中国省际农作物生产碳公平及其驱动因素  

Carbon fairness in inter provincial crop production and its driving factors in China

作　　者：汤李琛 曾贤刚[1] 陈慧 李洁[1] 陈宓 张仲元 TANG Li-chen;ZENG Xian-gang;CHEN Hui;LI Jie;CHEN Mi;ZHANG Zhong-yuan(School of Ecology&Environment,Renmin University of China,Beijing 100872,China;Business School,Hubei University,Wuhan 430062,China;School of Population and Health,Renmin University of China,Beijing 100872,China;School of Economics,Renmin University of China,Beijing 100872,China)

机构地区：[1]中国人民大学生态环境学院,北京100872 [2]湖北大学商学院,湖北武汉430062 [3]中国人民大学人口与健康学院,北京100872 [4]中国人民大学经济学院,北京100872

出　　处：《中国环境科学》2024年第12期7063-7078,共16页China Environmental Science

基　　金：国家社会科学研究基金资助重大项目(18&ZD048);中央高校建设一流大学(学科)和特色发展引导专项资金资助项目(21XNL006);中国人民大学“交叉创新研究计划”重点资助项目。

摘　　要：在采用生命周期评价法测算2006~2021年全国及31个省份农作物生产碳排放量的基础上,从碳汇角度构建农作物生产碳公平系数,利用XGBoost模型识别碳公平的关键驱动因素及其非线性响应关系.结果表明,考察期内,全国农作物生产碳公平整体趋于降低,碳公平系数由1.025下降至0.944.全国农作物生产碳公平的区域差异性显著,整体表现为“粮食主产区>产销平衡区>粮食主销区”.碳公平程度总体呈由西北向东南递减,并存在高值聚集与低值聚集减弱的趋势.除农田灌溉条件、城乡收入差距、科技创新水平因素外,其他驱动因素对碳公平的影响具有复杂的非线性特征.从时间效应来看,农业生产结构是影响碳公平的最重要因素,农田灌溉条件、粮食单产因素的重要性始终排名靠前;从区域效应来看,农业生产结构因素排名靠前,其他驱动因素的重要性存在一定的差异.On the basis of using the life cycle assessment method to calculate the carbon emissions of crop production in China and 31 provinces from 2006 to 2021,the carbon fairness coefficient of crop production was constructed from the perspective of carbon sink.The XGBoost model was used to identify the key driving factors of carbon fairness and their nonlinear response relationships.The results showed that during the inspection period,the overall carbon fairness of crop production in China tended to decrease,with the carbon fairness coefficient decreasing from 1.025 to 0.944.The regional differences in carbon fairness of crop production in China were significant,with the overall performance being"main grain production area>the production and sales balance area>main grain sales area".The overall degree of carbon fairness was decreasing from northwest to southeast,and there was a trend of weakening high-value aggregation and low-value aggregation.Except for factors such as farmland irrigation conditions,urban-rural income gap,and technological innovation level,other driving factors had complex nonlinear characteristics in their impact on carbon fairness.From the perspective of time effects,agricultural production structure was the most important factor affecting carbon fairness,and the importance of farmland irrigation conditions and grain yield per hectare factors always ranked high.From the perspective of regional effects,agricultural production structure factor ranked high,and there were certain differences in the importance of other driving factors.

关 键 词：农作物生产 碳公平 驱动因素 XGBoost模型 

分 类 号：X24[环境科学与工程—环境科学]