Assessing pollution and health risks from chromite mine tailings contaminated soils in India by employing synergistic statistical approaches

Investigation of arsenic contamination in soil and plants along the river of Xinzhou abandoned gold mine in Qingyuan, China

The exploitation of mineral resources is very important for economic development, but disorderly exploitation poses a serious threat to the ecological environment. However, investigations on the advantages of plant species and environmental pollution in polluted mining areas are limited. Thus, a survey was conducted to evaluate the impacts of abandoned mines on the surrounding ecological environment along rivers in polluted areas and to determine the Arsenic (As) pollution status in soil and plants. The results showed that the soil and vegetation along the river in the survey area were seriously polluted by As. The total As content of the 15 samples was significantly greater than the national soil background value (GB 15618-2018), and degree of pollution was nonlinearly related to the distance from the mine source, R2 = 0.9844. B. bipinnata, P. vittata and B. nivea were predominant with degrees of dominance of 0.01-0.33, 0.05-0.11, and 0.06-0.14 respectively. The As enrichment capacities of Juncus and P. vittata were significantly greater than those of the other plants, while the bioaccumulation factors (BCFs) were 21.81 and 7.04, respectively.

Eisenia fetida-driven vermitechnology for the eco-friendly transformation of steel waste slag into organic amendment: An insight through microbial diversity and multi-model approach

The processing of steel waste slag from the black metallurgical sector seriously threatened the ecology. To counter these dangers, appropriate detoxification methods were required. Vermitechnology was one such strategy that could successfully convert this industrial waste into nutrient-rich products suitable for use in agriculture. This research primarily focuses on employing vermitechnology for the transformation of waste steel slag into vermicompost and to determine changes in microbial composition, nutrient cycling, and metal detoxification facilitated by earthworms (Eisenia fetida). Earthworm populations in steel waste vermibeds (sw-vermibeds) increased by 2.87-3.07 folds. T1(SW + CD-1:1) comparatively showed increased levels of nutrients such as nitrogen, phosphorus, and potassium. Microbial and enzymatic parameters were more pronounced in treatment T1. The findings of phospholipid fatty acid (PLFA) diversity demonstrate microbial diversity and fatty acid composition. Based on PLFA Sobol Sensitivity Analysis (SSA), PUFA and cyclo were the most sensitive inputs to the presence of heavy metal (HMs) concentrations in SW. In accordance with Taylor-based modelling, R-tree, and Mars were the most trusted regression models for predicting HMs toxicity on microbes. The bioavailable metal fractions of HMs (Fe, Ni, Cd, Cu, Pb, and Cr) decreased by 61-83%. The correlation was performed for 0 and 90 days for metal microbial interactions r (0 days), [BSR vs Fe, Cd, Cu, Ni = -0.99, -0.82, -0.43, -0.99] and r (90 days), [FDA vs Fe, Cu, Ni = -0.97, -0.47, -0.95]. Overall, the results indicated that T1(1:1 SW + CD) provided more favorable conditions for the development of microbes and Eisenia fetida. This research presents a new perspective to the world community on the transformation of harmful steel waste slag into advantageous biological resources by introducing a novel method of employing Eisenia fetida to remediate hazardous steel waste slag.

Evaluating the efficacy of vermicomposted products in rain-fed wetland rice and predicting potential hazards from metal-contaminated tannery sludge using novel machine learning tactic

The study assessed the ecotoxicity and bioavailability of potential metals (PMs) from tannery waste sludge, alongside addressing the environmental concerns of overuse of chemical fertilizers, by comparing the impacts of organic vermicomposted tannery waste, chemical fertilizers, and sole application of tannery waste on soil and rice (Oryza sativa L.) plants. The results revealed that T3, which received high-quality vermicomposted tannery waste as an amendment, exhibited superior enzymatic characteristics compared to tannery sludge amended (TWS) treatments (T8, T9). After harvesting, vermicomposted tannery waste treatment (T3) showed a more significant decrease in PMs bioavailability. Accumulation of PMs in rice was minimal across all treatments except T8 and T9, where toxic tannery waste was present, resulting in a high-risk classification (class 5 < 0.01) according to the SAMOE risk assessment. Results from Fuzzy-TOPSIS, ANN, and Sobol sensitivity analyses (SSA) further indicated that elevated concentrations of PMs (Ni, Pb, Cr, Cu) adversely impacted soil-plant health synergy, with T3 showing a minimal risk in comparison to T8 and T9. According to SSA, microbial biomass carbon and acid phosphatase activity were the most sensitive factors affected by PMs concentrations in TWS. The results from the ANN assay revealed that the primary contributing factor of toxicity on the TWS was the exchangeable fraction of Cr. Correlation statistics underscored the significant detrimental effect of PMs' bioavailability on microbial and enzymatic parameters. Overall, the findings suggest that vermicomposting of tannery sludge waste shows potential as a viable organic amendment option in the near future.

