碳中和目标下中国省域碳平衡能力与城镇化的关系

doi:10.31497/zrzyxb.20221208

摘要/Abstract

摘要：

厘清碳平衡能力与城镇化的关系对实现碳中和目标和推动新型城镇化发展具有重要的理论价值及实践意义。采用温室气体清单法、碳吸收清查法、碳平衡指标法和多元城镇化测量法分别测算1999—2018年中国省域碳平衡能力与各类城镇化指标，利用空间自然断点分级法和Granger因果检验法分别分析中国省域碳平衡能力与城镇化的时空演变特征及互动关系。主要结论如下：（1）中国碳排放不断增多，碳吸收不断减少，碳平衡能力呈上升、下降、先减后增和先增后减四种趋势，碳排放呈“东多西少”分布，碳吸收与碳平衡能力分别呈“西多东少”和“西强东弱”分布。（2）中国人口、经济、空间、生态城镇化和城镇化综合指标不断提升，其中空间城镇化大致呈“西高东低”分布，其余则呈“东高西低”分布。（3）除空间城镇化外，中国整体碳平衡能力与各类城镇化的关系均为反馈型，而各省域增长保护型数量最多，中立型数量最少。

关键词: 碳中和, 碳平衡能力, 城镇化, 时空演变, 省域差异

Abstract:

It has great theoretical value and practical significance to clarify the relationship between carbon balance capacity and urbanization for realizing the carbon neutrality target and the development of new urbanization. The greenhouse gas inventory method, carbon absorption inventory method, carbon balance index method and multiple urbanization measurement method were used to calculate the carbon balance capacity and urbanization indicators of various types of China's provincial-level regions from 1999 to 2018 respectively. The spatial natural breakpoint classification method and Granger causality test were used to analyze the spatio-temporal evolution and interaction between China's provincial carbon balance capacity and urbanization. Furthermore, the development paths of new urbanization in different types of regions were discussed. Main conclusions are as follows: Firstly, China's provincial carbon emissions continue to increase, carbon absorption continue to decline and carbon balance capacity showed four trends, namely, increasing, decreasing, decreasing first and then increasing, and increasing first and then decreasing. The spatial distribution of carbon emissions presented a pattern of "more in the east and less in the west", and the spatial distributions of carbon absorption and carbon balance capacity were "more in the west and less in the east" and "stronger in the west and weaker in the east", respectively. Secondly, the population, economy, space, ecological urbanization and urbanization comprehensive indexes of China's provinces were increasing continuously. In addition, the spatial urbanization showed a pattern of "high in the west and low in the east", while the other types of urbanization showed "high in the east and low in the west" distribution. Thirdly, except for spatial urbanization, the relationship between carbon balance capacity and various types of urbanization was feedback type, and the provincial growth and protection type was the most, followed by the reduction and destruction type, and the neutral type was the least. The development path of China's new urbanization can be divided into four types: growth and protection type, destruction and reduction type, feedback type and neutral type. Improving regional carbon balance capacity and enhancing the development path of new urbanization had important theoretical and practical significance for realizing regional sustainable development targets. Regional differences in population, economic, social and ecological development had an influence on the realization of "dual carbon" and new urbanization goals. Therefore, in designing carbon reduction action plans, regional differences should be considered to identify carbon reduction levels and adopt differentiated measures to form carbon reduction networks.

Key words: carbon neutrality, carbon balance capacity, urbanization, spatio-temporal evolution, provincial differences

李竹, 王兆峰, 吴卫, 邵海琴. 碳中和目标下中国省域碳平衡能力与城镇化的关系[J]. 自然资源学报, 2022, 37(12): 3136-3152.

LI Zhu, WANG Zhao-feng, WU Wei, SHAO Hai-qin. The relationship between China's provincial carbon balance capacity and urbanization under carbon neutrality target[J]. JOURNAL OF NATURAL RESOURCES, 2022, 37(12): 3136-3152.

