Analyses of Carbon Emissions from Agricultural Inputs and Outputs in China in a Low Carbon Context.

Climate change in agriculture has important impacts on human life and health, so it is crucial to explore the process of carbon peaking in China's agricultural resource inputs and to provide data support for greenhouse gas (GHG) emission reduction in agriculture. The LMDI model and Tapio decoupling model were used in this study, and the interrelationship between carbon emissions from agricultural resource inputs and agricultural output was analyzed deeply. Meanwhile, global and local Moran's I indices were introduced to further analyze the degree of spatially significant correlation. The results showed that China's total agricultural carbon emissions from 2003 to 2021 showed an"inverted U-shaped"curve, indicating a first growth and then a downward trend, and reached a peak in 2015. Carbon emissions in east China have always been in the first place, followed by central China. However, the Northwest region, which has the lowest carbon emissions among the seven regions, has risen significantly to become the third largest source of agricultural carbon emissions by 2021. The use of fertilizers was the major factor contributing to agricultural carbon emissions, with an average annual contribution of 58%. while pesticides, agricultural films and diesel use were secondary factors. The global Moran' s I index showed significant spatial correlation in agricultural carbon emissions, but the degree of spatial aggregation gradually weakened over time. The local Moran' s I showed that the high-high aggregation was mainly concentrated in east China and central China. According to the results of the LMDI model, agricultural production efficiency, regional industrial structure, and the size of the agricultural labor force play an inhibitory role in the growth of agricultural carbon emissions, of which agricultural production efficiency is the main inhibitory factor, with an annual average emission reduction of 6.475 7 million tons. Agricultural industrial structure, the level of regional economic development, and the level of urbanization, on the other hand, promote the growth of agricultural carbon emissions, and the level of regional economic development is the main factor that promotes the growth of agricultural carbon emissions, with an annual average of about 8.91 million tons. The Tapio decoupling model showed that all regions achieved strong decoupling after 2016, and that agricultural economic growth was accompanied by a reduction in agricultural carbon emissions, which reached a desirable state, indicating that the effect of emission reduction after 2016 was significant. [ABSTRACT FROM AUTHOR]