Spatiotemporal dynamics of energy-related CO2 emissions in China based on nighttime imagery and land use data

It is difficult to accurately estimate the spatial distribution of carbon dioxide (CO2) at the grid scale because of the lack of city-level statistical data. In this paper, CO2 emission regions were devided into urban area, industrial area and rural area in order to accurately calculate CO2 emission...

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Autores principales:	Wei Wei, Xueyuan Zhang, Xiaoyan Cao, Liang Zhou, Binbin Xie, Junju Zhou, Chuanhua Li
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	CO2 emission Nighttime light imagery Land use data Spatiotemporal analysis Mainland China Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/434867d8d51d4cee9079a8192e653ed1
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id	oai:doaj.org-article:434867d8d51d4cee9079a8192e653ed1
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spelling	oai:doaj.org-article:434867d8d51d4cee9079a8192e653ed12021-12-01T04:59:33ZSpatiotemporal dynamics of energy-related CO2 emissions in China based on nighttime imagery and land use data1470-160X10.1016/j.ecolind.2021.108132https://doaj.org/article/434867d8d51d4cee9079a8192e653ed12021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21007974https://doaj.org/toc/1470-160XIt is difficult to accurately estimate the spatial distribution of carbon dioxide (CO2) at the grid scale because of the lack of city-level statistical data. In this paper, CO2 emission regions were devided into urban area, industrial area and rural area in order to accurately calculate CO2 emissions. In addition, a more accurate calculation model for energy-related CO2 emissions was proposed through integrating nighttime light datasets and land use data. The maps of estimated CO2 emissions in different regions were compared and examined through using spatial dependence and grid overlay methods to understand the spatial distribution characteristics and spatiotemporal dynamics of CO2 emissions in China. The results showed that the model proposed in this study was appropriate and reliable for CO2 emissions not only in urban and rural areas but also in industrial areas. CO2 emissions in China were mainly concentrated in the coastal areas and the northern area, and the amount of carbon emissions increased rapidly from 2000 to 2018 in the Middle Yellow River. These results could improve the understanding of regional discrepancies of spatiotemporal CO2 emission dynamics at gride scale, and provide a scientific reference for the formulation of energy conservation and emission reduction policies by the local government.Wei WeiXueyuan ZhangXiaoyan CaoLiang ZhouBinbin XieJunju ZhouChuanhua LiElsevierarticleCO2 emissionNighttime light imageryLand use dataSpatiotemporal analysisMainland ChinaEcologyQH540-549.5ENEcological Indicators, Vol 131, Iss , Pp 108132- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	CO2 emission Nighttime light imagery Land use data Spatiotemporal analysis Mainland China Ecology QH540-549.5
spellingShingle	CO2 emission Nighttime light imagery Land use data Spatiotemporal analysis Mainland China Ecology QH540-549.5 Wei Wei Xueyuan Zhang Xiaoyan Cao Liang Zhou Binbin Xie Junju Zhou Chuanhua Li Spatiotemporal dynamics of energy-related CO2 emissions in China based on nighttime imagery and land use data
description	It is difficult to accurately estimate the spatial distribution of carbon dioxide (CO2) at the grid scale because of the lack of city-level statistical data. In this paper, CO2 emission regions were devided into urban area, industrial area and rural area in order to accurately calculate CO2 emissions. In addition, a more accurate calculation model for energy-related CO2 emissions was proposed through integrating nighttime light datasets and land use data. The maps of estimated CO2 emissions in different regions were compared and examined through using spatial dependence and grid overlay methods to understand the spatial distribution characteristics and spatiotemporal dynamics of CO2 emissions in China. The results showed that the model proposed in this study was appropriate and reliable for CO2 emissions not only in urban and rural areas but also in industrial areas. CO2 emissions in China were mainly concentrated in the coastal areas and the northern area, and the amount of carbon emissions increased rapidly from 2000 to 2018 in the Middle Yellow River. These results could improve the understanding of regional discrepancies of spatiotemporal CO2 emission dynamics at gride scale, and provide a scientific reference for the formulation of energy conservation and emission reduction policies by the local government.
format	article
author	Wei Wei Xueyuan Zhang Xiaoyan Cao Liang Zhou Binbin Xie Junju Zhou Chuanhua Li
author_facet	Wei Wei Xueyuan Zhang Xiaoyan Cao Liang Zhou Binbin Xie Junju Zhou Chuanhua Li
author_sort	Wei Wei
title	Spatiotemporal dynamics of energy-related CO2 emissions in China based on nighttime imagery and land use data
title_short	Spatiotemporal dynamics of energy-related CO2 emissions in China based on nighttime imagery and land use data
title_full	Spatiotemporal dynamics of energy-related CO2 emissions in China based on nighttime imagery and land use data
title_fullStr	Spatiotemporal dynamics of energy-related CO2 emissions in China based on nighttime imagery and land use data
title_full_unstemmed	Spatiotemporal dynamics of energy-related CO2 emissions in China based on nighttime imagery and land use data
title_sort	spatiotemporal dynamics of energy-related co2 emissions in china based on nighttime imagery and land use data
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/434867d8d51d4cee9079a8192e653ed1
work_keys_str_mv	AT weiwei spatiotemporaldynamicsofenergyrelatedco2emissionsinchinabasedonnighttimeimageryandlandusedata AT xueyuanzhang spatiotemporaldynamicsofenergyrelatedco2emissionsinchinabasedonnighttimeimageryandlandusedata AT xiaoyancao spatiotemporaldynamicsofenergyrelatedco2emissionsinchinabasedonnighttimeimageryandlandusedata AT liangzhou spatiotemporaldynamicsofenergyrelatedco2emissionsinchinabasedonnighttimeimageryandlandusedata AT binbinxie spatiotemporaldynamicsofenergyrelatedco2emissionsinchinabasedonnighttimeimageryandlandusedata AT junjuzhou spatiotemporaldynamicsofenergyrelatedco2emissionsinchinabasedonnighttimeimageryandlandusedata AT chuanhuali spatiotemporaldynamicsofenergyrelatedco2emissionsinchinabasedonnighttimeimageryandlandusedata
_version_	1718405596347105280

Spatiotemporal dynamics of energy-related CO2 emissions in China based on nighttime imagery and land use data

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