also contain noxious ones like sulfuric (H2S) and chloride (HCl) acid. Their existence is conditional on the biomass type being gasified and the conditions under which the process is being carried out. There is a wide range in the LHV of syngas, from 4 to 13 MJ/Nm3,
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which is dependent on the feedstock, gasification method, and operating circumstances (Liu & Ji, 2013; Qian et al., 2013; Wu et al., 2014). The combined ash and unconverted organic component produce char, which is rich in carbon. The amount of organic matter that remains after gasification is determined by the technology used and the operating conditions. On the other hand, the quantity of ash produced is proportional to the type of biomass that was incinerated. Depending on how much of the organic fraction has been transformed, the char’s LHV can range from 25 to 30 MJ/kg (Molino et al., 2016). It is the oxidation of biomass, which can occur in either an all-thermal or autothermal phase, that often supplies the energy needed for the major reactions that occur during gasification, which are endothermic. By engaging in a process known as incomplete combustion, the gasifier in an autothermal process generates its heat. In the all-thermal process, on the other hand, energy is brought in from the outside to do the gasification at the right level (Molino et al., 2016).
5.3 Biogas Generation Biogas is a sustainable fuel obtained from the anaerobic breakdown of different biological-based feedstocks via cooperative metabolic activities of acidogenic, hydrolytic, and methanogenic bacteria. Biogas contains approximately methane (60%), CO2 (40%), and H2S (2000 ppm), which are the major impurities. Methane capture during biogas production helps to reduce CH4 emissions, and it can also be used as a sustainable energy source for all applications that require natural gas. In 2014 biogas production enhanced (from 0.28 Ej to 1.28 Ej) with a volume of 59 billion m3. Many countries throughout the world grow corn primarily for the production of biogas (Nikkhah et al., 2020; Scarlat et al., 2018; Villadsen et al., 2019).
5.4 Bioethanol Production Alternatives to gasoline that are renewable and environmentally friendly include bioethanol. It is simple to add an oxygenated component for cleaner combustion to gasoline. Bioethanol production consists of different steps including initial treatment, fermentation, hydrolysis, recovery, and refinement. The use of bioethanol as a fuel began during the worldwide fuel crisis in the 1970s, and as a result of its widespread use across numerous industries, its production capacity increased from a lesser extent of 1 billion L (1975) to 39 billion L (2006). The main source of bioethanol production is corn, a crop with high sugar or starch content. Since it is widely planted around the world, corn produced 817 million tons worldwide in 2009, more than both rice (678 million tons) and wheat combined (682 million tons) (Nikkhah et al., 2020; Sirajunnisa & Surendhiran, 2016; Thangavelu et al., 2016).
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5.5 Biodiesel Production Without requiring significant hardware modifications, biodiesel, a substitute fuel for diesel, can be used in standard diesel engines. “Bio” suggests that it comes from a natural, renewable source, while “diesel” indicates that it is used as a fuel for diesel- powered motors. All through the process of transesterification, biodiesel can be made using oilseeds like canola, sunflower, peanut, and soybean. In several nations, including Italy, Germany, Turkey, and France, it might be the best alternative fuel. The world’s top biodiesel producers in 2014 are shown in Fig. 5.2. One of the amazing resources for the production of biodiesel is oilseeds. In this context, peanuts are recognized as one of the primary oilseed sources for the manufacturing of biodiesel, and the initial biofuel to run a diesel engine was made from peanuts. Renewability and biodegradability, a higher flash point, and the lack of sulfur and aromatic compounds are the benefits of biodiesel. However, the creation of feedstock involves the use of several inputs, like diesel fuel and chemical fertilizers, which might increase greenhouse gas emissions, whenever the origin of its production is oilseeds (Eryilmaz et al., 2016; Zhang & Balasubramanian, 2016).
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Fig. 5.3 The maximum distance a car may go using different biofuels (an average fuel usage of 10 L/100 km was estimated). (Nikkhah et al., 2020)
5.6 Green Technology Comparison The production of biodiesel (59,204.61 MJha−1), bioethanol (26,786.58 MJha−1), and biogas (267,084.00 MJha−1) comes from different energy crop sources. The findings showed unequivocally that using corn silage as a source of biogas produced more net energy than the other two biofuel production methods. The range that a typical car can cover while using different biofuels is shown in Fig. 5.3 (1 ha energy crop utilization for biofuel), assuming a 10-L gasoline consumption rate per 100 km. According to estimates, a car can go 62,000 km on biogas, 14,000 km on bioethanol, and 6000 km on biodiesel. In comparison to bioethanol and biodiesel, it means that biogas has the best potential for use as a transportation fuel. In some nations, biogas is used as a clean-burning transportation fuel. The European Union has also established a goal to boost the use of biofuels; more specifically, 10% of the fuels used in the transport industry should be made from biofuels by 2020, and the percentage should continue to rise after that year. Moreover, Iran has promised to reduce its GHG emissions following the Paris Agreement. Therefore, the utilization of upgraded biogas as a fossil fuel replacement in the transport industry could contribute to the reduction of greenhouse gas emissions. Since 2002, the use of biogas in urban transportation alone in Sweden has reduced the country’s annual carbon dioxide emissions by 9000 metric tons (Ahmad et al., 2017; Nikkhah et al., 2020).
6 Carbon Offsets When bioenergy is used in place of fossil fuels, carbon dioxide emissions are cut immediately. Therefore, the benefits of carbon mitigation measures can be maximized by a combination of energy crop production including carbon sinks and
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offset credits. To accomplish this goal and enhance the average carbon stock in the soil while simultaneously producing a source of biomass, energy crops can be planted in areas that were formerly used for agriculture or pasture. Reusing the carbon stored in biomass for energy production helps solve the essential problem of long-term preservation of the biotic carbon stores, as in the case of a permanent forest. There is some evidence that growing perennial energy crops can boost soil carbon levels. However, this idea is still in its infancy and needs more research, including in-depth life cycle analyses for certain crops grown in different locations. Over the next few decades, the global percentage of bioenergy may decline if laws are not put in place to encourage novel bioenergy technology and sustainable biomass production plans. Water use, biodiversity, and societal and economic concerns might all take a major hit without the correct parameters in place. Using integrated assessment models over the long run, the feasibility and cost of obtaining low atmospheric CO2 stability levels will be significantly impacted by the combination of biomass technology carbon capture and storage (Favero et al., 2020). It is technically possible to capture, transport, and repossess CO2 where biomass is utilized as a fuel for gasification, combustion, and hydrogen generation in a big-scale plant. Incorporating the charcoal produced by smaller, more scattered solid biomass gasification operations into the soil has the potential to improve crop yields, soil water retention, and soil carbon content (Bolan et al., 2022). People are suggesting these alternatives to slow down climate change because they can quickly lower the amount of CO2 in the air.
7 Biofuel Cost It is now possible to produce a wide variety of biofuels. Conventional biofuels that are considered “conventional” have seen extensive commercialization. These include ethanol made from corn and sugar and fatty acid methyl ester biodiesel made from oilseeds. Before biofuels with low net greenhouse gases and low indirect land-use change impact are employed widely, a long way still needs to be traveled. The crops that do not produce food and wastes obtained from lignocellulose (from agriculture and forestry, including stoves, straws, bagasse, and woody biomass) are used to create these fuels. Because electricity and hydrogen are not practical for use in heavy-duty fleets or air travel, low-carbon biofuels are seen as essential to the long-term decarbonization of the transportation industry. Carbon intensity limitations in the United States and renewable fuel rules, like the federal Renewable Fuel Standard (RFS), have promoted the adoption of both traditional and innovative biofuels (LCFS). From 2011 to 2022, the RFS increased the requirements for renewable fuels to have a lower carbon footprint across their whole life cycle. The definition of advanced fuels used in the RFS policy is different from the one used in this article. It states that advanced fuels must cut greenhouse gas emissions over their entire life cycle by at least 50% in comparison to a reference baseline based on projections for 2010. The LCFS uses a continuous scale to measure the carbon
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intensity of fuels and rewards those with a lower intensity without limiting the use of alternative fuels like natural gas, electricity, or biofuels. The LCFS mandated a gradual but steadily increasing reduction in carbon intensity in California’s transportation fuel pool beginning in 2011 (Witcover & Williams, 2017).
8 Outlook 1. Unlike our staple foods, which have been refined over generations, committed bioenergy crops have not been domesticated (Engels & Thormann, 2020). For example, there are more than 600 species of eucalyptus, but it is not known how to choose which is best for a particular location. If energy crops are to be grown sustainably, it will be necessary to conduct additional research on the inputs of agrochemicals and fertilizers. 2. Bioenergy crops need low-input systems that require only a small number of resources such as water and fertilizer. Given the current state of breeding, significant gains in bioenergy crop yields are projected to be achieved during the next few decades. The cultivation of both genetically modified (GM) and non-GM plants opens novel biotechnological avenues. Since the development of perennial crops is less expensive and the soil’s chemistry and structure are preserved, they are preferred over annual crops. Biomass yield is one metric, while plant structure and chemical composition of the feedstock are others. C4 grasses, such as miscanthus, may see increased productivity if their cold sensitivity is addressed (McCalmont et al., 2017). 3. Developing new high-value energy sources from biomass could play a crucial role in the industry’s long-term success. There are numerous biomaterials and chemical feedstocks that may be derived from biomass, and they can also be utilized as renewable hydrogen supply (Popa, 2018). 4. Going forward, biomass feedstocks will replace the petrochemicals used today. Lubricants, textiles, polymers, biodegradable plastics, high matrix composites, adhesives, stabilizers, paints, thickeners, and a variety of cellulosics are all examples (Rahman et al., 2021). If high-value products can be recovered from energy crops first, then the residues can be used to produce lower-value energy. This could make energy crops more cost-effective. Food, animal feed, industrial and chemical feedstocks, energy, and other items and materials could be made from the many fractions of the total crop that are now being researched and developed (de Jong & Jungmeier, 2015). For example, New Zealand built a prototype plant with a closed loop to separate biomass into its constituent parts (Krzeminski et al., 2017).
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9 Conclusions and Remarks In this chapter, the potential of biofuel production from energy crops was described. It is concluded that biofuel and biogas production from energy crops is an environmentally friendly process. On the other hand, all kinds of bioenergy will immediately lower CO2 emissions when they are used in place of fossil fuels. Therefore, to maximize the effects of carbon mitigation techniques, energy crop production should be combined with carbon sinks and offset credits. However, it is believed that one of the best methods to lessen the planet’s expanding ecological footprint is through the usage of renewable energy. With specialized energy crops expected to offer a higher share of biomass feedstock in the ensuing decades, bioenergy is expected to continue its position as the largest contributor to global renewable energy in the short to medium term and replace fossil fuel consumption. It is important to conduct more research on the economics of producing biofuel because it is helpful to control pollution, as it is an environmentally friendly approach.
References Abraham, A., Mathew, A. K., Park, H., Choi, O., Sindhu, R., Parameswaran, B., Pandey, A., Park, J. H., & Sang, B. I. (2020). Pretreatment strategies for enhanced biogas production from lignocellulosic biomass. Bioresource Technology, 301, 122725. https://doi.org/10.1016/j. biortech.2019.122725 Ahmad, N., Hamid, I., & Kazmi, S. T. H. (2017). Beyond COP21: What did Asian countries pledge in the Paris Agreement. André Cremonez, P., Feroldi, M., Cézar Nadaleti, W., de Rossi, E., Feiden, A., de Camargo, M. P., Cremonez, F. E., & Klajn, F. F. (2015). Biodiesel production in Brazil: Current scenario and perspectives. Renewable and Sustainable Energy Reviews, 42, 415–428. https://doi. org/10.1016/j.rser.2014.10.004 Aydın, H. (2016). Scrutinizing the combustion, performance and emissions of safflower biodiesel– kerosene fueled diesel engine used as power source for a generator. Energy Conversion and Management, 117, 400–409. https://doi.org/10.1016/j.enconman.2016.03.046 Bandh, S. A. (2022a). Climate change: The social and scientific construct (1st ed.). Springer. https://doi.org/10.1007/978-3-030-86290-9 Bandh, S. A. (2022b). Sustainable agriculture: Technological progressions and transitions (1st ed.). Springer. https://doi.org/10.1007/978-3-030-83066-3 Bandh, S. A., Shafi, S., Peerzada, M., Rehman, T., Bashir, S., Wani, S. A., & Dar, R. (2021). Multidimensional analysis of global climate change: A review. Environmental Science and Pollution Research International, 28(20), 24872–24888. https://doi.org/10.1007/ s11356-021-13139-7 Bandh, S. A., Parray, J. A., & Shameem, N. (2022). Climate change and microbial diversity: Advances and challenges (1st ed.). Apple Academic Press. https://www.routledge.com/Climate- Change-a nd-M icrobial-D iversity-A dvances-a nd-C hallenges/Bandh-Parray-S hameem/p/ book/9781774637821 Bandh, S. A., Malla, F. A., Qayoom, I., Mohi-ud-Din, H., Butt, A. K., Altaf, A., Wani, S. A., Betts, R., Truong, T. H., Pham, N. D. K., Cao, D. N., & Ahmed, S. F. (2023). Importance of blue carbon in mitigating climate change and plastic/microplastic pollution and promoting cir-cular economy. Sustainability, 15(3), 2682. https://doi.org/10.3390/su15032682
84
M. Irfan et al.
Bolan, N., Hoang, S. A., Beiyuan, J., Gupta, S., Hou, D., Karakoti, A., Joseph, S., Jung, S., Kim, K.-H., Kirkham, M. B., Kua, H. W., Kumar, M., Kwon, E. E., Ok, Y. S., Perera, V., Rinklebe, J., Shaheen, S. M., Sarkar, B., Sarmah, A. K., et al. (2022). Multifunctional applications of biochar beyond carbon storage. International Materials Reviews, 67(2), 150–200. https://doi. org/10.1080/09506608.2021.1922047 Bórawski, P., Bełdycka-Bórawska, A., Szymańska, E. J., Jankowski, K. J., Dubis, B., & Dunn, J. W. (2019). Development of renewable energy sources market and biofuels in the European Union. Journal of Cleaner Production, 228, 467–484. https://doi.org/10.1016/j. jclepro.2019.04.242 Chandra, R., Takeuchi, H., & Hasegawa, T. (2012). Methane production from lignocellulosic agricultural crop wastes: A review in context to second generation of biofuel production. Renewable and Sustainable Energy Reviews, 16(3), 1462–1476. https://doi.org/10.1016/j.rser.2011.11.035 Cherry, C. E., & Pidgeon, N. F. (2018). Is sharing the solution? Exploring public acceptability of the sharing economy. Journal of Cleaner Production, 195, 939–948. https://doi.org/10.1016/j. jclepro.2018.05.278 Coady, M. D., Parry, I., Le, N.-P., & Shang, B. (2019). Global fossil fuel subsidies remain large: An update based on country-level estimates. International Monetary Fund. Czyżewski, B., Czyżewski, A., & Kryszak, Ł. (2019). The market treadmill against sustainable income of European Farmers: How the CAP has struggled with Cochrane’s curse. Sustainability, 11(3), 791. https://doi.org/10.3390/su11030791 Datta, A., Hossain, A., & Roy, S. (2019). An overview on biofuels and their advantages and disadvantages. Asian Journal of Chemistry, 31(8), 1851–1858. https://doi.org/10.14233/ ajchem.2019.22098 de Jong, E., & Jungmeier, G. (2015). Biorefinery concepts in comparison to petrochemical refineries. In Industrial biorefineries & white biotechnology (pp. 3–33). Elsevier. Demirbaş, A. (2001). Biomass resource facilities and biomass conversion processing for fuels and chemicals. Energy Conversion and Management, 42(11), 1357–1378. https://doi.org/10.1016/ S0196-8904(00)00137-0 Demirbas, A., Bafail, A., Ahmad, W., & Sheikh, M. (2016). Biodiesel production from non- edible plant oils. Energy Exploration and Exploitation, 34(2), 290–318. https://doi. org/10.1177/0144598716630166 Desa, U. (2017). http://esa.un.org/unpp (gelesen am 16, 2010 (2008 revision). Accessed: May 19 (p. 2009b): World population prospects. United Nations Department of Economic and Social Affairs Population Division. DGS. (2005). Planning Installing bioenergy systems: A guide for installers. Architects and Engineers, GREENPro project. Earthscan Publications. Diallo, B., Li, M., Tang, C., Ameen, A., Zhang, W., & Xie, G. H. (2019). Biomass yield, chemical composition and theoretical ethanol yield for different genotypes of energy sorghum cultivated on marginal land in China. Industrial Crops and Products, 137, 221–230. https://doi. org/10.1016/j.indcrop.2019.05.030 Elavarasan, R. M. (2019). The motivation for renewable energy and its comparison with other energy sources: A review. European Journal of Sustainable Development Research, 3(1), em0076. https://doi.org/10.20897/ejosdr/4005 Engels, J. M. M., & Thormann, I. (2020). Main challenges and actions needed to improve conservation and sustainable use of our crop wild relatives. Plants, 9(8), 968. https://doi.org/10.3390/ plants9080968 Eryilmaz, T., Yesilyurt, M. K., Cesur, C., & Gokdogan, O. (2016). Biodiesel production potential from oil seeds in Turkey. Renewable and Sustainable Energy Reviews, 58, 842–851. https://doi. org/10.1016/j.rser.2015.12.172 Favero, A., Daigneault, A., & Sohngen, B. (2020). Forests: Carbon sequestration, biomass energy, or both? Science Advances, 6(13), eaay6792. https://doi.org/10.1126/sciadv.aay6792 Fu, D.-h., Jiang, L.-y., Mason, A. S., Xiao, M.-l., Zhu, L.-r., Li, L.-z., Zhou, Q.-h., Shen, C.-j., & Huang, C.-h. (2016). Research progress and strategies for multifunctional rapeseed: A case
5 Promoting Energy Crops to Replace Fossil Fuel Use
85
study of China. Journal of Integrative Agriculture, 15(8), 1673–1684. https://doi.org/10.1016/ S2095-3119(16)61384-9 Gabrielli, P., Gazzani, M., & Mazzotti, M. (2020). The role of carbon capture and utilization, carbon capture and storage, and biomass to enable a net-zero-CO2 emissions chemical industry. Industrial and Engineering Chemistry Research, 59(15), 7033–7045. https://doi.org/10.1021/ acs.iecr.9b06579 Geissdoerfer, M., Vladimirova, D., & Evans, S. (2018). Sustainable business model innovation: A review. Journal of Cleaner Production, 198, 401–416. https://doi.org/10.1016/j. jclepro.2018.06.240 Grangeiro, L. C., de Almeida, S. G. C., de Mello, B. S., Fuess, L. T., Sarti, A., & Dussán, K. J. (2019). New trends in biogas production and utilization. In Sustainable bioenergy (pp. 199–223). Elsevier. Guo, S., Liu, Q., Sun, J., & Jin, H. (2018). A review on the utilization of hybrid renewable energy. Renewable and Sustainable Energy Reviews, 91, 1121–1147. https://doi.org/10.1016/j. rser.2018.04.105 Hajjari, M., Tabatabaei, M., Aghbashlo, M., & Ghanavati, H. (2017). A review on the prospects of sustainable biodiesel production: A global scenario with an emphasis on waste-oil biodiesel utilization. Renewable and Sustainable Energy Reviews, 72, 445–464. https://doi.org/10.1016/j. rser.2017.01.034 Ilic, D., Williams, K., Farnish, R., Webb, E., & Liu, G. (2018). On the challenges facing the handling of solid biomass feedstocks. Biofuels, Bioproducts and Biorefining, 12(2), 187–202. https://doi.org/10.1002/bbb.1851 Islam, M. K., Wang, H., Rehman, S., Dong, C., Hsu, H. Y., Lin, C. S. K., & Leu, S. Y. (2020). Sustainability metrics of pretreatment processes in a waste derived lignocellulosic biomass biorefinery. Bioresource Technology, 298, 122558. https://doi.org/10.1016/j.biortech.2019.122558 Kamm, B., Gruber, P. R., & Kamm, M. (2006). Biorefineries-industrial processes and products (Vol. 2). Wiley-VCH Press. Khatib, S. E., & Yassine, N. A. (2019). Advances in synthetic biology and metabolic engineering in the production of biofuel. International Journal of Current Microbiology and Applied Sciences, 8(9), 1762–1772. https://doi.org/10.20546/ijcmas.2019.809.204 Krzeminski, P., Leverette, L., Malamis, S., & Katsou, E. (2017). Membrane bioreactors–a review on recent developments in energy reduction, fouling control, novel configurations, LCA and market prospects. Journal of Membrane Science, 527, 207–227. https://doi.org/10.1016/j. memsci.2016.12.010 Li, W., & Zhang, H. (2017). Decomposition analysis of energy efficiency in China’s Beijing- Tianjin-Hebei region. Polish Journal of Environmental Studies, 26(1), 189–203. https://doi. org/10.15244/pjoes/65290 Liu, B., & Ji, S. (2013). Comparative study of fluidized-bed and fixed-bed reactor for syngas methanation over Ni-W/TiO2-SiO2 catalyst. Journal of Energy Chemistry, 22(5), 740–746. https://doi.org/10.1016/S2095-4956(13)60098-4 Malla, F. A., Mushtaq, A., Bandh, S. A., Qayoom, I., Ho-ang, A. T., & Shahid-e-Murtaza. (2022). Understanding climate change: Scientific opinion and public perspective. In S. A. Bandh (Ed.), Climate change: The social and scientific construct. Springer Nature Publishing. https://link. springer.com/chapter/10.1007/978-3-030-86290-9_1 McCalmont, J. P., Hastings, A., McNamara, N. P., Richter, G. M., Robson, P., Donnison, I. S., & Clifton-Brown, J. (2017). Environmental costs and benefits of growing Miscanthus for bioenergy in the UK. Global Change Biology Bioenergy, 9(3), 489–507. https://doi.org/10.1111/ gcbb.12294 Molino, A., Chianese, S., & Musmarra, D. (2016). Biomass gasification technology: The state of the art overview. Journal of Energy Chemistry, 25(1), 10–25. https://doi.org/10.1016/j. jechem.2015.11.005 Muntean, M., Guizzardi, D., Schaaf, E., Crippa, M., Solazzo, E., Olivier, J., & Vignati, E. (2018). Fossil CO2 emissions of all world countries (p. 2). Publications Office of the European Union.
