Abstract:Based on the carbon emission / carbon sink data in 2005, 2010, 2015 and 2017, an empirical study on the spatial connection of carbon emission / carbon sink at the county level of Beijing, Tianjin and Hebei (BTH) was made by using social network analysis and exploratory spatial data analysis, and divides the carbon balance zoning, providing the path to divide the carbon balance zoning on the county spatial scale. The results showed that (1) the average annual growth rate of carbon emissions in the BTH region slowed down from 10.05% in 2005~2010 to 1.25% in 2010~2017. The total amount of carbon sinks decreased first and then increased, with an increase of 15% in 2010~2017. However, the net carbon emissions reached 600 million tons in 2017, reflecting that the current carbon neutralization pressure is still huge. The north and west of Beijing Tianjin Hebei were the main high-value areas of carbon compensation rate, and Beijing Tianjin Tangshan, Shijiazhuang, Handan-Xingtai and their surrounding areas were the low-value areas of carbon compensation rate; (2) The pattern of Beijing Tianjin Hebei carbon emission spatial network gradually became clear, forming three main carbon emission spatial linkage areas: Beijing Tianjin carbon emission area, Shijiazhuang carbon emission area and Handan carbon emission area, accounting for 36.65%, 9.64% and 6.76% of the whole respectively;(3) According to the results, BTH region was divided into 7 carbon balance functional areas: centralized carbon sink area, local regulation area, core linkage carbon emission area, dispersion linkage carbon emission area, dispersion Island carbon emission area, general linkage carbon emission area and general Island carbon emission area. 19 key counties inside were defined as core county, action county or bridge county, accounting for 22.07%, 32.62%, 12.81%, 0.45%, 1.14%, 22.55% and 8.36% of the whole respectively.
曲福田,卢 娜,冯淑怡.土地利用变化对碳排放的影响[J]. 中国人口·资源与环境, 2011,21(10):76-83. Qu F T, Lu N, Feng S Y. Effects of land use change on carbon emissions[J]. China Population, Resources and Environment, 2011, 21(10):76-83.
[2]
李小康,王晓鸣,华 虹.土地利用结构变化对碳排放的影响关系及机理研究[J]. 生态经济, 2018,34(1):14-19. Li X K, Wang X M, Hua H. Research on Influences of land use structure change on carbon emissions[J]. Ecological Economy, 2018, 34(1):14-19.
[3]
Chang C C, Liao Y T, Chang Y W. Life cycle assessment of alternative energy types-including hydrogen-for public city buses in Taiwan[J]. International Journal of Hydrogen Energy, 2019,44(33):18472-18482.
[4]
黄琳琳,王 远,张 晨,等.闽三角地区碳排放时空差异及影响因素研究[J]. 中国环境科学, 2020,40(5):2312-2320. Huang L L, Wang Y, Zhang C, Huang Y M. A spatial-temporal decomposition analysis of CO2 emissions in Fujian Southeast Triangle Region[J]. China Environmental Science, 2020,40(5):2312-2320.
[5]
王 勇,王 颖.中国实现碳减排双控目标的可行性及最优路径——能源结构优化的视角[J]. 中国环境科学, 2019,39(10):4444-4455. Wang Y, Wang Y. Feasibility and optimal pathway of China's double targets for carbon reduction——The perspective of energy structure optimization[J]. China Environmental Science, 2019,39(10):4444-4455.
[6]
韦彦汀,李思佳,张 华.成渝城市群碳排放时空特征及其影响因素[J]. 中国环境科学, 2022,42(10):4807-4816. Wei Y D, Li S J, Zhang H. Temporal-spatial evolution of carbon emission and driving factors in the Chengdu-Chongqing urban agglomeration[J]. China Environmental Science, 2022,42(10):4807-4816.
[7]
Liu Q, WU S, Lei Y, et al. Exploring spatial characteristics of city-level CO2 emissions in China and their influencing factors from global and local perspectives[J]. Science of the Total Environment, 2020,754:142206.
