Spatiotemporal evolution and influencing factors of agricultural carbon emissions in Hebei Province at the county scale

Global climate change, caused by greenhouse gas emissions, is a common challenge for human society. Counties are the smallest administrative units covered by statistics in China, and are also the basic unit at which agricultural carbon emissions data are collected. Studying the spatiotemporal evolution and drivers of agricultural carbon emissions in counties is important for improving the inventory of agricultural carbon emission data, establishing agricultural carbon emission monitoring systems, and formulating regional emission reduction policies. A county-level greenhouse gas emission inventory was established by combining the agricultural greenhouse gas inventory with the characteristics of county data in this study. The agricultural carbon emissions of 168 counties in Hebei Province from 2009 to 2019 were measured firstly, and the spatial and temporal evolution and drivers of agricultural carbon emissions in counties were analyze then from the perspective of spatial spillover using exploratory spatial statistics and spatial measurement methods. The boundary effects of spatial spillover were investigated finally by using a dynamic spatial model to reveal the regular changes induced by the spatial spillover of agricultural carbon emissions in counties with increasing distance. The study results showed that agricultural carbon emissions in Hebei Province were decreasing during the study duration, with land management, livestock and poultry enteric fermentation, and manure management accounting for 33.00%, 42.57%, and 24.33% of agricultural carbon emissions, respectively. A high spatial agglomeration of agricultural carbon emissions at the county scale was found, and the distribution of agricultural carbon emissions hotspots was closely related to the structure of the agricultural industry. The hotspots of agricultural carbon emissions caused by land management were in Shenzhou, Wuqiang, and Raoyang counties in the south of Hebei, whereas the hotspots of livestock emissions were in Fengning, Weichang, Luanping, and Longhua counties in the north of Hebei. County agricultural carbon emissions had a significant spatial spillover effect, and agricultural carbon emissions in neighboring areas increased the overall carbon emissions in the region. Agricultural economic development was the main driver for the increase in agricultural carbon emissions. The agricultural industry structure, mechanization, fertilizer application intensity, rural energy consumption, and farmers’ income were important factors that increased the agricultural carbon emissions. The urbanization rate had an inverse effect on agricultural carbon emissions. Agricultural carbon emissions were affected by both spatial and boundary factors. The spatial spillover of agricultural carbon emissions in the county showed an increasing trend within 30 km, and a decreasing trend within 30–85 km, and the spatial spillover boundary of agricultural carbon emissions was thus approximately 30 km. The spatial spillover of carbon emissions occurred in approximately 6–8 neighboring counties. This study provides a basis and data foundation for establishing regional agricultural carbon emission reduction policies.