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Mushtaq, B., Bandh, S. A., & Shafi, S. (2020). Environmental management: Environmental issues, awareness and abatement (1st ed.). Springer. https://doi.org/10.1007/978-981-15-3813-1 Nelson, L., Park, S., & Hubbe, M. A. (2018). Thermal depolymerization of biomass with emphasis on gasifier design and best method for catalytic hot gas conditioning. BioResources, 13(2), 4630–4727. https://doi.org/10.15376/biores.13.2.Nelson Nikkhah, A., El Haj Assad, M., Rosentrater, K. A., Ghnimi, S., & Van Haute, S. (2020). Comparative review of three approaches to biofuel production from energy crops as feedstock in a developing country. Bioresource Technology Reports, 10, 100412. https://doi. org/10.1016/j.biteb.2020.100412 Owusu, P. A., & Asumadu-Sarkodie, S. (2016). A review of renewable energy sources, sustainability issues and climate change mitigation. Cogent Engineering, 3(1), 1167990. https://doi. org/10.1080/23311916.2016.1167990 Parray, J. A., Bandh, S. A., & Shameem, N. (2022). Climate change and microbes: Impact and vulnerability (1st ed.). Apple Academic Press. https://www.routledge.com/ Climate-C hange-a nd-M icrobes-I mpacts-a nd-Vulnerability/Parray-B andh-S hameem/p/ book/9781774637210 Petit-Boix, A., & Leipold, S. (2018). Circular economy in cities: Reviewing how environmental research aligns with local practices. Journal of Cleaner Production, 195, 1270–1281. https:// doi.org/10.1016/j.jclepro.2018.05.281 Popa, V. I. (2018). Biomass for fuels and biomaterials. In Biomass as renewable raw material to obtain bioproducts of high-tech value (pp. 1–37). Elsevier. Popp, J., Harangi-Rákos, M., Gabnai, Z., Balogh, P., Antal, G., & Bai, A. (2016). Biofuels and their co-products as livestock feed: Global economic and environmental implications. Molecules, 21(3), 285. https://doi.org/10.3390/molecules21030285 Prasad, S., Kumar, S., Sheetal, K., & Venkatramanan, V. (2020). Global climate change and biofuels policy: Indian perspectives. In Global climate change and environmental policy (pp. 207–226). Springer. Qian, K., Kumar, A., Patil, K., Bellmer, D., Wang, D., Yuan, W., & Huhnke, R. L. (2013). Effects of biomass feedstocks and gasification conditions on the physiochemical properties of char. Energies, 6(8), 3972–3986. https://doi.org/10.3390/en6083972 Rahman, M. S., Hasan, M. S., Nitai, A. S., Nam, S., Karmakar, A. K., Ahsan, M. S., Shiddiky, M. J. A., & Ahmed, M. B. (2021). Recent developments of carboxymethyl cellulose. Polymers, 13(8), 1345. https://doi.org/10.3390/polym13081345 Raman, L. A., Deepanraj, B., Rajakumar, S., & Sivasubramanian, V. (2019). Experimental investigation on performance, combustion and emission analysis of a direct injection diesel engine fuelled with rapeseed oil biodiesel. Fuel, 246, 69–74. https://doi.org/10.1016/j.fuel.2019.02.106 Rashid, A., Asif, F. M. A., Krajnik, P., & Nicolescu, C. M. (2013). Resource conservative manufacturing: An essential change in business and technology paradigm for sustainable manufacturing. Journal of Cleaner Production, 57, 166–177. https://doi.org/10.1016/j.jclepro.2013.06.012 Roy, S., Dikshit, P. K., Sherpa, K. C., Singh, A., Jacob, S., & Chandra Rajak, R. C. (2021). Recent nanobiotechnological advancements in lignocellulosic biomass valorization: A review. Journal of Environmental Management, 297, 113422. https://doi.org/10.1016/j.jenvman.2021.113422 Rozina, Asif, S., Ahmad, M., Zafar, M., & Ali, N. (2017). Prospects and potential of fatty acid methyl esters of some non-edible seed oils for use as biodiesel in Pakistan. Renewable and Sustainable Energy Reviews, 74, 687–702. https://doi.org/10.1016/j.rser.2017.02.036 Rutz, D., & Janssen, R. (2007). Biofuel technology handbook (p. 95). WIP Renewable Energies. Scarlat, N., Dallemand, J.-F., & Fahl, F. (2018). Biogas: Developments and perspectives in Europe. Renewable Energy, 129, 457–472. https://doi.org/10.1016/j.renene.2018.03.006 Schipfer, F. (2017). Densification and conversion technologies for bioenergy and advanced biobased material supply chains-a European case study. TU Wien. Searchinger, T. D., Beringer, T., Holtsmark, B., Kammen, D. M., Lambin, E. F., Lucht, W., Raven, P., & van Ypersele, J.-P. (2018). Europe’s renewable energy directive poised to harm global forests. Nature Communications 9, 3741. https://doi.org/10.1038/s41467-018-06175-4
5 Promoting Energy Crops to Replace Fossil Fuel Use
87
Sirajunnisa, A. R., & Surendhiran, D. (2016). Algae–A quintessential and positive resource of bioethanol production: A comprehensive review. Renewable and Sustainable Energy Reviews, 66, 248–267. https://doi.org/10.1016/j.rser.2016.07.024 Suresh, M., Jawahar, C. P., & Richard, A. (2018). A review on biodiesel production, combustion, performance, and emission characteristics of non-edible oils in variable compression ratio diesel engine using biodiesel and its blends. Renewable and Sustainable Energy Reviews, 92, 38–49. https://doi.org/10.1016/j.rser.2018.04.048 Thangavelu, S. K., Ahmed, A. S., & Ani, F. N. (2016). Review on bioethanol as alternative fuel for spark ignition engines. Renewable and Sustainable Energy Reviews, 56, 820–835. https://doi. org/10.1016/j.rser.2015.11.089 Usman, M., Makhdum, M. S. A., & Kousar, R. (2021). Does financial inclusion, renewable and non-renewable energy utilization accelerate ecological footprints and economic growth? Fresh evidence from 15 highest emitting countries. Sustainable Cities and Society, 65, 102590. https://doi.org/10.1016/j.scs.2020.102590 Usmani, Z., Sharma, M., Karpichev, Y., Pandey, A., Chander Kuhad, R. C., Bhat, R., Punia, R., Aghbashlo, M., Tabatabaei, M., & Gupta, V. K. (2020). Advancement in valorization technologies to improve utilization of bio-based waste in bioeconomy context. Renewable and Sustainable Energy Reviews, 131, 109965. https://doi.org/10.1016/j.rser.2020.109965 Van Duren, I., Voinov, A., Arodudu, O., & Firrisa, M. T. (2015). Where to produce rapeseed biodiesel and why? Mapping European rapeseed energy efficiency. Renewable Energy, 74, 49–59. https://doi.org/10.1016/j.renene.2014.07.016 Villadsen, S. N. B., Fosbøl, P. L., Angelidaki, I., Woodley, J. M., Nielsen, L. P., & Møller, P. (2019). The potential of biogas; the solution to energy storage. ChemSusChem, 12(10), 2147–2153. https://doi.org/10.1002/cssc.201900100 Wakil, M. A., Kalam, M. A., Masjuki, H. H., Atabani, A. E., & Rizwanul Fattah, I. M. (2015). Influence of biodiesel blending on physicochemical properties and importance of mathematical model for predicting the properties of biodiesel blend. Energy Conversion and Management, 94, 51–67. https://doi.org/10.1016/j.enconman.2015.01.043 Witcover, J., & Williams, R. B. (2017). Biofuel tracker: Capacity for low carbon fuel policies– assessment through 2018. Wu, Y., Yang, W., & Blasiak, W. (2014). Energy and exergy analysis of high temperature agent gasification of biomass. Energies, 7(4), 2107–2122. https://doi.org/10.3390/en7042107 Zhang, Z.-H., & Balasubramanian, R. (2016). Investigation of particulate emission characteristics of a diesel engine fueled with higher alcohols/biodiesel blends. Applied Energy, 163, 71–80. https://doi.org/10.1016/j.apenergy.2015.10.173 Zhao, Y. L., Dolat, A., Steinberger, Y., Wang, X., Osman, A., & Xie, G. H. (2009). Biomass yield and changes in chemical composition of sweet sorghum cultivars grown for biofuel. Field Crops Research, 111(1–2), 55–64. https://doi.org/10.1016/j.fcr.2008.10.006 Zieliński, M., Dębowski, M., Kisielewska, M., Nowicka, A., Rokicka, M., & Szwarc, K. (2019). Cavitation-based pretreatment strategies to enhance biogas production in a small-scale agricultural biogas plant. Energy for Sustainable Development, 49, 21–26. https://doi.org/10.1016/j. esd.2018.12.007
Chapter 6
Changes in the Agriculture Sector That Are Essential to Mitigate and Adapt to Climate Changes Enohetta B. Tambe, Charles C. Anukwonke, Iheoma E. Mbuka-Nwosu, and Chinedu I. Abazu Abstract Growing human population and preference for diet are driving global food demands. Consequently, the environmental systems that sustain food production is being stretched, altering agricultural networks and leading to an increasing number of people living in hunger in some regions across years. The situation is exacerbated by climate change, which is mainly caused by greenhouse gas emissions through anthropogenic activities, including the agricultural sector. Sustaining the environmental systems for food production requires climate-smart contributions in the agricultural sector, which should principally achieve increase in food productivity, enhance resilience and reduce emissions. These contributions are essential to address production of better, nutritious and more food and pest and disease management, policies and programmes that reduce farmers’ vulnerability to shocks, making data available for informed decision-making, reduce deforestation, strengthen carbon sequestration, reduce emission per kilogram of food produced and insure farmers among others. However, accessing and accommodating these climate-smart agricultural (CSA) changes is not uniform across regions, especially in low-income economies that are mainly dependent on climate-sensitive livelihoods. These limitations challenge the progress and well-being of these people who are already suffering existing deprivations. While the global temperature remains dynamic, managing the interconnectedness, necessity and traditional techniques of these CSA changes with the quest for progress in food security is an essential consideration. Therefore, a nexus paradigm that strengthens synergies and accommodates the trade-offs of
E. B. Tambe · C. C. Anukwonke (*) Department of Environmental Management, Chukwuemeka Odumegwu Ojukwu University, Uli, Nigeria I. E. Mbuka-Nwosu Department of Environmental Management, Federal University of Technology, Owerri, Nigeria C. I. Abazu Department of Urban and Regional Planning, Chukwuemeka Odumegwu Ojukwu University, Uli, Nigeria © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 S. A. Bandh (ed.), Strategizing Agricultural Management for Climate Change Mitigation and Adaptation, https://doi.org/10.1007/978-3-031-32789-6_6
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these CSA changes is a viable option for mitigation and adaptation, while taking into cognizance local priorities in realising sustained food needs. Keywords Agricultural changes · Climate-smart agriculture · Synergies · Mitigation · Adaptation
1 Introduction Ending hunger in the growing human population is one of the contemporary challenges facing societies. In the course of meeting food needs for the growing population, the networks on which survival depends are being weakened. This is occurring through agricultural production at the expense of huge transformation of environmental resources, such as water, soils, biodiversity and natural resources (Brack, 2019; Klauser, 2021). Following this recurrent transformation of environmental resources and subsequent creation of conditions such as spread of transboundary diseases and pests, production of copious volumes of wastes and their regenerative capacities are stretched, leading to unhealthy environmental support systems (FAO, 2017a; Tambe et al., 2022). The consequence of this is a vicious cycle that undermines productivity and reduces agricultural output and its interconnected impacts that lead to hunger, poverty, deprivation and human suffering (Anukwonke et al., 2022). Over the years, climate change has posed as a true titian with one of such challenge emanating from the agricultural sector is the emission of greenhouse gases such as methane, nitrous oxide and carbon dioxide into the atmosphere (Lynch et al., 2021). These emissions are estimated to contribute between 19% and 29% of total anthropogenic greenhouse gas emissions (CCAFS, 2015; Klauser, 2021). The addition of these gases causes enhanced increase of global temperature, a condition usually referred to as ‘climate change’ (IPCC, 2021). This environmental condition leads to alteration of ecological processes, shifting of agroecosystem boundaries, weather variability, invasive species and frequent extreme weather events. Over the years, climate shifts have manifested as a true titian with concerns on the major source of livelihood and stresses on soil fertility (Akanwa et al., 2019; Anabaraonye et al., 2021). These environmental stressors weaken human survival networks and undermine achievement of all the sustainable development goals (Anukwonke et al., 2022; United Nations, 2017; Malla et al., 2022; Bandh et al., 2021, 2023; Mushtaq et al., 2020). As a result of the deleterious effects of climate change and the contribution from the agricultural sector, it is essential to identify the pathways through which the sector is contributing to greenhouse gas emissions. This identification facilitates restructuring of these pathways with a view of achieving networks that could curb these emissions and sustain human progress (Akinnagbe & Irohibe, 2014; Mumtaz et al., 2019; Parray et al., 2022 Bandh et al., 2022 Bandh, 2022a, b).
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The necessity to restructure these pathways is based on the premise that throughout human agricultural history, experts have recently come to understand that the focus on agriculture, which has been on investment in resource-intensive farming systems and high input, cannot guarantee sustainable agriculture and food production for society (FAO, 2017a). Consequently, ‘holistic’ approaches are needed that take into cognizance climate-smart agriculture (CSA), agroforestry, conservation agriculture and agro-ecology. Each of these approaches seek to address sustainable resource use and attainment of at least one of these core pillars: increased food productivity, enhanced resilience and reduced emissions. Following the potential of CSA to address all of these pillars, many authors contend that climate-smart agriculture incorporates many of the field-based and farm-based sustainable agricultural land management strategies that are already well known and in widespread use, including residue management, agroforestry and conservation tillage (Abhilash et al., 2021; FAO, 2010). Consequently, this approach (CSA), which takes into consideration traditional and indigenous knowledge, has become the paradigm for sustainable agriculture in the twenty-first century and is detailed in this chapter. However, while these approaches are promising tools in sustaining the agricultural sector, the pathways and resources to achieve their pillars vary and are not uniformly accessible across regions (Anuga et al., 2019; CIAT & World Bank, 2018; Opeyemi et al., 2021). The variation necessitates a consideration of local priorities and nexus approaches that capture significant synergies and accommodate trade- offs (Abegunde & Obi, 2022). Similarly, lagging of its utilisation and acceptability is characterised in economies that are worst hit by food insecurity and with huge reliance on climate-sensitive livelihoods. This challenges the existing poor economic status of these people and undermines achievement of sustainable development goals. Exploring the frontiers of the extent of application of these approaches, their efficiency, acceptability and benefits could provide opportunity to widen their scope and promote a sustainable pattern of agriculture. However, while the climate is likely to keep changing, and more food is needed to feed the ever-growing human population, some of the approaches are likely to remain dynamic to accommodate these changes. In this regard, to what extend can we keep changing these approaches while sustaining the pillars they seek? These are pertinent issues that challenge the future we want. This chapter has addressed the explored changes in the agricultural sector necessary to sustain food production in the midst of accelerating climate and examine issues that open frontiers for investigation in sustaining the sector.
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2 Feeding the World in Climate Crisis: The Sources of Agricultural Greenhouse Gases 2.1 Food Demands and Productivity Projection on feeding and meeting increasing caloric needs of the growing human population is a shared vision for member countries of the Food and Agriculture Organization (FAO). Despite progress made so far to reduce food insecurity, the challenges of meeting global food needs are rife. There is illuminating inequality, about 795 million people still suffer from hunger and more than two billion are facing micronutrient deficiencies (FAO, 2017a; OPHI & UNDP, 2019). Consequently, achieving food security in the next decades is quite challenging in the face of further deforestation, land degradation and climate change (FAO, 2016). Notwithstanding the increasing global climate, food production with reference to the first decade of the twenty-first century is expected to increase by 70% in 2050 to cater to the projected 9–10 billion people in the world. In developing countries, their production is expected to double (FAO, 2009, 2017a). Similarly, 90% (with over 80% in developing countries) of the expected increase in agricultural production will employ increased intensive agriculture, while 10% will make use of land expansion. While crop yield is expected to grow, the growth rate will be at a slower rate (decelerating growth) when compared to historical records. The overall agricultural production is expected to strengthen livelihood assets, enhance the well-being status of farmers and the rural poor and reduce the prevalence of undernourishment in developing countries from 16.3% in the first decade of the twenty-first century to 4.8% by 2050 (FAO, 2009). This is aligned to the fact that in many economies across the world, agriculture makes up a sizeable portion of the GDP, and 2.5 billion people globally rely on it for their living (FAO, 2016). Similarly, given that roughly two-thirds of the world’s poorest people work in agriculture and that three-quarters of the world’s poorest people still reside in rural regions, improving global agricultural performance is essential to alleviating poverty and food insecurity. These achievements in relation to the role of agriculture seem impressive and are interconnected to the pathways of realising a sustainable future. Unfortunately, the projected increase in food production with its associated expansion of land use by 10% will occur at the expense of reducing the forest canopy (Brack, 2019). Although there is decelerating deforestation associated with agricultural development, agriculture is the main driver of forest removal and accounted for 27% of all tree canopy loss between 2001 and 2015 (Brack, 2019; European Commission, 2013). However, there are variations in contributions of this forest canopy loss across the various agricultural sectors. According to the European Commission (2013), livestock accounted for 46%, crops for animal feed 11%, soybeans 19%, oil palm 8%, maize 11%, sugarcane 5% and rice 6%. The replacement of forest areas with these practices in an unsustainable way increases the vulnerability of the practices to environmental stressors. Increased temperatures, weather
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unpredictability, shifting agro-ecosystem boundaries, invasive plants and pests and an increase in extreme weather events are just a few of the negative effects of climate change that are already being felt (World Bank, 2021b). On farms, climate change is diminishing animal output, the nutritional value of main grains and crop yields. To sustain existing yields and enhance output and food quality to satisfy demand, significant adaptation and mitigation expenditures will be needed (UNFCCC, 2021; World Bank, 2021a).
2.2 Agriculture and Greenhouse Gas Emissions: Land Preparation to Pre-harvest Expanding land use in agriculture is reducing forest canopy and degrading its environment. This reduction in forest canopy emanating from the agricultural sector is posing huge challenges in sustaining agricultural production and a healthy environment for societies (Brack, 2019; FAO, 2016). This is based on the premise that the forests are responsible for capturing a significant quantity of carbon dioxide from the atmosphere. The captured carbon dioxide is used during photosynthesis (food production in the plant) and constitute the biomass of the plant: roots, leaves, branches and tree trunks. Carbon is also stored in forests in soils, roots, leaf litter and woody debris. These carbon-storing sectors of the forests and their environment are essential in mitigating climate change from anthropogenic activities. When the forests and their environment are replaced through agricultural development that cannot balance the carbon capture, the result is decrease in the sources of carbon sinks to sustain a healthy environment, increase greenhouse gases in the atmosphere, increase erosion and siltation, loss of freshwater resources and a weakening of a myriad of ecological networks that sustain life (Ali et al., 2020; Ancha et al., 2019). These in turn undermine the support system of agricultural production and increase the climate challenge – a vicious cycle, characterised by poverty, hunger, migration, inequality, gender inequality, urban challenges and violent conflict among others that undermine progress in societies (Anukwonke et al., 2022). While the agricultural sector is an essential tenet in sustaining human dignity, the practice is also contributing hugely (estimated to be 19–29%) to the net total anthropogenic greenhouse gas emissions such as methane, carbon dioxide and nitrous oxide (Crippa et al., 2021; Lynch et al., 2021; UNFCCC, 2021). The main sources of greenhouse gas emissions in the sector usually occur during agricultural operation and inputs, such as the use of tractor fuel, fertilizer manufacture and application, soil tillage, transportation, production and transportation of pesticide, threshing, harvesting and irrigation; agricultural land management such as manure management, waste management and N fertilizer management; and biomass burning and decay among others (Kitamura et al., 2021; Lazcano et al., 2021; Tuğrul, 2019). Greenhouse gas emission in the sector also occurs through food losses in the production chain from the harvest to table (FAO, 2014, 2015). For example, when
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chemical fertilizers are applied on soils to enhance plant growth, a series of chemical reactions lead to the emission of nitrous oxide, contributing about 2.5% of total greenhouse gas emissions (Lazcano et al., 2021). Consequently, expanding agricultural lands through clearing the forest canopy (and replacing with crops and/or livestock) while seeking to maintain a habitable greenhouse gas emission requires identifying, mimicking and integrating natural approaches in the agricultural sector that should maintain the values of the natural land use (natural forests) or enhance it.
