Inter-comparison of predicted population exposure distributions during four selected episodes in Helsinki and evaluation against measured data
Air pollution causes significant excess mortality and health effects. Action plans required by the EU legislation should optimally account for the complex interactions of population distributions, time-activity and the sources of air pollution. This paper presents FUMAPEX study results on probabilistic exposure modelling for evaluation of population exposure distributions during selected episodes in Helsinki. The air quality model characterised best the episodes of local origin, while highest exposures occurred during a long-range transported episode (average annual exposures exceeded three-fold). Fixed monitoring data represented different population exposure percentiles (from 65th to 95th) depending on the episode type and monitoring station.
Keywords: population exposure, exposure distribution, air pollution, particulate matter, PM25, long-range transportation, inversion, wildfire, action plan, policy, air quality, Helsinki, Finland, exposure modelling