长江经济带碳排放的空间关联性及其影响因素
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摘要
从空间关联角度出发,通过引入碳排放量来改进传统引力模型,运用社会网络分析方法对2007—2017年长江经济带各省市的碳排放空间关联性进行研究,并运用二次分配程序(QAP)方法对其影响因素进行分析。研究表明:长江经济带碳排放空间关联网络越来越复杂;碳排放存在着明显的空间关联性和空间溢出效应,各省市在碳排放空间关联网络中所处地位和作用存在着显著的非均衡性;地理邻近关系、能源消费差异等对长江经济带碳排放空间关联关系有着显著的影响。最后提出长江经济带各省市协同减排的建议。
From the perspective of spatial correlation, this paper analyzes the spatial correlation of carbon emissions in Yangtze River Economic Zone in 2007-2017 based on gravity model and social network analysis method, and uses quadratic assignment procedure method to analyze its influencing factors. The results show that: the spatial correlation network of carbon emissions is becoming more and more complicated; the carbon emissions among different provinces have obvious spatial correlation and spatial spillover effect; the status and role of each province in spatial correlation network of carbon emissions are obvious disequilibrium due to their unequal hierarchy; geographical proximity, energy consumption and others have significant influence on spatial correlation of carbon emissions. Finally, some suggestions on coordinated emission reduction among provinces and cities in Yangtze River Economic Belt are put forward.
From the perspective of spatial correlation, this paper analyzes the spatial correlation of carbon emissions in Yangtze River Economic Zone in 2007-2017 based on gravity model and social network analysis method, and uses quadratic assignment procedure method to analyze its influencing factors. The results show that: the spatial correlation network of carbon emissions is becoming more and more complicated; the carbon emissions among different provinces have obvious spatial correlation and spatial spillover effect; the status and role of each province in spatial correlation network of carbon emissions are obvious disequilibrium due to their unequal hierarchy; geographical proximity, energy consumption and others have significant influence on spatial correlation of carbon emissions. Finally, some suggestions on coordinated emission reduction among provinces and cities in Yangtze River Economic Belt are put forward.
引文
[1]蒋金荷.中国碳排放量测算及影响因素分析[J].资源科学,2011,33(4):597-604.
[2]马大来，陈仲常，王玲.中国省际碳排放效率的空间计量[J].中国人口·资源与环境,2015, 25(1):67-77.
[3]WANK K, WEI Y. China's regional industrial energy efficiency and carbon emissions abatement costs[J].Applied Energy,2014,130(3):617-631.
[4]CHANG C C. A multivariate causality test of carbon dioxide emissions, energy consumption and economic growth in China[J].Applied Energy, 2010,87(11):3533-3537.
[5]史常亮,揭昌亮,朱俊峰.中国农业能耗碳排放脱钩的影响因素解析[J].产经评论,2016, 7(4):116-126.
[6]王俊松,贺灿飞.能源消费、经济增长与中国CO2排放量变化：基于LMDI方法的分解分析[J].长江流域资源与环境,2010,19(1):18-23.
[7]邹非,朱庆华,王菁.中国建筑业二氧化碳排放的影响因素分析[J].管理现代化,2016, 36(4):24-28.
[8]REY S, JANIKAS M. Space-time analysis of regional system[J].Geographical Analysis, 2006,38(1):67-86.
[9]AUFFHAMMER M, CARSON R. Forecasting the path of China's CO2 emissions using province-level information[J].Journal of Environmental Economics and Management, 2008,55(3):229-247.
[10]马艳艳,逯雅雯,孙玉涛.技术进步、结构调整与碳排放强度：基于中国省区层面空间面板数据模型的实证[J].研究与发展管理,2016,28(5):23-33.
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[12]孙亚男,刘华军,刘传明中国省际碳排放的空间关联性及其效应研究:基于SNA的经验考察[J].上海经济研究,2016,34(2):82-92.
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[14]赵玉焕,李浩,刘娅,等.京津冀CO2排放的时空差异及影响因素研究[J].资源科学,2018, 40(1):207-215.
[15]蔡博峰,王金南.长江三角洲地区城市二氧化碳排放特征研究[J].中国人口·资源与环境, 2015,25(10):45-52.
[16]魏丹青,黄炜,曹植.省域碳排放影响因素分析及减碳机制探讨：以浙江省为例[J].生态经济,2017,33(12):14-18.
[17]黄蕊,王铮,丁冠群,等.基于STIRPAT模型的江苏省能源消费碳排放影响因素分析及趋势预测[J].地理研究,2016,35(4):781-789.