2.3 Food Losses and Greenhouse Gas Emissions: Harvest to Consumers’ Table It is estimated that 33% of all foods produced across the world for human consumption do not reach the consumer’s table (FAO, 2014, 2015). It ends up as food wastes. While this remains a challenge to the economy, food security and environmental health, it is also a waste of natural resources (Łaba et al., 2022; World Bank, 2020). This is because, in the course of food production, energy and resources are being invested for growing, processing, packaging, transportation and marketing the food. The utilisation of energy by tractors to prepare the land for cultivation, energy used by distribution vehicles and industrial processes emit a copious amount of carbon dioxide into the environment. Similarly, in the production and usage of input materials such as fertilizers, irrigation process and packaging materials, emission of greenhouse gases occurs. Furthermore, the degradation of food waste is a potent source of methane emission. Globally, these emissions associated with food waste is estimated at 8% (4.4GtCO2eq) of the total anthropogenic greenhouse gas emissions (FAO, 2015; World Bank, 2020). While food losses occur at all stages from harvest to consumers’ table, the volume of losses varies in space and depends on the local condition of each economy and income status (FAO, 2015; Obinaju & Ikpeida, 2021; Seberini, 2020). The per capita footprint of food losses is highest in North America and is least in sub- Saharan Africa. Generally, high-income economies suffer more food losses at the processing, transportation and consumption stages. This has been attributed to aesthetic preferences. For low-income economies, higher food losses occur at the production and post-harvest phases (Obinaju & Ikpeida, 2021; World Bank, 2020). This has been correlated with weak infrastructure and insufficient knowledge on storage and handling in the climatic conditions that favours food spoilage. The losses could vary for similar crops and livestock across regions (Barthelmie, 2022; FAO, 2015; Mrowczyńska-Kamińska et al., 2021). For example, in the European economies, vegetable production is more carbon-intensive (grams of carbon dioxide associated with the production of one unit of electricity in Kw/h) than its related production in the industrialised and Southeast Asia. Conversely, Asia is more carbon intensive in cereal production than Europe. The difference is associated with the type of cereal produced. For example, because of the decomposition
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of organic matter in paddy fields, rice (commonly grown in Asia) has a higher carbon intensity than wheat. Furthermore, while the volume of loss of some foods like meat could be relatively small, their contributions to climate impact, expressed in carbon footprint, are huge when compared to plant-based food (FAO, 2015; Poore & Nemecek, 2018). The carbon footprint of food waste is the total amount of greenhouse gases emitted throughout its life cycle, and it is measured in kg of CO2 equivalents. For example, meat contributes less than 5% of total food losses. Unfortunately, it contributes more than 20% of the carbon footprint associated with food losses. This is because the calculation of the carbon footprint of meat waste takes into consideration all the processes that lead to meat production. These include fertilizer used to produce the feed, emission from ruminants and those related to manure management. Consequently, it is a cause for concern and necessitates that emission reduction strategies should focus on major climate hotspot foods such as cereals and meat. Also, although the consumption phase of the food production chain accounts only about 22% of total food losses, it contributes to 37% of the carbon footprint associated with food losses (FAO, 2015). This is because the closer the food is to the table (e.g. 1 kg of rice), any loss will have a higher carbon intensity associated with harvesting, transportation and processing compared to a similar quantity of food lost at an earlier stage (e.g. 1 kg of rice during harvesting) of the production chain. Tracing these pathways that greenhouse gas emissions occur in the food production chain constitutes an essential prerequisite in restructuring the agricultural sector with a view of imbibing ways of addressing the weaknesses of the supply chain, curbing emissions and achieving a productive agricultural system.
3 Agricultural Changes Necessary to Mitigate and Adapt to Climate Change 3.1 Concepts and Principles for Sustainable Agriculture: Climate-Smart Agriculture In the course of human quest in achieving sustainability in agriculture and a productive society, it has become clearer that ‘holistic’ approaches are needed that take into cognizance climate-smart agriculture (CSA), agroforestry, conservation agriculture and agro-ecology (Klauser, 2021; Leakey, 2019). Many authors contend that climate-smart agriculture incorporates many of the field-based and farm-based sustainable agricultural land management strategies that are already well known and in widespread use, including residue management, agroforestry and conservation tillage (Abhilash et al., 2021; FAO, 2010). This is because the application of these fields and farm practices, as well as how they might be enhanced in light of a changing climate, has, meanwhile, received the majority of attention in climate-smart agriculture.
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Climate-smart agriculture (CSA), according to FAO, is a strategy for changing food and agricultural systems to promote sustainable development and protect food security in the face of climate change (FAO, 2019a). It is a crucial method of addressing the interconnected problems of food security and climate change by managing the landscapes’ crops, livestock, forests and fisheries (World Bank, 2018a, 2021a). To maintain crop output, CSA can contribute to adaptation and mitigation techniques. For instance, CSA improves soil properties, water and fertilizer usage efficiency, and yield stability and strengthen carbon capture, all of which help to produce agricultural systems that are more climate resilient (Abhilash et al., 2021; FAO, 2019b). CSA was introduced at the 2010 Hague Conference on Agriculture, Food Security, and Climate Change and is a pathway to contribute to the attainment of sustainable progress (Amin et al., 2015; Klauser, 2021). This contemporary pattern of agriculture is based on the premise of achieving triple success: increased food productivity, enhanced resilience and reduced emissions. Although CSA is based on existing technology, knowledge and principles of sustainable agriculture, it is distinct in some aspects. The approach captures the pathways in the agricultural production chain (cradle to grave) that address emissions, such as food losses; considers the synergies and trade-offs between productivity, mitigation and adaptation; and takes into cognizance new funding opportunities and reduces the deficiency in investment. It addresses the interlinked challenge of accelerating climate change and food security (availability, stability, access and utilisation). While ensuring environmental health, CSA seeks to sustain the quality of food produced and maintain an acceptable quantity of food and cultural satisfaction of societies. This in turn is contributing in reducing vulnerability to poverty in societies and hunger and enhancement of fullness of life, especially for those with huge reliance on climate-sensitive livelihoods. In this regard, CSA falls within the confines of sustainability and captures most of the sustainable development goals and their interconnectedness, such as goal number 2 on zero hunger, 4 on descent job and economic growth, 13 on climate action, 12 on responsible consumption and production and 14/15 on life on land and below water (Anukwonke et al., 2022; Klauser, 2021). In achieving the triple success of CSA, trade-offs must frequently be made (FAO, 2017a). In order to do this, we must consider the pathways that hamper the agricultural system, find synergies and evaluate the advantages and disadvantages of various choices in light of the stakeholder objectives discovered through participatory methods. In addition, CSA upholds ecosystem services and adopts a landscape strategy that expands on the ideas of sustainable agriculture while moving beyond the constrained sectoral strategies that lead to competing and uncoordinated land uses and toward integrated planning and management (CCAFS, 2022; FAO, 2017a). While CSA is a method for directing measures to change agri-food systems toward environmentally friendly and climate-resilient practices, it also aids in achieving other globally recognised objectives like the Sustainable Development Goals (SDGs) and the Paris Agreement (UNFCCC, 2021). CSA supports the FAO Strategic Framework 2022–2031, which is anchored on the ‘four betters’ – better productivity, better
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nutrition, better environment and a better living for everyone, leaving no one behind. The strategic framework of FAO suggests that the strategy be implemented through five action points: boosting the funding and finance alternatives, strengthening national and local institutions, supporting enabling policy frameworks and applying CSA practices at the field level. Many of the strategies that make up CSA already exist globally and are utilised by farmers to manage a variety of production risks, despite the fact that the idea is new and continually evolving (CCAFS, 2022). In order to mainstream CSA, a thorough inventory of current practices, future-looking behaviours and institutional and financial enablers for CSA adoption must be done. The creation of technologies and practices, the production of climate change models and scenarios, information technologies, insurance plans, value chains and the improvement of institutional and political enabling environments are just a few of the many entrance points for CSA. It therefore incorporates various interventions at the food system, landscape, value chain or policy level in addition to just a few technologies at the farm level. In addition to providing potential for agricultural sector development and economic progress, CSA technology and practices offer ways to address the difficulties posed by climate change. Consequently, a practice is said to be CSA if it advances food security and at least one of the other CSA goals of mitigation and/or adaptation to climate change (FAO, 2018a). Around the world, CSA refers to thousands of technologies and methods. According to evidence from the literature, farmers are utilising a number of agricultural innovations either from native knowledge or new technology, such as conservation agriculture, intercropping/crop diversification, terracing, enhanced seedling and integrated soil fertility management to increase their capacity for climate change and variability adaptation. The variation of these methods and their application means a CSA method should be created in a context- specific way, taking into consideration local climatic and environmental, market, economic and cultural variables, in order to be as successful as feasible (Celeridad, 2018).
3.2 The Action Plans for Realising CSA: Mitigation and Adaptation Strategies Around the world, there is growing interest in CSA interventions. These interventions take into consideration different elements such as policies, investments, institutions and technologies, harmonised in local contexts and applicable off-farm and on-farm (FAO, 2021; Matteoli et al., 2021). These interventions are usually referred to as ‘mitigation and adaptation and strategies’. While mitigation proffers ways to reduce the impacts of climate change, adaptation seeks to chart pathways to accommodate and live with the changing climate. These strategies are mutually applied and have been evolving (Rasul & Sharma, 2016). To facilitate this in agriculture, the FAO’s five action plans for CSA implementation, which mitigate and adapt to
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climate change and ensure sustainable food production, serve as the foundation to achieve the triple win of CSA: increased productivity, enhanced resilience and reduced emissions. These action plans are as follows: widen the base of evidence, support planning and enabling policy frameworks, boost local and national institutions, expand available financing and put procedures into action in the field. Although the various agricultural sub-sectors face specific challenges in achieving the triple win of CSA, these sub-sectors are interconnected (Matteoli et al., 2021). Thus, understanding this interconnectedness provides better tools to strengthen synergies within and across the sub-sectors, while reducing the trade-offs. These considerations constitute the highlights of this section. Firstly, a sound evidence base is a crucial enabling factor in developing agricultural policy. This should capture the current and projected impact of climate change in the specific economy and identify key areas of vulnerabilities (FAO, 2017a; Rosenstock et al., 2019). Therefore, a key component of enhancing nations’ ability for adaptation is expanding the evidence base. Assessing the effects of climate change and greenhouse gas (GHG) emissions from agriculture and food systems, finding and analysing climate-smart alternatives within the context of sustainable development, determining the institutional and financial requirements for implementation and, of course, information obtained through the feedback loop of monitoring and evaluation are just a few examples. Governments should be able to respond to inquiries like these with the help of the information gathered. This information gathered should respond to questions such as the following: What are the most probable climatic consequences at the sectoral and sub-sectoral levels, and how do the time frames connected to those impacts influence the timeline of adaptation interventions? What is the relationship between the costs of adaptation for a particular sector or sub-sector and the revenues and benefits to livelihoods that are anticipated to result? Would boosting imports and diversifying the local, regional and national economy be a better use of these investments? The promotion of a gender-responsive strategy is one significant part of developing the evidence basis, which is a fundamental emphasis of climate-smart agriculture (FAO, 2021). As a result, this stage should involve gathering data that has been broken down by sex and doing a gender analysis. It serves as the foundation for agricultural policies and project design that encourage the equality and equity of opportunity for men and women in this way (FAO, 2017a). After a strong evidence base is established, a unified national CSA plan (policy) is created. This plan serves as a guide for integrating agriculture-related climate change measures into relevant sectoral plans and strategies; existing policies are revised and new policies are developed as necessary to create the right conditions for implementing prioritised CSA options, set the right incentives, remove obstacles to adoption and account for potential trade-offs (FAO, 2017a). It is necessary to perform a thorough analysis of present policies and their intended and unforeseen effects on the top goals for national development. The objective is to provide guidance for the modification and development of policies and guarantee the highest level of policy coherence, supported by inclusive decision-making procedures and multi-stakeholder discussion.
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Coordinated planning and policy coherence across sectors allow for the identification of pertinent interlinkages, the enhancement of synergies and the avoidance, at the very least minimisation, or compensation of potential trade-offs (Lewis & Rudnick, 2019). There may be trade-offs between current policies enacted to increase the priority area of agricultural production and goals for adaptation and mitigation as well as for the sustainable use of natural resources. For instance, providing fossil fuel or energy subsidies to pump irrigation water in arid areas may temporarily boost output. However, in the long run, they may lead to energy loss and overuse of water resources, which would ultimately weaken farmers’ resilience (FAO, 2017a). Similarly, increasing the share of bioenergy usage as an alternative to fossil in agricultural systems should consider the huge water needs associated with this renewable energy option (Liu et al., 2018). Thus, synergies and trade-offs should take into consideration several parameters, especially local priorities. The tenure rights of food producers are a crucial factor to take into account when planning climate-smart agriculture operations (FAO, 2017a). Numerous techniques endorsed by CSA programmes, such agroforestry or conservation agriculture, need upfront investment and take time to reap the rewards. The only way to ensure that agricultural producers would profit from such investments is to have solid tenure rights to cultivated land. Adopting advocated methods is sometimes hampered by weak or absent tenure rights since there is a danger of being evicted, especially for women and indigenous people. Social protection programmes and initiatives may be significant components of the CSA implementation process and contribute to national efforts on social protection and equality, depending on the socio-economic background and preferred climate-smart agricultural alternatives (FAO, 2017a; FAO, 2018b). Food vouchers, cash transfers, risk insurance and the transfer of productive assets are examples of social protection policies that directly reduce the poverty of low-income food producers and increase their access to essential services For example, in India, climate- risk insurance policies have been developed that cover one million farmers against crop losses related to extreme weather events (CCAFS, 2015). This, in turn, strengthens the beneficiaries’ capacity for production and empowers them to invest in more creative, resilient and sustainable farming techniques as well as to engage in economically profitable activities. Thirdly, highly technical procedures that involve institutional coordination across all economies in wealthy and developing countries are needed. This is because CSA implementation is knowledge-intensive and inventive. Consequently, building capacity is a crucial component of this process (FAO, 2017a). Institutions serve as the organisational force for those who make decisions about what to eat and as a means of scaling up and maintaining CSA (CCAFS, 2022). Three alternative scales, regional, national and local, should be built to create the appropriate institutional capacity. According to the Consortium of International Agriculture Research Centers (CGIAR) Research Program on Climatic Change, Agriculture and Food Security, national institutions often play a crucial part in the provision of knowledge about technology and management alternatives, climate variability and predictions and market circumstances (CCAFS, 2015). For example, these institutions, through
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research, can harmonise scientific and traditional knowledge and make available climate forecast to farmers and advise them on certain areas where planting could be avoided. This approach reduces economic losses. Similarly, these organisations may support local farmers, increase their responsiveness to climate change and promote climate-smart methods that can reduce the negative impacts of agriculture on the environment. Building and promoting multi-stakeholder networks, collaborations and platforms is an efficient strategy to guarantee the growth of institutional capacity across different levels (FAO, 2017a, 2019c). These may make it easier to, for instance, create innovations for climate-smart agriculture together, produce data to support the knowledge-intensive decision-making processes involved in CSA or put CSA alternatives into practice on the ground. The fourth action plan is to expand available financing. Many climate-smart agriculture solutions have shown positive economic returns on investment, and long- term advantages of CSA adaptation and mitigation strategies can be anticipated for national economies and food security (FAO, 2017a). The development of sustainable agriculture in poor nations can be facilitated by climate-smart agriculture through the mobilisation of additional financial resources from bilateral partners and international climate financing instruments (Csaky et al., 2017; Opeyemi et al., 2021). Climate financing and official development aid for CSA may boost public domestic and private sector investments in CSA, particularly financial services, and help developed nations reach their USD 100 billion climate finance objective (World Bank, 2021b). There are also several funds available that poor nations can access to facilitate the implementation of CSA. These funds include the Green Climate Fund (GCF), Global Environmental Facility (GEF), Official Development Assistance (ODA), National Sectoral Budgets, private-orientated investment and many other sources of finance (Chiriac et al., 2020; FAO, 2019a). For example, REDD+, Reducing Emissions from Deforestation and Forest Degradation, is an illustration of a finance system for sustainable forest management, plus the sustainable management of forests, and the conservation and enhancement of forest carbon stocks (IFC, 2016). With the help of this method, poor nations may get compensation for the carbon that forests store. REDD+ can be a useful tool for developing countries to continue storing carbon on their forested land and pursue the associated adaptation and livelihood co-benefits given the costs associated with sustainable forest management and the lost economic opportunities associated with alternative land uses, like crop or livestock production (Negra & Wollenberg, 2011). Similarly, the International Atomic Energy Agency (IAEA), FAO, World Bank and African Development Bank (AfDB) are also some of the organisations driving the implementation and funding of climate-smart agriculture (UNFCCC, 2021). These organisations support CSA in addressing the causes and effects of climate change by monitoring agrochemical inputs for improving food safety, developing cutting-edge land and water management technology packages and enhancing carbon sequestration through innovative land-water management practices. Nuclear technology has the potential to support climate-smart agriculture in a number of
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ways, including evaluating the effects of agricultural practices on climate change; assessing the effects of climate change on agriculture; creating technologies for adaptation, such as induced crop mutation that are resistant to abiotic stressors, enabling them to flourish in a variety of environmental situations; water-saving technology solutions; resilience building to climate change; and enhancing agricultural practices to support climate change mitigation. The fifth action plan is to put the procedures into action in the field. This should capture the main goals of CSA which seek to increase the capacity of individual food producers and other food system stakeholders to create efficient, resilient and sustainable food production systems and value chains in the context of reducing greenhouse gas emissions and adapting to climate change (FAO, 2019a). Additionally, it may entail choosing flexible and appropriate CSA possibilities and aims at involving the peasant farmers according to their expertise, needs and priorities. The actions in the field should address the numerous strategies for resource use efficiency, strengthen synergies and design pathways to reduce and accommodate trade-offs while seeking to achieve the goals of climate-smart agriculture. Let us examine how the goals of CSA can be achieved in the field (farm) until the food reaches the consumer’s table.
3.3 Application of CSA to Mitigate and Adapt to Climate Change: Farm to Table At the farm level, several CSA approaches such as use of cleaner agricultural equipment, nutrient-rich livestock feed, the use of higher-yielding seed and animal varieties and the precise, timely and well-dosed application of fertilizers and pesticides can all increase the productivity of a system while lowering the need for external inputs, for example, use of cleaner agricultural equipment like diesel exhaust and generating biofuel from agricultural wastes, e.g. transforming wastes such as wheat, rice and corn straws and palm oil mill effluent (POME) to bioenergy (Gathorne- Hardy, 2016; Panpatte & Jhala, 2019). These approaches will reduce greenhouse gas emissions per hectare, improve air quality and reduce exposure of farmers to air pollution. Similarly, by increasing the recycling of wastes and by-products as inputs within food production systems or the larger value chain, the utilisation of such inputs may be further decreased and extend the lifespan of our resource base (FAO, 2017b). Utilising agricultural leftovers, agro-industrial waste products like oilseed cake or manure as fertilizer are a few examples. Climate-smart agriculture can address the effects of climate change by creating new varieties of seeds that are tolerant to heat, accommodate pest diversity, salinity and resistant to floods and droughts (Amin et al., 2015). Such agricultural technologies conserve resources, sustain yield and reduce emissions. Similarly, management of pests and diseases can be a key tactic for increasing the effectiveness of resource utilisation. Healthy organisms, including both plants and animals, may make better
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use of agricultural inputs like fertilizers, cattle feed and fish feed, which raise the total productivity of the corresponding production system. Additionally, pest and disease management lowers the possibility of agricultural or animal losses, which would increase output. Through effective water management, such as use of drip irrigation or energy- efficient irrigation on agricultural lands, especially in water-stressed regions, the amount of fossil fuel burnt for the agricultural activity per hectare is reduced (Caldera et al., 2021; Klauser, 2021). Similarly, strengthening capacity for using green energy or energy-efficient mechanisation also reduces emission. Improved management of organic wastes by encouraging aerobic decomposition through the process of composting, or incorporating soil for the duration of the off-term drainage, can all reduce methane (CH4) emissions caused by rice cultivation, usage of rice types with a better harvest index, more oxidative roots and fewer sterile tillers, as well as the use of fermented compost instead of unfermented fertilizer as biogas slurry (Amin et al., 2015). Reduced tillage, enhanced use of manure and organic wastes improve the integration of soil and its biodiversity. While soil tillage is important to ensure increase in crop production, it is essential to identify crops in specific environments that can accommodate reduced tillage and sustain yield (Valujeva et al., 2022). Also, partial covering of the soil might be extremely important for the build-up of carbon content in the soil. Crop diversification, alley cropping and agroforestry can disrupt disease cycle and improve pest control, interaction of useful soil bacteria, suppress weed development, increase yield, strengthen carbon capture, reduce soil erosion, enhance nutrient and water use efficiency and reduce farmers’ vulnerability to shocks (Barman et al., 2022; Siarudin et al., 2021; Wolz et al., 2018). They also strengthen land-use efficiency and enhance soil quality. Expanding into different crops or animal species and utilising integrated agricultural techniques like crop-livestock (silvopastoral) systems, agroforestry or mixed crop-aquaculture-livestock systems are all examples of diversification. This makes it possible to spread risks among various agricultural operations that are exposed to climate pressures and weather extremes to varying degrees, hence decreasing the revenue volatility of food producers. Also, creating a favourable microclimate for crops growing beneath shade trees in agroforestry systems, for instance, can reduce heat stress and boost the resilience of the entire production system (FAO, 2017a). Efficient soil management through the application of appropriate techniques to accommodate soil organic carbon, reduce use of chemical fertilizer and enhance the use of livestock excrement (organic fertilizer) can achieve reduction in the input of resources, curb emissions per hectare of food produced, increase crop yield and reduce farmers’ resilience to shocks (Kitamura et al., 2021; Owoade, 2020; Tuğrul, 2019). For example, organic fertilizers are preferred to chemical fertilizers because they improve soil texture and aeration, facilitate soil-water retention, stimulate the development of healthy roots and impede processes that lead to nitrous oxide emissions (Lazcano et al., 2021). Similarly, strengthening ground cover through reducing tillage and crop rotation in order to reduce erosion and land degradation is
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interconnected to processes that increase crop yield, enhance carbon capture and reduce emission of greenhouse gases. From harvest to table, reducing food losses can be achieved through creation of awareness, policy formulation, capacity development, incentives and redesign of the incentive mechanism; enhancement of sustainable consumption and production; strengthening of infrastructures to reduce spoilage/deaths in high crop/livestock production season; increasing linkages along the food chain; strengthening of food handling, packaging and logistic; and providing financing mechanism to farmers (Igeta & Nakamura, 2022; Lee & Jung, 2017; Pakravan-Charvadeh & Flora, 2022). The inevitable food wastes generated at the table or during food processing can be transformed to boost energy security and reduce methane emissions, while the residue can be used to improve soil nutrient, boost carbon capture and increase productivity (Panpatte & Jhala, 2019). These climate-smart approaches that ensure enhanced productivity, reduced emissions and enhanced farmers’ resilience are summarised diagrammatically (Fig. 6.1). These approaches can be efficiently achieved in a system where there is provision of funds; appropriate programmes and policies that are characterised with equality, equity and justice; infrastructures; local and national institutions; international cooperation; and goodwill.
