Mari Kauhaniemi

Increasing the Number of Allergenic Pollen Species in SILAM Forecasts

SILAM has been among the first regional dispersion models to develop the ability to compute pollen emission and dispersion. For previous seasons forecasts have been provided for birch, grasses, olive and ragweed. For the current season this list has been extended by alder and mugwort. The growing number of modelled species makes it possible to draw conclusions from the existing experiences, related to the features of the input data and algorithms applied to describe the pollen emission. We demonstrate, that the currently available options in SILAM allow adding new pollen species with minimal development effort and limited input data, to allow forecasts with comparable quality to the previously developed taxa.

Assessment of Population Exposure to Particulate Matter for London and Helsinki

Most epidemiological studies have been conducted based on relations between pollution concentrations measured at fixed ambient air quality monitoring sites, or modelled values using land-use regression models, and various health indicators. However, such simplistic modelling ignores several crucial factors, such as, (i) the activity patterns of individuals, i.e. people’s day-to-day movements, and (ii) the differences between indoor and outdoor air. We have developed a mathematical model for the determination of human exposure to ambient air pollution in an urban area, called EXPAND (EXposure model for Particulate matter And Nitrogen oxiDes). The model combines (i) predicted concentrations, and (ii) information on people’s activities and location of the population, to evaluate the spatial and temporal variation of average exposure of the urban population to ambient air pollution in different microenvironments. In particular, the model takes into account the movements of the population and the infiltration from outdoor to indoor air. We present fine-resolution numerical results on annual spatial concentration, time activity and population exposures to PM2.5 in London and in the Helsinki Metropolitan Area, for 2008 and 2009. We have shown that the effect of neglecting the movements of the population, which is the currently commonly applied procedure, can result in an underprediction of exposure by several tens of per cent.

A Model Evaluation Strategy Applied to Modelling of PM in the Helsinki Metropolitan Area

We have developed a deterministic urban scale dispersion modelling system further by adding a road dust suspension model. The system includes both vehicular exhaust emissions and suspended road dust. The modelling system was combined with a regional scale chemical transport model for calculations of concentrations in an urban area for the year 2008, and for the year 2010 measured regional background concentration was used. The time series’ were modelled for a spatial area more extensive than before using the FORE road dust suspension model. The predictions were compared against observed concentrations of PM2.5 and PM10. The use of the index of determination (r2) is discussed. We criticize the use of r2 alone as well as in addition to an index of agreement—type measure of agreement, and review the underlying data assumptions for the use of both measures. We then suggest a strategy to develop model evaluation statistical understanding, practice and nomenclature.

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.

Utilization of Meandering in a Receptor-Oriented Solution of the Line Source Dispersion Equation

Lateral dilution in line source dispersion models is usually treated as the sum of short and long period variations of the wind direction and dilution by wind speed perpendicular to the road. We present an alternative solution, where the influence of meandering is estimated assuming normally distributed long term fluctuations of wind direction. The average of receptor-oriented wind direction, which is based on probability distribution, differs substantially from the meteorological mean value in case of wind directions nearly parallel to the road.