Association between PM2.5 from a coal mine fire and FeNO concentration 7.5 years later.

BACKGROUND AND AIM: There are few long-term studies of respiratory health effects of landscape fires, despite increasing frequency and intensity due to climate change. We investigated the association between exposure to coal mine fire PM2.5 and fractional exhaled nitric oxide (FeNO) concentration 7.5 years later. METHODS: Adult residents of Morwell, who were exposed to the 2014 Hazelwood mine fire over 6 weeks, and unexposed residents of Sale, participated in the Hazelwood Health Study Respiratory Stream in 2021, including measurements of FeNO concentration, a marker of eosinophilic airway inflammation. Individual exposure to coal mine fire PM2.5 was modelled and mapped to time-location diaries. The effect of exposure to PM2.5 on log-transformed FeNO in exhaled breath was investigated using multivariate linear regression models in the entire sample and stratified by potentially vulnerable subgroups. RESULTS: A total of 326 adults (mean age: 57 years) had FeNO measured. The median FeNO level (interquartile range [IQR]) was 17.5 [15.0] ppb, and individual daily exposure to coal mine fire PM2.5 was 7.2 [13.8] µg/m3. We did not identify evidence of association between coal mine fire PM2.5 exposure and FeNO in the general adult sample, nor in various potentially vulnerable subgroups. The point estimates were consistently close to zero in the total sample and subgroups. CONCLUSION: Despite previous short-term impacts on FeNO and respiratory health outcomes in the medium term, we found no evidence that PM2.5 from the Hazelwood coal mine fire was associated with any long-term impact on eosinophilic airway inflammation measured by FeNO levels.

Mine water inrush source discrimination model based on KPCA-ISSA-KELM.

In order to ensure the safety of coal mine production, a mine water source identification model is proposed to improve the accuracy of mine water inrush source identification and effectively prevent water inrush accidents based on kernel principal component analysis (KPCA) and improved sparrow search algorithm (ISSA) optimized kernel extreme learning machine (KELM). Taking Zhaogezhuang mine as the research object, firstly, Na+, Ca2+, Mg2+, Cl-, SO2- 4 and HCO- 3 were selected as evaluation indexes, and their correlation was analyzed by SPSS27 software, with reducing the dimension of the original data by KPCA. Secondly, the Sine Chaotic Mapping, dynamic adaptive weights, and Cauchy Variation and Reverse Learning were introduced to improve the Sparrow Search Algorithm (SSA) to strengthen global search ability and stability. Meanwhile, the ISSA was used to optimize the kernel parameters and regularization coefficients in the KELM to establish a mine water inrush source discrimination model based on the KPCA-ISSA-KELM. Then, the mine water source data are input into the model for discrimination in compared with discrimination results of KPCA-SSA-KELM, KPCA-KELM, ISSA-KELM, SSA-KELM and KELM models. The results of the study show as follows: The discrimination results of the KPCA-ISSA-KELM model are in agreement with the actual results. Compared with the other models, the accuracy of the KPCA-ISSA-KELM model is improved by 8.33%, 12.5%, 4.17%, 21.83%, and 25%, respectively. Finally, when these models were applied to discriminate water sources in a coal mine in Shanxi, and the misjudgment rates of each model were 28.57%, 19.05%, 14.29%, 23.81%, 9.52% and 4.76%, respectively. From this, the KPCA-ISSA-KLEM model is the most accurate about discrimination and significantly better than other models in other evaluation indicators, verifying the universality and stability of the model. It can be effectively applied to the discrimination of inrush water sources in mines, providing important guarantees for mine safety production.

In Situ Lung Dust Analysis by Automated Field Emission Scanning Electron Microscopy With Energy Dispersive X-ray Spectroscopy: A Method for Assessing Inorganic Particles in Lung Tissue From Coal Miners.