3.4 Climate-Smart Investments, Prospects and Challenges Globally, CSA technology is developing with support from many international organisations in order to accomplish the triple win of increased production, resilience and greenhouse gas reduction. Over US$2.5 billion has been invested in these three areas of the CSA’s strategic goals, with the potential to benefit over 80 million people in nations including Zimbabwe, Bangladesh, Zambia, Mali, Congo, Morocco, Lesotho, Burkina Faso, Ghana and Cote d’Ivoire (World Bank, 2021a). Unfortunately, these are not the only countries with climate-sensitive livelihoods. A number of World Bank-funded initiatives in China promote institutions and practices for resilient and low-emission agriculture, totalling US$755 million. Through enhanced water usage efficiency on 44,000 hectares of farmland and innovative technology that have improved soil conditions and increased output of rice by 12% and maize by 9%, one project has contributed to the growth of climate-smart agriculture (World Bank, 2021b). Through this programme, more than 29,000 farmer cooperatives have reported greater revenues and increased climate resilience. Another project that is now finished has enhanced the soil carbon sink by 71,683 tonnes of CO2 and decreased greenhouse gas emissions by 23,732 tonnes of CO2 equivalent. A project in Bangladesh seeks to strengthen the adaptability of livestock farmers by enhancing animal health and addressing climate mitigation by enhancing emission intensity and improving production efficiency (FAO, 2014). This includes enhancements to feeding methods, animal health, breeding, manure and
These can be achieved in a system where there is provision of funds, appropriate policies and programs,infrastructures,local and national institutions,international cooperation and goodwill.
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Fig. 6.1 Agricultural changes necessary to achieve the triple win of CSA 1. Increase farmers’ income and enhance resilience 2. Strengthen soil quality and increase carbon capture 3. Enhance soil nutrient and increase productivity 4. Provide the necessary water needs and increase productivity 5. Strengthen efficiency in resource utilisation and reduce emission 6. Reduce emission per hectare 7. Reduce energy utilisation in the production chain 8. Transforming agricultural wastes to bioenergy curbs emissions 9. Increase production using organic nutrient 10. Reduce energy utilisation for production by reducing food losses associated with harvesting 11. Appropriate timing in harvesting increases productivity 12. Timely harvesting reduces unnecessary inputs, maximises resource use and reduces emissions 13. Strengthening transportation facilities reduced food spoilage and increase productivity 14. Reducing food losses associated with transportation assists in reducing emissions related to production and enhance resilience 15. Improved infrastructure in storage/packaging reduces food losses and increases production, reduces emissions associated with production and enhances resilience 16. Sustainable consumption policies reduce food wastes and reduce emissions, strengthen environmental quality and increase productivity and enhance farmers’ resilience 17. Increased productivity enhances farmers’ income and resilience to shocks 18. Reduced emissions strengthens environmental health and increases productivity 19. Increase in sustainable production reduces emissions, guarantees farmers’ health and enhances resilience to shocks
waste management, and low-emission technologies for tasks like milk chilling and transport. Brazilian researchers investigated methods for agricultural expansions to support low-carbon agriculture while increasing private profitability as part of the sustainable production in areas previously converted to Agricultural Use Project (ABC
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Cerrado) (FAO, 2019a). A total of 20,025 direct beneficiaries (20% female) received technical support and training from the initiative between 2014 and 2019. These people comprised farmers and their families, attendees at field days and associates who were helping 378,513 hectares of land be managed sustainably. Over the following 10 years, it is predicted that these activities will help sequester 7.4 million tonnes of CO2 equivalent. The Colombia Mainstreaming Sustainable Cattle Ranching Project showing those silvopastoral systems (SPS), when combined with additional tools for landscape management, technical support and incentives, may result in notable successes for both farmers and the environment (World Bank, 2019). Participating farmers converted 38,390 hectares of pastureland to SPS throughout the course of the project’s 10 years (2010–2020). Milk productivity improved by roughly 25% compared to producing regions without SPS, milk production costs dropped by 9% per litre, animal stocking rate rose by 26%, and farmer revenue increased by as much as $523 per hectare annually. As a consequence of the Mexico Sustainable Rural Development initiative, 1842 agribusinesses implemented 2286 eco-friendly technologies, including sustainable waste management, renewable energy and energy-efficient technology (World Bank, 2019). Similarly, in Uzbekistan, the World Bank is collaborating with the government to support a transition away from cotton and wheat monoculture toward a more resilient agricultural system that incorporates horticulture and uses climate- smart techniques that enhance soil health and lessen land degradation (FAO, 2019a). Through the distribution of improved, drought-tolerant seeds, more effective irrigation and increased use of forestry for farming and conservation agriculture practices, a bank-supported project in Niger that is specifically created to deliver climate-smart agriculture seeks to assist 500,000 farmers and pastoralists in 44 communes (Nkonya et al., 2018; World Bank, 2018b). The project has helped 336,518 farmers manage their land more sustainably and changed the farming techniques on 79,938 hectares so far. Improving water usage productivity in irrigated agriculture is the primary goal of the Pakistan Punjab Irrigated Agriculture Productivity Improvement Program Project (Pasha, 2015; Rasool & Hassan, 2017). The initiative helps to raise living standards, agricultural productivity, employment and incomes while also having a good impact on the environment. As of 2019, 23,500 hectares of high-efficiency irrigation systems had been installed, and work on installing systems covering an additional 3677 hectares was ongoing. Additionally, 11,916 watercourses had been improved, and work on improving another 1220 was ongoing. Moreover, 5000 laser land-levelling units had also been deployed, and 621 ponds had been built. The initiative has produced more than 15,000 full-time employments; improved water management benefits 5.7 million acres of agriculture and directly benefits 500,000 agricultural households. The Climate-Smart Agriculture Project’s goal in Kenya is to help smallholder farming and pastoral communities become more resilient to the dangers associated with climate change (FAO, 2019a). In order to do this, climate-smart agriculture practices must be expanded, agricultural seed systems must be strengthened, and agro-meteorological, market, climatic and consulting services must be supported.
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Beginning 2015, a programme funded by the World Bank has been assisting pastoralists in the Sahel, specifically in Burkina Faso, Chad, Mali, Mauritania, Niger, and Senegal, to embrace climate-smart agriculture. Initiatives to enhance rangeland management, animal health and animal rearing are increasing production and resilience and lowering emissions. Similarly, the bank is boosting CSA in Malawi by helping farmers be more resilient to recurring and severe droughts and by raising soil health for greater agricultural output and the adaptation and mitigation of climate change (CIAT, ICRISAT, BFS/USAID, 2020). A variety of CSA methods have been followed by almost 140,000 farmers, and roughly 28,000 hectares of land now have better soil health. The Maharashtra Project for Climate Resilient Agriculture, one of the biggest CSA projects the bank has funded to date at US$420 million, is anticipated to provide US$386 million in climate change benefits (World Bank, 2021b). As of June 2020, 56,602 hectares of land have benefited from enhanced irrigation and drainage technology, and 309,800 project beneficiaries have embraced climate-smart agricultural practices. While the global climate is likely to keep changing and the necessity to keep employing technology and genetic diversity in agriculture (Begna, 2022), invasive species and new diseases among others are issues that will continue to face mankind. Similarly, with no specific formula to climate change adaptation and mitigation across regions, improving knowledge on microclimate changes that can sustain local food production and meet the needs of societies remains frontiers of research. Again, one of the tenets to achieve CSA is that it takes into cognizance new funding opportunities and reduce the deficiency in investments. Despite the availability of these funds, technologies and registered successes in CSA, the resources needed to access these climate-smart approaches and measuring the efficiency of an approach are quite challenging in some regions of the world, especially to those who are dependent on climate-sensitive livelihoods (CIAT & World Bank, 2018; FAO & ICRISAT, 2019; Jellason et al., 2018). The concern of accessing funds and technology are made worse when violent conflicts undermine local and international cooperation and knowledge sharing (Fang et al., 2020). Even when these technologies and funds are made available, it is essential to consider gender parity and equity if the goal is to seek a productive and resilient society (Fapojuwo et al., 2018). Ensuring that everyone have access to this knowledge and funds, especially with the prevalence of subsistence farming in developing countries, is an issue that needs consistent examination in our agenda for achieving sustainable development.
4 Conclusions The impacts of climate change and alterations on agriculture and the socio-economic system as a whole are growing worrisome. Following the complex nature of this challenge, mankind has only an exit route – designing pathways to live with the changing climate. These pathways have been evolving, and in the agricultural sector, CSA is the contemporary approach to mitigate and adapt to climate change.
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This is aligned to its scope of embracing all existing agricultural techniques and also characterised with innovations such as new funding opportunities and reducing the deficiency in investments, with a view of achieving increased productivity, enhanced resilience and reduced emissions. Achieving this triple win requires a comprehensive and coordinated strategy from all parties involved in the agricultural chain, ensuring no one is left behind. While the global climate continues to keep rising, there are variations across regions with different levels of impacts on agriculture. Consequently, there is no unique formula to address the challenges across the globe. Thus, consistent consideration of local priorities, enhanced synergies and reduced trade-offs remain issues at the frontiers of research that needs a multidisciplinary approach.
References Abegunde, V. O., & Obi, A. (2022). The role and perspective of climate smart agriculture in Africa: A scientific review. Sustainability, 14(4), 1–15. https://doi.org/10.3390/su14042317 Abhilash, A. R., Arti, K., Ram, N. S., & Kavita, K. (2021). Climate-smart agriculture: An integrated approach for attaining agricultural sustainability. In V. K. H. Mallappa & M. Shirur (Eds.), Climate change and resilient food system. https://doi.org/10.1007/978-981033-4538-6-5 Akanwa, A. O., Mba, H. C., Ogbuene, E. B., Nwachukwu, M. U., & Anukwonke, C. C. (2019). Potential of agroforestry and environmental greening for climate change minimization. In R. Abhishek et al. (Eds.), Climate change and agroforestry system (p. 389). International Standard, CRC-Apple Academic Press and Taylor & Francis. Akinnagbe, O. M., & Irohibe, I. J. (2014). Agricultural adaptation strategies to climate change impacts in Africa: A review. Bangladesh Journal of Agricultural Research, 39(3), 407–418. https://doi.org/10.3329/bjar.v39i3.21984 Ali, N., Hu, X., & Hussain, J. (2020). The dependency of rural livelihood on forest resources in Northern Pakistan’s Chaprote Valley. Global Ecology and Conservation, 22, 1–11. https://doi. org/10.1016/j.gecco.2020.e01001 Amin, A., Mubeen, M., Hammad, H., & Nasim, W. (2015). Climate smart agriculture: An approach for sustainable food security. Agricultural Research Communication, 2(3), 13–21. Anabaraonye, B., Okafor, J. C., Ewa, B. O., & Anukwonke, C. C. (2021). The impacts of climate change on soil fertility in Nigeria. In D. K. Choudhary, A. Mishra, & A. Varma (Eds.), Climate change and the microbiome. Soil biology (Vol. 63, pp. 606–621). Springer. https://doi. org/10.1007/978-3-030-76863-8_31 Ancha, P. U., Shomkegh, S. A., & Onuche, P. (2019). Contribution of Odoba forest reserve to livelihoods of the rural people in Ogbadibo Local Government Area, Benue State, Nigeria. Asian Journal of Environment and Ecology, 9(1), 1–12. Anuga, S. W., Gordon, C., Boon, E., & Surugu, J. M.-I. (2019). Determinants of climate smart agriculture (CSA) adoption among smallholder food crop farmers in the Techiman Municipality, Ghana. Ghana Journal of Geography, 11(1), 124–139. https://doi.org/10.4314/gjg.v11i1.8 Anukwonke, C. C., Tambe, E. B., Nwafor, D. C., & Malik, K. T. (2022). Climate change and interconnected risks to sustainable development. In S. A. Bandh (Ed.), Climate change: The social and scientific construct (pp. 71–78). Springer International Publishing. https://doi. org/10.1007/978-3-030-86290-9_5 Bandh, S. A. (2022a). Climate change: The social and scientific construct (1st ed.). Springer. https://doi.org/10.1007/978-3-030-86290-9
108
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Bandh, S. A. (2022b). Sustainable agriculture: Technological progressions and transitions (1st ed.). Springer. https://doi.org/10.1007/978-3-030-83066-3 Bandh, S. A., Shafi, S., Peerzada, M., Rehman, T., Bashir, S., Wani, S. A., & Dar, R. (2021). Multidimensional analysis of global climate change: A review. Environmental Science and Pollution Research International, 28(20), 24872–24888. https://doi.org/10.1007/ s11356-021-13139-7 Bandh, S. A., Parray, J. A., & Shameem, N. (2022). Climate change and microbial diversity: Advances and challenges (1st ed.). Apple Academic Press. https://www.routledge.com/Climate- Change-a nd-M icrobial-D iversity-A dvances-a nd-C hallenges/Bandh-Parray-S hameem/p/ book/9781774637821 Bandh, S. A., Malla, F. A., Qayoom, I., Mohi-ud-Din, H., Butt, A. K., Altaf, A., Wani, S. A., Betts, R., Truong, T. H., Pham, N. D. K., Cao, D. N., & Ahmed, S. F. (2023). Importance of blue carbon in mitigating climate change and plastic/microplastic pollution and promoting circular economy. Sustainability, 15(3), 2682. https://doi.org/10.3390/su15032682 Barman, A., Saha, P., Patel, S., & Bera, A. (2022). Crop diversification an effective strategy for sustainable agriculture development. In V. S. Meena, M. Choudhary, R. P. Yadav, & S. Kumari (Eds.), Sustainable crop production (pp. 1–18). IntechOpen. https://doi.org/10.5772/ intechopen.102635 Barthelmie, R. J. (2022). Impact of dietary meat and animal products on GHG footprints: The UK and the US. Climate, 10(3), 1–18. https://doi.org/10.3390/cli10030043 Begna, T. (2022). Effect of climate change on crop genetic diversity and productivity. International Journal of Novel Research in Civil Structural and Earth Sciences, 9(1), 1–10. Brack, D. (2019). Forests and climate change. United Nations Forum on Forests. Caldera, U., Sadiqa, A., Gulagi, A., & Breyer, C. (2021). Irrigation efficiency and renewable energy powered desalination as key components of Pakistan’s water management strategy. Smart Energy, 4. https://doi.org/10.1016/j.segy.2021.100052 CCAFS. (2015). Six steps to success. CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). CCAFS. (2022). What is climate smart agriculture. Research program on climate change, agriculture and food security. Wageningen University and CCAFS. https://ccafs.cgiar.org/ climate-smart-agriculture Celeridad, R. (2018). Contextual and universal: Scaling context-specific climate-smart agriculture. World Agroforestry Centre. https://ccafs.cgiar.org/blog/contextual-and-universal-scaling- context-specific-climate-smart-agriculture#.XLYjytJKhdi Chiriac, D., Naran, B., & Falconer, A. (2020). Examining the climate finance gap for small-scale agriculture. Climate policy initiative and IFAD. Crippa, M., Solazzo, E., Guizzardi, D., Monforti-Ferrario, F., Tubiello, F. N. & Leip, P. (2021). Food systems are responsible for a third of global anthropogenic GHG emissions. Nature Food, 2, 198–209. https://doi.org/10.1038/s43016-021-00225-9 Csaky, E., Frei-Oldenburg, A., Hess, U., Kuhn, S., Miller, C., Varangis, P., & Perry, D. (2017). Climate smart financing for rural MSMEs: Enabling policy frameworks. G20 Global Partnership for Financial Inclusion (GPFI). European Commission. (2013). The impact of EU consumption on deforestation: Comprehensive analysis of the impact of EU consumption on deforestation. European Commission. Fang, X., Kothari, S., McLoughlin, C., & Yenice, M. (2020). The economic consequences of conflict in sub-Saharan Africa. International Monetary Fund (International Myeloma Foundation). Fapojuwo, O. E., Ogunnaike, M. G., Shittu, A. M., Kehinde, M. O., & Oyawole, F. P. (2018). Gender gaps and adoption of climate smart practices among cereal farm households in Nigeria. Nigerian Journal of Agricultural Economics (NJAE), 8(1), 38–49. Food and Agriculture Organization. (2009). Global agriculture towards 2050. Food and Agriculture Organization. Food and Agriculture Organization. (2010). Climate-smart agriculture: Policies, practices and financing for food security, adaptation and mitigation. Report prepared for The Hague
6 Changes in the Agriculture Sector That Are Essential to Mitigate and Adapt…
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Conference on Agriculture, Food Security, and Climate Change October 31 to 5 November 2010. Food and Agriculture Organization. Food and Agriculture Organization. (2014). Food wastage footprint. Full cost accounting. Food and Agriculture Organization. Food and Agriculture Organization. (2015). Food wastage footprint and climate change. Food and Agriculture Organization. Food and Agriculture Organization. (2016). Food and agriculture: Key to achieving the 2030 agenda for sustainable development. Food and Agriculture Organization. http://www.fao. org/3/a-i5499e.pdf Food and Agriculture Organization. (2017a). The future of food and agriculture – Trends and challenges. Food and Agriculture Organization. Food and Agriculture Organization. (2017b). Climate-smart agriculture sourcebook (2nd ed.). Food and Agriculture Organization. http://www.fao.org/climate-smart-agriculture-sourcebook/en FOA (2018a). Climate-smart agriculture case studies 2018. Successful approaches from different regions. Rome. www.fao.org/3/CA2386EN/ca2386en.pdf FAO (2018b). Northeastern Nigeria- situation report October 2018. Food and Agriculture Organization. (2019a). Climate-smart agriculture and the sustainable development goals: Mapping interlinkages, synergies and trade-offs and guidelines for integrated implementation. Food and Agriculture Organization. Food and Agriculture Organization. (2019b). Social protection: Working towards universal coverage of social protection. Food and Agriculture Organization. http://www.fao.org/ social-protection/overview/en/ Food and Agriculture Organization. (2019c). Guidelines for the design and implementation of monitoring and evaluation systems for climate-smart agriculture. Food and Agriculture Organization. Food and Agriculture Organization. (2021). Climate smart agriculture sourcebook. Food and Agriculture Organization. http://www.fao.org/climate-smart-agriculture-sourcebook Food and Agriculture Organization, & International Crops Research Institute for the Semi-Arid Tropics. (2019). Climate-smart agriculture in the Adamawa State of Nigeria (CSA country profiles for Africa series). International Center for Tropical Agriculture (Inter-American Center of Tax Administrators), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Food and Agriculture Organization of the United Nations (FAO). Gathorne-Hardy, A. (2016). The sustainability of changes in agricultural technology: The carbon, economic and labour implications of mechanisation and synthetic fertiliser use. Ambio. Royal Swedish Academy of Sciences,, 45(8), 885–894. https://doi.org/10.1007/s13280-016-0786-5 Igeta, J., & Nakamura, H. (2022). Business incentive to reduce food losses in Japan. Sustainability, 14(4), 1–20. https://doi.org/10.3390/su14042266 Inter-American Center of Tax Administrators, & World Bank. (2018). Climate-smart agriculture in Malawi (CSA country profiles for Africa series). International Center for Tropical Agriculture (Inter-American Center of Tax Administrators). Inter-American Center of Tax Administrators, International Crops Research Institute for the Semi- Arid Tropics, & BFS/USAID. (2020). Climate-smart agriculture in Niger (CSA country profiles for Africa series). International Center for Tropical Agriculture (Inter-American Center of Tax Administrators), Bureau for Food Security, United States Agency for International Development (BFS/USAID). International Finance Corporation. (2016). REDD market overview. International Finance Corporation. IPCC. (2021). Summary for policymakers. In V. Masson-Delmotte et al. (Eds.), Climate change: The physical science basis. Contribution of working group I to the sixth assessment report of the intergovernmental panel on climate change (pp. 1–40). IPCC. Jellason, N. P., Conway, J., & Baines, R. N. (2018). Understanding impacts and barriers to adoption of climate-smart agriculture (CSA) practices in North-Western Nigerian drylands.
