India [in How to reduce agrifood systems' future hidden costs? A multi-country case study]

We review the hidden costs of food systems in India as developed in the FAO SOFA 2023 report and evaluate the results in the context of India. Additionally, we assess the factors of change to reduce the hidden costs of food systems in India through a multi-model approach. We use a suite of interconn...

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Detalles Bibliográficos
Autores principales: Singh, Vartika, Stevanović, Miodrag, Kumar Ghosh, Ranjan, Bodirsky, Benjamin Leon, Popp, Alexander, Lotze-Campen, Hermann
Formato: Informe técnico
Lenguaje:Inglés
Publicado: FABLE Consortium 2024
Materias:
Acceso en línea:https://hdl.handle.net/10568/159601
Descripción
Sumario:We review the hidden costs of food systems in India as developed in the FAO SOFA 2023 report and evaluate the results in the context of India. Additionally, we assess the factors of change to reduce the hidden costs of food systems in India through a multi-model approach. We use a suite of interconnected models to implement scenarios and assess their impact on reducing the hidden costs. We create two scenarios of transformation and evaluate them across 14 indicators of food system changes encompassing the four dimensions of health, environment, inclusion, and economic costs. We also conduct stakeholder consultations to discuss the analysis and gather stakeholder opinions. We find that large average hidden cost reductions until 2050 come mainly from shift towards healthy diets, improved crop and livestock production, avoided cropland expansion and mitigated NO3 run-off. Timely shifts in dietary patterns, curbing nitrogen emissions from cropland surface runoff, and managing land use change emerge as pivotal factors for reduction of hidden costs in India. Our analysis points towards the importance of assessment of hidden costs of food systems in India using existing data and evidence. At the same time, the results from our analysis highlight the importance of reviewing analysis of hidden costs, methodological validation, and forward-looking projections within agrifood systems.