Integrated ecological risk assessment of heavy metals in an oil shale mining area after restoration

Quantification of an integrated approach to heavy metal source apportionment and probabilistic health risk assessment in the black soil region of central Jilin Province, China

The northeast black soil region is critical for grain production in China but has experienced significant heavy metals (HMs) contamination due to intensive agriculture. This study investigates the levels of Cr, Ni, Cu, Zn, Cd, As, Pb, and Hg in agricultural soils within the black soil region of central Jilin Province. Enrichment factor (EF) and geo-accumulation index (Igeo) indicate that Ni and Cr are significantly affected by human activities, with notable pollution levels. The Positive Matrix Factorization (PMF) model identifies four primary pollution sources: coal combustion, traffic emissions, and soil parent material (24.70 %); fertilizers and pesticides (24.50 %); mining (27.81 %); and organic fertilizers combined with soil parent material (22.99 %). The potential ecological risk assessment results reveal a generally low potential ecological risk in the study area, although Hg and Cd contribute notably to the overall risk. The human health risk assessment (HHRA) results show that non-carcinogenic risk for all populations are below the threshold of 1, while the average carcinogenic risk for all populations exceed the acceptable threshold of 1E-6. Children face higher non-carcinogenic and carcinogenic risks compared to adults. By integrating the PMF results with potential ecological and health risk assessments, it was found that coal combustion and mining activities contribute most significantly to potential ecological and health risks, respectively. This study investigates the pollution characteristics, sources, and ecological and health risks of HMs in agricultural soils in the black soil region. The findings offer valuable insights for policymakers in developing effective environmental management strategies.

Dynamic estimation of the soil environmental carrying capacity for Benzo(a)pyrene in an industrial city, China: Insight from both duration and rate of regional emission

An in-depth investigation of the maximum environmental load is crucial for soil security and pollution prevention. This research focused on soil environmental carrying capacity (SECC) for different risk receptors in a Chinese industrial city. By determining risk threshold for various land use types, we integrated mass balance and iterative models to capture dynamic net input fluxes with spatial heterogeneity. This enabled quantitative characterization of Benzo(a)pyrene (BaP) SECC through top-down and bottom-up approaches (corresponding to duration (D) and rate of regional emission, respectively). The thresholds were in the order of agricultural land < residential land < forest < industrial land < park. The top-down analysis showed D increased ∼1.5x with a 5% input flux decline until 2031. The bottom-up analysis suggested industrial emissions decreased by approximately 10% as the pollution control period was extended from 20 to 50 years. Both methods showed that at maximum background values (C0), D was ∼4x and the industrial emission rate was ∼10% higher than at minimum C0. SECC values near industrial areas significantly decreased, even reaching negative values, signifying complete carrying capacity loss. This study provided an approach to the dynamics of SECC under diverse scenarios, aiding informed decision-making for sustainable land management.

The effect of heavy precipitation on the leaching of heavy metals from tropical coastal legacy tailings

The continued growth in demand for mineral resources has led to a large amount of mining wastes, which is a major challenge in the context of carbon neutrality and climate change. In this study, runoff migration, batch leaching, and column experiments were used to investigate the short-, medium-, and long-term leaching of heavy metals from legacy tailings, respectively; the cumulative metal release kinetic equations were established, and the long-term effects of tailings leaching were verified by HYDRUS-1D. In runoff migration experiments, surface dissolution of tailings and the co-migration of adsorbed soil particles by erosion were the main carriers in the early stages of leachate formation (Mn ∼ 65 mg/L and SO42- up to 2697.2 mg/L). Batch leaching tests showed that the concentration of heavy metals in soil leached by acid rain were 0.1 ∼ 22.0 μg/L for Cr, 0.7 ∼ 26.0 μg/L for Cu, 4.8 ∼ 5646.0 μg/L for Mn, 0.3 ∼ 232.4 μg/L for Ni, and 1.3 ∼ 448.0 μg/L for Zn. The results of column experiments indicated that some soluble components and metals with high mobility showed a significant decreasing trend at cumulative L/S ≤ 2. Additionally, the metals have higher leaching rates under TCLP conditions, as shown by Mn > Co > Zn > Cd > Ni > Cu > Pb > Cr. The fitting results of Langmuir equation were closer to the cumulative release of metals in the real case, and the release amounts of Mn, Zn, Co, and Ni were higher with 55, 5.84, 2.66, and 2.51 mg/kg, respectively. The water flow within tailings affects the spatial distribution of metals, which mainly exist in relatively stable chemical fractions (F3 + F4 + F5 > 90 %) after leaching. Numerical simulation verified that Mn in leachate has reached 8 mg/L at a scale of up to 100 years. The research results are expected to provide technical basis for realizing the resource utilization of tailings in the future.

