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.

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.

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.

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.

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.

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.

Analysis of strength failure in gangue-based cementitious backfill body from a microscopic perspective.

Backfill mining is an effective way to solve environment pollute, surface subsidence, and groundwater system damage which caused by coal mining. However, the complex underground environment may change the physical and mechanical properties of the backfill body, which poses a risk of strength failure. This paper analyzed the failure of gangue-based cemented backfill body which made up of gangue and fly ash. The results show that physicochemical reactions will generate quartz, kaolinite, and other high-strength substances; hydration reaction between the fine particles will generate hydrocalcium silicate and other C-S-H gels, they wrapped gangues as a whole, which provide a high strength of the cemented backfill body. Several experiments were carried out in order to find the reason for failure in samples under loads. The conclusion drawn as following: (1) When the load is large, the cracks extend from the surface of the samples to the interior, at the same time, the length and width of the cracks increasing obviously and connecting as net. Especially the external load exceeds the peak intensity. (2) The relationship between sample failure and pores is weak, but obvious with crack development, especially the cracks connected as a net. (3) The interface structure formed by gangue is an important source of crack development and, thus, will stimulate the development of cracks.

Experimental research on the influence of acid on the chemical and pore structure evolution characteristics of Wenjiaba tectonic coal.

The chemical and pore structures of coal play a crucial role in determining the content of free gas in coal reservoirs. This study focuses on investigating the impact of acidification transformation on the micro-physical and chemical structure characteristics of coal samples collected from Wenjiaba No. 1 Mine in Guizhou. The research involves a semi-quantitative analysis of the chemical structure parameters and crystal structure of coal samples before and after acidification using Fourier Transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) experiments. Additionally, the evolution characteristics of the pore structure are characterized through high-pressure mercury injection (HP-MIP), low-temperature nitrogen adsorption (LT-N2A), and scanning electron microscopy (SEM). The experimental findings reveal that the acid solution modifies the structural features of coal samples, weakening certain vibrational structures and altering the chemical composition. Specifically, the asymmetric vibration structure of aliphatic CH2, the asymmetric vibration of aliphatic CH3, and the symmetric vibration of CH2 are affected. This leads to a decrease in the contents of -OH and -NH functional groups while increasing aromatic structures. The crystal structure of coal samples primarily dissolves transversely after acidification, affecting intergranular spacing and average height. Acid treatment corrodes mineral particles within coal sample cracks, augmenting porosity, average pore diameter, and the ratio of macro-pores to transitional pores. Moreover, acidification increases fracture width and texture, enhancing the connectivity of the fracture structure in coal samples. These findings provide theoretical insights for optimizing coalbed methane (CBM) extraction and gas control strategies.

Human health risks of heavy metal(loid)s mediated through crop ingestion in a coal mining area in Eastern China.

The heavy metal(loid)s (HMs) in soils can be accumulated by crops grown, which is accompanied by crop ingestion into the human body and then causes harm to human health. Hence, the health risks posed by HMs in three crops for different populations were assessed using Health risk assessment (HRA) model coupled with Monte Carlo simulation. Results revealed that Zn had the highest concentration among three crops; while Ni was the main polluting element in maize and soybean, and As in rice. Non-carcinogenic risk for all populations through rice ingestion was at an "unacceptable" level, and teenagers suffered higher risk than adults and children. All populations through ingestion of three crops might suffer Carcinogenic risk, with the similar order of Total carcinogenic risk (TCR): TCRAdults > TCRTeenagers > TCRChildren. As and Ni were identified as priority control HMs in this study area due to their high contribution rates to health risks. According to the HRA results, the human health risk was associated with crop varieties, HM species, and age groups. Our findings suggest that only limiting the Maximum allowable intake rate is not sufficient to prevent health risks caused by crop HMs, thus more risk precautions are needed.

Research and application of bag filter system for railway ballast bed coal suction vehicles: An optimization and application study.

The current bag filter system used by railway ballast bed coal suction vehicles for cleaning coal dust from railway tunnels has low operational efficiency and generates significant volumes of dust. This paper describes a simulation test unit designed to enhance the dust removal performance in railway tunnels. The flow field inside the simulation test unit is investigated under different operating conditions through numerical simulations, and the variations in air volume and working resistance, total dust collection efficiency, and optimal operating parameters of a pulse cleaning system are identified through a series of experiments. The numerical results show that the pulse cleaning system does not significantly affect the uniformity of the flow field distribution at the bottom of the filter cartridge during the process of operation. The experimental research indicates that the simulation test unit satisfies the design requirements, achieving an average total dust removal efficiency of 99.93%. A field application shows that the total dust mass concentration at the operator position can be reduced from 335.8 mg∙m-3 to 4.2 mg∙m-3, effectively improving the operating environment within the tunnel.

