Study on key grouting blocking parameters of gas drainage boreholes in soft coal seams.

The construction of gas extraction boreholes in soft coal seams is prone to collapse and deformation, and grouting reinforcement is one of the main methods to solve the problem of efficient sealing. However, the reasonable selection of key grouting parameters still needs further research. In response to the problem of selecting grouting sealing parameters for gas drainage drilling in soft coal seams, based on the "concentric ring" reinforcement sealing technology obtained in previous research, the key parameters and sealing technology of the "concentric ring" reinforcement were studied through theoretical calculation and numerical simulation experiments. The slurry diffusion morphology and range under different grouting pressures and grouting time slurry viscosity were obtained. Finally, in order to explore the application effect of key grouting parameters, on-site industrial tests were conducted in a soft and high gas coal seam. The research results indicate that the optimal grouting pressure for the "retaining wall rock hole ring" should not be less than 3 MPa, the reasonable grouting time should be 10-15 min, and the water material ratio of the grouting material should be greater than 1:1; The use of new reinforcement sealing and grouting technology can ensure long-term good extraction effect. Compared to the testing of drilling sealing effect using ordinary cloth bags with two plugs and one injection, The adoption of new reinforcement sealing technology can effectively prevent the deformation and collapse of the borehole before sealing, and due to two rounds of grouting and pre reinforcement of fractured coal, the sealing effect of the borehole is also relatively good. The research results have important theoretical value for guiding the drilling and sealing grouting engineering of gas extraction in soft coal seams.

Pyrolysis and combustion of industrial hemp, coal and their blends for thermal analysis by thermogravimetric analysis/Fourier transform infrared spectrometer.

In this study, the thermal behaviours of Cannabis sativa (CS), coal and their five different blends at a heating rate (ß) of 10, 20, 30, 40 and 50°C min-1; the synergistic effects between CS and coal; and the distribution of gases formed during pyrolysis and combustion were investigated by using the thermogravimetric analysis/Fourier transform infrared spectrometer (TGA/FTIR) integrated system. The TG and DTG curves showed that the thermal decomposition of pyrolysis and combustion of all feedstocks at all ß values had three main decomposition stages. The synergistic effect was observed for DTGmax, mass loss (ML), or final residue (FR) at least once at a given ß of each blend; and the synergy was more effective for DTGmax and ML in pyrolysis than in combustion, whereas the opposite was true for FR. The lowest emissions of CO2, CH4, NOx and SO2 except CO during pyrolysis occurred at the blend of 0% CS + 100% Coal. However, the highest emissions of CO, CH4, NOx and SO2 except CO2 during combustion were observed at the blend of 80% CS + 20% Coal. The emissions of CO, CO2, NOx and SO2 from all samples during pyrolysis were lower than that of combustion, indicating that pyrolysis can be preferred due to its lower emission to the environment. Different structural properties of CS, coal and their blends caused different thermal behaviours, synergistic effects and gas products during pyrolysis and combustion by TGA/FTIR, suggesting detailed further investigation for upper-scale pyrolysis and combustion applications.

Valorization of pyrolysis oils recycled from waste car tires as potential collector in coal flotation: Production, characterization, and collecting mechanism.

The present research study investigates the performance of pyrolysis oils recycled from waste tires as a collector in coal flotation. Three different types of pyrolysis oils (namely, POT1, POT2, and POT3) were produced through a two-step pressure pyrolysis method followed by an oil rolling process. The characteristics of POTs were adjusted using various oil-modifying additives such as mineral salts and organic solvents. The chemical structure of POTs was explored by employing necessary instrumental analysis techniques, including microwave-assisted acid digestion (MAD), inductively coupled plasma atomic emission spectroscopy (ICP-AES), Fourier-transform infrared spectroscopy (FT-IR), and gas chromatography-mass spectrometry (GC-MS). The collecting performance of POTs in coal flotation was evaluated using an experimental design based on Response Surface Methodology (RSM), considering the ash content and yield of the final concentrate. The effect of the type and dosage of POTs was evaluated in conjunction with other important operating variables, including the dosage of frother, dosage of depressant, and the type of coal. Results of POTs characterization revealed that the pyrolysis oils were a complex composition of light and heavy hydrocarbon molecules, including naphthalene, biphenyl, acenaphthylene, fluorene, and pyrene. Statistical analysis of experimental results showed that among different POTs, POT1 exhibited remarkable superiority, achieving not only a 15% higher coal recovery but also a 12% lower ash content. The outstanding performance of POT1 was attributed to its unique composition, which includes a concentrated presence of carbon chains within the optimal range for efficient flotation. Additionally, the FT-IR spectra of POT1 reveal specific functional groups, including aromatic and aliphatic compounds, greatly enhancing its interaction with coal surfaces, as confirmed by contact angle measurement. This research provides valuable insights into the specific carbon chains and functional groups that contribute to the effectiveness of POT as a collector, facilitating the optimization of coal flotation processes and underscoring the environmental advantages of employing pyrolysis oils as sustainable alternatives in the mining industry.

