The rapid development of the global chemical industry has led to widespread groundwater contamination, with frequent pollution incidents posing severe threats to water safety. However, there has been insufficient assessment of the health risks posed by chlorinated hydrocarbon contamination in groundwater around chemical industrial parks. This study evaluates the chlorinated hydrocarbon contamination in groundwater at a chemical park and conducts a multi-pathway health risk assessment, identifying the key risk pollutants. In addition, sensitivity analysis of the primary exposure pathways was performed using the Monte Carlo method. The results indicate severe exceedance of pollutant concentrations with widespread diffusion. Carcinogenic risks were mainly driven by vinyl chloride, whose oral cancer slope factor was significantly higher than that of other substances, while non-carcinogenic risks were dominated by trichloro-ethylene, which had the lowest reference dose. Both carcinogenic and non-carcinogenic risks through the drinking water pathway accounted for approximately 90% of the total risk, whereas the risk contribution from dermal contact was negligible. Although boiling water can partially reduce the risks, its effect on high-concentration pollutants is limited. Additionally, sensitivity analysis showed that pollutant concentration was the primary influencing factor for risk values, followed by exposure duration. The findings of this study provide a scientific basis for effectively formulating pollution control measures and ensuring the drinking water safety of nearby residents.

The net primary productivity (NPP) of vegetation is the key indicator for assessing ecosystem productivity and carbon cycling. The Ulan Mulun River Basin (UMRB) in Northwest China is a typical coal mining area, including open-pit mining (OPM) and underground coal mining (UGM). There are limited studies utilizing long-term, high-resolution data to investigate the spatiotemporal and driving mechanisms of NPP in different types of mining and non-coal mining (NCM) areas. In this study, NPP was estimated using high-resolution Landsat data (30 m) and an improved CASA model for the period 1987–2022. The spatiotemporal variations in NPP across the basin were systematically investigated using Theil–Sen–MK trend analysis, partial derivatives, and multivariate regression residual to explore and quantify the impacts of climate variability (CV) and human activities (HAs) on the different coal mining and NCM areas. The research results show that the overall fluctuating upward trend of vegetation cover in the country is 64.84% during the period from 1987 to 2022. However, there is a decreasing trend of NPP in the coal mining areas. Precipitation was the major factor influencing the change in NPP (21.835 gC/m²/a), while HAs had a lesser effect (4.667 gC/m²/a). In addition, UGM and NCM were more positively affected by HAs than OPM, while OPM was more positively affected by CV than UGM and NCM. These findings can guide scientific ecological restoration strategies, assess carbon balance impacts, and optimize land management and planning in mining areas to achieve a balance between resource development and environmental protection.