Evaluation of a modelling system for predicting the concentrations of PM 2.5 in an urban area

Abstract

We present a modelling system that contains a treatment of the emissions and atmospheric dispersion of fine particulate matter (PM 2.5) on an urban scale, combined with a statistical model for estimating the contribution of long-range transported aerosols. The model of PM 2.5 emissions includes exhaust emissions, cold starts and driving, as well as, non-exhaust emissions originated from urban vehicular traffic. The influence of primary vehicular emissions from the road and street network was evaluated using a roadside emission and dispersion model, CAR-FMI, in combination with a meteorological pre-processing model, MPP-FMI. We have computed hourly sequential time series of the PM 2.5 concentrations in 2002 in a numerical grid in the Helsinki Metropolitan Area. The predicted results were compared against measured data at two locations in central Helsinki: urban roadside station of Vallila and urban background station of Kallio. The predicted daily average PM 2.5 concentrations agreed well with the measured values; e.g., the index of agreement values were 0.83 and 0.86 at Vallila and Kallio, respectively, and the absolute values of fractional bias ⩽0.13. As expected, the scatter of data points is substantially wider for the hourly concentration values; e.g., the index of agreement values were 0.69 and 0.74. We also computed the spatial concentration distributions of PM 2.5. The predicted contribution from long-range transport to the street level PM 2.5 varied spatially from 40% in the most trafficked areas to nearly 100% in the outskirts of the area. The emissions originated from cold starts and driving were responsible for <4% of the annual average concentrations at the roadside and urban stations. The model can potentially be used as a practical tool of assessment of urban PM 2.5 contributions in various European regions.