Addressing Uncertainty in Efficient Mitigation of Agricultural Greenhouse Gas Emissions

Better information on greenhouse gas (GHG) emissions and mitigation potential in the agricultural sector is necessary to manage these emissions and identify responses that are consistent with the food security and economic development priorities of countries. Critical activity data (what crops or livestock are managed in what way) are poor or lacking for many agricultural systems, especially in developing countries. In addition, the currently available methods for quantifying emissions and mitigation are often too expensive or complex or not sufficiently user friendly for widespread use.The purpose of this focus issue is to capture the state of the art in quantifying greenhouse gases from agricultural systems, with the goal of better understanding our current capabilities and near-term potential for improvement, with particular attention to quantification issues relevant to smallholders in developing countries. This work is timely in light of international discussions and negotiations around how agriculture should be included in efforts to reduce and adapt to climate change impacts, and considering that significant climate financing to developing countries in post-2012 agreements may be linked to their increased ability to identify and report GHG emissions (Murphy et al 2010, CCAFS 2011, FAO 2011).

Agriculture is a major source of non-CO2 greenhouse gas (GHG) emissions, namely methane (CH4) and nitrous oxide (N2O), and reactive trace gases, such as ammonia (NH3). CH4 emissions originate primarily from enteric fermentation of ruminants and during manure storage. N2O emissions are produced in microbial processes of soils and manure. Emissions of NH3 arise from livestock housing systems, manure storage and application to the soil as well as during grazing. Mitigating GHG emissions has emerged as a key priority for policy makers, researchers and stakeholders, evident in the ambitious emission reduction targets set at both the EU and national levels. However, mitigation measures at the farm level incur different marginal abatement costs (MACs) due to farm and regional specific characteristics. Farm specific calculations of MACs are still limited. Therefore, we aim at (i) modeling non-CO2 GHG emissions, (ii) computing MACs of mitigation measures and (iii) identifying cost-efficient mitigation measures for the Austrian farms using the Farm Optimization Model FAMOS. FAMOS is a mixed-integer linear farm optimization model implemented in GAMS (General Algebraic Modeling Systems; https://www.gams.com/). It is extended with a non-CO2 GHG emission accounting module that follows the guidelines for national GHG inventories provided by the Intergovernmental Panel on Climate Change. Country and farm-specific emission factors are used in the non-CO2 GHG emission accounting. This module enhances the accuracy of emission calculations at the farm level. FAMOS maximizes farm net returns, defined as the sum of market revenues and policy payments minus the costs of production and investment, subject to the farm’s resource endowments such as available land, livestock housing capacity and farm family labor. Agronomic production relationships (e.g., fertilizer and feed balances), farm management practices (e.g., crop rotations, fertilization, irrigation, tillage, feeding and grazing strategies), and legal compliances (e.g., CAP measures and payments, fertilizer intensities as part of the Austrian agri-environmental OEPUL programme) are taken into account. The model uses farm level data from various data sources (e.g., Farm Structure Survey, Integrated Administration and Control System, Standard Gross Margin Catalogue) and is individually solved for each farm in Austria. The model results show that the MACs of mitigation measures differ between farm types and agricultural production regions. For instance, MACs are higher for specialized farms with few and labor-intensive management options. The MACs are lower for managerial measures (e.g., changes in fertilizer management), compared to technological (e.g., changes in livestock housing) and agronomic measures (e.g., cover cropping). Our analysis complements the existing research by calculating MACs of selected mitigation measures at farm level. These results may inform farmers, farm consultants and policy makers in fostering the implementation of cost-efficient mitigation strategies at farm level.