110
E. B. Tambe et al.
Journal of Agricultural Education and Extension, 27(206), 1–18. https://doi.org/10.108 0/1389224X.2020.1793787 Kitamura, R., Sugiyama, C., Yasuda, K., Nagatake, A., Yuan, Y., Du, J., Yamaki, N., Taira, K., Kawai, M., & Hatano, R. (2021). Effects of three types of organic fertilizers on greenhouse gas emissions in a grassland on Andosolin Southern Hokkaido, Japan. Frontiers in Sustainable Food Systems, 5, 649613. https://doi.org/10.3389/fsufs.2021.649613 Klauser, D. (2021). Climate-smart, resilient agriculture – Improving smallholders’ resilience, mitigation and profitability in all we do. Syngenta Foundation for Sustainable Agriculture. Łaba, S., Cacak-Pietrzak, G., Łaba, R., Sułek, A., & Szczepański, K. (2022). Food losses in consumer cereal production in Poland in the context of food security and environmental impact. Agriculture, 12(5), 1–17. https://doi.org/10.3390/agriculture12050665 Lazcano, C., Zhu-Barker, X., & Decock, C. (2021). Effects of organic fertilizers on the soil microorganisms responsible for N2O emissions: A review. Microorganisms, 9(983), 1–18. https:// doi.org/10.3390/microorganisms9050983 Leakey, R. B. (2019). A holistic approach to sustainable agriculture: Trees, science and global society. Burleigh Dodds Science Publishing. https://doi.org/10.19103/AS.2018.0041.25 Lee, S., & Jung, K. (2017). Exploring effective incentive design to deduce food waste: A natural experiment of policy change from community based charge to RFID based weight charge. Sustainability, 9(11), 1–17. https://doi.org/10.3390/su9112046 Lewis, J., & Rudnick, J. (2019). The policy enabling environment for climate smart agriculture: A case study of California. Frontiers in Sustainable Food Systems, 3(31), 1–12. https://doi. org/10.3389/fsufs.2019.00031 Liu, J., Hull, V., Godfray, H. C. J., Tilman, D., Gleick, P., Hoff, H., Pahl-Wostl, C., Xu, Z., Chung, M. G., Sun, J., & Li, S. (2018). Nexus approaches to global sustainable development. Nature Sustainability, 1(9), 466–476. https://doi.org/10.1038/s41893-018-0135-8 Lynch, J., Cain, M., Frame, D., & Pierrehumbert, R. (2021). Agriculture’s contribution to climate change and role in mitigation is distinct from predominantly fossil CO2-emitting sectors. Frontiers in Sustainable Food Systems, 4, 1–9. https://doi.org/10.3389/fsufs.2020.518039 Malla, F. A., Mushtaq, A., Bandh, S. A., Qayoom, I., Ho-ang, A. T., & Shahid-e-Murtaza. (2022). Understanding climate change: Scientific opinion and public perspective. In S. A. Bandh (Ed.), Climate change: The social and scientific construct. Springer Nature Publishing. https://link. springer.com/chapter/10.1007/978-3-030-86290-9_1 Matteoli, F., Schnetze, J., & Jacobs, H. (2021). Climate-smart agriculture (CSA): An integrated approach for climate change management in the agriculture sector. In J. M. Luetz & D. Ayal (Eds.), Handbook of climate change management (pp. 409–437). Springer. https://doi. org/10.1007/978-3-030-57281-5_148 Mrowczyńska-Kamińska, A., Bajan, B., Pawłowski, K. P., Genstwa, N., & Zmyślona, J. (2021). Greenhouse gas emissions intensity of food production systems and its determinants. PLoS One, 16(4), e0250995. https://doi.org/10.1371/journal.pone.0250995 Mumtaz, M., de Oliveira, J. A., & Ali, S. H. (2019). Climate change impacts and adaptation in agricultural sector: The case of local responses in Punjab, Pakistan. In S. Hussain (Ed.), Climate change and agriculture. https://doi.org/10.5772/intechopen.83553 Mushtaq, B., Bandh, S. A., & Shafi, S. (2020). Environmental management: Environmental issues, awareness and abatement (1st ed.). Springer. https://doi.org/10.1007/978-981-15-3813-1 Negra, C., & Wollenberg, E. (2011). Lessons from REDD+ for agriculture. CCAFS. Nkonya, E., Ru, Y., & Kato, E. (2018). Economics of land degradation in Niger. In Fostering transformation and growth in Niger’s agricultural sector (pp. 1–17). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-873-5_2 Obinaju, L. C., & Ikpeida, D. W. (2021). Determinants of food wastes among farming households in Uyo Local Government Area, Akwa Ibom State, Nigeria. European Journal of Agriculture and Forestry Research, 9(4), 17–33. https://doi.org/10.37745/ejafr.2013 Opeyemi, G., Opaluwa, H. I., Adeleke, A. O., & Ugbaje, B. (2021). Effect of climate smart agricultural practices on farming households’ food security in Ika North East Local Government
6 Changes in the Agriculture Sector That Are Essential to Mitigate and Adapt…
111
Area, Delta State, Nigeria. Journal of Agriculture and Food Sciences, 19(2), 30–42. https://doi. org/10.4314/jafs.v19i2.4 OPHI, & United Nations Development Program. (2019). Global multidimensional poverty index: Illuminating inequalities. OPHI and UNDP. Owoade, F. M. (2020). Soil carbon management practices, knowledge of climate change and CO2 emission of some land use types in Ogbomoso Agricultural Zone, Oyo State, Nigeria. West African Journal of Applied Ecology, 28(1), 173–188. Pakravan-Charvadeh, M. R., & Flora, C. (2022). Sustainable food consumption pattern with emphasis on socioeconomic factors to reduce food waste. International Journal of Environmental Science and Technology, 19(10), 9929–9944. https://doi.org/10.1007/s13762-022-04186-9 Panpatte, D. G., & Jhala, Y. K. (2019). Agricultural waste: A suitable source for biofuel production. In A. A. Rastegari, A. N. Yadav, & A. Gupta (Eds.), Prospects of renewable bioprocessing in future energy systems, biofuel and biorefinery technologies (Vol. 10, pp. 337–355). Springer Nature Switzerland. https://doi.org/10.1007/978-3-030-14463-0_13 Parray, J. A., Bandh, S. A., & Shameem, N. (2022). Climate change and microbes: Impact and vulnerability (1st ed.). Apple Academic Press. https://www.routledge.com/ Climate-C hange-a nd-M icrobes-I mpacts-a nd-Vulnerability/Parray-B andh-S hameem/p/ book/9781774637210 Pasha, H. (2015). Growth of the provincial economies. Institute for Policy Reforms. Poore, J., & Nemecek, T. (2018). Reducing food’s environmental impacts through producers and consumers. Science, 360(6392), 987–992. https://doi.org/10.1126/science.aaq0216 Rasool, A., & Hassan, M. A. (2017). CPEC-prospects and challenges for agriculture in Pakistan (Vision-2025). Faisalabad Chamber of Commerce and industry. http://fcci.com.pk/rte/ Agriculture-Report.pdf Rasul, G., & Sharma, B. (2016). The nexus approach to water–energy–food security: An option for adaptation to climate change. Climate Policy, 16(6), 682–702. https://doi.org/10.1080/1469306 2.2015.1029865 Rosenstock, T., Lamanna, C., Namoi, N., Arslan, A., & Richards, M. (2019). What is the evidence base for climate smart agriculture in East and Southern Africa? A systematic map: Investigating the business of a productive, resilient and low emission future. In Climate-smart agriculture papers (pp. 141–151). https://doi.org/10.1007/978-3-319-92798-5_12 Seberini, A. (2020). Economic, social and environmental world impacts of food waste on society and zero waste as a global approach to their elimination. SHS Web of Conferences, 74, 1–10. https://doi.org/10.1051/shsconf/20207403010 Siarudin, M., Rahman, S. A., Artati, Y., Indrajaya, Y., Narulita, S., Ardha, M. J., & Larjavaara, M. (2021). Carbon sequestration potential of agroforestry systems in degraded landscapes in West Java, Indonesia. Forests, 12(6), 1–13. https://doi.org/10.3390/f12060714 Tambe, E. B., Okonkwo, A. U., & Eme, L. C. (2022). Determinants of volume of POME generation in palm oil mills for planning wastewater recovery in biogas energy development. Journal of Applied Sciences and Environmental Management, 26(3), 369–376. https://doi.org/10.4314/ jasem.v26i3.1 Tuğrul, K. M. (2019). Soil management in sustainable agriculture. In M. Hasanuzzaman, M. M. Filho, M. Fujita, & T. A. Nogueira (Eds.), Sustainable crop production (pp. 1–15). IntechOpen. https://doi.org/10.5772/intechopen.88319 UNFCCC. (2021). Climate smart agriculture. https://unfccc.int/BLOG/Climate-Smart- Agriculture. UNFCCC. United Nations. (2017). The sustainable development goals report. United Nations. Valujeva, K., Pilecka-Ulcugaceva, J., Skiste, O., Liepa, S., Lagzdins, A., & Grinfelde, I. (2022). Soil tillage and agricultural crops affect greenhouse gas emissions from Cambic Calcisol in a temperate climate. Acta Agriculturae Scandinavica, Section B — Soil and Plant Science, 72(1), 835–846. https://doi.org/10.1080/09064710.2022.2097123. Section B. Wolz, K. J., Lovell, S. T., Branham, B. E., Eddy, W. C., Keeley, K., Revord, R. S., Wander, M. M., Yang, W. H., & DeLucia, E. H. (2018). Frontiers in alley cropping: Transformative solutions
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for temperate agriculture. Global Change Biology, 24(3), 883–894. https://doi.org/10.1111/ gcb.13986 Word Bank (2018a). Climate-smart agriculture. http://www.worldbank.org/en/topic/ climate-smart-agriculture World Bank (2018b). Nigeria-agricultural and livestock transformation project. https://ewsdata. rightsindevelopment.org/files/documents/09/WB-P164509 World Bank (2019). Data Bank. https://databank.worldbank.org World Bank. (2020). Nigeria food smart country diagnostic. World Bank. World Bank. (2021a). World Bank facts and sheets. World Bank. https://www.worldbank.org/en/ topic/climate-smart-agriculture World Bank. (2021b). Shaping a climate-smart global food system. World Bank. https://www. worldbank.org/en/topic/agriculture/publication/shaping-a-climate-smart-global-food-system
Chapter 7
Adaptation and Maladaptation to Climate Change: Farmers’ Perceptions Vahid Karimi , Masoud Bijani , Zeynab Hallaj Negin Fallah Haghighi , and Mandana Karimi
, Naser Valizadeh
,
Abstract Nowadays, climate change is one of the most important environmental disasters around the world and it has dramatically negative effects on agricultural productions and farmers’ communities. Furthermore, farmers are one of the most vulnerable communities to the impacts of climate change. Also, most researchers have limited their research to the biological and physical fields of environmental crises. Thus, it doubles the need for farmers’ perception and perspective on the social and economic effects of climate change. As a result, studying farmers’ perceptions and their vulnerabilities and strategies for adapting to climate change can improve the sustainability of this part of the community, which is the most important player in rural areas, especially in developing countries, and farmers’ maladaptation can be reduced with this disaster. Methodology in this research will be a systematic review analysis by extracting and analyzing articles published in Elsevier, Springer, and MDPI scientific databases between 2010 and 2022. Finally, in the field of farmers’ perception of climate change, analysis of farmers’ maladaptation in the field of climate change and identification of adaptation strategies in technical, social, and economic dimensions will be studied.
V. Karimi · M. Bijani (*) · Z. Hallaj Department of Agricultural Extension and Education, College of Agriculture, Tarbiat Modares University (TMU), Tehran, Iran e-mail: [email protected] N. Valizadeh Department of Agricultural Extension and Education, School of Agriculture, Shiraz University, Shiraz, Iran N. Fallah Haghighi Department of Technology Development Studies (DTDS), Iranian Research Organization for Science and Technology (IROST), Tehran, Iran M. Karimi Department of Sociology, University of Victoria, Victoria, BC, Canada © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 S. A. Bandh (ed.), Strategizing Agricultural Management for Climate Change Mitigation and Adaptation, https://doi.org/10.1007/978-3-031-32789-6_7
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Keywords Climate change · Foresight · Maladaptation · Farmers’ perception · Adaptation strategies
1 Introduction More than decades of research on environmental crises have revealed to the human society that anthropogenic programs and activities are among the most important effective components in mitigating or intensifying the impacts of these crises on human societies, namely, local societies (Valizadeh et al., 2021; Karimi et al., 2022). Nowadays, the phenomenon of climate change, which is one of the most important environmental crises in the current decade, has caused countries to have a deeper view at better adaptation to this crisis at the international, national, and local levels, because it had adverse effects on various social, economic, political, and environmental dimensions according to various studies and international reports (Abbasian et al., 2017; Karimi et al., 2021). For this reason, adaptation to climate change has attracted the attention of scientific and academic societies in different regions of the world, especially in developed countries in the past years, and in order to better adapt to this phenomenon, the decision-makers of all countries attempt to choose adaptation strategies to mitigate the adverse impacts of climate change (Malla et al., 2022; Bandh et al., 2021; Chi et al., 2020). Considering this issue, the terms “adaptation” and “vulnerability” are widely used to describe responses to climate change (Smith & Brown, 2014). A brief definition of adaptation indicates that it is making some adjustments to natural or human systems using the beneficial opportunities or reduces potential adverse impacts in response to new or changing environments (IPCC, 2007; Nieuwaal et al., 2009). Thus, the created adaptation strategies can reduce the social, economic, environmental, etc. vulnerability caused by climate change (Brady et al., 2019). Therefore, it can be said that vulnerability components can be a good ground for planning and adjusting adaptation measures against the short-term and long-term outcomes of climate change (Salik et al., 2015). On the other hand, if the programs and strategies used to mitigate the adverse impacts of this phenomenon are not adequately efficient in terms of effectiveness, cost, and feasibility, and it exacerbates the adverse effects of this phenomenon for societies and increases vulnerability, it will cause the maladaptation of societies and the reduction of resilience of societies due to the ineffectiveness of maladaptive policies and actions. As a result, this leads into irreparable impacts such as drying of international wetlands, which is the laststep of coping up with climate change, as well as some problems such as migration of local communities, social conflicts, and increasing poverty, jeopardizing the food security of nations, sustainable livelihood of local communities, disruption of biodiversity, increase in migrations, disturbance in ecosystems, etc (Chi et al., 2021; Valizadeh et al., 2022). In general, now, there is no framework for assessing maladaptation risks (Magnan, 2014). In addition, no acceptable assessment criteria are available to determine the effects of maladaptation over
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time (Granberg & Glover, 2014). The main reason for the inaccessibility of the above instruments is that maladaptation is always exposed to unpredictable natural and human changes. Hence, with full recognition and deep understanding of this concept and evaluating the experiences of different countries, it is possible to help government organizations and decision-makers to identify suitable shortterm and long-term adaptive measures and strategies by considering maladaptive risks in the planning stage and implement them based on the conditions of each region (Magnan et al., 2016). The present study attempts to investigate and analyze the concepts of vulnerability, adaptation, and maladaptation to climate change in different dimensions and concepts due to extensive research in the field of various dimensions of the technical impacts of climate change.
2 Risk Perception of Climate Change Many environmental researchers and theorists believe that the majority of environmental crisis such as climate change and the main cause of environmental problems are referred to human behavior and anthropogenic activities (Shiri et al., 2011; Lechowska, 2018). Meanwhile, behavior prediction under environmental risk conditions depends on how much a person is intended to recognize the risk (Lucas & Pabuayon, 2011; Ricart et al., 2018). Thus, the decisions of societies to adopt environmental measures are considerably affected by cognitive aspects such as awareness, perceptions, expectations, and habits (Keshavarz & Karami, 2014; Tang et al., 2013). Among the above cognitive assumptions, individual’s risk perception plays a crucial role in shaping natural hazard policy and response management systems (Fallah Haghighi & Bijani, 2020; Schneiderbauer et al., 2021; Soubry et al., 2020). In recent years, there has been increasing concerns to shift the focus on fluctuations in risk perception and identify the causes of this problem (Kahsay et al., 2019), because one’s perception of risk plays an important role in his/her decision-making process (Salehi et al., 2018). Risk perception is guiding decision-making about risk acceptance and the central influence on behavior before, during, and after a disaster (Marshall, 2020). Also, risk perception is a mental assessment of the probability of a special type of incident and how we concern about its consequences (Fierros- González & López-Feldman, 2021). Therefore, in the current situation in which climate changes are increasing and local communities, especially farmers, need to adapt and cope up with these changes in order to maintain and sustain their livelihood resources, it is necessary to understand the different dimensions of the risk of agricultural activities in these conditions and the relationship between risk perceptions and behavioral decision-making when individuals’ choices are examined in relation to climate change (Karimi et al., 2018). In a general definition, the perception of the climate change risk means one’s perceived probability of being exposed to the effects of climate change and one’s assessment of how these effects are harmful to things that are valuable to the actor (Shen et al., 2018). In this regard, several studies have examined climate risk perception by farmers and livestock farmers
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(Lebel et al., 2015). However, in most studies on risk, risk perception is a secondary concept, and authors have assumed that it is clearly expressed by actors. However, the concept of risk perception needs to be examined (Miranda Sara et al., 2016; Schneiderbauer et al., 2021). Also, the social nature of knowing has made risk perception a necessity (Bandh et al., 2020, 2023; Nursey-Bray et al., 2012). On the other hand, many studies have investigated farmers’ risk perception of climate change, which has been performed in developing countries. Recently, farmers’ risk perception of climate change in industrialized countries has become an important research area (Harth, 2021; Takahashi et al., 2016). Thus, risk perception is considered to maintain a central position in the planning agenda of various countries (Barrucand et al., 2017). Also, the scientists of social science have found that people respond to risks based on risk perception (Bustillos Ardaya et al., 2017). In this regard, the perception of climate risk is an important element in the attitude of farmers towards adaptation. Also, risk perception influences natural hazard policy and management systems (Fourment et al., 2020), as risk perception has long been considered as a vital determinant of human response to environmental shocks and changes (Frank et al., 2010). However, empirical research on adaptability has mostly ignored psychological factors, such as risk perception and perceived adaptability capacity in determining adaptability. Most of the review of literature has identified the issue of resource limitations as an important determinant of adaptation (Altea, 2020; Simonsson et al., 2011). Generally, various studies on climate change have shown that a higher perception of climate change risk is associated with a greater tendency to adapt to climate change (Carlton et al., 2015; de Mendonca & Gullo, 2020; Ullah et al., 2018).
3 Vulnerability to Climate Change In different studies, various definitions of vulnerability have been presented. According to the IPCC (2007), vulnerability is the degree to which a system is susceptible to the impacts of climate change, including climate variability and the lack of coping up with them. Vulnerability is based on some factors such as the extent of climate change, sensitivity, and adaptive capacity of the system being exposed (Parry et al., 2007). Adger (2006) believes that vulnerability often includes exposure and sensitivity to disturbances or external stress and the relevant adaptation capacity (Adger, 2006). Turner et al. (2003) defines vulnerability as the degree to which a system, subsystem, or combination of systems leads to a disturbance or stress in exposure to risks (Turner et al., 2003). Plummer et al. (2013) consider vulnerability as a key issue that refers to “the gap between exposure to physical threats to human well-being and the capacity of individuals and communities to deal with those threats” (Plummer et al., 2013). Butler et al. (2014) consider vulnerability as a manifestation of poverty characterized by limited access to savings, education, health, land, housing, food, and political empowerment (Butler et al., 2014). Unexpected climate events and the resulting possible
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disasters are not only caused by natural events; however, it is also “the product of social, political and economic environments” (the part being separated from the natural environment), because these environments form the life structure of different groups of people. In other words, damages of unexpected climatic events such as hurricanes, droughts, and floods and gradual climate changes such as high temperatures are largely caused by the social, political, and economic vulnerabilities of people on Earth. Social structuralists (e.g., those who follow a unified framework), when they consider the causes of vulnerability, adopt different approaches. By investigating social systems, they view various causes of the outcome of an event. They also consider the integrated framework of vulnerability with having an external dimension along an internal dimension. The external dimension is shown by the “exposure” of the system to climatic changes; however, the internal dimension includes its “sensitivity” and “adaptability” to these stressful factors (Salik et al., 2015). Thus, from the perspective of a social structuralist, vulnerability to unexpected climatic events is associated with some factors including “exposure,” “sensitivity,” and “adaptability,” Exposure refers to the nature, magnitude, and frequency of unexpected climatic events (or the degree of pressure) that a system encounters. Sensitivity refers to the degree to which a system (e.g., a family) is affected by unexpected climatic events. Adaptability refers to the actual or potential ability of a system against unexpected events and successful response to climate stimuli (McCarthy et al., 2001). Another definition of adaptability is “the ability to design and implement effective adaptation strategies, or to respond to increasing risks and pressure on reducing the probability of its occurrence, or reducing the harmful outcomes that lead to damages caused by climate risks”. In general, in the conceptual model of vulnerability in climate change conditions, there are three key variables (sensitivity, exposure, and adaptive capacity) that influence vulnerability in climate change conditions as presented in Fig. 7.1 (Salik et al., 2015). On the other hand, the agricultural sector is considered as the largest water user. Different scenarios of climate change indicate that water stress will increase in the future (Karimi et al., 2018) and it is possible that in arid and semiarid Fig. 7.1 Conceptual framework of vulnerability
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regions, the amount of agriculture fields will decrease significantly. The great dependence of agriculture in many of these areas on surface water resources can exacerbate the impacts of climate change and seriously threaten the production and livelihood of farming families. In this regard, various researches have been presented on the vulnerability of farmers under the climate change conditions. The first study was done by Pandey et al. (2014) on “the assessment of water vulnerability to climate change at the household level in two forest-dependent rural communities and semi-urban regions of the Uttarakhand Himalaya in India”. The results of the survey study showed that the vulnerability of rural households is higher than that of urban households. Also, the use of natural resources and climatic factors have the most impact on revealing vulnerability, access to water, and increasing search for food, the greatest effect on sensitivity to climate changes, and social networking has the greatest effect on adaptive capacity (Pandey et al., 2014). The research “an integrative assessment of water vulnerability in first nation communities in Southern Ontario, Canada”, has been done by Plummer et al. (2013). Document analysis, questionnaire, and semistructured interviews were used in this study. For data collection, besides participating with the natives in document analysis, 300 samples were collected in three locations where the natives lived, and semistructured interviews were conducted with 30 experts. The results showed that a comprehensive overview of water vulnerability requires adequate understanding of the level of knowledge in specific areas (Plummer et al., 2013). Butler et al. (2014) used the framework of adaptation pathway for the first time in the study “the application of the adaptation pathway for rural livelihood and global changes in the southern island of Indonesia.” Data collection was performed using open-ended interviews with formal and informal leaders in southern Indonesia. They identified a total of 20 direct and indirect components affecting rural poverty and vulnerability. Finally, the adaptation pathway was drawn by them (Butler et al., 2014).
