Details:

• Creators:
  Farzaneh, Reza ; Vallamsundar, Suriya ; Jaikumar, Rohit ; Venugopal, Madhusudan ; Askariyeh, Mohammad ; ... More +

  Farzaneh, Reza ; Vallamsundar, Suriya ; Jaikumar, Rohit ; Venugopal, Madhusudan ; Askariyeh, Mohammad ; Johnson, Jeremy ; Li, Wen-Whai ; Chavez, Mayra C ; Ramirez, Ivan M Less -
• Corporate Creators:
  Texas A&M Transportation Institute
• Corporate Contributors:
  Texas. Dept. of Transportation. Research and Technology Implementation Office ; United States. Department of Transportation. Federal Highway Administration

  Texas. Dept. of Transportation. Research and Technology Implementation Office ; United States. Department of Transportation. Federal Highway Administration Less -
• Subject/TRT Terms:
  [+]

  AERMOD Air Dispersion Air Quality CAL3QHCR Case Studies Conformity Data Analysis Data Research Evaluation Evaluation And Assessment Hot-Spot Analysis Monitoring Near-road NEPA Particulate Matter Particulates Sensitivity Analysis Transportation Conformity
• Publication/ Report Number:
  FHWA/TX-20/0-6943-R1
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  November 2016–August 2019
• Corporate Publisher:
  Texas. Dept. of Transportation. Research and Technology Implementation Office
• Abstract:
  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.
• Format:
  PDF
• Funding:
  Project 0-6943
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  [+]

  urn:sha256:f2572731a09e81e01acf3fe0a08d9ff89ef3997e2c0ba2102129bbfdb4716970
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/56552/dot_56552_DS1.pdf
• File Type:
  [PDF-8.97 MB]