Cost-effective opportunities for climate change mitigation in Indian agriculture

This study focuses on low-carbon transitions in the mid-term and analyzes mitigation potentials of greenhouse gas (GHG) emissions in 2020 and 2030 in a comparison based on bottom-up-type models. The study provides in-depth analyses of technological mitigation potentials and costs by sector and analyzes marginal abatement cost (MAC) curves from 0 to 200 US $/tCO2 eq in major countries. An advantage of this study is that the technological feasibility of reducing GHG emissions is identified explicitly through looking at distinct technological options. However, the results of MAC curves using the bottom-up approach vary widely according to region and model due to the various differing assumptions. Thus, this study focuses on some comparable variables in order to analyze the differences between MAC curves. For example, reduction ratios relative to 2005 in Annex I range from 9 % to 31 % and 17 % to 34 % at 50 US $/tCO2 eq in 2020 and 2030, respectively. In China and India, results of GHG emissions relative to 2005 vary very widely due to the difference in baseline emissions as well as the diffusion rate of mitigation technologies. Future portfolios of advanced technologies and energy resources, especially nuclear and renewable energies, are the most prominent reasons for the difference in MAC curves. Transitions toward a low-carbon society are not in line with current trends, and will require drastic GHG reductions, hence it is important to discuss how to overcome various existing barriers such as energy security constraints and technological restrictions.

Marginal abatement cost curves for agricultural climate policy: State-of-the art, lessons learnt and future potential

Developing farm-specific marginal abatement cost curves: Cost-effective greenhouse gas mitigation opportunities in sheep farming systems

Agriculture in Africa requires substantial investments, public and private, to increase agriculture productivity and achieve food security. Climate-smart agriculture options showing a win-win potential between food security and climate change adaptation on one side, and mitigation on the other side would enhance the capacity of the agriculture sector to sustainably support food security, incorporating the need for adaptation and the potential for mitigation into development strategies. The paper discusses a three-phase methodology to analyze the national agriculture investment plans with reference to climate change mitigation, through a combination of biological and economic modeling. Agriculture investments which can deliver food security and adaptation benefits are tested for their mitigation potential through a rapid screening methodology aimed at verifying the potential increase in Carbon sequestration and reduction in greenhouse gases (GHG) emissions. The mitigation benefits are estimated using the Ex-ante Carbon balance Tool (Ex-act) which can estimate the impact on GHG emissions and carbon sequestration of different land use and change scenarios. Last, Marginal abatement cost (MAC) curves are built in order to identify the least cost options. MAC curves show the order in which measures can be implemented and the relative cost of mitigation measures. Malawi case study is used as empirical application of the proposed methodology.

As the second largest source of greenhouse gas (GHG) emissions, the agricultural system has an arduous task of reducing emissions. There is an urgent need to think about how to achieve the goal of peaking carbon emissions in agricultural production at the lowest cost. This paper applied the Intergovernmental Panel on Climate Change (IPCC) factor method to calculate the GHG emissions of China’s agricultural production systems and deconstruct it into the crop farming and animal husbandry sectors. Input–output indicators based on parametric directional distance functions were constructed to assess the green production efficiency (GPE) of different agricultural sectors and scientifically quantify the marginal abatement costs (MACs) of different GHGs. The results showed the following: (a) During 2000 to 2020, GHG emissions from China’s agricultural production systems averaged 87.73 million tons of CO 2 -eq and showed a fluctuating downward trend. CH 4 emissions accounted for the largest average proportion of 55%, mainly animal enteric fermentation and rice methane emissions. (b) The average level of agricultural GPE in China is 0.79, and 0.76 for crop farming is slightly higher than 0.67 for animal husbandry. (c) The average MAC is 1,861.71 yuan/ton CO 2 -eq, and it is increasing year by year. The shadow price is positively correlated with the efficiency level. The “high-efficiency–low-cost” areas are key areas for agricultural emission reduction, such as Henan and Shandong provinces. Formulate emission reduction strategies according to the characteristics of regional GHG emissions to promote the realization of the “dual carbon” goal of agriculture.

