Relationships between a Calculated Mass Concentration and a Measured Concentration of PM_2.5and Respirable Particle Matter Sampling Direct-Reading Instruments in Taconite Mines

Abstract

Objectives:The purposes of this study are to investigate workers' exposures to respirable particles generated in taconite mines and to compare two metric methods for mass concentrations using direct-reading instruments. Methods: Air monitorings were conducted at six mines where subjects have been exposed primarily to particulate matters in crushing, concentrating, and pelletizing processes. Air samples were collected during 4 hours of the entire work shift for similarly exposure groups(SEGs) of nine jobs(N=37). Following instruments were employed to evaluate the workplace: a nanoparticle aerosol monitor(particle size range; 10-1000 nm, unit: ㎛ 2 /cc, Model 9000, TSI Inc.); DustTrak air monitors(PM10, PM2.5, unit: ㎎/ ㎥, Model 8520, TSI Inc.); a condensation particle counter(size range; 20-1000 nm, unit: #/cc, P-Trak 8525, TSI Inc.); and an optical particle counter(particle number by size range 0.3-25 ㎛, unit: #/cc, Aerotrak 9306, TSI Inc.). Results:The highest airborne concentration among SEGs was for furnace operator followed by pelletizing maintenance workers in number of particle and surface area, but not in mass concentrations. The geometric means of PM2.5 by the DustTrak and the Ptrak/Aerotrak were 0.04 mg/m 3 (GSD 2.52) and 0.07 mg/m 3 (GSD 2.60), respectively. Also, the geometric means of RPM by the DustTrak and the Ptrak/Aerotrak were 0.16 ㎎/㎥(GSD 2.24) and 0.32 ㎎/㎥(GSD 3.24), respectively. The Pearson correlation coefficient for DustTrak PM2.5 and Ptrak/Aerotrak PM2.5 was 0.56, and that of DustTrak RPM and Ptrak/Aerotrak RPM was 0.65, indicating a moderate positive association between the two sampling methods. Surface area and number concentration were highly correlated(R 2 = 0.80), while PM2.5 and RPM were also statistically correlated each other(R 2 = 0.79). Conclusions:The results suggest that it is possible to measure airborne particulates by mass concentrations or particle number concentrations using real-time instruments instead of using the DustTrak Aerosol monitor that monitor mass concentrations only.

Exposure Characterization of Ultrafine Particles From the Blast Furnace Process in a Steelmaking Plant

“…Data on the correlation among the three metrics are limited for engineered nanoparticles, especially metal nanoparticles. Chung et al reported that SAC and NC were highly correlated, and NC and MC had a moderate positive association 32 , which was con rmed in our previous study about Fe 2 O 3 nanoparticles released from a manufacturing facility 23 . In our preliminary study on nanoparticles generated from gas metal arc welding, we found that the MC was not as sensitive as NC or SAC 26 .…”

Light Scattering Method for Aerosol Sizing Based on Machine Learning

“…They use a preknown refractive index to measure the particle size one by one based on the total sideward scattering light intensity. 13 However, these PSD measurement techniques are based on the preset refractive index, and the measurement error would be very large, while the actual refractive index of the aerosol deviates from the ground truth. Zhang et al used multiple scattering and transmission light signals to retrieve the PSD and simultaneously decouple the refractive index of aerosols with the predetermined distribution mode.…”

“…Portable particle spectrometers, such as TSI-3330 and TSI-9306, are widely used for analyzing aerosol particle size in the field. They use a preknown refractive index to measure the particle size one by one based on the total sideward scattering light intensity . However, these PSD measurement techniques are based on the preset refractive index, and the measurement error would be very large, while the actual refractive index of the aerosol deviates from the ground truth.…”