The scientific landscape of phytoremediation of tailings: a bibliometric and scientometric analysis.

This article seeks to evaluate the scientific landscape of the phytoremediation of mine tailings through a series of bibliometric and scientometric techniques. Phytoremediation has emerged as a sustainable approach to remediate metal-contaminated mine waste areas. A scientometric analysis of 913 publications indexed in Web of Science from 1999 to 2023 was conducted using CiteSpace. The results reveal an expanding, interdisciplinary field with environmental sciences as the core category. Keyword analysis of 561 nodes and 2,825 links shows a focus on plant-metal interactions, microbial partnerships, bioavailability, and field validation. Co-citation analysis of 1,032 nodes and 2,944 links identifies seminal works on native species, plant-microbe interactions, and amendments. Temporal mapping of 15 co-citation clusters indicates a progression from early risk assessments and native plant inquiries to integrated biological systems, economic feasibility, and sustainability considerations. Recent trends emphasize multidimensional factors influencing adoption, such as plant-soil-microbe interactions, organic amendments, and field-scale performance evaluation. The findings demonstrate an intensifying translation of phytoremediation from scientific novelty to engineering practice. This quantitative and qualitative analysis of research trends aids in understanding the development of phytoremediation for mine tailings. The results provide valuable insights for researchers and practitioners in this evolving field.

Characteristics of China's coal mine methane emission sources at national and provincial levels.

Methane (CH4) is the second most abundant greenhouse gas. China is the largest CH4 emitter in the world, with coal mine methane (CMM) being one of the main anthropogenic contributions. Thus, there is an urgent need for comprehensive estimates and strategies for reducing CMM emissions in China. However, the development of effective strategies is currently challenged by a lack of information on temporal variations in the contributions of different CMM sources and the absence of provincial spatial analysis. Here, considering five sources and utilization, we build a comprehensive inventory of China's CMM emissions from 1980 to 2022 and quantify the contributions of individual sources to the overall CMM emissions at the national and provincial levels. Our results highlight a significant shift in the source contributions of CMM emissions, with the largest contributor, underground mining, decreasing from 89% in 1980 to 69% in 2022. Underground abandoned coal mines, which were ignored or underestimated in past inventories, have become the second source of CMM emissions since 1999. From 2011 to 2022, we identified Shanxi, Guizhou, and Shaanxi as the three largest CMM-emitting provinces, while the Emissions Database for Global Atmospheric Research (EDGAR) v8 overestimated emissions from Inner Mongolia, ranking it third. Notably, we observed a substantial decrease (exceeding 1 Mt) in CMM emissions in Sichuan, Henan, Liaoning, and Hunan between 2011 and 2022, which was not captured by EDGAR v8. To develop targeted CMM emission reduction strategies at the provincial level, we classified 31 provinces into four groups based on their CMM emission structures. In 2022, the number of provinces with CMM emissions mainly from abandoned coal mines has exceeded that of provinces with mainly underground mines, which requires attention. This study reveals the characteristics of the source of CMM emissions in China and provides emission reduction directions for four groups of provinces.

Spatial patterns of toxic elements in stream sediment transportation at a hilly mine area.

