长三角城市群多部门碳排放的时空特征、影响要素与空间规划响应研究

Temporal and Spatial Dynamic Characteristics, Influencing Factors and Corresponding Planning Strategies of Carbon Emissions by Sectors in the Yangtze River Delta

刘 超
同济大学建筑与城市规划学院 助理教授,博士 自然资源部国土空间智能规划技术重点实验室 研究员

张洪博
同济大学建筑与城市规划学院 硕士研究生

黄雨嫣
同济大学建筑与城市规划学院 硕士研究生

摘要: 从碳排放总量及工业、民用、交通、电力四部门排放量出发,可视化分析长三角城市群碳排放的时空特征,构建模型分析 其影响要素,并从国土空间规划的视角提出响应策略。首先,对1990—2021年长三角碳排放进行时空数据可视化;其次, 通过空间自相关分析碳排放空间协同性;再次,考虑国土空间规划分区,采用改进STIRPAT模型遴选出社会经济、建成 环境方面对总量、地均碳排放的显著影响因子及其弹性系数;最后,提出针对长三角地区碳减排的空间规划策略。结果 表明,碳排放以区域性中心城区为聚集,城市化水平、人口要素、人均财富等要素会促进区域碳排放。基于此,提出碳排 放分区划定、低碳产业引导、用地分类与格局优化等空间响应策略。

Abstract: In this paper, we visualize and analyze the spatial and temporal characteristics of carbon emissions in the Yangtze River Delta urban agglomeration from the perspective of total carbon emissions and emissions from the industrial, civil, transportation, and electric power sectors, construct a model to analyze influencing factors, and propose a response strategy from the perspective of territorial spatial planning. Firstly, the spatial and temporal data of carbon emissions in the Yangtze River Delta from 1990 to 2021 are visualized. Secondly, the spatial pattern of carbon emissions is analyzed through spatial autocorrelation. Thirdly, taking into consideration of national spatial planning zones, the improved STIRPAT model is used to select the factors and their elasticity coefficients of the socioeconomic and built-environmental factors that have significant impacts on the total amount of carbon emissions and the average per capita carbon emissions. Finally, spatial planning strategies for reducing carbon emissions in the Yangtze River Delta region are proposed. The results show that carbon emissions are clustered in the regional central city, and urbanization level, population factor, per capita wealth, and other factors contribute to regional carbon emissions. Based on this, spatial response strategies are proposed, including delineation of carbon emission zoning, guidance of low-carbon industries, and optimization of land use classification and pattern.

关键词:碳排放;STIRPAT模型;国土空间规划;时空特征;长三角

Keyword: carbon emission; STIRPAT Model; territorial spatial planning; temporal and spatial dynamic characteristics; Yangtze River Delta

