As the exploitation and utilization of metal mines continue, issues concerning the groundwater ecological environment have become increasingly prominent, attracting significant attention. However, few studies have predicted the ecological risks associated with the attenuation of heavy metals in mining areas. This research focuses on a typical lead-zinc mine in Jiangxi Province, China. We employed a Self-Organizing Map (SOM) to analyze groundwater pollution clustering and integrated the Domenico model with Monte Carlo simulation to predict heavy metal attenuation. To assess present and long-term ecological risks, we applied the potential ecological risk index. The research findings indicate that: Mn, Fe, and As exhibited significant enrichment during periods, while Cu, Cd, As, and Al showed the highest coefficients of variation. According to the SOM-based clustering analysis, Zn and Pb show a strong correlation with Cd, while Cu, As, and Al are strongly correlated with Fe. The assessment of potential ecological risks reveals that single-factor evaluations for both periods mostly indicate slight ecological risks (E_rⁱ<30). Cd, As, Cu, and Mn pose very high ecological risks. The comprehensive ecological risk is very high around the tailings pond and the waste dump, with 11.11 % of the sites showing very high ecological risk. Combining the SOM output with the potential ecological risk analysis, cluster 1 includes sites identified as very high ecological risk points, with As being the key ecological risk factor. The ecological risk prediction based on Monte Carlo simulation indicates that the ecological risk of As will decrease by 75.6 % to 13,565, yet it persists at very high ecological risk. This study will offer critical insights for controlling heavy metal pollution in groundwater and for guiding ecological restoration in mining areas and their surroundings.

With the reform of China’s urbanization increasing in popularity, the security issues posed by urban groundwater, especially groundwater in industrial areas, have attracted scholars’ attention. This research aimed to predict and quantify the migration process of contaminants in a microconfined aquifer by conducting a groundwater contamination investigation in an abandoned chemical plant in the Jiangsu Province of China. First, data such as regional hydrogeological parameters and types of contaminants were obtained via hydrogeological drilling, groundwater well monitoring, pumping tests, and laboratory permeability tests, which helped identify the most serious pollution factor: chloroform. Then, a groundwater flow model was built using the Groundwater Modeling System (GMS) and verified using the general-purpose parameter estimation (PEST) package. In addition, based on the three-dimensional multi-species model for transport (MT3DMS) in GMS, a transport model was established. The results illustrate that the plume range of chloroform diffuses with water flow, but, because of its slow diffusion rate and inability to degrade naturally, the concentration of the contaminant has remained several times higher than the safety standard for a long time. The contaminant spread vertically to the soil layer above the microconfined aquifer under pressure, resulting in direct pollution. In addition, the contaminant in the microconfined aquifer is anticipated to migrate down to the clay layer and become enriched. However, the first confined aquifer has not been seriously polluted in the past 20 years. Finally, a sensitivity analysis of the parameters shows that groundwater contamination in the Yangtze delta region is greatly affected by precipitation recharge and hydraulic conductivity.

The accumulation of nitrogen in groundwater in the industrial plots, especially the high ammonium, can result in a serious threat to the groundwater system in the urban area. This study monitored the dissolved inorganic nitrogen (DIN) of the polluted groundwater four times in one year in a retired nitrogenous fertilizer plant site with a production history of nearly 40 years, to analyze the spatial-temporal characteristics of DIN species (NH₄⁺-N, NO₃⁻-N, and NO₂⁻-N) and the effects of groundwater environment on their transfer and transformation. The results showed that NH₄⁺-N (<0.025 to 1310 mg/L) was the main DIN species (61.38–76.80%) with low mobility, whereas the concentration of NO₃⁻-N and NO₂⁻-N was 0.15–146 mg/L and <0.001–12.4 mg/L, accounting for 22.34–36.07% and 0.53–2.83% of total DIN, respectively. The concentration and proportion of NO₃⁻-N and NO₂⁻-N showed an upward trend with time, posing a threat to the safety of surrounding groundwater, and their high spatial-temporal variation was related to the morphological transformation and the transport. In the wet season, the pH and redox condition benefited the nitrification, and NO₃⁻-N easily migrated from the deep soil solution to groundwater, hence the NO₃⁻-N can be accumulated. Therefore, the analysis of species and behaviors of DIN in shallow groundwater is indispensable for environmental risk assessment.

Red mud is a highly alkaline solid waste with an annual emission of over 200 million tons, which requires large-scale utilization methods. Soil Cd remediation is a global concern, due to its high toxicity and strong mobility. Given red mud’s potential for soil Cd remediation, this study reviews its basic characteristics, the mechanisms of soil Cd immobilization by red mud, and the use of red mud-based passivators for agricultural soil Cd remediation. In general, red mud regulates soil pH, thus increasing the soil’s Cd adsorption capacity; provides abundant surface active sites for adsorption and complexation with soil Cd; introduces cations to immobilize Cd via ion exchange; and enriches Cd-resistant microbe species to reduce soil Cd toxicity. Furthermore, the potential environmental risks and suggestions on red mud application are discussed. Further research should focus on improving the remediation effectiveness of red mud on cadmium-contaminated agricultural soil, demonstrating its long-term efficacy and economic costs, and proposing practical technical models and standards for application.