图/表 13

图1

图2

表1

图3

图4

表2

图5

表3

表4

表5

表6

表7

表8

参考文献 39

[1]	习近平. 继往开来,开启全球应对气候变化新征程: 在气候雄心峰会上的讲话. 北京: 人民日报, 2020-12-13(2).
	[ XI J P. Building on past achievements and embarking on a new global journey to tackle climate change: Speech at the Climate Ambition Summit. Beijing: People's Daily, 2020-12-13(2).]
[2]	陆大道, 陈明星. 关于“国家新型城镇化规划(2014—2020)”编制大背景的几点认识. 地理学报, 2015, 70(2): 179-185. doi: 10.11821/dlxb201502001
	[ LU D D, CHEN M X. Several viewpoints on the background of compiling the "National New Urbanization Planning (2014-2020)". Acta Geographica Sinica, 2015, 70(2): 179-185.] doi: 10.11821/dlxb201502001
[3]	王鑫静, 程钰. 城镇化对碳排放效率的影响机制研究: 基于全球118个国家面板数据的实证分析. 世界地理研究, 2020, 29(3): 503-511. doi: 10.3969/j.issn.1004-9479.2020.03.2019211
	[ WANG X J, CHENG Y. Research on the influencing mechanism of urbanization on carbon emission efficiency: Based on an empirical study of 118 countries. World Regional Studies, 2020, 29(3): 503-511.] doi: 10.3969/j.issn.1004-9479.2020.03.2019211
[4]	王锋, 秦豫徽, 刘娟, 等. 多维度城镇化视角下的碳排放影响因素研究: 基于中国省域数据的空间杜宾面板模型. 中国人口·资源与环境, 2017, 27(9): 151-161.
	[ WANG F, QIN Y H, LIU J, et al. A study on the influencing factors of carbon emissions from the perspective of multi-dimensional urbanization: Based on the spatial Dubin panel model of China provinces. China Population, Resources and Environment, 2017, 27(9): 151-161.]
[5]	王磊, 郭灿, 李慧明. 天津城市系统碳通量与碳平衡测度研究. 干旱区资源与环境, 2016, 30(11): 30-36.
	[ WANG L, GUO C, LI H M. Carbon flux and carbon balance in urban system of Tianjin. Journal of Arid Land Resources and Environment, 2016, 30(11): 30-36.]
[6]	郭海湘, 杨钰莹, 左芝鲤. 中国城市群碳平衡仿真模拟研究. 中国地质大学学报: 社会科学版, 2018, 18(2): 114-125.
	[ GUO H X, YANG Y Y, ZUO Z L. Simulation study on urban carbon balance of urban clusters in China. Journal of China University of Geosciences: Social Sciences Edition, 2018, 18(2): 114-125.]
[7]	余光英, 员开奇. 基于碳平衡适宜性评价的城市圈土地利用结构优化. 水土保持研究, 2014, 21(5): 179-184, 192.
	[ YU G Y, YUN K Q. Urban agglomerations land use structure optimization based on carbon balance suitability evaluation. Research of Soil and Water Conservation, 2014, 21(5): 179-184, 192.]
[8]	HUANG W, DENG C B. A geographic approach to carbon accounting of Wisconsin. Journal of Maps, 2016, 12(2): 324-333. doi: 10.1080/17445647.2015.1020892
[9]	胡剑波, 王青松. 基于碳平衡的民族地区生态补偿量化研究. 广西民族研究, 2019, 35(6): 145-154.
	[ HU J B, WANG Q S. An quantitative study on ecological compensation in ethnic minority areas based on carbon balance. Guangxi Ethnic Studies, 2019, 35(6): 145-154.]
[10]	HASENAUER H. The carbon balance of forest ecosystems. Austrian Journal of Forest Science, 2011, 128(1): 33-52.
[11]	葛汝冰, 吝涛, 刘晓芳, 等. 基于城市功能分区的碳收支平衡时空分异研究. 气候变化研究进展, 2016, 12(2): 101-111.
	[ GE R B, LIN T, LIU X F, et al. Study on spatial-temporal differentiation of regional carbon balance based on urban functional zoning. Climate Change Research, 2016, 12(2): 101-111.]
[12]	ZUBIZARRETA G A, PUKKALA T, PELTOLA H. Effects of wood harvesting and utilisation policies on the carbon balance of forestry under changing climate: A finnish case study. Forest Policy and Economics, 2016, 62: 168-176. doi: 10.1016/j.forpol.2015.08.007
[13]	王渊刚, 罗格平, 赵树斌, 等. 新疆耕地变化对区域碳平衡的影响. 地理学报, 2014, 69(1): 110-120.
	[ WANG Y G, LUO G P, ZHAO S B, et al. Effects of arable land change on regional carbon balance in Xinjiang. Acta Geographica Sinica, 2014, 69(1): 110-120.] doi: 10.11821/dlxb201401011