4 Concepts and Dimensions of Adaptation Adaptation is a progressive and constant process that occurs over time. For having positive adaptation to his/her changing environment, human uses inherent and acquired mechanisms that have biological, psychological, and social origins. The adaptive behavior is divided into two main groups: (1) Autonomous adaptation “a response dependent on individual characteristics such as what happens in natural systems and animal environments”. (2) Planned adaptation “which is the result of organized policies based on awareness and evaluation of changing conditions” (IPCC, 2007). Hence, many adaptation actions also reduce some risks related to the current climate fluctuations and can support the economic and social development programs in accordance
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to capacity building against water scarcity and climate change. Adaptation refers to the issues related to communities, the systems that support these communities, and their various functions in physical, economic, and natural environments. The meaning of this term as a framework refers to a concept that can easily be related to all the stages and departments of crisis management. Adaptation is the features and behaviors of the system that enhance the ability to cope with external stresses (Brooks, 2003). Adaptation includes a response to a shock that is caused by human beings or nature and can occur before, during, or after the event and causes the stability or improvement of social-ecological systems (Berrang-Ford et al., 2011). Adjustments in socioeconomic and ecological systems in response to the impacts and consequences of real or expected climate stimuli are also called adaptation to climate change (Plummer et al., 2013).
4.1 Psychological Adaptation Psychological adaptation is successive adaptation to changes and creating a relationship between self and the environment in a way that maximum self- improvement along with social well-being is enabled while observing external facts; thus, adaptation does not mean adjustment with others. Adaptation means recognizing the fact that each person must pursue his/her goals according to cultural and social frameworks (Zhang et al., 2018). When we believe that a person has learnt the appropriate responses in interacting with the environment, he is adapted. A person in a specific social situation can adapt to that situation in different ways (Kamrul Hasan & Kumar, 2020). When a person’s physical and psychological balance is disturbed in such a way that he/she is involved in an unpleasant state, and he/she needs to use internal forces and external support to create balance, and he/she succeeds in this new mechanism and solves the problem for his/her own benefit, it is said that the adaptation process has occurred (Kamrul Hasan & Kumar, 2020. Adaptation is a dynamic, evolving process that involves a balance between what individuals want and what their society accepts. In other words, adaptation is a two-way process; on the one hand, it effectively communicates with the community, and on the other hand, the community also provides some instruments through which the individual actualizes his/her potential. In this interaction, the individual and the society are changed and a relatively stable adjustment is created. Adaptation dimensions include physical adaptation, psychological adaptation, and social adaptation. Before achieving psychological, moral, and physical adaptations, we should adapt socially (Zhang et al., 2018)).
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4.2 Social Adaptation As adaptation encompasses a wide range and includes dimensions such as community, family, emotions, work, health, and marriage, some experts consider social adaptation as the top of other dimensions. The dimensions of adaptation may change in any period of time and in any stage of social evolution. However, there is no society that does not face the problem of maladaptation of its people. Therefore, this section deals with a brief description of social adaptation from the point of view of researchers and experts. From social aspects, adaptation refers to all the strategies that a person uses to manage stressful life situations (Marshall et al., 2010) and social adaptation is a reflection of human interaction with other individuals, satisfaction with individual actions, and how to perform the roles that are likely to be affected by personality, culture, and family relationships (Marshall et al., 2010). A person’s characteristics (skills, attitudes, values, and physical states) and the sensitivity of the situations that a person encounters are among the factors that affect adaptation to the environment and its changes, and since the person and the environment are always changing, these two factors are effective on determining adaptation, satisfaction, and success as adaptation occurs between these two specific factors (Bandh, 2022; Wong et al., 2019). Like physical, emotional, and mental growth, social adaptation is a continuous quantity and it gradually reaches perfection and is achieved during life naturally and in coping with experiences. After childhood and upon entering adolescence, the psychosocial development changes from a simple transformation to a deep and qualitative transformation, and by using social skills, the teenager can find his/her position among social interactions and communication with his/her peers and adults and be accepted by society. Success in social acceptance leads to social adaptation and may guide a person to the stage of social penetration, which is a level higher than social acceptance, and in this stage, he/she can affect other individuals. Social penetration is a process through which human relationships move from the level of liking to more intimacy.
5 Concepts and Dimensions of Maladaptation An unsuccessful adaptation may simply be considered an unsuccessful action (UNEP, 2019). However, the given adaptation is considered maladaptive when it causes long-term or short-term vulnerability of the target communities (Barnett & O’Neill, 2010). Maladaptation is a concept related to adaptation and vulnerability but not well recognized (Lukasiewicz et al., 2016). Table 7.1 presents definitions of maladaptation on climate change. Adaptation planning is an exercise in uncertainty, and based on incomplete information, many adaptation strategies fail. Some go further and create conditions that actually make the situation worse (Antoci et al., 2019). This is called maladaptation. Apart from wasting time and money,
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Table 7.1 Definitions of maladaptation in the literature Definition It is an exercise if vulnerability is increased. Adaptation includes those adaptation responses that increase the vulnerability to climate impacts compared to the features they have, applying on other features, and exacerbating the effects in other ways, including increase in greenhouse gas emissions. The potential of adaptive actions that intentionally increase vulnerability is named maladaptation. Maladaptation in terms of specific or general resilience: Much emphasis on building successful resilience for a (specified) driver (e.g., air conditioning to be cool on a hot day) can be undermined. Resilience to other (general) stimuli (e.g., heat tolerance in case of power disconnection causes the air conditioner to cut off). Incompatibility refers to adaptive actions that do not mitigate vulnerability but rather exacerbate it. Maladaptation is defined as ordinary business development that inadvertently increases exposure and/or vulnerability to climate change by ignoring the effects of climate change. Maladaptation can also include actions taken to adapt to climate effects that are not successful in reducing vulnerability, but rather increase it. Maladaptation occurs when short-term strategies increase vulnerability in the long-term. Actions being performed to prevent or reduce climate vulnerability. A change that adversely affects or increases the vulnerability of other systems, sectors, or social groups. Adaptation efforts that are failed in this way or are costly in this process. Maladaptation arises not only from unwanted and weakly planned adaptation actions, but also from intentional decisions in which broader considerations overemphasize short-term outcomes and reduce or ignore long-term threats that include a full range of interactions resulting from planned actions. Adaptation is a process that directly or indirectly results into increased vulnerability to climate change and change and/or significantly mitigates current and future adaptation capacities or opportunities. Intervention in one place or sector may increase the vulnerability of another place or sector or increase the vulnerability of a target group to future climate change. Maladaptation refers to negative changes and actions to which the families and individuals resort in response to climatic stressful factors which is opposing to their well-being or the entire community. Maladaptation is defined as the result of an intentional consistency policy or direct measurement of vulnerability for purposeful or external actors or the mitigation of the prerequisites of sustainable development with the indirect increase of the vulnerability of society.
Source Burton (1997) Granberg and Glover (2014)
IPCC (2001) Walker et al. (2004, 2009)
UNFCCC (2007) OECD (2009)
Barnett and O’Neill (2010, 2012, 2013)
Rickards and Howden (2012) IPCC (2013)
Magnan (2014)
Mycoo (2014)
Yaro et al. (2015) Juhola et al. (2016)
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maladaptation is a process by which individuals become vulnerable to climate change. Weak planning is the main cause of maladaptation, yet the diverse manifestations are complex and it is difficult to identify maladaptation with certainty before (Chi et al., 2020). However, there is now enough experience to show how maladaptation occurs, the contexts that may be most susceptible to such an outcome, and the design of shortcomings in strategies that should be avoided. However, unless adaptation projects directly address the vulnerability stimuli, maladaptation will remain a risk. All the definitions presented in Table 7.1 indicate that maladaptation results from adaptation that cannot reduce vulnerability or unintentionally increase it. For example, Jones et al. (2015) defined maladaptation as follows: “maladaptation occurs when short-term strategies increase vulnerability in the long term.” Gersonius et al. (2012) point out that uncertainty makes it difficult to design adaptive measures and decide which measures are adequate to mitigate climate risks. Adaptation measures may lead to reduced reversibility in response to uncertain changes in climate conditions. However, climate uncertainty is not the only factor that increases the risks of maladaptation. Adaptation involves many systems, contexts, time frames, development processes, and actors. In addition, effectiveness of adaptation is affected by human behavior and institutional adaptation. Adaptation has a time lag feature and different temporal and spatial effects (Barnett & O’Neill, 2010). Thus, the results of adaptation are mostly uncertain, which can easily lead to maladaptive decisions. In certain cases, the overall adaptive capacity is mitigated (Eriksen & Brown, 2011).
5.1 Infrastructural Maladaptation Researchers believe that individuals have different abilities to adapt to natural disasters and their vulnerability to natural disasters is not similar; however, people’s ability can be increased in order to deal with the impacts of climate change. One of the ways to increase adaptability in local communities is the proper use of existing resources and potential opportunities among local people (Anderson & Woodrow, 2019). Evidence shows that to effectively prevent and control climate change, local communities not only resort to technical means (Breshears et al., 2011), but also, human societies can adjust the design and structure of their systems in such a way as to enhance their flexibility and adaptability in coping with the increasing risks caused by weather conditions (Grothmann & Patt, 2005). Livelihood assets with emphasis on the access and use of water resources, food and health conditions, literacy rate, and GDP industry are among the infrastructure items that are effective on increasing the adaptability of local communities under climate change conditions (Mohammadi et al., 2019). The review of literature mostly focuses on maladaptation from coastal areas that encounter the need to protect against the impacts of sea level rise, saltwater intrusion, coastal storms, and other climate change consequences. Various forms of infrastructure conservation, mangrove planting, and planned retreat to adopt the
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discourse of “living with floods” have been performed around the world; however, most of these choices have consequences. A case from Fiji indicates that seawalls built to protect people against rising sea levels actually expose people living there at greater risk because they ultimately avoid storm water drainage. To some extent, seawalls and other infrastructure give people a false sense of security and encourage them to stay in locations or continue activities that make them vulnerable to climate change if the infrastructures are damaged. In the studied example, seawalls also transferred vulnerability to others along the coast due to changes in sediments, creating negative environmental consequences by threatening the marine ecosystem health (Piggott-McKellar et al., 2020; Schipper, 2020). Another study in Bangladesh investigated these actions from a gender perspective and noted that flood control has several negative consequences including the removal of floodplains that have been an important source of income and food and the reduction of nutrients in flooded soils. However, these measures eliminate even more opportunities for women compared to men. When these flooded areas disappeared, poor women without land could no longer find food and resources for selling and this reduced their livelihood security (Sultana, 2010).
5.2 Institutional Maladaptation Institutions, as social institutions responsible for guiding and regulating social activities, have a crucial role in coping up with the challenge of climate change (Dovers & Hezri, 2010). Institutions not only affect how households are influenced by climate change, they also shape the ability of households to respond to climate change and provide different adaptation methods and mediate the external interventions in the context of adaptation (Agrawal, 2001). Rural institutions are of great importance in the formation of adaptation and its outcomes, and whether adaptation strategies among the rural poor will be successful or not depends on the nature of the dominant formal and informal local institutions (Glover & Granberg, 2021). Adaptation to climate change is very important locally and its effectiveness depends on local institutions through which incentives are provided for structured individual and collective actions and how these institutions function at the local level. However, efforts to adapt to the effects of climate change depend on the success of specific institutional arrangements because adaptation never takes place in an institutional vacuum (Glover & Granberg, 2021). The role of institutional arrangements at the local level is in helping rural residents for effective response to the impacts of climate change in a comprehensive and sustainable manner, build their resilience, and protect their livelihoods against the effects of climate change. There are many adaptation choices that can mitigate the risks of climate change on crops and increase agricultural production (Howden et al., 2007). Changes in inputs such as changing cultivars/species and replacing current cultivars or species because of needing appropriate heat period and other crop requirements with cultivars or species being more resistant to temperature rise and heat and drought shocks,
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changing the amount of fertilizers, retaining soil moisture (e.g., leaving crop residue on the ground), diversifying sources of income via change in the form of integrating agriculture with other farming activities such as livestock breeding, using species or cultivars resistant to pests and diseases, and using weather condition forecasting are some of the factors to reduce production risks in this regard (Sahu & Mishra, 2013). From an institutional perspective, institutional factors determine the social, economic, and environmental outcomes of adaptation, as well as the conditions that occurred and the processes by which such decisions are made to some extent (Glover & Granberg, 2021). Research on agricultural climate insurance indicates that farmers with insurance change how they use their land or interact differently with the networks they previously worked on to reduce climate risks. These changes include focusing on insured cash crops over drought-resistant livelihood crops, hybrid plant, or moisture retention techniques, meaning farmers become reliant on insurance. Furthermore, without the need to weigh the risks of planting different crops seasonally, farmers no longer involve with their previous networks; thus, reducing the total knowledge base, social capital, and risk awareness necessary to reduce uncertainty (Müller et al., 2017).
5.3 Behavioral Maladaptation Adapting to climate change can reduce climate damage, but adapting to climate change is a long-term, complex, and systematic response process that individuals, families, and farmers are faced with some barriers to use it (Castro, 2019) and are often affected by various adaptation obstacles, and even these adaptation obstacles lead to the unsuccessful adaptation process to climate change (Wang et al. 2020). These barriers not only limit the ability of farmers or individuals to identify, evaluate, and manage the risk of climate change (Gunathilaka et al., 2018), but also reduce the efficiency of household adaptation, delay in adaptation opportunities, increase the costs of adaptation, and impede the regulation and implementation of climate change adaptation policies (Monirul Islam et al., 2014). Thus, the inability of some rural households to use climate change adaptation methods is related to the barriers to adopting efficient adaptation actions in this field (Zhang et al., 2017). Adaptation to climate change requires changes in attitudes and behavior, which are probably more important than physical and institutional changes. However, all behavioral changes do not seem good. A study on how farming communities respond to climate change in northern Ghana shows how farmers temporarily migrate from rural areas in search of work due to insecurity caused by lack of rainfall. But this strategy, by diversifying incomes and reducing pressure on food reserves, leads to labor shortages so that when agricultural conditions are good, no adequate individuals are available to ensure a successful harvest. Thus, migration makes agriculture more difficult and changes social structures, creating new dynamics and challenges (Antwi-Agyei et al., 2018). In sum, adaptation and maladaptation should be considered as a continuum, where outcomes ranging from an ideal shift
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towards a climate-resilient pathway to irreversible high vulnerability. We have many examples of maladaptation around the world, the present condition still continues, and the shift between adaptation and maladaptation can be subtle and fast. Similarly, a strategy can have positive outcomes but still lead to maladaptation (Singh et al., 2016).
6 Conclusions The research literature shows that climate change adversely affects agriculture, and yet the small part of agriculture that remains is the main source of livelihood among farmers, which is one of the most important reasons for adaptation to climate change among farmers, and adaptation is an essential tool to reduce the sensitivities and damages caused by climate change. Therefore, considering the regular and predictable changes of climate change, it is necessary to design relevant response strategies to reduce the adverse impacts of climate change. Inadequate capital, high cost of agricultural inputs, lack of information about adaptation, insufficient access to credit facilities, low knowledge of adaptation options, lack of agricultural technologies, weak and unsustainable practices, sociocultural barriers, institutional barriers, and shortcomings of ecological zones are among the issues that are considered some barriers to make adaptation decisions for farmers. The literacy of farmers, agricultural experience, access to services, credit, and climate information are factors that increase the capacity of farmers to adapt to climate change. Also, due to the increase in population in some rural and urban areas, climate change exposes individuals to more natural disasters and also causes many economic and social problems; thus, creating a supportive institutional environment for the success of adaptation efforts is necessary to provide a correct understanding and response to the complex interactions caused by climate change and to help rural development and build more resistant and adaptable environments to climate change. The importance of the government’s policies and strategic investment plans is such that we should be ensured about the amount of access and also the improvement of farmers’ access to climate forecasting information, and this access should be economical and farmers should access and support credit schemes to increase the ability and flexibility of their adaptation measures in response to climate conditions. Investment in training systems and creating off-farm employment opportunities in rural areas can be considered as a political option to reduce the adverse impacts of climate change. Most of the financial support used by governments can be government bonds, tax deductible reserves, public and private partnerships, and securities related to climate change insurance. In many developing countries, financial budgets or government bonds are regularly used to pay for damages caused by natural disasters. Also, the insurance influence among people is limited, and people cannot pay for insurance coverage obtained via insurance markets or a national public insurance program. However,
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low-income countries often use the government’s financial budget as a financial instrument, the use of insurance products against the risks of natural disasters and the design of financial protection strategies can be very efficient, and suitable and this plan is possible with the aid of the World Bank. Climate change may influence regional food security using a “bottom-up” approach that, by minimizing the performance gap and improving the product yield, increasing efficiency in the input water and nutrients with the cultivars, resistant products can lead to sustainable production and finally meet the food demands of the people under climate changes. Therefore, it is recommended to promote cost-effective, efficient, and coherent measures to compensate for the impacts of climate change in the region. Also, continuous training of farmers about climate change and protection and conservation of the natural environment are suggested to enhance awareness and increase the understanding of farmers about ways to protect natural resources. –– Supporting farmers in the use and development of local knowledge and combining it with adaptation mechanisms introduced for local improvement Climate Change Adaptation System Due to climate changes and changes in the amount and the raining season, farmers should be familiar with early and drought-resistant crops. Water shortage is one of the major problems under climate change conditions. Governments should introduce national or regional irrigation technologies in order that farmers can use rainwater. Farmers’ use of diverse livelihood systems to mitigate the effects of climate change shocks, diversification of the agricultural system such as the use of multipurpose cultivation, hybrid farming, and improving the agricultural system to modern and high-cash crops with the support of experts and the executive body of agriculture. Integrated systems should be established in different governments and nongovernmental organizations for sustainable rural development and food security of rural residents to reduce the vulnerability of agricultural sectors against problems caused by climate change and enhance the adaptation capacity of farmers.
