Cargando…

Features and drivers for energy-related carbon emissions in mega city: The case of Guangzhou, China based on an extended LMDI model

Based on the apparent energy consumption data, a systematic and comprehensive city-level total carbon accounting approach was established and applied in Guangzhou, China. A newly extended LMDI method based on the Kaya identity was adopted to examine the main drivers for the carbon emissions incremen...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Changjian, Wu, Kangmin, Zhang, Xinlin, Wang, Fei, Zhang, Hongou, Ye, Yuyao, Wu, Qitao, Huang, Gengzhi, Wang, Yang, Wen, Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6370191/
https://www.ncbi.nlm.nih.gov/pubmed/30742627
http://dx.doi.org/10.1371/journal.pone.0210430
_version_ 1783394325990735872
author Wang, Changjian
Wu, Kangmin
Zhang, Xinlin
Wang, Fei
Zhang, Hongou
Ye, Yuyao
Wu, Qitao
Huang, Gengzhi
Wang, Yang
Wen, Bin
author_facet Wang, Changjian
Wu, Kangmin
Zhang, Xinlin
Wang, Fei
Zhang, Hongou
Ye, Yuyao
Wu, Qitao
Huang, Gengzhi
Wang, Yang
Wen, Bin
author_sort Wang, Changjian
collection PubMed
description Based on the apparent energy consumption data, a systematic and comprehensive city-level total carbon accounting approach was established and applied in Guangzhou, China. A newly extended LMDI method based on the Kaya identity was adopted to examine the main drivers for the carbon emissions increments both at the industrial sector and the residential sector. Research results are listed as follow: (1) Carbon emissions embodied in the imported electricity played a significant important role in emissions mitigation in Guangzhou. (2) The influences and impacts of various driving factors on industrial and residential carbon emissions are different in the three different development periods, namely, the 10(th) five-year plan period (2003–2005), the 11(th) five-year plan period (2005–2010), and the 12(th) five-year plan period (2010–2013). The main reasons underlying these influencing mechanisms were different policy measures announced by the central and local government during the different five-year plan periods. (3) The affluence effect (g-effect) was the dominant positive effect in driving emissions increase, while the energy intensity effect of production (e-effect-Production), the economic structure effect (s-effect) and the carbon intensity effect of production (f-effect-Production) were the main contributing factors suppressing emissions growth at the industrial sector. (4) The affluence effect of urban (g-effect-AUI) was the most dominant positive driving factor on emissions increment, while the energy intensity effect of urban (e-effect-Urban) played the most important role in curbing emissions growth at the residential sector.
format Online
Article
Text
id pubmed-6370191
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-63701912019-02-22 Features and drivers for energy-related carbon emissions in mega city: The case of Guangzhou, China based on an extended LMDI model Wang, Changjian Wu, Kangmin Zhang, Xinlin Wang, Fei Zhang, Hongou Ye, Yuyao Wu, Qitao Huang, Gengzhi Wang, Yang Wen, Bin PLoS One Research Article Based on the apparent energy consumption data, a systematic and comprehensive city-level total carbon accounting approach was established and applied in Guangzhou, China. A newly extended LMDI method based on the Kaya identity was adopted to examine the main drivers for the carbon emissions increments both at the industrial sector and the residential sector. Research results are listed as follow: (1) Carbon emissions embodied in the imported electricity played a significant important role in emissions mitigation in Guangzhou. (2) The influences and impacts of various driving factors on industrial and residential carbon emissions are different in the three different development periods, namely, the 10(th) five-year plan period (2003–2005), the 11(th) five-year plan period (2005–2010), and the 12(th) five-year plan period (2010–2013). The main reasons underlying these influencing mechanisms were different policy measures announced by the central and local government during the different five-year plan periods. (3) The affluence effect (g-effect) was the dominant positive effect in driving emissions increase, while the energy intensity effect of production (e-effect-Production), the economic structure effect (s-effect) and the carbon intensity effect of production (f-effect-Production) were the main contributing factors suppressing emissions growth at the industrial sector. (4) The affluence effect of urban (g-effect-AUI) was the most dominant positive driving factor on emissions increment, while the energy intensity effect of urban (e-effect-Urban) played the most important role in curbing emissions growth at the residential sector. Public Library of Science 2019-02-11 /pmc/articles/PMC6370191/ /pubmed/30742627 http://dx.doi.org/10.1371/journal.pone.0210430 Text en © 2019 Wang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Wang, Changjian
Wu, Kangmin
Zhang, Xinlin
Wang, Fei
Zhang, Hongou
Ye, Yuyao
Wu, Qitao
Huang, Gengzhi
Wang, Yang
Wen, Bin
Features and drivers for energy-related carbon emissions in mega city: The case of Guangzhou, China based on an extended LMDI model
title Features and drivers for energy-related carbon emissions in mega city: The case of Guangzhou, China based on an extended LMDI model
title_full Features and drivers for energy-related carbon emissions in mega city: The case of Guangzhou, China based on an extended LMDI model
title_fullStr Features and drivers for energy-related carbon emissions in mega city: The case of Guangzhou, China based on an extended LMDI model
title_full_unstemmed Features and drivers for energy-related carbon emissions in mega city: The case of Guangzhou, China based on an extended LMDI model
title_short Features and drivers for energy-related carbon emissions in mega city: The case of Guangzhou, China based on an extended LMDI model
title_sort features and drivers for energy-related carbon emissions in mega city: the case of guangzhou, china based on an extended lmdi model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6370191/
https://www.ncbi.nlm.nih.gov/pubmed/30742627
http://dx.doi.org/10.1371/journal.pone.0210430
work_keys_str_mv AT wangchangjian featuresanddriversforenergyrelatedcarbonemissionsinmegacitythecaseofguangzhouchinabasedonanextendedlmdimodel
AT wukangmin featuresanddriversforenergyrelatedcarbonemissionsinmegacitythecaseofguangzhouchinabasedonanextendedlmdimodel
AT zhangxinlin featuresanddriversforenergyrelatedcarbonemissionsinmegacitythecaseofguangzhouchinabasedonanextendedlmdimodel
AT wangfei featuresanddriversforenergyrelatedcarbonemissionsinmegacitythecaseofguangzhouchinabasedonanextendedlmdimodel
AT zhanghongou featuresanddriversforenergyrelatedcarbonemissionsinmegacitythecaseofguangzhouchinabasedonanextendedlmdimodel
AT yeyuyao featuresanddriversforenergyrelatedcarbonemissionsinmegacitythecaseofguangzhouchinabasedonanextendedlmdimodel
AT wuqitao featuresanddriversforenergyrelatedcarbonemissionsinmegacitythecaseofguangzhouchinabasedonanextendedlmdimodel
AT huanggengzhi featuresanddriversforenergyrelatedcarbonemissionsinmegacitythecaseofguangzhouchinabasedonanextendedlmdimodel
AT wangyang featuresanddriversforenergyrelatedcarbonemissionsinmegacitythecaseofguangzhouchinabasedonanextendedlmdimodel
AT wenbin featuresanddriversforenergyrelatedcarbonemissionsinmegacitythecaseofguangzhouchinabasedonanextendedlmdimodel