Evaluating Economic Growth, Industrial Structure, and Water Quality of the Xiangjiang River Basin in China Based on a Spatial Econometric Approach

This research utilizes the environmental Kuznets curve to demonstrate the interrelationship between economic growth, industrial structure, and water quality of the Xiangjiang river basin in China by employing spatial panel data models. First, it obtains two variables (namely, COD(Mn), which represents the chemical oxygen demand of using KMnO(4) as chemical oxidant, and NH(3)-N, which represents the ammonia nitrogen content index of wastewater) by pretreating the data of 42 environmental monitoring stations in the Xiangjiang river basin from 2005 to 2015. Afterward, Moran’s I index is adopted to analyze the spatial autocorrelation of COD(Mn) and NH(3)-N concentration. Then, a comparative analysis of the nonspatial panel model and spatial panel model is conducted. Finally, this research estimates the intermediate effect of the industrial structure of the Xiangjiang river basin in China. The results show that spatial autocorrelation exists in pollutant concentration and the relationship between economic growth and pollutant concentration shapes as an inverted-N trajectory. Moreover, the turn points of the environmental Kuznets curve for COD(Mn) are RMB 83,001 and RMB 108,583 per capita GDP. In contrast, the turn points for NH(3)-N are RMB 50,980 and RMB 188,931 per capita GDP. Additionally, the environmental Kuznets curve for COD(Mn) can be explained by industrial structure adjustment, while that for NH(3)-N cannot. As a consequence, the research suggests that the effect of various pollutants should be taken into account while making industrial policies.