Particle concentrations, dispersion modelling and evaluation in southern Sweden

Abstract

Health impact assessments of differential air pollution rely on epidemiologically established relationships between concentration levels where people are exposed and adverse health outcomes. To assess air pollution concentrations, land use regression is commonly used. However, an alternative tool is dispersion modelling, where a detailed inventory of pollution sources together with meteorological data drives calculations of compound dispersion. With this, both spatial and temporal variation can be assessed. In this study, we evaluated results of a Gaussian dispersion model applied to an emissions inventory for Scania, the southernmost county in Sweden. The dispersion considered was particulate matter of aerodynamic diameter < 10 µm (PM10), particulate matter of aerodynamic diameter < 2.5 µm (PM2.5) and black carbon (BC) during an 11-year period (2000–2011). Mean concentrations and 95th percentiles expressed in µg/m3 ranged from 10.1 to 12.6 and 16.6 to 20.7 for PM2.5 and from 14.0 to 18.8 and 22.6 to 27.0 for PM10, respectively. Seven monitoring stations were used for evaluation. Correlations (R2) ranged from 0.44 to 0.86 for PM2.5 (mean bias from − 9.0 to 0.1 µg/m3) and from 0.46 to 0.83 for PM10 (mean bias − 6.1 to 3.5 µg/m3). An evaluated database of PM and BC concentrations for Scania is now available for future exposure assessment projects. Calculations were based on a well-known dispersion model with detailed emission data as input. The evaluation showed correlation coefficients for PM in line with previous literature. The data on PM10, PM2.5 and BC concentrations will, therefore, be used in subsequent studies, epidemiological as well as health impact assessments.