The spatial pattern of toxic metals plays a major role in watershed diffuse metal non-point source pollution, particularly during stream sediment transportation at hills mines. This study investigated a typical hilly mine area to quantitatively analyze the characteristics, sensitivities, and influencing factors of toxic elements transported in stream sediments through field research and Geodetector models. The results showed that the spatial patterns of toxic elements in stream sediment transportation at the hills mine area were significantly influenced by water erosion and sulfate. Water erosion and sulfate promoted the transport differences of stream sediment metals from upstream to downstream at the hills mine area. Arsenic, cadmium, mercury, and antimony in the stream sediments at the hills mine exhibited higher coefficients of variation (101 % to 397 %) than those in plain and basin topographies. Potential ecological risks of arsenic and cadmium were assessed as high-risk levels, at 19 % and 64 %, respectively. Metal import in the midstream sediments of the hills mine area was accelerated by strong water erosion. Sulfate and dissolved organic matter (DOM) were highly enriched in stream sediments, with sulfate showing a strong correlation with toxic metals (24 %). Positive responses were observed between arsenic, mercury, antimony, and sulfate in sediments, with sensitivities of 41 %, 25 %, and 16 %, respectively, while cadmium was associated with DOM, with a sensitivity of 46 %. Importantly, water erosion interactions with functional type of mine significantly influenced on the spatial transportation patterns of toxic metals in stream sediments. The interactive influences of sulfate combined with bicarbonate on arsenic, mercury, and antimony and bicarbonate combined with DOM on cadmium were enhanced compared to individual factors (>20 %). This study elucidates the spatial patterns of metals during stream sediment transportation in hills mine and offers the novel insights for developing effective watershed metal management strategies in hilly mine environments.

Numerical simulation on transient electromagnetic response of separation layer water in coal seam roof.

Mining stress induces deformation and fracture of the overlaying rock, which will result in water filling the separation layer if the aquifer finds access to abscission space along the fracture channels. Accurate detection is crucial to prevent water hazards induced by water-bearing fractures. The 3-D time-domain finite-difference method with Yee's grid was adopted to calculate full-space transient electromagnetic response; meanwhile, a typical geologic and geophysical model with a water-bearing block in an separation layer was built according to regional tectonics and stratigraphic developments. By using numerical simulation, the induced voltage and apparent resistivity for both vertical and horizontal components were acquired, and then an approximate inversion was carried out based on the "smoke ring" theory. The results indicate that the diffusion velocity of induced voltage is significantly affected by the water-bearing body in the fracture, and the horizontal velocity of induced voltage is lower than the vertical one. The induced voltage curves indicate that the horizontal response to an anomaly body is stronger than the vertical one, leading to a high apparent resistivity resolution of conductivity contrast and separation layer boundary in the horizontal direction. The results of 3-D simulation making use of a measured data model also demonstrate that the horizontal component of apparent resistivity can reflect the electrical structure in a better way; however, its ability to recognize the concealed and fine conductor is rather weak. Accordingly, the observation method or numerical interpolation method needs to be further improved for data processing and interpretation.

Explosive utilization efficiency enhancement: An application of machine learning for powder factor prediction using critical rock characteristics.

Maximizing the use of explosives is crucial for optimizing blasting operations, significantly influencing productivity and cost-effectiveness in mining activities. This work explores the incorporation of machine learning methods to predict powder factor, a crucial measure for assessing the effectiveness of explosive deployment, using important rock characteristics. The goal is to enhance the accuracy of powder factor prediction by employing machine learning methods, namely decision tree models and artificial neural networks. The analysis finds key rock factors that have a substantial impact on the powder factor, hence enabling more accurate planning and execution of blasting operations. The analysis uses data from 180 blast rounds carried out at a dolomite mine in south-south Nigeria. It incorporates measures such as root mean square error (RSME), mean absolute error (MAE), R-squared (R2), and variance accounted for (VAF) to determine the best models for predicting powder factor. The results indicate that the decision tree model (MD4) outperforms alternative approaches, such as artificial neural networks and Gaussian Process Regression (GPR). In addition, the research presents an efficient artificial neural network equation (MD2) for estimating the values of optimum powder factor, demonstrating outstanding blasting fragmentation. In conclusion, this research provides significant information for improving the accuracy of powder factor prediction, which is especially advantageous for small-scale blasting operations.

The possible application of fly ash (FA) to ameliorate acid mine water (AMD) for irrigation of potato (Solanum tuberosum L.).