CONTEXT.­: Overexposure to respirable coal mine dust can cause severe lung disease including progressive massive fibrosis (PMF). Field emission scanning electron microscopy with energy dispersive x-ray spectroscopy (FESEM-EDS) has been used for in situ lung dust particle analysis for evaluation of disease etiology. Automating such work can reduce time, costs, and user bias. OBJECTIVE.­: To develop and test an automated FESEM-EDS method for in situ analysis of inorganic particles in coal miner lung tissue. DESIGN.­: We programmed an automated FESEM-EDS procedure to collect particle size and elemental data, using lung tissue from 10 underground coal miners with PMF and 4 control cases. A statistical clustering approach was used to establish classification criteria based on particle chemistry. Data were correlated to PMF/non-PMF areas of the tissue, using corresponding brightfield microscopy images. Results for each miner case were compared with a separate corresponding analysis of particles recovered following tissue digestion. RESULTS.­: In situ analysis of miner tissues showed higher particle number densities than controls and densities were generally higher in PMF than non-PMF areas. Particle counts were typically dominated by aluminum silicates with varying percentages of silica. Compared to digestion results for the miner tissues, in situ results indicated lower density of particles (number per tissue volume), larger size, and a lower ratio of silica to total silicates-probably due to frequent particle clustering in situ. CONCLUSIONS.­: Automated FESEM-EDS analysis of lung dust is feasible in situ and could be applied to a larger set of mineral dust-exposed lung tissues to investigate specific histologic features of PMF and other dust-related occupational diseases.

Distribution of mercury and methylmercury in aquacultured fish in special waters formed by coal mining subsidence.

In China, fence net aquaculture practices have been established in some subsidence waters that have been formed in coal mining subsidence areas. Within this dynamic ecological context, diverse fish species grow continuously until being harvested at the culmination of their production cycle. The purpose of this study was to investigate diverse factors influencing the bioavailability and distribution of mercury (Hg) and methylmercury (MeHg), which have high physiological toxicity in fish, in the Guqiao coal mining subsidence area in Huainan, China. Mercury and MeHg were analyzed in 38 fish samples of eight species using direct mercury analysis (DMA-80) and gas chromatography-cold vapor atomic fluorescence spectrometry (GC-CVAFAS). The analysis results show that the ranges of Hg and MeHg content and methylation rate in the fish were 7.84-85.18 ng/g, 0.52-3.52 ng/g, and 0.81-42.68 %, respectively. Meanwhile, conclusions are also summarized as following: (1) Monophagous herbivorous fish that were fed continuously in fence net aquaculture areas had higher MeHg levels and mercury methylation rates than carnivorous fish. Hg and MeHg contents were affected by different feeding habits of fish. (2) Bottom-dwelling fish show higher MeHg levels, and habitat selection in terms of water depth also partially affected the MeHg content of fish. (3) The effect of fence net aquaculture on methylation of fish in subsidence water is mainly from feed and mercury-containing bottom sediments. However, a time-lag is observed in the physiological response of benthic fishes to the release of Hg from sediments. Our findings provides baseline reference data for the ecological impact of fence net aquaculture in waters affected by soil subsidence induced by coal mining in China. Prevalent environmental contaminants within coal mining locales, notably Hg, may infiltrate rain-induced subsidence waters through various pathways.

Limestone water mixing process and hydrogen and oxygen stable isotope fractionation response under mining action.

North China type coalfield are gradually mining deep, and the mixing of groundwater is intensified. Hydrogen and oxygen isotopes are important elements for tracing groundwater movement. The fractionation response mechanism under mining conditions is not clear. In this paper, combined with numerical simulation, MixSIAR isotope mixing model and other methods, according to the δD, δ18O and hydrochemical information of various water bodies, the impact of coal mining on hydrogen and oxygen isotope fractionation is analyzed from multiple perspectives. The results show that summer soil water is the main source of recharge for limestone water, accounting for 30.7%-41.5%, and the Zhan River is the main source of recharge for limestone water. Before groundwater recharge, evaporation leads to the increase of δ18O in surface water by 0.31‰-5.58‰, water loss by 1.81%-28.00%, the increase of δ18O in soil water by 0.47‰-6.33‰, and water loss by 2.74%-35.80%. Compared with the coal mining layer, the degree of hydrogen and oxygen isotope drift and water-rock interaction in the coal mine stopping layer are significantly improved. The results of numerical simulation show that the pumping activity reduces the 18O concentration in the mining layer. The ion ratio is used as a new variable to eliminate the influence of water-rock interaction when calculating the mixing ratio. The results show that the limestone water is in a state of receiving external recharge, and mixing effect increases the δ18O in limestone water by 0.86‰ on average, and the δD increases by 0.72‰ on average. The research results explain the controlled process of hydrogen and oxygen isotope fractionation under mining conditions, which is of great significance to coal mine safety production.

