文献类型：期刊文献

英文题名：Spatial differentiation of carbon emissions from residential energy consumption: A case study in Kaifeng, China

作者：Rong, Peijun[1,2];Zhang, Yan[3];Qin, Yaochen[2];Liu, Gangjun[4];Liu, Rongzeng[1]

第一作者：Rong, Peijun

通讯作者：Zhang, Y[1]

机构：[1]Henan Univ Econ & Law, Collaborat Innovat Ctr Urban & Rural Harmonious D, Zhengzhou 450052, Peoples R China;[2]Henan Univ, Sch Environm & Planning, Kaifeng 475004, Peoples R China;[3]Qiongtai Normal Univ, Ecol Econ Res Ctr, Haikou 571199, Hainan, Peoples R China;[4]RMIT Univ, Coll Sci Engn & Hlth, Melbourne, Vic 3000, Australia

第一机构：河南财经政法大学

通讯机构：[1]corresponding author), Qiongtai Normal Univ, Ecol Econ Res Ctr, Haikou 571199, Hainan, Peoples R China.

年份：2020

卷号：271

外文期刊名：JOURNAL OF ENVIRONMENTAL MANAGEMENT

收录：;WOS:【SSCI(收录号:WOS:000558812000008)，SCI-EXPANDED(收录号:WOS:000558812000008)】；

基金：This research was supported by grants from the Soft Science Research Plan of Henan Province (No. 41901588), Hainan Provincial Natural Science Foundation of China (No. 2019RC248), National Natural Science Foundation of China (No. 41671536), Humanities and Social Sciences Project of Henan Provincial Department of Education (No. 2019-ZZJH-093, 2019-ZZJH-149), Leading talent project of basic research of Centaline thousand talents plan (No. ZYQR201810122), Research project of Huamao Financial Research Institute (No. HYK-2019007).

语种：英文

外文关键词：Carbon emissions; Residential energy consumption; Spatial pattern; Differentiation mechanism; GWR

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.