[8]
李玉玲,李世平,祁静静.陕西省土地利用碳排放影响因素及脱钩效应分析[J]. 水土保持研究, 2018,25(1):382-390. Li Y L, Li S P, Qi J J. Influencing factors on carbon emissions of land uses and analysis of their decoupling effects in Shaanxi province[J]. Research of Soil and Water Conservation, 2018,25(1):382-390.
[9]
蔡博峰,曹 东,刘兰翠,等.中国交通二氧化碳排放研究[J]. 气候变化研究进展, 2011,7(3):197-203. Cai B F, Cao D, Liu L C, et al. China transport CO2 emission study[J]. Advances in Climate Change Research, 2011,7(3):197-203.
[10]
林 彤,杨木壮,吴大放,等.基于InVEST-PLUS模型的碳储量空间关联性及预测——以广东省为例[J]. 中国环境科学, 2022,42(10):4827-4839. Lin T, Ynag M Z, Wu D F, et al. Spatial correlation and prediction of land use carbon storage based on the InVEST-PLUS model-A case study in Guangdong Province[J]. China Environmental Science, 2022, 42(10):4827-4839.
[11]
董雪兵,池若楠.中国区域经济差异与收敛的时空演进特征[J]. 经济地理, 2020,40(10):11-21. Dong X B, Chi R N. Characteristics of the temporal and spatial pattern of the economic disparity and convergence between different regions in China[J]. Economic Geography, 2020,40(10):11-21.
[12]
刘佳骏,史 丹,汪 川.中国碳排放空间相关与空间溢出效应研究[J]. 自然资源学报, 2015,30(8):1289-1303. Liu J J, Shi D, Wang C. A Study on spatial spillover and correlation effect of carbon emissions across 30provinces in China[J]. Journal of Natural Resources, 2015,30(8):1289-1303.
[13]
杨国清,朱文锐,文 雅,等.20年来广东省土地利用碳排放强度与效率空间分异研究[J]. 生态环境学报, 2019,28(2):332-340. Yang G Q, Zhu W R, Wen Y, et al. Spatial differentiation in the intensity and efficiency of carbon emission from land use in Guangdong province in past two decades[J]. Ecology and Environmental Sciences, 28(2):332-340.
[14]
赵桂梅,陈丽珍,孙立成,等.空间分异视角下中国碳排放强度的Markov稳态预测[J]. 科技管理研究, 2017,37(22):228-233. Zhao G M, Chen L Z, Sun LC, et al. Markov steady state prediction of carbon emission intensity in China based on the perspective of spatial differentiation[J]. Science and Technology Management Research, 2017,37(22):228-233.
[15]
蔺雪芹,边 宇,王 岱.京津冀地区工业碳排放效率时空演化特征及影响因素[J]. 经济地理, 2021,41(6):187-195. Lin X Q, Bian Y, Wang D. Spatiotemporal evolution characteristics and influencing factors of industrial carbon emission efficiency in Beijing-Tianjin-Hebei region[J]. Economic Geography, 2021,41(6):187-195.
[16]
邓祥征,蒋思坚,李 星,等.区域土地利用影响地表CO2浓度异质性特征的动力学机制[J]. 地理学报, 2022,77(4):936-946. Deng X Z, Jiang S J, Li X, et al. Dynamics of regional land uses affecting spatial heterogeneity of surface CO2 concentration[J]. Acta Geographica Sinica, 2022,77(4):936-946.
[17]
赵雲泰,黄贤金,钟太洋,等.1999~2007年中国能源消费碳排放强度空间演变特征[J]. 环境科学, 2011,32(11):3145-3152. Zhao Y T, Huang X J, Zhong T Y, et al. Spatial pattern evolution of carbon emission intensity from energy consumption in China[J]. Environmental Science, 2011,32(11):3145-3152.
