Evaluation of Uncertainties in Measuring Particulate Matter Emission Factors from Atmospheric Fugitive Sources Using Optical Remote Sensing

Abstract:

Measurements of particulate matter (PM) emissions generated from fugitive sources are of interest in air pollution studies, since such emissions vary widely both spatially and temporally. This research focuses on determining the uncertainties in quantifying fugitive PM emission factors (EFs) generated from mobile vehicles using a vertical scanning micro-pulse lidar (MPL). The goal of this research is to identify the greatest sources of uncertainty of the applied lidar technique in determining fugitive PM EFs, and to recommend methods to reduce the uncertainties in this measurement. The MPL detects the PM plume generated by mobile fugitive sources that are carried downwind to the MPL’s vertical scanning plane. Range-resolved MPL signals are measured, corrected, and converted to light extinction coefficients, through inversion of the lidar equation and calculation of the lidar ratio. In this research, both the near-end and far-end lidar equation inversion methods are considered. Range-resolved PM mass concentrations are then determined from the extinction coefficient measurements using the measured mass extinction efficiency (MEE) value, which is an intensive PM property. MEE is determined by collocated PM mass concentration and light extinction measurements, provided respectively by a DustTrak and an open-path laser transmissometer. These PM mass concentrations are then integrated with wind information, duration of plume event, and vehicle distance travelled to obtain fugitive PM EFs. To obtain the uncertainty of PM EFs, uncertainties in MPL signals, lidar ratio, MEE, and wind variation are considered. Error propagation method is applied to each of the above intermediate steps to aggregate uncertainty sources. Results include determination of uncertainties in each intermediate step, and comparison of uncertainties between the use of near-end and far-end lidar equation inversion methods.