From risk to response: Causal effects of soil heavy metal ecological risk on microbial community assembly in mining area.

Source Apportionment-Based Assessment of Ecological and Health Risk for Potentially Toxic Elements in the Soil Around a Uranium Mine

Uranium is a critical strategic resource. However, uranium mining can cause severe contamination of surrounding soils by potentially toxic elements (PTEs). Conventional approaches that separately perform source apportionment and risk assessment fail to establish a direct linkage between pollution sources and their associated environmental and health risks. Herein, we develop an integrated framework that combines the absolute principal component score–multiple linear regression (APCS-MLR) model, the potential ecological risk index, and Monte Carlo simulation. The established framework was used to try quantifying the potential sources of soil PTEs and their corresponding ecological and human risks in a uranium mining area. The results showed that the concentrations of U, Th, Cd, and Cr significantly exceeded local background levels, with Cd and U exhibiting higher spatial variability than the other PTEs. The APCS-MLR model identified three potential sources of soil PTE contamination: mining activities, mixed anthropogenic-natural, and natural sources. Mining and mixed sources were the dominant contributors to ecological risk, jointly accounting for 88.7% of the total ecological risk, with Cd identified as the primary ecological risk pollutant. The mixed sources also contributed the largest proportions of non-carcinogenic and carcinogenic health risks, accounting for 52.56% and 67.5%, respectively. Furthermore, children were found to face greater health risks than adults due to higher exposure levels. Priority factor analysis indicated that pollution management should continuously monitor Cd derived from mining activities based on statistical inference. Overall, the proposed integrated framework successfully established a quantitative linkage between pollution sources and associated risks, providing a scientific basis for source-specific and zone-specific soil pollution management in uranium mining areas.

Heavy metal ecological risk, bioaccumulation, and dietary health risks in a karst soil-fruit system of Rosa roxburghii in Southwest China.

Karst regions commonly have elevated geogenic heavy-metal backgrounds, but paired soil-fruit evidence for specialty fruit systems remains limited. In this study, 245 paired soil-fruit samples were collected from 22 major Rosa roxburghii production areas in Guizhou Province, Southwest China. Concentrations of Pb, Cd, Hg, As, and Cr were determined, Geoaccumulation index, potential ecological risk index, bioaccumulation factor, and dietary health risk models were applied. Soil Cd, Hg, and As were above the agricultural soil screening values in 20.5%, 0.84%, and 5.01% of samples, respectively. Cd was identified as a priority element for soil monitoring, whereas Hg was the main contributor to ecological risk index. The mean RI value was 120.61, suggesting low average comprehensive ecological risk among sampled soils. Pb and Cd concentrations in all fruit samples complied with applicable national food safety limits, with 100% compliance. The bioaccumulation capacity followed the order Cd > Hg > Cr > Pb > As, indicating the highest transfer potential for Cd. The HI values were 0.25 for adults and 0.83 for children, both below 1. Soil pH was negatively associated with fruit Cd concentration, suggesting that pH may be a potential factor associated with Cd transfer. PCA indicated exploratory co-variation patterns among soil heavy metals, fruit accumulation, bioaccumulation factors, ecological risk indices, and dietary health risk indicators. These findings indicate that Rosa roxburghii fruits from the sampled orchards were generally safe for consumption under the conservative exposure scenario. While Cd and Hg should remain priority elements for follow-up monitoring in karst orchards.

Evaluating the Health and Ecological Risks of Toxic Elements in the Agricultural Soil of China using Traditional and Advanced Techniques: A One Health Approach

Agricultural soil quality is critical for sustainable food production, yet contamination by toxic elements (TEs) may pose ecological and human health risks. This study assessed the concentrations, ecological impacts, and potential health risks of five TEs (Cr, Cu, Cd, Pb, and Zn) in agricultural soils across China by combining traditional pollution indices, health risk models, and machine learning. A total of 1131 georeferenced samples compiled from published studies, representing 6 plantation types, food crop, fruit, vegetable, tea, medicinal, and others, were analyzed. Spatial mapping, Pearson correlation analysis, and the United States Environmental Protection Agency (USEPA) health risk framework were used to characterize contamination levels and estimate exposure. Among the plantation types examined, food crop plantations showed the highest contamination levels, with Pb and Zn most prominent, whereas Cd contributed most to ecological risk. Pollution index classification identified several regional hotspots warranting further monitoring. Estimated hazard indices remained below the threshold of concern for both adults and children, although they were consistently higher in children, and carcinogenic risks fell within acceptable limits for both groups. Of the three models tested, Random Forest performed the best (R2 = 0.99, 0.98, 0.96, 0.92, and 0.89 for Cu, Cd, Pb, Zn, and Cr, respectively), outperforming CatBoost and support vector regression. Feature importance and partial dependence analyses identified pH, magnesium, clay content, and total phosphorus as the most influential predictors of TE distribution. Interpreted within a One Health framework, these findings support continued monitoring and targeted management of agricultural soils in China.