Anthropogenic processes drive spatiotemporal variability of sulfate in groundwater from a multi-aquifer system: Dilution caused by mine drainage.

The water quality evolution of surface and groundwater caused by mining activities and mine drainage is a grave public concern worldwide. To explore the effect of mine drainage on sulfate evolution, a multi-aquifer system in a typical coal mine in Northwest China was investigated using multi-isotopes (δ34SSO4, δ18OSO4, δD, and δ18Owater) and Positive Matrix Factorization (PMF) model. Before mining, the Jurassic aquifer was dominated by gypsum dissolution, accompanied by cation exchange and bacterial sulfate reduction, and the phreatic aquifers and surface water were dominated by carbonate dissolution. Significant increase in sulfate in phreatic aquifers due to mine drainage during the early stages of coal mining. However, in contrast to common mining activities that result in sulfate contamination from pyrite oxidation, mine drainage in this mining area resulted in accelerated groundwater flow and enhanced hydraulic connections between the phreatic and confined aquifers. Dilution caused by the altered groundwater flow system controlled the evolution of sulphate, leading to different degrees of sulfate decrease in all aquifers and surface water. As the hydrogeochemical characteristic of Jurassic aquifer evolved toward phreatic aquifer, this factor should be considered to avoid misjudgment in determining the source of mine water intrusion. The study reveals the hydrogeochemical evolution induced by mine drainage, which could benefit to the management of groundwater resources in mining areas.

Mechanisms of secondary biogenic coalbed methane formation in bituminous coal seams: a joint experimental and multi-omics study.

Coal seam microbes, as endogenous drivers of secondary biogenic gas production in coal seams, might be related to methane production in coal seams. In this study, we carried out anaerobic indoor culture experiments of microorganisms from three different depths of bituminous coal seams in Huainan mining area, and revealed the secondary biogas generation mechanism of bituminous coal seams by using the combined analysis of macro-genome and metabolism multi-omics. The results showed that the cumulative mass molar concentrations (Molality) of biomethane production increased with the increase of the coal seam depth in two consecutive cycles. At the genus level, there were significant differences in the bacterial and archaeal community structures corresponding to the three coal seams 1#, 6#, and 9#(p < 0.05). The volatile matter of air-dry basis (Vad) of coal was significantly correlated with differences in genus-level composition of bacteria and archaea, with correlations of R bacterial = 0.368 and R archaeal = 0.463, respectively. Functional gene analysis showed that the relative abundance of methanogenesis increased by 42% before and after anaerobic fermentation cultivation. Meanwhile, a total of 11 classes of carbon metabolism homologues closely related to methanogenesis were detected in the liquid metabolites of coal bed microbes after 60 days of incubation. Finally, the fatty acid, amino acid and carbohydrate synergistic methanogenic metabolic pathway was reconstructed based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The expression level of mcrA gene within the metabolic pathway of the 1# deep coal sample was significantly higher than that of the other two groups (p < 0.05 for significance), and the efficient expression of mcrA gene at the end of the methanogenic pathway promoted the conversion of bituminous coal organic matter to methane. Therefore, coal matrix compositions may be the key factors causing diversity in microbial community and metabolic function, which might be related to the different methane content in different coal seams.

[Neural network analysis of mechanization's impact on coal miner's occupational health].

In order to clarify the transmission mechanism of the impact of mechanization on the occupational health of miners and to provide empirical evidence for the development of new quality productivity in the coal industry that balances health and efficiency. In August 2022, we selected a typical coal mine, constructed a comprehensive evaluation index of miners' occupational health through a questionnaire survey based on the fully connected neural network model. A Bayesian model was used to verify the influence of mechanization level on miners' occupational health. We found that: the predicted probability of occupational diseases could be used as a comprehensive indicator of the level of occupational health, providing a basis for early intervention and prevention of occupational diseases. Mechanization could directly promote the improvement of miners' occupational health level, and also indirectly affect occupational health level by influencing hazards level and work intensity. The indirect effect of mechanization on work intensity was positive, and the indirect effect of mechanization on hazards level was positive. Presented the "inverted U-shaped" process in the mechanization breakthrough semi-mechanized level would realize the economies of scale of health protection, its impact on the prevention and control of occupational hazards would turn from negative to positive.

