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United States Department of Agriculture

Agricultural Research Service

Research Project: EMISSION AND DISPERSION OF AIR QUALITY CONSTITUENTS FROM AGRICULTURAL SYSTEMS Title: Aglite lidar: Calibration and retrievals of well characterized aerosols from agricultural operations using a three-wavelength elastic lidar

Authors
item Zavyalov, Vladimir - SPACE DYNAMICS LABORATORY
item Marchant, Christian - SPACE DYNAMICS LABORATORY
item Bingham, Gail - SPACE DYNAMICS LABORATORY
item Wilkerson, Thomas - SPACE DYNAMICS LABORATORY
item HATFIELD, JERRY
item Martin, Randal - UTAH STATE UNIVERSITY
item Silva, Philip - UTAH STATE UNIVERSITY
item Moore, Kori - SPACE DYNAMICS LABORATORY
item Swasey, Jason - SPACE DYNAMICS LABORATORY
item Ahlstrom, Douglas - SPACE DYNAMICS LABORATORY
item Jones, Tanner - SPACE DYNAMICS LABORATORY

Submitted to: Journal of Applied Remote Sensing (JARS)
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: March 26, 2009
Publication Date: March 31, 2009
Citation: Zavyalov, V.V., Marchant, C.C., Bingham, G.E., Wilkerson, T.D., Hatfield, J.L., Martin, R.S., Silva, P.J., Moore, K.D., Swasey, J., Ahlstrom, D.J., Jones, T.L. 2009. Aglite lidar: Calibration and retrievals of well characterized aerosols from agricultural operations using a three-wavelength elastic lidar. Journal of Applied Remote Sensing (JARS). 3:033522. [doi:10.1117/1.3122363]

Interpretive Summary: The distribution of particulates in space around agricultural facilities is difficult to obtain with point samplers and the variation in time is more difficult to evaluate because the rapid changes in the wind movement. The standard methods for measuring particulates in the air collect data for a single point and it is difficult to measure the entire plume using this method. A Lidar (LIght Detection And Ranging) system using three wavelengths was developed and calibrated with single point monitors in the atmosphere. Once calibrated the sensitivity of the Lidar was evaluated over different systems and found to be sensitive to different particulate size fractions. This unit is able to map the concentrations of different size fractions within a plume emitted from different agricultural operations. This system offers a potential system for use by scientists and air quality specialists to measure particulate emission and dispersion from agricultural operations.

Technical Abstract: Lidar (LIght Detection And Ranging) provides the means to quantitatively evaluate the spatial and temporal variability of particulate emissions from agricultural activities. AGLITE is a three-wavelength portable scanning lidar system built at the Space Dynamic Laboratory (SDL) to measure the spatial and temporal distribution of particulate concentrations around an agricultural facility. The retrieval algorithm takes advantage of measurements taken simultaneously at three laser wavelengths (355, 532, and 1064 nm) to extract particulate optical parameters, convert these parameters to volume concentration, and estimate the particulate mass concentration of a particulate plume. The quantitative evaluation of particulate optical and physical properties from the lidar signal is complicated by the complexity of particle composition, particle size distribution, and environmental conditions such as heterogeneity of the ambient air conditions and atmospheric aerosol loading. Additional independent measurements of particulate physical and chemical properties are needed to unambiguously calibrate and validate the particulate physical properties retrieved from the lidar measurements. The calibration procedure utilizes point measurements of the particle size distribution and mass concentration to characterize the aerosol and calculate the aerosol parameters. Once calibrated, the Aglite system is able to map the spatial distribution and temporal variation of the particulate mass concentrations of aerosol fractions such as TSP, PM10, PM2.5, and PM1. This ability is of particular importance in the characterization of agricultural operations being evaluated to minimize emissions and improve efficiency, especially for mobile source activities.

Last Modified: 9/10/2014
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