Spatial patterns and driving factors of urban residential embedded carbon emissions: An empirical study in Kaifeng, China

被引:0
|
作者
Rong P. [1 ,2 ]
Zhang Y. [3 ]
Qin Y. [2 ]
Liu G. [4 ]
Liu R. [1 ]
机构
[1] Collaborative Innovation Center on Urban and Rural Harmonious Development of Henan Province, Henan University of Economics and Law, Zhengzhou
[2] School of Environment and Planning, Henan University, Kaifeng
[3] Ecological Economic Research Center, Qiongtai Normal University, Haikou
[4] College of Science, Engineering and Health, RMIT University, Melbourne, 3000, VIC
基金
中国国家自然科学基金; 海南省自然科学基金;
关键词
Carbon emissions; Differentiation mechanism; GWR; Residential energy consumption; Spatial pattern;
D O I
10.1016/j.jenvman.2020.110895
中图分类号
学科分类号
摘要
Effective strategies, policies and measures for carbon emission reduction need to be developed and implemented according to good understanding of both local conditions and spatial differentiation mechanism of energy consumption associated with human activities at high resolution. In the study, we first collected statistical yearbooks, high resolution remotely sensed imageries, and 3895 usable questionnaires for the urban areas of Kaifeng; then measured the carbon emissions from household energy consumption, using the accounting method provided in the IPCC GHG Inventory Guidelines; and finally applied both exploratory and explanatory statistical methods to characterize the spatial pattern of carbon emissions at high resolution, identify key influencing factors, and gain better understanding of the spatial differentiation mechanism of urban residential carbon emissions. Our study reached the following conclusions: (1) Central heating facilities with controllable flow are important for carbon emissions reduction, but its spatial distribution shows unfairness; (2) Spatial clusters of high carbon emission areas were primarily located in the outer suburbs of the city, validated to some extent the hypothesis that urban sprawl has a driving effect on the increasing urban residential carbon emissions; (3) Factors like size of residential area, family structure, life style, personal preference and behavior rather than household income have significant impacts on household carbon emissions, implying that effective control of residential areas, promotion of family life and low-carbon lifestyle, and effective guidance of proper behaviors and preferences will play a crucial role in reducing urban residential carbon emissions; and (4) Most of the identified influencing factors exhibit clear and specific spatial patterns and gradients of impact, implying that measures for urban residential carbon emission reduction should be adapted to location conditions. The study has generated a set of concrete evidences and improved understandings of the spatially differentiated mechanisms upon which the formation and deployment of any effective strategies, policies and measures for reducing urban residential carbon emissions should be based. © 2020 Elsevier Ltd
引用
收藏
相关论文
共 50 条
  • [1] Spatial differentiation of carbon emissions from residential energy consumption: A case study in Kaifeng, China
    Rong, Peijun
    Zhang, Yan
    Qin, Yaochen
    Liu, Gangjun
    Liu, Rongzeng
    JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2020, 271
  • [2] Spatial Heterogeneity of Urban Residential Carbon Emissions in China
    Zhang, Jinping
    Qin, Yaochen
    2013 21ST INTERNATIONAL CONFERENCE ON GEOINFORMATICS (GEOINFORMATICS), 2013,
  • [3] Spatiotemporal patterns and driving mechanism of carbon emissions in China's urban residential building sector
    Chen, Huadun
    Du, Qianxi
    Huo, Tengfei
    Liu, Peiran
    Cai, Weiguang
    Liu, Bingsheng
    ENERGY, 2023, 263
  • [4] Drivers and spatial patterns of carbon emissions from residential buildings: An empirical analysis of Fuzhou city (China)
    Li, Xiaojuan
    Lin, Chengxin
    Lin, Mingchao
    Jim, C. Y.
    BUILDING AND ENVIRONMENT, 2024, 257
  • [5] Spatial–temporal heterogeneity and driving factors of carbon emissions in China
    Tao Ding
    Yufei Huang
    Weijun He
    Delin Zhuang
    Environmental Science and Pollution Research, 2021, 28 : 35830 - 35843
  • [6] Analysis of the coupling coordination spatial network and driving factors of urban pollution and carbon emissions in China
    Luo, Qingfeng
    Wang, Jingyuan
    ENVIRONMENTAL RESEARCH COMMUNICATIONS, 2025, 7 (03):
  • [7] Empirical study on Spatial Spillover of provincial carbon emissions and influencing factors in China
    Tong Xin
    Tong Lin
    Li Xuesen
    PROCEEDINGS OF THE 28TH CHINESE CONTROL AND DECISION CONFERENCE (2016 CCDC), 2016, : 1009 - 1013
  • [8] Spatial differentiation of daily travel carbon emissions in small- and medium-sized cities: An empirical study in Kaifeng, China
    Rong, Peijun
    Zhang, Lijun
    Qin, Yaochen
    Xie, Zhixiang
    Li, Yanan
    JOURNAL OF CLEANER PRODUCTION, 2018, 197 : 1365 - 1373
  • [9] Study on the Evolution of Spatial and Temporal Patterns of Carbon Emissions and Influencing Factors in China
    Sun, Maowen
    Liang, Boyi
    Meng, Xuebin
    Zhang, Yunfei
    Wang, Zong
    Wang, Jia
    LAND, 2024, 13 (06)
  • [10] Spatial-Temporal Patterns and Driving Factors of Logistics Carbon Emissions: Case Study of Yangtze River Delta in China
    Zhu, Enyan
    Yao, Jian
    Zheng, Wenjia
    Sun, Chang
    Sha, Mei
    TRANSPORTATION RESEARCH RECORD, 2024, 2678 (11) : 594 - 607