Quantification and Characterization of Dust Emissions from Tracked Vehicles and Helicopters Using Optical Remote Sensing Poster Number: 90 Abstract Unique military activities, such as movement of tracked vehicles on unimproved roads and flying of rotary winged aircraft in arid regions, emit particulate matter (PM) to the atmosphere. Both visual air quality and public health can be adversely affected by PM emissions. Remote methods to quantify the mass of PM emitted from these fugitive sources are not well established. In this study, a novel method using optical remote sensing (ORS) was developed to quantify the size distributions, mass concentrations, and emission factors for PM that is emitted to the atmosphere during select military activities. The ORS devices consist of a ground-based Micro-Pulse Lidar (MPL), two Open Path-Fourier Transform InfraRed (OP-FTIR) spectrometers and two Open Path- Laser Transmissometers (OP-LTs). An algorithm was formulated to invert the Lidar equation, which was applied to compute the dust extinction profiles from the MPL’s backscatter light signals. This method was then implemented characterize dust plumes from military activities. Dust emissions that were generated by the movement of three types of tracked vehicles (M-113, Bradley, and M-1) were characterized at Yakima Training Center (YTC) in Washington State, USA. Also, dust plumes that were generated by lying rotary winged aircraft (Bell 210 helicopter) over two surface types (i.e. desert pavement and disturbed desert soils) were characterized at Yuma Proving Ground (YPG) in Arizona, USA. Schematics of Field Campaigns Ke Du a, Mark J. Rood a, Byung J. Kim b, Michael R. Kemme b, Ram A. Hashmonay c, Ravi Varma d, and Wangki Yuen a Methodology and Site Photos Experimental setup for measuring dust emissions from the flying of helicopters Helicopter, monitoring equipment and dust plume Professional Affiliations a. University of Illinois at Urbana-Champaign b. U.S. Army Engineer Research and Development Center-Construction Engineering Research Laboratory (ERDC-CERL) c. ARCADIS d. National University of Ireland Raw MPL data Normalized relative backscattering (NRB) Extinction profile,  1-D mass concentration profile, g/m 3 MPL data correction Plume transmittance Particle size distribution, N(D p ) from OP-FTIR and OP-LT Refractive index, m Particle density,  Mie model K * = Conc. =  K * 2-D mass concentration profile from interpolation of four 1-D profiles along MPL scanning paths Dust emission factor, g/vkm* or g/helicopter pass Lidar equation inverting method Wind data Helicopter Dust plume Experimental setup for measuring dust emissions from the moving tracked vehicles MPL Tracked vehicle Dust plume *vkm: vehicle kilometer traveled

Results Summary and Conclusions Compare results from this method to those obtained with other independent measurements  Dust plumes generated from the moving of tracked vehicles and the flying of helicopters were detected using optical remote sensing.  MPL is capable of conducting "time of flight" measurements, which are important for capturing the properties of the entire plume compared to other measurement techniques  The dust plumes were characterized for their horizontal and vertical dimensions, heterogeneity, temporal variability, extinction profile, and transmittance by using MPL and reflective targets. Future Work 2008 Partners in Environmental Technology Technical Symposium & Workshop, Dec 2-4, Washington D.C. Poster Number: 90 Evolution of plume extinction profile during a helicopter pass (Bell 210 Helicopter moving at 30 km/hr toward the MPL)  Funding support from the Strategic Environmental Research and Development Program (SERDP) of Department of Defense (DoD)  Support staff from Yuma Proving Ground  Support staff from Yakima Training Center  Desert Research Institute (DRI) Acknowledgements PM mass emission factors for helicopters Evolution of plume mass concentration for PM 10 profile during a vehicle travel (Bradley Tank, moving at 32 km/hr toward the MPL) Direction vehicle is moving PM mass emission factors for tracked vehicles Bradley Tank M1A1 Tank M113 Tank  10 3 Direction helicopter is flying 0 2  (m -1 ) 1.2   -3 8   Towers for point measurements OP-FTIR and OP-LT’s optical paths Towers for point measurements OP-FTIR and OP-LT’s optical paths Towers for point measurements OP-FTIR and OP-LT’s optical paths Towers for point measurements OP-FTIR and OP-LT’s optical paths Towers for point measurement OP-FTIR and OP-LT’s optical paths Towers for point measurement OP-FTIR and OP-LT’s optical paths OP-FTIR and OP-LT’s optical paths Towers for point measurement OP-FTIR and OP-LT’s optical paths Towers for point measurement OP-FTIR and OP-LT’s optical paths Towers for point measurement OP-FTIR and OP-LT’s optical paths Towers for point measurement Direction helicopter is flying 0 2    -3 8   Towers for point measurements OP-FTIR and OP-LT’s optical paths Towers for point measurements OP-FTIR and OP-LT’s optical paths Towers for point measurements OP-FTIR and OP-LT’s optical paths Towers for point measurements OP-FTIR and OP-LT’s optical paths Towers for point measurement OP-FTIR and OP-LT’s optical paths Towers for point measurement OP-FTIR and OP-LT’s optical paths OP-FTIR and OP-LT’s optical paths Towers for point measurement OP-FTIR and OP-LT’ s optical paths Towers for point measurement OP-FTIR and OP- LT ’ s optical paths Towers for point measurement OP-FTIR and OP-LT’s optical paths Towers for point measurement t t Desert PavementDisturbed Soil