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A platform for research: civil engineering, architecture and urbanism
The impact of incorporating spatial, temporal variability on running stabilized mobile emissions inventories
AbstractTo improve prediction of hourly running stabilized vehicle volumes for emissions modeling, a new method was recently developed that disaggregates the period-based volumes produced by travel demand models into hourly volumes using observed traffic count data and multivariate multiple regression. In addition to a more robust method for estimating hourly volumes, the method also provides a means for introducing spatial variability of mobile emissions into air quality modeling. In this study, the new methodology is used to disaggregate travel demand volumes both temporally and spatially. The impact of the increased spatial and temporal resolution on estimated mobile emissions was then investigated for San Diego and Los Angeles. The results indicate that actual on-road running stabilized vehicle emissions exhibit less pronounced peaking during the day and a much slower decay of emissions during the late evening hours than would be predicted by the current method for allocating period volumes to specific hours within that period. The new method also identifies corridors (or clustered locations) producing the bulk of hourly emissions. This study should prove useful for further refining of control strategies for transportation conformity purposes and for improving the performance of air quality models, which tend to underpredict ozone concentrations.
The impact of incorporating spatial, temporal variability on running stabilized mobile emissions inventories
AbstractTo improve prediction of hourly running stabilized vehicle volumes for emissions modeling, a new method was recently developed that disaggregates the period-based volumes produced by travel demand models into hourly volumes using observed traffic count data and multivariate multiple regression. In addition to a more robust method for estimating hourly volumes, the method also provides a means for introducing spatial variability of mobile emissions into air quality modeling. In this study, the new methodology is used to disaggregate travel demand volumes both temporally and spatially. The impact of the increased spatial and temporal resolution on estimated mobile emissions was then investigated for San Diego and Los Angeles. The results indicate that actual on-road running stabilized vehicle emissions exhibit less pronounced peaking during the day and a much slower decay of emissions during the late evening hours than would be predicted by the current method for allocating period volumes to specific hours within that period. The new method also identifies corridors (or clustered locations) producing the bulk of hourly emissions. This study should prove useful for further refining of control strategies for transportation conformity purposes and for improving the performance of air quality models, which tend to underpredict ozone concentrations.
The impact of incorporating spatial, temporal variability on running stabilized mobile emissions inventories
Niemeier, D.A. (author)
Atmospheric Environment ; 37 ; 27-37
2003-03-10
11 pages
Article (Journal)
Electronic Resource
English