Modelling of the urban concentrations of PM<sub>2.5</sub> on a high resolution
for a period of 35 years, for the assessment of lifetime exposure and health
effects
Abstract. Reliable and self-consistent data on air quality is needed for an extensive period of time for conducting long-term, or even lifetime health impact assessments. We have modelled the urban scale concentrations of fine particulate matter (PM2.5) in the Helsinki Metropolitan Area for a period of 35 years, from 1980 to 2014. These high resolution computations included both the emissions originated from vehicular traffic (separately exhaust and suspension emissions) and those from small-scale combustion, and were conducted using the road network dispersion model CAR-FMI and the multiple source Gaussian dispersion model UDM-FMI. The regional background concentrations were evaluated based on reanalyses of the atmospheric composition on global and European scales, using the SILAM model. The modelled concentrations of PM2.5 agreed fairly well or well with the measured data at a regional background station and at four urban measurement stations, during 1999–2014. There was no systematic deterioration of the agreement of predictions and data for earlier years (the 1980's and 1990's), compared with the results for more recent years (2000's and early 2010's). The local vehicular emissions were about five-folds higher in the 1980's, compared with the emissions during the latest considered years. However, the local small-scale combustion emissions increased slightly over time. The highest urban concentrations of PM2.5 occurred in the 1980's; these have since decreased to about to a half of the highest values. However, there is only a very slight decreasing trend of the PM2.5 concentrations during the last decade. Regional background is the largest contribution in this area. Vehicular exhaust has been the most important local source, but the relative shares of both small-scale combustion and vehicular suspension emissions have increased. The study provides long-term, high-resolution concentration databases on regional and urban scales that have been used for the assessment of health effects.