Search Results (577)

Agricultural soils surrounding mining areas are often polluted with heavy metals (HMs) due to long-term mining activities and high geological background values. In this study, we investigated the distribution and transport of Cu, Cr, Zn, Cd, Pb, and As in a soil–rice system near a century-old mining site, evaluated their toxic effects on rice (Oryza sativa L.) throughout the growth period, and assessed the associated health risks using the Nemerow index and potential ecological risk index. The results showed that HM contents in rice grown in contaminated soils were significantly higher than in the control. HMs mainly accumulated in roots, with the lowest contents in grains. Cd exhibited the highest enrichment capacity, with bioconcentration factors of 0.79, 1.04, and 1.95 at the tillering, heading, and maturity stages, respectively, and its accumulation increased with rice growth. Transport from stems to leaves was relatively strong. HM exposure significantly inhibited rice growth, reducing plant height, biomass, tiller number, and panicle emergence. In addition, oxidative stress indicators and antioxidant enzyme activities, as well as root amino acid exudation, were markedly altered under HM stress. According to soil–rice HM contents, the pollution level of agricultural soils reached a high class, with As, Pb, Cd, and Zn as the main contributors. The potential ecological risk reached a moderate level, with Cd identified as the dominant factor. Notably, the health risks to children were substantially higher than those to adults, and Monte Carlo simulation indicated a 100% probability of non-carcinogenic and carcinogenic risks for adults and children. The above results highlighting the urgent need for risk management in mining-affected regions. Full article

Mine tailings management poses a major challenge, with up to 99% of the mined material remaining as finely ground residues. This study analyzes a SERNAGEOMIN database from 653 Chilean tailing deposits using a multivariate framework that integrates completeness assessments, descriptive statistics, and hierarchical clustering on log-transformed and standardized chemical concentrations of 56 elements in order to identify dominant geochemical patterns. This study aims to provide an integrated and systematic interpretation of the Chilean database, the most comprehensive public dataset on mine tailings in Chile. The results reveal four distinct geochemical profiles: (i) silicate copper tailings, rich in Cu and associated with a SiO₂-Al₂O₃ matrix; (ii) Zn-Pb-Cd-As polymetallic tailings, with the highest concentrations of heavy metals and rare earth elements (REEs), representing both high environmental risk and potential economic value; (iii) carbonate-matrix tailings (CaCO₃ and limestone), characterized by high CaO and loss of calcination (LOI) but low trace metal contents, suggesting buffering potential against acid mine drainage (AMD); and (iv) clay-rich tailings (kaolin and Au-Cu-Au), marked by high Al₂O₃ and anomalous Co enrichments, indicating unexploited potential for critical metal recovery. These profiles support applications such as their use as source signatures in receptor models and the classification of tailing deposits lacking geochemical information. Full article

The depletion of natural resources remains a major global challenge, emphasizing the need to develop sustainable processes that enable both metal recovery and waste recycling. This study investigates the leaching of valuable metals from lead smelting slag using methanesulfonic acid (MSA), a biodegradable and environmentally benign reagent. Batch experiments were performed under different MSA concentrations (0.35–1.4 M) and temperatures (22–80 °C). Metal dissolution increased nearly linearly with acid concentration up to 1 M, with maximum recoveries after 60 min of 85% Zn, 64% Pb, 75% Cu, and 68% Fe. Copper dissolution was governed by the oxidation of Cu₂S, while Fe leaching was affected by pH variations that promoted re-precipitation. Kinetic modeling indicated mixed chemical–diffusion control mechanisms, with activation energies of 22.6 kJ mol⁻¹ for Zn and 31–33 kJ mol⁻¹ for Pb, Cu, and Fe. Beyond efficient metal extraction, the process generated a leach residue with reduced concentrations of base metals and a mineralogical composition dominated by stable calcium-silicate phases, improving its potential suitability for reuse in construction or mining backfill applications. Overall, methanesulfonic acid proved to be an effective and sustainable lixiviant, combining high metal recovery with the generation of recyclable slag, thereby contributing to circular metallurgical practices. Full article

