Assessing the impact of population, income and technology on energy consumption and industrial pollutant emissions in China

Elucidating the complex mechanism of the impact of demographic changes, economic growth, and technological advance impacts on energy consumption and pollutant emissions is fundamentally necessary to inform effective strategies on energy saving and emission reduction in China. Here, based on a balanced provincial panel dataset in China over the period 1990-2012, we used an extended STIRPAT model to investigate the effects of human activity on energy consumption and three types of industrial pollutant emissions (exhaust gases, waste water and solid waste) at the national and regional levels and tested the environmental Kuznets curve (EKC) hypothesis. Empirical results show that a higher population density would result in a decrease in energy consumption in China as a whole and in its eastern, central and western regions, but the extent of its effect on the environment depends on the type of pollutants. Higher population density increased wastewater discharge but decreased solid waste production in China and its three regions. The effect of economic development on the environment was heterogeneous across the regions. The proportion of industrial output had a significant and positive influence on energy consumption and pollutant emissions in China and its three regions. Higher industrial energy intensity resulted in higher levels of pollutant emissions. No strong evidence supporting the EKC hypothesis for the three industrial wastes in China was found. Our findings further demonstrated that the impact of population, income and technology on the environment varies at different levels of development. Because of the regional disparities in anthropogenic impact on the environment, formulating specific region-oriented energy saving and emission reduction strategies may provide a more practical and effective approach to achieving sustainable development in China. (C) 2015 Elsevier Ltd. All rights reserved.