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Field Comparison of TSI DustTrak PM Monitor with Tapered Element Oscillating Microbalance (TEOM)

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  2015 ASABE Annual International Meeting  152161447.(doi:10.13031/aim.20152161447)
Authors:   Xufei Yang, Hong Li, Chen Zhang
Keywords:   Mie scattering; PM10; mass concentration; TEOM; DustTrak.

Abstract. The TSI DustTrak PM monitor has been extensively used for monitoring particulate matter (PM) concentrations at various animal facilities. The instrument measures PM concentrations based on the principle of light scattering. Several assumptions (e.g., size, refractive index, and density) are adopted during the calibration process; however, they may not apply to PM emanating from agricultural settings. In this study, PM10 monitoring was conducted at a broiler house and a dairy barn, with four instruments implemented: three TSI DustTrak and one TEOM. Here, the TEOM unit is selected as a transfer standard since it has been approved by the U.S. Environmental Protection Agency (USEPA) as a Federal Equivalent Method (FEM) for PM10 monitoring. PM10 concentrations in the broiler house – as measured by the TEOM – ranged from 0.173 to 12.701 mg/m3 (average: 2.914 mg/m3), which were significantly higher than those determined by the DustTrak units. An average correction factor of 3.751 was derived from correlation analysis (R2=0.92); and the correction factor deceased with PM10 concentration. In the dairy barn, the TEOM did not work properly with negative mass readings occasionally observed; and no significant correlation (R2=0.07) was found between the DustTrak and TEOM. A comparison of multiple DustTrak units affirmed the importance of timely calibration. A drift in the DustTrak’s response factor after 10 months can be over 20%. Future research will include monitoring efforts at additional farms, measurement of the size distribution and refractive indices of PM10 samples, and the modeling of Mie scattering to better understand the limitations and perspectives of DustTrak and its applications to agricultural PM monitoring

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