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Abstract
Fugitive dust from confined livestock operations is a primary air quality issue associated with impaired visibility, nuisance odor, and other quality-of-life factors. Particulate matter has conventionally been measured using costly scientific instruments such as transmissometers, nephelometers, or tapered-element, oscillating microbalances (TEOMs). The use of digital imaging and automated data-acquisition systems has become a standard practice in some locations to track visibility conditions on roadways; however, the concept of using photometry to measure fugitive dust concentrations near confined livestock operations is relatively new. We have developed a photometric method to estimate path-averaged particulate matter (PM10) concentrations using digital SLR cameras and high-contrast visibility targets. Digital imaging, followed by automated image processing and interpretation, would be a plausible, cost-effective alternative for operators of confined livestock facilities to monitor on-site dust concentrations. We report on the development and ongoing evaluation of such a method for use by cattle feeders and open-lot dairy producers.
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Purpose
To develop a low-cost practical alternative for measurement of path-averaged particulate matter (PM10) concentrations downwind of open-lot animal feeding operations.
What Did We Do?
Working downwind of a cattle feedyard under a variety of dust conditions, we photographed an array of high contrast visibility targets with dSLR cameras and compared contrast data extracted from the photographs with path-averaged particulate matter (PM10) concentration data collected from several TEOMs codeployed alonside the visibility targets.
What Have We Learned?
We have developed a photometric method to estimate path-averaged particulate matter (PM10) concentrations using digital SLR cameras and high-contrast visibility targets. Using contrast data from digital images we expect to predict PM10 concentrations within 20% of TEOM values under the dustiest conditions. Digital imaging, followed by automated image processing and interpretation, may be a plausible, cost-effective alternative for operators of open-lot livestock facilities to monitor on-site dust concentrations and evaluate the abatement measures and management practices they put in place.
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Future Plans
We intend to improve the prediction accuracy of the photometric method and automate it such that it can be easily adapted for use as a cost-effective alternative for measuring path-averaged particulate matter (PM10) concentrations at cattle feedyards and open-lot dairies.
Authors
Brent Auvermann, Professor of Biological and Agricultural Engineering, Texas A&M AgriLife Research. b-auvermann@tamu.edu
Sharon Preece, Senior Research Associate, Texas A&M AgriLife Research; Brent W. Auvermann, Professor of Biological and Agricultural Engineering, Texas A&M AgriLife Research; Taek M. Kwon, Professor of Electrical and Computer Engineering, University of Minnesota-Duluth; Gary W. Marek, Postdoctoral Research Associate, Texas A&M AgriLife Research; Kevin Heflin, Extension Associate, Texas A&M AgriLife Research; K. Jack Bush, Research Associate, Texas A&M AgriLife Research.
Additional Information
Please contact Brent W. Auvermann, Professor of Biological and Agricultural Engineering, Texas A&M AgriLife Research, 6500 Amarillo Boulevard West, Amarillo TX, 79106, Phone: 806-677-5600, Email: b-auvermann@tamu.edu.
Acknowledgements
This research was underwritten by grants from the USDA National Institute on Food and Agriculture (contract nos. 2010-34466-20739 and 2009-55112-05235).
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