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The heterogeneous drivers of CO(2) emissions in China’s two major economic belts: new evidence from spatio-temporal analysis

CO(2) emissions have become increasingly prominent in China, and the primary emitters are economic belts that are spread throughout China. Two major economic belts, i.e., the Yangtze River Economic Belt (YTREB) and the Yellow River Economic Belt (YREB). Combined with stochastic impacts by regression...

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Autores principales: Zhang, Jingxue, Cheng, Chuan, Feng, Yanchao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10043523/
https://www.ncbi.nlm.nih.gov/pubmed/37363018
http://dx.doi.org/10.1007/s10668-023-03169-1
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author Zhang, Jingxue
Cheng, Chuan
Feng, Yanchao
author_facet Zhang, Jingxue
Cheng, Chuan
Feng, Yanchao
author_sort Zhang, Jingxue
collection PubMed
description CO(2) emissions have become increasingly prominent in China, and the primary emitters are economic belts that are spread throughout China. Two major economic belts, i.e., the Yangtze River Economic Belt (YTREB) and the Yellow River Economic Belt (YREB). Combined with stochastic impacts by regression on population, affluence and technology model, the spatial Durbin model under the space-and-time fixed effect and the Geographical and Time-Weighted Regression are employed to explore the spatio-temporal distribution characteristics and heterogeneous drivers of CO(2) emissions in the two economic belts. The results are as follows. First, CO(2) emissions exhibit obvious spatial correlation features in the YREB, but no such obvious spatial correlation is found in the YRETB. Second, in the YREB, the magnitude of the total influencing factors on CO(2) emissions follows an order where affluence (A) is the biggest driver, followed by energy intensity (EI), technology (TEC) and openness (OP), while the biggest driver in the YRETB is industrial structure supererogation (ISS), followed by population (P), energy intensity (EI), and affluence (A). Both direct and spatial spillover effects of the drivers are observed in the two economic belts. Third, the CO(2) emissions show a notable temporal lag effect in the YREB, but not in the YRETB. Fourth, the effects of the CO(2) emission drivers illustrate significant spatio-temporal heterogeneity in the two economic belts.
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spelling pubmed-100435232023-03-28 The heterogeneous drivers of CO(2) emissions in China’s two major economic belts: new evidence from spatio-temporal analysis Zhang, Jingxue Cheng, Chuan Feng, Yanchao Environ Dev Sustain Article CO(2) emissions have become increasingly prominent in China, and the primary emitters are economic belts that are spread throughout China. Two major economic belts, i.e., the Yangtze River Economic Belt (YTREB) and the Yellow River Economic Belt (YREB). Combined with stochastic impacts by regression on population, affluence and technology model, the spatial Durbin model under the space-and-time fixed effect and the Geographical and Time-Weighted Regression are employed to explore the spatio-temporal distribution characteristics and heterogeneous drivers of CO(2) emissions in the two economic belts. The results are as follows. First, CO(2) emissions exhibit obvious spatial correlation features in the YREB, but no such obvious spatial correlation is found in the YRETB. Second, in the YREB, the magnitude of the total influencing factors on CO(2) emissions follows an order where affluence (A) is the biggest driver, followed by energy intensity (EI), technology (TEC) and openness (OP), while the biggest driver in the YRETB is industrial structure supererogation (ISS), followed by population (P), energy intensity (EI), and affluence (A). Both direct and spatial spillover effects of the drivers are observed in the two economic belts. Third, the CO(2) emissions show a notable temporal lag effect in the YREB, but not in the YRETB. Fourth, the effects of the CO(2) emission drivers illustrate significant spatio-temporal heterogeneity in the two economic belts. Springer Netherlands 2023-03-28 /pmc/articles/PMC10043523/ /pubmed/37363018 http://dx.doi.org/10.1007/s10668-023-03169-1 Text en © The Author(s), under exclusive licence to Springer Nature B.V. 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. 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
Zhang, Jingxue
Cheng, Chuan
Feng, Yanchao
The heterogeneous drivers of CO(2) emissions in China’s two major economic belts: new evidence from spatio-temporal analysis
title The heterogeneous drivers of CO(2) emissions in China’s two major economic belts: new evidence from spatio-temporal analysis
title_full The heterogeneous drivers of CO(2) emissions in China’s two major economic belts: new evidence from spatio-temporal analysis
title_fullStr The heterogeneous drivers of CO(2) emissions in China’s two major economic belts: new evidence from spatio-temporal analysis
title_full_unstemmed The heterogeneous drivers of CO(2) emissions in China’s two major economic belts: new evidence from spatio-temporal analysis
title_short The heterogeneous drivers of CO(2) emissions in China’s two major economic belts: new evidence from spatio-temporal analysis
title_sort heterogeneous drivers of co(2) emissions in china’s two major economic belts: new evidence from spatio-temporal analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10043523/
https://www.ncbi.nlm.nih.gov/pubmed/37363018
http://dx.doi.org/10.1007/s10668-023-03169-1
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