Comparison of the monitoring of surface deformations in open-pit mines with Sentinel-1A and TerraSAR-X satellite radar data.

In case necessary precautions are not taken in surface mines, serious accidents and loss of life may occur, particularly due to large mass displacements. It is extremely important to identify the early warning signs of these displacements and take the necessary precautions. In this study, free medium-resolution satellite radar images from the European Space Agency's (ESA) C-band Sentinel-1A satellite and commercial high-resolution satellite radar images (SAR, Synthetic Aperture Radar) from the Deutsches Zentrum für Luft- und Raumfahrt's (DLR) X-band TerraSAR-X satellite were obtained, and it was attempted to reveal the traceability and adequacy of monitoring of deformations and possible mass displacements in the dump site of an open-pit coal mine. The compatibility of the results obtained from the satellite radar data with two devices of Global Positioning System (GPS) which were installed in the field was evaluated. Furthermore, the velocity results in the Line Of Sight (LOS) direction and vertical deformation velocity results obtained with all three approaches (GPS/Sentinel-1A, GPS/TerraSAR-X, and Sentinel-1A/TerraSAR-X) were compared. It was observed that the results were statistically equal and the directions of movement were similar/compatible. The result of this study showed that deformations at mine sites can be monitored with sufficient accuracy for early warning with free Sentinel-1A satellite data, although the TerraSAR-X satellite offers a higher resolution.

Ecological disturbance effects of surface vegetation during coal mining in arid regions of Western China.

Coal mining in arid western regions is damaging the fragile ecology, causing problems such as surface damage, vegetation destruction, and soil erosion. These issues are obstacles to the development of green coal, as mining activities can disrupt the distribution of surface vegetation, leading to its spread outside the mining area and affecting surrounding areas. Based on Landsat data, the binary pixel model was used to calculate the vegetation coverage (FVC) in mining area from 2005 to 2021. Through vegetation coverage classification and regression trend analysis, the temporal and spatial changes and evolution trends of vegetation disturbance caused by coal mining and climate were analyzed. Correlation analysis revealed the range of ecological disturbance caused by coal mining at the coal mine scale and mining area scale. The results show that the vegetation coverage of the mining area showed a decreasing trend from 2005 to 2021. Winter and spring precipitation was the primary factor affecting vegetation growth in the area, while coal mining had indirect and secondary effects on vegetation. Human activities played a significant role in improving vegetation, and between 2015 and 2018, the area of vegetation improvement increased by 133.41% compared to that of 2009-2014. Compared to the reference area, the impact range of vegetation disturbance in the mining area is 2.5-5 km, while the impact range of vegetation disturbance in the coal mine is less than 500 m. Therefore, this study provides a theoretical basis for studying the impact of mining activities on vegetation and boundary identification.

Influence of land use change on habitat quality: a case study of coal mining subsidence areas.

Revealing the spatiotemporal evolution characteristics and key driving processes behind the habitat quality is of great significance for the scientific management of production, living, and ecological spaces in resource-based cities, as well as for the efficient allocation of resources. Focusing on the largest coal-mining subsidence area in Jiangsu Province of China, this study examines the spatiotemporal evolution of land use intensity, morphology, and functionality across different time periods. It evaluates the habitat quality characteristics of the Pan'an Lake area by utilizing the InVEST model, spatial autocorrelation, and hotspot analysis techniques. Subsequently, by employing the GTWR model, it quantifies the influence of key factors, unveiling the spatially varying characteristics of their impact on habitat quality. The findings reveal a notable surge in construction activity within the Pan'an Lake area, indicative of pronounced human intervention. Concurrently, habitat degradation intensifies, alongside an expanding spatial heterogeneity in degradation levels. The worst habitat quality occurs during the periods of coal mining and large-scale urban construction. The escalation in land use intensity emerges as the primary catalyst for habitat quality decline in the Pan'an Lake area, with other factors exhibiting spatial variability in their effects and intensities across different stages.