References Abbasian, A. R., Chizari, M., & Bijani, M. (2017). Farmers’ views on the factors inhibiting the implementation of soil conservation practices (The Case of Koohdasht Township, Iran). Journal of Agricultural Science and Technology (JAST), 19(4), 797–807. Adger, W. N. (2006). Vulnerability. Global Environmental Change, 16(3), 268–281. https://doi. org/10.1016/j.gloenvcha.2006.02.006 Agrawal, A. (2001). Common property institutions and sustainable governance of resources. World Development, 29(10), 1649–1672. https://doi.org/10.1016/S0305-750X(01)00063-8 Altea, L. (2020). Perceptions of climate change and its impacts: A comparison between farmers and institutions in the Amazonas Region of Peru. Climate and Development, 12(2), 134–146. https://doi.org/10.1080/17565529.2019.1605285
7 Adaptation and Maladaptation to Climate Change: Farmers’ Perceptions
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Anderson, M. B., & Woodrow, P. J. (2019). Rising from the ashes: Development strategies in times of disaster. Routledge. Antoci, A., Gori, L., Sodini, M., & Ticci, E. (2019). Maladaptation and global indeterminacy. Environment and Development Economics, 24(6), 643–659. https://doi.org/10.1017/ S1355770X19000251 Antwi-Agyei, P., Dougill, A. J., Stringer, L. C., & Codjoe, S. N. A. (2018). Adaptation opportunities and maladaptive outcomes in climate vulnerability hotspots of northern Ghana. Climate Risk Management, 19, 83–93. https://doi.org/10.1016/j.crm.2017.11.003 Bandh, S. A. (2022). Climate change: The social and scientific construct (1st ed.). Springer. https:// doi.org/10.1007/978-3-030-86290-9 Bandh, S. A., Mushtaq, B., & Shafi, S. (2020). Environmental management: Environmental issues, awareness and abatement (1st ed.). Springer. https://doi.org/10.1007/978-981-15-3813-1 Bandh, S. A., Shafi, S., Peerzada, M., Rehman, T., Bashir, S., Wani, S. A., & Dar, R. (2021). Multidimensional analysis of global climate change: A review. Environmental Science and Pollution Research International, 28(20), 24872–24888. https://doi.org/10.1007/ s11356-021-13139-7 Bandh, S. A., Malla, F. A., Qayoom, I., Mohi-ud-Din, H., Butt, A. K., Altaf, A., Wani, S. A., Betts, R., Truong, T. H., Pham, N. D. K., Cao, D. N., & Ahmed, S. F. (2023). Importance of blue carbon in mitigating climate change and plastic/microplastic pollution and promoting circular economy. Sustainability, 15(3), 2682. https://doi.org/10.3390/su15032682 Barnett, J., & O’Neill, S. (2010). Maladaptation. Global Environmental Change, 20(2), 211–213. https://doi.org/10.1016/j.gloenvcha.2009.11.004 Barnett, J., & O’Neill, S. J. (2012). Islands, resettlement and adaptation. Nature Climate Change, 2(1), 8–10. https://doi.org/10.1038/nclimate1334 Barnett, J., & O’Neill, S. J. (2013). Minimising the risk of maladaptation: A framework for analysis. Climate Adaptation Futures, 87–93. https://doi.org/10.1002/9781118529577.ch7 Barrucand, M. G., Giraldo Vieira, C., & Canziani, P. O. (2017). Climate change and its impacts: Perception and adaptation in rural areas of Manizales, Colombia. Climate and Development, 9(5), 415–427. https://doi.org/10.1080/17565529.2016.1167661 Berrang-Ford, L., Ford, J. D., & Paterson, J. (2011). Are we adapting to climate change? Global Environmental Change, 21(1), 25–33. https://doi.org/10.1016/j.gloenvcha.2010.09.012 Brady, S. P., Bolnick, D. I., Angert, A. L., Gonzalez, A., Barrett, R. D. H., Crispo, E., Derry, A. M., Eckert, C. G., Fraser, D. J., Fussmann, G. F., Guichard, F., Lamy, T., McAdam, A. G., Newman, A. E. M., Paccard, A., Rolshausen, G., Simons, A. M., & Hendry, A. P. (2019). Causes of maladaptation. Evolutionary Applications, 12(7), 1229–1242. https://doi.org/10.1111/eva.12844 Breshears, D. D., López-Hoffman, L., & Graumlich, L. J. (2011). When ecosystem services crash: Preparing for big, fast, patchy climate change. Ambio, 40(3), 256–263. https://doi.org/10.1007/ s13280-010-0106-4 Brooks, N. (2003). Vulnerability, risk and adaptation: A conceptual framework. Tyndall Centre for Climate Change Research Working Paper, 38(38), 1–16. Burton, I. (1997). Vulnerability and adaptive response in the context of climate and climate change. Climatic Change, 36(1/2), 185–196. https://doi.org/10.1023/A:1005334926618 Bustillos Ardaya, A. B., Evers, M., & Ribbe, L. (2017). What influences disaster risk perception? Intervention measures, flood and landslide risk perception of the population living in flood risk areas in Rio de Janeiro state, Brazil. International Journal of Disaster Risk Reduction, 25, 227–237. https://doi.org/10.1016/j.ijdrr.2017.09.006 Butler, J. R. A., Suadnya, W., Puspadi, K., Sutaryono, Y., Wise, R. M., Skewes, T. D., Kirono, D., Bohensky, E. L., Handayani, T., Habibi, P., Kisman, M., Suharto, I., Hanartani, Supartarningsih, S., Ripaldi, A., Fachry, A., Yanuartati, Y., Abbas, G., Duggan, K., & Ash, A. (2014). Framing the application of adaptation pathways for rural livelihoods and global change in eastern Indonesian islands. Global Environmental Change, 28, 368–382. https://doi.org/10.1016/j. gloenvcha.2013.12.004
128
V. Karimi et al.
Carlton, J. S., Perry-Hill, R., Huber, M., & Prokopy, L. S. (2015). The climate change consensus extends beyond climate scientists. Environmental Research Letters, 10(9), 094025. Castro, B. (2019). The shifting limits of drought adaptation in rural Colombia. In E. Mapedza, D. Tsegai, M. Bruntrup, & R. Mcleman (Eds.) (pp. 77–86). Elsevier. https://doi.org/10.1016/ B978-0-12-814820-4.00006-7. Chi, C. F., Lu, S. Y., & Lee, J. D. (2020). Ostensibly effective adaptive measures could potentially be maladaptations: A case study of the Jiadung coastal area, Pingtung County, Taiwan. Coastal Management, 48(6), 643–676. https://doi.org/10.1080/08920753.2020.1803575 Chi, C. F., Lu, S. Y., Hallgren, W., Ware, D., & Tomlinson, R. (2021). Role of spatial analysis in avoiding climate change maladaptation: A systematic review. Sustainability, 13(6), 3450. https://doi.org/10.3390/su13063450 de Mendonca, M. B., & Gullo, F. T. (2020). Landslide risk perception survey in Angra dos Reis (Rio de Janeiro, southeastern Brazil): A contribution to support planning of non structural measures. Land Use Policy, 91. https://doi.org/10.1016/j.landusepol.2019.104415 Dovers, S. R., & Hezri, A. A. (2010). Institutions and policy processes: The means to the ends of adaptation. Wiley Interdisciplinary Reviews: Climate Change, 1(2), 212–231. Eriksen, S., & Brown, K. (2011). Sustainable adaptation to climate change. Climate and Development, 3(1), 3–6. https://doi.org/10.3763/cdev.2010.0064 Fallah Haghighi, N., & Bijani, M. (2020). A gap analysis between current and desired situation of economic factors affecting human resources development in Iran. GeoJournal, 85(4), 1175–1190. https://doi.org/10.1007/s10708-019-10017-1 Fierros-González, I., & López-Feldman, A. (2021). Farmers’ perception of climate change: A review of the literature for Latin America. Frontiers in Environmental Science, 9, 205. https:// doi.org/10.3389/fenvs.2021.672399 Fourment, M., Ferrer, M., Barbeau, G., & Quénol, H. (2020). Local perceptions, vulnerability and adaptive responses to climate change and variability in a winegrowing region in Uruguay. Environmental Management, 66(4), 590–599. https://doi.org/10.1007/s00267-020-01330-4 Frank, E., Eakin, H., & López-Carr, D. (2010, September). Risk perception and adaptation to climate risk in the coffee sector of Chiapas, Mexico. In Proceedings of the conference on international research on food security, natural resource management and rural development, Tropentag, Zurich, Switzerland (pp. 14–16). Gersonius, B., Morselt, T., van Nieuwenhuijzen, L., Ashley, R., & Zevenbergen, C. (2012). How the failure to account for flexibility in the economic analysis of flood risk and coastal management strategies can result in maladaptive decisions. Journal of Waterway, Port, Coastal, and Ocean Engineering, 138(5), 386–393. https://doi.org/10.1061/(ASCE)WW.1943-5460.0000142 Glover, L., & Granberg, M. (2021). The politics of maladaptation. Climate, 9(5), 69. https://doi. org/10.3390/cli9050069 Granberg, M., & Glover, L. (2014). Adaptation and maladaptation in Australian national climate change policy. Journal of Environmental Policy & Planning, 16(2), 147–159. https://doi.org/1 0.1080/1523908X.2013.823857 Grothmann, T., & Patt, A. (2005). Adaptive capacity and human cognition: The process of individual adaptation to climate change. Global Environmental Change, 15(3), 199–213. https:// doi.org/10.1016/j.gloenvcha.2005.01.002 Gunathilaka, R. P. D., Smart, J. C. R., & Fleming, C. M. (2018). Adaptation to climate change in perennial cropping systems: Options, barriers and policy implications. Environmental Science and Policy, 82, 108–116. https://doi.org/10.1016/j.envsci.2018.01.011 Harth, N. S. (2021). Affect, (group-based) emotions, and climate change action. Current Opinion in Psychology, 42, 140–144. https://doi.org/10.1016/j.copsyc.2021.07.018 Howden, S. M., Soussana, J. F., Tubiello, F. N., Chhetri, N., Dunlop, M., & Meinke, H. (2007). Adapting agriculture to climate change. Proceedings of the National Academy of Sciences of the United States of America, 104(50), 19691–19696. https://doi.org/10.1073/pnas.0701890104 IPCC. (2001). 2001: Impacts, adaptation and vulnerability. Climate change (J. J. McCarthy, O. F. Canziani, N. A. Leary, D. J. Dokken, & K. S. White, Eds.). Cambridge University Press.
7 Adaptation and Maladaptation to Climate Change: Farmers’ Perceptions
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IPCC. (2007). Climate change the physical science basis. In AGU fall meeting abstracts, 2007. IPCC. (2013). Climate change: The physical science basis. Contribution of working group I to the fifth assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press. Jones, L., Carabine, E., & Schipper, L. (2015). (Re) conceptualising maladaptation in policy and practice: Towards an evaluative framework. Available at SSRN 2643009. Juhola, S., Glaas, E., Linnér, B. O., & Neset, T. S. (2016). Redefining maladaptation. Environmental Science and Policy, 55, 135–140. https://doi.org/10.1016/j.envsci.2015.09.014 Kahsay, H. T., Guta, D. D., Birhanu, B. S., & Gidey, T. G. (2019). Farmers’ perceptions of climate change trends and adaptation strategies in semiarid highlands of Eastern Tigray, Northern Ethiopia. Advances in Meteorology, 2019, 1–13. https://doi.org/10.1155/2019/3849210 Kamrul Hasan, Md., & Kumar, L. (2020). Perceived farm-level climatic impacts on coastal agricultural productivity in Bangladesh. Climatic Change, 161(4), 617–636. Springer. Karimi, V., Karami, E., & Keshavarz, M. (2018). Climate change and agriculture: Impacts and adaptive responses in Iran. Journal of Integrative Agriculture, 17(1), 1–15. https://doi. org/10.1016/S2095-3119(17)61794-5 Karimi, V., Valizadeh, N., Karami, S., & Bijani, M. (2021). Climate change and adaptation: Recommendations for agricultural sector. In Exploring synergies and trade-offs between climate change and the sustainable development goals (pp. 97–118). Springer. https://doi. org/10.1007/978-981-15-7301-9_5 Karimi, V., Valizadeh, N., Rahmani, S., Bijani, M., & Karimi, M. (2022). Beyond climate change: Impacts, adaptation strategies, and influencing factors. In Climate change (pp. 49–70). Springer. https://doi.org/10.1007/978-3-030-86290-9_4 Keshavarz, M., & Karami, E. (2014). Farmers’ decision-making process under drought. Journal of Arid Environments, 108, 43–56. https://doi.org/10.1016/j.jaridenv.2014.03.006 Lebel, P., Whangchai, N., Chitmanat, C., Promya, J., & Lebel, L. (2015). Perceptions of climate- related risks and awareness of climate change of fish cage farmers in northern Thailand. Risk Management, 17(1), 1–22. https://doi.org/10.1057/rm.2015.4 Lechowska, E. (2018). What determines flood risk perception? A review of factors of flood risk perception and relations between its basic elements. Natural Hazards, 94(3), 1341–1366. https://doi.org/10.1007/s11069-018-3480-z Lucas, M. P., & Pabuayon, I. M. (2011). Risk perceptions, attitudes, and influential factors of rainfed lowland rice farmers in Ilocos Norte, Philippines. Asian Journal of Agriculture and Development, 8 (1362-2016-107714), 61–77. https://doi.org/10.22004/ag.econ.199327 Lukasiewicz, A., Pittock, J., & Finlayson, C. M. (2016). Are we adapting to climate change? A catchment-based adaptation assessment tool for freshwater ecosystems. Climatic Change, 138(3–4), 641–654. https://doi.org/10.1007/s10584-016-1755-5 Magnan, A. (2014). Avoiding maladaptation to climate change: Towards guiding principles. S.A.P.I.EN.S. Surveys and Perspectives Integrating Environment and Society, 7(1). Magnan, A. K., Schipper, E. L. F., Burkett, M., Bharwani, S., Burton, I., Eriksen, S., Gemenne, F., Schaar, J., & Ziervogel, G. (2016). Addressing the risk of maladaptation to climate change. WIREs Climate Change, 7(5), 646–665. https://doi.org/10.1002/wcc.409 Malla, F. A., Mushtaq, A., Bandh, S. A., Qayoom, I., Ho-ang, A. T., & Shahid-e-Murtaza. (2022). Understanding climate change: Scientific opinion and public perspective. In S. A. Bandh (Ed.), Climate change: The social and scientific construct. Springer Nature Publishing. https://link. springer.com/chapter/10.1007/978-3-030-86290-9_1 Marshall, T. M. (2020). Risk perception and safety culture: Tools for improving the implementation of disaster risk reduction strategies. International Journal of Disaster Risk Reduction, 47, 101557. https://doi.org/10.1016/j.ijdrr.2020.101557 Marshall, D., Bridges, J. F., Hauber, B., Cameron, R., Donnalley, L., Fyie, K., & Reed Johnson, F. (2010). Conjoint analysis applications in health—How are studies being designed and reported? An update on current practice in the published literature between 2005 and 2008. The Patient: Patient-Centered Outcomes Research, 3, 249–256.
130
V. Karimi et al.
McCarthy, J. J., Canziani, O. F., Leary, N. A., Dokken, D. J., & White, K. S. (Eds.). (2001). Climate change 2001: Impacts, adaptation, and vulnerability: Contribution of working group II to the third assessment report of the Intergovernmental Panel on Climate Change (Vol. 2). Cambridge University Press. Miranda Sara, L. M., Jameson, S., Pfeffer, K., & Baud, I. (2016). Risk perception: The social construction of spatial knowledge around climate change-related scenarios in Lima. Habitat International, 54, 136–149. https://doi.org/10.1016/j.habitatint.2015.12.025 Mohammadi, P., Malekian, A., Ghorbani, M., & Nazri Samani, A. A. (2019). Investigating the relationship between the vulnerability of communities and climate changes in Kermanshah Province. Geography and Environmental Sustainability, 9(3), 33–47. https://doi.org/10.22126/ ges.2019.3873.1994 Monirul Islam, Md., Sallu, S., Hubacek, K., & Paavola, J. (2014) Limits and barriers to adaptation to climate variability and change in Bangladeshi coastal fishing communities. Marine Policy, 43, 208–216. https://doi.org/10.1016/j.marpol.2013.06.007 Müller, B., Johnson, L., & Kreuer, D. (2017). Maladaptive outcomes of climate insurance in agriculture. Global Environmental Change, 46, 23–33. https://doi.org/10.1016/j. gloenvcha.2017.06.010 Mycoo, M. A. (2014). Autonomous household responses and urban governance capacity building for climate change adaptation: Georgetown, Guyana. Urban Climate, 9, 134–154. https://doi. org/10.1016/j.uclim.2014.07.009 Nieuwaal, Kv., Driessen, P., Spit, T., & Termeer, K. (2009). A state of the art of governance literature on adaptation to climate change. Towards a research agenda. IOP Conference Series: Earth and Environmental Science, 6(36). https://doi.org/10.1088/1755-1307/6/36/362019 Nursey-Bray, M., Pecl, G. T., Frusher, S., Gardner, C., Haward, M., Hobday, A. J., Jennings, S., Punt, A. E., Revill, H., & van Putten, I. (2012). Communicating climate change: Climate change risk perceptions and rock lobster fishers, Tasmania. Marine Policy, 36(3), 753–759. https://doi.org/10.1016/j.marpol.2011.10.015 Organization for Economic Cooperation and Development (OECD). (2009). Integrating climate change adaptation into development co-operation: Policy guidance. Organization for Economic Cooperation and Development Publishing. Pandey, R., Kala, S., & Pandey, V. (2014). Assessing climate change vulnerability of water at household level. Mitigation and Adaptation Strategies for Global Change, 1–15. https://doi. org/10.1007/s11027-014-9556-5 Parry, M. L., Canziani, O., Palutikof, J., Van der Linden, P., & Hanson, C. (Eds.). (2007). 2007-impacts, adaptation and vulnerability: Working group II contribution to the fourth assessment report of the IPCC. Climate Change. Cambridge University Press, 4. Piggott-McKellar, A. E., Nunn, P. D., McNamara, K. E., & Sekinini, S. T. (2020). Dam (n) seawalls: A case of climate change maladaptation in Fiji. In Managing climate change adaptation in the Pacific region (pp. 69–84). Springer. https://doi.org/10.1007/978-3-030-40552-6_4 Plummer, R., de Grosbois, D., Armitage, D., & de Loë, R. C. (2013). An integrative assessment of water vulnerability in First Nation communities in Southern Ontario, Canada. Global Environmental Change, 23(4), 749–763. https://doi.org/10.1016/j.gloenvcha.2013.03.005 Ricart, S., Olcina, J., & Rico, A. M. (2018). Evaluating public attitudes and farmers’ beliefs towards climate change adaptation: Awareness, perception, and populism at European level. Land, 8(1), 4. https://doi.org/10.3390/land8010004 Rickards, L., & Howden, S. M. (2012). Transformational adaptation: Agriculture and climate change. Crop and Pasture Science, 63(3), 240–250. https://doi.org/10.1071/CP11172 Sahu, N. C., & Mishra, D. (2013). Analysis of perception and adaptability strategies of the farmers to climate change in Odisha, India. APCBEE Procedia, 5, 123–127. https://doi.org/10.1016/j. apcbee.2013.05.022 Salehi, S., Chizari, M., Sadighi, H., & Bijani, M. (2018). Assessment of agricultural groundwater users in Iran: A cultural environmental bias. Hydrogeology Journal, 26(1), 285–295. https:// doi.org/10.1007/s10040-017-1634-9
7 Adaptation and Maladaptation to Climate Change: Farmers’ Perceptions
131
Salik, K. M., Jahangir, S., Zahdi, W. Z., & Hasson, S. (2015). Climate change vulnerability and adaptation options for the coastal communities of Pakistan. Ocean & Coastal Management, 112, 61–73. https://doi.org/10.1016/j.ocecoaman.2015.05.006 Schipper, E. L. F. (2020). Maladaptation: When adaptation to climate change goes very wrong. One Earth, 3(4), 409–414. https://doi.org/10.1016/j.oneear.2020.09.014 Schneiderbauer, S., Fontanella Pisa, P. F., Delves, J. L., Pedoth, L., Rufat, S., Erschbamer, M., Thaler, T., Carnelli, F., & Granados-Chahin, S. (2021). Risk perception of climate change and natural hazards in global mountain regions: A critical review. Science of the Total Environment, 784, 146957. https://doi.org/10.1016/j.scitotenv.2021.146957 Shen, R., Ye, Z. C., Gao, J., Hou, Y. P., & Ye, H. (2018). Climate change risk perception in global: Correlation with petroleum and liver disease: A meta-analysis. Ecotoxicology and Environmental Safety, 166, 453–461. https://doi.org/10.1016/j.ecoenv.2018.09.080 Shiri, Sh., Bijani, M., Chaharsoughi Amin, H., Noori, H., & Soleymanifard, A. (2011). Effectiveness Evaluation of the Axial Plan of Wheat from Expert Supervisors’ View in Ilam Province. World Applied Sciences Journal, 14(11), 1724–1729. Simonsson, L., Swartling, Å. G., André, K., Wallgren, O., & Klein, R. J. T. (2011). Perceptions of risk and limits to climate change adaptation: Case studies of two Swedish urban regions. In Climate change adaptation in developed nations (pp. 321–334). Springer. https://doi. org/10.1007/978-94-007-0567-8_23 Singh, C., Dorward, P., & Osbahr, H. (2016). Developing a holistic approach to the analysis of farmer decision-making: Implications for adaptation policy and practice in developing countries. Land Use Policy, 59, 329–343. https://doi.org/10.1016/j.landusepol.2016.06.041 Smith, A. M., & Brown, M. A. (2014). Policy considerations for adapting power systems to climate change. Electricity Journal, 27(9), 112–125. https://doi.org/10.1016/j.tej.2014.10.001 Soubry, B., Sherren, K., & Thornton, T. F. (2020). Are we taking farmers seriously? A review of the literature on farmer perceptions and climate change, 2007–2018. Journal of Rural Studies, 74, 210–222. https://doi.org/10.1016/j.jrurstud.2019.09.005 Sultana, F. (2010). Living in hazardous waterscapes: Gendered vulnerabilities and experiences of floods and disasters. Environmental Hazards, 9(1), 43–53. https://doi.org/10.3763/ ehaz.2010.SI02 Takahashi, B., Burnham, M., Terracina-Hartman, C., Sopchak, A. R., & Selfa, T. (2016). Climate change perceptions of NY state farmers: The role of risk perceptions and adaptive capacity. Environmental Management, 58(6), 946–957. https://doi.org/10.1007/s00267-016-0742-y Tang, J., Folmer, H., & Xue, J. (2013). Estimation of awareness and perception of water scarcity among farmers in the Guanzhong Plain, China, by means of a structural equation model. Journal of Environmental Management, 126, 55–62. https://doi.org/10.1016/j.jenvman.2013.03.051 Turner, B. L., Kasperson, R. E., Matson, P. A., McCarthy, J. J., Corell, R. W., Christensen, L., Eckley, N., Kasperson, J. X., Luers, A., Martello, M. L., Polsky, C., Pulsipher, A., & Schiller, A. (2003). A framework for vulnerability analysis in sustainability science. Proceedings of the National Academy of Sciences of the United States of America, 100(14), 8074–8079. https:// doi.org/10.1073/pnas.1231335100 Ullah, H., Rashid, A., Liu, G., & Hussain, M. (2018). Perceptions of mountainous people on climate change, livelihood practices and climatic shocks: A case study of Swat District, Pakistan. Urban Climate, 26, 244–257. https://doi.org/10.1016/j.uclim.2018.10.003 UNFCCC. (2007). Climate change: Impacts, vulnerabilities and adaptation in developing countries. UNFCCC. United Nations Environment Programme (UNEP). (2019). Frontiers 2018/2019 emerging issues of environmental concern. United Nations environmental concern. United National Environment Programme. Valizadeh, N., Haji, L., Bijani, M., Haghighi, N. F., Fatemi, M., Viira, A-H., Parra-Acosta, Y. K., Kurban, A., & Azadi, H. (2021). Development of a scale to remove farmers’ sustainability barriers to meteorological information in Iran. Sustainability, 13(22), 12617. https://doi. org/10.3390/su132212617