The role of afforestation with diverse woody species in enhancing and restructuring the soil microenvironment in polymetallic coal gangue dumps.

To elucidate the effects of long-term (20 years) afforestation with different woody plant species on the soil microenvironment in coal gangue polymetallic contaminated areas. This study analyzed the soil physicochemical properties, soil enzyme activities, soil ionophore, bacterial community structure, soil metabolite, and their interaction relationships at different vertical depths. Urease, sucrase, and acid phosphatase activities in the shallow soil layers increased by 4.70-7.45, 3.83-7.64, and 3.27-4.85 times, respectively, after the restoration by the four arboreal plant species compared to the plant-free control soil. Additionally, it reduced the content of available elements in the soil and alleviated the toxicity stress for Cd, Ni, Co, Cr, As, Fe, Cu, U, and Pb. After the long-term restoration of arboreal plants, the richness and Shannon indices of soil bacteria significantly increased by 4.77-23.81% and 2.93-7.93%, respectively, broadening the bacterial ecological niche. The bacterial community structure shaped by different arboreal plants exhibited high similarity, but the community similarity decreased with increasing vertical depth. Soils Zn, U, Sr, S, P, Mg, K, Fe, Cu, Ca, Ba, and pH were identified as important influencing factors for the community structure of Sphingomonas, Pseudarthrobacter, Nocardioides, and Thiobacillus. The metabolites such as sucrose, raffinose, L-valine, D-fructose 2, 6-bisphosphate, and oxoglutaric acid were found to have the greatest effect on the bacterial community in the rhizosphere soils for arboreal plants. The results of the study demonstrated that long-term planting for woody plants in gangue dumps could regulate microbial abundance and symbiotic patterns through the accumulation of rhizosphere metabolites in the soil, increase soil enzyme activity, reduce heavy metal levels, and improve the soil environment in coal gangue dumps.

Numerical simulation study on the evolution law of mechanical properties of different metamorphic coals after heat treatment.

In order to study the effect of temperature on the structure and mechanical properties of coal with different metamorphic degree. Three coal samples with varying degrees of metamorphism were chosen for analysis. The discrete element software PFC2D is used to simulate the heat treatment and compression of coal. The findings indicate that during the heating process, low-order coal exhibits noticeable thermal cracks at an early stage, while thermal crack development in middle-order coal is concentrated in the later stages. In contrast, high-order coal demonstrates a more stable macroscopic structure. The strength and stiffness of low rank coal show the lowest value and decrease significantly within 135 °C. However, the strength and stiffness of medium rank coal decrease significantly after 135 °C. The changes of mechanical properties and damage modes of coal caused by thermal damage are often ignored, which may lead to the deviation of design and research results from the actual situation. Therefore, this study is of great significance to the prevention and control of coal mine disasters.

Hydrothermal Synthesis of Cancrinite from Coal Gangue for the Immobilization of Sr.

The primary objective of this study is to investigate and develop a rapid and effective method for the immobilization of Sr in the event of a nuclear leakage incident. Coal gangue, an underutilized form of solid waste from the coal industry, can be used as a raw material for curing Sr due to its high content of silica-alumina oxides. In the present study, Sr was successfully solidified in cancrinite synthesized using a hydrothermal method with coal gangue as raw material. A stable cancrinite phase was formed at a relative alkali concentration of more than 6 M. When the Sr/Al(Si) ratio was <1/6, cancrinite was the only stable phase that varied with the hydrothermal temperature and time. When the Sr/Al(Si) ratio increased to 1/2, the cancrinite phase completely disappeared, and a new strontium feldspar phase (SrAl2Si2O8) appeared. PCT leaching experiments showed that when Sr/Al(Si) < 1/6, the Sr leaching rate of Sr-cancrinite samples obtained by hydrothermal synthesis at 180 °C for 24 h was very low.