Spatiotemporal change characteristics of vegetation coverage in Shangwan Mine of China's Shendong Mining Area.

The coal mining might cause the disturbance to the vegetation and the disturbance impacts might exist the differences for different areas, and few literatures compared and analyzed different disturbed areas based on the location of the mining face, and paid attention to the post mining self-healing effects of vegetation. Here, this paper selected the GaoFen multispectral images during 2017-2021 to study different areas of Shangwan Mine which includes the old mining area more than 5 years after mining, the new working face underground mined in 2018 and 2019, the natural growth control area and the open-pit mining affected area. The spatiotemporal changes of the surface fraction vegetation coverage (FVC) were analyzed in each area and the correlation between vegetation coverage and climatic factors was studied. The results showed that: (1) The overall vegetation coverage showed a moderate decrease trend in fluctuation from 2017 to 2021. The Open-pit mining affected areas showed the largest decline, reaching 68.3%. The FVC in the underground mining areas had a downward trend, but self-healing effect after mining was also observed. (2) The overall FVC in the study area was positively correlated with the number of precipitation days. (3) There were differences in the sensitivity to mining disturbance for different landform in the underground mining areas. (4) Although the FVC in the Old mining areas had recovered to the level of Natural growth control area, but the annual fluctuation was larger, which might mean lower ecological stability.

Environmental impact assessment of acidic coal gangue leaching solution on groundwater: a coal gangue pile in Shanxi, China.

With the continual advancement of coal resource development, the comprehensive utilization of coal gangue as a by-product encounters certain constraints. A substantial amount of untreated coal gangue is openly stored, particularly acidic gangue exposed to rainfall. The leaching effect of acidic solutions, containing heavy metal ions and other pollutants, results in environmental challenges such as local soil or groundwater pollution, presenting a significant concern in the current ecological landscape of mining areas. Investigating the migration patterns of pollutants in the soil-groundwater system and elucidating the characteristics of polluted solute migration are imperative. To understand the migration dynamics of pollutants and unveil the features of solute migration, this study focuses on a coal gangue dump in a mining area in Shanxi. Utilizing indoor leaching experiments and soil column migration experiments, a two-dimensional soil-groundwater model is established using the finite element method of COMSOL. This model quantitatively delineates the migration patterns of key pollutant components leached from coal gangue into the groundwater. The findings reveal that sulfate ions can migrate and infiltrate groundwater within a mere 7 years in the vadose zone of aeration. Moreover, the average concentration of iron ions in groundwater can reach approximately 58.3 mg/L. Convection, hydrodynamic dispersion, and adsorption emerge as the primary factors influencing pollution transport. Understanding the leaching patterns and environmental impacts of major pollutants in acidic coal gangue is crucial for predicting soil-groundwater pollution and implementing effective protective measures.

Spatial and temporal distribution characteristics and risk assessment of heavy metals in groundwater of Pingshuo mining area.

Groundwater pollution in the Pingshuo mining area is strongly associated with mining activities, with heavy metals (HMs) representing predominant pollutants. To obtain accurate information about the pollution status and health risks of groundwater, 189 groups of samples were collected from four types of groundwater, during three periods of the year, and analyzed for HMs. The results showed that the concentration of HMs in groundwater was higher near the open pit, waste slag pile, riverfront area, and human settlements. Except for Ordovician groundwater, excessive HMs were found in all investigated groundwater of the mining area, as compared with the standard thresholds. Fe exceeded the threshold in 13-75% of the groundwater samples. Three sources of HMs were identified and quantified by Pearson's correlation analysis and the PMF model, including coal mining activities (68.22%), industrial, agricultural, and residential chemicals residue and leakage (16.91%), and natural sources (14.87%). The Nemerow pollution index revealed that 7.58% and 100% of Quaternary groundwater and mine water samples were polluted. The health risk index for HMs in groundwater showed that the non-carcinogenic health risk ranged from 0.18 to 0.42 for adults, indicating an acceptable level. Additionally, high carcinogenic risks were identified in Quaternary groundwater (95.45%), coal series groundwater (91.67%), and Ordovician groundwater (26.67%). Both carcinogenic and non-carcinogenic risks were greater for children than adults, highlighting their increased vulnerability to HMs in groundwater. This study provides a scientific foundation for managing groundwater quality and ensuring drinking water safety in mining areas.

