A novel approach to forecast dust concentration in open pit mines by integrating meteorological parameters and production intensity.

Mine dust pollution poses a hindrance to achieving green and climate-smart mining. This paper uses weather forecast data and mine production intensity data as model inputs to develop a novel model for forecasting daily dust concentration values in open pit mines by employing and integrating multiple machine learning techniques. The results show that the forecast model exhibits high accuracy, with a Pearson correlation coefficient exceeding 0.

An Improved Machine Learning Approach for Optimizing Dust Concentration Estimation in Open-Pit Mines.

Dust is a severe environmental issue in open-pit mines, and accurate estimation of its concentration allows for viable solutions for its control and management. This research proposes a machine learning-based solution for accurately estimating dust concentrations. The proposed approach, tested using real data from the Haerwusu open-pit coal mine in China, is based upon the integrated random forest-Markov chain (RF-MC) model.

Annual dust pollution characteristics and its prevention and control for environmental protection in surface mines.

Dust pollution is a critical challenge in achieving green mining of open-pit coal mines. The scientific basis for dust prevention and management hinges on a thorough understanding of the long-term characteristics of dust pollution. However, analyzing the characteristics of long-term dust pollution in open-pit coal mines has always been a void in research due to the effect of the mines' geographical location and operating conditions.

Dust pollution in cold region Surface Mines and its prevention and control.

The application of traditional dust reduction methods in surface mines is limited, particularly during winter due to long-term drought and a rainless environment. Therefore, it is essential to investigate dust pollution in cold region mines and get insights into its scientific prevention and control. This research analyzed dust pollution (concentration of TSP, PM10, PM2.