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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Research » Publications at this Location » Publication #330184

Title: Lidar method to estimate emission rates from extended sources

Author
item Willis, W. - University Of Iowa
item Eichinger, W - University Of Iowa
item Prueger, J.h - Collaborator
item Hapeman, Cathleen
item Li, H. - University Of Delaware
item Buser, M. - Oklahoma State University
item Hatfield, J.l. - Desiderio Finamore Veterinary Research Institute (FEPAGRO)
item Wanjura, J. - Collaborator
item Holt, G. - Collaborator
item Torrents, A. - University Of Maryland
item Plenner, S. - University Of Iowa
item Clarida, W. - University Of Iowa
item Browne, S.d. - University Of Iowa

Submitted to: Journal of Atmospheric and Ocean Technology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/5/2016
Publication Date: 2/1/2017
Citation: Willis, W., Eichinger, W., Prueger, J., Hapeman, C.J., Li, H., Buser, M., Hatfield, J., Wanjura, J., Holt, G., Torrents, A., Plenner, S., Clarida, W., Browne, S. 2017. Lidar method to estimate emission rates from extended sources. Journal of Atmospheric and Ocean Technology. 34:335-345.

Interpretive Summary: The release of pollutants and particles from agricultural sources is difficult to measure. Typically, point measurements are made and then combined with models to estimate an emission rate from an area. However, these methods often fall short in when considering the spatial and temporal resolution and even accuracy. Lidar technology uses a laser to illuminate the particles and then the reflected light is analyzed to determine the density of the particulate matter. It is known for its ability to capture entire plume extents in near real time. Thus, a new methodology using lidar data was used to estimate particulate emission rates from a poultry house where a known amount of dust was released upwind of a vegetative environmental buffer. Several hundred scans were collected over four-hour sampling periods. For each scan, the emission plumes showed lofting, puffs, and considerable non-Gaussian dynamics (bell-curves), but Gaussian shapes emerged when these scans were averaged over time. The capture efficiency of the buffer was then determined using the estimated emission rates and the known release rates of the particles. These results suggest resolution of temporal changes can influence the interpretation of remotely-sensed atmospheric data as well as plume modeling, monitoring, and regulation of large pollutant sources. This technique will assist in the design of more effective vegetative environmental buffers.

Technical Abstract: Currently, point measurements, often combined with models, are the primary means by which atmospheric emission rates are estimated from extended sources. However, these methods often fall short in their spatial and temporal resolution and accuracy. In recent years, lidar has emerged as a suitable tool for supplementing point measurements in agricultural research and is known for its ability to capture entire plume extents in near real time. A methodology using lidar data was used to estimate particulate emission rates from extended sources, specifically to a study in which a known amount of dust was released upwind of a vegetative environmental buffer. For each instantaneous scan in this study, the emitted plumes experienced lofting, puffs, and considerable non-Gaussian dynamics, but Gaussian shapes emerged when these scans were averaged over time. The capture efficiency of the buffer was then determined from the estimated emission rates and the known release rates. The measured efficiencies agree with the ranges previously published, which provides confidence in the efficacy of the method. A comprehensive uncertainty analysis revealed an uncertainty of 20%. These results suggest resolution of temporal changes can influence the interpretation of remotely-sensed atmospheric data as well as plume modeling, monitoring, and regulation of extended pollutant sources.