Date of Award

2021-08-01

Degree Name

M.S.En.E.

Department

Civil Engineering

Advisor(s)

Weh-Whai Li

Abstract

Departments of transportation across the United States have presented concerns over making the American Meteorological Society (AMS) and U.S. Environmental Protection Agency (EPA) Regulatory Model (AERMOD) the new regulatory air dispersion model for federally funded transportations projects. Concerns arose from the lack of data presented on its use in transportation projects. AERMOD was developed to present a steady-state air dispersion model used on industrial complexes which present static emission sources unlike the dynamic sources presented by transportation projects. We used multiple analytical and statistical methods to further understand the sensitivity of the model results based on different factors and therefore create data and cases of what is expected from the model when used in dynamic transportation projects. Eight factors which were the focus of this study are surface roughness, emission type, meteorology, traffic, source characterization, environment, yearly difference, and albedo & Bowen ratio. Adjusting the different factors and comparing them with a baseline scenario made following the guidelines promulgated in the federal regulatory PM2.5 Hot-Spot Analysis, we analyze how each of the factors affects the results produced. This study generates emission and air dispersion estimates using traffic and meteorological data from 2016 and 2015 allowing us to compare our results with already existing monitored data. Following regulatory modeling guidelines produced accurate results, it was also found that certain regulatory guidelines such as the use of 5-year offsite data can become counterproductive when compared to monitored data. We found that adjusting factors such as surface roughness, albedo, and Bowen ratio significantly affect the ultimate results. Correct calculation of these factors was found to be significant. Not only do we provide data to demonstrate how different factors affect the model but most importantly provide a guideline for the reproduction of this study in multiple areas across the world to create a deeper understanding of the use of AERMOD for transportation projects.

Language

en

Provenance

Received from ProQuest

File Size

124 p.

File Format

application/pdf

Rights Holder

Ivan Mauricio Ramirez

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