The driving factors and spatial evolution of industrial water pollution governance efficiency in the Yangtze River Delta urban agglomeration in China.

Abstract

In order to explore the effective path to improve the efficiency of industrial water pollution governance efficiency (WGE), this study takes 27 prefecture-level cities in the Yangtze River Delta urban agglomeration in China as the research object, measures WGE through the improved SBM model, and tests the impact of WGE drivers using the spatial Durbin model (SDM). The study found that environmental pollution governance investment (EPGI) is positively correlated with WGE, and industrial agglomeration status (IAS) has inhibitory effects on the improvement of WGE. By testing IAS2, it was determined that the impact of IAS on WGE has a "U"-shaped relationship. The direct impact of EPGI on WGE is 0.5016, and the indirect impact on WGE is 0.6428; the direct impact of IAS on WGE is -0.3036, and the indirect impact on WGE is -0.5158. Among the other tested impact drivers, per capita GDP (PCG), industrial structure (IS), and level of technological innovation (TIL) are positively correlated with the dependent variable WGE, while energy consumption intensity (ECI), environmental regulation intensity (ERI), and degree of openness to foreign investment (FIR) are negatively correlated with the dependent variable WGE. In addition to the impact of the aforementioned main drivers, IAS and EPGI, these six drivers also largely influence and determine the final impact on WGE.