Driving factors and decoupling effects of agricultural carbon emissions in Jiangxi Province based on time-varying parameter C-D production function

The reduction of agricultural emission plays an important role in realizing the dual-carbon goals. It is thus of great significance to examine the characteristics and drivers of regional agricultural carbon emission. We measured agricultural carbon emission in Jiangxi Province from the perspective of input-output and production processes, and explored the drivers and decoupling dynamics of agricultural carbon emission by using the LMDI decomposition method together with the Tapio decoupling model modified by time-varying parameter C-D production function. The results showed that agricultural carbon emission in Jiangxi increased by 26.4% from 2010 to 2021, and the carbon emission intensity decreased year by year with an average annual rate of 4.9%. Factors such as agricultural carbon intensity, labor input, and capital stock collectively reduced carbon emission by a total of 61.05 Mt, with a contribution of 27.0%, 44.5% and 28.5%, respectively. Level of agricultural economic development, agricultural structure, and technological progress had strong driving effects, which accounted for 75.7%, 5.6% and 18.8%, respectively. Agricultural carbon emission in Jiangxi was weakly decoupled from economic development, capital stock, and technological progress factors, but was negatively decoupled from labor input. Moreover, the decoupling state was more desirable in the later period than in the earlier period. Our results suggested that the application of the time-varying parameter C-D production function is innovative and applicable by incorporating technology, labor, and capital factors in the examination of carbon emission drivers and decoupling effects.

Dynamic Linkages among Climate Change, Mechanization and Agricultural Carbon Emissions in Rural China

Climate change has become a major environmental issue facing all countries, having a significant effect on all aspects of agricultural production, such as the agricultural mechanization process and fertilizer use. Greenhouse gases produced by agricultural machinery and fertilizers during agricultural production are an important cause of climate change. On the basis of the above facts, researching the connection between agricultural mechanization, climate change, and agricultural carbon emissions is crucial for the development of low-carbon agriculture and for addressing climate change. We used a variety of econometric models and methods to analyze data from China's multiple provinces (cities) covering the years 2000 through 2019, in order to meet the research objectives. Furthermore, we utilized rainfall and sunlight as variables to assess climate change and adopted Granger tests to establish the link between rainfall, sunlight, agricultural mechanization, and carbon emissions in farming. The findings indicate a bidirectional causality relationship between rainfall, sunlight, agricultural mechanization, and carbon emissions in farming. Rainfall and sunlight are Granger causes of agricultural mechanization. Furthermore, agricultural mechanization has favorable effects on carbon emissions of agriculture, and climate change has long-term implications on agricultural mechanization and carbon emissions of agriculture. Finally, this paper investigated the green path suitable for the low-carbon development of Chinese agriculture, arguing that the government should formulate low-carbon agricultural policies by region and actively promote the upgrading of agricultural machinery.