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ESTIMATING ODOR IMPACT WITH COMPUTATIONAL FLUID DYNAMICS
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Description: Book cover
ESTIMATING ODOR IMPACT WITH COMPUTATIONAL FLUID DYNAMICS

ESTIMATING ODOR IMPACT WITH COMPUTATIONAL FLUID DYNAMICS

ESTIMATING ODOR IMPACT WITH COMPUTATIONAL FLUID DYNAMICS

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Description: Book cover
ESTIMATING ODOR IMPACT WITH COMPUTATIONAL FLUID DYNAMICS
Abstract
The detection and nuisance concentrations of odors are frequently quoted in terms of dilutions from the initial source concentration. Meteorological dispersion modeling has been used to estimate the dilutions achieved between a release point, such as a stack, and a downwind receptor. Conventional models have proven to yield reasonable results for neutral and stable atmospheric conditions, within the acknowledged limitations of Gaussian dispersion models. However in regions with numerous buildings or sharp topography-induced turbulence, the Gaussian models are not able to provide results which take the turbulence into account. Computational Fluid Dynamics (CFD) is becoming available as a tool to assist with modeling the airflow and dispersion of pollutants among complex urban geometries on the scales of a section of a building exterior up to a few city blocks. This tool allows more accurate predictions of impacts within the regions of local turbulence. This can be especially important in urban areas where several buildings are within a mutual zone of influence and where air intakes are located on the top of a building with its own recirculation zone.This paper illustrates the capabilities of CFD in modeling odor dispersion in urban microenvironments and compares the results of CFD modeling in actual source-neighbor building situations with results obtained using the conventional U.S. EPA model ISCST3 and the newer U.S. EPA model AERMOD in complex terrain modes.A scaling factor has been frequently used to estimate the higher, short-term response to odors when using the 20 to 30-minute average dispersion coefficients of the conventional U.S. EPA models. CFD models report a steady state solution and the results also need to be adjusted to reflect the short-term odor response. This paper summarizes a peak-tomean adjustment that is appropriate to CFD models that has been developed using an extensive data base collected by the U.S. EPA during its analysis of the proposal for onehour ambient sulfur dioxide standards.
The detection and nuisance concentrations of odors are frequently quoted in terms of dilutions from the initial source concentration. Meteorological dispersion modeling has been used to estimate the dilutions achieved between a release point, such as a stack, and a downwind receptor. Conventional models have proven to yield reasonable results for neutral and stable atmospheric conditions, within...
Author(s)
Michael RubyJ.D. McAlpine
SourceProceedings of the Water Environment Federation
SubjectSession 3: Fate and Odor Modeling I
Document typeConference Paper
PublisherWater Environment Federation
Print publication date Jan, 2004
ISSN1938-6478
SICI1938-6478(20040101)2004:3L.200;1-
DOI10.2175/193864704784327449
Volume / Issue2004 / 3
Content sourceOdors and Air Pollutants Conference
First / last page(s)200 - 224
Copyright2004
Word count319

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ESTIMATING ODOR IMPACT WITH COMPUTATIONAL FLUID DYNAMICS
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Description: Book cover
ESTIMATING ODOR IMPACT WITH COMPUTATIONAL FLUID DYNAMICS
Abstract
The detection and nuisance concentrations of odors are frequently quoted in terms of dilutions from the initial source concentration. Meteorological dispersion modeling has been used to estimate the dilutions achieved between a release point, such as a stack, and a downwind receptor. Conventional models have proven to yield reasonable results for neutral and stable atmospheric conditions, within the acknowledged limitations of Gaussian dispersion models. However in regions with numerous buildings or sharp topography-induced turbulence, the Gaussian models are not able to provide results which take the turbulence into account. Computational Fluid Dynamics (CFD) is becoming available as a tool to assist with modeling the airflow and dispersion of pollutants among complex urban geometries on the scales of a section of a building exterior up to a few city blocks. This tool allows more accurate predictions of impacts within the regions of local turbulence. This can be especially important in urban areas where several buildings are within a mutual zone of influence and where air intakes are located on the top of a building with its own recirculation zone.This paper illustrates the capabilities of CFD in modeling odor dispersion in urban microenvironments and compares the results of CFD modeling in actual source-neighbor building situations with results obtained using the conventional U.S. EPA model ISCST3 and the newer U.S. EPA model AERMOD in complex terrain modes.A scaling factor has been frequently used to estimate the higher, short-term response to odors when using the 20 to 30-minute average dispersion coefficients of the conventional U.S. EPA models. CFD models report a steady state solution and the results also need to be adjusted to reflect the short-term odor response. This paper summarizes a peak-tomean adjustment that is appropriate to CFD models that has been developed using an extensive data base collected by the U.S. EPA during its analysis of the proposal for onehour ambient sulfur dioxide standards.
The detection and nuisance concentrations of odors are frequently quoted in terms of dilutions from the initial source concentration. Meteorological dispersion modeling has been used to estimate the dilutions achieved between a release point, such as a stack, and a downwind receptor. Conventional models have proven to yield reasonable results for neutral and stable atmospheric conditions, within...
Author(s)
Michael RubyJ.D. McAlpine
SourceProceedings of the Water Environment Federation
SubjectSession 3: Fate and Odor Modeling I
Document typeConference Paper
PublisherWater Environment Federation
Print publication date Jan, 2004
ISSN1938-6478
SICI1938-6478(20040101)2004:3L.200;1-
DOI10.2175/193864704784327449
Volume / Issue2004 / 3
Content sourceOdors and Air Pollutants Conference
First / last page(s)200 - 224
Copyright2004
Word count319

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Michael Ruby# J.D. McAlpine. ESTIMATING ODOR IMPACT WITH COMPUTATIONAL FLUID DYNAMICS. Alexandria, VA 22314-1994, USA: Water Environment Federation, 2018. Web. 29 Oct. 2025. <https://www.accesswater.org?id=-291264CITANCHOR>.
Michael Ruby# J.D. McAlpine. ESTIMATING ODOR IMPACT WITH COMPUTATIONAL FLUID DYNAMICS. Alexandria, VA 22314-1994, USA: Water Environment Federation, 2018. Accessed October 29, 2025. https://www.accesswater.org/?id=-291264CITANCHOR.
Michael Ruby# J.D. McAlpine
ESTIMATING ODOR IMPACT WITH COMPUTATIONAL FLUID DYNAMICS
Access Water
Water Environment Federation
December 22, 2018
October 29, 2025
https://www.accesswater.org/?id=-291264CITANCHOR