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PloS One 2022Investigating the division of coal spontaneous combustion stages and the selection of indicator gases is significant to the safe production of coal mines. In this study,...
Investigating the division of coal spontaneous combustion stages and the selection of indicator gases is significant to the safe production of coal mines. In this study, the characteristic temperature of coal spontaneous combustion, the generation law of indicator gases, the combustion process, and the division of the combustion stages of coal samples taken from Hongqingliang (HQL) and Dayan (DY) mines were investigated using thermogravimetric analysis experiment, indicator gas detection experiment, and coal oxidation spontaneous combustion experiment. The results of the thermogravimetric analysis experiment showed that the pyrolysis temperatures of the HQL and DY coals were 115.76°C and 131.80°C, and the ignition temperatures were 337.74°C and 360.18°C, respectively. The indicator gas detection results showed that the first-appearance temperature of C2H4 was 85°C for the HQL and DY coals, whereas the first-appearance temperature of C2H6 varied: 115°C for the HQL coal and 130°C for the DY coal. The first-appearance temperatures of C2H2 were 180°C and 195°C for the HQL and DY coals, respectively. The experiments on coal oxidation spontaneous combustion showed that the spontaneous combustion period of the HQL and DY coals were 35.45 and 42.3 days, respectively. The heating process during combustion could be divided into four stages: a latent period of spontaneous combustion, a slow spontaneous heating period, an accelerated spontaneous heating period, and a period of combustion. The critical temperature of each stage showed a good correlation with the incipient temperature of the indicator gases, namely C2H2, C2H4, and C2H6, and the appearance of the above gases can be used to characterize the degree of spontaneous combustion of coal.
Topics: Coal; Gases; Oxidation-Reduction; Spontaneous Combustion; Temperature
PubMed: 35476715
DOI: 10.1371/journal.pone.0267479 -
North Carolina Medical Journal 2018In North Carolina, coal-burning power plants remain the major source of electrical production. Coal burning generates coal ash that is stored in landfills and slurry... (Review)
Review
In North Carolina, coal-burning power plants remain the major source of electrical production. Coal burning generates coal ash that is stored in landfills and slurry ponds that are often located near residential communities, signifying high potential for environmental contamination and increasing health risks. We reviewed the literature on potential health effects of coal-burning plants to summarize current knowledge on health risks. We searched English-language publications issued between January 1, 1987, and December 31, 2017, on PubMed and Google Scholar. The algorithm of identification, screening, eligibility, and inclusion/exclusion we used provided 113 peer-reviewed publications selected for the review. Over the past 30 years, scientists reported that the people living in close proximity to coal-fired plants had higher rates of all-cause and premature mortality, increased risk of respiratory disease and lung cancer, cardiovascular disease, poorer child health, and higher infant mortality. The elevated health risk was associated with exposure to air pollutants from the power plant emissions and to a spectrum of heavy metals and radioactive isotopes in coal ash. In North Carolina, further studies are required to profile the severity of the cumulative impacts of multiple air, water, and soil contaminants related to coal-burning power plants and coal ash impoundments on human health and the environment. Prioritized study directions on evaluation of health impacts of coal-burning power plants in North Carolina are suggested.
Topics: Coal; Coal Ash; Environmental Health; Environmental Pollution; Humans; Power Plants; Residence Characteristics
PubMed: 30228133
DOI: 10.18043/ncm.79.5.289 -
Journal of Exposure Science &... Jan 2022Coal-fired power plants are a major source of air pollution that can impact children's health. Limited research has explored if proximity to coal-fired power plants...
BACKGROUND
Coal-fired power plants are a major source of air pollution that can impact children's health. Limited research has explored if proximity to coal-fired power plants contributes to children's neurobehavioral disorders.
OBJECTIVE
This community-based study collected primary data to investigate the relationships of residential proximity to power plants and neurobehavioral problems in children.
METHODS
235 participants aged 6-14 years who lived within 10 miles of two power plants were recruited. Exposure to particulate matter ≤10 μm (PM) was measured in children's homes using personal modular impactors. Neurobehavioral symptoms were assessed using the Child Behavior Checklist (CBCL). Multiple regression models were performed to test the hypothesized associations between proximity/exposure and neurobehavioral symptoms. Geospatial statistical methods were used to map the spatial patterns of exposure and neurobehavioral symptoms.
RESULTS
A small proportion of the variations of neurobehavioral problems (social problems, affective problems, and anxiety problems) were explained by the regression models in which distance to power plants, traffic proximity, and neighborhood poverty was statistically associated with the neurobehavioral health outcomes. Statistically significant hot spots of participants who had elevated levels of attention deficit hyperactivity disorder, anxiety, and social problems were observed in the vicinity of the two power plants.
