城市居民生活碳排放及影响因素的时空异质性

摘要
图/表
参考文献
相关文章 (15)

全文: PDF (2335 KB) HTML (1 KB)
输出: BibTeX | EndNote (RIS)

摘要基于地图可视化、空间自相关、标准差椭圆和空间马尔科夫链探究中国2006~2020年城市居民生活碳排放的时空特征,并采用时空地理加权模型(GTWR)实证考察城市居民生活碳排放影响因素的时空异质性.结果显示:中国城市居民生活碳排放逐年增长,年均增长率为10.12%,但增速逐渐放缓;呈现东高西低的空间差异特征,且在样本后期呈现逐渐收敛态势.城市居民生活碳排放水平的空间分布呈现显著的空间聚集特征;标准差椭圆呈现向心集聚的趋势,且分布重心逐渐向西南移动,累计迁移了68.97km;居民生活碳排放的动态演进受到邻地城市碳排放水平的影响.各影响因素存在明显的时空异质性.时间趋势上,人口密度、经济发展、对外开放和产业结构在大部分城市促进碳排放,但影响力逐年减弱;技术投入和环境规制则降低碳排放,且影响力逐年增强;空间分布上,人口密度、经济发展和对外开放在南部的影响力更强,而技术投入、产业结构和环境规制的影响力在东部更强.

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	许嘉俊
	杨晓军
	李睿

关键词 ：城市, 居民生活碳排放, 影响因素, 时空异质性

Abstract：This paper studied the spatial and temporal features of carbon emission in urban households in China between 2006 and 2020, using these methods including map visualization, spatial autocorrelation, standard deviation ellipse and spatial Markov chain, and tested the spatial and temporal heterogeneity of driving forces using spatio-temporal geographically weighted regression (GTWR). Carbon emission in urban households increased over years with a growth rate of 10.12% on average, however, the growth was gradually stopping, where it was higher in the east and lower in the west, and it converged when time approached the end of the sample period. The spatial distribution of carbon emission in urban households significantly showed a geographic concentration. The standard deviation ellipse tended to show a center agglomeration, and the core of the distribution shifted to the southwest for about 68.97km. The dynamics of the carbon emission in urban households was affected by the carbon emission of neighboring cities. The driving forces showed significant differences across geographic spaces and over time. Temporally, the impact of the driving forces, including population density, economic growth, opening up to the world, and sectoral structure, on carbon emission was positive but weakening over time, and the impact of technology and environmental regulations were negative and growing stronger over time. Spatially, the impact of population density, economic growth, and opening up to the world, were much stronger in the south, and the impact of technology, sectoral structure, and environmental regulation were much stronger in the east.

Key words： city carbon emission in urban households driving forces spatial and temporal heterogeneity

收稿日期: 2023-07-03

PACS:

X24

基金资助:国家社会科学基金资助项目(23BGL222)

作者简介: 许嘉俊(1994-),男,福建泉州人,武汉大学博士研究生,主要从事环境经济学研究.发表论文8篇.jiajunxu@whu.edu.cn.

引用本文:

许嘉俊, 杨晓军, 李睿. 城市居民生活碳排放及影响因素的时空异质性[J]. 中国环境科学, 2024, 44(3): 1732-1742. XU Jia-jun, YANG Xiao-jun, LI Rui. The spatial and temporal heterogeneity of carbon emission and its driving forces in urban households. CHINA ENVIRONMENTAL SCIENCECE, 2024, 44(3): 1732-1742.

链接本文:

