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Study on the extension of the dynamic benchmark system of per capita carbon emissions in China’s county
County is the center of China’s socio-economic development and the key node for urban–rural integration. Also, the county is an important carrier for promoting urban and rural green development. Improving green and low-carbon development capabilities and formulating county-level low-carbon standards...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9449929/ https://www.ncbi.nlm.nih.gov/pubmed/36070041 http://dx.doi.org/10.1007/s11356-022-22668-8 |
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author | Yang, Fengmei Shi, Longyu Wang, Xiaotong Gao, Lijie |
author_facet | Yang, Fengmei Shi, Longyu Wang, Xiaotong Gao, Lijie |
author_sort | Yang, Fengmei |
collection | PubMed |
description | County is the center of China’s socio-economic development and the key node for urban–rural integration. Also, the county is an important carrier for promoting urban and rural green development. Improving green and low-carbon development capabilities and formulating county-level low-carbon standards will play a significant role in promoting China’s new people-oriented urbanization and rural revitalization. Although there have been extensive studies on low-carbon benchmarks, over half of the benchmarks tend to ignore the development stage of the evaluated region and its needs. When the region’s economy reaches a certain level, constraints from low-carbon targets may limit the local development process. This study firstly allocated county carbon intensity reduction targets (CIRT) by considering the differences in county carbon reduction capacity and responsibility. Secondly, a dynamic benchmark system of per capita carbon emissions (PCCE) in counties in China is constructed. Finally, we took Changxing County in Zhejiang Province as a research case to verify the dynamic benchmark of PCCE. According to the carbon intensity target reduction rate (CITRR), China’s counties can be divided into three categories: low carbon emissions reduction capability-responsible counties (L-CERCRC), medium carbon emissions reduction capability-responsible counties (M-CERCRC), and high carbon emissions reduction capability-responsible counties (H-CERCRC). The results show that (1) due to the national CO(2) emission reduction target in 2030, the carbon intensity will be 60% lower than in 2005, the CITRR for China’s 1510 counties range from 8.36 to 137.83%; the average CITRR is 48.40%. (2) Changxing County’s CITRR is 57.71%, which belongs to the H-CERCRC. The PCCE of Changxing County will be much higher than the benchmark when the carbon peak is reached in the future. (3) For reaching the aiming benchmark, Changxing County is suggested to adjust its relevant influencing factors of PCCE for converting local’s PCCE reaching to the benchmark within a certain time period. The dynamic benchmark system for PCCE in China’s counties established in this study is economically sensitive, which not only takes the differences of counties into account, but also meets the needs of counties’ diverse development form stages. This system provides counties a few coordinated directions which can improve the local’s economic development and reduce greenhouse gas (GHGs) emissions through the development progress. |
format | Online Article Text |
id | pubmed-9449929 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-94499292022-09-07 Study on the extension of the dynamic benchmark system of per capita carbon emissions in China’s county Yang, Fengmei Shi, Longyu Wang, Xiaotong Gao, Lijie Environ Sci Pollut Res Int Research Article County is the center of China’s socio-economic development and the key node for urban–rural integration. Also, the county is an important carrier for promoting urban and rural green development. Improving green and low-carbon development capabilities and formulating county-level low-carbon standards will play a significant role in promoting China’s new people-oriented urbanization and rural revitalization. Although there have been extensive studies on low-carbon benchmarks, over half of the benchmarks tend to ignore the development stage of the evaluated region and its needs. When the region’s economy reaches a certain level, constraints from low-carbon targets may limit the local development process. This study firstly allocated county carbon intensity reduction targets (CIRT) by considering the differences in county carbon reduction capacity and responsibility. Secondly, a dynamic benchmark system of per capita carbon emissions (PCCE) in counties in China is constructed. Finally, we took Changxing County in Zhejiang Province as a research case to verify the dynamic benchmark of PCCE. According to the carbon intensity target reduction rate (CITRR), China’s counties can be divided into three categories: low carbon emissions reduction capability-responsible counties (L-CERCRC), medium carbon emissions reduction capability-responsible counties (M-CERCRC), and high carbon emissions reduction capability-responsible counties (H-CERCRC). The results show that (1) due to the national CO(2) emission reduction target in 2030, the carbon intensity will be 60% lower than in 2005, the CITRR for China’s 1510 counties range from 8.36 to 137.83%; the average CITRR is 48.40%. (2) Changxing County’s CITRR is 57.71%, which belongs to the H-CERCRC. The PCCE of Changxing County will be much higher than the benchmark when the carbon peak is reached in the future. (3) For reaching the aiming benchmark, Changxing County is suggested to adjust its relevant influencing factors of PCCE for converting local’s PCCE reaching to the benchmark within a certain time period. The dynamic benchmark system for PCCE in China’s counties established in this study is economically sensitive, which not only takes the differences of counties into account, but also meets the needs of counties’ diverse development form stages. This system provides counties a few coordinated directions which can improve the local’s economic development and reduce greenhouse gas (GHGs) emissions through the development progress. Springer Berlin Heidelberg 2022-09-07 2023 /pmc/articles/PMC9449929/ /pubmed/36070041 http://dx.doi.org/10.1007/s11356-022-22668-8 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022, Springer Nature or its licensor 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 | Research Article Yang, Fengmei Shi, Longyu Wang, Xiaotong Gao, Lijie Study on the extension of the dynamic benchmark system of per capita carbon emissions in China’s county |
title | Study on the extension of the dynamic benchmark system of per capita carbon emissions in China’s county |
title_full | Study on the extension of the dynamic benchmark system of per capita carbon emissions in China’s county |
title_fullStr | Study on the extension of the dynamic benchmark system of per capita carbon emissions in China’s county |
title_full_unstemmed | Study on the extension of the dynamic benchmark system of per capita carbon emissions in China’s county |
title_short | Study on the extension of the dynamic benchmark system of per capita carbon emissions in China’s county |
title_sort | study on the extension of the dynamic benchmark system of per capita carbon emissions in china’s county |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9449929/ https://www.ncbi.nlm.nih.gov/pubmed/36070041 http://dx.doi.org/10.1007/s11356-022-22668-8 |
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