文献类型：期刊文献

英文题名：The Determinants of Carbon Emissions in the Chinese Construction Industry: A Spatial Analysis

作者：Lu, Na[1];Feng, Shuyi[2];Liu, Ziming[3];Wang, Weidong[1];Lu, Hualiang[4];Wang, Miao[1]

机构：[1]Jiangsu Univ, Sch Finance & Econ, Zhenjiang 212013, Jiangsu, Peoples R China;[2]Nanjing Agr Univ, Coll Publ Adm, Nanjing 210095, Peoples R China;[3]East China Univ Sci & Technol, Sch Social & Publ Adm, Shanghai 200237, Peoples R China;[4]Changzhou Univ, Sch Business, Changzhou 213146, Peoples R China

年份：2020

卷号：12

期号：4

外文期刊名：SUSTAINABILITY

收录：;WOS:【SSCI(收录号:WOS:000522460200146)，SCI-EXPANDED(收录号:WOS:000522460200146)】；

基金：This research is supported by the Philosophy and Social Science Fund of Education Department of Jiangsu Province (Grant No. 2019SJA1891), the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province, China (Grant No. 17KJB170004), the National Natural Science Foundation of China (NSFC) (Grant No. 71673144 and 71773046), the key Project of Philosophy and Social Science Research in Colleges and Universities in Jiangsu Province (Grant No. 2017ZDIXM061), Humanities and Social Science Foundation of the Ministry of Education of China (Grant No. 16YJC630125), the Fundamental Research Funds for the Central Universities, and the Innovation Programme of the Shanghai Municipal Education Commission (Grant No. 2017-01-07-00-02-E00008).

语种：英文

外文关键词：carbon emissions; the construction industry; spatial analysis; spillover effects

摘要：As the largest carbon emitter in the world, China is confronted with great challenges of mitigating carbon emissions, especially from its construction industry. Yet, the understanding of carbon emissions in the construction industry remains limited. As one of the first few attempts, this paper contributes to the literature by identifying the determinants of carbon emissions in the Chinese construction industry from the perspective of spatial spillover effects. A panel dataset of 30 provinces or municipalities from 2005 to 2015 was used for the analysis. We found that there is a significant and positive spatial autocorrelation of carbon emissions. The local Moran's I showed local agglomeration characteristics of H-H (high-high) and L-L (low-low). The indicators of population density, economic growth, energy structure, and industrial structure had either direct or indirect effects on carbon emissions. In particular, we found that low-carbon technology innovation significantly reduces carbon emissions, both in local and neighboring regions. We also found that the industry agglomeration significantly increases carbon emissions in the local regions. Our results imply that the Chinese government can reduce carbon emissions by encouraging low-carbon technology innovations. Meanwhile, our results also highlight the negative environmental impacts of the current policies to promote industry agglomeration.