http://www.zghjkx.com.cn/CN/ 或 http://www.zghjkx.com.cn/CN/Y2024/V44/I3/1732

[1] 刘莉娜,曲建升,黄雨生,等.中国居民生活碳排放的区域差异及影响因素分析[J]. 自然资源学报, 2016,31(8):1364-1377. Liu L N, Qu J S, Huang Y S, et al. Analyze on the spatio-temporal pattern and influence factors of China's per capita household carbon emissions[J]. Journal of Natural Source, 2016,31(8):1364-1377.
[2] 曾晓莹,邱荣祖,林丹婷,等.中国交通碳排放及影响因素时空异质性[J]. 中国环境科学, 2020,40(10):4304-4313. Zeng X Y, Qiu R Z, Lin D T, et al. Spatio-temporal heterogeneity of transportation carbon emissions and its influencing factors in China[J]. China Environmental Science, 2020,40(10):4304-4313.
[3] 彭璐璐,李楠,郑智远,等.中国居民消费碳排放影响因素的时空异质性[J]. 中国环境科学, 2021,41(1):463-472. Peng L L, Li N, Zheng Z Y, et al. Spatial-temporal heterogeneity of carbon emissions and influencing factors on household consumption of China[J]. China Environmental Science, 2021,41:(1)463-472.
[4] 曾晓莹,邱荣祖,林丹婷,等.中国交通碳排放及影响因素时空异质性[J]. 中国环境科学, 2020,40(10):4304-4313. Zeng X Y, Qiu R Z, Lin D T, et al. Spatio-temporal heterogeneity of transportation carbon emissions and its influencing factors in China[J]. China Environmental Science, 2020,40(10):4304-4313.
[5] 史琴琴,鲁丰先,陈海,等.中原经济区城镇居民消费间接碳排放时空格局及其影响因素[J]. 资源科学, 2018,40(6):1297-1306. Shi Q Q, Lu F X, Chen H, et al. Temporal-spatial patterns and factors affecting indirect carbon emissions from urban consumption in the central plains economic region[J]. Resources Science, 2018,40(6):1297-1306.
[6] 吕倩,刘海滨.基于夜间灯光数据的黄河流域能源消费碳排放时空演变多尺度分析[J]. 经济地理, 2020,40(12):12-21. Lyu Q, Liu H B. Multiscale spatio-temporal characteristics of carbon emission of energy consumption in Yellow River basin based on the nighttime light datasets[J]. Economic Geography, 2020,40(12):12-21.
[7] 苏凯,陈毅辉,范水生,等.市域能源碳排放影响因素分析及减碳机制研究——以福建省为例[J]. 中国环境科学, 2019,39(2):859-867. Su K, Chen Y H, Fan S S, et al. Influencing factors and reduction mechanism of carbon emissions at the city-range:An empirical study on Fujian province[J]. China Environmental Science, 2019,39(2):859-867.
[8] 刘茂辉,刘胜楠,李婧,等.天津市减污降碳协同效应评估与预测[J]. 中国环境科学, 2022,42(8):3940-3949. Liu M H, Liu S N, Li J, et al. The action mechanism of logistics agglomeration on the cross-regional transfer of carbon emissions[J]. China Environmental Science, 2022,42(8):3940-3949.
[9] 王健,林双娇.物流产业集聚对碳排放跨区域转移的作用机制[J]. 中国环境科学, 2021,41(7):3441-3452. Wang J, Lin S J. The action mechanism of logistics agglomeration on the cross-regional transfer of carbon emissions[J]. China Environmental Science, 2021,41(7):3441-3452.
[10] 郭艺,张鹏飞,葛力铭,等.长江经济带电力碳排放时空变化及影响因素——基于区域和产业视角[J]. 中国环境科学, 2023,43(3):1438-1448. Guo Y, Zhang P F, Ge L M, et al. The spatio-temporal variation and influencing factors of electricity-related carbon emissions in the Yangtze River Economic Belt from the region and industry perspectives[J]. China Environmental Science, 2023,43(3):1438-1448.
[11] 马晓君,董碧滢,于渊博,等.东北三省能源消费碳排放测度及影响因素[J]. 中国环境科学, 2018,38(8):3170-3179. Ma X J, Dong B Y, Yu Y B, et al. Measurement of carbon emissions from energy consumption in three Northeastern provinces and its driving factors[J]. China Environmental Science, 2018,38(8):3170-3179.
[12] 范建双,周琳.中国城乡居民生活消费碳排放变化的比较研究[J]. 中国环境科学, 2018,38(11):4369-4383. Fan J S, Zhou L. A comparative study on the changes of residential living consumption carbon emissions in urban and rural China[J]. China Environmental Science, 2018,38(11):4369-4383.
[13] 田中华,杨泽亮,蔡睿贤.广东省能源消费碳排放分析及碳排放强度影响因素研究[J]. 中国环境科学, 2015,35(6):1885-1891. Tian Z H, Yang Z L, Cai R X. Analysis of Guangdong carbon emissions from energy consumption and the driving factors of its intensity change[J]. China Environmental Science, 2015,35(6):1885-1891.
