Effects of population and land urbanization on China’s environmental impact: empirical analysis based on the extended STIRPAT model

Abstract

China has been undergoing a very rapid but unbalanced urbanization, characterized by under-urbanization of its population and faster urbanization of the land. In such a situation, the urbanization of the population and the land may produce different effects on the natural environment. In addition, due to substantial inter-regional differences, the influence of urbanization on the environment is likely to vary across regions at different stages of economic and social development. This article expands the basic STIRPAT–Stochastic Impacts by Regression on Population, Affluence and Technology, model by adding industrialization level, foreign trade degree, population urbanization level and land urbanization level. Based on panel data from 2006 to 2014 and using this extended STIRPAT model, the article analyses the effects of the driving forces, especially population urbanization and land urbanization, on the environmental impact for the whole of China as well as on its eastern, middle and western regions. The results indicate that for the whole of China, population urbanization produces a significant negative effect on the environmental impact, while land urbanization has a small, but not statistically significant, positive effect. The effects of population urbanization and land urbanization vary across the eastern, middle and western regions, which are at different stages of economic and social development. Population urbanization and land urbanization have no significant influences on environmental impact in the eastern and middle regions, while in the western region population urbanization has a significant negative influence on environmental impact. The main driving factors of environmental impact remain population, affluence and energy intensity. This study also quantitatively calculates the actual contribution rate of each driving force for the 2006–2014 period. It contributes to understanding the characteristics and key driving forces in each region, allowing for appropriate policy recommendations.