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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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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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 |
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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 |
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