[18]
张华明,元鹏飞,朱治双.中国城市人口规模、产业集聚与碳排放[J]. 中国环境科学, 2021,41(5):2459-2470. Zhang H M, Yuan P F, Zhu Z S. City population size, industrial agglomeration and CO2 emission in Chinese prefectures[J]. China Environmental Science, 2021,41(5):2459-2470.
[19]
韩 楠,罗新宇.多情景视角下京津冀碳排放达峰预测与减排潜力[J]. 自然资源学报, 2022,37(5):1277-1288. Han N, Luo X Y. Carbon emission peak prediction and reduction potential in Beijing-Tianjin-Hebei region from the perspective of multiple scenarios[J]. Journal of Natural Resources, 2022,37(5):1277-1288.
[20]
汪 浩,陈操操,潘 涛,等.县域尺度的京津冀都市圈CO2排放时空演变特征[J]. 环境科学, 2014,35(1):385-393. Wang H, Chen C C, Pan Tao, et al. County scale characteristics of CO2 emission's spatial-temporal evolution in the Beijing-Tianjin-Hebei metropolitan region[J]. Environmental Science, 2014,35(1):385-393.
[21]
李艳梅,孙丽云,张红丽,等.京津冀区域间产业转移对能源消费碳排放强度的影响[J]. 资源科学, 2017,39(12):2275-2286. Li Y M, Sun L Y, Zhang H L, et al. The impact of interregional transfer of industries on carbon emission intensity of energy consumption in Beijing-Tianjin-Hebei[J]. Resources Science, 2017,39(12):2275-2286.
[22]
赵荣钦,张 帅,黄贤金,等.中原经济区县域碳收支空间分异及碳平衡分区[J]. 地理学报, 2014,69(10):1425-1437. Zhao R Q, Zhang S, Huang X J, et al. Spatial variation of carbon budget and carbon balance zoning of Central Plains Economic Region at county-level[J]. Acta Geographica Sinica, 2014,69(10):1425-1437.
[23]
李 璐,董 捷,徐 磊,等.功能区土地利用碳收支空间分异及碳补偿分区——以武汉城市圈为例[J]. 自然资源学报, 2019,34(5):1003-1015. Li L, Dong J, Xu L, et al. Spatial variation of land use carbon budget and carbon compensation zoning in functional areas:A case study of Wuhan Urban Agglomeration[J]. Journal of Natural Resources, 2019, 34(5):1003-1015.
[24]
夏四友,杨 宇.基于主体功能区的京津冀城市群碳收支时空分异与碳补偿分区[J]. 地理学报, 2022,77(3):679-696. Xia S Y, Yang Y. Spatio-temporal differentiation of carbon budget and carbon compensation zoning in Beijing-Tianjin-Hebei Urban Agglomeration based on the Plan for Major Function-oriented Zones[J]. Acta Geographica Sinica, 2022,77(3):679-696.
[25]
李 健,马晓芳,苑清敏.区域碳排放效率评价及影响因素分析[J]. 环境科学学报, 2019,39(12):4293-4300. Li J, Ma X F, Yuan Q M. Evaluation and influencing factors' analysis of regional carbon emission efficiency[J]. Acta Scientiae Circumstantiae, 2019,39(12):4293-4300.
[26]
郑 航,叶阿忠.城市群碳排放空间关联网络结构及其影响因素[J]. 中国环境科学, 2022,42(5):2413-2422. Zheng H, Ye A Z. Spatial correlation network structure and influencing factors of carbon emission in urban agglomeration[J]. China Environmental Science, 2022,42(5):2413-2422.
[27]
北京市统计局.北京统计年鉴[M]. 北京:中国统计出版社, 2005. Beijing Municipal Bureau of Statistics. Beijing statistical yearbook[M]. Beijing:China Statistics Press, 2005.
[28]
北京市统计局.北京统计年鉴[M]. 北京:中国统计出版社, 2010. Beijing Municipal Bureau of Statistics. Beijing statistical yearbook[M]. Beijing:China Statistics Press, 20010.