Selenium-modified activated coke: a high-capacity and facile designed Hg0 adsorbent for coal-fired flue gas.

The substantial amount of mercury emissions from coal-fired flue gas causes severe environmental contamination. With the Minamata Convention now officially in force, it is critical to strengthen mercury pollution control. Existing activated carbon injection technologies suffer from poor desulfurization performance and risk secondary-release risks. Therefore, considering the potential industrial application of adsorbents, we selected cost-effective and readily available activated coke (AC) as the carrier in this study. Four metal selenides-copper, iron, manganese, and tin-were loaded onto the AC to overcome the application problems of existing technologies. After 120 min of adsorption, the CuSe/AC exhibited the highest efficiency in removing Hg0, surpassing 80% according to the experimental findings. In addition, the optimal adsorption temperature window was 30-120 °C, the maximum adsorption rate was 2.9 × 10-2 mg·g-1·h-1, and the effectiveness of CuSe/AC in capturing Hg0 only dropped by 5.2% in the sulfur-containing atmosphere. The physicochemical characterization results indicated that the AC surface had a uniform loading of CuSe with a nanosheet structure resembling polygon and that the Cu-to-Se atomic ratio was close to 1:1. Finally, two possible Hg0 reaction pathways on CuSe/AC were proposed. Moreover, it was elucidated that the highly selective binding of Hg0 with ligand-unsaturated Se- was the key factor in achieving high adsorption efficiency and sulfur resistance in the selenium-functionalized AC adsorbent. This finding offers substantial theoretical support for the industrial application of this adsorbent.

Impact of long-term mining activity on groundwater dynamics in a mining district in Xinjiang coal Mine Base, Northwest China: insight from geochemical fingerprint and machine learning.

Long-term coal mining could lead to a serious of geo-environmental problems. However, less comprehensive identification of factors controlling the groundwater dynamics were involved in previous studies. This study focused on 68 groundwater samples collected before and after mining activities, Self-Organizing Maps (SOM) combining with Principal Component Analysis (PCA) derived that the groundwater samples were classified into five clusters. Clusters 1-5 (C1-C5) represented the groundwater quality affected by different hydrochemical processes, mainly including mineral (carbonate and evaporite) dissolution and cation exchange, which were controlled by the hydrochemical environment at different stages of mining activities. Combining with the time-series data, the Extreme Gradient Boosting Decision Trees (XGBoost) derived that the mine water inflow (feature relative importance of 40.0%) and unit goaf area (feature relative importance of 29.2%) were dominant factors affecting the confined groundwater level, but had less or lagged impact on phreatic groundwater level. This was closely related to the height of the water flow fractured zone and hydraulic connection between aquifers. The results of this study on the coupled evolution of groundwater dynamics could enhance our understanding of the effects of mining on aquifer systems and contribute to the prevention of water hazards in the coalfields.

Distribution, occurrence, and leachability of typical heavy metals in coal gasification slag.

Coal gasification slag (CGS) contains variable amounts of heavy metals, which can negatively impact the environment. The mineral composition, element distribution, occurrence, and leaching characteristics of heavy metals in coal gasification coarse slag (CGCS) and coal gasification fine slag (CGFS) are studied to explain the leaching behavior of heavy metals in CGS. The movable components of heavy metals in CGFS (0.06 %-63.03 %) are significantly higher than those in CGCS (0 %-18.72 %). Leaching Environmental Assessment Framework 1313 data shows that heavy metals Zn, Cr, Cd, As, Pb, Ni, and Cu exhibit high leaching rates at low pH conditions, with Zn leaching concentrations as high as 2.11 mg/L at pH 2. Zn, Cr, and As exhibit obvious amphoteric leaching characteristics, and the leaching concentration of As at high pH (1.34 mg/L) even exceeds that at low pH (1.31 mg/L). Except for Cu, all heavy metals in CGS exceed the class III groundwater standard in some cases. Therefore, evaluation is needed before resource utilization of CGS due to potential leaching of some heavy metals.

