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.

[Intertemporal allocation and cost of forest carbon sequestration in China under the carbon neutrality target]. / ç¢³ä¸­å’Œç›®æ ‡ä¸‹ä¸­å›½æ£®æž—å›ºç¢³é‡è·¨æœŸåˆ†é åŠæˆæœ¬.

The situations are complex and variant in the three stages of "carbon emission peak", "rapid reduction of carbon emission" and "deep decarbonization for carbon neutrality" in China's carbon neutralization roadmap. Forest carbon sequestration is an important means to achieve the goal of carbon neutralization in China. Its intertemporal allocation is a vital way to balance industrial emission reduction and forest carbon sequestration, reduce the cost of carbon neutrality, and gradually achieve the goal of carbon neutrality based on optimal cost. Based on the cost optimization allocation theory, we simulated the cost change process of three stages of carbon neutralization in China by quoting the theory of marginal carbon sequestration cost and combining with the existing domestic marginal abatement cost theory. The results showed that annual forest carbon sequestrations with the optimal cost in China was 20 million t, 775 million t and 1.982 billion t respectively in the three stages of "carbon emission peak", "rapid reduction of carbon emission" and "deep decarbonization for carbon neutrality", accounting for 1.8%, 17.5%, and 37.6% of the total emission reduction in each period. Compared with the way relying only on industrial emission reduction, forest carbon sequestration under the optimal cost design reduced the total cost by 48, 79136, and 909253 million US$ in the three stages of carbon neutralization, respectively. Due to the limited cost advantage of forest carbon sequestration, industrial emission reduction should be emphasized in the "carbon emission peak" stage. In the "rapid reduction of carbon emissions" stage, the cost advantage of forest carbon sequestration will be increasingly prominent. In the stage of "deep decarbonization for carbon neutrality", it is necessary to fully exploit the cost advantage of forest carbon sequestration to achieve the goal of "zero carbon" to avoid the risk of high costs, especially for industries with high decarbonization cost or that will never be completely decarbonized. The optimal cost design for forest carbon sequestration can save 988.437 billion US $ in carbon-neutral costs.