[29]
北京市统计局.北京统计年鉴[M]. 北京:中国统计出版社, 2015. Beijing Municipal Bureau of Statistics. Beijing statistical yearbook[M]. Beijing:China Statistics Press, 2015.
[30]
北京市统计局.北京统计年鉴[M]. 北京:中国统计出版社, 2017. Beijing Municipal Bureau of Statistics. Beijing statistical yearbook[M]. Beijing:China Statistics Press, 2017.
[31]
天津市统计局.天津统计年鉴[M]. 北京:中国统计出版社, 2005. Tianjin Municipal Bureau of Statistics. Tianjin statistical yearbook[M]. Beijing:China Statistics Press, 2005.
[32]
天津市统计局.天津统计年鉴[M]. 北京:中国统计出版社, 2010. Tianjin Municipal Bureau of Statistics. Tianjin statistical yearbook[M]. Beijing:China Statistics Press, 2010.
[33]
天津市统计局.天津统计年鉴[M]. 北京:中国统计出版社, 2015. Tianjin Municipal Bureau of Statistics. Tianjin statistical yearbook[M]. Beijing:China Statistics Press, 2015.
[34]
天津市统计局.天津统计年鉴[M]. 北京:中国统计出版社, 2017. Tianjin Municipal Bureau of Statistics. Tianjin statistical yearbook[M]. Beijing:China Statistics Press, 2017.
Chen J, Gao M, Cheng S, et al. County-level CO2 emissions and sequestration in China during 1997~2017[J]. Scientific Data, 2020, 7(1):1-12.
[40]
方大春,孙明月.高铁时代下长三角城市群空间结构重构——基于社会网络分析[J]. 经济地理, 2015,35(10):50-56. Fang D C, Sun M Y. The reconstruction of the spatial structure of the Yangtze River Delta city group in the high-speed rail era-based on the social network analysis[J]. Economic Geography, 2015,35(10):50-56.
[41]
魏燕茹,陈松林.福建省土地利用碳排放空间关联性与碳平衡分区[J]. 生态学报, 2021,41(14):5814-5824. Wei Y R, Chen S L. Spatial correlation and carbon balance zoning of land use carbon emissions in Fujian Province[J]. Acta Ecologica Sinica, 2021,41(14):5814-5824.
[42]
赵康杰,吴亚君.高铁网络与经济网络演进特征及协同关系研究——以中国省域中心城市为例[J]. 华东经济管理, 2020,34(2):77-85. Zhao K J, Wu Y J. Study on evolution characteristics and synergy between high-speed railway networkand economic network in China's Provincial center cities:take provincial center cities for example[J]. East China Economic Management, 2020,34(2):77-85.
[43]
Dou Y, Luo X, Dong L, et al. An empirical study on transit-oriented low-carbon urban land use planning:exploratory spatial data analysis (ESDA) on Shanghai, China[J]. Habitat International, 2016,53:379-89.
[44]
Anselin L. Local indicators of spatial association-LISA[J]. Geographical Analysis, 1995,27(2):93-115.
[45]
陈国亮,陈建军.产业关联、空间地理与二三产业共同集聚——来自中国212个城市的经验考察[J]. 管理世界, 2012,(4):82-100. Chen G L, Chen J J. Industrial Relevance, Spatial geography and the joint agglomeration of secondary and tertiary industries-an empirical study from 212 cities in China[J]. Journal of Management World, 2012,(4):82-100.
[46]
Marshall A. Principles of Economics[M]. London:Macmillan Press, 1920:21-27.
[47]
王 凤,刘艳芳,孔雪松,等.基于社会网络理论的农村社会空间联系分析——以武汉市黄陂区李集镇为例[J]. 经济地理, 2016,36(4):141-148,202. Wang F, Liu Y F, Kong X S, et al. Analysis of spatial interaction in rural society based on theory of social network:a case of Liji Town in Wuhan city[J]. Economic Geography, 2016,36(4):141-148,202.