Synergistic impact of bioavailable PHEs and alkalinity on microbial diversity and traits in agricultural soil adjacent to chromium-asbestos mines

Soil microbial communities undergo constant fluctuations, particularly in response to environmental factors. Although the deposition of toxic mine waste is recognized for introducing potentially hazardous elements (PHEs) into the soil, its specific impacts on microbial communities remain unclear. This study aims to explore the combined effects of soil alkalinity and bioavailable PHEs on microbial diversity and traits in agricultural soil adjacent to a chromium-asbestos mining area. By employing a comprehensive analysis, this study indicated that microbiological attributes were reduced in contaminated areas (zone 1), whereas both the levels of bioavailable PHEs (CrWs: 31.08 mg/kg, NiWs: 13.90 mg/kg) and alkalinity indices (CROSS, MCAR, MH) were significantly higher. The spatial distribution of soil alkalinity and bioavailable PHEs, primarily originating from chromium-asbestos mines, has been determined. This study also elucidates the negative relationship between soil stressors (Alkalinity and PHEs) and microbial activities (soil enzymatic activity, microbial respiration, and biomass carbon). The vector's length exhibited a notable difference between zone 1 (0.51) and zone 2 (0.32), indicating a substantial limitation on carbon (C). Also, the investigation of soil bacterial diversity unveiled notable disparities in the prevalence of microbial populations inside zone 1. Proteobacteria constituted 57.18% of the total population indicating a noteworthy prevalence in the contaminated soils. Finally, the random forest (RF) algorithm from machine learning was selected and proven to be a robust choice in Taylor diagrams for predicting the causative stressors responsible for the deterioration of soil microbial health. Therefore, this research offers insights into the health and resilience of soil microbial communities under synergistic stress conditions, which will aid environmentalists in planning future interventions and improving sustainable farming techniques.

Risk assessment and source analysis of heavy metals in soil around an asbestos mine in an arid plateau region, China

Asbestos is widely used in construction, manufacturing, and other common industrial fields. Human activities such as mining, processing, and transportation can release heavy metals from asbestos into the surrounding soil environment, posing a health hazard to the mining area's environment and its surrounding residents. The purpose of the present study was to determine the extent of ecological and human health damage caused by asbestos pollution, as well as the primary contributors to the contamination, by examining a large asbestos mine and the surrounding soil in China. The level of heavy metal pollution in soil and sources were analyzed using methods such as the geo-accumulation index (Igeo), potential ecological risk index (RI), and positive matrix factorization (PMF) model. A Monte Carlo simulation-based health risk model was employed to assess the health risks of heavy metals in the study area's soil to human beings. The results showed that the concentrations of As, Pb, Cr, Cu, and Ni in the soil were 1.74, 0.13, 13.31, 0.33, and 33.37 times higher than the local soil background values, respectively. The Igeo assessment indicated significant accumulation effects for Ni, Cr, and As. The RI evaluation revealed extremely high comprehensive ecological risks (RI ≥ 444) in the vicinity of the waste residue heap and beneficiation area, with Ni exhibiting strong individual potential ecological risk (Eir ≥ 320). The soil health risk assessment demonstrated that As and Cr posed carcinogenic risks to adults, with mean carcinogenic indices (CR) of 1.56E - 05 and 4.14E - 06, respectively. As, Cr, and Cd posed carcinogenic risks to children, with mean CRs of 1.08E - 04, 1.61E - 05, and 2.68E - 06, respectively. Cr also posed certain non-carcinogenic risks to both adults and children. The PMF model identified asbestos contamination as the primary source of heavy metals in the soil surrounding the asbestos mining area, contributing to 79.0%. According to this study, it is recommended that management exercise oversight and regulation over the concentrations of Ni, Cr, Cd, and As in the soil adjacent to asbestos mines, establish a designated control zone to restrict population activities, and locate residential zones at a safe distance from the asbestos mine production zone.

Evaluation of heavy metal speciation distribution in soil and the accumulation characteristics in wild plants: A study on naturally aged abandoned farmland adjacent to tailings

