Development of Traffic Air Quality Simulation Model

The U.S. Environmental Protection Agency currently promulgates the use of CAL3QHC to model the concentrations of carbon monoxide near roadway intersections. The steady-state and macroscopic methods used in this model represent rough approximations of the physical phenomena that occur at intersection...

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Veröffentlicht in:Transportation research record 2006-01, Vol.1987 (1987), p.73-81
Hauptverfasser: Kim, Brian, Wayson, Roger, Fleming, Gregg
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container_title Transportation research record
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creator Kim, Brian
Wayson, Roger
Fleming, Gregg
description The U.S. Environmental Protection Agency currently promulgates the use of CAL3QHC to model the concentrations of carbon monoxide near roadway intersections. The steady-state and macroscopic methods used in this model represent rough approximations of the physical phenomena that occur at intersections and are unintuitive for the users. Therefore, the traffic air quality simulation model (TRAQSIM) was developed to create a theoretically more realistic (more natural), easier to understand, and more flexible modeling environment than CAL3QHC. Instead of the steady-state plume equations used in CAL3QHC, TRAQSIM models dispersion through the use of Gaussian puffs emitted from discrete moving sources in a traffic simulation environment. Although most components incorporated in TRAQSIM are not new, the combination of these components within a fully integrated environment is new and provides the potential for a more direct (more logical) expansion of modeling capabilities. As part of an initial validation assessment, a relative comparison of the results obtained with CAL3QHC and TRAQSIM showed that TRAQSIM produced a more intuitively correct spatial allocation of concentrations. The validation assessment also showed good agreement by both models when the data obtained with the models were compared with the measured data, with overall R values of .721 for CAL3QHC and .605 for TRAQSIM. Although these values appear to favor CAL3QHC, the analysis of individual cases showed mixed results (i.e., six cases favored CAL3QHC and five cases favored TRAQSIM). Therefore, additional assessments with larger data sets will need to be conducted before any definitive conclusions can be made. This paper describes the data and methodologies used to develop TRAQSIM and the initial validation work.
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The steady-state and macroscopic methods used in this model represent rough approximations of the physical phenomena that occur at intersections and are unintuitive for the users. Therefore, the traffic air quality simulation model (TRAQSIM) was developed to create a theoretically more realistic (more natural), easier to understand, and more flexible modeling environment than CAL3QHC. Instead of the steady-state plume equations used in CAL3QHC, TRAQSIM models dispersion through the use of Gaussian puffs emitted from discrete moving sources in a traffic simulation environment. Although most components incorporated in TRAQSIM are not new, the combination of these components within a fully integrated environment is new and provides the potential for a more direct (more logical) expansion of modeling capabilities. As part of an initial validation assessment, a relative comparison of the results obtained with CAL3QHC and TRAQSIM showed that TRAQSIM produced a more intuitively correct spatial allocation of concentrations. The validation assessment also showed good agreement by both models when the data obtained with the models were compared with the measured data, with overall R values of .721 for CAL3QHC and .605 for TRAQSIM. Although these values appear to favor CAL3QHC, the analysis of individual cases showed mixed results (i.e., six cases favored CAL3QHC and five cases favored TRAQSIM). Therefore, additional assessments with larger data sets will need to be conducted before any definitive conclusions can be made. 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As part of an initial validation assessment, a relative comparison of the results obtained with CAL3QHC and TRAQSIM showed that TRAQSIM produced a more intuitively correct spatial allocation of concentrations. The validation assessment also showed good agreement by both models when the data obtained with the models were compared with the measured data, with overall R values of .721 for CAL3QHC and .605 for TRAQSIM. Although these values appear to favor CAL3QHC, the analysis of individual cases showed mixed results (i.e., six cases favored CAL3QHC and five cases favored TRAQSIM). Therefore, additional assessments with larger data sets will need to be conducted before any definitive conclusions can be made. 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