Some areas in Johannesburg abounds with mine wastes namely, acid mine drainage (AMD) as well as fly ash (FA), which are by-products of gold mining and coal burning, respectively. Studies show that a solution formed through mixing these wastes neutralises the acidity of AMD and is an alternative source of irrigation. While studies show improved growth and yield of plants irrigated with fly ash-amended AMD, there are rarely sufficient studies conducted in South Africa showing evidence of altered pH of AMD and that food crops irrigated with fly ash-amended AMD exhibit improved concentration of essential nutrient elements. In this study, AMD was sourced from a gold mine in Johannesburg and fly ash collected from a coal-burning power station in the Mpumalanga Province, mixed at 1:0, 1:1, and 3:1 (w/v) of fly ash to AMD and used to irrigate potatoes. The objective was to assess whether the solutions of FA-amended AMD alter the pH of the AMD and to evaluate if irrigating potatoes with the aforementioned improve the concentration of essential nutrient elements and heavy metals in the tubers. Results show that the pH of AMD was increased in the 1:0 and 1:1 solutions but decreased in the 3:1 solution. The concentrations of Pb and Co were decreased in tubers irrigated with the 50 % AMD and 75 % AMD while that of Ni and Cd were markedly increased in tubers irrigated with solutions of fly ash-amended AMD. In the main, the potato tubers exhibited significantly higher concentrations of Al, Mo, Cu, Ca, Mg, and Zn when irrigated with fly-ash-amended AMD. The pH range levels from FA-AMD treated samples were within the acceptable pH range (5.5-6.5) which is acceptable for water that could be used for irrigation of crops. Also, the decreased Co and Pb and improved concentration of essential nutrient elements indicate that the constituents absorbed large quantities of the heavy metals while releasing the nutrients. In conclusion, the selected fly ash has proven as an alternative low-cost readily-available, affordable, and accessible adsorbent that neutralize the acidity of AMD, decrease the concentration of heavy metals, and increase the concentration of essential nutrient elements. Importantly, the liming potential among other traits of the fly ash improved the quality of the AMD such that the wastes were proven in this study suitable to irrigate potatoes.

Temporal dynamics of contaminants in an estuarine system affected by acid mine drainage discharges.

The estuary of Huelva is constituted by the common mouth of the Odiel and Tinto rivers, which are extreme cases of acid mine drainage contamination due to the Iberian Pyrite Belt, the world's largest sulfide mineral province. The drained acidic waters are subjected to seawater mixing and thus, to dilution and precipitation processes that drive the load of contaminants entering the oceanic environment. This research reports the distribution of major metal(loid)s present in the highly acidic waters across the entire Tinto and Odiel estuarine systems as they are subjected to acid mine drainage neutralization, until reaching the ocean. The datasets presented are divided in low- and high-flow periods, corresponding to dry/warm and wet/cold seasons, respectively. Iron and Al were almost entirely removed from solution with pH increase at both periods due to their precipitation as schwertmannite and basaluminite, respectively. These mineral phases also, controlled the behavior of As, Cu and Pb, which were removed from solution, with >90 % of their concentration ending up in the particulate phase due to sorption processes. However, at pH >7, As returned entirely to the dissolved phase at both sampled seasons because of desorption, similarly to Cu at the low-flow period. On the other hand, concentrations of Zn, Cd, Mn, Co and Ni in solution decreased only by dilution with seawater, with null partitioning to any sorption processes during estuarine mixing until reaching the Atlantic Ocean.

Evaluation of PVC and PTFE filters for direct-on-filter crystalline silica quantification by FTIR.