Ecological risk assessment of heavy metals in desulfurized seawater discharged from a coal-fired power plant in Qingdao.

Despite the prevalence of discharge of large volumes of heavy-metal-bearing seawater from coal-fired power plants into adjacent seas, studies on the associated ecological risks remain limited. This study continuously monitored concentrations of seven heavy metals (i.e. As, Cd, Cr, Cu, Hg, Pb, and Zn) in surface seawater near the outfall of a coal-fired power plant in Qingdao, China over three years. The results showed average concentrations of As, Cd, Cr, Cu, Hg, Pb, and Zn of 2.63, 0.33, 2.97, 4.63, 0.008, 0.85, and 25.00 µg/L, respectively. Given the lack of data on metal toxicity to local species, this study investigated species composition and biomass near discharge outfalls and constructed species sensitivity distribution (SSD) curves with biological flora characteristics. Hazardous concentrations for 5% of species (HC5) for As, Cd, Cr, Cu, Hg, Pb, and Zn derived from SSDs constructed from chronic toxicity data for native species were 3.23, 2.22, 0.06, 2.83, 0.66, 4.70, and 11.07 µg/L, respectively. This study further assessed ecological risk of heavy metals by applying the Hazard Quotient (HQ) and Joint Probability Curve (JPC) based on long-term heavy metal exposure data and chronic toxicity data for local species. The results revealed acceptable levels of ecological risk for As, Cd, Hg, and Pb, but unacceptable levels for Cr, Cu, and Zn. The order of studied heavy metals in terms of ecological risk was Cr > Cu ≈ Zn > As > Cd ≈ Pb > Hg. The results of this study can guide the assessment of ecological risk at heavy metal contaminated sites characterized by relatively low heavy metal concentrations and high discharge volumes, such as receiving waters of coal-fired power plant effluents.

An efficient method of preparing Si-Fe-Al-Ca alloy from coal gasification fine slag via plasma smelting and alternating current magnetic field.

It is of great significance to solve the environmental problems caused by the unreasonable treatment of coal gasification slag. This study successfully produced Si-Fe-Al-Ca alloy from low-carbon fine slag with petroleum coke as reducing agent in a plasma furnace with an alternating current magnetic field, which solved the problem of the high reactivity requirement of carbon reductant for plasma smelting. The optimum carbon content of the mixed low-carbon fine slag and petroleum coke is 105% of the theoretical value. As the strength of the alternating current magnetic field increased (from 0% to 100% of the maximum power), the yield of the alloy (from 25.46% to 58.19%) and the recovery ratios of each element (Si, Fe, Al, Ca, Ti) increased. In addition, as the magnetic field strength increased, the pores inside the alloy became smaller, the composition of the alloy became more homogeneous, and a better separation of the alloy from the slag was observed. The main composition of the alloy at the strongest alternating current magnetic field is Si: 51.14 wt%, Fe: 28.41 wt%, Al: 9.14 wt%, Ca: 7.15 wt%, Ti: 2.03 wt%. We attribute the enhanced smelting effect of the alternating current magnetic field to the resistive heat and Lorentz force produced by the induced current. In addition, the skin effect concentrated the induced current on the surface of the oxide particles and carbon particles, which increased the temperature of the reaction interface and promoted the carbothermal reduction reaction.

Coal-Derived Humic Substances: Insight into Chemical Structure Parameters and Biomedical Properties.

An investigation was carried out on humic substances (HSs) isolated from the coal of the Kansk-Achinsk basin (Krasnoyarsk Territory, Russia). The coal HSs demonstrate the main parameters of molecular structure inherent to this class of natural compounds. An assessment was performed for the chemical, microbiological, and pharmacological safety parameters, as well as the biological efficacy. The HS sample meets the safety requirements in microbiological purity, toxic metals content (lead, cadmium, mercury, arsenic), and radionuclides. The presence of 11 essential elements was determined. The absence of general, systemic toxicity, cytotoxicity, and allergenic properties was demonstrated. The coal HS sample was classified as a Class V hazard (low danger substances). High antioxidant and antiradical activities and immunotropic and cytoprotective properties were identified. The ability of the HS to inhibit hydroxyl radicals and superoxide anion radicals was revealed. Pronounced actoprotective and nootropic activities were also demonstrated in vivo. Intragastric administration of the HS sample resulted in the improvement of physical parameters in mice as assessed by the "swim exhaustion" test. Furthermore, intragastric administration in mice with cholinergic dysfunction led to a higher ability of animals with scopolamine-induced amnesia to form conditioned reflexes. These findings suggest that the studied HS sample is a safe and effective natural substance, making it suitable for use as a dietary bioactive supplement.

