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Trade-Offs between Agricultural Production, GHG Emissions and Income in a Changing Climate, Technology, and Food Demand Scenario

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  • Paresh B. Shirsath

    (CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), Borlaug Institute for South Asia (BISA), International Maize and Wheat Improvement Centre (CIMMYT), New Delhi 110012, India)

  • Pramod K. Aggarwal

    (CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), Borlaug Institute for South Asia (BISA), International Maize and Wheat Improvement Centre (CIMMYT), New Delhi 110012, India)

Abstract

Climate-smart agriculture targets integrated adaptation and mitigation strategies for delivering food security and greenhouse gas emissions reduction. This study outlines a methodology to identify the trade-offs between food production, emissions, and income under technology and food demand-shift scenario and climate change. The methodology uses Climate Smart Agricultural Prioritization (CSAP) toolkit a multi-objective land-use allocation model, and detailed databases, characterizing the agricultural production processes at the land-unit scale. A case study has also been demonstrated for Bihar, a state in India. The quantification of trade-offs demonstrates that under different technology growth pathways alone the food self-sufficiency for Bihar cannot be achieved whilst the reduction in emission intensity targets are achievable up to 2040. However, both food self-sufficiency and reduction in emission intensity can be achieved if we relax constraints on dietary demand and focus on kilo-calories maximization targets. The district-level analysis shows that food self-sufficiency and reduction in emission intensity targets can be achieved at a local scale through efficient crop-technology portfolios.

Suggested Citation

  • Paresh B. Shirsath & Pramod K. Aggarwal, 2021. "Trade-Offs between Agricultural Production, GHG Emissions and Income in a Changing Climate, Technology, and Food Demand Scenario," Sustainability, MDPI, vol. 13(6), pages 1-13, March.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:6:p:3190-:d:516946
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    References listed on IDEAS

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    1. Dunnett, A. & Shirsath, P.B. & Aggarwal, P.K. & Thornton, P. & Joshi, P.K. & Pal, B.D. & Khatri-Chhetri, A. & Ghosh, J., 2018. "Multi-objective land use allocation modelling for prioritizing climate-smart agricultural interventions," Ecological Modelling, Elsevier, vol. 381(C), pages 23-35.
    2. Leslie Lipper & Nancy McCarthy & David Zilberman & Solomon Asfaw & Giacomo Branca (ed.), 2018. "Climate Smart Agriculture," Natural Resource Management and Policy, Springer, number 978-3-319-61194-5, March.
    3. Nancy McCarthy & Leslie Lipper & David Zilberman, 2018. "Economics of Climate Smart Agriculture: An Overview," Natural Resource Management and Policy, in: Leslie Lipper & Nancy McCarthy & David Zilberman & Solomon Asfaw & Giacomo Branca (ed.), Climate Smart Agriculture, pages 31-47, Springer.
    4. Brandt, Patric & Kvakić, Marko & Butterbach-Bahl, Klaus & Rufino, Mariana C., 2017. "How to target climate-smart agriculture? Concept and application of the consensus-driven decision support framework “targetCSA”," Agricultural Systems, Elsevier, vol. 151(C), pages 234-245.
    5. Shirsath, Paresh B. & Aggarwal, P.K. & Thornton, P.K. & Dunnett, A., 2017. "Prioritizing climate-smart agricultural land use options at a regional scale," Agricultural Systems, Elsevier, vol. 151(C), pages 174-183.
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    1. Deo, Aniket & Shirsath, Paresh B. & Aggarwal, Pramod K., 2024. "Identifying resource-conscious and low-carbon agricultural development pathways through land use modelling," Land Use Policy, Elsevier, vol. 143(C).

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