Direct-on-Filter (DoF) analysis of respirable crystalline silica (RCS) by Fourier Transform Infrared (FTIR) spectroscopy is a useful tool for assessing exposure risks. With the RCS exposure limits becoming lower, it is important to characterize and reduce measurement uncertainties. This study systematically evaluated two filter types (i.e., polyvinyl chloride [PVC] and polytetrafluoroethylene [PTFE]) for RCS measurements by DoF FTIR spectroscopy, including the filter-to-filter and day-to-day variability of blank filter FTIR reference spectra, particle deposition patterns, filtration efficiencies, and pressure drops. For PVC filters sampled at a flow rate of 2.5 L/min for 8 h, the RCS limit of detection (LOD) was 7.4 µg/m3 when a designated laboratory reference filter was used to correct the absorption by the filter media. When the spectrum of the pre-sample filter (blank filter before dust sampling) was used for correction, the LOD could be up to 5.9 µg/m3. The PVC absorption increased linearly with reference filter mass, providing a means to correct the absorption differences between the pre-sample and reference filters. For PTFE, the LODs were 12 and 1.2 µg/m3 when a designated laboratory blank or the pre-sample filter spectrum was used for blank correction, respectively, indicating that using the pre-sample blank spectrum will reduce RCS quantification uncertainty. Both filter types exhibited a consistent radially symmetric deposition pattern when particles were collected using 3-piece cassettes, indicating that RCS can be quantified from a single measurement at the filter center. The most penetrating aerodynamic diameters were around 0.1 µm with filtration efficiencies ≥ 98.8% across the measured particle size range with low-pressure drops (0.2-0.3 kPa) at a flow rate of 2.5 L/min. This study concludes that either the PVC or the PTFE filters are suitable for RCS analysis by DoF FTIR, but proper methods are needed to account for the variability of blank absorption among different filters.

Development of the wastewater treatment technology for the mine 'Ternivska' of the Kryvyi Rih iron ore plant.

Wastewater treatment in mining and mineral processing technology is a topical problem worldwide. The purpose of this study is to substantiate and develop the technology of complex wastewater treatment for the mine 'Ternivska' of the Public Joint Stock Company 'Kryvyi Rih Iron Ore Plant' with the production of highly purified water suitable for secondary use or ecologically safe discharge into surface water bodies. The proposed technology is based on the sequential application of the following stages: preliminary treatment of contaminated mine waters by coagulation and soda-lime softening methods to remove hardness, suspended solids, and colloidal substances; desalination via reverse osmosis; evaporation and crystallization of reverse osmosis concentrate in a vacuum evaporation unit; dehydration of salt sludge in a centrifuge with drying of salt crystals in a dryer. The treatment of mine water with an initial salinity of 80 g/L will give an annual effect of 1357 thousand m3 of desalinated water with a mineralization of up to 100 mg/L and 739.6 tons of mineral salt mixture. The purified water can serve as an additional source of fresh water for technological needs in industry or alternative purposes. The obtained solid salt product can be used as an alternative reagent for water-softening processes. In general, the proposed processing of mineralized mine water can be considered a zero-waste technology with clean water production and by-product utilization.

Method for Underground Mining Shaft Sensor Data Collection.

The motivation behind this research is the lack of an underground mining shaft data set in the literature in the form of open access. For this reason, our data set can be used for many research purposes such as shaft inspection, 3D measurements, simultaneous localization and mapping, artificial intelligence, etc. The data collection method incorporates rotated Velodyne VLP-16, Velodyne Ultra Puck VLP-32c, Livox Tele-15, IMU Xsens MTi-30 and Faro Focus 3D. The ground truth data were acquired with a geodetic survey including 15 ground control points and 6 Faro Focus 3D terrestrial laser scanner stations of a total 273,784,932 of 3D measurement points. This data set provides an end-user case study of realistic applications in mobile mapping technology. The goal of this research was to fill the gap in the underground mining data set domain. The result is the first open-access data set for an underground mining shaft (shaft depth -300 m).

Multi-decadal geochemical evolution of drainage from underground coal mines in the Appalachian basin, USA.

