AERMOD for near-road pollutant dispersion: Evaluation of model performance with different emission source representations and low wind options |
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| Institution: | 1. Zachary Department of Civil Engineering, Texas A&M University, College Station, TX 77843-3136, United States;2. Texas A&M Transportation Institute, Texas A&M University System, College Station, TX 77843-3135, United States;3. Department of Civil Engineering, Indian Institute of Technology, Guwahati, India;4. Department of Landscape Architecture and Urban Planning, Texas A&M University, College Station, TX 77840-3137, United States;1. Civil Engineering Department, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, India;2. Civil Engineering Department, Indian Institute of Technology Madras, Chennai, India;1. School of Science and Technology, Tecnológico de Monterrey. Monterrey. Mexico;2. Universidad Tecnológica de Bolívar. Cartagena. Colombia;3. CAIA Eng. Bogotá. Colombia;1. Civil and Environmental Engineering, Technion – Israel Institute of Technology, Israel;2. Center for Risk Analysis, The Gertner Institute, Chaim Sheba Medical Center, Tel Hashomer, 52621, Israel;1. Centre for Environmental Science and Engineering, Indian Institute of Technology, Bombay, Mumbai 400 076, India;2. Council of Scientific & Industrial Research-National Environmental Engineering Research Institute, Mumbai 400 018, India;3. Department of Environmental Science, Aarhus University, P.O. Box 358, Frederiksborgvej 399, 4000 Roskilde, Denmark;4. Department for Environmental, Social and Spatial Change, Roskilde University, Universitetsvej1, 4000 Roskilde, Denmark |
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| Abstract: | The performance of the regulatory dispersion model AERMOD in simulating vehicle-emitted pollutant concentrations near-roadway using area or volume source representation of emissions and with different low wind options was assessed using the SF6 tracer data from the General Motors (GM) Sulfur Dispersion Experiment. At downwind receptor locations, AERMOD, using either area or volume source emissions, can reasonably predict the tracer concentrations near the surface (0.5 m) but the model performance decreases at higher elevations (3.5m and 9.5m above the surface). For upwind receptors, using an area source representation leads to significant under-predictions due to AERMOD’s lack of treatment of lateral plume meander, but using volume source representation leads to over-predictions of upwind concentrations regardless of the low wind options for plume meander. Among the three low wind options currently available in AERMOD, best model performance is obtained with low wind option 3, which treats plume meander with a higher minimal standard deviation of the horizontal crosswind component (σv,min = 0.3 m s−1), eliminates upwind component of dispersion and uses an effective lateral dispersion parameter (σy) to replicate centerline concentration. The optional adjustment of the surface friction velocity in the meteorological preprocessor AERMET does not lead to obvious improvements in predicted near-road concentrations for this application. |
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| Keywords: | Dispersion model AERMOD Mobile sources Near-road Sensitivity Vertical distribution |
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