Experimental investigation on dynamic deformation characteristics of the overlying strata in backfilling strip mining at different time scales.

The dynamic subsidence disaster caused by underground mining of coal resources is a complex spatiotemporal process, which is a common disaster in mining areas. The backfilling strip mining technology is a green and sustainable coal mining method, which has been commonly used to reduce the subsidence disaster of the overlying strata and protect surface buildings. The transient deformation is the main reason of surface buildings damage; therefore, in this study, the similar material model was used to research dynamic deformation characteristics of the overlying strata in backfilling strip mining at different time scales, and the optical image method was employed to monitor and obtain the movement data of the overlying strata automatically. The data analysis shows that there is a time-scale effect in mining subsidence. The deformation of the overlying strata increases instantaneously at a certain time under the monitoring of small time scale, and this phenomenon gradually disappears as time scales increase. According to the subsidence velocity of small time scale, the subsidence state of the overlying strata can be further divided into the abrupt subsidence state and the gentle subsidence state. This is really significant for promoting the development of the backfilling strip mining technology and preventing the damage of surface buildings.

Construction and application of a novel WGAN-CNN-based predicting approach for dust concentration at underground coal mine working faces.

To enhance the real-time monitoring and early-warning capabilities for dust disasters in underground coal mine, this paper presents a novel WGAN-CNN-based prediction approach to predict the dust concentration at underground coal mine working faces. Dust concentration, wind speed, temperature, and methane concentration were collected as the original data due to their nonlinear relationship. The consistency between the generated and original data distributions was verified through PCA dimensionality reduction analysis. The predictive performance of this approach was assessed using five metrics (R2, EVS, MSE, RMSE, and MAE) and compared with three other algorithms (Random Forest Regressor, MLP Regressor, and LinearSVR). The findings indicate that a majority of the generated data falls within the distribution range of the real dataset, exhibiting reduced levels of volatility and dispersion. The R2 values of prediction results are all above 98%, and the MSE values are between 0.0007 and 0.0106. The proposed approach exhibits superior predictive accuracy and robust model generalization capabilities compared to alternative algorithms, thereby enhancing the real-time monitoring and early-warning level of dust disasters in underground coal mine. This will facilitate the realization of advanced prevention and control measures for dust disasters, showcasing a wide range of potential applications.

Acid mine drainage from coal mines in the eastern Himalayan sub-region: Hydrogeochemical processes, seasonal variations and insights from hydrogen and oxygen stable isotopes.

Uncontrolled coal mining using non-scientific methods has presented a major threat to the quality of environment, particularly the water resources in eastern himalayan sub-region of India. Water bodies in the vicinity of mining areas are contaminated by acid mine drainage (AMD) that is released into streams and rivers. This study attempted to assess the impact of AMD, deciphering hydrogeochemical processes, seasonal fluctuations, and stable isotope features of water bodies flowing through and around coal mining areas. Self-organizing maps (SOMs) used to separate and categorize AMD, AMD-impacted and non-AMD impacted water from the different study locations for two sampling seasons revealed four clusters (C), with C1 and C2 impacted by AMD, C3 and C4 showing negligible to no impact of AMD. AMD impacted water was SO42- - Mg2+- Ca2+ hydrochemical type with sulphide oxidation and evaporation dominating water chemistry, followed by silicate weathering during both the sampling seasons. Water with negligible-to-no AMD-impact was Mg2+- Ca2+- SO42- to Ca2+ - HCO3- to mixed hydrochemical type with rock weathering and dissolution, followed by ion exchange as major factors controlling water chemistry during both the sampling seasons. Most of physicochemical parameters of C1 and C2 exceeded the prescribed limits, whereas in C3 and C4 water samples, parameters were found within the prescribed limits. Stable isotopes of hydrogen (δ2H) and oxygen (δ18O) during post-monsoon (PoM) varied between -41.04 ‰ and -29.98 ‰, and -6.60 ‰ to -3.94 ‰; and during pre-monsoon (PrM) varied between -58.18 ‰ and - 33.76 ‰ and -8.60 ‰ to -5.46 ‰. Deuterium excess (d-excess) ranged between 1.57 ‰ and 12.47 ‰ during PoM and 5.70 ‰ to 15.17 ‰ during PrM season. The stable isotopes analysis revealed that evaporation, mineral dissolution and mixing with rainwater are the key factors in study area.