Preface Field Study of Greenhouse Gas Emissions and Mitigation in Cropping Systems 1. Quantifying Nitrous Oxide Emissions from Agricultural Soils and Management Impacts S. J. Del Grosso and W. J. Parton 2. Nitrogen Source Effects on Nitrous Oxide Emissions from Irrigated Cropping Systems in Colorado A. D. Halvorson and S. J. Del Grosso 3. Nitrous Oxide Emissions at the Surface of Agricultural Soils in the Red River Valley of the North, U.S.A. Rebecca L. Phillips and Cari D. Ficken 4. Exchange Fluxes of NOX, NH3, and N2O from Typical Wheat, Paddy, and Maize Fields in the Yangtze River Delta and North China Plain Yuanyuan Zhang, Shuangxi Fang, Junfeng Liu, and Yujing Mu 5. Greenhouse Gas Emissions from Rice Cropping Systems W. R. Horwath 6. Understanding Greenhouse Gas Emissions from Croplands in China Zucong Cai and Xiaoyuan Yan 7. Redox Potential Control on Cumulative Global Warming Potentials from Irrigated Rice Fields Kewei Yu 8. Fertilizer Nitrogen Management To Reduce Nitrous Oxide Emissions in the U.S. Robert L. Mikkelsen and Clifford S. Snyder 9. Physical and Chemical Manipulation of Urea Fertilizer To Limit the Emission of Reactive Nitrogen Species M. I. Khalil 10. Mitigation Options for Methane and Nitrous Oxide from Agricultural Soil: From Field Measurement to Evaluation of Overall Effectiveness Hiroko Akiyama, Yoshitaka Uchida, and Akinori Yamamoto 11. Effects of Nitrogen Fertilizer Types on Nitrous Oxide Emissions Martin Burger and Rodney T. Venterea 12. Discerning Agricultural Management Effects on Nitrous Oxide Emissions from Conventional and Alternative Cropping Systems: A California Case Study E. C. Suddick, K. Steenwerth, G. M. Garland, D. R. Smart, and J. Six 13. N2O Emissions and Water Management in California Perennial Crops David R. Smart, M. Mar Alsina, Michael W. Wolff, Michael G. Matiasek, Daniel L. Schellenberg, John P. Edstrom, Patrick H. Brown, and Kate M. Scow 14. Global Nitrous Oxide Emissions: Sources and Opportunities for Mitigation R. M. Rees 15. Climate Impacts from Agricultural Emissions: Greenhouse Species and Aerosols Jeffrey S. Gaffney, Nancy A. Marley, and John E. Frederick Modeling of Greenhouse Gas Emissions and Mitigation in Cropping Systems 16. Mitigating Greenhouse Gas Emissions from Agroecosystems: Scientific Basis and Modeling Approach Changsheng Li 17. Soil Organic Matter Cycling and Greenhouse Gas Accounting Methodologies S. J. Del Grosso, S. M. Ogle, and W. J. Parton 18. Emissions of Nitrous Oxide from Agriculture: Responses to Management and Climate Change M. Abdalla, P. Smith, and M. Williams 19. Assessing the Environmental Impact of Agriculture in Europe: The Indicator Database for European Agriculture Adrian Leip 20. Development of Spatial Inventory of Nitrous Oxide Emissions from Agricultural Land Uses in California Using Biogeochemical Modeling Lei Guo, Dongmin Luo, Changsheng Li, and Michael FitzGibbon Greenhouse Gas Emissions and Mitigation in Animal Systems 21. Greenhouse Gas Emission Sources from Beef and Dairy Production Systems in the United States Kimberly R. Stackhouse, Sara E. Place, Michelle S. Calvo, Qian Wang, and Frank M. Mitloehner 22. Greenhouse Gas Emissions from Cattle Feedlot Manure Composting and Anaerobic Digestion as a Potential Mitigation Strategy Brandon Gilroyed, Xiying Hao, Francis J. Larney, and Tim A. McAllister 23. Mitigation of Greenhouse Gas Emissions from U.S. Beef and Dairy Production Systems Sara E. Place, Kim R. Stackhouse, Qian Wang, and Frank M. Mitloehner 24. Improved Productivity Reduces Greenhouse Gas Emissions from Animal Agriculture Judith L. Capper 25. Evaluation of Poultry Litter Fertilization Practices on Greenhouse Gas Emissions Dexter B. Watts, H. Allen Torbert, and Thomas R. Way 26. Quantification and Mitigation of Greenhouse Gas Emissions from Dairy Farms Hamed M. El-Mashad and Ruihong Zhang Editors' Biographies Indexes Author Index Subject Index

