Temporal and spatial dynamics of carbon emissions in animal husbandry and their influencing factors: A case study of three provinces in Northeast China

There is a significant correlation between the development of animal husbandry and the spatial clustering distribution of carbon emissions. Employing the IPCC methodology, we accurately estimated carbon emissions from animal husbandry across 36 prefecture-level cities in the three northeastern provinces of China. We further integrated a spatial correlation model with the Tapio decoupling model to explore the relationship between the spatial clustering of animal husbandry development and carbon emissions, utilizing the Log-Mean Divisia Index (LMDI) decomposition model for analyzing the decoupling relationship. Our findings indicate that from 2004 to 2021, carbon emissions from animal husbandry in these provinces exhibited a fluctuating trend, decreasing from 48.241 million tonnes of CO₂-eq in 2004 to 41.574 million tonnes of CO₂-eq in 2021, a reduction of 13.82 %. Additionally, during the study period, the average annual GDP output in low-cluster areas declined by 0.34 %, while average annual CO₂ emissions increased by 8.11 % compared to high-cluster areas. The enhancement of production efficiency emerges as a potent means to mitigate the conflict between economic development and carbon emissions and to curb the rise in emissions. In conclusion, this study elucidates the similarity in spatial aggregation and decoupling of animal husbandry development on a regional scale, providing crucial insights for government strategies aimed at relocating animal husbandry to optimally suited areas and refining the industrial structure.