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Forecasting the carbon dioxide emissions in 53 countries and regions using a non-equigap grey model

Non-equigap GM(1,1) model with conformable fractional accumulation (CFNGM(1,1)) is proposed to analyze the relationship between energy consumption and carbon dioxide emissions. Two cases are used to prove the validity of the model. In this article, energy consumption is used as input and carbon diox...

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Detalles Bibliográficos
Autores principales: Xu, Zhicun, Liu, Lianyi, Wu, Lifeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7685912/
https://www.ncbi.nlm.nih.gov/pubmed/33236310
http://dx.doi.org/10.1007/s11356-020-11638-7
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author Xu, Zhicun
Liu, Lianyi
Wu, Lifeng
author_facet Xu, Zhicun
Liu, Lianyi
Wu, Lifeng
author_sort Xu, Zhicun
collection PubMed
description Non-equigap GM(1,1) model with conformable fractional accumulation (CFNGM(1,1)) is proposed to analyze the relationship between energy consumption and carbon dioxide emissions. Two cases are used to prove the validity of the model. In this article, energy consumption is used as input and carbon dioxide emissions are used as output. Carbon dioxide emissions of 53 countries and regions in North America, South America, Europe, Commonwealth of Independent States (CIS), Middle East, Africa, and Asia Pacific are predicted. The forecast results show that the carbon dioxide emissions of 30 countries and regions have risen to varying degrees. The top three countries with carbon dioxide emissions in the next three years are China, the USA, and India. More attention should be paid to the carbon dioxide emissions of China.
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spelling pubmed-76859122020-11-25 Forecasting the carbon dioxide emissions in 53 countries and regions using a non-equigap grey model Xu, Zhicun Liu, Lianyi Wu, Lifeng Environ Sci Pollut Res Int Research Article Non-equigap GM(1,1) model with conformable fractional accumulation (CFNGM(1,1)) is proposed to analyze the relationship between energy consumption and carbon dioxide emissions. Two cases are used to prove the validity of the model. In this article, energy consumption is used as input and carbon dioxide emissions are used as output. Carbon dioxide emissions of 53 countries and regions in North America, South America, Europe, Commonwealth of Independent States (CIS), Middle East, Africa, and Asia Pacific are predicted. The forecast results show that the carbon dioxide emissions of 30 countries and regions have risen to varying degrees. The top three countries with carbon dioxide emissions in the next three years are China, the USA, and India. More attention should be paid to the carbon dioxide emissions of China. Springer Berlin Heidelberg 2020-11-25 2021 /pmc/articles/PMC7685912/ /pubmed/33236310 http://dx.doi.org/10.1007/s11356-020-11638-7 Text en © Springer-Verlag GmbH Germany, part of Springer Nature 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Research Article
Xu, Zhicun
Liu, Lianyi
Wu, Lifeng
Forecasting the carbon dioxide emissions in 53 countries and regions using a non-equigap grey model
title Forecasting the carbon dioxide emissions in 53 countries and regions using a non-equigap grey model
title_full Forecasting the carbon dioxide emissions in 53 countries and regions using a non-equigap grey model
title_fullStr Forecasting the carbon dioxide emissions in 53 countries and regions using a non-equigap grey model
title_full_unstemmed Forecasting the carbon dioxide emissions in 53 countries and regions using a non-equigap grey model
title_short Forecasting the carbon dioxide emissions in 53 countries and regions using a non-equigap grey model
title_sort forecasting the carbon dioxide emissions in 53 countries and regions using a non-equigap grey model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7685912/
https://www.ncbi.nlm.nih.gov/pubmed/33236310
http://dx.doi.org/10.1007/s11356-020-11638-7
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