Lead and zinc pollution is a prevalent issue in agricultural soils surrounding lead and zinc mines, posing a serious risk to crop growth and soil health. Heavy metal-resistant, plant growth-promoting bacteria (PGPB) capable of supporting plant development under high metal exposure have significant potential for mitigating these deleterious effects. Here we isolated and identified the Pb- and Zn-resistant and plant growth-promoting bacterial strain Serratia ureilytica T6 based on 16S rRNA and average nucleotide identity (ANI) analysis. Furthermore, 14 strains (T1–T14) from a rice paddy soil irrigated by Pb-Zn mine effluent were isolated and identified, and their phytopromoting characteristics were determined. Genome analysis of S. ureilytica T6 showed a genome size of 5,102,941 bp, with G + C content of 59.74%. A total of 4822 genes were annotated by RAST, among which 15 genes were putatively associated with Pb-Zn resistance. The genome of S. ureilytica T6 was found to possess multiple genes associated with probiotic properties by a comparative analysis of KEGG, GO, and COG databases. Several taxonomic identifications of S. ureilytica T6 revealed that strain T6 is Gram-negative, facultative anaerobic and motile. The pH growth range of S. ureilytica T6 was between 4.00 and 9.50; temperature growth range was 4–37 °C; NaCl tolerance was 0–9%. S. ureilytica T6 displayed a high tolerance to a variety of heavy metals, with minimum inhibitory concentrations of 1.5 and 9 mmol·L⁻¹ for Pb and Zn. S. ureilytica T6 can utilize a variety of carbon sources and nitrogen sources. T6 has the ability to produce indole-3-acetic acid (IAA), siderophore, and phosphorus and potassium solubilization, and it was initially judged that strain T6 has the potential for plant growth-promoting ability. Different plant growth-promoting effects of T6 inoculations were observed in improving rice biomass, plant height, etc. We observed that with increasing Pb and Zn stress, SOD activity first increased and then decreased, while POD and CAT activities gradually decreased. The addition of S. ureilytica T6 significantly enhanced the activities of SOD, POD, and CAT in rice seedlings under low to moderate Pb and Zn stress but had no significant effect under high concentrations (150 mg·L⁻¹) of Pb or Zn. In addition, S. ureilytica T6 has the potential to be used as a phytoremediation tool. Full article

The use of recycled aggregate provides clear environmental advantages but may introduce chemical interactions that influence cement hydration, particularly when the material originates from mining by-products containing heavy metals. This study examines cementitious composites containing different volume fractions of recycled aggregate derived from Pb–Zn mine tailings and identifies the mechanisms responsible for the observed early-age hydration delay. The recycled aggregate was characterized using XRD, hydration was monitored through ultrasonic pulse velocity (UPV) and temperature evolution, mechanical performance was assessed at 1, 3, and 7 days, and phase evolution was interpreted using SEM-EDS and thermodynamic equilibrium modeling (GEMS/Cemdata18). The results show that heavy-metal-bearing phases (Zn-, Pb-, and Fe-sulfides/sulfates) promote the formation of metastable metal–silicate complexes, temporarily lowering the oxidation potential and delaying setting by up to 28 h in mixtures containing 100% recycled aggregate. Early-age strength was substantially reduced; however, by day 7, all mixtures except that with 100% recycled aggregate approached the strength of the reference mixtures with natural aggregate. Despite these effects, recycled aggregate can be safely incorporated at replacement levels up to 25 vol.%, which preserves acceptable fresh and hardened properties. Nevertheless, the presence of persistent sulfate-bearing phases (e.g., epsomite, anglesite) indicates a potential for long-term sulfate release and associated durability risks, warranting further investigation. Full article