中图分类号:TU984

文献标识码: A

资金资助

中国 中国青年自然科学基金项目 52108060

上海市 上海市科技支撑双碳专项 22DZ1207800

上海市 上海市启明星人才项目 22QB1404900

胡鞍钢. 中国实现2030年前碳达峰目标及主要途径[J]. 北京工业大学学报(社会科学版),2021,21(3):1-15.
HU An'gang. China's goal of peaking carbon dioxide emissions before 2030 and the main ways to achieve it[J]. Journal of Beijing University of Technology (Social Sciences Edition), 2021, 21(3): 1-15.
李雨晨,秦宇,杨柳,等. 长江上游大中型水库碳排放量估算与分析:以IPCC国家温室气体清单指南为基础[J]. 湖泊科学,2023,35(1):131-144.
LI Yuchen, QIN Yu, YANG Liu, et al. Estimation and analysis of carbon emissions from large and medium-sized reservoirs in the upper reaches of the Yangtze River: based on the IPCC guidelines for national greenhouse gas inventories[J]. Journal of Lake Sciences, 2023, 35(1): 131-144.
赵俊,王迪,付士磊. 基于二氧化碳通量监测的低碳城市研究进展与思考[J]. 城市建筑空间,2022,29(5):243-245.
ZHAO Jun, WANG Di, FU Shilei. Research pro-gress and reflections on low-carbon cities based on carbon dioxide flux monitoring[J]. Urban Architecture and Space, 2022, 29(5): 243-245.
孟天佑. 城市碳排放规律及基于CO2响应系数的无限长线源扩散模型研究[D]. 徐州:中国矿业大学,2015.
MENG Tianyou. Research on urban carbon emission patterns and infinite long line source diffusion model based on CO2 response coeffi-cient[D]. Xuzhou: China University of Mining and Technology, 2015.
刘良云,陈良富,刘毅,等. 全球碳盘点卫星遥感监测方法、进展与挑战[J]. 遥感学报,2022,26(2):243-267.
LIU Liangyun, CHEN Liangfu, LIU Yi, et al. Satellite remote sensing monitoring methods, progress, and challenges for global carbon
inventory[J]. Journal of Remote Sensing, 2022,26(2): 243-267.
彭竞霄. 长株潭城市群碳排放仿真模拟及低碳空间规划策略研究[D]. 株洲:湖南工业大学,2021.
PENG Jingxiao. Simulation of carbon emissions and low-carbon spatial planning strategies for the Changsha-Zhuzhou-Xiangtan urban agglomeration[D]. Zhuzhou: Hu'nan University of Technology, 2021.
王伟,邹伟,张国彪,等. “双碳”目标下的城市群国土空间规划路径与治理机制[J]. 环境保护,2022,50(s1):64-69.
WANG Wei, ZOU Wei, ZHANG Guobiao, et al. Land spatial planning path and governance mechanism for urban agglomerations under the "dual carbon" goal[J]. Environmental Protection, 2022, 50(s1): 64-69.
鄢金明,王建军. 双碳目标下的广州国土空间规划编制思考[C]//面向高质量发展的空间治理——2021中国城市规划年会论文集. 北京:中
国建筑工业出版社,2021:525-532.
YAN Jinming, WANG Jianjun. Thoughts on the compilation of Guangzhou's territorial spatial planning under the dual carbon goal[C]//Spatial governance for high-quality development -proceedings of the 2021 China Annual National Planning Conference. Beijing: China Architecture & Building Press, 2021: 525-532.
张赫,王睿,于丁一,等. 基于差异化控碳思路的县级国土空间低碳规划方法探索[J]. 城市规划学刊,2021(5):58-65.
ZHANG He, WANG Rui, YU Dingyi, et al. Exploring low-carbon planning methods for countylevel territorial space based on differentiated carbon control ideas[J]. Urban Planning Forum, 2021(5):58-65.
DONG J, LI C. Structure characteristics and influencing factors of China's carbon emission spatial correlation network: a study based on the dimension of urban agglomerations[J]. Science of the Total Environment, 2022, 853: 158613.
WANG G Z, HAN Q, DE VRIES B. The multi-objective spatial optimization of urban land use based on low-carbon city planning[J]. Ecological Indicators, 2021, 125: 107540.
ZHANG A X, DENG R G. Spatial-temporal evolution and influencing factors of net carbon sink efficiency in Chinese cities under the background of carbon neutrality[J]. Journal of Cleaner Production, 2022, 365: 132547.
HONG S F, HUI E C, LIN Y Y. Relationship between urban spatial structure and carbon emissions: a literature review[J]. Ecological
Indicators, 2022, 144: 109456.
龚利,屠红洲,龚存. 基于STIRPAT模型的能源消费碳排放的影响因素研究——以长三角地区为例[J]. 工业技术经济,2018,37(8):95-102.
GONG Li, TU Hongzhou, GONG Cun. Research on influencing factors of carbon emissions from energy consumption based on STIRPAT model - taking the Yangtze River Delta as an example[J]. Journal of Industrial Technological Economics, 2018, 37(8): 95-102.
LI Z, WANG F, KANG T T, et al. Exploring differentiated impacts of socioeconomic factors and urban forms on city-level CO2 emissions in China: spatial heterogeneity and varyingimportance levels[J]. Sustainable Cities and Society, 2022, 84: 104028.
闫凤英,杨一苇. 空间规划的碳排放约束机制与治理框架[J]. 西部人居环境学刊,2021,36(3):37-45.
YAN Fengying, YANG Yiwei. Carbon emission constraint mechanism and governance framework for spatial planning[J]. Journal of Human Settlements in West China, 2021, 36(3): 37-45.
