DOI: 10.14457/tu.the.2024.502
title: Prediction model of dust concentration: comparison between real-time direct reading device and standard monitor

description: This research predicted equations for a real-time device by focusing on wood dust (inhalable fraction and total fraction), calcium carbonate dust (PM2.5, respirable dust, and PM10), and PNOR (respirable dust and PM10). A real-time device determined dust concentration in conjunction with the standard method, presented as a geometric mean. A paired sample t-test was used to discern the difference in dust concentration between the two devices, and correlation was calculated by simple linear regression analysis at a 0.05 significance level.Results were that for wood dust, the geometric mean concentrations obtained from the standard measurement were 1.286 ± 0.333 mg/m3 for the inhalable fraction, and 0.553 ± 0.139 mg/m3 for the total fraction; from real-time measurement, Sidepak AM520, were 0.319 ± 0.060 mg/m3 for inhalable fraction, and 0.298 ± 0.062 mg/m3 for the total fraction. The geometric mean of wood dust concentration measured by the real-time device differed significantly from those calculated by the standard method (p = 0.002) for the inhalable fraction, and (p = 0.039) for the total fraction. The real-time device underestimated both the inhalable and total fractions. The two devices were moderately correlated (r = 0.596, p = 0.002). This might be explained by the weakness (r = 0.392, p = 0.039) of the 35.5% (R2 = 0.355) model for the inhalable fraction, explicable by the 15.4% (R2 = 0.154) model for the total fraction. For calcium carbonate dust, the geometric mean concentrations obtained from standard measurement were 1.062 ± 0.338 mg/m3 for PM2.5, 2.625 ± 1.065 mg/m3 for PM10, and 0.589 ± 0.227 mg/m3 for respirable dust; from real-time measurement produced 0.531 ± 0.194 mg/m3 for PM2.5, 1.240 ±0.397 mg/m3 for PM10, and 0.939 ± 0.474 mg/m3 for respirable dust. The geometric means of these three sizes of calcium carbonate dust concentration measured by the real-time device differed significantly from those obtained by the standard method (p = 0.000). The real-time device overestimated respirable dust, while underestimating PM2.5 and PM10. Two devices were strongly correlated (r = 0.654, p = 0.000), potentially explicable by the 42.8% (R2 = 0.428) model for PM2.5; were strongly correlated (r = 0.804, p = 0.000), potentially explicable by the 64.6% (R2 = 0.646) model for PM10; and were strongly correlated (r = 0.679, p = 0.000), potentially explicable by the 46.0% (R2 = 0.460) model for respirable dust. For PNOR, the geometric mean concentrations obtained from standard measurement were 0.106 ± 0.026 mg/m3 for PM10 and 0.038 ± 0.013 mg/m3 for respirable dust; from real-time measurement produced 0.036 ± 0.015 mg/m3 for PM10 and 0.024 ± 0.015 mg/m3 for respirable dust. The geometric means of these two sizes of PNOR concentration measured by the real-time device differed significantly from those obtained by the standard method (p = 0.000). The real-time device underestimated respirable dust and PM10. The two devices were strongly correlated (r = 0.713, p = 0.000), potentially explicable by the 50.8% (R2 = 0.508) model for PM10; and were strong (r = 0.618, p = 0.000), potentially explicable by the 38.2% (R2 = 0.382) model for respirable dust. These findings suggest that a real-time device may be used for dust measurement, it lacks the accuracy of the standard method. Therefore, the error must be decreased by using correction factors and predicted equations. Based on the correlation, Sidepak (AM520) was suitable for measuring PM10 of calcium carbonate dust and PNOR. The device may be unsuited for wood dust measurement, but it may be used for dust screening. Measurement by a real-time device could determine the dust concentration and help occupational hygienists by indicating immediate values while saving expense and time.