Climate-smart livestock production at landscape level in Kenya

PurposeMitigating agricultural greenhouse gas (GHG) emissions is an essential part of China's effort to achieve net-zero emissions. This study assesses the cost-effectiveness of China's agricultural GHG reduction under diverse carbon policies.Design/methodology/approachThe study employs a parametric non-radial distance function approach and estimates the technical abatement potential and marginal abatement cost (MAC) of GHG in China's agricultural sector for the 2008–2017 period.FindingsAgriculture is expected to make a great contribution to China's net-zero emissions progress. This study empirically analyses the cost-effectiveness of China's agricultural GHG reduction under diverse carbon policies. A parametric non-radial distance function approach is used to derive technical abatement potential and MAC of GHG for the 2008–2017 period. The results indicate that no significant improvement had been achieved in terms of agricultural GHG reduction in China during 2008–2017. The country's agricultural sector could reduce 20–40% GHG emissions with a mean value of 31%. In general, western provinces have larger reduction potential than eastern ones. The average MAC for the whole country is 4,656 yuan/ton CO2e during 2008–2017. For most western provinces, their MAC values are considerably higher than those for most eastern provinces. Compared with previous sectoral estimates of GHG mitigation cost, this study’s estimates indicate that reducing agricultural GHG emissions in some provinces is likely to be cost-effective. The Chinese government should consider expanding its national carbon market to cover agricultural sector.Practical implicationsThe Chinese government should consider expanding its national carbon market to cover agricultural sector.Originality/valueExisting studies in the field mostly ignore input constraints, which is inconsistent with carbon mitigation policy practice, especially in the agricultural sector. This study’s approach integrates both input and output constraints reflecting differing policy practice.

Major US electric utility climate pledges have the potential to collectively reduce power sector emissions by one-third

Spatially explicit database on crop-livestock management, soil, climate, greenhouse gas emissions and mitigation potential for all of Bangladesh

The quantification of greenhouse gas (GHG) emissions is increasingly important in spatial planning for regions, cities, and areas. The combination of territorial and consumption-based accounting (CBA) approaches can currently be considered best practice for calculating GHG emissions at sub-national levels, in terms of informing local decision-making about the different climate impacts of spatial planning policies, both within the boundaries of a given region and for the inhabitants of that region. This study introduces four European case studies that were conducted using the two quantification approaches to assess the climate impacts of locally relevant planning policies. The case studies represent different scales of spatial planning, different European planning systems, and different situations in terms of data availability. Territorial results are not suitable for inter-regional comparison, but rather for internal monitoring, while CBA allows for comparison and provides a comprehensive picture of the global carbon footprint of residents, however, with indications that are more difficult to link to spatial planning decisions. Assessing impacts, and in particular interpreting results, requires both methodological understanding and knowledge of the local context. The results of the case studies show that setting climate targets and monitoring the success of climate action through a single net emissions figure can give false indications. The study shows that the two approaches to quantifying GHG emissions provide complementary perspectives on GHG emissions at the sub-national level and thus provide a more thorough understanding of the GHG emission patterns associated with spatial planning policies. The identification of the regional differences in GHG emission sources and mitigation potentials are the main functions of sub-national GHG inventories and the impact assessment for spatial planning. Harmonization of the data collection for sub-national GHG inventories and the transparency of underlying assumptions would greatly support the coherence of climate action and the implications to spatial planning.

An evaluation of the effect of greenhouse gas accounting methods on a marginal abatement cost curve for Irish agricultural greenhouse gas emissions