Heavy metal composite pollution is widespread in the surrounding environment of tailings ponds in arid and semi-arid regions, leading to the abandonment of substantial agricultural land. This study investigates the speciation distribution and plant accumulation characteristics of heavy metals in abandoned farmland with different durations of natural aging. The aim is to comprehend the local heavy metal behavior pattern in the soil-plant system and offer insights for environmental remediation. Our findings reveal that Cd stands out as the primary heavy metal pollutant in this area. The mobility ranking of heavy metals is Cd > Pb > Zn > Cu, with Cd and Pb mobility decreasing along the basin. Notably, active Pb exhibits a higher affinity for soil binding compared to other metals. The predominant plant species in the region are primarily small shrubs, herbaceous plants, and semi-shrubs that demonstrate tolerance to drought and salt. Most plant samples showed elevated levels of Cd, Pb, and Zn, surpassing the maximum tolerance levels for dietary minerals in livestock. This elevated metal content poses potential threats to the health of local livestock and wildlife, yet it is also considered a potential for phytoremediation. Selected dominant plant species from the current study include Kalidium foliatum & gracile which shows potential as a Cd accumulator and indicator. Neotrinia splendens and Reaumuria songarica demonstrate potential as Cd excluders, with the latter exhibiting higher tolerance to Cd (62.9 mg/kg). Additionally, our observations indicate that different plant parts exhibit distinct responses to heavy metals, and Zn synergistically influences the aerial part accumulation of Cd. This study holds significant importance in understanding the complex behavior patterns of multi-metal pollutants in the natural environment. The identification of native plants with remediation potential is valuable for phytoremediation of environment pollution in mining area.

Characteristics, source analysis, and health risk assessment of potentially toxic elements pollution in soil of dense molybdenum tailing ponds area in central China

The issue of potentially toxic elements (PTEs) contamination of regional soil caused by mining activities and tailings accumulation has attracted wide attention all over the world. The East Qinling is one of the three main molybdenum mines in the world, and the concentration of PTEs such as Hg, Pb and Cu in the slag is high. Quantifying the amount of PTEs contamination in soil and identifying potential sources of contamination is vital for soil environmental management. In the present investigation, the pollution levels of 8 PTEs in the Qinling molybdenum tailings intensive area were quantitatively identified. Additionally, an integrated source-risk method was adopted for resource allocation and risk assessment based on the PMF model, the ecological risk, and the health risk assessment model. The mean concentrations of Cu, Ni, Pb, Cd, Cr, Zn, As, and Hg in the 80 topsoil samples ranged from 0.80 to 13.38 times the corresponding background values; notably high levels were observed for Pb and Hg. The source partitioning results showed that PTEs were mainly affected by four pollution sources: natural and agricultural sources, coal-burning sources, combined transport and mining industry sources, and mining and smelting sources. The health risk assessment results revealed that the risks of soil PTEs for adults are acceptable, while the risks for children exceeded the limit values. The obtained results will help policymakers to obtain the sources of PTEs of tailing ponds intensive area. Moreover, it provides priorities for the governance of subsequent pollution sources and ecological restoration.

Elucidating the synergistic effect of acidity and metalloid poisoning on the microbiome through metagenomics and machine learning approaches

The abundance and diversity of the microflora in a complex environment such as soil is everchanging. Mica mining has led to metalloid poisoning and changes in soil biogeochemistry affecting the overall produce and leading to toxic dietary exposure. The study focuses on two prominent stressors acidity and arsenic, in mining-contaminated agricultural locations. Soil samples were collected from agricultural fields at a distance of 50 m (zone 1) and 500 m (zone 2) from active mines. Mean arsenic concentration was higher in zone 1 and pH was lower. Geostatistical and self-organizing maps were employed to report that the pattern of localization of soil acidity and arsenic content is similar indicating a causal relationship. Cluster and principal component analysis were further used to materialize a negative effect of soil acidity fractions and arsenic labile pool on soil enzymatic activity (fluorescein diacetate, dehydrogenase, β-1,4-glucosidase, phosphatase, and urease), respiration and Microbial biomass carbon. Soil metagenomic analysis revealed significant differences in the abundance of microbial populations with zone 1 (contaminated zone) having lower alpha and beta diversity. Finally, the efficacy of several machine-learning tools was tested using Taylor diagrams and an effort was made to select a potent algorithm to predict the causal stressors responsible for depreciating soil microbial health. Random Forrest had superior predictive power based on numerical evidence and was therefore chosen as the best-fitted model. The aforementioned insights into soil microbial health and sustenance in stressed conditions can be beneficial for predicting remedial strategies and practicing sustainable agriculture.

Source apportionment and migration characteristics of heavy metal(loid)s in soil and groundwater of contaminated site

