Spatial-temporal differentiation characteristics and key driving factors of agricultural carbon emissions in the three northeastern provinces of China

Climate change caused by increasing carbon dioxide emissions is one of the major challenges today. Promoting the development of low-carbon agriculture is an effective way to deal with climate threats and agricultural nonpoint source pollution. Accurately measuring the effect of agricultural carbon emissions and its spatial and temporal evolution characteristics is the basis for promoting the development of low-carbon of agriculture, and studying the key driving factors of agricultural carbon emissions and the trade-off and coordination relationship between driving factors is of great significance for formulating regional carbon emission reduction policies in Northeast China. Based on the input data of agricultural materials and the IPCC method, this study calculated the agricultural carbon emissions of three provinces in Northeast China from 2000 to 2019, used the spatial autocorrelation analysis method to clarify the spatial and temporal differentiation characteristics of agricultural carbon emissions, and explored the driving factors of agricultural carbon emissions and their interactions through the LMDI decomposition model and geographic detector. The results showed the following: 1) The total carbon emissions of the three provinces in Northeast China showed a trend of increasing and then decreasing. The incremental changes in carbon emissions can be divided into three stages: the fluctuating rising period (2000–2009), transitional period (2010–2015), and steady decline period (2016–2019). In 2015, the total amount of agricultural carbon emissions reached a peak of 17.5966 million t, an increase of 67.88% compared to that in 2000, with an average annual increase of 4.53%. During the study period, all carbon sources showed different degrees of growth, and chemical fertilizer application was the main carbon source, accounting for 75.12%. 2) The spatial distribution of the total carbon emissions in the three northeastern provinces had a significant spatial autocorrelation. The hotspots of carbon emissions were mainly distributed in the northeastern plain area, and it showed agglomeration trend and scope were expanding. The cold spots of carbon emissions were mainly distributed in the Changbai and Daxing’an Mountains and did not change significantly over time. 3) Total agricultural carbon emissions in the three northeastern provinces were affected by several factors. The improvement of agricultural production efficiency, the optimization of agricultural industrial structure, and the reduction of agricultural labor force had an inhibitory effect on carbon emissions, and the proportions of carbon emissions reduction were 207.31%, 21.56%, and 20.72%, while the level of agricultural economic development had a strong driving effect on carbon emissions, achieving a 349.59% carbon increment. The interaction between the levels of agricultural economic development, agricultural production efficiency, and agricultural structure is more nonlinear than the influence of a single factor on carbon emissions. The superposition of the labor force scale and other factors shows the effect of two-factor enhancement. The research results revealed that the carbon emission effect of the three northeastern provinces was easily affected by the surrounding areas, and the degree of influence increased. Simultaneously, there was a strong synergy between the driving factors of carbon emissions.