黄河流域农业碳排放时空演化特征及其影响因素分析OA

To investigate the spatial and temporal distribution characteristics of agricultural carbon emissions in the Yellow River Basin,this study calculates the total agricultural carbon emissions of the provinces(autonomous regions)in the Yellow River Basin from 2013 to 2023 using carbon emission factors provided by the Intergovern-mental Panel on Climate Change.The intensity of agricultural carbon emissions in each province(autonomous re-gion)is determined,spatial autocorrelation is examined using the Moran's index,and the influencing factors of agricultural carbon emissions are quantitatively decomposed using the logarithmic mean Divisia index(LMDI)method,in order to further explore the driving and inhibiting effects of these factors on carbon emissions.The re-sults show that(1)From 2013 to 2023,agricultural carbon emissions in the nine provinces(autonomous regions)of the Yellow River Basin generally exhibited a trend of"slow increase-year-by-year decline-slight rebound".An-imal husbandry is the dominant source of agricultural carbon emissions.The total agricultural carbon emissions display a spatial distribution pattern characterized by"high in the north and south,low in the center",with rela-tively high emissions in Inner Mongolia Autonomous Region,Sichuan Province,Henan Province,and Shandong Province,and relatively low emissions in Qinghai Province,Gansu Province,Ningxia Hui Autonomous Region,Shaanxi Province,and Shanxi Province.(2)The overall trend of agricultural carbon emission intensity in each province(autonomous region)is declining;however,the intensity in Qinghai Province has remained consistently high.(3)The global Moran's index indicates significant positive spatial autocorrelation of agricultural carbon emission intensity in the Yellow River Basin overall,except in 2016 and 2017,and this spatial clustering effect has strengthened year by year.The local Moran scatter plots further confirm that most provinces are located in the first and third quadrants,with only a few outliers,revealing significant spatial autocorrelation of agricultural car-bon emission intensity in the region.(4)The LMDI decomposition results indicate that economic and structural effects exert positive driving effects on agricultural carbon emissions,whereas demographic,industrial structure,and technological effects exert negative inhibitory effects on carbon emissions.