Nutrient uptake efficiency and stoichiometry for different plant functional groups on spoil heap after hard coal mining in Upper Silesia, Poland.

Various plant functional groups (PFGs) used in the reclamation of post-mining heaps may differ in their nutrient uptake efficiency and thus in their effect on the ecosystem development. The effect of PFGs may be additionally modified by the applied reclamation measures such as e.g. topsoiling. In this study we compared the nutrient uptake efficiencies and plant stoichiometry for two PFGs (grasses and forbs) growing on the sites reclaimed by applying topsoil (TS) and unreclaimed sites on carboniferous bare rock (BR) in hard coal spoil heap in Upper Silesia (southern Poland). Basic soil parameters, including pH, texture, soil organic carbon, and nutrients (N, P, K, Ca, and Mg), were measured, and the aboveground plant biomass and nutrient content in plant tissue were determined. Forbs were characterized by a larger biomass and higher nutrient concentrations (except for P) than grasses. The TS treatment supported higher concentrations of N and P in plant tissues but not to the level ensuring more significant primary biomass production. The nutrient concentration and elemental stoichiometry in plant tissue indicated that N was the primary limiting element. However, the major growth limitation for N-fixing forbs was from P. Forbs were much more efficient in nutrient uptake than grasses, independent of the reclamation treatment. Therefore, they stimulate nutrient cycling in the restored ecosystems more than grasses.

Comprehensive insight into mercury contamination in atmospheric, terrestrial and aquatic ecosystems surrounding a typical antimony-coal mining district.

This study comprehensively investigated mercury (Hg) contents of various environmental compartments in a typical antimony-coal mining area with intensive industrial activities over the past 120 years to analyze Hg environmental behaviors and evaluate Hg risks. The total mercury (THg) contents in river water, sediments, soils, PM10, dust falls, vegetables and corns were 1.16 ± 0.63 µg/L, 2.01 ± 1.64 mg/kg, 1.87 ± 3.88 mg/kg, 7.87 ± 18.68 ng/m3, 13.01 ± 14.53 mg/kg, 0.30 ± 0.34 mg/kg and 3.11 ± 0.51 µg/kg, respectively. The δ202Hg values in soils and dust falls were - 1.58 ∼ 0.12‰ and 0.25 ∼ 0.30‰, respectively. Environmental samples affected by industrial activities in the Xikuangshan (XKS) presented higher THg and δ202Hg values. Binary mixing model proved that atmospheric deposition with considerable Hg deposition flux (0.44 ∼ 6.40, 3.12 ± 2.20 mg/m2/y) in the XKS significantly contributed to Hg accumulations on surface soils. Compared with soils, sediments with more frequent paths and higher burst probabilities presented higher dynamic Hg risks. Children were faced higher health risk of multiple Hg exposure than adults. Furthermore, the health risk of THg by consuming leaf vegetables deserved more attention. These findings provided scientific basis for managing Hg contamination.

Revealing soil microbial ecophysiological indicators in acidic environments laden with heavy metals via predictive modeling: Understanding the impacts of black diamond excavation.

Appraising the activity of soil microbial community in relation to soil acidity and heavy metal (HM) content can help evaluate it's quality and health. Coal mining has been reported to mobilize locked HM in soil and induce acid mine drainage. In this study, agricultural soils around coal mining areas were studied and compared to baseline soils in order to comprehend the former's effect in downgrading soil quality. Acidity as well as HM fractions were significantly higher in the two contaminated zones as compared to baseline soils (p < 0.01). Moreover, self-organizing and geostatistical maps show a similar pattern of localization in metal availability and soil acidity thereby indicating a causal relationship. Sobol sensitivity, cluster, and principal component analyses were employed to enunciate the relationship between the various metal and acidity fractions with that of soil microbial properties. The results indicate a significant negative impact of metal bioavailability, and acidity on soil microbial activity. Lastly, Taylor diagrams were employed to predict soil microbial quality and health based on soil physicochemical inputs. The efficiency of several machine learning algorithms was tested to identify Random Forrest as the best model for prediction. Thus, the study imparts knowledge about soil pollution parameters, and acidity status thereby projecting soil quality which can be a pioneer in sustainable agricultural practices.

