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China’s city-level carbon emissions during 1992–2017 based on the inter-calibration of nighttime light data

Accurate, long-term, full-coverage carbon dioxide (CO(2)) data in units of prefecture-level cities are necessary for evaluations of CO(2) emission reductions in China, which has become one of the world’s largest carbon-emitting countries. This study develops a novel method to match satellite-based D...

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Autores principales: Chen, Jiandong, Gao, Ming, Cheng, Shulei, Liu, Xin, Hou, Wenxuan, Song, Malin, Li, Ding, Fan, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7870850/
https://www.ncbi.nlm.nih.gov/pubmed/33558535
http://dx.doi.org/10.1038/s41598-021-81754-y
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author Chen, Jiandong
Gao, Ming
Cheng, Shulei
Liu, Xin
Hou, Wenxuan
Song, Malin
Li, Ding
Fan, Wei
author_facet Chen, Jiandong
Gao, Ming
Cheng, Shulei
Liu, Xin
Hou, Wenxuan
Song, Malin
Li, Ding
Fan, Wei
author_sort Chen, Jiandong
collection PubMed
description Accurate, long-term, full-coverage carbon dioxide (CO(2)) data in units of prefecture-level cities are necessary for evaluations of CO(2) emission reductions in China, which has become one of the world’s largest carbon-emitting countries. This study develops a novel method to match satellite-based Defense Meteorological Satellite Program’s Operational Landscan System (DMSP/OLS) and Suomi National Polar-orbiting Partnership’s Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) nighttime light data, and estimates the CO(2) emissions of 334 prefecture-level cities in China from 1992 to 2017. Results indicated that the eastern and coastal regions had higher carbon emissions, but their carbon intensity decreased more rapidly than other regions. Compared to previous studies, we provide the most extensive and long-term CO(2) dataset to date, and these data will be of great value for further socioeconomic research. Specifically, this dataset provides a foundational data source for China’s future CO(2) research and emission reduction strategies. Additionally, the methodology can be applied to other regions around the world.
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spelling pubmed-78708502021-02-10 China’s city-level carbon emissions during 1992–2017 based on the inter-calibration of nighttime light data Chen, Jiandong Gao, Ming Cheng, Shulei Liu, Xin Hou, Wenxuan Song, Malin Li, Ding Fan, Wei Sci Rep Article Accurate, long-term, full-coverage carbon dioxide (CO(2)) data in units of prefecture-level cities are necessary for evaluations of CO(2) emission reductions in China, which has become one of the world’s largest carbon-emitting countries. This study develops a novel method to match satellite-based Defense Meteorological Satellite Program’s Operational Landscan System (DMSP/OLS) and Suomi National Polar-orbiting Partnership’s Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) nighttime light data, and estimates the CO(2) emissions of 334 prefecture-level cities in China from 1992 to 2017. Results indicated that the eastern and coastal regions had higher carbon emissions, but their carbon intensity decreased more rapidly than other regions. Compared to previous studies, we provide the most extensive and long-term CO(2) dataset to date, and these data will be of great value for further socioeconomic research. Specifically, this dataset provides a foundational data source for China’s future CO(2) research and emission reduction strategies. Additionally, the methodology can be applied to other regions around the world. Nature Publishing Group UK 2021-02-08 /pmc/articles/PMC7870850/ /pubmed/33558535 http://dx.doi.org/10.1038/s41598-021-81754-y Text en © The Author(s) 2021 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Chen, Jiandong
Gao, Ming
Cheng, Shulei
Liu, Xin
Hou, Wenxuan
Song, Malin
Li, Ding
Fan, Wei
China’s city-level carbon emissions during 1992–2017 based on the inter-calibration of nighttime light data
title China’s city-level carbon emissions during 1992–2017 based on the inter-calibration of nighttime light data
title_full China’s city-level carbon emissions during 1992–2017 based on the inter-calibration of nighttime light data
title_fullStr China’s city-level carbon emissions during 1992–2017 based on the inter-calibration of nighttime light data
title_full_unstemmed China’s city-level carbon emissions during 1992–2017 based on the inter-calibration of nighttime light data
title_short China’s city-level carbon emissions during 1992–2017 based on the inter-calibration of nighttime light data
title_sort china’s city-level carbon emissions during 1992–2017 based on the inter-calibration of nighttime light data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7870850/
https://www.ncbi.nlm.nih.gov/pubmed/33558535
http://dx.doi.org/10.1038/s41598-021-81754-y
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