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County-level CO(2) emissions and sequestration in China during 1997–2017
With the implementation of China’s top-down CO(2) emissions reduction strategy, the regional differences should be considered. As the most basic governmental unit in China, counties could better capture the regional heterogeneity than provinces and prefecture-level city, and county-level CO(2) emiss...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7665019/ https://www.ncbi.nlm.nih.gov/pubmed/33184289 http://dx.doi.org/10.1038/s41597-020-00736-3 |
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author | Chen, Jiandong Gao, Ming Cheng, Shulei Hou, Wenxuan Song, Malin Liu, Xin Liu, Yu Shan, Yuli |
author_facet | Chen, Jiandong Gao, Ming Cheng, Shulei Hou, Wenxuan Song, Malin Liu, Xin Liu, Yu Shan, Yuli |
author_sort | Chen, Jiandong |
collection | PubMed |
description | With the implementation of China’s top-down CO(2) emissions reduction strategy, the regional differences should be considered. As the most basic governmental unit in China, counties could better capture the regional heterogeneity than provinces and prefecture-level city, and county-level CO(2) emissions could be used for the development of strategic policies tailored to local conditions. However, most of the previous accounts of CO(2) emissions in China have only focused on the national, provincial, or city levels, owing to limited methods and smaller-scale data. In this study, a particle swarm optimization-back propagation (PSO-BP) algorithm was employed to unify the scale of DMSP/OLS and NPP/VIIRS satellite imagery and estimate the CO(2) emissions in 2,735 Chinese counties during 1997–2017. Moreover, as vegetation has a significant ability to sequester and reduce CO(2) emissions, we calculated the county-level carbon sequestration value of terrestrial vegetation. The results presented here can contribute to existing data gaps and enable the development of strategies to reduce CO(2) emissions in China. |
format | Online Article Text |
id | pubmed-7665019 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-76650192020-11-17 County-level CO(2) emissions and sequestration in China during 1997–2017 Chen, Jiandong Gao, Ming Cheng, Shulei Hou, Wenxuan Song, Malin Liu, Xin Liu, Yu Shan, Yuli Sci Data Data Descriptor With the implementation of China’s top-down CO(2) emissions reduction strategy, the regional differences should be considered. As the most basic governmental unit in China, counties could better capture the regional heterogeneity than provinces and prefecture-level city, and county-level CO(2) emissions could be used for the development of strategic policies tailored to local conditions. However, most of the previous accounts of CO(2) emissions in China have only focused on the national, provincial, or city levels, owing to limited methods and smaller-scale data. In this study, a particle swarm optimization-back propagation (PSO-BP) algorithm was employed to unify the scale of DMSP/OLS and NPP/VIIRS satellite imagery and estimate the CO(2) emissions in 2,735 Chinese counties during 1997–2017. Moreover, as vegetation has a significant ability to sequester and reduce CO(2) emissions, we calculated the county-level carbon sequestration value of terrestrial vegetation. The results presented here can contribute to existing data gaps and enable the development of strategies to reduce CO(2) emissions in China. Nature Publishing Group UK 2020-11-12 /pmc/articles/PMC7665019/ /pubmed/33184289 http://dx.doi.org/10.1038/s41597-020-00736-3 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Chen, Jiandong Gao, Ming Cheng, Shulei Hou, Wenxuan Song, Malin Liu, Xin Liu, Yu Shan, Yuli County-level CO(2) emissions and sequestration in China during 1997–2017 |
title | County-level CO(2) emissions and sequestration in China during 1997–2017 |
title_full | County-level CO(2) emissions and sequestration in China during 1997–2017 |
title_fullStr | County-level CO(2) emissions and sequestration in China during 1997–2017 |
title_full_unstemmed | County-level CO(2) emissions and sequestration in China during 1997–2017 |
title_short | County-level CO(2) emissions and sequestration in China during 1997–2017 |
title_sort | county-level co(2) emissions and sequestration in china during 1997–2017 |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7665019/ https://www.ncbi.nlm.nih.gov/pubmed/33184289 http://dx.doi.org/10.1038/s41597-020-00736-3 |
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