| 中国农业碳排放驱动机制与经济脱钩效应 |
| 摘要点击 929 全文点击 28 投稿时间：2025-04-22 修订日期：2025-10-14 |
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| 中文关键词 农业碳排放 区域差异 驱动因素 LMDI分解 随机森林 脱钩效应 |
| 英文关键词 agricultural carbon emissions regional differences driving factors LMDI decomposition random forest decoupling effect |
| DOI 10.13227/j.hjkx.202504271 |
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| 中文摘要 |
| 农业是我国碳排放的重要领域，厘清其排放特征及驱动机制对于推进农业绿色低碳转型具有重要意义. 基于2011~2022年全国31个省域数据，运用IPCC排放系数法核算农业碳排放总量及强度，揭示其时空演变特征. 结果发现，全国农业碳排放总体呈波动上升态势，东中部地区排放总量占比近60%，而碳排放强度整体下降55.16%，显示农业碳效率持续提升. 进一步采用LMDI分解模型量化农业生产效率、经济发展水平和产业结构等因素对碳排放变化的贡献，并引入随机森林与SHAP方法识别驱动因素的非线性重要性，结果表明经济发展水平、化肥投入和农业机械总动力等是主要驱动因子. Tapio模型分析显示，2015年以来我国农业碳排放与经济增长关系逐步由弱脱钩向强脱钩转变，但区域间脱钩状态差异显著. 研究建议应因地制宜推动农业投入结构优化与绿色技术推广，强化多维监测与差异化减排政策，以加快农业低碳转型进程. |
| 英文摘要 |
| Agriculture is a significant sector of carbon emissions in China. Clarifying its emission characteristics and driving mechanisms is of great significance for promoting the green and low-carbon transformation of agriculture. Based on the panel data of 31 provincial regions across the country from 2011 to 2022， this study uses the IPCC emission coefficient method to calculate the total amount and intensity of agricultural carbon emissions， revealing their spatio-temporal evolution characteristics. Research findings indicate that the overall carbon emissions from agriculture across the country have shown a fluctuating upward trend. The total emissions from the eastern and central regions accounted for nearly 60%， while the overall carbon emission intensity decreased by 55.16%， suggesting a continuous improvement in agricultural carbon efficiency. The LMDI decomposition model was further adopted to quantify the contributions of factors such as agricultural production efficiency， economic development level， and industrial structure to the changes in carbon emissions. The random forest and SHAP methods were introduced to identify the nonlinear importance of the driving factors. The results showed that economic development level， fertilizer input， and total power of agricultural machinery were the main driving factors. The Tapio model analysis showed that since 2015， the relationship between agricultural carbon emissions and economic growth in China gradually shifted from weak decoupling to strong decoupling， but the decoupling status varied significantly among regions. The research suggests that efforts should be made to optimize the agricultural input structure and promote green technologies in a way that suits local conditions and strengthen multi-dimensional monitoring and differentiated emission reduction policies so as to accelerate the low-carbon transformation process of agriculture. |
