Application of the United States environmental protection agency's AERMOD model to an industrial area

Jampana, Siva Sailaja; Kumar, Ashok; Varadarajan, Charanya

doi:10.1002/ep.10010

Cited by 7 publications

(2 citation statements)

References 3 publications

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“…The computer programs are developed to solve these mathematical equations in order to predict the downwind concentrations from a release. The US EPA has introduced several air quality models over the last four decades to study the compliance of the new and existing regulations for industrial sources [1–7]. There are two basic types of regulatory models that are in use today.…”

Section: Introductionsupporting

confidence: 89%

Application of the United States environmental protection agency's AERSCREEN to the air quality problems

Bhat

Kumar

2011

Env Prog and Sustain Energy

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Section: Introductionsupporting

confidence: 89%

Application of the United States environmental protection agency's AERSCREEN to the air quality problems

Bhat

Kumar

2011

Env Prog and Sustain Energy

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“…AERMOD can also be used for predicting the concentrations of various pollutants emitted by point, line, and area sources. This model is typically used for large areas (26)(27)(28)(29)(30)(31) or stationary sources (32,33). Results from studies in India (34) and China (35) suggest that AERMOD may generally underestimate PM 10 concentrations.…”

mentioning

confidence: 99%

Predicting Near-Road PM_2.5 Concentrations

Chen

Bai

Eisinger

et al. 2009

Transportation Research Record: Journal of the Transportation R

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Scientific evidence has increasingly shown an association between particulate matter (PM) and adverse human health impacts. Accurately predicting near-road PM2.5 concentrations is therefore important for project-level transportation conformity and health risk analysis. This study assessed the capability and performance of three dispersion models–-CALINE4, CAL3QHC, and AERMOD–-in predicting near-road PM2.5 concentrations. The comparative assessment included identifying differences among the three models in relation to methodology and data requirements. An intersection in Sacramento, California, and a busy road in London were used as sampling sites to evaluate how model predictions differed from observed PM2.5 concentrations. Screen plots and statistical tests indicated that, at the Sacramento site, CALINE4 and CAL3QHC performed moderately well, while AERMOD under-predicted PM2.5 concentrations. For the London site, both CALINE4 and CAL3QHC resulted in overpredictions when incremental concentrations due to on-road emission sources were low, while underpredictions occurred when incremental concentrations were high. The street canyon effect and receptor location likely contributed to the relatively poor performance of the models at the London site.

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Review of environmental software in Asia

Meenakshi¹,

Khan

Kumar³

2007

Environ. Prog.

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Application of the United States environmental protection agency's AERMOD model to an industrial area

Cited by 7 publications

References 3 publications

Application of the United States environmental protection agency's AERSCREEN to the air quality problems

Application of the United States environmental protection agency's AERSCREEN to the air quality problems

Predicting Near-Road PM_2.5 Concentrations

Review of environmental software in Asia

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Application of the United States environmental protection agency's AERMOD model to an industrial area

Cited by 7 publications

References 3 publications

Application of the United States environmental protection agency's AERSCREEN to the air quality problems

Application of the United States environmental protection agency's AERSCREEN to the air quality problems

Predicting Near-Road PM2.5 Concentrations

Review of environmental software in Asia

Contact Info

Product

Resources

About

Predicting Near-Road PM_2.5 Concentrations