Associations of coal mine dust exposure with arterial stiffness and atherosclerotic cardiovascular disease risk in chinese coal miners.

OBJECTIVE: Whether coal mine dust exposure increases cardiovascular diseases (CVDs) risk was rarely explored. Our objective was to examine the association between coal mine dust exposure and cardiovascular risk. METHODS: We estimated cumulative coal mine dust exposure (CDE) for 1327 coal miners by combining data on workplace dust concentrations and work history. We used brachial-ankle pulse wave velocity (baPWV, a representative indicator of arterial stiffness) and ten-year atherosclerotic cardiovascular disease (ASCVD) risk to assess potential CVD risk, exploring their associations with CDE. RESULTS: Positive dose-response relationships of CDE with baPWV and ten-year ASCVD risk were observed after adjusting for covariates. Specifically, each 1 standard deviation (SD) increase in CDE was related to a 0.27 m/s (95% CI: 0.21, 0.34) increase in baPWV and a 1.29 (95% CI: 1.14, 1.46) elevation in OR (odds ratio) of risk of abnormal baPWV. Moreover, each 1 SD increase in CDE was associated with a 0.74% (95% CI: 0.63%, 0.85%) increase in scores of ten-year ASCVD and a 1.91 (95% CI: 1.62, 2.26) increase in OR of risk of ten-year ASCVD. When compared with groups unexposed to coal mine dust, significant increase in the risk of arterial stiffness and ten-year ASCVD in the highest CDE groups were detected. CONCLUSION: The study suggested that cumulative exposure to coal mine dust was associated with elevated arterial stiffness and ten-year ASCVD risk in a dose-response manner. These findings contribute valuable insights for cardiovascular risk associated with coal mine dust.

Dynamics of carbon storage driven by land use/land cover transformation in coal mining areas with a high groundwater table: A case study of Yanzhou Coal Mine, China.

Intensive anthropogenic activities have led to drastic changes in land use/land cover (LULC) and impacted the carbon storage in high-groundwater coal basins. In this paper, we conduct a case study on the Yanzhou Coalfield in Shandong Province of China. We further classify waterbodies by using the Google Earth Engine (GEE) to better investigate the process of LULC transformation and the forces driving it in four periods from 1985 to 2020 (i.e., 1985-1995, 1995-2005, 2005-2015, and 2015-2020). We modeled the spatiotemporal dynamics of carbon storage by using InVEST based on the transformation in LULC and its drivers, including mining (M), reclamation (R), urbanization and village relocation (U), and ecological restoration (E). The results indicate that carbon storage had depleted by 19.69 % (321099.06 Mg) owing to intensive transformations in LULC. The area of cropland shrank with the expansion of built-up land and waterbodies, and 56.31 % of the study area underwent transitions in land use in the study period. U was the primary driver of carbon loss while E was the leading driver of carbon gain. While the direct impact of M on carbon loss accounted for only 5.23 % of the total, it affected urbanization and led to village relocation. R led to the recovery of cropland and the reclamation of water for aquaculture, which in turn improved the efficiency of land use. However, it contributed only 2.09 % to the total increase in carbon storage. Numerous complicated and intertwined processes (211) drove the changes in carbon storage in the study area. The work here provides valuable information for decision-makers as well as people involved in reclamation and ecological restoration to better understand the link between carbon storage and the forces influencing it. The results can be used to integrate the goals of carbon sequestration into measures for land management.

Calculation and program realization of coal pillar setting parameters in Huainan mining area.

Coal pillar retention plays a crucial role in ensuring safety and minimizing ground deformation in coal mining operations. However, accurately and efficiently determining the optimal size of protective pillars, reducing coal pillar pressure, and addressing challenges such as limited access to retention parameters, lengthy observation times, and high labor costs are challenges that must be addressed. In this paper, we presented a methodology using Huainan mine as a case study to address these challenges. The solution involves deriving the formula for coal pillar retention parameters based on the Three Regulations definition and requirements. The total least squares algorithm was integrated with surface observation station data and the MATLAB software platform to automate the coal pillar retention solution. Furthermore, a linear regression model of coal pillar retention-related parameters was established using the geological mining condition data. The proposed ELM neural network model was optimized using a genetic algorithm and combined with the linear regression model to establish a predictive model. The results demonstrated that the proposed machine learning algorithm attains the requisite level of accuracy for industrial production.