Coal mine drainage (CMD) in Appalachia is a widespread source of dissolved metals, SO4, and acidity that can degrade aquatic habitats and water supplies for decades following mine closure and flooding. In the bituminous coalfield of Pennsylvania, the Irwin Coal Basin (ICB) contains a series of partly to completely flooded, abandoned underground mines separated by leaky barriers within the Pittsburgh coal seam. CMD originated throughout the basin from minepool aquifers that formed after mine closures dating from 1910 to 1957. Historical and recent water quality data for eight CMD sites across the ICB, plus mineralogy and cation-exchange capacity of overburden lithologies, were analyzed to quantify important reactants and evaluate spatial and temporal water-quality trends. As overburden thickness and residence time increase along a ~ 50-km flowpath northeast to southwest in the basin, CMD becomes more alkaline, and Na concentrations increase. Since the 1970s, all eight ICB discharges have become less acidic, with exponential decreases in acidity, SO4, and Fe concentrations; only two CMD remain net-acidic (acidic pH at equilibrium). Exponential decay models that include a steady-state asymptote consistent with background groundwater chemistry and siderite equilibrium describe the early-stage, rapid contaminant concentration decay immediately after the "first flush" (initial flooding) and the progressive evolution toward late-stage background conditions. A geochemical evolution PHREEQC model indicates that spatial and temporal trends in pH, net-acidity, SO4, Fe, and major cations could be explained by the continuous dilution of first flush water by ambient groundwater combined with sustained water-mineral reactions involving pyrite and carbonates (calcite, dolomite, siderite) plus cation-exchange by clays (illite, chlorite, mixed-layer illite/smectite). These data and model results indicate that 1) cation-exchange reactions enhance calcite dissolution and alkalinity production, resulting in the evolution of CMD to Na-SO4-HCO3 type waters, and 2) siderite equilibrium could maintain dissolved Fe >16 mg/L over the next 40 years.

A case of prolonged corneal sulfur foreign bodies and review of literature.

BACKGROUND: This case mainly describes a relatively rare case of an old mineral-like corneal foreign body that existed for up to 20 years, and did not significantly affect the visual quality of the patient. CASE PRESENTATION: A 56-year-old male miner complained of right eye vision loss for 3 years, swollen and painful for 4 months. Admission examination: Best corrected visual acuity was no light perception in the right eye and 20/20 in the left eye. Anterior segment examination: A large number of spot-like grayish-brown mineral foreign bodies in the conjunctiva of the nasal conjunctiva, emulsified silicone oil floating in the anterior chamber, Corneal foreign bodies in the right eye were widely distributed in the upper cortex and the proelastic layer. There were fewer foreign bodies in the left cornea. Previous medical history, 20 years ago due to forging and burning sulphur mine explosion, resulting in a large number of ore foreign bodies in the conjunctiva of both eyes. As these corneal foreign bodies did not affect the visual quality of the patient, we adopted a conservative treatment plan, did not remove these foreign bodies, and only carried out symptomatic treatment for the patient's secondary ocular hypertension. The patient was followed up normally in the outpatient department, and no cornea-related complications occurred up to now. CONCLUSIONS: First of all, it is necessary to understand the source and nature of the foreign body in patients with corneal and conjunctival foreign body injuries. In the second, for the old corneal metal foreign body, when the patient's visual acuity is stable and there are no symptoms of corneal irritation and inflammatory reaction, it can be Conservative treatment or outpatient follow-up observation. In the end, corneal Optical coherence tomography imaging should not be ignored, which is very important for determining the depth of embedding and the location of the corneal foreign body.

Chemical characterization of green liquor dregs from 16 Swedish pulp and paper mills between 2017 and 2019.

