Mining Publication: A Predictive Model for Elemental Carbon, Organic Carbon and Total Carbon Based on Laser Induced Breakdown Spectroscopy Measurements of Filter-collected Diesel Particulate Matter

Diesel particulate matter (DPM) produced from vehicle and equipment diesel exhaust is a common industrial inhalation hazard, particularly in underground mines. The sub-micron particles of DPM (< 800 nm) are composed of a carbonaceous core operationally defined as elemental carbon (EC), which are irregularly arranged graphitic-like “spherule” structures, and a wide-variety of adsorbed, semi-volatile organic carbon compounds (OC). In addition to associating chronic exposure to DPM with immunological, respiratory and cardiovascular health issues, the International Agency for Research on Cancer (IARC) categorizes this material as carcinogenic to humans, with workers regularly exposed to it demonstrating an elevated risk for lung cancer. Given the long-term health risks associated with repeated and prolonged exposure to DPM, efforts are being directed at reducing the exposure of miners and other workers who may encounter high levels of DPM over the course of a typical working day.

In this study, a partial least squares (PLS) regression model was generated from laser-induced breakdown spectroscopy and NIOSH Standard Method 5040 data derived from DPM samples collected on quartz fiber filters to evaluate the effectiveness of LIBS measurements in predicting OC, EC, and TC in air samples. The results provided here suggest that LIBS measurements coupled with PLS modeling represents a promising direction for the rapid analysis of DPM concentrations.