通过计算2000—2019年中国336个地级及以上城市碳排放和碳汇数据,构建城市碳足迹压力指数,从七大地区和城市规模的视角分析其差异、极化和空间集聚特征。研究发现:城市总体碳足迹压力呈增长态势,高值集中在华南、华东和华北地区,低值集中在西南地区,城市碳足迹压力与城市规模成正比。城市碳足迹压力总体差异水平较大,子群间净差异是总体差异的主要来源,主要集中在华南—西南地区。从城市规模来看,碳足迹压力差异主要集中在城市规模差异较大的组合。城市碳足迹压力极化水平下降明显,主要由认同度下降导致。城市碳足迹压力空间集聚类型主要表现为高—高集聚和低—低集聚,前者集中在华南、华东和华北地区,后者集中在西南地区。一线和新一线城市以高—高集聚为主,低—低集聚城市数量与城市规模成反比。
Based on the calculation of carbon emission and carbon sink data of 336 prefecture-level and above cities in China from 2000-2019, this paper constructs the city carbon footprint pressure index and analyzes the differences, polarization and spatial agglomeration characteristics from the perspective of seven regions and city size. The results are as follows: the carbon footprint pressure of Chinese cities is increasing. The high values are concentrated in South, East and North China, and the low values are concentrated in Southwest China. The carbon footprint pressure of cities is positively proportional to city size. The overall difference level is large, and the net difference between subgroups is the main source of overall difference, mainly concentrated in South China-Soutwest China, as well as the combination with large difference in city scale. The level of polarization decreases significantly, mainly caused by the decrease of identity. The main manifestations are high-high and low-low agglomeration, with the former concentrated in South, East and North China, and the latter in Southwest China. First-tier and new first-tier cities are dominated by high-high agglomeration, and the number of low-low agglomeration cities is inversely proportional to city size.
[1] 张晓娣.正确认识把握我国碳达峰碳中和的系统谋划和总体部署——新发展阶段党中央双碳相关精神及思路的阐释[J].上海经济研究, 2022(2): 14-33
[2] 庄贵阳,魏鸣昕.城市引领碳达峰、碳中和的理论和路径[J].中国人口·资源与环境,2021(9):114-121
[3] 杜之利,苏彤,葛佳敏,等.碳中和背景下的森林碳汇及其空间溢出效应[J].经济研究,2021(12):187-202
[4] Zhang C H, Ju W M, Chen J M, et al. China’s forest biomass carbon sink based on seven inventories from 1973 to 2008[J]. Climatic Change, 2013(3-4): 933-948
[5] 张逸如,刘晓彤,高文强,等.天然林保护工程区近20年森林植被碳储量动态及碳汇(源)特征[J].生态学报,2021(13):5093-5105
[6] 尚杰,杨滨键.种植业碳源、碳汇测算与净碳汇影响因素动态分析:山东例证[J].改革, 2019(6):123-134
[7] Chen J D, Gao M, Cheng S L, et al. County-level CO2emissions and sequestration in China during 1997-2017[J]. Scientific Data, 2020(1):1-12
[8] 禹湘,陈楠,李曼琪.中国低碳试点城市的碳排放特征与碳减排路径研究[J].中国人口·资源与环境,2020(7):1-9
[9] 王少剑,高爽,黄永源,等.基于超效率SBM模型的中国城市碳排放绩效时空演变格局及预测[J].地理学报,2020(6):1316-1330
[10] 韩梦瑶,刘卫东,谢漪甜,等.中国省域碳排放的区域差异及脱钩趋势演变[J].资源科学,2021(4):710-721
[11] 李建豹,黄贤金,揣小伟,等.长三角地区碳排放效率时空特征及影响因素分析[J].长江流域资源与环境,2020(7):1486-1496
[12] 张恒硕,李绍萍,彭民.中国农村能源消费碳排放区域非均衡性及驱动因素动态识别[J].中国农村经济,2022(1):112-134
[13] 邓荣荣,张翱祥.中国城市数字金融发展对碳排放绩效的影响及机理[J].资源科学,2021(11):2316-2330
[14] Oda T, Maksyutov S, Andres R J. The Open-source Data Inventory for Anthropogenic CO2, version 2016(ODIAC2016): A global monthly fossil fuel CO2 gridded emissions data product for tracer transport simulations and surface flux inversions[J]. Earth System Science Data, 2018(1):87-107
[15] Yang J, Huang X. The 30m annual land cover dataset and its dynamics in China from 1990 to 2019[J]. Earth Syst. Sci. Data, 2021(8): 3907–3925
[16] Chen J D, Fan W, Li D, et al. Driving factors of global carbon footprint pressure: Based on vegetation carbon sequestration[J]. Applied Energy, 2020, 267:114914
[17] 耿涌,董会娟,郗凤明,等.应对气候变化的碳足迹研究综述[J].中国人口·资源与环境,2010(10):6-12
[18] Venetoulis J, Talberth J. Refining the ecological footprint[J]. Environment Development & Sustainability, 2008(4):441-469
[19] Mancini M S, Galli A, Niccolucci V, et al. Ecological footprint: Refining the carbon footprint calculation[J]. Ecological Indicators, 2016, 61:390-403
[20] Dagum C. A new approach to the decomposition of the Giniincome inequality ratio[J]. Income Inequality, Poverty, and Economic Welfare, 1998:47-63
[21] 仲崇阳,胡彬,余子然.股东权益司法保护的空间非均衡及动态演进——相对差异与绝对差异双重视角的考察[J].财贸研究,2021(6):66-79
[22] Esteban J,Ray D. On the measurement of polarization[J]. Econometrica,1994(4):819-851
[23] Duclos J Y,Esteban J,Ray D. Polarization: concepts, measurement, estimation[J]. Econometrica,2004(6):1737-1772
[24] 林春,康宽,孙英杰.中国普惠金融的区域差异与极化趋势:2005—2016[J].国际金融研究,2019(8):3-13
[25] Tober W. A computer movie simulating urban growth in the Detroit region. Economic Geography, 1970(2): 234-240
[26] 吴英迪,蒙吉军.中国自然资源生态服务重要性评价与空间格局分析[J].自然资源学报,2022(1):17-33
[27] 张琛,彭超,孔祥智.中国农户收入极化的趋势与分解——来自全国农村固定观察点的证据[J].劳动经济研究,2019(2):21-41
[28] 潘家华,等.生态文明建设的理论构建与实践探索[M].中国社会科学出版社, 2019