Chemical inertness conversion of carbon fraction in coal gangue via N-doping for efficient benzo(a)pyrene degradation.

Efficient degradation of organic pollutants in complex media via advanced oxidation processes (AOPs) is still critical and challenging. Herein, nitrogen (N)-doped coal gangue (CG) catalysts (N-CG) with economic competitiveness and environmental friendliness were successfully synthesized to activate peroxymonosulfate (PMS), exhibiting ultrafast degradation performance toward benzo(a)pyrene (BaP) with 100.00 % and 93.21 % in contaminated solution and soil under optimized condition, respectively. In addition, 0.4 N-CG possessed excellent reusability toward BaP degradation with over 80.00 % after five cycles. However, BaP removal efficiency was significantly affected by some co-existing anions (HCO3- and SO42-) and humic acid (HA) in solution and soil, as well as inhibited under alkaline conditions, especially pH ≥ 9. According to the characterizations, N-doping could promote the generation of pyridinic N and graphitic N in N-CG via high-temperature calcination, which was conducive to produce hydroxyl radical (•OH), sulfate radical (SO4•-), superoxide radical (•O2-) and single oxygen (1O2). In 0.4 N-CG/PMS system, 1O2 and •O2- were proved to be the predominant reactive oxygen species (ROSs) in BaP degradation, as well as •OH and SO4•- made certain contributions. To sum up, this work provided a promising strategy for synthesis of CG-based catalysts by chemical inertness conversion of carbon fracture via N-doping for PMS activation and opened a novel perspective for environmental remediation of hydrophobic and hydrophilic contaminants pollution.

Investigation on the interaction mechanism during co-combustion of sewage sludge and coal slime: The effect of coal slime type and pretreatment method.

Co-combustion of sewage sludge (SS) and coal slime (CS) is the preferred method for mitigating their environmental impact and increasing their added value. However, the interaction mechanism between SS and CS during the co-combustion process has not yet developed a unified understanding. This work aims to obtain the effect of CS types on SS-CS co-combustion and reveal the interaction mechanism between SS and CS based on the influence of pretreatment methods on the interaction. The results showed that during co-combustion, SS reduced the ignition and burnout temperatures, and CS with high fixed carbon content (e.g., XCS) improved the comprehensive combustion characteristics. Principal component analysis showed that the effect of CS on co-combustion was more significant. The interaction between SS and CS mainly occurred within 100-700 °C, in which inhibition and synergism coexisted. The large differences in the interactions before and after de-volatilization and pickling treatments revealed that the volatiles and ash in SS were the main interaction factors. The analysis of the interaction mechanisms showed that the free radicals and heat released from the SS volatiles combustion accelerated the weight loss of CS, but the formation of tars from its incomplete combustion may inhibit the decomposition of CS. The interaction in the fixed carbon combustion stage was mainly caused by SS ash, which can catalyze the combustion of CS fixed carbon, but for the high ash CS (e.g., QCS), the combustion of fixed carbon was hindered by the addition of SS ash higher than 10 %. The final manifestation (synergy or inhibition) of SS and CS interactions was the result of the competitive balance of the above interactive behaviors. This work provides a more comprehensive understanding of the interaction between SS and CS during co-combustion.

Optimizing coal mine planning and design for sustainable development in the context of mass exploitation of coal deposits.

