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A Hybrid Framework for Direct CO(2) Emissions Quantification in China’s Construction Sector

Carbon emission quantifications in China are not consistent, with many standards and methods having been used over the years. This study identified the non-consideration of China-specific technology and databases as a factor limiting comprehensive quantification. The study aimed to comprehensively q...

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Autores principales: Ogungbile, Adedayo Johnson, Shen, Geoffrey Qiping, Wuni, Ibrahim Yahaya, Xue, Jin, Hong, Jingke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8625370/
https://www.ncbi.nlm.nih.gov/pubmed/34831721
http://dx.doi.org/10.3390/ijerph182211965
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author Ogungbile, Adedayo Johnson
Shen, Geoffrey Qiping
Wuni, Ibrahim Yahaya
Xue, Jin
Hong, Jingke
author_facet Ogungbile, Adedayo Johnson
Shen, Geoffrey Qiping
Wuni, Ibrahim Yahaya
Xue, Jin
Hong, Jingke
author_sort Ogungbile, Adedayo Johnson
collection PubMed
description Carbon emission quantifications in China are not consistent, with many standards and methods having been used over the years. This study identified the non-consideration of China-specific technology and databases as a factor limiting comprehensive quantification. The study aimed to comprehensively quantify regional direct CO(2) emission in the industry using a hybrid of economic and environmental data. We retrieved nineteen (19) sets of fossil fuel and electricity data from provincial energy yearbooks between 1997 and 2015 for the study. To generate regression models for each of the six regional construction industries in China, the study further integrated the results with three sets of econometric data: total annual construction output, cement, and steel product yearly consumption data. The study identified the North China region as the main source of direct CO(2) emission with over 30%, while Southeast China contributed the least. While there is a gradual shift to other energy sources, the study identified coal and crude oil to remain as the main energy sources in the industry. Cement and steel data exhibited a significant predictive relationship with CO(2) emissions in five regional construction industries. The study identified the need to have policies tailored to technological improvements to enhance renewable energy generation and usage in the industry. The models developed in this study could be used to generate initial quantifications of carbon emissions in construction industries with similar carbon-emitting characteristics for carbon tracking, and energy policies for decision making. However, the three economic indicators used in the study could be extended to generate more robust models in future research.
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spelling pubmed-86253702021-11-27 A Hybrid Framework for Direct CO(2) Emissions Quantification in China’s Construction Sector Ogungbile, Adedayo Johnson Shen, Geoffrey Qiping Wuni, Ibrahim Yahaya Xue, Jin Hong, Jingke Int J Environ Res Public Health Article Carbon emission quantifications in China are not consistent, with many standards and methods having been used over the years. This study identified the non-consideration of China-specific technology and databases as a factor limiting comprehensive quantification. The study aimed to comprehensively quantify regional direct CO(2) emission in the industry using a hybrid of economic and environmental data. We retrieved nineteen (19) sets of fossil fuel and electricity data from provincial energy yearbooks between 1997 and 2015 for the study. To generate regression models for each of the six regional construction industries in China, the study further integrated the results with three sets of econometric data: total annual construction output, cement, and steel product yearly consumption data. The study identified the North China region as the main source of direct CO(2) emission with over 30%, while Southeast China contributed the least. While there is a gradual shift to other energy sources, the study identified coal and crude oil to remain as the main energy sources in the industry. Cement and steel data exhibited a significant predictive relationship with CO(2) emissions in five regional construction industries. The study identified the need to have policies tailored to technological improvements to enhance renewable energy generation and usage in the industry. The models developed in this study could be used to generate initial quantifications of carbon emissions in construction industries with similar carbon-emitting characteristics for carbon tracking, and energy policies for decision making. However, the three economic indicators used in the study could be extended to generate more robust models in future research. MDPI 2021-11-15 /pmc/articles/PMC8625370/ /pubmed/34831721 http://dx.doi.org/10.3390/ijerph182211965 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ogungbile, Adedayo Johnson
Shen, Geoffrey Qiping
Wuni, Ibrahim Yahaya
Xue, Jin
Hong, Jingke
A Hybrid Framework for Direct CO(2) Emissions Quantification in China’s Construction Sector
title A Hybrid Framework for Direct CO(2) Emissions Quantification in China’s Construction Sector
title_full A Hybrid Framework for Direct CO(2) Emissions Quantification in China’s Construction Sector
title_fullStr A Hybrid Framework for Direct CO(2) Emissions Quantification in China’s Construction Sector
title_full_unstemmed A Hybrid Framework for Direct CO(2) Emissions Quantification in China’s Construction Sector
title_short A Hybrid Framework for Direct CO(2) Emissions Quantification in China’s Construction Sector
title_sort hybrid framework for direct co(2) emissions quantification in china’s construction sector
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8625370/
https://www.ncbi.nlm.nih.gov/pubmed/34831721
http://dx.doi.org/10.3390/ijerph182211965
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