TxDOT Research Library - Publication Details

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Title:

Evaluation of Air Quality Models with Near-Road Monitoring Data: Technical Report

Report No.:

FHWA/TX-20/0-6943-R1

Authors:

by Reza Farzaneh [and eight others]

Published:

2020

College Station, Texas

Texas A & M Transportation Institute

Type:

Online document

1 PDF (172 pages)

Online Access:

https://tti.tamu.edu/documents/0-6943-R1.pdf

Access Note:

9.3 MB

Summary

Air dispersion models (air quality models) are used in evaluation of transportation projects to ensure their compliance with federal regulations including the National Environmental Policy Act and transportation conformity quantitative hot-spot analysis requirements. The literature indicates a wide range of variabilities involved in the modeling process for the particulate matter (PM) hot-spot analysis. Sparse real-world data have limited the ability to evaluate the variabilities involved in the PM hot-spot analysis process. Availability of near-road monitoring data has provided a new source of data to address this gap. The objective of this study was to perform a modeling evaluation of the regulatory hot spot analysis and conduct a data research of the near-road monitoring observations to evaluate the potential association between the near-road PM2.5 concentrations and the key parameters. The study was performed for two case study sites in Texas, namely Houston and Fort Worth. The modeling process evaluation consisted of investigating the model behavior and variabilities involved in the PM2.5 hot-spot process through a series of sensitivity analyses. The results of the modeling variability analysis highlighted significant variations of the estimated near-road concentrations as a result of typical modeling options and data sources used in conducting a PM2.5 hot-spot analysis. The range of variability was highest for the model options, followed by model choice, and data source. In addition to sensitivity analysis, the data exploration indicated that the background concentration is the dominating factor in estimating the near-road PM2.5 concentrations. Traffic volume and speed were found to have a relatively weak association with the near-road concentrations of PM2.5 for the two case study sites. Wind direction and speed were found to have a stronger association with the concentrations; however, the lack of hourly near-road concentration data at the time of this study prevented a detailed analysis of this potential correlation at an hourly resolution.

Publ. Place

College Station, Texas

Contents

Chapter 1. Introduction --
Chapter 2. Literature Review and State-of-Practice --
Chapter 3. Study Design and Case Study Protocols --
Chapter 4. Data Exploration Research --
Chapter 5. Modeling Approach and Data --
Chapter 6. Modeling Scenarios and Results --
Chapter 7. Qualitative Evaluation --
Chapter 8. Findings and Conclusions --
Appendix A. Meteorological Data --
Appendix B. Background Concentration --
Appendix C. Time Series Plots

Notes

"Published: October 2020"

Study Number

TxDOT Research Project 0-6943

Study Title

Evaluation of Air Quality Models with Near-Road Monitoring Data

Study Sponsor

Lead University

TTI

Print Copy

Collection:

TxDOT/University Research Online Only

Call Number:

6943-1

OCLC No.

1286277033

More Like This

TxDOT Research Projects Database

Page:

Topics

Air quality
Case studies
Data analysis
Environmental impacts
Evaluation
Monitoring
Nonattainment areas
Particles
Pollution
Sensitivity analysis

Proper Names

TxDOT ENV Division

Places

Fort Worth (Tex.)
Houston (Tex.)

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blc2242

Cited in 2023 NCHRP Research Report 1058, "Assessing Air Pollution Dispersion Models for Emissions Regulation."

8/8/2023 at 10:34 AM

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Study

TxDOT Research Project 0-6943

Contributors

Farzaneh, Mohamadreza
Vallamsundar, Suriyapriya, 1983-
Jaikumar, Rohit
Venugopal, Madhusudhan
Askariyeh, Mohammad Hashem
Johnson, Jeremy D. (Jeremy Don)
Li, Wen-Whai
Chavez, Mayra Consuelo
Ramirez, Ivan M.

Texas A & M Transportation Institute
University of Texas at El Paso

Updated

7/1/2025 15:09:21

Cataloged

October 19, 2020 10:53:18

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