Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Jiandong, Gao, Ming, Cheng, Shulei, Hou, Wenxuan, Song, Malin, Liu, Xin, Liu, Yu, Shan, Yuli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
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
_version_ 1783609941088534528
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
work_keys_str_mv AT chenjiandong countylevelco2emissionsandsequestrationinchinaduring19972017
AT gaoming countylevelco2emissionsandsequestrationinchinaduring19972017
AT chengshulei countylevelco2emissionsandsequestrationinchinaduring19972017
AT houwenxuan countylevelco2emissionsandsequestrationinchinaduring19972017
AT songmalin countylevelco2emissionsandsequestrationinchinaduring19972017
AT liuxin countylevelco2emissionsandsequestrationinchinaduring19972017
AT liuyu countylevelco2emissionsandsequestrationinchinaduring19972017
AT shanyuli countylevelco2emissionsandsequestrationinchinaduring19972017