Determinants of diesel particulate matter (DPM) concentration in underground metalliferous mines using multivariate regression analysis

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Diesel particulate matter, diesel-powered equipment, exhaust gases, health effects.


The use of diesel engine powered equipment in underground mines across the globe has been increased considerably in the recent past to enhance the productivity and safety standards. However, the extensive use of diesel engine powered equipment caused severe health hazards because of the exposure to diesel particulate matter (DPM) and toxic gases discharged from the exhausts of these equipment. NIOH and IARC, USA, reported diesel exhausts including DPM are suspected as human carcinogen. The number of diesel equipment deployed in Indian underground mine has also increased exponentially, which resulted into significant level of DPM exposure. There have not been any comprehensive study on the exposure of DPM as well as any stipulation in the current mine safety legislation in India so far except a guideline from DGMS. The concentration of DPM depends upon many factors such as ventilation, engine designs, maintenance, types of fuel, condition of roadways, exhaust treatment arrangements etc. In the present study, field investigations were accomplished in the three underground metalliferous mines. Different parameters like quantity of air, power and life of engine and gradient of roadways were taken as independent variables to predict the concentration of DPM. Multivariate regression analysis was carried out for establishing the relation between DPM and these independent parameters, and a significant empirical equation has been derived. Thereafter, DPM values were measured by Airtec DPM monitoring instrument and the values predicted from the multivariate regression model and measured values from the instrument were validated through chi square test.


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How to Cite

Sagesh Kumar, M. R., Paul, P. S., & Bhattacharjee, R. M. (2021). Determinants of diesel particulate matter (DPM) concentration in underground metalliferous mines using multivariate regression analysis. Journal of Mines, Metals and Fuels, 69(7), 207–215.



Received 2021-09-01
Accepted 2021-09-01
Published 2021-09-02



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