Samples of flotation tailings generated during the exploitation and processing of Zn–Pb–Cu–Ag ore from the Rudnik mine (Serbia) were investigated for their mineralogical, geochemical, and magnetic susceptibility properties. The flotation tailings consist of a complex mineral assemblage, including silicates, carbonates, sulfides, phosphates, sulfates, oxides, hydroxides, and native elements. Quartz, calcite, and orthoclase dominate the coarse fraction (>400 µm), accompanied by epidote, Ca-garnet, and Ca-clinopyroxene. Sulfide minerals are concentrated in finer fractions (<400 µm), with pyrite and arsenopyrite being the most abundant, followed by pyrrhotite, sphalerite, galena, and chalcopyrite. These sulfides occur as dispersed grains within a silicate–carbonate matrix. Post-depositional oxidative alteration is moderately developed, with pyrite replaced by hematite, galena by cerussite, and chalcopyrite by malachite. Geochemical analyses reveal that SiO₂ (avg. 38.98 wt%), Fe₂O₃ (avg. 23.68 wt%), Al₂O₃ (avg. 8.95 wt%), CaO (avg. 9.03 wt%) and MgO (avg. 1.50 wt%) dominate the composition. Economically significant metals include Zn (avg. 0.47 wt%), Pb (avg. 0.20 wt%), Cu (avg. 0.11 wt%), Ag (max. 19 µg/g), and Bi (max. 130 µg/g). Mass magnetic susceptibility shows a strong correlation with S (r = 0.92), Co (r = 0.90), and Bi (r = 0.87); moderate correlation with Fe₂O₃, Al₂O₃, and As; and negative correlation with Mn, TiO₂, Zn, and Pb. The ferromagnetic phase most likely originates from pyrrhotite, as well as hematite formed during pyrite alteration and goethite. Full article

Reservoirs are hotspots for the coupling of nutrients and heavy metals, and they substantially modify the compositions and spatiotemporal distributions of microorganisms in fluvial systems. However, relatively few studies have been performed that investigate the microbial mechanisms driving interactions among heavy metals and nutrients in reservoirs. The Goupitan Reservoir, a seasonal stratified reservoir located within the Wujiang River catchment, was chosen as the research subject. The temporal and spatial variations in heavy metals and nutrients, and the metagenomic composition of the reservoir water were analyzed in January, April, July, and October 2019. The results revealed that As, Ni, Co, and Mn were derived primarily from mine wastewater, whereas Zn, Pb, Cd, and Cr were related to domestic and agricultural wastewater discharge. The study area was dominated by Proteobacteria, Actinobacteria, Cyanobacteria, and Bacteroidetes, with the proportion of dominant phyla reaching 90%. Decreases in the dissolved oxygen (DO) concentration and pH in the bottom water during July and October were conducive to increases in the abundance of the anaerobic bacterial groups Planctomycetes and Acidobacteria. The functional genes norBC and nosZ associated with denitrification (DNF), the key gene nrfAH involved in the dissimilatory nitrate reduction to ammonium (DNRA) process, the functional genes aprAB and dsrAB responsible for sulfate reduction/sulfide oxidation, as well as the thiosulfate oxidation complex enzyme system SOX, all exhibit high abundance in hypoxic water bodies and peak in the redoxcline, highlighting the significance of related nitrogen (N) and sulfur (S) metabolic processes. In addition, the concentrations of heavy metals significantly affected the spatial differentiation of the planktonic bacterial community structure, with Mn, Co, Fe, Ni, As, and Cu making relatively high individual contributions (p < 0.01). This study is important for elucidating the sources and microbiological mechanisms influencing heavy metals and nutrients in seasonally stratified subtropical reservoirs. Full article

