Cargando…

Building a novel multivariate nonlinear MGM(1,m,N|γ) model to forecast carbon emissions

With the proposal of the carbon neutrality target, China's attention to carbon emissions has been further enhanced. Effective prediction of future carbon emissions is important for the formulation of carbon neutralization target and action plans in the region. Many factors affecting carbon emis...

Descripción completa

Detalles Bibliográficos
Autores principales: Xiong, Pingping, Wu, Xiaojie, Ye, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9184399/
https://www.ncbi.nlm.nih.gov/pubmed/35702701
http://dx.doi.org/10.1007/s10668-022-02453-w
_version_ 1784724507395620864
author Xiong, Pingping
Wu, Xiaojie
Ye, Jing
author_facet Xiong, Pingping
Wu, Xiaojie
Ye, Jing
author_sort Xiong, Pingping
collection PubMed
description With the proposal of the carbon neutrality target, China's attention to carbon emissions has been further enhanced. Effective prediction of future carbon emissions is important for the formulation of carbon neutralization target and action plans in the region. Many factors affecting carbon emissions, cause their development trends may be nonlinear. To forecast the carbon emissions of coal and natural gas in the industrial sector more accurately, a new MGM(1,m,N|γ) model considering nonlinear characteristics is proposed in this paper. The new model introduces power function γ as nonlinear parameter, and the γ value is solved by nonlinear constraint function. We further deduce the simulation and prediction formula and then apply the improved model to the carbon emission forecast. The comparisons show that the nonlinear parameters can modify the trend of sequences and improve the prediction accuracy, which verifies the validity of the model. Finally, according to the influencing factors and forecast results, this paper analyzes the causes of high carbon emissions and puts forward reasonable suggestions for China's carbon governance.
format Online
Article
Text
id pubmed-9184399
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Springer Netherlands
record_format MEDLINE/PubMed
spelling pubmed-91843992022-06-10 Building a novel multivariate nonlinear MGM(1,m,N|γ) model to forecast carbon emissions Xiong, Pingping Wu, Xiaojie Ye, Jing Environ Dev Sustain Article With the proposal of the carbon neutrality target, China's attention to carbon emissions has been further enhanced. Effective prediction of future carbon emissions is important for the formulation of carbon neutralization target and action plans in the region. Many factors affecting carbon emissions, cause their development trends may be nonlinear. To forecast the carbon emissions of coal and natural gas in the industrial sector more accurately, a new MGM(1,m,N|γ) model considering nonlinear characteristics is proposed in this paper. The new model introduces power function γ as nonlinear parameter, and the γ value is solved by nonlinear constraint function. We further deduce the simulation and prediction formula and then apply the improved model to the carbon emission forecast. The comparisons show that the nonlinear parameters can modify the trend of sequences and improve the prediction accuracy, which verifies the validity of the model. Finally, according to the influencing factors and forecast results, this paper analyzes the causes of high carbon emissions and puts forward reasonable suggestions for China's carbon governance. Springer Netherlands 2022-06-10 /pmc/articles/PMC9184399/ /pubmed/35702701 http://dx.doi.org/10.1007/s10668-022-02453-w Text en © The Author(s), under exclusive licence to Springer Nature B.V. 2022 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 Article
Xiong, Pingping
Wu, Xiaojie
Ye, Jing
Building a novel multivariate nonlinear MGM(1,m,N|γ) model to forecast carbon emissions
title Building a novel multivariate nonlinear MGM(1,m,N|γ) model to forecast carbon emissions
title_full Building a novel multivariate nonlinear MGM(1,m,N|γ) model to forecast carbon emissions
title_fullStr Building a novel multivariate nonlinear MGM(1,m,N|γ) model to forecast carbon emissions
title_full_unstemmed Building a novel multivariate nonlinear MGM(1,m,N|γ) model to forecast carbon emissions
title_short Building a novel multivariate nonlinear MGM(1,m,N|γ) model to forecast carbon emissions
title_sort building a novel multivariate nonlinear mgm(1,m,n|γ) model to forecast carbon emissions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9184399/
https://www.ncbi.nlm.nih.gov/pubmed/35702701
http://dx.doi.org/10.1007/s10668-022-02453-w
work_keys_str_mv AT xiongpingping buildinganovelmultivariatenonlinearmgm1mngmodeltoforecastcarbonemissions
AT wuxiaojie buildinganovelmultivariatenonlinearmgm1mngmodeltoforecastcarbonemissions
AT yejing buildinganovelmultivariatenonlinearmgm1mngmodeltoforecastcarbonemissions