Green liquor dregs (GLD) is an alkaline by-product from the pulp and paper industry with a pH between 10 and 14. Today most of the produced GLD in Sweden is landfilled. As a fine-grained alkaline material, it might be possible to use it for acid-generating mining waste remediation. To increase the utilization, quality characteristics and environmental performance need to be determined. In this study samples were collected 5 times from 16 mills during a period of 2.5 years, and were characterized by analyzing dry matter content, loss on ignition (LOI) 550 °C and LOI 950 °C, elemental analysis, pH, electrical conductivity, and calorific value. The results were then evaluated using multivariate statistics (PCA) as well as being compared to other studies and Swedish till. The results show that even if GLD is heterogenous (both within a mill and between different mills) trends can be seen for samples from most mills. When samples do stand out, it is predominately related to the same four mills. Most of the studied parameters showed characteristics favorable for use as a remediant; however, TOC, sulfur, and some of the elements require further study. In general, this study concludes that GLD can be a viable option for the remediation of small orphaned sulfidic mining sites and thus worthy of further studies on the interaction between GLD and acidic mining waste.Overall, GLD can be a good alternative for cost-effective remediation of smaller orphaned mining sites. It is readily available in large quantities, has the qualities needed for remediation of many orphaned acidic mining sites, and can often be locally sourced near the mining site. The use of GLD for mining site remediation is likely also a more sustainable method compared to traditional remediation methods.

A synthetic bacterial consortium improved the phytoremediation efficiency of ryegrass on polymetallic contaminated soil.

Polymetallic contamination of soils caused by mining activities seriously threatens soil fertility, biodiversity and human health. Bioremediation is thought to be of low cost and has minimal environmental risk but its effectiveness needs to be improved. This study aimed to identify the combined effect of plant growth and microbial strains with different functions on the enhancement of bioremediation of polymetallic contaminated soil. The microbiological mechanism of bioremediation was explored by amplicon sequencing and gene prediction. Soil was collected from polymetallic mine wastelands and a non-contaminated site for use in a pot experiment. Remediation efficiency of this method was evaluated by planting ryegrass and applying a mixed bacterial consortium comprising P-solubilizing, N-fixing and SO4-reducing bacteria. The plant-microbe joint remediation method significantly enhanced the above-ground biomass of ryegrass and soil nutrient contents, and at the same time reduced the content of heavy metals in the plant shoots and soil. The application of the composite bacterial inoculum significantly affected the structure of soil bacterial communities and increased the bacterial diversity and complexity, and the stability of co-occurrence networks. The relative abundance of the multifunctional genera to which the strains belonged showed a significant positive correlation with the soil nutrient content. Genera related to carbon (C), nitrogen (N), phosphorus (P), and sulphur (S) cycling and heavy metal resistance showed an up-regulation trend in heavy metal-contaminated soils after the application of the mixed bacterial consortium. Also, bacterial strains with specific functions in the mixed consortium regulated the expression of genes involved in soil nutrient cycling, and thus assisted in making the soil self-sustainable after remediation. These results suggested that the remediation of heavy metal-contaminated soil needs to give priority to the use of multifunctional bacterial agents.

Radiological characterization of the tailings of an abandoned copper mine using a neural network and geostatistical analysis through the Co-Kriging method.

The radiological characterization of soil contaminated with natural radionuclides enables the classification of the area under investigation, the optimization of laboratory measurements, and informed decision-making on potential site remediation. Neural networks (NN) are emerging as a new candidate for performing these tasks as an alternative to conventional geostatistical tools such as Co-Kriging. This study demonstrates the implementation of a NN for estimating radiological values such as ambient dose equivalent (H*(10)), surface activity and activity concentrations of natural radionuclides present in a waste dump of a Cu mine with a high level of natural radionuclides. The results obtained using a NN were compared with those estimated by Co-Kriging. Both models reproduced field measurements equivalently as a function of spatial coordinates. Similarly, the deviations from the reference concentration values obtained in the output layer of the NN were smaller than the deviations obtained from the multiple regression analysis (MRA), as indicated by the results of the root mean square error. Finally, the method validation showed that the estimation of radiological parameters based on their spatial coordinates faithfully reproduced the affected area. The estimation of the activity concentrations was less accurate for both the NN and MRA; however, both methods gave statistically comparable results for activity concentrations obtained by gamma spectrometry (Student's t-test and Fisher's F-test).