SIGNIFICANCE
Results of this study suggest an adverse impact of proximity to power plants on children's neurobehavioral health. Although coal-fired power plants are being phased out in the US, health concern about exposure from coal ash storage facilities remains. Furthermore, other countries in the world are increasing coal use and generating millions of tons of pollutants and coal ash. Findings from this study can inform public health policies to reduce children's risk of neurobehavioral symptoms in relation to proximity to power plants.
Topics: Adolescent; Air Pollutants; Air Pollution; Child; Child Behavior Disorders; Child Health; Coal; Coal Ash; Humans; Power Plants
PubMed: 34257388
DOI: 10.1038/s41370-021-00369-7 -
Australian and New Zealand Journal of... Apr 2014
Topics: Australia; Coal; Coal Mining; Forecasting; Greenhouse Effect; Humans; Public Health
PubMed: 24690044
DOI: 10.1111/1753-6405.12215 -
International Journal of Environmental... Oct 2022Coal and gas outbursts seriously threaten the mining safety of deep coal mines. The evaluation of the risk grade of these events can effectively prevent the occurrence...
Coal and gas outbursts seriously threaten the mining safety of deep coal mines. The evaluation of the risk grade of these events can effectively prevent the occurrence of safety accidents in deep coal mines. Characterized as a high-dimensional, nonlinear, and small-sample problem, a risk evaluation method for deep coal and gas outbursts based on an improved quantum particle swarm optimization support vector machine (IQPSO-SVM) was constructed by leveraging the unique advantages of a support vector machine (SVM) in solving small-sample, high-dimension, and nonlinear problems. Improved quantum particle swarm optimization (IQPSO) is used to optimize the penalty and kernel function parameters of SVM, which can solve the optimal local risk and premature convergence problems of particle swarm optimization (PSO) and quantum particle swarm optimization (QPSO) in the training process. The proposed algorithm can also balance the relationship between the global search and local search in the algorithm design to improve the parallelism, stability, robustness, global optimum, and model generalization ability of data fitting. The experimental results prove that, compared with the test results of the standard SVM, particle swarm optimization support vector machine (PSO-SVM), and quantum particle swarm optimization support vector machine (QPSO-SVM) models, IQPSO-SVM significantly improves the risk assessment accuracy of coal and gas outbursts in deep coal mines. Therefore, this study provides a new idea for the prevention of deep coal and gas outburst accidents based on risk prediction and also provides an essential reference for the scientific evaluation of other high-dimensional and nonlinear problems in other fields. This study can also provide a theoretical basis for preventing coal and gas outburst accidents in deep coal mines and help coal mining enterprises improve their safety management ability.
Topics: Algorithms; Coal; Risk Assessment; Support Vector Machine
PubMed: 36232168
DOI: 10.3390/ijerph191912869 -
Molecules (Basel, Switzerland) Oct 2020This study examines how the several major industries, associated with a carbon artifact production, essentially belong to one, closely knit family. The common parents... (Review)
Review
This study examines how the several major industries, associated with a carbon artifact production, essentially belong to one, closely knit family. The common parents are the geological fossils called petroleum and coal. The study also reviews the major developments in carbon nanotechnology and electrocatalysis over the last 30 years or so. In this context, the development of various carbon materials with size, dopants, shape, and structure designed to achieve high catalytic electroactivity is reported, and among them recent carbon electrodes with many important features are presented together with their relevant applications in chemical technology, neurochemical monitoring, electrode kinetics, direct carbon fuel cells, lithium ion batteries, electrochemical capacitors, and supercapattery.
Topics: Carbon; Coal; Electrodes; Nanotechnology; Petroleum
PubMed: 33126632
DOI: 10.3390/molecules25214996 -
PloS One 2023Aiming at the problems of low accuracy of coal gangue recognition and difficult recognition of mixed gangue rate, a coal rock recognition method based on modal fusion of...
Aiming at the problems of low accuracy of coal gangue recognition and difficult recognition of mixed gangue rate, a coal rock recognition method based on modal fusion of RGB and infrared is proposed. A fully mechanized coal gangue transportation test bed is built, RGB images are obtained by camera, and infrared images are obtained by industrial microwave heating system and infrared thermal imager. the image data of the whole coal, whole gangue, and coal gangue with different gangue mixing as training and test samples, identify the released coal gangue and its mixing rate. The AlexNet, VGG-16, ResNet-18 classification networks and their convolutional neural networks with modal feature fusion are constructed. results: The classification accuracy of ResNet networks on RGB and infrared image data is higher than AlexNet and VGG-16 networks. The early convergence network performance of ResNet is verified through the convergence of different models. The recognition rate of the network is 97.92 the confusion matrix statistics, which verifies the feasibility of the application of modal fusion method in the field of coal gangue recognition. The fusion of modal features and early models of ResNet coal gangue, which is the basic premise for realizing intelligent coal caving.
