Comparing Air Dispersion Model Predictions with Measured Concentrations of VOCs in Urban Communities

• Published in: Environmental science & technology 2004-04, Vol.38 (7), p.1949-1959
• Main Authors: Pratt, Gregory C, Wu, Chun Yi, Bock, Don, Adgate, John L, Ramachandran, Gurumurthy, Stock, Thomas H, Morandi, Maria, Sexton, Ken
• Format: Article
• Language: English
• Subjects: Air Movements; Air Pollutants - analysis; Air pollution; Applied sciences; Atmospheric pollution; Cities; Dispersion; Exact sciences and technology; Forecasting; Models, Theoretical; Organic Chemicals; Pollutants; Pollutants physicochemistry study: properties, effects, reactions, transport and distribution; Pollution; Sensitivity and Specificity; Urban areas; VOCs; Volatile organic compounds; Volatilization
• ISSN: 0013-936X; 1520-5851
• DOI: 10.1021/es030638l

Air concentrations of nine volatile organic compounds were measured over 48-h periods at 23 locations in three communities in the Minneapolis−St. Paul metropolitan area. Concentrations at the same times and locations were modeled using a standard regulatory air dispersion model (ISCST3). The goal of the study was to evaluate model performance by comparing predictions with measurements using linear regression and estimates of bias. The modeling, done with mobile and area source emissions resolved to the census tract level and characterized as model area sources, represents an improvement over large-scale air toxics modeling analyses done to date. Despite the resolved spatial scale, the model did not fully capture the spatial resolution in concentrations in an area with a sharp gradient in emissions. In a census tract with a major highway at one end of the tract (i.e., uneven distribution of emissions within the tract), model predictions at the opposite end of the tract overestimated measured concentrations. This shortcoming was seen for pollutants emitted mainly by mobile sources (benzene, ethylbenzene, toluene, and xylenes). We suggest that major highways would be better characterized as line sources. The model also failed to fully capture the temporal variability in concentrations, which was expected since the emissions inventory comprised annual average values. Based on our evaluation metrics, model performance was best for pollutants emitted mainly from mobile sources and poorest for pollutants emitted mainly from area sources. Important sources of error appeared to be the source characterization (especially location) and emissions quantification. We expect that enhancements in the emissions inventory would give the greatest improvement in results. As anticipated for a Gaussian plume model, performance was dramatically better when compared to measurements that were not matched in space or time. Despite the limitations of our analysis, we found that the regulatory air dispersion model was generally able to predict space and time matched 48-h average ambient concentrations of VOC species within a factor of 2 on average, results that meet regulatory model acceptance criteria.