Can energy efficiency progress reduce PM2.5 concentration in China’s cities? Evidence from 105 key environmental protection cities in China, 2004–2015

Abstract

At present, PM2.5 is still one of the most serious air pollution issues in China. By empirically testing the actual inhibitory effect of China’s total factor energy efficiency progress on PM2.5, this paper can provide a new evaluation index for energy conservation in China and help Chinese cities understand the beneficial environmental effect of total factor productivity (TFP) progress under the constraint of energy consumption to point out an effective path of energy conservation and emission reduction that is highly in line with China’s current high-quality development strategy. Based on the panel data of 105 key environmental protection cities in China, this paper evaluates total factor energy efficiency with range directional model (RDM) and global Malmquist (GM) productivity index based on data envelopment analysis (DEA); it then uses spatial econometric models to test the impact of energy efficiency progress on PM2.5 concentration. The efficiency evaluation results show that the total factor energy efficiency of 105 key environmental protection cities has increased by an average of 35.9% from 2004 to 2015, with an average annual progress rate of 2.2%. Compared with Eastern and Central China, the progress of energy efficiency in the western region during 2004–2015 is relatively lagged. The average energy efficiency progress rate of higher administrative hierarchy cities and super cities with more than 10 million permanent residents is much higher than that of other cities. The results of GM index decomposition show that technological progress is the main driving force of energy efficiency progress. The spatial econometric analysis results show that there is a significant positive spatial autocorrelation in the concentration of PM2.5 in sample cities, and the energy efficiency progress can significantly inhibit the PM2.5 pollution in local and adjacent cities. The influence of each explanatory variable on PM2.5 concentration is mainly composed of the spatial spillover effect.