[18]张勇,张乐勤,包婷婷.安徽省城市化进程中的碳排放影响因素研究：基于STIRPAT模型[J].长江流域资源与环境,2014,23(4):512-517.
[19]REILLY W J. Methods for the study of retail relationships[M].Austin, TX:University of Texas, 1929.
[20]杨桂元,吴齐,涂洋.中国省际碳排放的空间关联及其影响因素：基于社会网络分析方法[J].商业经济与管理,2016,294(4):56-70.
[21]张翼.基于空间关联网络结构的中国省域协同碳减排研究[J].统计与信息论坛,2017, 32(2):63-70.
[22]华军,刘传明,孙亚男.中国能源消费的空间关联网络结构特征及其效应研究[J].中国工业经济,2015,32(5):83-95.
[23]GARGIULO F, LENORMAND M, HUET S. Commuting network models:getting the essentials[J].Journal of Artificial Societies and Social Simulation, 2012,15(2):1-10.
[2]马大来，陈仲常，王玲.中国省际碳排放效率的空间计量[J].中国人口·资源与环境,2015, 25(1):67-77.
[3]WANK K, WEI Y. China's regional industrial energy efficiency and carbon emissions abatement costs[J].Applied Energy,2014,130(3):617-631.
[4]CHANG C C. A multivariate causality test of carbon dioxide emissions, energy consumption and economic growth in China[J].Applied Energy, 2010,87(11):3533-3537.
[5]史常亮,揭昌亮,朱俊峰.中国农业能耗碳排放脱钩的影响因素解析[J].产经评论,2016, 7(4):116-126.
[6]王俊松,贺灿飞.能源消费、经济增长与中国CO2排放量变化：基于LMDI方法的分解分析[J].长江流域资源与环境,2010,19(1):18-23.
[7]邹非,朱庆华,王菁.中国建筑业二氧化碳排放的影响因素分析[J].管理现代化,2016, 36(4):24-28.
[8]REY S, JANIKAS M. Space-time analysis of regional system[J].Geographical Analysis, 2006,38(1):67-86.
[9]AUFFHAMMER M, CARSON R. Forecasting the path of China's CO2 emissions using province-level information[J].Journal of Environmental Economics and Management, 2008,55(3):229-247.
[10]马艳艳,逯雅雯,孙玉涛.技术进步、结构调整与碳排放强度：基于中国省区层面空间面板数据模型的实证[J].研究与发展管理,2016,28(5):23-33.
[11]李建豹,黄贤金,吴常艳.中国省域碳排放影响因素的空间异质性分析[J].经济地理,2015,35(11):21-28.
[12]孙亚男,刘华军,刘传明中国省际碳排放的空间关联性及其效应研究:基于SNA的经验考察[J].上海经济研究,2016,34(2):82-92.
[13]李建豹,黄贤金.基于空间面板模型的碳排放影响因素分析:以长江经济带为例[J].长江流域资源与环境,2015,24(10):1665-1671.
[14]赵玉焕,李浩,刘娅,等.京津冀CO2排放的时空差异及影响因素研究[J].资源科学,2018, 40(1):207-215.
[15]蔡博峰,王金南.长江三角洲地区城市二氧化碳排放特征研究[J].中国人口·资源与环境, 2015,25(10):45-52.
[16]魏丹青,黄炜,曹植.省域碳排放影响因素分析及减碳机制探讨：以浙江省为例[J].生态经济,2017,33(12):14-18.
[17]黄蕊,王铮,丁冠群,等.基于STIRPAT模型的江苏省能源消费碳排放影响因素分析及趋势预测[J].地理研究,2016,35(4):781-789.
[18]张勇,张乐勤,包婷婷.安徽省城市化进程中的碳排放影响因素研究：基于STIRPAT模型[J].长江流域资源与环境,2014,23(4):512-517.
[19]REILLY W J. Methods for the study of retail relationships[M].Austin, TX:University of Texas, 1929.
[20]杨桂元,吴齐,涂洋.中国省际碳排放的空间关联及其影响因素：基于社会网络分析方法[J].商业经济与管理,2016,294(4):56-70.
[21]张翼.基于空间关联网络结构的中国省域协同碳减排研究[J].统计与信息论坛,2017, 32(2):63-70.
[22]华军,刘传明,孙亚男.中国能源消费的空间关联网络结构特征及其效应研究[J].中国工业经济,2015,32(5):83-95.
[23]GARGIULO F, LENORMAND M, HUET S. Commuting network models:getting the essentials[J].Journal of Artificial Societies and Social Simulation, 2012,15(2):1-10.