Modeling odor dispersion from a swine facility using AERMOD

D. D. Schulte; M. R. Modi; C. G. Henry; R. R. Stowell; D. P. Billesbach; S. J. Hoff; L. D. Jacobson

Modeling odor dispersion from a swine facility using AERMOD

D. D. Schulte, M. R. Modi, C. G. Henry, R. R. Stowell, D. P. Billesbach, S. J. Hoff, L. D. Jacobson

Bioproducts and Biosystems Engineering

Research output: Contribution to conference › Paper › peer-review

8 Scopus citations

Abstract

Meteorological conditions, odor emissions, and ambient odor levels at a four-barn, swine finishing facility in Iowa were measured in the summer and fall of 2004. This paper compares ambient odor levels measured using a Nasal Ranger® compared to those predicted by AERMOD, a relatively new air dispersion model. Scaling factors needed to adjust predicted odor levels to those observed ranged from 1.66 to 3.12, depending on the source configuration used by the model. Predicted odors levels from the point source configuration required the smallest scaling factor (1.66) and accounted for the greatest percentage of variability in the data when compared to Nasal Ranger readings.

Original language	English (US)
State	Published - Dec 1 2007
Event	International Symposium on Air Quality and Waste Management for Agriculture - Broomfield, CO, United States Duration: Sep 16 2007 → Sep 19 2007

Other

Other	International Symposium on Air Quality and Waste Management for Agriculture
Country/Territory	United States
City	Broomfield, CO
Period	9/16/07 → 9/19/07

Keywords

Air quality
Modeling
Odors
Swine

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title = "Modeling odor dispersion from a swine facility using AERMOD",

abstract = "Meteorological conditions, odor emissions, and ambient odor levels at a four-barn, swine finishing facility in Iowa were measured in the summer and fall of 2004. This paper compares ambient odor levels measured using a Nasal Ranger{\textregistered} compared to those predicted by AERMOD, a relatively new air dispersion model. Scaling factors needed to adjust predicted odor levels to those observed ranged from 1.66 to 3.12, depending on the source configuration used by the model. Predicted odors levels from the point source configuration required the smallest scaling factor (1.66) and accounted for the greatest percentage of variability in the data when compared to Nasal Ranger readings.",

keywords = "Air quality, Modeling, Odors, Swine",

author = "Schulte, {D. D.} and Modi, {M. R.} and Henry, {C. G.} and Stowell, {R. R.} and Billesbach, {D. P.} and Hoff, {S. J.} and Jacobson, {L. D.}",

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AU - Schulte, D. D.

AU - Modi, M. R.

AU - Henry, C. G.

AU - Stowell, R. R.

AU - Billesbach, D. P.

AU - Hoff, S. J.

AU - Jacobson, L. D.

PY - 2007/12/1

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N2 - Meteorological conditions, odor emissions, and ambient odor levels at a four-barn, swine finishing facility in Iowa were measured in the summer and fall of 2004. This paper compares ambient odor levels measured using a Nasal Ranger® compared to those predicted by AERMOD, a relatively new air dispersion model. Scaling factors needed to adjust predicted odor levels to those observed ranged from 1.66 to 3.12, depending on the source configuration used by the model. Predicted odors levels from the point source configuration required the smallest scaling factor (1.66) and accounted for the greatest percentage of variability in the data when compared to Nasal Ranger readings.

AB - Meteorological conditions, odor emissions, and ambient odor levels at a four-barn, swine finishing facility in Iowa were measured in the summer and fall of 2004. This paper compares ambient odor levels measured using a Nasal Ranger® compared to those predicted by AERMOD, a relatively new air dispersion model. Scaling factors needed to adjust predicted odor levels to those observed ranged from 1.66 to 3.12, depending on the source configuration used by the model. Predicted odors levels from the point source configuration required the smallest scaling factor (1.66) and accounted for the greatest percentage of variability in the data when compared to Nasal Ranger readings.

KW - Air quality

KW - Modeling

KW - Odors

KW - Swine

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T2 - International Symposium on Air Quality and Waste Management for Agriculture

Y2 - 16 September 2007 through 19 September 2007

ER -

Modeling odor dispersion from a swine facility using AERMOD

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