Abstract
Exposure to coal dust in underground coal mines poses significant health risks to workers, including the development of diseases such as coal workers' pneumoconiosis and silicosis. Current available methods for monitoring coal dust exposure are expensive and time-consuming, necessitating the exploration of alternative approaches. Low-cost light scattering particulate matter sensors offer a promising solution, and its development in recent years has demonstrated some success in air quality monitoring However, its application in sensing coal particles is limited partially due to that the operating condition in a mine is different than the atmosphere. Thus, the objective of this paper is to evaluate the impact of common factors encountered in a mining environment on these sensors. The findings revealed that the Air trek and Gaslab sensors were unsuitable, showing poor correlation with reference monitors. SPS30 was promising for low concentrations (0-1.0 mg m−3), while PMS5003 effectively monitored up to 3.0 mg m−3. Changing sensor orientation reduced accuracy. Higher wind speeds (3 m s−1) improved results. Low-cost sensors performed well with coal dust but poorly with Arizona road dust. This study underscores the imperative for enhancing these sensors, thereby facilitating their potential application to enhance the occupational health of miners.
Recommended Citation
M. M. Zaid et al., "Advancing Occupational Health In Mining: Investigating Low-cost Sensors Suitability For Improved Coal Dust Exposure Monitoring," Measurement Science and Technology, vol. 35, no. 2, article no. 025128, IOP Publishing, Feb 2024.
The definitive version is available at https://doi.org/10.1088/1361-6501/ad0c2e
Department(s)
Civil, Architectural and Environmental Engineering
Second Department
Mining Engineering
Keywords and Phrases
coal dust; exposure monitoring; low-cost sensor; occupational health; particulate matter
International Standard Serial Number (ISSN)
1361-6501; 0957-0233
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2023 IOP Publishing, All rights reserved.
Publication Date
01 Feb 2024
Comments
National Science Foundation, Grant 5D30123C17714