Coal mining environment causes adverse effects on workers.

Background: The objective of this study is to study the adverse effects of coal mining environment on workers to discover early effective biomarkers. Methods: The molecular epidemiological study was conducted with 502 in-service workers, who were divided into miner and auxiliary. We measured the individual levels of dust exposure for participants. Clinical examinations were conducted by qualified doctors. Peripheral blood was collected to measure biochemistry, hemogram, and karyocyte apoptosis. Results: All workers were healthy who have not found with any diseases that can be diagnosed medically in the physical examination and showed no difference in dust exposure level, age, height, weight, and body mass index between groups. The working years of miners were lower than that of auxiliaries (p < 0.001). Compared with auxiliaries, the concentration and percentage of lymphocytes (p = 0.040, p = 0.012), basophils (p = 0.027, p = 0.034), and red blood cells (p < 0.001) and the concentration of hemoglobin of miners were lower (p < 0.001). The percentage of neutrophils (p = 0.003), the concentration of mean corpuscular hemoglobin concentration (p = 0.002), and the proportion of karyocyte apoptosis in miners were higher (p < 0.001). Miners presented higher blood urea nitrogen (p < 0.001), ratio of blood urea nitrogen to creatinine (p < 0.001), the high density lipoprotein cholesterol (p < 0.001), lower creatinine (p < 0.05), and cholesterol (p < 0.001). Conclusion: The coal mining environment impacted mining workers' immune function, renal function, and the hematopoietic system, including BUN/CRE, HGB, RBC, and LYMPH, which could be used as early biomarkers to screen the health of coal miners.

Review of soil environment quality in India near coal mining regions: current and future predictions.

Production and utilization of coal are one of the primary routes of accumulation of Toxic Elements (TEs) in the soil. The exploration of trends in the accumulation of TEs is essential to establishing a soil pollution strategy, implementing cost-effective remediation, and early warnings of ecological risks. This study provides a comprehensive review of soil concentrations and future accumulation trends of various TEs (Cr, Ni, Pb, Co, Cu, Cd, Zn, Fe, Mn, and As) in Indian coal mines. The findings revealed that average concentrations of Cr, Mn, Ni, Cu, Zn, Pb, and Co surpass India's natural background soil levels by factors of 2, 4.05, 5.32, 1.77, 9.6, and 6.15, respectively. Geo-accumulation index values revealed that 27.3%, 14.3%, and 7.7% of coal mines are heavily polluted by Ni, Co, and Cu, respectively. Also, the Potential Ecological Risk Index indicates that Cd and Ni are primary contaminants in coal mines. Besides, the health risk assessment reveals oral ingestion as the main exposure route for soil TMs. Children exhibit a higher hazard index than adults, with Pb and Cr being major contributors to their non-carcinogenic risk. In addition, carcinogenic risks exist for females and children, with Cr and Cu as primary contributors. Multivariate statistical analysis revealed that TEs (except Cd) accumulated in the soil from anthropogenic sources. The assessment of future accumulation trends in soil TE concentrations reveals dynamic increases that significantly impact both the ecology and humans at elevated levels. This study signifies a substantial improvement in soil quality and risk management in mining regions.

Multivariate analysis applied to X-ray fluorescence to assess soil contamination pathways: case studies of mass magnetic susceptibility in soils near abandoned coal and W/Sn mines.

Determining the origin and pathways of contaminants in the natural environment is key to informing any mitigation process. The mass magnetic susceptibility of soils allows a rapid method to measure the concentration of magnetic minerals, derived from anthropogenic activities such as mining or industrial processes, i.e., smelting metals (technogenic origin), or from the local bedrock (of geogenic origin). This is especially effective when combined with rapid geochemical analyses of soils. The use of multivariate analysis (MVA) elucidates complex multiple-component relationships between soil geochemistry and magnetic susceptibility. In the case of soil mining sites, X-ray fluorescence (XRF) spectroscopic data of soils contaminated by mine waste shows statistically significant relationships between magnetic susceptibility and some base metal species (e.g., Fe, Pb, Zn, etc.). Here, we show how qualitative and quantitative MVA methodologies can be used to assess soil contamination pathways using mass magnetic susceptibility and XRF spectra of soils near abandoned coal and W/Sn mines (NW Portugal). Principal component analysis (PCA) showed how the first two primary components (PC-1 + PC-2) explained 94% of the sample variability, grouped them according to their geochemistry and magnetic susceptibility in to geogenic and technogenic groups. Regression analyses showed a strong positive correlation (R2 > 0.95) between soil geochemistry and magnetic properties at the local scale. These parameters provided an insight into the multi-element variables that control magnetic susceptibility and indicated the possibility of efficient assessment of potentially contaminated sites through mass-specific soil magnetism.

