ARS | Publication request: Using lidar to characterize particles from point and diffuse sources in an agricultural field

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: July 1, 2011
Publication Date: March 23, 2012
Citation: Wojcik, M.D., Martin, R.S., Hatfield, J.L. 2012. Using lidar to characterize particles from point and diffuse sources in an agricultural field. In: Chang, N., editor. Environmental Remote Sensing and Systems Analysis. Boca Raton, Florida: CRC Press. p. 299-331.

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 Energy Dynamics Laboratory (EDL) to measure the spatial and temporal distribution of particulate concentrations around an agricultural facility. The data analysis 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, and PM2.5. This ability is of particular importance in the characterization of agricultural operations and is being evaluated to minimize emissions and improve agricultural efficiency. We describe a method which provides unambiguous measurement and characterization of the particulate emissions from agricultural production operations in near-real time. Point-sampled data are used to provide the aerosol characterization needed for the particle concentration and size fraction calibration, while the lidar provides 3D mapping of particulate concentrations entering, moving around, and leaving the facility. Differences between downwind and upwind measurements provide an integrated aerosol concentration profile, which, when multiplied by the wind speed profile, produces the facility source flux. This approach assumes only conservation of mass, eliminating reliance on boundary layer theory, reliance on knowledge about the absolute radiometric performance of the lidar instrument, and detailed optical properties of the aerosol itself.