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 total CO2 equivalent across country each province separately, then used Logarithmic Mean Divisia Index (LMDI) analyze how forces changed in different provinces from 2001 2019. (3) Results: ? During period 2001–2019, national carbon showed an overall downward trend. Economic growth population contributed positively (which means more CO2), while technological advancement, structural change agriculture, industrial structure had negative effects less CO2). ? Using aspects provincial husbandry, we categorized 31 into four types: fluctuating rising, fast falling, slow steadily falling. Then, according magnitude provinces, classified three economic adjustment-driven, progress-driven, growth-driven. ? The agricultural some are not consistent with shown at level.