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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Auteurs principaux: Yi Zhou, Jinyan Zhang, Shanying Hu
Format: article
Langue:EN
Publié: Nature Portfolio 2021
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Accès en ligne: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
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