Sci Total Environ. 2024 Jun 28:174371. doi: 10.1016/j.scitotenv.2024.174371. Online ahead of print.
ABSTRACT
Groundwater in karst regions is of immense value due to its vital support for regional ecosystems and residents’ livelihoods. However, it is simultaneously threatened by multi-source pollution from agricultural non-point sources, industrial and domestic point sources, and mining activities. This study focuses on the Guangxi of China, which features typical karst topography, aiming to thoroughly assess the groundwater quality and related health risks in Guangxi, especially identifying the impacts of various key pollution sources on the groundwater environment. A total of 1912 groundwater samples were collected, covering an area of approximately 237,600 km2. The spatial distribution of pollutants was analysed using the Nemeroww index method and Kriging interpolation, while multivariate statistical and cluster analysis methods were employed to identify the main types of pollution sources. Furthermore, based on the human health risk assessment model of the U.S. Environmental Protection Agency (US EPA), a risk assessment was conducted for key pollutants. The results revealed widespread heavy metal contamination in Guangxi’s groundwater, particularly with concentrations of Mn, As, Al, Pb reaching up to 9.4 mg/L, 2.483 mg/L, 37.95 mg/L, 4.761 mg/L, respectively, significantly exceeding China’s national Class III groundwater quality standards. Cluster analysis indicated that mining and industrial activities are the primary sources of pollution. The health risk assessment demonstrated that these activities pose a significant risk to public health. The aim of this study is to provide a scientific basis for the protection of the groundwater environment in Guangxi and other karst areas, the formulation of pollution prevention and control strategies, and the optimization of urban and industrial land use layouts. Future research should focus on advanced isotopic and molecular biological techniques to trace pollution sources more precisely and evaluate the effectiveness of pollution control measures.
PMID:38945232 | DOI:10.1016/j.scitotenv.2024.174371