Exploring the accumulation capacity of dominant plants based on soil heavy metals forms and assessing heavy metals contamination characteristics near gold tailings ponds

Heavy metal contamination of soil commonly accompanies problems around gold mine tailings ponds. Fully investigating the distribution characteristics of heavy metals and the survival strategies of dominant plants in contaminated soils is crucial for effective pollution management and remediation. This study aims to investigate the contamination characteristics, sources of heavy metals (As, Cd, Pb, Hg, Cu, Zn, Cr, and Ni) in soils around gold mine tailings ponds areas (JHH and WZ) and to clarify the form distribution of heavy metals (As, Cd, Pb, Hg) in contaminated plots as well as their accumulation and translocation in native dominant plants. The results of the study showed that the concentrations of As, Pb, Cd, Cu, and Zn in soil exceeded the national limits at parts of the sampling sites in both study areas. The Nemerow pollution index showed that both study areas reached extreme high pollution levels. Spatial analysis showed that the main areas of contamination were concentrated around metallurgical plants and tailings ponds, with Cd exhibiting the most extensive area of contamination. In the JHH, As (74%), Cd (66%), Pb (77%), Zn (47%) were mainly from tailings releases, and Cu (52%) and Hg (51%) were mainly from gold ore smelting. In the WZ, As (42%), Cd (41%), Pb (73%), Cu (47%), and Zn (41%) were mainly from tailings releases. As, Cd, Pb, and Hg were mostly present in the residue state, and the proportion of water-soluble, ion-exchangeable, and carbonate-bound forms of Cd (19.93%) was significantly higher than that of other heavy metals. Artemisia L. and Amaranthus L. are the primary dominating plants, which exhibited superior accumulation of Cd compared to As, Pb, and Hg, and Artemisia L. demonstrated a robust translocation capacity for As, Pb, and Hg. Compared to the concentrations of other forms of soil heavy metals, the heavy metal content in Artemisia L correlates significantly better with the total soil heavy metal concentration. These results offer additional systematic data support and a deeper theoretical foundation to bolster pollution-control and ecological remediation efforts in mining areas.

Risk assessment of heavy metals in agricultural soil based on the coupling model of Monte Carlo simulation-triangular fuzzy number

Soils in areas wherein agriculture and mining coexist are experiencing serious heavy metal contamination, posing a great threat to the ecological environment and human health. In this study, heavy metals (As, Cd, Cr, Cu, Ni, Pb, and Zn) in agricultural soil samples from mining areas were analyzed to explore pollution status, bioavailability, potential sources, and ecological/health risks. Particularly, the coupling model of Monte Carlo simulation-triangular fuzzy number (MCS-TFN) was established to quantify ecological/health risks accurately. Results showed that Cd was heavily enriched in soil and had the highest bioavailability based on both geo-accumulation index (Igeo) and chemical speciation analysis. Pollution sources apportioned with the absolute principal component score-multiple linear regression (APCS-MLR) model demonstrated that heavy metals were mainly derived from agricultural activities, followed by mining activities and natural sources. The MCS-TFN ecological risk assessment classified Cd into the high-risk category with a probability of 40.96%, whereas other heavy metals were categorized as the low risk. Cd was regarded as the major pollutant for the ecosystem. Moreover, the MCS-TFN health risk assessment indicated that As showed high noncarcinogenic risk (0.07% probability) and moderate carcinogenic risk (1.87% probability), and Cd presented low carcinogenic risk (80.19% probability). As and Cd were identified as the main heavy metals that pose a threat to human health. The MCS-TFN risk assessment is superior to the traditional deterministic risk assessment since it can obtain the risk level and the corresponding probability, and significantly reduce the uncertainty in risk assessment.

Unintended mitigation effect of air pollutant regulation on the aquatic cadmium: Evidence from the 11-FYPEP in China

This paper evaluates the unintended mitigation effect of air pollutant regulation on aquatic cadmium (Cd) emissions in the China's Eleventh Five-Year Plan for Environmental Protection (11-FYPEP), by employing a continuous Difference-in-Difference-in-Difference (DDD) estimator. We find that: (1) Although the 11-FYPEP did not target to reduce Cd emission, the implementation of 11-FYPEP reduced the emissions by 2.8 %. (2) The Cd emission is closely related to the industrial level, because the reduction of Cd is 6.1 % higher in areas with lower industrial output, and the mediating effect of the number of industrial enterprises accounts for 6.8 % of the Cd reduction. Based on our findings, implications like improving production efficiency and modifying industrial structure are proposed, as the 11-FYPEP achieves Cd reduction in an unsustainable way.

