A Study on Regional Carbon Emissions Accounting and Influencing Factors of Minority Region in Chongqing, China

The low-carbon economy development in minority regions is important in achieving carbon peaking and carbon neutrality in China. Taking the Minority Region of Chongqing (MRC) as an example, this paper analyzes the spatial and temporal evolution characteristics of carbon emissions in this region based on land use change data and economic statistics in 2010, 2015, and 2020, and analyzes influencing factors using the single factor decomposition method. The results show that the area of construction land in this region is increasing yearly, the grassland area is decreasing significantly, and both arable land and forest land are reducing first and then growing. From the overall carbon emission structure, the carbon emission in the region shows a slightly decreasing trend, among which industrial and other construction land emissions are the largest, followed by livestock emissions. However, the structure and changes of carbon emissions from land use in different county units vary. Industrial carbon emissions in 2020 show the spatial distribution characteristics of high in the north and low in the middle, with the highest industrial carbon emissions in Shizhu County, emitting 465,200 t, accounting for 32.4% of the total industrial carbon emissions, while livestock carbon emissions are high in the northeast and low in the southwest, with the largest livestock emissions in Qianjiang District, emitting 338,073.7 t, accounting for 32.4% of the overall livestock emissions are high in the southwest and low in the northeast, and Pengshui County has the most agricultural emissions, emitting 80,910.45 t, accounting for 24.1% of agricultural carbon emissions. The intensity of various influencing factors differs in different districts and counties. In terms of influencing factors, population size, and primary industry GDP have a suppressive effect on per capita carbon emissions, whereas the urbanization rate has a catalytic effect. The study results have significant reference value for studying the low-carbon development model of minority regions in China.