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City- and county-level spatio-temporal energy consumption and efficiency datasets for China from 1997 to 2017
Understanding the evolution of energy consumption and efficiency in China would contribute to assessing the effectiveness of the government’s energy policies and the feasibility of meeting its international commitments. However, sub-national energy consumption and efficiency data have not been publi...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8948207/ https://www.ncbi.nlm.nih.gov/pubmed/35332163 http://dx.doi.org/10.1038/s41597-022-01240-6 |
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author | Chen, Jiandong Liu, Jialu Qi, Jie Gao, Ming Cheng, Shulei Li, Ke Xu, Chong |
author_facet | Chen, Jiandong Liu, Jialu Qi, Jie Gao, Ming Cheng, Shulei Li, Ke Xu, Chong |
author_sort | Chen, Jiandong |
collection | PubMed |
description | Understanding the evolution of energy consumption and efficiency in China would contribute to assessing the effectiveness of the government’s energy policies and the feasibility of meeting its international commitments. However, sub-national energy consumption and efficiency data have not been published for China, hindering the identification of drivers of differences in energy consumption and efficiency, and implementation of differentiated energy policies between cities and counties. This study estimated the energy consumption of 336 cities and 2,735 counties in China by combining Defense Meteorological Satellite Program/Operational Line-scan System (DMSP/OLS) and Suomi National Polar-Orbiting Partnership/Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) satellite nighttime light data using particle swarm optimization-back propagation (PSO-BP). The energy efficiency of these cities and counties was measured using energy consumption per unit GDP and data envelopment analysis (DEA). These data can facilitate further research on energy consumption and efficiency issues at the city and county levels in China. The developed estimation methods can also be used in other developing countries and regions where official energy statistics are limited. |
format | Online Article Text |
id | pubmed-8948207 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-89482072022-04-08 City- and county-level spatio-temporal energy consumption and efficiency datasets for China from 1997 to 2017 Chen, Jiandong Liu, Jialu Qi, Jie Gao, Ming Cheng, Shulei Li, Ke Xu, Chong Sci Data Data Descriptor Understanding the evolution of energy consumption and efficiency in China would contribute to assessing the effectiveness of the government’s energy policies and the feasibility of meeting its international commitments. However, sub-national energy consumption and efficiency data have not been published for China, hindering the identification of drivers of differences in energy consumption and efficiency, and implementation of differentiated energy policies between cities and counties. This study estimated the energy consumption of 336 cities and 2,735 counties in China by combining Defense Meteorological Satellite Program/Operational Line-scan System (DMSP/OLS) and Suomi National Polar-Orbiting Partnership/Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) satellite nighttime light data using particle swarm optimization-back propagation (PSO-BP). The energy efficiency of these cities and counties was measured using energy consumption per unit GDP and data envelopment analysis (DEA). These data can facilitate further research on energy consumption and efficiency issues at the city and county levels in China. The developed estimation methods can also be used in other developing countries and regions where official energy statistics are limited. Nature Publishing Group UK 2022-03-24 /pmc/articles/PMC8948207/ /pubmed/35332163 http://dx.doi.org/10.1038/s41597-022-01240-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Chen, Jiandong Liu, Jialu Qi, Jie Gao, Ming Cheng, Shulei Li, Ke Xu, Chong City- and county-level spatio-temporal energy consumption and efficiency datasets for China from 1997 to 2017 |
title | City- and county-level spatio-temporal energy consumption and efficiency datasets for China from 1997 to 2017 |
title_full | City- and county-level spatio-temporal energy consumption and efficiency datasets for China from 1997 to 2017 |
title_fullStr | City- and county-level spatio-temporal energy consumption and efficiency datasets for China from 1997 to 2017 |
title_full_unstemmed | City- and county-level spatio-temporal energy consumption and efficiency datasets for China from 1997 to 2017 |
title_short | City- and county-level spatio-temporal energy consumption and efficiency datasets for China from 1997 to 2017 |
title_sort | city- and county-level spatio-temporal energy consumption and efficiency datasets for china from 1997 to 2017 |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8948207/ https://www.ncbi.nlm.nih.gov/pubmed/35332163 http://dx.doi.org/10.1038/s41597-022-01240-6 |
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