[14] 计志英,赖小锋,贾利军.家庭部门生活能源消费碳排放:测度与驱动因素研究[J]. 中国人口·资源与环境, 2016,26(5):64-72. Ji Z Y, Lai X F, Jia L J. Measurement and driving factors of carbon emissions from household energy consumption[J]. China Population Resources and Environment, 2016,26(5):64-72.
[15] 丁凡琳,陆军,赵文杰.城市居民生活能耗碳排放测算及空间相关性研究——基于287个地级市的数据[J]. 经济问题探索, 2019, 442(5):40-49. Ding F L, Lu J, Zhao W J. Carbon emission measurement for residents' energy consumption and its spatial correlations analysis:a case study of 287 cities in China[J]. Inquiry into Economic Issues, 2019,442(5):40-49.
[16] 曹翔,高瑀.低碳城市试点政策推动了城市居民绿色生活方式形成吗?[J]. 中国人口·资源与环境, 2021,31(12):93-103. Cao X, Gao Y. Has the policy of low-carbon city pilot led to a green life?[J]. China Population Resources and Environment, 2021,31(12):93-103.
[17] 范丹,梁佩凤,刘斌.雾霾污染的间外溢与治理政策的检验分析[J]. 中国环境科学, 2020,40(6):2741-2750 Fan D, Liang P F, Liu B. An analysis of the spatial spillover of smog pollution and policy testing[J]. China Environmental Science, 2020,40(6):2741-2750.
[18] 郭政,陈爽,董平,等.长江三角洲城市群工业污染时空演化及其驱动因素[J]. 中国环境科学, 2019,39(3):1323-1335. Guo Z, Chen S, Dong P. Spatio-temporal evolution of industrial pollution in the Yangtze River Delta urban agglomeration and its driving factors[J]. China Environmental Science, 2019,39(3):1323-1335.
[19] 穆学青,郭向阳,明庆忠,等.黄河流域旅游生态安全的动态演变特征及驱动因素[J]. 地理学报, 2022,77(3):714-735. Mu X Q, Guo X Y, Ming Q Z, et al. Dynamic evolution characteristics and driving factors of tourism ecological security in the Yellow River Basin[J]. Acta Geographica Sinica, 2022,77(3):714-735.
[20] Bo H, Bo W, Barry M. Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices[J]. International Journal of Geographical Information Science, 2010, 24(3/4):383-401.
[21] 崔丹,李沅曦,吴殿廷.京津冀地区旅游经济增长的时空演化及影响因素[J]. 地理学报, 2022,77(6):1391-1410. Cui D, Li Y X, Wu D T. Spatiotemporal evolution and influencing factors of tourism economic growth in Beijing-Tianjin-Hebei region[J]. Acta Geographica Sinica, 2022,77(6):1391-1410.
[22] Dietz T, Rosa E A. Effects of population and affluence on CO₂ emissions[J]. Proceedings of the National Academy of Sciences, 1997,94(1):175-179.
[23] 陈诗一,陈登科.雾霾污染、政府治理与经济高质量发展[J]. 经济研究, 2018,53(2):20-34. Chen S Y, Chen D K. Air pollution, government regulations and high-quality economic development[J]. Economic Research Journal, 2018,53(2):20-34.
[24] 杨友才,牛晓童.社会信任对环境规制碳减排效果的影响——基于中国281个地级市的面板数据[J]. 中国人口·资源与环境, 2023, 33(4):82-92. Yang Y C, Niu X T. Impact of social trust on the effectiveness of environmental regulations on carbon emission reduction:based on panel data from 281 prefecture-level cities in China[J]. China Population Resources and Environment, 2023,33(4):82-92.
[25] Xu J J, Wang J C, Li R, et al. Spatio-temporal effects of urbanization on CO₂ emissions:Evidences from 268 Chinese cities[J]. Energy Policy, 2023,177:113569.
[26] 靳玮,王弟海,张林.碳中和背景下的中国经济低碳转型:特征事实与机制分析[J]. 经济研究, 2022,57(12):87-103. Jin W, Wang D H, Zhang L. China's low-carbon economic transitions towards carbon neutrality:characteristics and mechanisms[J]. Economic Research Journal, 2022,57(12):87-103.
[27] 陈浩,郑洁.技术进步和产业结构调整对中国碳排放强度的影响[J]. 商业研究, 2022,536(6):1-12. Chen H, Zheng J. The impact of technical progress and industrial structure adjustment on China's carbon emission intensity[J]. Commercial Research, 2022,536(6):1-12.
[28] 李子豪.外商直接投资对中国碳排放的门槛效应研究[J]. 资源科学, 2015,37(1):163-174. Li Z H. Threshold effects of foreign direct investment on China's carbon emissions[J]. Resources Science, 2015,37(1):163-174.