School of Public Administration, Southwestern University of Finance and Economics, Chengdu, Sichuan, 611130, China.
School of Statistics, Southwestern University of Finance and Economics, Chengdu, Sichuan, 611130, China.
Sci Data. 2022 Mar 24;9(1):101. doi: 10.1038/s41597-022-01240-6.
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.
了解中国能源消耗和效率的演变将有助于评估政府能源政策的有效性和实现国际承诺的可行性。然而，中国尚未公布省级能源消耗和效率数据，这阻碍了对能源消耗和效率差异驱动因素的识别，也阻碍了在城市和县之间实施差异化能源政策。本研究通过结合 DMSP/OLS 和 NPP/VIIRS 卫星夜间灯光数据，使用粒子群优化-反向传播（PSO-BP）算法，对中国 336 个城市和 2735 个县的能源消耗进行了估算。采用单位 GDP 能耗和数据包络分析（DEA）对这些城市和县区的能源效率进行了测量。这些数据可以促进中国城市和县一级能源消耗和效率问题的进一步研究。所开发的估算方法也可用于其他官方能源统计数据有限的发展中国家和地区。
