Model Dependence on Predicted Odor Impacts
Abstract:Previous studies have cited differences in predicted impacts from the Industrial Source Complex (ISC) model, the AERMOD model (Diosey, 2002 and Porter, 2003), and CALPUFF (Donaldson, 2008). These studies compared the overall difference of the models when predicting impacts from treatment processes as a whole. More recent studies (Porter, 2004 and 2007) have cited the difference in predictions for point or area sources when the different dispersion models were used.
One particular issue identified in the U.S. Environmental Protection Agency's (EPA) model performance evaluation was that low level point sources from process units tended to be under-predicted by AERMOD relative to ISC, while area sources tended to be over-predicted. This suggests that odor impacts using AERMOD would shift the control strategies from reducing offsite odor impacts from enclosed process areas (headworks facilities and solids processing) to open tanks and basins (primary clarifiers and aeration basins).
CALPUFF is currently generally used primarily as a long-range model for regulatory purposes, and its performance continues to be evaluated in near-field applications to be used on a case-by-case basis. This study examines the difference between point, area, and volume source runs from AERMOD and CALPUFF and discusses how differences occur. While EPA used field studies to demonstrate the performance of the AERMOD and CALPUFF models, these field studies were not representative of short process stacks or open basins. Thus, the differences may in part be due to the changes in the dispersion algorithm or in the way the atmospheric boundary layer is characterized in the more refined AERMOD and CALPUFF dispersion models.
Odor impacts must define the intensity, frequency and duration of the event. Unlike criteria pollutant modeling, these values are not defined by their corresponding ambient air quality standard. Whether the modeling analysis is intended to represent recognition, complaint or nuisance conditions greatly affects how the models need to be set-up. Because odor concentrations maximize when wind conditions are light and atmosphere conditions are stable, a model which better characterizes pollutant concentrations under those conditions is desirable.
CALPUFF was found to under-predict impacts compared to AERMOD by about a factor of two for area and volume sources but was in better agreement with AERMOD for point sources. Agreement was better between the two models when building wake effects were not an issue for the point sources.
Document Type: Research Article
Publication date: January 1, 2012
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