The rapid industrial growth has generated heavy metal(loid)s contamination in the soil, which poses a serious threat to the ecology and human health. In this study, 580 samples were collected in Henan Province, China, for source apportionment, migration characterization and health risk evaluation using self-organizing map, positive matrix factorization and multivariate risk assessment methods. The results showed that samples were classified into four groups and pollution sources included chromium slag dump, soil parent rock and abandoned factory. The contents of Cr, Pb, As and Hg were low in Group 1. Group 2 was characterized by total Cr, Cr(Ⅵ) and pH. The enrichment of total Cr and Cr(Ⅵ) in soil was mainly attributed to chromium slag dump, accounting for more than 84.0%. Group 3 was dominated by Hg and Pb. Hg and Pb were primarily attributed to abandoned factory, accounting for 84.7% and 70.0%, respectively. Group 4 was characterized by As. The occurrence of As was not limited to one individual region. The contribution of soil parent rock reached 83.0%. Furthermore, the vertical migration of As, Hg, Pb and Cr(Ⅵ) in soil was mainly influenced by medium permeability, pH and organic matter content. The trends of As, Pb, and Hg with depth were basically consistent with the trends of organic matter with depth, and were negatively correlated with the change in pH with depth. The trends of Cr(Ⅵ) with depth were basically consistent with the changes in pH with the depth. The content of Cr(Ⅵ) in the deep soil did not exceed the detection limits and Cr(Ⅵ) contamination occurred in the deep aquifer, suggesting that Cr(Ⅵ) in the deep groundwater originated from the leakage of shallow groundwater. The assessment indicated that the non-carcinogenic and carcinogenic risks for children and adults could not be neglected. Moreover, children were more susceptible than adults.

Organic Matter Counteracts the Enhancement of Cr(III) Extractability during the Fe(II)-Catalyzed Ferrihydrite Transformation: A Nanoscale- and Molecular-Level Investigation

Phase transformation of ferrihydrite to more stable Fe (oxyhydr)oxides, catalyzed by iron(II) [Fe(II)], significantly influences the mobility of heavy metals [e.g., chromium (Cr)] associated with ferrihydrite. However, the impact of organic matter (OM) on the behavior of Cr(III) in the Fe(II)-catalyzed transformation of ferrihydrite and the underlying mechanisms are unclear. Here, the Fe(II)-catalyzed transformation of the coprecipitates of Fe(III), Cr(III), or rice straw-derived OM was studied at the nanoscale and molecular levels using Fe and Cr K-edge X-ray absorption spectroscopy and spherical aberration corrected scanning transmission electron microscopy (Cs-STEM). Batch extraction results suggested that the OM counteracted the enhancement of Cr(III) extractability during the Fe(II)-catalyzed transformation. Cs-STEM and XAS analysis suggested that Cr(III) could be incorporated into the goethite formed by Fe(II)-catalyzed ferrihydrite transformation, which, however, was inhibited by the OM. Furthermore, Cs-STEM analysis also provided direct nanoscale level evidence that residual ferrihydrite could re-immobilize the released Cr(III) during the Fe(II)-catalyzed transformation process. These results highlighted that the decreased extractability of Cr(III) mainly resulted from the inhibition of OM on the Fe(II)-catalyzed transformation of ferrihydrite to secondary Fe (oxyhydr)oxides, which facilitates insightful understanding and prediction of the geochemical cycling of Cr in soils with active redox dynamics.

Appraise potassium chemistry and distribution patterns in tailing soil, India: Through quantity - Intensity relations and multi model statistical methods

Tailings are waste materials left behind after mineral extraction. Giridih district of Jharkhand, India has the second largest ore of mica mines in the country. This study evaluated the forms of potassium (K⁺) and quantity-intensity relationships in soils contaminated by tailings around the abundant mica mines. A total of 63 rice rhizosphere soil samples (8-10 cm depth) were collected from agricultural fields near 21 mica mines in the Giridih district at different distances: 10 m (zone 1), 50 m (zone 2), and 100 m (zone 3). The samples were collected to quantify various forms of potassium in the soil and characterize non-exchangeable K (NEK) reserves and Q/I isotherms. The semi-logarithmic release of NEK with continuous extractions suggests a decrease in release over time. Significant values of threshold K⁺ levels were observed in zone 1 samples. As K⁺ concentrations increased, the activity ratio (AR_e^K) and its corresponding labile K⁺ (K_L) concentrations decreased. The AR_e^K, K_L, and fixed K⁺ (K_X) values were higher in zone 1 [AR_e^K: 3.2 (mol L^-1)^1/2 × 10^-4, K_L: 0.058 cmol kg^-1, and K_X: 0.038 cmol kg^-1), except for readily available K⁺ (K₀) for zone 2 (0.028 cmol kg^-1). The potential buffering capacity and K⁺ potential values were higher in zone 2 soils. In zone 1, Vanselow selectivity coefficients (K_V) and Krishnamoorthy-Davis-Overstreet selectivity coefficients (K_KDO) were higher, while Gapon constants were higher in zone 3. It was found that AR_e^K was significantly correlated with K₀, K_L, K⁺ saturation, -ΔG, K_V, and K_KDO. Different statistical methods such as positive matrix factorization, self-organizing maps, geostatistics, and Monte Carlo simulation approaches were employed to predict soil K⁺ enrichment, source apportionment, distribution patterns, availability for plants, and contribution to soil K⁺ maintenance. Thus, this study significantly contributes to understanding K⁺ dynamics in mica mine soils and operational K⁺ management.