Topics: Coal; Neural Networks, Computer
PubMed: 36758046
DOI: 10.1371/journal.pone.0281397 -
Scientific Reports Jul 2022The slip and instability mechanisms of coal-rock parting-coal structures under uniaxial loading conditions were investigated using experiments and case verification. The...
The slip and instability mechanisms of coal-rock parting-coal structures under uniaxial loading conditions were investigated using experiments and case verification. The slip and the corresponding precursors were described by monitoring the displacement, strain, and acoustic emissions (AEs) of coal and rock parting blocks during testing, and the experimental results were verified by analyzing the microseismic (MS) effects during the working face advancing in a coal seam bifurcation area. The main conclusions were as follows: (1) each slip of the discontinuities sandwiched between coal and rock parting produced shear and tensile cracks, but the shear cracks was dominant; (2) for the instability mode that was characterized by low peak stress, high energy release, and a stable b value of AE, each slip corresponds to a peak frequency of AE, which can reveal the final instability mode; (3) the sudden drop in the fault total area of AE can be regarded as a precursor for the warning fracture or slip instability of a discontinuity; and (4) the MS events in the coal seam bifurcation area were mainly characterized by a wide frequency and high amplitude, especially near the coal bifurcation line, where there were obvious characteristics of low-frequency shear fracture for the MS events. This study is relevant for the early warning of coal-rock dynamic disasters triggered by the slip, fracture, and instability of coal-rock parting compound structures in coal mines.
Topics: Acoustics; Coal
PubMed: 35840759
DOI: 10.1038/s41598-022-15738-x -
Philosophical Transactions. Series A,... Apr 2022Malaysia is a net importer of coal, petroleum products and piped natural gas. Moreover, its primary energy supply is dominated by fossil fuels, at about 93% in total,... (Review)
Review
Malaysia is a net importer of coal, petroleum products and piped natural gas. Moreover, its primary energy supply is dominated by fossil fuels, at about 93% in total, with coal and natural gas constituting the highest shares in electricity generation. Thus, there is need for Malaysia to take swift action in transitioning to a high renewable energy system for long-term sustainability and meeting its climate action commitment under the Paris Agreement. A net-zero emissions vision guided by a roadmap may effectively motivate and catalyse carbon-free energy deployments. In this paper, we revisit the carbon-free energy roadmap that was developed in 2015 and compare it with the current generation development plan to identify the gaps between them. We argue that the roadmap is still relevant to the net-zero emissions vision; however, we have also identified gaps that merit further research and improvement. The identified gaps mainly relate to more recent data, along with technology and policy developments. Accordingly, we put forward potential research suggestions to bridge these gaps for future development of a roadmap that would assist Malaysia in shaping a long-term plan towards realizing a high renewable net-zero power generation system. This article is part of the theme issue 'Developing resilient energy systems'.
Topics: Carbon Dioxide; Coal; Electricity; Fossil Fuels; Malaysia; Renewable Energy
PubMed: 35220765
DOI: 10.1098/rsta.2021.0132 -
International Journal of Environmental... May 2022Soil pollution in coal mining areas is a serious environmental problem in China and elsewhere. In this study, surface and vertical profile soil samples were collected...
Soil pollution in coal mining areas is a serious environmental problem in China and elsewhere. In this study, surface and vertical profile soil samples were collected from a coal mine area in Dazhu, Southwestern China. Microscopic observation, concentrations, chemical speciation, statistical analysis, spatial distribution, and risk assessment were used to assess heavy metal pollution. The results show that the weathering of coal-bearing sandstone and mining activities substantially contributed to soil pollution. The concentrations of Fe, Ni, Cu, Zn, Mn, Cd, Hg, and Pb exceeded their background values. Cd caused the most intense pollution and was associated with heavily-extremely contaminated soils. The residual fraction was dominant for most metals, except Cd and Mn, for which the reducible fraction was dominant (Cd: 55.17%; Mn: 81.16%). Zn, Ni, Cd, and Cu presented similar distribution patterns, and Hg and As also shared similar distribution characteristics. Factor 1 represented anthropogenic and lithologic sources, which were affected by mining activities; Factor 2 represented anthropogenic sources, e.g., fertilizers and traffic pollution; and Factor 3 represented the contribution of metals from soil-forming parent material. More than half of the study area had high pollution risk and was not suitable for vegetable cultivation.
Topics: Cadmium; China; Coal; Coal Mining; Environmental Monitoring; Environmental Pollution; Mercury; Metals, Heavy; Risk Assessment; Soil; Soil Pollutants
PubMed: 35682077
DOI: 10.3390/ijerph19116493