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Analysis and Forecasting of PM2.5, PM4, and PM10 Dust Concentrations, Based on In Situ Tests in Hard Coal Mines

Author

Listed:
  • Dominik Bałaga

    (Division of Machines and Equipment, KOMAG Institute of Mining Technology, Pszczyńska 37 Street, 44-101 Gliwice, Poland)

  • Marek Kalita

    (Division of Machines and Equipment, KOMAG Institute of Mining Technology, Pszczyńska 37 Street, 44-101 Gliwice, Poland)

  • Piotr Dobrzaniecki

    (Division of Machines and Equipment, KOMAG Institute of Mining Technology, Pszczyńska 37 Street, 44-101 Gliwice, Poland)

  • Sebastian Jendrysik

    (Division of Mechatronic Systems, KOMAG Institute of Mining Technology, Pszczyńska 37 Street, 44-101 Gliwice, Poland)

  • Krzysztof Kaczmarczyk

    (Division of Machines and Equipment, KOMAG Institute of Mining Technology, Pszczyńska 37 Street, 44-101 Gliwice, Poland)

  • Krzysztof Kotwica

    (Faculty of Mechanical Engineering and Robotics, AGH University of Science and Technology, Mickiewicza 30 Av., 30-059 Kraków, Poland)

  • Iwona Jonczy

    (Faculty of Mining, Safety Engineering and Industrial Automation, Silesian University of Technology, Akademicka 2 Street, 44-100 Gliwice, Poland)

Abstract

The method of analyzing the results of dust concentration measurements in mine workings that was conducted within the ROCD (Reducing risks from Occupational exposure to Coal Dust) European project using the developed dust prediction algorithm is presented. The analysis was based on the measurements of average dust concentration with the use of the CIP-10R gravimetric dust meters, for the respirable PM4 dust concentration, and IPSQ analyzer for instantaneous concentration measurements (including PM2.5 dust) and with the use of Pł-2 optical dust meters for instantaneous concentration measurements of PM10 dust. Based on the analyses of the measurement results, the characteristics of the distribution of PM10, PM4, and PM2.5 dust particles were developed for the tested dust sources. Then, functional models based on power functions were developed. The determined models (functions) allow predicting the dust distribution in such conditions (and places) for which we do not have empirical data. The developed models were implemented in a specially developed online tool, which enables predicting the concentration of PM10, PM4, and PM2.5 dust (on the basis of dust concentration of one source) at any distance from the dust source.

Suggested Citation

  • Dominik Bałaga & Marek Kalita & Piotr Dobrzaniecki & Sebastian Jendrysik & Krzysztof Kaczmarczyk & Krzysztof Kotwica & Iwona Jonczy, 2021. "Analysis and Forecasting of PM2.5, PM4, and PM10 Dust Concentrations, Based on In Situ Tests in Hard Coal Mines," Energies, MDPI, vol. 14(17), pages 1-17, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:17:p:5527-:d:629037
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    Keywords

    dust; in situ tests; prediction;
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