| On-road vehicles have been identified as one of the major sources of urban airpollution for megacities in China. In particular, the curb concentrations of traffic-relatedpollutants are in general higher than the urban average, leading to more significant publichealth effects. Therefore, characterizing vehicle emissions and curb concentrations ofvehicular pollutants for typical roads is essential to mitigate urban air pollution.In this research, field investiagtion of real-world traffic flow data were conducted ontypical roads in Beijing to derive key inputs, including hourly profiles for total trafficvolume, fleet composition by vehicle category, and proportion of on-road trucks registeredin other provinces except Beijing (i.e., outsider trucks). Average speed information hasbeen also collected from previous studies. The Emission Factor Model for the BeijingVehicle Fleet (EMBEV) was applied to estimate emission factors and emission intensity ofNOX、PM2.5and BC for those typical roads. Furhermore, the curb concentrations ofprimary vehicular popllutants were simulated with special attentions paid to theapplicability of dispersion models, meteorolical effects and potential contribution by thoseoutsider trucks with higher PM2.5and BC emission factors.Our results show that two peaks of hourly traffic volume occoured during morning andevening rush period for each road. Average hourly emission factors of NOX, PM2.5and BCwere strongly correlated with hourly volume proportions of heavy-duty diesel vehicles (e.g.,diesel buses and trucks). However, hourly total traffic volumes and the higher emissionfactor during the night time both impacted emission intensity results. Taking the SouthThird Ring Road for example, the peak of hourly average BC emission factors, about40mg/(km·veh), occured during the night time when trucks were allowed to drive withinurban aera. On the other hand, the peaks of hourly BC emission intensity occurredsychoronically in the morning and evening rush period, appriximately100g/(km·h). Theimpact of outsider trucks was significant to emission intensity during night time. Taking theNorth Fourth Ring Road and the South Third Ring Road for example,50%~60%ofemission might increase. Two models, the CALINE3and the AERMOD, were applied to estimate curbconcentrations of vehicle-emitted pollutants (e.g., NOX, PM2.5and BC). Results showedthat the AERMOD could provide more reasonable simulations compared to the CALINE3based on the real-time air quality monitoring data. Taking BC for example, simulatedaverage BC concentration contributed by primary vehicle emissions during the day andnight time of summer period were1.6±2.7μg/m3and3.3±1.4μg/m3, respectively, for theNorth Fourth Ring Road as of the year2009. In winter period, simulated concentrationsincreased to3.4±4.1μg/m3and3.7±4.6μg/m3, respectively. For urban roads, light-dutypassenger cars and diesel buses were leading contributors among all vehicle categories tocurb BC concentration during the day time. During the night time, diesel trucks became thedominant contributor. The unfavorable dispersion conditions during the night time and thewinter time have been identified the more important factor leading to higher curb pollutantconcentrations. Futhermore, if the outsider trucks are taken into account for the NorthFourth Ring Road during the night time, the average BC concentration contributed by on-road vehicles can rise to5.6μg/m3during the night time. If all those outsider trucks driveinto urban area during the noon period, when the dispersion conditions are usually mostfavorbale, the traffic-contributed BC concentrations during the night time can be controlledbelow2μg/m3, with a very slght increase of BC concentration (~0.2μg/m3) during thenoon period. Our research can improve the understanding of policy-makers for controllingvehicle emissions and urban air pollution in the future. |
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