Real Drivers and Spatial Characteristics of CO2 Emissions from Animal Husbandry: A Regional Empirical Study of China

(1) Studying the driving factors and spatiotemporal characteristics of China's regional animal husbandry emissions is highly relevant to policy formulation. (2) Methods: We calculated the total CO2 equivalent emissions of animal husbandry across the country and each province separately, and then used the Logarithmic Mean Divisia Index (LMDI) to analyze how the driving forces of animal husbandry emissions changed across the country and in different provinces from 2001 to 2019. (3) Results:(1) During the period 2001-2019, national animal husbandry carbon emissions showed an overall downward trend. Economic growth and population contributed positively to the emissions (which means more CO2), while technological advancement, structural change in agriculture, and change in the national industrial structure had negative effects (which means less CO2). (2) Using aspects of provincial animal husbandry, we categorized 31 provinces into four types: fluctuating rising, fast falling, slow falling, and steadily falling. Then, according to the magnitude of the different driving forces in different provinces, we classified 31 provinces into three types: economic structure adjustment-driven, technological progress-driven, and economic growth-driven. (3) The driving effects of agricultural structural change and population in some provinces are not consistent with the effects shown at the national level.