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

US Transportation Collection2020PDFTech ReportFarzaneh, RezaVallamsundar, SuriyaJaikumar, RohitVenugopal, MadhusudanAskariyeh, MohammadJohnson, JeremyLi, Wen-WhaiChavez, Mayra CRamirez, Ivan MTexas A&M Transportation InstituteTexas. Dept. of Transportation. Research and Technology Implementation OfficeUnited States. Department of Transportation. Federal Highway AdministrationTexas. Dept. of Transportation. Research and Technology Implementation OfficeUnited StatesAir qualityCase studiesData analysisEvaluationMonitoringParticulatesSensitivity analysisEvaluation and assessmentConformityNear-roadAir DispersionAERMODCAL3QHCRData ResearchParticulate MatterHot-Spot AnalysisTransportation ConformityNEPAFHWA/TX-20/0-6943-R1Project 0-6943November 2016\u2013August 2019Air 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 PM\u2082.\u2085 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 PM\u2082.\u2085 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 PM\u2082.\u2085 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 PM\u2082.\u2085 concentrations. Traffic volume and speed were found to have a relatively weak association with the near-road concentrations of PM\u2082.\u2085 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.113