[14]	程分生, 尤龙辉, 叶功富, 等. 亚热带红壤侵蚀区马尾松不同套种模式生态系统碳平衡. 应用生态学报, 2021, 32(4): 1163-1174. doi: 10.13287/j.1001-9332.202104.001
	[ CHENG F S, YOU L H, YE G F, et al. Carbon balance in an interplanting Pinus massoniana stand in subtropical eroded red soil region, China. Chinese Journal of Applied Ecology, 2021, 32(4): 1163-1174.]
[15]	LAFRATTA M, LEACH M, THORPE R B, et al. Economic and carbon costs of electricity balancing services: The need for secure flexible low-carbon generation. Energies, 2021, 14(16): 5123, Doi: 10.3390/en14165123. doi: 10.3390/en14165123
[16]	岳冬冬, 王鲁民, 方海, 等. 基于碳平衡的中国海洋渔业产业发展对策探析. 中国农业科技导报, 2016, 18(4): 1-8.
	[ YUE D D, WANG L M, FANG H, et al. Development strategy of marine fisheries in China based on the carbon balance. Journal of Agricultural Science and Technology, 2016, 18(4): 1-8.] doi: 10.13304/j.nykjdb.2015.695
[17]	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. 地理学报, 2014, 69(10): 1425-1437. doi: 10.11821/dlxb201410003
	[ 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. Acta Geographica Sinica, 2014, 69(10): 1425-1437.] doi: 10.11821/dlxb201410003
[18]	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. 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. Journal of Natural Resources, 2019, 34(5): 1003-1015.] doi: 10.31497/zrzyxb.20190508
[19]	黄华, 蔡克光, 邢谷锐. 基于碳平衡视角的广东省城市低碳发展特征及对策研究. 城市发展研究, 2015, 22(11): 12-18.
	[ HUANG H, CAI K G, XING G R. The low-carbon development features and countermeasures based on carbon balance of the cities in Guangdong province. Urban Development Studies, 2015, 22(11): 12-18.]
[20]	彭文英, 马思瀛, 张丽亚, 等. 基于碳平衡的城乡生态补偿长效机制研究: 以北京市为例. 生态经济, 2016, 32(9): 162-166.
	[ PENG W Y, MA S Y, ZHANG L Y, et al. Long-term mechanism of urban-rural ecological compensation based on carbon balance: A case study of Beijing. Ecological Economy, 2016, 32(9): 162-166.]
[21]	沈杨, 汪聪聪, 高超, 等. 基于城市化的浙江省湾区经济带碳排放时空分布特征及影响因素分析. 自然资源学报, 2020, 35(2): 329-342.
	[ SHEN Y, WANG C C, GAO C, et al. Spatio-temporal distribution and its influencing factors of carbon emissions in economic zone of Zhejiang Bay Area based on urbanization. Journal of Natural Resources, 2020, 35(2): 329-342.] doi: 10.31497/zrzyxb.20200207
[22]	MOUSSA S, KYEREH B, TOUGIANI A, et al. West African Sahelian cities as source of carbon stocks: Evidence from Niger. Sustainable Cities and Society, 2019, 50: 101653, Doi: 10.1016/j.scs.2019.101653. doi: 10.1016/j.scs.2019.101653
[23]	国家统计局. 中国统计年鉴. 北京: 中国统计出版社, 2000—2019.
	[ National Bureau of Statistics. China Statistical Yearbook. Beijing: China Statistics Press, 2000—2019.]
[24]	国家统计局. 中国能源统计年鉴. 北京: 中国统计出版社, 2000—2019.
	[ National Bureau of Statistics. China Energy Statistical Yearbook. Beijing: China Statistics Press, 2000—2019.]
[25]	付超, 于贵瑞, 方华军, 等. 中国区域土地利用/覆被变化对陆地碳收支的影响. 地理科学进展, 2012, 31(1): 88-96. doi: 10.11820/dlkxjz.2012.01.012
	[ FU C, YU G R, FANG H J, et al. Effects of land use and cover change on terrestrial carbon balance of China. Progress in Geography, 2012, 31(1): 88-96.] doi: 10.11820/dlkxjz.2012.01.012
[26]	鲁丰先, 张艳, 秦耀辰, 等. 中国省级区域碳源汇空间格局研究. 地理科学进展, 2013, 32(12): 1751-1759. doi: 10.11820/dlkxjz.2013.12.004
	[ LU F X, ZHANG Y, QIN Y C, et al. Spatial patterns of provincial carbon source and sink in China. Progress in Geography, 2013, 32(12): 1751-1759.] doi: 10.11820/dlkxjz.2013.12.004