Mining activities have led to contamination of natural resources by heavy metals (HMs). Biomagnification studies of HMs within food webs are necessary for understanding the progressive increase in metal burdens across trophic levels and their potential ecotoxicological consequences. This study examined the trophic transfer of Cd, Cu, Pb, and Zn in a tri-trophic model involving maize plants (Zea mays), their herbivore, the grasshopper Sphenarium purpurascens, and their predator, the spider Neoscona oaxacensis, under controlled conditions. Samples from all individuals were collected in Huautla, Morelos, Mexico, where three tailing deposits are present, containing approximately 780,000 tons of waste rich in HMs. We evaluated the body biomass of the grasshopper and the percentage of maize leaf material consumed with and without HMs. HM bioaccumulation in maize, grasshopper, and spider tissues was analyzed, and the enrichment process, along with gender related effects on HM bioaccumulation in females and males of S. purpurascens, was studied. The results revealed enrichment of Pb, Cd, and Cu in maize leaf tissue, except for Zn. Grasshoppers exhibited biomagnification of the same metals, except for Cd. Metal bioaccumulation resulted in a reduced biomass of female and male grasshoppers, accompanied by an increased leaf consumption compared to grasshoppers fed maize leaves without HMs. The HMs’ bioaccumulation levels differed between genders, with males recording significantly higher concentrations of Zn and Pb. The excretion of HMs in feces and their bioaccumulation in exoskeletons are two efficient metal detoxification strategies in grasshoppers. This study revealed biomagnification in the spider N. oaxacensis, confirming metal biomagnification to higher trophic levels and providing critical insight into exposure pathways, risks to wildlife and humans, and how metal pollutants may disrupt ecosystem integrity. Full article

Soil pollution by heavy metals (HMs) poses a major threat to soil quality and human health, with mining and smelting industries identified as key sources. Soils around smelters are often considered polluted hotspots, being generally unsuitable for agricultural activities. Although many studies have identified microbial taxa able to survive in such environments, most have focused on relatively low HM concentrations. The purpose of the study was to assess the ecological risk and to evaluate the diversity and structural shifts in microbial communities, as well as to predict key metabolic pathways associated with HM resistance in soils near Pb–Zn smelter in Bulgaria. The soils ranged from low-risk to disastrous, with cadmium (Cd) identified as the primary contributor to soil toxicity. High-throughput sequencing of 16S rRNA and ITS amplicons revealed widespread dominance of the phyla Proteobacteria, Actinobacteriota and Acidobacteriota, and Ascomycota, with the prevailing classes Acidobacteriae, Chloroflexia, and Eurotiomycetes, indicating their high tolerance to HMs. Functional predictions suggested enrichment of key pathways in the most polluted soils related to HM resistance, including efflux systems and detoxifying enzymes. These results highlight the necessity of integrating soil microbial indicators into agricultural management strategies to ensure safe food production. Full article

This research investigated the characteristics and risks associated with heavy metal contamination in farmland soils surrounding an industrial aggregation area in Yuncheng City, southern Shanxi Province. It analyzed the concentrations and spatial accumulation patterns of eight heavy metal elements, employed principal component analysis (PCA) to identify sources, and assessed both the ecological and health risks. The results revealed the following: (1) The mean concentrations of Pb, Cd, As, Hg, Cr, Zn, Cu, and Ni in the study area were 26.1, 0.29, 13.4, 0.05, 61.4, 72.94, 27.15, and 32.33 mg·kg⁻¹, respectively. These concentrations were elevated above local background levels but remained within Chinese regulatory thresholds for agricultural soil. According to the geoaccumulation index, only Cd was classified as slightly polluted, while the other elements were essentially uncontaminated. The Nemerow comprehensive pollution index indicated light pollution. The potential ecological risk index identified Cd and Hg as the primary contributors to ecological risk, indicating moderate contamination. (2) Source apportionment results revealed that As, Cr, and Ni originated from industrial–natural sources; Cd, Zn, and Cu were linked to industrial production; and Pb and Hg were attributed to mining and traffic sources. (3) Health risk assessments suggested that non-carcinogenic risks for adults and children (0.28 and 0.51, respectively) were within safe limits. However, the carcinogenic risk for children (1.02 × 10⁻⁴) exceeded the acceptable threshold, while the level for adults (4.67 × 10⁻⁵) remained acceptable. This study provides a scientific basis for preventing, controlling and remediating local heavy metal contamination in soil. Full article

