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Proceedings Paper

Aerosol detection using lidar-based atmospheric profiling
Author(s): Mohamed I. Elbakary; Hossam M. Abdelghaffar; Kwasi Afrifa; Hesham A. Rakha; Mecit Cetin; Khan M. Iftekharuddin
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Paper Abstract

A compact light detection and ranging (LiDAR) is a system that provides aerosols profile measurements by identifying the aerosol scattering ratio as function of the altitude. The aerosol scattering ratios are used to obtain multiple aerosol intensive ratio parameters known as backscatter color ratio, depolarization ratio, and lidar ratio. The aerosol ratio parameters are known to vary with aerosol type, size, and shape. In this paper, we employed lidar measurements to detect the potential source of the aerosol in the neighborhood of the campus of Old Dominion University. The lidar is employed to collect measurements at several locations in the area of study. Then, the lidar ratio and the color ratio are retrieved from collected measurements. To find the source of aerosol in the measurements, a tracking algorithm is implemented and employed to track the concentration of that pollution in the data. The results show that the source of soot pollution in the area of study is Hampton Blvd, a major street, in the area of the campus where the diesel trucks travel between the ports in the city of Norfolk.

Paper Details

Date Published: 24 August 2017
PDF: 7 pages
Proc. SPIE 10395, Optics and Photonics for Information Processing XI, 103951H (24 August 2017); doi: 10.1117/12.2275626
Show Author Affiliations
Mohamed I. Elbakary, Old Dominion Univ. (United States)
Hossam M. Abdelghaffar, Virginia Tech (United States)
Kwasi Afrifa, Old Dominion Univ. (United States)
Hesham A. Rakha, Virginia Tech (United States)
Mecit Cetin, Old Dominion Univ. (United States)
Khan M. Iftekharuddin, Old Dominion Univ. (United States)

Published in SPIE Proceedings Vol. 10395:
Optics and Photonics for Information Processing XI
Khan M. Iftekharuddin; Abdul A. S. Awwal; Mireya García Vázquez; Andrés Márquez; Víctor H. Diaz-Ramirez, Editor(s)

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