[27]	陶波, 葛全胜, 李克让, 等. 陆地生态系统碳循环研究进展. 地理研究, 2001, 20(5): 564-575.
	[ TAO B, GE Q S, LI K R, et al. Progress in the studies on carbon cycle in terrestrial ecosystem. Geographical Research, 2001, 20(5): 564-575.] doi: 10.11821/yj2001050006
[28]	义白璐, 韩骥, 周翔, 等. 区域碳源碳汇的时空格局: 以长三角地区为例. 应用生态学报, 2015, 26(4): 973-980.
	[ YI B L, HAN J, ZHOU X, et al. Spatiotemporal pattern of carbon sources and sinks in Yangtze River Delta Region, China. Chinese Journal of Applied Ecology, 2015, 26(4): 973-980.]
[29]	刘英, 赵荣钦, 焦士兴. 河南省土地利用碳源/汇及其变化分析. 水土保持研究, 2010, 17(5): 154-157, 162.
	[ LIU Y, ZHAO R Q, JIAO S X. Research on carbon sources/sinks of land use of Henan province. Research of Soil and Water Conservation, 2010, 17(5): 154-157, 162.]
[30]	王子超, 熊灵, 王子岚. 陆地边疆省份旅游发展与经济增长的互动效应研究: 基于面板数据的Granger因果检验. 中国软科学, 2016, 31(12): 172-181.
	[ WANG Z C, XIONG L, WANG Z L. The interactive effect between tourism development and economic growth in borderland provinces: A Granger causality test based on panel data. China Soft Science, 2016, 31(12): 172-181.]
[31]	刘晓婷, 陈闻君. 基于ESDA-GIS的新疆能源碳排放空间差异动态演化分析. 干旱区地理, 2016, 39(3): 678-685.
	[ LIU X T, CHEN W J. Dynamic evolution of spatial disparity of energy carbon emissions in Xinjiang based on ESDA-GIS. Arid Land Geography, 2016, 39(3): 678-685.]
[32]	范建双, 虞晓芬, 周琳. 南京市土地利用结构碳排放效率增长及其空间相关性. 地理研究, 2018, 37(11): 2177-2192. doi: 10.11821/dlyj201811005
	[ FAN J S, YU X F, ZHOU L. Carbon emission efficiency growth of land use structure and its spatial correlation: A case study of Nanjing city. Geographical Research, 2018, 37(11): 2177-2192.] doi: 10.11821/dlyj201811005
[33]	IPCC. IPCC Guidelines for National Green Gas Inventories: Volume Ⅱ. Japan: IGES. http://www.ipcc.eh/ipccreports/Methodology-reports.htm , 2006-07-01.
[34]	王刚, 张华兵, 薛菲, 等. 成都市县域土地利用碳收支与经济发展关系研究. 自然资源学报, 2017, 32(7): 1170-1182.
	[ WANG G, ZHANG H B, XUE F, et al. Relations between land use carbon budget and economic development at county level in Chengdu city. Journal of Natural Resources, 2017, 32(7): 1170-1182.]
[35]	卢俊宇, 黄贤金, 戴靓, 等. 基于时空尺度的中国省级区域能源消费碳排放公平性分析. 自然资源学报, 2012, 27(12): 2006-2017.
	[ LU J Y, HUANG X J, DAI L, et al. Spatio-temporal scale analysis on the equality of energy consumption carbon emission distribution in China. Journal of Natural Resources, 2012, 27(12): 2006-2017.]
[36]	尹鹏, 王富喜, 段佩利. 中国基本公共服务效率与城镇化质量的时空耦合关系研究. 地理科学, 2021, 41(4): 571-579. doi: 10.13249/j.cnki.sgs.2021.04.003
	[ YIN P, WANG F X, DUAN P L. Spatial-temporal coupling relationship between basic public service efficiency and urbanization quality in China. Scientia Geographica Sinica, 2021, 41(4): 571-579.] doi: 10.13249/j.cnki.sgs.2021.04.003
[37]	DUMITRESCU E I, HURLIN C. Testing for Granger noncausality in heterogeneous panels. Economic Modelling, 2012, 29: 1450-1460. doi: 10.1016/j.econmod.2012.02.014
[38]	杜强, 陈乔, 杨锐. 基于Logistic模型的中国各省碳排放预测. 长江流域资源与环境, 2013, 22(2): 143-151.
	[ DU Q, CHEN Q, YANG R. Forecast carbon emissions of provinces in China based on Logistic model. Resources and Environment in the Yangtze Basin, 2013, 22(2): 143-151.]
[39]	王怡睿, 黄煌, 石培基. 中国城镇化质量时空演变研究. 经济地理, 2017, 37(1): 90-97.
	[ WANG Y R, HUANG H, SHI P J. Spatial and temporal evolution of urbanization quality in China. Economic Geography, 2017, 37(1): 90-97.] doi: 10.2307/142042

