title: Optical remote sensing to quantify fugitive particulate mass emissions from stationary short-term and mobile continuous sources: part II. Field applications.
abstract: Quantification of emissions of fugitive particulate matter (PM) into the atmosphere from military training operations is of interest by the United States Department of Defense. A new range-resolved optical remote sensing (ORS) method was developed to quantify fugitive PM emissions from puff sources (i.e., artillery back blasts), ground-level mobile sources (i.e., movement of tracked vehicles), and elevated mobile sources (i.e., airborne helicopters) in desert areas that are prone to generating fugitive dust plumes. Real-time, in situ mass concentration profiles for PM mass with particle diameters <10 μm (PM(10)) and <2.5 μm (PM(2.5)) were obtained across the dust plumes that were generated by these activities with this new method. Back blasts caused during artillery firing were characterized as a stationary short-term puff source whose plumes typically dispersed to <10 m above the ground with durations of 10-30 s. Fugitive PM emissions caused by artillery back blasts were related to the zone charge and ranged from 51 to 463 g PM/firing for PM(10) and 9 to 176 g PM/firing for PM(2.5). Movement of tracked vehicles and flying helicopters was characterized as mobile continuous sources whose plumes typically dispersed 30-50 m above the ground with durations of 100-200 s. Fugitive PM emissions caused by moving tracked vehicles ranged from 8.3 to 72.5 kg PM/km for PM(10) and 1.1 to 17.2 kg PM/km for PM(2.5), and there was no obvious correlation between PM emission and vehicle speed. The emission factor for the helicopter flying at 3 m above the ground ranged from 14.5 to 114.1 kg PM/km for PM(10) and 5.0 to 39.5 kg PM/km for PM(2.5), depending on the velocity of the helicopter and type of soil it flies over. Fugitive PM emissions by an airborne helicopter were correlated with helicopter speed for a particular soil type. The results from this range-resolved ORS method were also compared with the data obtained with another path-integrated ORS method and a Flux Tower method.
authors.affiliation: Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, China. kdu@iue.ac.cn
authors.forename: Ke
authors.initials: K
authors.lastname: Du
authors.forename: Wangki
authors.initials: W
authors.lastname: Yuen
authors.forename: Wei
authors.initials: W
authors.lastname: Wang
authors.forename: Mark J
authors.initials: MJ
authors.lastname: Rood
authors.forename: Ravi M
authors.initials: RM
authors.lastname: Varma
authors.forename: Ram A
authors.initials: RA
authors.lastname: Hashmonay
authors.forename: Byung J
authors.initials: BJ
authors.lastname: Kim
authors.forename: Michael R
authors.initials: MR
authors.lastname: Kemme
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000706:statistics & numerical data; D000401:Aircraft / Q000706:statistics & numerical data; D001272:Atmosphere / Q000737:chemistry; D004784:Environmental Monitoring / Q000379:methods*; D007700:Kinetics; D007834:Lasers; D008027:Light; D008956:Models, Chemical; D010316:Particle Size; D052638:Particulate Matter / Q000032:analysis*; D058998:Remote Sensing Technology / Q000379:methods*; D017550:Spectroscopy, Fourier Transform Infrared; D001335:Vehicle Emissions / Q000032:analysis; D054041:Weapons / Q000706:statistics & numerical data; D014919:Wind
chemical_list: D000393:Air Pollutants; D052638:Particulate Matter; D001335:Vehicle Emissions