Regression analysis and driving force model building of CO2 emissions in China

Abstract In recent years, global warming has become increasingly devastating, leading to severe consequences, such as extreme weather events and sea-level rise. To reduce carbon dioxide emissions, it is essential to recognize different emission sources and key driving factors. Three main carbon emis...

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Autores principales:	Yi Zhou, Jinyan Zhang, Shanying Hu
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a733e8708c8a42f0a2e7a92b8989e042
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spelling	oai:doaj.org-article:a733e8708c8a42f0a2e7a92b8989e0422021-12-02T16:36:04ZRegression analysis and driving force model building of CO2 emissions in China10.1038/s41598-021-86183-52045-2322https://doaj.org/article/a733e8708c8a42f0a2e7a92b8989e0422021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-86183-5https://doaj.org/toc/2045-2322Abstract In recent years, global warming has become increasingly devastating, leading to severe consequences, such as extreme weather events and sea-level rise. To reduce carbon dioxide emissions, it is essential to recognize different emission sources and key driving factors. Three main carbon emission sources from the period between 1990 and 2017 were identified in China: the energy industry, fuel combustion in other industries, and industrial process. For each source, a driving force model was developed via multiple linear regression. Based on these models, forecasts of the carbon intensity and total CO2 emissions were obtained from 2018 to 2030. The results demonstrate that the CO2 emission intensity and total emissions will continue to decrease but more effort will be required to achieve the goal of Paris Agreement.Yi ZhouJinyan ZhangShanying HuNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yi Zhou Jinyan Zhang Shanying Hu Regression analysis and driving force model building of CO2 emissions in China
description	Abstract In recent years, global warming has become increasingly devastating, leading to severe consequences, such as extreme weather events and sea-level rise. To reduce carbon dioxide emissions, it is essential to recognize different emission sources and key driving factors. Three main carbon emission sources from the period between 1990 and 2017 were identified in China: the energy industry, fuel combustion in other industries, and industrial process. For each source, a driving force model was developed via multiple linear regression. Based on these models, forecasts of the carbon intensity and total CO2 emissions were obtained from 2018 to 2030. The results demonstrate that the CO2 emission intensity and total emissions will continue to decrease but more effort will be required to achieve the goal of Paris Agreement.
format	article
author	Yi Zhou Jinyan Zhang Shanying Hu
author_facet	Yi Zhou Jinyan Zhang Shanying Hu
author_sort	Yi Zhou
title	Regression analysis and driving force model building of CO2 emissions in China
title_short	Regression analysis and driving force model building of CO2 emissions in China
title_full	Regression analysis and driving force model building of CO2 emissions in China
title_fullStr	Regression analysis and driving force model building of CO2 emissions in China
title_full_unstemmed	Regression analysis and driving force model building of CO2 emissions in China
title_sort	regression analysis and driving force model building of co2 emissions in china
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/a733e8708c8a42f0a2e7a92b8989e042
work_keys_str_mv	AT yizhou regressionanalysisanddrivingforcemodelbuildingofco2emissionsinchina AT jinyanzhang regressionanalysisanddrivingforcemodelbuildingofco2emissionsinchina AT shanyinghu regressionanalysisanddrivingforcemodelbuildingofco2emissionsinchina
_version_	1718383649028571136

Regression analysis and driving force model building of CO2 emissions in China

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