目标层	准则层（权重）	指标（权重）	代码（方向）
城镇化综合指标C	Z₁人口城镇化（0.139）	城镇人口占比/%（0.033）	X₁+
		非农从业人员占比/%（0.105）	X₂+
	Z₂经济城镇化（0.558）	人均GDP/万元（0.139）	X₃+
		二产业产值占比/%（0.020）	X₄+
		三产业产值占比/%（0.071）	X₅+
		人均社会消费品零售额/万元（0.155）	X₆+
		人均社会固定资产投资额/万元（0.173）	X₇+
	Z₃空间城镇化（0.073）	建成区面积占土地面积占比/%（0.073）	X₈+
	Z₄生态城镇化（0.230）	建成区绿化覆盖率/%（0.013）	X₉+
		人均公园绿地面积/m²（0.043）	X₁₀+
		森林覆盖率/%（0.090）	X₁₁+
		工业固体废物综合利用率/%（0.040）	X₁₂+
		生活垃圾无害化处理率/%（0.043）	X₁₃+

省级	年份			省级	年份			省级	年份
省级	1999	2009	2018	省级	1999	2009	2018	省级	1999	2009	2018
上海↑	0.017	0.031	0.042	安徽∩	0.636	0.742	0.652	湖北↑	0.945	1.298	1.625
天津↑	0.053	0.063	0.076	浙江∪	0.690	0.638	0.730	甘肃↑	1.243	1.741	1.908
山东↓	0.201	0.153	0.135	陕西↓	1.854	1.481	0.810	湖南∪	2.018	1.832	2.474
山西↓	0.321	0.245	0.131	广东↑	0.790	0.842	0.892	吉林↑	1.255	1.681	2.490
江苏∪	0.153	0.150	0.160	海南↓	2.294	1.341	1.336	江西∪	2.899	2.255	2.767
宁夏↓	0.393	0.260	0.211	新疆∩	1.941	1.954	1.412	广西∪	3.554	3.088	3.210
北京↑	0.141	0.259	0.431	贵州∪	1.769	1.350	1.429	黑龙江↑	1.779	2.807	3.379
河北↑	0.328	0.343	0.447	重庆↑	0.728	0.960	1.473	四川↑	2.594	2.748	3.710
河南∪	0.469	0.332	0.461	福建↓	2.139	1.611	1.586	青海∪	4.571	4.346	4.375
辽宁↑	0.265	0.367	0.500	内蒙古↓	2.772	1.665	1.539	云南∪	4.580	3.772	5.274

