ArticleScientific data2022
City- and county-level spatio-temporal energy consumption and efficiency datasets for China from 1997 to 2017.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Improvements in sustainable energy utilization in global urban areas: Insights from remote sensing surveys.iScience · 2026Article
- Influence of urban innovation capacity on urban energy transition in China-the moderating role of climate risk.Scientific reports · 2026Article
- Multi-resolution dataset of electricity consumption in Chinese cities.Scientific data · 2025Article
- A comprehensive city-level final energy consumption dataset including renewable energy for China, 2005-2021.Scientific data · 2024Article
- Electricity and natural gas tariffs at United States wastewater treatment plants.Scientific data · 2024Article
- Spatio-temporal variations of energy carbon emissions in Xinjiang based on DMSP-OLS and NPP-VIIRS nighttime light remote sensing data.PloS one · 2024Article
- A news-based climate policy uncertainty index for China.Scientific data · 2023Article
- City- and county-level spatio-temporal energy consumption and efficiency datasets for China from 1997 to 2017.Scientific data · 2022Article
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Authors and funding
7 authors.
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Abstract
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.
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