Environmental relevance monitoring and assessment of ochreous precipitates, hydrochemistry and water sources from abandoned coal mine drainage.

This study investigated the mineralogical and chemical characteristics of ochreous precipitates and mine water samples from abandoned Upper Carboniferous hard coal mines in an extensive former mining area in western Germany. Mine water characteristics have been monitored and assessed using a multi-methodological approach. Thirteen mine water discharge locations were sampled for hydrochemical analysis, with a total of 46 water samples seasonally collected in the whole study area for stable isotopic analyses. Mineralogical composition of 13 ochreous precipitates was identified by a combination of powder X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and field emission scanning electron microscopy (FE-SEM/EDS). Results showed that abandoned mine drainage was characterized by circumneutral pH, Eh values ranging from 163 to 269 mV, relatively low concentrations of Fe and Mn, and was dominated by HCO3- > SO42- > Cl- > NO3- and Na+ > Ca2+ > Mg2+ > K+. Goethite and ferrihydrite were the dominant precipitated Fe minerals, with traces of quartz, dolomite, and clay minerals. Some metal and metalloid elements (Mn, Al, Si, and Ti) were found in the ochreous sediments. The role of bacteria in the formation of secondary minerals was assessed with the detection of Leptothrix ochracea. The δ18O and δ2H values of mine water plotted on and close to the GMWL and LMWLs indicated local derivation from meteoric water and represented the annual mean precipitation isotopic composition. Results might help to develop strategies for the management of water resources, contaminated mine water, and public health.

Study on methane degradation by microbial agents based on chelating wetting agent carriers.

Due to the low permeability characteristics of the deep gas-containing coal seam, the conventional prevention and control measures that cannot solve the problems of gas outbursts are unsatisfactory for the prevention and control of the coal and gas outbursts disaster. Therefore, in this study, a strain of methane-oxidizing bacteria M07 with high-pressure resistance, strong resistance, and high methane degradation rate was selected from coal mines. The growth and degradation abilities of M07 in chelating wetting agent solutions to assess its adaptability and find the optimal agent-to-M07 ratio. It provides a new method for integrating the reduction of impact tendency and gas pressure in deep coal mines. The experimental results show that M07 is a Gram-positive bacterium of the genus Bacillus, which has strong resistance and adaptability to high-pressure water injection. By degrading 70 mol of methane, M07 produces 1 mol of carbon dioxide, which can reduce gas pressure and reduce the risk of gas outbursts in coal mines. As the experiment proves, the best effect was achieved when the M07 concentration of the chelating wetting agent was 0.05%. The methane-oxidizing bacteria based on the chelating wetting agent as carriers prove a new prevention and control method for the integrated prevention and control of coal and gas outbursts in coal mines and also provide a new idea for microbial application in coal mine disaster control.

Serum metabolic changes link metal mixture exposures to vascular endothelial inflammation in residents living surrounding rivers near abandoned lead-zinc mines.