变量	ESC	Z₁	Z₂	Z₃	Z₄	C
LLC检验	-2.995 (0.001)	-2.120 (0.017)	-3.843 (0.000)	-3.208 (0.000)	-4.253 (0.000)	-2.821 (0.002)
Fisher-ADF检验Z值	-7.155 (0.000)	-5.187 (0.000)	-8.880 (0.000)	-6.786 (0.000)	-8.107 (0.000)	-7.552 (0.000)
检验结果	平稳	平稳	平稳	平稳	平稳	平稳

截面单位	ESC→Z₁	Z₁→ESC	因果类型	截面单位	ESC→Z₁	Z₁→ESC	因果类型	截面单位	ESC→Z₁	Z₁→ESC	因果类型
中国	2.808^***	6.354^***	反馈	安徽	0.179	-0.121^**	减少	甘肃	0.257^**	0.113	保护
上海	0.182^*	-0.240	保护	浙江	0.487^***	0.077^***	反馈	湖南	-0.310^*	0.238^***	反馈
天津	0.487^**	0.414^*	反馈	陕西	-0.334^***	-0.833^***	反馈	吉林	0.027	0.470^**	增长
山东	-0.093	-0.046	中立	广东	0.205	0.218^***	增长	江西	0.140	0.049	中立
山西	0.016	-1.351^***	减少	海南	0.006	-0.965^***	减少	广西	-0.041	-0.0002	中立
江苏	0.022	0.167^***	增长	新疆	-0.236	-0.346^***	减少	黑龙江	0.018	0.880^**	增长
宁夏	-0.109	-0.326^*	减少	贵州	-0.357^**	-0.041	破坏	四川	-0.259	0.152^***	增长
北京	0.011	1.760^***	增长	重庆	0.024	0.250^***	增长	青海	-0.020	-0.234	中立
河北	0.076	0.271^***	增长	福建	-0.109^**	-0.038	破坏	云南	-0.028	0.025	中立
河南	-0.110^***	0.210^***	反馈	内蒙古	-0.155^***	0.068	破坏
辽宁	-0.020	0.706^**	增长	湖北	-0.001	0.290^**	增长

截面单位	ESC→Z₂	Z₂→ESC	因果类型	截面单位	ESC→Z₂	Z₂→ESC	因果类型	截面单位	ESC→Z₂	Z₂→ESC	因果类型
中国	7.318^***	7.689^***	反馈	安徽	-0.205^***	-0.177	破坏	甘肃	0.182	-0.022	中立
上海	0.071	-0.287	中立	浙江	0.070^***	0.142^***	反馈	湖南	-0.002	0.491^***	增长
天津	0.561^***	0.437^***	反馈	陕西	-0.121^**	-1.871^***	反馈	吉林	0.145^**	0.484^**	反馈
山东	-0.031	-0.066	中立	广东	0.410^***	0.449^***	反馈	江西	-0.163^*	0.199	破坏
山西	-0.093^***	-0.682	破坏	海南	-0.091^***	-0.931^**	反馈	广西	-0.064	0.006	中立
江苏	-0.226	0.266^***	增长	新疆	0.058	-0.425^***	减少	黑龙江	0.087^**	0.244	保护
宁夏	-0.117^*	-0.355	破坏	贵州	-0.157^*	-0.262	破坏	四川	0.098	0.438^***	增长
北京	-0.069^***	3.571^***	反馈	重庆	-0.033	0.737^***	增长	青海	-0.082^***	0.015	破坏
河北	0.004	0.637^***	增长	福建	-0071^***	-0.063	破坏	云南	0.070^***	0.170	保护
河南	-0.058	0.295^***	增长	内蒙古	-0.151^**	-0.166	破坏
辽宁	0.105	0.565^*	增长	湖北	0.066	0.389^**	增长