Spatiotemporal Characteristics and Reduction Pathways of County-level Agricultural Carbon Emissions for Shanxi Province in China
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Agriculture is the main source of greenhouse gas emissions second only to energy activities and industrial production. Agricultural carbon emission reduction can effectively alleviate the negative impact of greenhouse effect. Using the emission factor method, this paper combs four types of agricultural production activities, including agricultural inputs, farmland management, animal intestinal digestion and fecal management, calculates the county-level agricultural carbon emissions quantity and intensity in Shanxi Province from 2018 to 2022, and uses GeoDa software and spatial autocorrelation model to estimate the Global Moran’s index, revealing the spatial agglomeration characteristics of county-level carbon emissions. From the perspective of changing trend, agricultural carbon emissions show an increase for 64.10% in total counties. It is quite limited for the reduction of carbon emission intensity on county-level agriculture, and the potential compression space is large. Animal intestinal fermentation became the primary source of county-level agricultural carbon emissions during the study period. From the perspective of spatial distribution, the agricultural carbon emissions are relatively high for the northern and central counties of Shanxi Province. The counties with high carbon emission intensity are also mainly distributed in northern and central Shanxi Province. In 2022, the Global Moran’s index of county-level agricultural carbon emissions quantity and intensity were 0.4918 and 0.4933 respectively. This shows that both indicators for county-level agricultural carbon emissions have spatial autocorrelation. The spatial distributions scale was slightly expanded for carbon emission intensity in significantly agglomerated counties, and the spatial homogeneity was slightly enhanced. This has practical guiding significance for formulating more targeted differentiated policies and accelerating the realization of carbon emission reduction targets.
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Copyright (c) 2024 Xinghua WANG, Qiang WANG, Xiaoli GUO, Shunchen WU, Yi DUAN, Hao WEI, Yang ZHANG
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