Native plant species show significant promise for the remediation and rehabilitation of mine tailings contaminated with heavy metals (HM). Nonetheless, the harmful impact of HM can decrease plant survival, growth and reproduction, thereby diminishing the effectiveness of phytoremediation. Consequently, incorporating organic amendments into mine tailings, like biochar, can promote plant growth, decreasing the bioavailability of HM and their eventual potential to alter the food chain. This study aims to evaluate the capability of coconut fiber biochar in combination with Sanvitalia procumbens to phytostabilize HM in mine tailings by analyzing the effect of coconut fiber biochar on HM bioaccumulation levels (roots and leaves), as well as on morphological, physiological, and genotoxic parameters of S. procumbens grown in mine tailing substrate and mine tailing/biochar. Also, a physicochemical analysis of coconut fiber biochar was conducted. This research was conducted over 100 days on plants grown in greenhouse settings using two different substrates (mine tailing and agrolite [75/25 v/v] and mine tailing and coconut fiber biochar [75/25 v/v]). Every 25 days, 12 plants were selected per treatment for analysis. The bioaccumulation pattern exhibited by S. procumbens was Zn > Pb > Cu > Cd, in root and leaf tissues for both treatments. S. procumbes grown in mine tailing/biochar substrate showed the lowest HM bioaccumulation levels in both tissues in comparison to mine tailing substrate: Zn from 2.95 to 2.50 times lower; Pb 3.04 to 2.82; Cu 3.10 to 2.12; and Zn 2.12 to 3.00 in roots and leaves, respectively. The coconut fiber biochar was rich in functional groups, such as carboxyl and hydroxyl groups, which could favor HM adsorption. Immobilization percentage of HM by coconut fiber biochar showed the following pattern: Pb (66.33%) > Zn (64.50%) > Cu (62.82%) > Cd (55.39%). Incorporating coconut fiber biochar as an amendment improves HM phytostabilization efficiency by reducing their bioaccumulation, increasing biomass production and chlorophyll concentration, and reducing genetic damage levels. This strategy represents a sustainable approach towards reducing the ecological risk of HM biomagnification, alleviating the adverse effects of HM exposure on ecosystem health. Full article

Establishing robust geochemical baselines in the hyper-arid Atacama Desert remains challenging because of extreme climatic gradients, polymetallic mineralisation, and decades of intensive mining. To disentangle natural lithogeochemical signals from anthropogenic inputs, a region-wide, multi-institutional soil dataset (1404 samples; 32 elements) was compiled. The analytical workflow integrated compositional data analysis (CoDA) with isometric log-ratio transformation (ILR), principal component analysis (PCA), robust principal component analysis (RPCA), and consensus anomaly detection via hierarchical (HC) and spectral clustering (SC), applied both with and without spatial coordinates to capture compositional structure and geographic autocorrelation. Optimal cluster solutions differed among laboratory subsets (k = 2–17), reflecting instrument-specific biases. The dual workflows flagged 76 (geochemical-only) and 83 (geo-spatial) anomalies, of which 33 were jointly identified, yielding high-confidence exclusions. Regional baselines for 13 priority elements were subsequently computed, producing thresholds such as As = 66.9 mg · kg⁻¹, Pb = 53.6 mg · kg⁻¹, and Zn = 166.8 mg · kg⁻¹. Incorporating spatial variables generated more coherent, lithology-aligned clusters without sacrificing sensitivity to geochemical extremes (Jaccard index = 0.26). These findings demonstrate that a reproducible, compositional-aware machine learning workflow can separate overlapping geogenic and anthropogenic signatures in heterogeneous terrains. The resulting baselines provide an operational reference for environmental monitoring in northern Chile and a transferable template for other arid mining locations. Full article