Metal exposure is associated with vascular endothelial inflammation, an early pathological phenotype of atherosclerotic cardiovascular events. However, the underlying mechanism linking exposure, metabolic changes, and outcomes remains unclear. We aimed to investigate the metabolic changes underlying the associations of chronic exposure to metal mixtures with vascular endothelial inflammation. We recruited 960 adults aged 20-75 years from residential areas surrounding rivers near abandoned lead-zinc mine and classified them into river area and non-river area exposure groups. Urine levels of 25 metals, Framingham risk score (FRS), and serum concentrations of intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1), as biomarkers of vascular endothelial inflammation, were assessed. A "meet-in-the-middle" approach was applied to identify causal intermediate metabolites and metabolic pathways linking metal exposure to vascular endothelial inflammation in representative metabolic samples from 64 participants. Compared to the non-river area exposure group, the river area exposure group had significantly greater urine concentrations of chromium, copper, cadmium, and lead; lower urine concentrations of selenium; elevated FRS; and increased concentrations of ICAM-1 and VCAM-1. In total, 38 differentially abundant metabolites were identified between the river area and non-river area exposure groups. Among them, 25 metabolites were significantly associated with FRS, 8 metabolites with ICAM-1 expression, and 10 metabolites with VCAM-1 expression. Furthermore, fructose, ornithine, alpha-ketoglutaric acid, urea, and cytidine monophosphate, are potential mediators of the relationship between metal exposure and vascular endothelial inflammation. Additionally, the metabolic changes underlying these effects included changes in arginine and proline metabolism, pyrimidine metabolism, starch and sucrose metabolism, galactose metabolism, arginine biosynthesis, and alanine, aspartate, and glutamate metabolism, suggesting the disturbance of amino acid metabolism, the tricarboxylic acid cycle, nucleotide metabolism, and glycolysis. Overall, our results reveal biomechanisms that may link chronic exposure to multiple metals with vascular endothelial inflammation and elevated cardiovascular risk.

Modeling the geochemical evolution of mine waters during mixing.

This study focuses on assessing the hydrogeochemical processes influencing the mobility of dissolved metal and metalloid species during mine effluent mixing. Field samples were collected to characterize effluents at an active gold mine located in the Abitibi Greenstone belt in western Québec, Canada. Controlled laboratory mixing experiments were further performed with real effluents. In situ physicochemical parameters, concentrations of major dissolved ions and trace elements were analyzed. Mineralogical analyses were also performed on precipitates from the laboratory mixtures. The data were used for statistical analyses and for modeling the geochemical evolution of effluents using PHREEQC with the wateq4f.dat database (with modifications). The results suggest that the formation of secondary minerals such as schwertmannite, Fe(OH)3, and jarosite could significantly affect the concentrations of trace elements in effluents. The precipitation of secondary minerals immobilized trace elements through coprecipitation and sorption processes. The main limitations of the modeling approach used here include the evaluation of the ion balance for low pH samples with high Fe and Al concentrations and the omission of biological processes. The approach provides insights into the geochemical evolution of mine effluents and could be adapted to several mining sites as a tool for improving water management.

Microbial community structure in an uranium-rich acid mine drainage site: implication for the biogeochemical release of uranium.

The generation of acid mine drainage (AMD) characterized by high acidity and elevated levels of toxic metals primarily results from the oxidation and dissolution of sulfide minerals facilitated by microbial catalysis. Although there has been significant research on microbial diversity and community composition in AMD, as well as the relationship between microbes and heavy metals, there remains a gap in understanding the microbial community structure in uranium-enriched AMD sites. In this paper, water samples with varying levels of uranium pollution were collected from an abandoned stone coal mine in Jiangxi Province, China during summer and winter, respectively. Geochemical and high-throughput sequencing analyses were conducted to characterize spatiotemporal variations in bacterial diversity and community composition along pollution groups. The results indicated that uranium was predominantly concentrated in the AMD of new pits with strong acid production capacity, reaching a peak concentration of 9,370 µg/L. This was accompanied by elevated acidity and concentrations of iron and total phosphorus, which were identified as significant drivers shaping the composition of bacterial communities, rather than fluctuations in seasonal conditions. In an extremely polluted environment (pH < 3), bacterial diversity was lowest, with a predominant presence of acidophilic iron-oxidizing bacteria (such as Ferrovum), and a portion of acidophilic heterotrophic bacteria synergistically coexisting. As pollution levels decreased, the microbial community gradually evolved to cohabitation of various pH-neutral heterotrophic species, ultimately reverting back to background level. The pH was the dominant factor determining biogeochemical release of uranium in AMD. Acidophilic and uranium-tolerant bacteria, including Ferrovum, Leptospirillum, Acidiphilium, and Metallibacterium, were identified as playing key roles in this process through mechanisms such as enhancing acid production rate and facilitating organic matter biodegradation.