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Research on industrial carbon emission prediction and resistance analysis based on CEI-EGM-RM method: a case study of Bengbu

This paper focuses on the development trend of industrial carbon emissions in Bengbu city, Anhui Province in the next ten years, and how to help the industry reach the carbon peak as soon as possible. The research process and conclusions are as follows: (1) Through literature review and carbon emiss...

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Autores principales: Dai, Dawei, Zhou, Biao, Zhao, Shuhang, Li, Kexin, Liu, Yuewen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10477190/
https://www.ncbi.nlm.nih.gov/pubmed/37666896
http://dx.doi.org/10.1038/s41598-023-41857-0
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author Dai, Dawei
Zhou, Biao
Zhao, Shuhang
Li, Kexin
Liu, Yuewen
author_facet Dai, Dawei
Zhou, Biao
Zhao, Shuhang
Li, Kexin
Liu, Yuewen
author_sort Dai, Dawei
collection PubMed
description This paper focuses on the development trend of industrial carbon emissions in Bengbu city, Anhui Province in the next ten years, and how to help the industry reach the carbon peak as soon as possible. The research process and conclusions are as follows: (1) Through literature review and carbon emission index method, five main factors affecting industrial carbon emission are identified. (2) The resistance model is used to analyze the main resistance factors of industrial carbon emission reduction in Bengbu city. (3) Based on the existing data of Bengbu city from 2011 to 2020, the grey prediction EGM (1,1) model is used to predict the industrial carbon emissions of Bengbu city from 2021 to 2030. The results show that among the five factors, the urbanization rate has the most significant impact on industrial carbon emissions, while energy intensity has the least impact. Bengbu’s industrial carbon emissions will continue to increase in the next decade, but the growth rate will be flat. Based on the findings of the analysis, specific recommendations on urbanization development, energy structure, and industrial structure of Bengbu city are put forward.
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spelling pubmed-104771902023-09-06 Research on industrial carbon emission prediction and resistance analysis based on CEI-EGM-RM method: a case study of Bengbu Dai, Dawei Zhou, Biao Zhao, Shuhang Li, Kexin Liu, Yuewen Sci Rep Article This paper focuses on the development trend of industrial carbon emissions in Bengbu city, Anhui Province in the next ten years, and how to help the industry reach the carbon peak as soon as possible. The research process and conclusions are as follows: (1) Through literature review and carbon emission index method, five main factors affecting industrial carbon emission are identified. (2) The resistance model is used to analyze the main resistance factors of industrial carbon emission reduction in Bengbu city. (3) Based on the existing data of Bengbu city from 2011 to 2020, the grey prediction EGM (1,1) model is used to predict the industrial carbon emissions of Bengbu city from 2021 to 2030. The results show that among the five factors, the urbanization rate has the most significant impact on industrial carbon emissions, while energy intensity has the least impact. Bengbu’s industrial carbon emissions will continue to increase in the next decade, but the growth rate will be flat. Based on the findings of the analysis, specific recommendations on urbanization development, energy structure, and industrial structure of Bengbu city are put forward. Nature Publishing Group UK 2023-09-04 /pmc/articles/PMC10477190/ /pubmed/37666896 http://dx.doi.org/10.1038/s41598-023-41857-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Dai, Dawei
Zhou, Biao
Zhao, Shuhang
Li, Kexin
Liu, Yuewen
Research on industrial carbon emission prediction and resistance analysis based on CEI-EGM-RM method: a case study of Bengbu
title Research on industrial carbon emission prediction and resistance analysis based on CEI-EGM-RM method: a case study of Bengbu
title_full Research on industrial carbon emission prediction and resistance analysis based on CEI-EGM-RM method: a case study of Bengbu
title_fullStr Research on industrial carbon emission prediction and resistance analysis based on CEI-EGM-RM method: a case study of Bengbu
title_full_unstemmed Research on industrial carbon emission prediction and resistance analysis based on CEI-EGM-RM method: a case study of Bengbu
title_short Research on industrial carbon emission prediction and resistance analysis based on CEI-EGM-RM method: a case study of Bengbu
title_sort research on industrial carbon emission prediction and resistance analysis based on cei-egm-rm method: a case study of bengbu
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10477190/
https://www.ncbi.nlm.nih.gov/pubmed/37666896
http://dx.doi.org/10.1038/s41598-023-41857-0
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