Research Papers

Lidar based emissions measurement at the whole facility scale: Method and error analysis

[+] Author Affiliations
Gail E. Bingham, Christian C. Marchant, Vladimir V. Zavyalov, Douglas J. Ahlstrom, Kori D. Moore, Derek S. Jones, Thomas Wilkerson

Space Dynamics Laboratory, 1695 North Research Parkway, North Logan, UT 84341

Larry E. Hipps, Randal S. Martin

Utah State University, Logan, UT 84322

Jerry L. Hatfield, John H. Prueger, Richard L. Pfeiffer

National Soil Tilth Laboratory, Agricultural Research Service, 2110 University Blvd., Ames, IA 50011-4420

J. Appl. Remote Sens. 3(1), 033510 (February 20, 2009). doi:10.1117/1.3097919
History: Received August 4, 2008; Revised January 20, 2009; Accepted February 17, 2009; February 20, 2009; Online February 20, 2009
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Abstract

Particulate emissions from agricultural sources vary from dust created by operations and animal movement to the fine secondary particulates generated from ammonia and other emitted gases. The development of reliable facility emission data using point sampling methods designed to characterize regional, well-mixed aerosols are challenged by changing wind directions, disrupted flow fields caused by structures, varied surface temperatures, and the episodic nature of the sources found at these facilities. We describe a three-wavelength lidar-based method, which, when added to a standard point sampler array, 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, 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. We describe the method, examine measurement error, and demonstrate the approach using data collected over a range of agricultural operations, including a swine grow-finish operation, an almond harvest, and a cotton gin emission study.

© 2009 Society of Photo-Optical Instrumentation Engineers

Citation

Gail E. Bingham ; Christian C. Marchant ; Vladimir V. Zavyalov ; Douglas J. Ahlstrom ; Kori D. Moore, et al.
"Lidar based emissions measurement at the whole facility scale: Method and error analysis", J. Appl. Remote Sens. 3(1), 033510 (February 20, 2009). ; http://dx.doi.org/10.1117/1.3097919


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