Evaluating the impact of clean energy consumption and factor allocation on China’s air pollution: A spatial econometric approach

Abstract

China’s air pollution has become a widespread concern in the academic world, but there are few studies based on spatial measurement methods to quantify the impact of clean energy consumption and factor allocation on a variety of pollutants. Based on an exploratory spatial data analysis, a spatial Durbin model and extended Cobb-Douglas production function (C-D production function) are used to study the direct, indirect and total effects of clean energy consumption and element allocation on China’s air pollution emissions. The exploratory spatial data analysis results showed that the three emissions had significant agglomeration effects, and the spatial aggregation patterns of the emissions were similar to the patterns of fossil energy consumption spatial aggregation. The spatial Durbin model estimation results showed that the clean energy consumption proportion and factor allocation of energy and labour inhibited air pollution emissions. The spatial spillover effect was greater than the direct effect. The fossil energy structure and factor allocation of energy and capital stock were positively related to air pollution emissions. These findings help to formulate regional industrial policies and energy policies and contribute to the governance of air pollution and the sustainable development of economic, environmental and energy resources.