Abstract
Greenhouse gas (GHG) emissions from agricultural activities have a significant impact on global climate change. Benin, a country in West Africa, relies heavily on agriculture, particularly cotton, maize, and rice cultivation. The study aims to estimate GHG emissions across 77 communities in Benin from 2000 to 2019 with a focus on cotton, maize, and rice cultivation. The study utilizes the Integrated Versatile Estimation System (IVES) and the IPCC's T1 estimation recommendations to estimate GHG emissions. The local spatial Moran index is used to identify factors affecting GHG emissions, including population density and education levels in communities. The study reveals that N2O emissions from cotton, maize, and rice cultivation have significantly increased over time, with high GHG concentrations observed in northern Benin and lower concentrations in the south. Moreover, the study finds that population density and education levels in communities are crucial factors determining agricultural GHG emissions. Higher population densities are associated with lower emissions, and higher education levels are associated with lower emissions, indicating better knowledge and adoption of sustainable agricultural practices. This research offers valuable insights into the factors driving agricultural GHG emissions in Benin, and it provides policy recommendations to reduce emissions and mitigate the impact of climate change. As agriculture is a vital sector for many countries globally, these findings are useful in efforts to reduce emissions in the agricultural sector worldwide.
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This paper is funded by National Key Research and Development Program of China (2021YFE0117900) and China Scholarship Council (CSC).
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Jacquet, I., Zhang, J., Wang, K. et al. Mitigating greenhouse gas emissions from agriculture in Benin: spatial estimation and reduction options. Environ Dev Sustain (2023). https://doi.org/10.1007/s10668-023-04195-9
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DOI: https://doi.org/10.1007/s10668-023-04195-9