Literature DB >> 30473286

Factor decomposition of carbon emissions in Chinese megacities.

Longyu Shi1, Jing Sun2, Jianyi Lin3, Yang Zhao4.   

Abstract

In this article, per capita urban carbon emissions were decomposed into manufacturing, transportation, and construction sectors using logarithmic mean Divisia index (LMDI) method. This new decomposition method can provide information about specific drivers of carbon emissions, including urban growth and resident living standards, rather than general demographic and economic factors identified by traditional methods. Using four Chinese megacities (Beijing, Tianjin, Shanghai, and Chongqing) as case studies, we analyzed the factors that influenced per capita carbon emissions from 2010 to 2015. The results showed that per capita carbon emissions increased in Tianjin and Chongqing whereas decreased in Beijing and Shanghai, and that manufacturing was a key driving force. In these four megacities, energy conservation strategies were successfully implemented despite poor energy structure optimization during 2010-2015. Development of manufacturing and improvement of resident living standards in the cities led to an increase in carbon emissions. The unique dual-core urban form of Tianjin might mitigate the increased carbon emissions caused by the transportation sector. Reductions in carbon emissions could be achieved by further optimizing energy structures, limiting the number of private cars, and controlling per capita construction.
Copyright © 2018. Published by Elsevier B.V.

Entities:  

Keywords:  China megacities; Factor decomposition; LMID; Per capita carbon emissions

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Year:  2018        PMID: 30473286     DOI: 10.1016/j.jes.2018.03.026

Source DB:  PubMed          Journal:  J Environ Sci (China)        ISSN: 1001-0742            Impact factor:   5.565


  1 in total

1.  Can Environmental Quality Improvement and Emission Reduction Targets Be Realized Simultaneously? Evidence from China and A Geographically and Temporally Weighted Regression Model.

Authors:  Feng Dong; Yue Wang; Xiaojie Zhang
Journal:  Int J Environ Res Public Health       Date:  2018-10-24       Impact factor: 3.390

  1 in total

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