The effects of vehicular exhaust buoyancy during worst case pollution scenarios near roadways
- Univ. of California, Davis, CA (United States)
The California Department of Transportation (CALTRANS) has been using CALINE4, a gaussian finite line-source dispersion model, to estimate air pollutant concentrations near roadways given an estimate of traffic flow rates, vehicular emission factors, roadway geometry, and local meteorology. Modelers have typically used CALINE4 to simulate low wind near parallel thermally stable conditions to estimate a worst case pollution scenario (i.e., highest predicted pollutant concentrations) for a proposed roadway. In October 1995, the University of California, Davis (UCD), in conjunction with the CALTRANS Environmental Program, began a two-year investigation to determine if CALINE4 was adequately predicting CO concentrations during worst case meteorological conditions. Based on physical reasoning and a literature review of several highway dispersion studies conducted in the late 1970`s, it was reasoned that gaussian models may over-predict CO concentrations during worst case scenarios because these models do not adequately parameterize the increased vertical dispersion of pollutants due to vehicular emission buoyancy. To explore the role that exhaust buoyancy plays in roadway pollutant dispersion, a series of experiments were conducted on I-80 (near Sacramento) during winter pre-dawn commute hours. Results of the dispersion studies were inconclusive due to difficulty in capturing sufficiently low wind speed conditions during the sampling effort, however, in a compare-contrast study of field measurements versus CALINE4 predictions it was verified that CALINE4 adequately predicts both the magnitude and qualitative shape of non-worst case pollution scenarios. In addition, based on integrated mass flux from downwind CO concentration and wind profiles it was found that the use of CT-EMFAC, a regional scale emission factor model, overpredicted observed modal emissions by as much as 250 to 480%.
- OSTI ID:
- 362049
- Report Number(s):
- CONF-980632--
- Country of Publication:
- United States
- Language:
- English
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