132
V. Karimi et al.
Valizadeh, N., Karimi, V., Fooladi Heleileh, B., Hayati, D., & Bijani, M. (2022). Formulating of small-scale farmers’ perception towards climate change in arid areas: Facilitating social interventions for agricultural sustainability. Water and Environment Journal, 36(2), 199–213. https://doi.org/10.1111/wej.12741 Walker, B., Holling, C. S., Carpenter, S. R., & Kinzig, A. P. (2004). Resilience, adaptability and transformability in social–ecological systems. Ecology and Society, 9(2), 5. https://doi. org/10.5751/ES-00650-090205 Walker, B. H., Abel, N., Anderies, J. M., & Ryan, P. (2009). Resilience, adaptability, and transformability in the Goulburn-Broken catchment, Australia. Ecology and Society, 14(1), 12. https://doi.org/10.5751/ES-02824-140112 Wang, W., Zhao, X., Cao, J., Li, H., & Zhang, Q. (2020). Barriers and requirements to climate change adaptation of mountainous rural communities in developing countries: The case of the eastern Qinghai-Tibetan Plateau of China. Land Use Policy, 95, 1688–1698. https://doi. org/10.1016/j.landusepol.2019.104354 Wong, M. S., Lee, C., Myers, D. J., Hwang, D., Kearns, J. A., Li, T., et al. (2019). Size-independent peak efficiency of III-nitride micro-light-emitting-diodes using chemical treatment and sidewall passivation. Applied Physics Express, 12(9), 097004. Yaro, J. A., Teye, J., & Bawakyillenuo, S. (2015). Local institutions and adaptive capacity to climate change/variability in the northern savannah of Ghana. Climate and Development, 7(3), 235–245. https://doi.org/10.1080/17565529.2014.951018 Zhang, Q., Zhao, X. Y., & Wang, Y. R. (2017). Adaptation needs of farmers to climate change in all ecological vulnerable alpine region: Take Gannan Plateau for example. Acta Ecologica Sinica, 37, 1688–1698. https://doi.org/10.5846/stxb201510112054 Zhang, H., Mu, J. E., & McCarl, B. A. (2018). Adaptation to climate change via adjustment in land leasing: Evidence from dryland wheat farms in the US Pacific Northwest. Land Use Policy, 79, 424–432.
Chapter 8
Farmers’ Perception of Climate Change in Climatically Vulnerable Ecosystem of Bangladesh Foyez Ahmed Prodhan, Muhammad Ziaul Hoque, Md. Safiul Islam Afrad, Md. Enamul Haque, Minhaz Ahmed, Md. Humayun Kabir, Md. Sadekur Rahman, and Naima Sultana Abstract Climate change affects cropping seasons, water availability, and the environment. This also increases the prevalence of pests and diseases, which ultimately affect crop production and food availability. Hence, understanding how agricultural communities perceive the dynamics of climate change may increase their adaptability to it. The purpose of this research was to assess how farmers perceive climate change and how they think it will affect agricultural yields, as well as the impact of socioeconomic determinants on such perceptions. The investigation took place in four upazilas in four climatically vulnerable districts of Bangladesh such as Nachole upazila in Chapai Nawabganj District, Roumari upazila in Kurigram District, F. A. Prodhan · M. Z. Hoque (*) Department of Agricultural Extension and Rural Development, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, Bangladesh Institute of Climate Change and Environment, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, Bangladesh e-mail: [email protected] M. S. I. Afrad · M. E. Haque Department of Agricultural Extension and Rural Development, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, Bangladesh M. Ahmed Department of Agroforestry and Environment, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, Bangladesh M. H. Kabir Department of Soil Science, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, Bangladesh Md. Sadekur Rahman Department of Agricultural Extension Education, Hajee Mohammod Danesh Science and Technology University, Dinajpur, Bangladesh N. Sultana National Agricultural Training Academy, Department of Agricultural Extension, Farmgate, Dhaka, Bangladesh © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 S. A. Bandh (ed.), Strategizing Agricultural Management for Climate Change Mitigation and Adaptation, https://doi.org/10.1007/978-3-031-32789-6_8
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Dumuria upazila in Kurigram District, and Teknaf upazila in Cox’s Bazar District. A total of 320 participants were enlisted for the research using a proportional random sampling method. Face-to-face interviews were conducted according to a pretested interview plan in order to gather primary data. The research found that in all four study areas, the majority of respondents observed a rise in temperature, drought, and a reduction in rainfall, but there was an increased frequency of floods in Roumari and Dumuria upazilas over the last 10–20 years. Perceptions of climate change were shown to be significantly influenced by socioeconomic criteria such as education, family size, agricultural experience, and access to information sources, according to a correlation analysis. Major consequences of climate change were evident as increased pest and disease infestation and a drop in crop production by 40–60% as perceived by the respondents. Keywords Climate change · Perception · Crop production impacts · Vulnerable ecosystem · Bangladesh
1 Introduction The term “climate change” is used to describe any long-term shift in weather patterns, whether due to natural variation or anthropogenic activity (IPCC, 2007). The changes are caused by a combination of diverse climatic issues, such as rainfall and temperature, as well as an increase in greenhouse gas (GHG) emissions caused by human activity. Some of the negative implications of climate change in poor nations include increased frequency of drought and flood, loss of biodiversity, decline of wild and other natural resources, a rise in the prevalence of infectious illnesses and other threats to public health, and changed livelihood patterns (Abaje & Giwa, 2007; Hassan & Nhemachena, 2008; Hassan et al., 2021; Hoque et al., 2019; Prodhan et al., 2022a). Although the intensity of the effect differs significantly by area, climate change is anticipated to have a substantial impact on agricultural productivity and alter crop patterns (Prodhan et al., 2022b). For the millions of impoverished people whose lives and livelihoods rely on agriculture in this setting, the effect of climate change on agriculture is a matter of significant worry and relevance (Deressa & Hassan, 2009; Gwary, 2010; Hoque et al., 2022; Prodhan et al., 2021, 2022a; Malla et al., 2022; Bandh et al., 2021, 2023; Mushtaq et al., 2020; Parray et al., 2022). Bangladesh is one of the nations across the globe that faces the greatest threat from climate change. Bangladesh has a lot of different natural disasters like droughts, floods, flash floods, river bank erosion, and cyclones (Prodhan et al., 2020, 2022b). In addition, the nation is undergoing climate change, which can be observed in the form of an increase in temperature, an increase in the level of the sea, and variations in the seasons, such as the way rainfalls is changing, which affects plants and crops (Cao et al., 2022; Chowdhury et al., 2012; Hoque et al., 2019, 2022; Nasim et al., 2019). Changes in the world’s climate are expected to have a big effect on agriculture in the future. This shift in weather would have severe
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consequences for agriculture and the environment (Prodhan et al., 2022a). Rising temperatures are the principal climate change impact on Bangladeshi agriculture, which lead to more evaporation and droughts, which make it hard to get enough water for irrigation and other uses in northwest Bangladesh (Hoque et al., 2010; Mandal, 2008; Nasim et al., 2019; Prodhan et al., 2020). Many issues with soil health that reduce agricultural output are the result of a combination of climate change and unreasonable human activity. The loss of organic matter and soil fertility, insufficient nutrients, high salinity, excessive erosion of the soil’s top layer, and waterlogging are only some of the problems that need to be addressed. Drought has become a common natural occurrence in this area, where crop loss ranges from 20% to 60% (Banglapedia, 2006). The soils of Bangladesh’s char region are severely depleted, and organic matter content is relatively low owing to light soil textures. Productivity of these soils cannot be increased and sustained unless arrangements are made to rebuild soil health; changes in cropping systems establish with a view to adapt under changing climate. The coastal area of Bangladesh having huge natural resources is becoming more vulnerable because of cyclone, high tide, and inclusion of salinity limiting the livelihoods of over 36 million people (Hoque et al., 2019, 2022; Miah et al., 2010; Prodhan et al., 2022b; Ziaul Hoque et al., 2022; Bandh et al., 2022 Bandh, 2022a, b). To develop better strategies to assist farmers in dealing with the issues brought on by climate change, it is necessary to understand how farmers perceive climate change and what variables influence their view. Farmers in this area would have to adjust to climate change in order to maintain high crop production. However, little is known about how farmers in the study region perceived climate change. Understanding the global climate and how it is changing it is prerequisite to adopt an adequate step to prevent climate change. As a consequence, the study made an effort to assess farmers’ perception of climate change in the study area as well as the factors driving those beliefs. In light of the aforementioned facts, the following objectives were set to guide the research: The objectives were to (i) identify the socioeconomic features of the respondents, (ii) determine the perceptions of respondents on climate change and its impact on agricultural production, and (iii) analyze how respondents’ socioeconomic status affects their perception on climate change in the study region.
2 Methodology The study included four climatically vulnerable districts, namely, Chapai Nawabganj, Kurigram, Khulna, and Cox’s Bazar. The research locations were chosen using a multistage random sampling process. After selecting four districts, one upazila from each district, namely, (i) Nachole upazila of Chapai Nawabganj District, (ii) Roumari upazila of Kurigram District, (iii) Dumuria upazila of Khulna District, and (iii) Teknaf upazila of Cox’s Bazar District (Fig. 8.1), was selected purposively considering the type and nature of climatic hazard and the livelihood system of the farmers. The sample size in each upazila across all districts was determined using a proportional random sampling method. A total of 320 farmers, 80 from each upazila, were chosen as a representative
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Fig. 8.1 Study area map
sample for the research using random sampling techniques. A pretested interview schedule was employed to obtain data from respondents. Respondents were requested to provide personal information such as their age, education, farm size, yearly income,
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training, and mass media exposure. Farmers were asked if temperatures, rainfall, droughts, and floods had increased, decreased, or stayed the same since their adolescence as compared to the recent past. The questions were designed so that respondents could compare situations in the recent past (less than 5 years) and the distant past (period since their adolescence) to assess any perceived changes in length. To evaluate the findings, the obtained data was collated and statistically examined. Quantitative data was analyzed using descriptive statistics, and findings were presented as percentages or counts to reflect farmers’ perspectives on climate change. Using Pearson’s correlation, the relationship between some farmer traits and how they felt about climate change was looked into.
3 Findings and Discussion 3.1 Features of the Respondents’ Socioeconomic Status This section explored the socioeconomic characteristics of the study’s respondents. The purpose was to get an idea about the population characteristics of climatically vulnerable areas’ farmers. Table 8.1 displays the socioeconomic parameters Table 8.1 Distribution of respondents based on their social and economic status Character Age
Measuring unit Actual year
Education
Year of schooling
Family size
Number
Farm size
Actual (ha)
Farming experience
No. of years
Exposure to mass media
Scores
Categories Young aged (up to 35) Middle aged (36–45) Old (>45) Illiterate (0) Primary (1–5) Secondary (6–10) Higher secondary (>10) Small (up to 4) Medium (5–6) Large (7 and above) Small (up to 1) Medium(1.01–3.0) Large (above3.0) Poor (up to 15) Moderate (16–20) High (above 20) Low (up to 15) Medium (16–25) High (above 25)
No. of respondents 98
Percent Mean SD 36.75 43.25 10.54
129 93 90 87 73 70
48.38 34.88 33.75 32.63 27.38 26.25
113 119 88 153 98 69 106 137 77 87 140 93
42.38 44.63 33.00 57.38 36.75 25.88 39.75 51.38 28.88 32.63 52.50 34.88
4.05
3.76
4.68
4.90
0.94
0.65
10.75 6.01
20.86 3.23
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including age, education, family size, farm size, agricultural experience, and interaction with information sources. The majority of respondents (48.38%) were of middle age, compared to 34.88% of older respondents and 36.75% of younger respondents. In contrast to the 33.75% of respondents who were illiterate, the biggest percentage of respondents (32.63%) had a primary level of education, followed by secondary education (27.38%) and upper secondary education (26.25%). More than two-fifths (42.38% and 44.63%) of the respondents falls under both small and medium families as compared with the 33% large category. Moreover, half of the respondents (57.38%) had small farms, while 36.75% had medium farms, and 25.88% had big farms. Among those who answered the survey, 51.38% had some agricultural experience, 39.75% had none, and 28.88% had extensive farming experience. Most of the respondents (52.50%) were found to have medium exposure to mass media, while 34.88% were in high and 32.63% respondents were found to have low contact with sources of information.
3.2 Farmers’ Perception to Climate Change The majority of respondents in the study regions saw changes in temperature, precipitation, and flood and drought conditions; therefore, they had a good understanding of climate change (Figs. 8.1, 8.2, 8.3 and 8.4). Changes in perceptions of temperature and precipitation, as well as flood and drought, were classified into four distinct areas. Nearly all participants agreed that the shift in climate conditions over the previous two decades was undeniable.
73.33
70.00
% Respondents
62.50
26.67
56.67
25.83 11.67
0 Nachole
Roumary
Increased
33.33 10
Dumuria
21.67 8.33
Decreased Unchanged
Teknaf
Fig. 8.2 Farmers’ perception on the pattern of temperature changes in four climatically vulnerable areas
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76.67
%Respondents
64.17
15
8.33
Nachole
15.00
58.33
35.83
30.83
20.83
Roumary
54.17
18.33
10.83
Dumuria
Increased Decreased Unchanged
Teknaf
Fig. 8.3 Farmers’ perception on the trend of rainfall changes in four climatically vulnerable areas
79.17
%Respondents
50
20.83
50.00
45.83 27.50 22.50
40.00 25
Increased Decreased
29.17 10
Unchanged
0 Nachole
Roumary
Dumuria
Teknaf
Fig. 8.4 Farmers’ perception on the trend of flood changes in four climatically vulnerable areas
3.2.1 Farmers’ Perception on Temperature Changes The result indicates that about three-fourths (73.33%) of the respondents perceived that the temperature of Nachole upazila in Chapai Nawabganj District is increasing with time. On the contrary only 8% of them have not noticed any change in temperature. At Roumari in Kurigram District more than two-fifths (62.5%) of the respondents observed an increase in temperature during the last two decades, while 56.67% of respondents have noticed the temperature is increasing for the last 10–20 years up to the recent time at Dumuria in Khulna District. In case of Teknaf in Cox’s Bazar District 70% of respondents expressed their opinion that temperature is also increasing with time. It can be concluded that temperature at the four upazilas in four climatically vulnerable districts is increasing over the past 10–20 years (Fig. 8.2).
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3.2.2 Farmers’ Perception on Rainfall Changes The information contained in Fig. 8.3 revealed that more than three-fifths (76.67%) of the respondents perceived that the rainfall of Nachole upazila in Chapai Nawabganj District is decreasing with time. At Roumari in Kurigram District 64.7% of the respondents observed a decrease in rainfall during the last two decades, while 58.33% of respondents have noticed rainfall is increasing for the last 10–20 years up to the recent time at Dumuria in Khulna District. In case of Teknaf in Cox’s Bazar District more than half (54.17%) of respondents expressed their opinion that rainfall is also increasing with time. Results also indicate that the rainfall trend at the four upazilas in four climatically vulnerable districts is decreasing over the past 10–20 years. 3.2.3 Farmers’ Perception on Flood The result presented in Fig. 8.4 revealed that about fourth-fifths (79.17%) of the respondents perceived that the flood incidence in Nachole upazila in Chapai Nawabganj District is decreasing with time. At Roumari in Kurigram district half of the respondents (50%) observed an increase in flood incidence during the last two decades, while 45.83% of respondents have noticed flood incidence to be increasing for the last 10–20 years up to the recent time at Dumuria in Khulna District. In case of Teknaf in Cox’s Bazar District 50% of respondents expressed their opinion that flood incidence is also increasing with time. Results also indicate that the flood occurrence trend at Roumari and Dumuria upazilas in Kurigram and Khulna Districts, respectively, is increasing, while it is decreasing in Nachole and Teknaf over the past 10–20 years. 3.2.4 Farmers’ Perception on Drought The information contained in Fig. 8.5 revealed that about fourth-fifths (79.17%) of the respondents perceived that the drought of Nachole upazila in Chapai Nawabganj District is increasing with time. At Roumari in Kurigram District three-fifths (60.83%) of the respondents observed an increase in drought during the last two decades, while half of the respondents (50%) have noticed drought is increasing for the last 10–20 years up to the recent time at Dumuria in Khulna District. In case of Teknaf in Cox’s Bazar District 54.17% of respondents expressed their opinion that drought is also increasing with time. Results also indicate that drought occurring at four upazilas in four climatically vulnerable districts is increasing over the past 10–20 years.
0
20.83
%Respondents
Roumary
14.17
60.83
25
Dumuria
35.83
50
14.17
29.17
Teknaf
16.67
54.17
Fig. 8.5 Farmers’ perception on the trend of drought changes in four climatically vulnerable areas
Nachole
79.17
Unchanged
Decreased
Increased
8 Farmers’ Perception of Climate Change in Climatically Vulnerable Ecosystem… 141
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3.2.5 Perception of Farmers About the Impact of Climate Change The respondents’ perceived impact of climate change on crop production is discussed in this section. The purpose was to get an idea about climate change and climate variability issue such as temperature, flood, rainfall, drought, and salinity on crop production and its yield. The results presented in Table 8.2 show that most of the farmers reported that about 11% of cultivable land at Nachole in Chapai Nawabganj District remained uncultivated in Rabi season because of drought, while at Roumari in Kurigram District about 8% land in Kharif-1 season remained fallow due to flood (Table 8.2). At Dumuria and Teknaf upazilas about 18% and 24% land, respectively, remained uncultivated in Kharif-1 season because of salinity. The study showed that because of climatic hazards, disease and pest infestation increased with time in Kharif-1 season (Table 8.3). It was found that at Nachole upazila 65% of respondents perceived that severe disease/pest infestation increased in Kharif-1 due to drought. At Roumari more than three-fifths of respondents (62%) expressed their opinion that maximum disease/pest infestation was found in Kharif-2 because of regular flood. Salinity in the coastal area, i.e., Dumuria (57.5% of respondents) and Teknaf (64.7% of respondents), was observed as the main factor of disease/pest infestation. The substantial reduction in crop yields (40–60%) was attributed to drought, erratic rainfall, flood, river bank erosion, and salinity (Table 8.4). From the respondents’ opinion it was observed that climatic events such as drought and erratic rainfall cause severe yield loss (40–60%) at Nachole upazila in Chapai Nawabganj District, while flood and erratic rainfall reduced crop yields severely at Roumari
Table 8.2 Uncultivable land due to drought, flood, and salinity problems of the respondents in four climatically vulnerable areas Nachole Drought Season (%) Rabi 10.54 Kharif-1 5.75 Kharif-2 7.84
Roumari Drought (%) 4.53 2.78 3.93
Dumuria Flood (%) 5.1 7.5 9.67
Flood Drought (%) – 5.05 – 4.08 – 10.08
Teknaf Salinity (%) 6.04 17.59 7.01
Drought – – –
Flood (%) 5.79 4 6.41
Salinity (%) 7.38 24.23 9.51
Table 8.3 Severity of disease/pest infestation due to drought, flood, and salinity problems at four upazilas in climatically vulnerable districts Season Rabi Kharif-1 Kharif-2
Nachole Roumari Drought Flood Respondents opinion (%) 65.00 29.80 74.00 51.90 50.00 62.70
Dumuria Flood
Salinity
Teknaf Flood
Salinity
41.70 38.30 56.70
43.30 57.50 23.30
39.20 35.30 47.60
48.00 64.70 13.70
Cold waves
Erratic rainfall/change and unpredictability in rain pattern Increased rainfall Decreased rainfall Heat waves
Climate change and climate variability issues Sea level rise (SLR)/ inundation Salt water intrusion/ salinity intrusion Increase of tropical cyclones Storm surges Tidal surge Flood Waterlogging River bank erosions Sedimentation/carpeting Drought
0 0 20– 40 20– 40
Crops Cereal crops, Tuber crops, Vegetables, 0 Pulse crops, Oilseed crops, 0 Spice and fruit crops 0 0 0 0 0 0 40– 60 40– 60 0 0 40–60 20–40 40–60 0