Long-term mining activities have introduced heavy metals (HMs) into the soil, ultimately threatening environmental sustainability. Precisely forecasting the spatial patterns of HMs and performing risk evaluations in mining regions are essential for efficient pollution control. In this study, 213 topsoil samples were collected from the Fengfeng Mining Area, which has a 150-year mining history. To determine the spatial distribution of soil HM speciation, correlation analysis was conducted by integrating landform types, and visualization was carried out through Kriging interpolation. Results indicate that the mean levels of Cd, Cu, Pb, and Zn exceed their respective background values by 6.48, 1.61, 4.79, and 4.35 times. The bioavailability sequence is Cd > Pb > Zn > Cu, with elevated levels of bioavailable Cd and Pb observed in the western hilly region. Based on the secondary phase to primary phase ratio (RSP) and the risk assessment code (RAC), Pb and Cd were identified as posing high ecological risks, whereas Cu and Zn do not cause severe contamination. This study provides a scientific foundation for industrial transformation and sustainable development in resource-exhausted cities. Full article

The Zhilingtou Au-Mo-Pb-Zn polymetallic deposit is located in the southwestern Zhejiang Province, NE China, and is tectonically situated in the Shaoxing-Longquan uplift belt. Although previous studies have indicated that Au mineralization in this area occurred between 135 Ma and 145 Ma, evidence for coeval intrusive rocks has been lacking. Furthermore, it remains controversial whether the Au mineralization and (~113 Ma) Mo-Pb-Zn mineralization belong to the same magmatic-hydrothermal system. This study conducted comprehensive high-precision geochronological, petrochemical, and Sr-Nd isotopic analyses on the newly discovered granite porphyry intrusion in the mining area. The aim is to constrain the emplacement age of the intrusion, reveal the petrogenesis and source of ore-forming materials, and further discuss the mineralization mechanism. LA-ICP-MS zircon U-Pb dating results indicate that the granite porphyry was formed at 137.8 ± 0.95 Ma, which is broadly consistent with previously reported ages of Au mineralization. It is inferred that this intrusion may be related to a Au mineralization event at around 138 Ma. Geochemical characteristics show that the rock is peraluminous I-type granite, enriched in light rare earth elements (LREEs) and large ion lithophile elements (LILEs) and depleted in high field strength elements (HFSEs) such as Nb, Ta, and Ti, indicating an “island arc-type” geochemical signatures. Sr-Nd isotopic compositions (initial ⁸⁷Sr/⁸⁶Sr = 0.712364–0.712711; ε_Nd(t) = −13.9 to −13.4; two-stage Nd model ages T_DM2 = 1877–1908 Ma) suggest that the magma was derived from ancient crustal materials with the addition of mantle-derived components. Integrating existing geochronological, isotopic, and fluid inclusion evidence, it is proposed that the Zhilingtou deposit may have experienced two mineralization events: an early event (~138 Ma) involving Au-Ag mineralization related to the granite porphyry and a later event (~113 Ma) comprising Mo-Pb-Zn mineralization associated with a porphyry–epithermal system. Together, these events form a composite mineralization system. This study has important implications for refining regional metallogenic theories and guiding future ore exploration. Full article

Accurate multivariate Gaussian simulation is critical for resource assessment and mine planning, especially in polymetallic deposits where strong trends, data bias, and multivariate outliers introduce complexity. In this scenario, standard workflows applied to non-stationary domains may result in undesirable data statistics reproduction, especially the multivariate relationships between variables. This study proposes an enhanced simulation framework that integrates data standardization, multivariate outlier detection, trend modeling and removal, and a dual application of the Projection Pursuit Multivariate Transform (PPMT). The approach is demonstrated within a high-grade mineralized breccia domain of the Peñasquito deposit, utilizing data from diamond core and reverse circulation (RC) drill holes, including Au, Ag, Pb, and Zn. Bias in RC data was corrected using data standardization, and multivariate outliers were identified through the application of a robust Mahalanobis distance. Trend modeling was performed using a moving window average and was removed using the Gaussian Mixture Model and Stepwise Conditional Transform. PPMT was applied both before and after trend modeling in order to improve decorrelation and simulation performance. Results show improved data reproduction through histograms, variograms, and complex relationships, as well as correlation coefficients. Cross-validation confirms reduced bias and improved accuracy. This research highlights the importance of treating multivariate outliers and applying PPMT both before and after trend modeling. The study demonstrates that applying PPMT twice is more effective for managing persistent non-stationary features, especially in high-grade domains. Full article