Leaching Behavior of As and Pb in Lead-Zinc Mining Waste Rock under Mine Drainage and Rainwater

At present, the pollution of arsenic (As) and lead (Pb) is becoming increasingly serious. The pollution caused by the release of As and Pb from lead-zinc mines has seriously affected the water and soil environment and threatened human health. It is necessary to reveal the release characteristics of As and Pb. The actual scene of mine drainage (MD) and rainwater (RW) leaching waste rocks is the one of the main reasons for the release of As and Pb. However, the leaching behavior of As and Pb in these waste rocks under MD and RW suffered from a lack of in-depth research. In this study, we investigated the occurrence of As and Pb in waste rocks (S1-S6) by using X-ray diffraction (XRD) and time-of-flight secondary ion mass spectrometry (TOF-SIMS), and then, the changes in As and Pb concentration and the hydrochemical parameter in leaching solution were systematically studied. Furthermore, the correlation between the release of As and Pb and mineral composition was also evaluated. Results showed that these waste rocks were mainly composed of carbonate and sulfide minerals. As and Pb were mainly bounded or associated with sulfide minerals such as arsenopyrite, pyrite, chalcopyrite, and galena in these waste rocks, and small parts of As and Pb were absorbed or encased by clay minerals such as kaolinite and chlorite. Under MD and RW leaching, the pH, redox potential (Eh), and electric conductivity (EC) of each waste rock tended to be consistent due to their buffering ability; the leachate pH of waste rocks with more carbonate minerals was higher than that of sulfide minerals. Both As and Pb were released most under MD leaching in comparison to RW, reaching 6.57 and 60.32 mg/kg, respectively, due to MD's low pH and high Eh value. However, As in waste rock released more under alkaline conditions because part of the arsenic was in the form of arsenate. As and Pb release were mainly positively correlated with the proportions of sulfide minerals in these waste rocks. MD leaching significantly promoted the release of As and Pb from waste rocks, which would cause a great threat to the surrounding environment, and control measures were imperative. This paper not only reveals the As and Pb pollution mechanism around the lead-zinc mining area but also provides a theoretical basis for the prevention and control of As and Pb pollution in the future.

Metal distribution behavior based on soil aggregate size in a post-restoration coastal mining area

Soil aggregate size plays an important role in controlling the distribution and transport of metals. Metals immobilized in soil particles will pose potential risks through production/sink flow and infiltration. This study explored the distribution behavior of metals based on soil aggregate size in a restored coastal mining area by establishing Structural Equation Model (SEM) and column experiments. The results showed that hydrological factors and a high degree of weathering accelerated the dissolution of metals from the mine, the desorption of Wa-NH₄⁺-N, the release of F^-, and the leaching of NO₃^-. Driven by soil properties, natural factors, and anthropogenic activities, the total metal content (Total_metal) of Cr, Ni, Zn, Mn, and As showed significant spatial heterogeneity compared to Cd, Co, Cu, and Pb. The geochemical fraction of metals (Geo_metal) indicated that Cd, Co, Pb, Zn, As, and Cu are mainly present in iron‑manganese oxidation bound, organically bound, and residual fractions. The results of SEM showed that the physicochemical properties, Wa-NH₄⁺-N, nitrate nitrogen, and inorganic anions of the soil could explain 69.1 %, 76.4 %, 97.1 %, and 80.0 % of the variation in K_d-Mn, K_d-Pb, K_d-Ni, and K_d-Zn, respectively. While K_d-Cd, K_d-Cu, and K_d-Cr could be predicted by the Total_metal, but the Geo_metal seemed to have little influence on metal K_d. The results of column experiments showed that macroaggregates (>0.25 mm) significantly affected the distribution of Co, Cr, Cu, Mn, Ni, Pb, and Zn in the topsoil. The severe disruption of soil aggregate structure resulted in small fluctuations of anthropogenic Cu, Mn, Pb, Zn, and As in different layers of deep soil. In addition, mineral composition in >0.15 mm particle size was more likely to change. Overall, the hydrological cycle of coastal mines increases the uncertainty of their response to risk. Our study provides a basis for future strategies for priority control and risk prevention.

Hierarchical health risk assessment and influence factors of an ecological post-restoration oil shale mining area based on metal bioavailability

The environmental problems caused by mining are continuous and multifaceted, in order to help manage and plan restored mining areas, the bioavailability of metals is an effective tool for measuring the potential risks to human health. This study analyzes the geochemical fractions of eight metals (As, Cd, Cr, Cu, Mn, Ni, Pb, and Zn) to compare their bioavailability and establishes a Hierarchical health risk (HHR) model to assess the human health risks of the mine area after restoration. The results indicated that children have the highest non-carcinogenic risks exposed through ingestion (HI-ingestion) due to their special behaviors; HI-dermal may be enriched in the body; and HI-inhalation is lowest, as it is related to soil particle size. Affected by local economic development, environmental climate, soil type, and mining, the carcinogenic risk of exposure through the skin (CR-dermal) for adults significantly exceeds the acceptable safety level (ASL). The spatial distribution shows that the harm of mining to human health is a continuous process. There was still a significant CR for adults after remediation, and the HI of tailings exposure was more serious. The Classification and Regression Tree (CART) model of metal bioavailability was developed by integrating the extrinsic and intrinsic factors of metals to explore the effects of different factors on metal bioavailability and predict. The results showed that the bioavailability of metals was a dynamic process that combined land use, the distance to traffic roads, physicochemical properties of soil, and geochemical fractions of metal, and that it affects human health both directly and indirectly. Due to the fragility and sensitivity of the ecosystem after the mining area is restored, it may face greater environmental health risks.