Eating Disorder Risks Associated with Time Spent Using Social Media at an AMREC Population in the Coal Mining Region of Santa Catarina.

Comparing one's appearance to other people's and believing in an ideal body shape can negatively impact an individual. The probability of developing ED in individuals with high body dissatisfaction is higher than in the general population, leading to long-term emotional and metabolic damage. Populational studies on the prevalence of ED in Brazil are scarce in the literature. The research was carried out through the Google Forms website and evaluated risk of eating disorders through the Eating Attitude Test, degree of body dissatisfaction in the sample through the Body Shape Questionnaire and the Internet Addiction Test was used to evaluate time spent on the internet. The results showed that 84.5% of the sample were female and 62.3% of the individuals had eutrophic by the Body Mass Index. About 40.2% of the population studied had abnormal attitudes towards food, indicating a possible risk of developing ED, and 62.5% of the sample did not show body dissatisfaction. Regarding internet use, 10.8% had problematic internet use. The presence of risky eating attitudes was more prevalent in participants dissatisfied with their bodies. In addition, participants with problematic internet use had a higher risk for EDs.

Selenate bioreduction in a large in situ field trial.

Removing selenium (Se) from mine effluent is a common challenge. A long-term, in situ experiment was conducted to bioremediate large volumes (up to 7500 mc d-1) of Se(VI)-contaminated water (mean 87 µg L-1) by injecting the water into a saturated waste rock fill (SRF) at a coal mining operation in Elk Valley, British Columbia, Canada. To stimulate/maintain biofilm growth in the SRF, labile organic carbon (methanol) and nutrients were added to the water prior to its injection. A conservative tracer (Br-) was also added to track the migration of injected water across the SRF, identify wells with minimal dilution and used to quantify the extent of bioreduction. The evolution of the Se species through the SRF was monitored in time and space for 201 d. Selenium concentrations of <3.8 µg L-1 were attained in monitoring wells located 38 m from the injection wells after 114 to 141 d of operation. Concentrations of Se species in water samples from complementary long-term (351-498 d) column experiments using influent Se(VI) concentrations of 1.0 mg L-1 were consistent with the results of the in situ experiment. Solid samples collected at the completion of the column experiments confirmed the presence of indigenous Se-reducing bacteria and that the sequestered Se was present as insoluble Se(0), likely in Se-S ring compounds. Based on the success of this ongoing bioremediation experiment, this technology is being applied at other mine sites.

The neurocognitive mechanism linking temperature and humidity with miners' alertness: an fNIRS study.

As the depth of coal mining increases, the temperature and humidity of the underground environment also rise, which can negatively impact the physiological health of miners, and may even pose a threat to their safety and lives. However, studies on the neurocognitive mechanisms underlying the relationship between temperature, humidity, and miners' alertness are scant. This study investigates several research objectives: (A) the differences in reaction time and error rate in different temperature and humidity conditions, which factor has a greater impact; (B) the differences in the levels of Oxy-Hb in different conditions and which factor has a greater impact; (C) the differences of activation degree between different regions of interest; and (D) the differences in the shape of Oxy-Hb time course between different conditions between different regions of interests. The fNIRS was used to measure the activity in 100 participants' prefrontal cortex in this study. The results showed that both temperature and humidity would lead to decreased alertness of miners, which would not only prolong the reaction time, increase the error rate, and increase the Oxy-Hb concentration, but also lead to increased activation of the prefrontal cortex and greater activation of the right side than that of the left side, the Oxy-Hb time course was different on both sides, and temperature has a greater effect on alertness than humidity.