Mining-induced coal dust causes various respiratory diseases to mine workers mainly coal workers' pneumoconiosis (CWP). Currently available underground monitors are expensive and bulky. These disadvantages limit them for regulatory sample monitoring purposes. Moreover, personal exposure levels for most miners remain unknown, risking them to potential overexposures. Low-cost light scattering particulate matter (PM) sensors offer a potential solution to this problem with the capability to characterize PM concentration with high spatio-temporal resolution. However, these sensors require precise calibration before they can be deployed in mining environments. No previous study has promulgated a standard protocol to assess these sensors for coal dust monitoring. The goal of this study was to calibrate Plantower PMS5003 sensors for coal dust monitoring using linear regression models. Two other commercially available PM sensors, the Airtrek and Gaslab CM-505 multi-gas sensors, were also evaluated and calibrated. They were evaluated for factors including linearity, precision, limit of detection, upper concentration limits, and the influence of temperature and relative humidity in a laboratory wind tunnel. The PMS5003 sensors were observed to be accurate below 3.0 mg/m3 concentration levels with R-squared values of 0.70 to 0.90 which was the best among the sensors under with an acceptable precision below 1.5 mg/m3. Moreover, this study shows that temperature and relative humidity have minimal influence on the efficacy of low-cost PM sensors' ability to monitor coal dust. This investigation reveals the feasibility of low-cost sensors for real-time personal coal dust monitoring in underground coal mines if a robust calibration model is applied.
All Science Journal Classification (ASJC) codes
- Environmental Engineering
- Environmental Chemistry
- Waste Management and Disposal