国家发展改革委,住房城乡建设部. 长江三角洲城市群发展规划(2015—2030)[R]. 2016.
National Development and Reform Commission,Ministry of Housing and Urban-Rural Development.Yangtze River Delta urban agglomera-tion development plan (2015-2030)[R]. 2016.
何斌,梅士龙,陆琛莉,等. MEIC排放清单在空气质量模式中的应用研究[J]. 中国环境科学,2017,37(10):3658-3668.
HE Bin, MEI Shilong, LU Chenli, et al. Application of MEIC emission inventory in air quality modeling[J]. China Environmental Science, 2017, 37(10): 3658-3668.
GONG P, CHEN B, LI X C, et al. Mapping essential urban land use categories in China (EULUC-China): preliminary results for 2018[J].Science Bulletin, 2020, 65(3): 182-187.
陈彦光. 基于Moran统计量的空间自相关理论发展和方法改进[J]. 地理研究,2009,28(6):1449-1463.
CHEN Yanguang. Development and improvement of spatial autocorrelation theory based on Moran's statistic[J]. Geographical Research, 2009, 28(6): 1449-1463.
孙俊,潘玉君,和瑞芳,等. 地理学第一定律之争及其对地理学理论建设的启示[J]. 地理研究,2012,31(10):1749-1763.
SUN Jun, PAN Yujun, HE Ruifang, et al. The debate on the first law of geography and its enlightenment to the construction of geographical theory[J]. Geographical Research, 2012, 31(10):1749-1763.
林彤,高建岗,王亚华. 基于国家耕地质量等别指数和空间自相关的苏北地区耕地保护分区[J].农业资源与环境学报,2023,40(3):525-533.
LIN Tong, GAO Jian'gang, WANG Yahua. Farmland protection zoning in northern Jiangsu based on national farmland quality grade index and spatial autocorrelation[J]. Journal of Agricultural Resources and Environment, 2023, 40(3): 525-533.
YORK R, ROSA E A, DIETZ T. STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts[J].
Ecological Economics, 2003(3): 46.
王瑛,何艳芬. 中国省域二氧化碳排放的时空格局及影响因素[J]. 世界地理研究,2020,29(3):512-522.
WANG Ying, HE Yanfen. Spatio-temporal pattern and influencing factors of carbon dioxide emissions in China's provinces[J]. World Geographic Research, 2020, 29(3): 512-522.
任晓松,赵国浩. 中国工业碳排放及其影响因素灰色预测分析——基于STIRPAT模型[J]. 北京交通大学学报(社会科学版),2014,13(4):18-24.
REN Xiaosong, ZHAO Guohao. Gray prediction analysis of China's industrial carbon emissions and its influencing factors - based on the STIRPAT model[J]. Journal of Beijing Jiaotong University (Social Science Edition), 2014, 13(4): 18-24.
陈邦丽,徐美萍. 中国碳排放影响因素分析——基于面板数据STIRPAT-Alasso模型实证研究[J].生态经济,2018,34(1):20-24.
CHEN Bangli, XU Meiping. Analysis of the influencing factors of China's carbon emissions - empirical research based on the STIRPAT-Alasso model of panel data[J]. Ecological Economy, 2018, 34(1): 20-24.
高明,吴雪萍,郭施宏. 城市化进程、环境规制与大气污染——基于STIRPAT模型的实证分析[J].工业技术经济,2016,35(9):110-117.
GAO Ming, WU Xueping, GUO Shihong.Urbanization process, environmental regulation and air pollution - based on the empirical analysis of the STIRPAT model[J]. Industrial Technology Economy, 2016, 35(9): 110-117.
陈占明,吴施美,马文博,等. 中国地级以上城市二氧化碳排放的影响因素分析:基于扩展的STIRPAT模型[J]. 中国人口•资源与环境,2018,28(10):45-54.
CHEN Zhanming, WU Shimei, MA Wenbo, et al. Analysis of the influencing factors of carbon dioxide emissions in cities above the prefecture level in China: based on the extended STIRPAT model[J]. China Population, Resources and Environment, 2018, 28(10): 45-54.
宋德勇,徐安. 中国城镇碳排放的区域差异和影响因素[J]. 中国人口•资源与环境,2011,21(11):8-14.
SONG Deyong, XU An. Regional differences and influencing factors of urban carbon emissions in China[J]. China Population, Resources and Environment, 2011, 21(11): 8-14.
孙敬水,陈稚蕊,李志坚. 中国发展低碳经济的影响因素研究——基于扩展的STIRPAT模型分析[J]. 审计与经济研究,2011,26(4):85-93.
SUN Jingshui, CHEN Zhirui, LI Zhijian. Research on the influencing factors of China's development of low-carbon economy - based on the analysis of the extended STIRPAT model[J]. Audit and Economic Research, 2011, 26(4): 85-93.
BO Z, DAN T, MENG L, et al. Trends in China's anthropogenic emissions since 2010 as the consequence of clean air actions[J]. Atmospheric Chemistry and Physics, 2018, 18(19): 14095-14111.
LI M, LIU H, GENG G, et al. Anthropogenic emission inventories in China: a review[J].National Science Review, 2017, 4(6): 834-866.
张乐勤,李荣富,陈素平,等. 安徽省1995年—2009年能源消费碳排放驱动因子分析及趋势预测——基于STIRPAT模型[J]. 资源科学,2012,34(2):316-327.
ZHANG Leqin, LI Rongfu, CHEN Suping, et al. Analysis and trend prediction of driving factors of energy consumption carbon emissions in Anhui Province from 1995 to 2009 - based on the STIRPAT model[J]. Resource Science, 2012, 34(2): 316-327.

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