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

Ying Yong Sheng Tai Xue Bao. 2023 Nov;34(11):3085-3094. doi: 10.13287/j.1001-9332.202311.011.

Abstract

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.

农业减排是实现我国碳达峰、碳中和目标的重要环节,研究区域农业碳排放特征和驱动因素对农业碳减排具有重要意义。本研究从投入产出和生产过程角度对江西省农业碳排放量进行测算,并基于时变参数C-D生产函数修正后的LMDI分解法和Tapio脱钩模型,探究江西省农业碳排放驱动因素与脱钩动态。结果表明: 江西省2010—2021年12年间农业碳排放量增长26.4%,碳排放强度在研究期内逐年下降,年均降速为4.9%。江西省农业碳排放强度、劳动投入和资本存量因素共使碳排量减少6105万t,累计分别贡献约27.0%、44.5%和28.5%;而经济发展水平、农业结构和技术进步因素具有较强推动作用,累计分别产生了75.7%、5.6%、18.8%的农业碳排放增量。江西省农业碳排放与经济发展、资本存量和技术进步因素的关系主要以弱脱钩为主,与劳动投入因素的关系以负脱钩为主,脱钩状态后期较前期更理想。因此,时变参数C-D生产函数将技术、劳动、资本要素纳入碳排放量的驱动因素和脱钩效应具有很好的创新性与适用性。.

Keywords: Cobb-Douglas production function.; LMDI decomposition method; Tapio decoupling model; agricultural carbon emission.

MeSH terms

  • Agriculture
  • Carbon Dioxide / analysis
  • Carbon* / analysis
  • China
  • Economic Development*

Substances

  • Carbon
  • Carbon Dioxide