Sustainable mining practices is a concept that embeds the principles of sustainable development into the whole mine life-cycle, from exploration, extraction and processing through to mine closure. The optimization of coal mine planning and the developing a standardized design for its sustainable development is very challenging and requires more effort. The present research attempts to address the conditions of sustainability and necessary measures for sustainable development, thereby providing appropriate solutions for each stage of mining operation besides expressing the necessity of sustainable development integration at different stages of mining life cycle (MLC). The approach of systems engineering is essential to assist the sustainability goals which are integrated with the expected results. Hence a method depending more on systems engineering principles and optimization can be incorporated to attain better results. Several socio-environmental factors associated with sustainability depends on the geographic condition and few mining engineering considerations such as mine location, topography, coal seam characteristics and so on. These systems engineering approach can be further enhanced by incorporating tools like Geographic Information System (GIS), which provides more accuracy and precision of the geographic conditions of the site identified for the coal mining plan. In order to begin this way of approach towards the sustainability development and mining planning, the appropriate optimization parameters should be identified. The outcome of these optimization parameters can be also achieved by optimizing coal mining system models.

Research on long-term migration behaviors of heavy metals after close-distance coal seam backfill mining.

The backfill mining of coal-based solid waste in goaf poses a potential risk of heavy metal pollution to the groundwater environment, and the migration behavior of heavy metals differs significantly under the disturbance of backfill mining in close-distance multi-layer coal seams and single-layer coal seams. In this study, a migration model of heavy metals after solid backfilling in the goaf of shallow-buried close-distance thick coal seams was established, and the impact of the overburden damage and the layered distribution of the filling body on the long-term migration behavior of heavy metals were analyzed. The results show that the migration of heavy metals after close-distance coal seam backfill mining exhibits a higher risk of heavy metal pollution. The peak permeability of overburden after close-distance coal seam backfill mining is about 600 × 10-19 m2 higher than that after single-layer coal seam backfill mining. The migration distance of heavy metals in the floor after backfill mining of close-distance coal seams is 7.41 m farther than that of single-layer coal seam backfill mining, and its migration time of heavy metals to the surface is 27 a earlier than that of single-layer coal seam. This research provides theoretical and empirical support for the ecological risk assessment and heavy metal pollution control in close-distance coal seam backfill mining. ENVIRONMENTAL IMPLICATION: The main filling material of close-distance coal seams backfill mining is coal gangue. Heavy metal elements such as Mn and Cr will be released in the underground environment for a long time, and the migration behavior of heavy metal elements will have an impact on the groundwater environment for more than 1000 years. This research provides theoretical and empirical support for the ecological risk assessment of close-distance coal seam backfill mining and the mitigation of heavy metal pollution.

Life cycle assessment of post-combustion carbon capture and storage for the ultra-supercritical pulverized coal power plant.

In this paper, different emerging post-combustion technologies, i.e., monoethanolamine (MEA), aqueous ammonia, pressure swing adsorption (PSA), temperature swing adsorption (TSA), membrane and calcium looping, were applied to an ultra-supercritical coal-fired power plant for carbon capture. A 'cradle-to-grave' life cycle assessment (LCA) was conducted to evaluate the technical performance and environmental impacts of the power plant with six emerging carbon capture technologies. Carbon capture significantly influences the impact categories directly associated with flue gas emission. The application of carbon capture reduced the GWP in the range of 49-75 %. TAP also reduced in the range of 18-51 %. However, the human toxicity potential, eutrophication potential, ecotoxicity potential and particulate matter formation potential increased due to energy and resource consumption in the upstream and downstream processes. For the life cycle water consumption potential, it decreased by 8 % with calcium looping, whereas it increased in the range of 36-75 % with other post-combustion technologies. The highest reduction in GWP and the least reduction in power efficiency was observed in calcium looping because of the high-temperature heat recovery from flue gas and elimination of complex solvent manufacturing. The plant with aqueous ammonia and membrane separation had the second and third highest reductions in GWP. In addition, the lowest values for TAP, FEP, and MEP were obtained in the membrane system. With MEA for CO2 capture, the total GWP value of the plant is slightly higher than these three technologies mentioned above, and the highest HTPc, FETP, and METP can be observed in this case. TSA and PSA have the most significant environmental impacts in most categories due to higher energy requirements.

Comprehensive effect of increased calcium content in coal on the selenium emission from coal-fired power plants: Combined laboratory and field experiments.

