Using Archived ITS Data for Sensitivity Analysis in the Estimation of Mobile Source Emissions

University Transportation Centers Program2000PDFTech ReportTurner, Shawn M.Gajewski, Byron J.Widenthal, MarieDresser, George B.Texas Transportation InstituteSouthwest Region University Transportation Center (U.S.)Southwest Region University Transportation Center (U.S.)United StatesSpeed dataTraffic dataIntelligent transportation systemsPollutantsSensitivity analysisEstimatesTraffic volumeTraffic modelsExhaust gasesMotor vehiclesPeriods of the dayHoursArchived dataData aggregationInput dataSan AntonioSWUTC/00/167406-1The study described in this paper demonstrates the use of archived ITS data from San Antonio's TransGuide traffic management center (TMC) for sensitivity analyses in the estimation of on-road mobile source emissions. Because of the stark comparison between previous speed/volume data sets used for emissions analyses and ITS data sets, the primary goal of the research team was to ascertain the effects that the additional level of detail in the ITS data sets had on estimating emissions. In particular, researchers wanted to determine the effects of input data aggregation level on emission estimates. The authors found that for monthly total emission estimates, aggregation level had little effect on the sum total of emissions. Differences between using 20-second and 60-minute speed and volume data were less than 5%, and aggregated data typically underestimated emissions estimates. When calculating emissions for particular hours-of-day, however, the authors found that aggregation level had a moderate effect on emission estimates, ranging to as much as 20% during the early morning hours of light traffic. Emission differences for NOx were never more than 15%, presumably due to the flat shape of the NOx curve. The authors conclude that, for existing applications and models, data aggregation may not have significant effects on the model estimate. The results largely depend on the 1) nature and complexity of the relationship between input data and unknown variable (e.g., shape of the emission curve or form of the equation); or 2) the time frame/duration of the analysis.131