Poster Number: 90

1. Poster Number: 90 Quantification and Characterization of Dust Emissions from Tracked Vehicles and Helicopters Using Optical Remote Sensing Ke Dua, Mark J. Rooda,Byung J. Kimb, Michael R. Kemmeb,Ram A. Hashmonayc,Ravi Varmad, and Wangki Yuena Abstract Professional Affiliations University of Illinois at Urbana-Champaign U.S. Army Engineer Research and Development Center-Construction Engineering Research Laboratory (ERDC-CERL) ARCADIS National University of Ireland 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. Methodology and Site Photos MPL data correction Raw MPL data Normalized relative backscattering (NRB) Plume transmittance Refractive index, m Lidar equation inverting method Mie model Extinction profile,  Particle size distribution, N(Dp) from OP-FTIR and OP-LT Particle density,  K* = Conc. = K* 1-D mass concentration profile, g/m3 Wind data 2-D mass concentration profile from interpolation of four 1-D profiles along MPL scanning paths Schematics of Field Campaigns Dust emission factor, g/vkm* or g/helicopter pass *vkm: vehicle kilometer traveled Dust plume Tracked vehicle MPL Dust plume Helicopter Experimental setup for measuring dust emissions from the flying of helicopters Experimental setup for measuring dust emissions from the moving tracked vehicles Helicopter, monitoring equipment and dust plume

2. 2008 Partners in Environmental Technology Technical Symposium & Workshop, Dec 2-4, Washington D.C. Poster Number: 90 Results Evolution of plume mass concentration for PM10 profile during a vehicle travel (Bradley Tank, moving at 32 km/hr toward the MPL) Evolution of plume extinction profile during a helicopter pass (Bell 210 Helicopter moving at 30 km/hr toward the MPL) OP OP - - FTIR and OP FTIR and OP-LT’s - LT ’ s OP OP - - FTIR and OP FTIR and OP-LT’s - LT ’ s Towers for Towers for Towers for Towers for point point point point optical paths optical paths optical paths optical paths measurements measurements measurement measurement OP OP - - FTIR and OP-LT’s FTIR and OP - LT ’ s OP OP - - FTIR and OP FTIR and OP-LT’s - LT ’ s Towers for Towers for point point Towers for Towers for point point optical paths optical paths optical paths optical paths measurement measurement measurements measurements t t OP OP - - FTIR and OP-LT’s FTIR and OP - LT ’ s OP OP - - FTIR and OP FTIR and OP - LT - LT ’ ’ s s Towers for Towers for point point Towers for Towers for point point optical paths optical paths optical paths optical paths measurement measurement measurements measurements OP OP - - FTIR and OP-LT’s FTIR and OP - LT ’ s OP OP - - FTIR and OP FTIR and OP - - ’ LT ’ s LT s Towers for Towers for point point Towers for Towers for point point optical paths optical paths optical paths optical paths measurement measurement measurements measurements OP OP - - FTIR and OP-LT’s FTIR and OP - LT ’ s OP OP - - FTIR and OP FTIR and OP - LT - LT ’ s ’ s Towers for Towers for point point Towers for Towers for point point optical paths optical paths optical paths optical paths measurement measurement measurement measurement ´ ´ 4 4 10 10 - - 3 3 (m-1) ´ ´ ´ ´ ´ ´ ´ ´ 0 0 8 8 10 10 - - 3 3 1.2 1.2 10 10 - - 2 2 1.6 1.6 10 10 - - 2 2 2 2 10 10 - - 2 2 Direction vehicle is moving Direction vehicle is moving Direction helicopter is flying Direction helicopter is flying Direction helicopter is flying Direction helicopter is flying PM mass emission factors for tracked vehicles PM mass emission factors for helicopters 103 M1A1 Tank Desert Pavement Disturbed Soil Bradley Tank M113 Tank Summary and Conclusions Future Work 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. Acknowledgements • 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)