Source–Sink Relationships and Environmental Risks of Surface Soil Heavy Metals and Metalloids: Multi-Media Monitoring in a Southwest China County

The pollution of soil by potentially toxic elements in industrial–agricultural transition zones threatens global food security and public health owing to their persistence and bioaccumulation. This study focused on Miyi County, Sichuan (China), a typical region with intensive vanadium–titanium magnetite mining and modern agriculture, and systematically analyzed eight heavy metals and metalloids (Cd, Hg, As, Pb, Cr, Cu, Zn, and Ni) across the categories of atmospheric deposition, irrigation water, agricultural inputs, and soil–crop systems. A rigorous four-stage full-chain diagnosis (concentration–load–ecology–health) was executed to evaluate pollution levels and pathways. The single-factor pollution index identified cadmium (Cd) as the primary pollutant, exhibiting a maximum index of 32.63. The Håkanson potential ecological risk index (RI) demonstrated that Cd was the absolute dominant contributor, reaching a catastrophic single-element risk factor (Ei) of 2191.8 and contributing over 70% to the comprehensive ecological risk. Spatially, soils displayed a distinct point-source cluster diffusion pattern: the northern metallurgical zone was dominated by a Cr-Zn-Cu-Ni industrial assemblage, while the southern zone was enriched in Cd, Pb, As, and Hg. Positive matrix factorization (PMF) source apportionment quantitatively demonstrated that industrial emissions via atmospheric deposition were the primary driver, contributing 55–75% of the total soil exogenous inputs, while agricultural sources (livestock manure and legacy arsenic pesticides) exacerbated localized accumulation. While overlying irrigation water remained safe, channel sediments acted as historical pollution sinks. The human health risk model revealed that children in industrial core areas faced unacceptable carcinogenic hazards, with a lifetime carcinogenic risk (LCR) reaching 5.6 × 10−4. These highly specific multi-media findings support a macro spatial risk zoning and source interception strategy to decouple economic growth from regional food safety degradation in global transition economies.

A soil microbial indicator framework for ecological effect assessment of heavy metal risks in red mud stockpiles: A meta-analysis of available evidence.

Red mud stockpiles may pose long-term heavy-metal-related risks to surrounding soils, yet microbial indicators for ecological effect assessment remain poorly defined. Because direct microbial evidence from red mud stockpiles is limited, published studies on heavy metal contaminated soils were synthesized to screen candidate indicators for this scenario. This meta-analysis integrated 116 studies comprising 763 observations and quantified responses of microbial biomass, alpha diversity, community structure, beta diversity, and enzyme activities to cadmium, mercury, arsenic, lead, chromium, copper, zinc, and nickel. Subgroup analyses, climatic meta-regressions, and precision-weighted random forest models evaluated associations between microbial responses and concentration-toxicity category, soil properties, climatic background, land use, and experimental setting. Heavy metal contamination was associated with significant decreases in microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) by 25.8% and 39.6%, respectively, lower bacterial richness and Shannon diversity, and significant shifts in bacterial community structure. Eight enzyme activities showed significant inhibition of 16.8%-41.8%, with dehydrogenase and urease showing high sensitivity and ecological relevance to microbial metabolic activity and nitrogen cycling. Urease, dehydrogenase, and MBC showed the clearest responses across potential ecological risk index-derived categories, while soil pH, soil organic carbon, soil texture, climatic background, land use, and experimental setting were associated with indicator-specific variation among studies. Overall, MBC, MBN, bacterial community structure, dehydrogenase, and urease were identified as candidate core indicators, supporting an evidence-based microbial framework for ecological effect assessment and risk management in red mud stockpile scenarios.

Priority control of potentially toxic elements in urban park soils through integrated source apportionment and health risk assessment