Effects of Lockdown due to the COVID-19 Pandemic on Air Quality at Latin America’s Largest Open-pit Coal Mine

Air quality in open - pit mines is the big concern relating to the occupational safety and healthy, as well as the surrounding environment. In the past years, management of the air quality in open - pit mines is challenge due to the limit of science and technology in the assessment of the effects of meteorological conditions and toxics in open - pit mines. Therefore, this study assessed the effects of meteorological conditions on the air quality in deep open - pit mines. The air velocity distribution and the dispersal mechanism of the air quality were evaluated at the Coc Sau open - pit coal mine (Vietnam) based on the measured and simulated datasets. Two fixed stations were set up in the ground to monitor the wind direction, wind speed and the temperature to evaluate the stable of the actual ozone layer based on the Pasquill ozone layer. The datasets were also used to analysis and 3D simulate to understand the air pollution mechanism in the Coc Sau open - pit coal mine. On the other hand, the change of the temperature in vertical was measured to determine the to determine the existence of a temperature inversion layer. It is considered as the main reason for the air quality reduction and the natural air circulation in deep open - pit mines. The findings indicated the existence of the temperature inversion layer and they are useful for proposing the artificial ventilation in deep open - pit mine, aiming to improve the air quality in open - pit mines. The 3D simulations also revealed that the high dust and gas concentrations in open - pit mines are due to the stable of the ozone layer.

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Key ecological aspects of coal mining technology (in terms of the Bureya open pit coal mine)

MINING INFORMATIONAL AND ANALYTICAL BULLETIN ◽

10.25018/0236-1493-2020-1-0-15-25 ◽

2020 ◽

Vol 1 ◽

pp. 15-25

Author(s):

Yu.A. Ozaryan ◽

◽

Yu.A. Vasyanovich ◽

Keyword(s):

Coal Mining ◽

Coal Mine ◽

Open Pit ◽

Mining Technology ◽

Ecological Aspects

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Assessment of the Underground Water Contaminated by the Leachate of Waste Dump of Open Pit Coal Mine Based on RBF Neural Network

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.599.272 ◽

2012 ◽

Vol 599 ◽

pp. 272-277 ◽

Cited By ~ 1

Author(s):

Zhi Bin Liu ◽

Xiao Wei Yang

Keyword(s):

Neural Network ◽

Network Model ◽

Neural Network Model ◽

Coal Mine ◽

Comprehensive Evaluation ◽

Rbf Neural Network ◽

Training Sample ◽

Underground Water ◽

Open Pit ◽

Waste Dump

This paper used RBF artificial neural network to evaluate the underground water contaminated by the leachate of waste dump of open pit coal mine of Xinqiu in Fuxin. Firstly, with the advantages of neural network method in dealing with nonlinear problem, the RBF neural network model was built. Then, the normalized standard matrix was taken as training sample and the MATLAB software was used to train the training sample. Finally, the monitoring data were taken as test samples and were inputted in the RBF neural network model to evaluate the groundwater quality of study area. At the same time, the concept of degree of membership was adopted in the result making it more objective and accurate. The result shows that the ground water of this mining is seriously polluted, class of its pollution is Ⅳ-Ⅴ.The method with strong classification function and reliable evaluation results is simple and effective, and can be widely applied in all kinds of water resources comprehensive evaluation.

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