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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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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. |
format | Online Article Text |
id | pubmed-7870850 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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