Spatial and Temporal Distribution of the Impact of Socio-economic Factors on Water Pollution

Abstract

Access to safe water and ensuring residents’ health are the main components of the United Nations Sustainable Development Goals (SDGs). Water pollution has a significant impact on residents’ health, and there are many factors that exacerbate water pollution. In this study, we applied the geographically and temporally weighted regression (GTWR) model to analyze the spatiotemporal distribution characteristics of factors affecting water pollution in China from 2005 to 2021. Hence, this article takes the chemical oxygen demand emissions (CODE) as the dependent variable, and the independent variables are ending permanent population (EPP), urbanization rate (UR), comprehensive production capacity of water supply (CPCOWS), per capita GDP (PCGDP), industrial water consumption proportion (IWCP), and per capita water consumption (PCWC). The conclusions are as follows: (1) The temporal evolution of CODE in different regions is highly consistent, with the order of water pollution severity being central, northeast, eastern, and western. (2) The effects of different factors on water pollution have obvious spatial and temporal heterogeneity. Overall, EPP, UR, CPCOWS, and PCWC have positive effects on water pollution, and PCGDP and IWCP have negative effects. (3) The direction of EPP and PCGDP impacts on CODE remains consistent across regions. UR impacts are primarily in the northeast, CPCOWS impacts are primarily in the eastern, central, and northeast, IWCP impacts are primarily in the central and western, and PCWC impacts are primarily in the eastern and central. Ultimately, some practical and feasible policy recommendations were proposed for different regions.