Coal combustion is the major contributor to global toxic selenium (Se) emissions. Inorganic elements in coals significantly affect Se partitioning during combustion. This work confirmed that the calcium (Ca) in ash had a stronger relationship with Se retention at 1300 °C than other major elements. Ca oxide chemically reacted with gaseous Se, and its sintering densification slightly affected Se adsorption capacities (44.45 -1840.71→35.17 -1540.15 mg/kg) at 300 - 1300 °C. Therefore, Ca in coals was identified as having potential for hindering gaseous Se emissions, and coals with increased Ca contents (2.74→5.19 wt%) were used in a 350 MW unit. The decreased Se mass distribution (3.54%→2.63%) in flue gas at air preheater inlet (320 -362 °C) confirmed the effectiveness of increased Ca content on gaseous Se emission reduction. More gaseous Se further condensed and was chemically adsorbed by fly ash when passed through an electrostatic precipitator, resulting in a significant increase in the Se content of fly ash. Additionally, the corresponding Se leaching ratio decreased from 4.88 - 35.74% to 1.87 - 26.31%, indicating enhanced stability of Se enriched in fly ash. This research confirmed the feasibility and environmental safety of sequestration of gaseous Se from flue gas to fly ash by increasing the Ca content in coals.

Leachability of hexavalent chromium from fly ash-marl mixtures in Sarigiol basin, Western Macedonia, Greece: environmental hazard and potential human health risk.

Hexavalent chromium (Cr (VI)) is an environmental contaminant brining high concerns due to its higher toxicity and mobility in comparison with trivalent chromium Cr(III). Cr (VI) has been linked with several adverse health effects, including respiratory diseases, lung cancer, and skin irritation. The primary sources of it in the environment are industrial activities.Most of the time, fly ash made of lignite can release Cr(VI) when it comes into contact with water in an aquatic environment. The objective of this study is the investigation of Cr (VI) concentration in leachates of fly ash and marl mixtures and the determination of its solubility under different pH conditions. Samples of fly ash were collected from the Power Plant of Agios Dimitrios. Additionally, samples of marl were collected from the mine of South Field, and both samples were mixed and prepared in in different proportions (% w.t.). The leaching experiments were carried out according to the EN-12457/1-4 (2003) standard under different pH conditions and chemical analysis of the leachates were performed by spectrophotometry with diphenylcarbazide (DPC). The environmental footprint of Cr (VI) in the study area was significant, especially in mixtures containing higher concentrations of fly ash. A critical pH range between 6 to 12 is observed. At acidic pH values, a high release of Cr (VI) was observed, while at the mentioned critical values (pH 10-12), a gradual decrease in its leachability was noticed. The high concentrations of Cr (VI) in the industrial area studied require immediate actions in terms of managing and limiting the potential hazardous impacts on the environment and by extension on the public health by developing appropriate prevention strategies.

Land subsidence prediction in coal mining using machine learning models and optimization techniques.

Land surface subsidence is an environmental hazard resulting from the extraction of underground resources. In underground mining, when mineral materials are extracted deep within the ground, the emptying or caving of the mined spaces leads to vertical displacement of the ground, known as subsidence. This subsidence can extend to the surface as trough subsidence, as the movement and deformation of the hanging-wall rocks of the mining stope propagate upwards. Accurately predicting subsidence is crucial for estimating damage and protecting surface buildings and structures in mining areas. Therefore, developing a model that considers all relevant parameters for subsidence estimation is essential. In this article, we discuss the prediction of land subsidence caused by the caving of a stop's roof, focusing on coal mining using the longwall method. The main aim of this research is to improve the accuracy of prediction models of land subsidence due to mining. For this purpose, we consider a total of 11 parameters related to coal mining, including mining thickness and depth (related to the deposit), as well as density, cohesion, internal friction angle, elasticity modulus, bulk modulus, shear modulus, Poisson's ratio, uniaxial compressive strength, and tensile strength (related to the overburden). We utilize information collected from 14 coal mines regarding mining and subsidence to achieve this. We then explore the prediction of subsidence caused by mining using the gene expression programming (GEP) algorithm, optimized through a combination of the artificial bee colony (ABC) and ant lion optimizer (ALO) algorithms. Modeling results demonstrate that combining the GEP algorithm with optimization based on the ABC algorithm yields the best subsidence prediction, achieving a correlation coefficient of 0.96. Furthermore, sensitivity analysis reveals that mining depth and density have the greatest and least effects, respectively, on land surface subsidence resulting from coal mining using the longwall method.