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作 者:刘娇 张汝飞 LIU Jiao;ZHANG Rufei(College of Economics,Hebei GEO University,Shijiazhuang,Hebei 050031,China)
机构地区:[1]河北地质大学经济学院,河北石家庄050031
出 处:《保定学院学报》2024年第2期11-20,共10页Journal of Baoding University
基 金:河北地质大学学生科技基金科研项目“中国农业碳排放效率测算及影响因素分析”(KAY202324)。
摘 要:准确把握农业碳排放效率空间关联特征对促进农业低碳高质量可持续发展具有重要意义。利用超效率SBM模型测算中国2009—2020年省级农业碳排放效率,利用修改的引力矩阵计算省际间引力值,构建空间关联网络引力矩阵,最后用社会网络分析法和QAP模型对空间关联网络的网络结构特征和驱动因素进行探索分析。结果表明:1)农业碳排放效率在研究期间呈现下降趋势且存在区域差异性。2)农业碳排放效率空间关联网络结构紧密、稳定性强、关联性强,森严的网络等级关系逐渐缓和。北京、上海、浙江等为网络中心,影响并控制着省际农业碳排放效率关联。3)交通运输水平、信息化水平、劳动力人均产值、科技水平等对空间关联形成发挥重要作用。因此,应根据中国农业碳排放效率空间关联网络特征,充分发挥地区的中心影响和中介作用,最终形成省际间互动协作的减排机制。Accurately grasping the spatial correlation characteristics of agricultural carbon emission efficiency(AEE)is of great significance in promoting low-carbon sustainable development of agriculture.In this paper,we use the super-efficient SBM model to measure AEE of 30 provinces in China from 2009 to 2020,and then we use the modified gravity matrix to get the inter-provincial gravity value and construct the gravity matrix of spatial correlation network,and then we use the social network analysis method and the QAP model to explore and analyze the characteristics of the network structure and the driving factors of the spatial correlation network.The results show that:1)AEE shows a decreasing trend and regional variability during the study period;2)the spatial correlation network structure of the agricultural carbon emission efficiency is tightly stabilized with strong correlation;3)the level of transportation,the level of informatization,the per capita output value of labor,and the level of science and technology play an important role in the formation of spatial correlation.According to the characteristics of the spatial correlation network of China's AEE,an inter-provincial interactive and collaborative emission reduction mechanism should be formed.
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