TPS 652: Air pollution exposure modeling 2, Exhibition Hall, Ground floor, August 28, 2019, 3:00 PM - 4:30 PM Background/Aim: Air pollution, a mixture of gases and particles suspended in the air, is the major environmental health threat globally. Assessment of concentrations of air pollution at places where people are exposed is necessary for assessing health impacts from air pollution. Commonly used methods for such assessment are land use regression and dispersion modelling. Dispersion modelling relies on a detailed inventory of pollution sources and calculations of compound dispersion and incorporates both spatial and temporal variation. The objective of this study was to evaluate results of a Gaussian dispersion model applied on an emission inventory for Scania, the southernmost county in Sweden. Methods: Dispersion modeling, based on particulate matter (PM) and Black Carbon (BC) sources during an 11-year period (2000-2011) was performed. For evaluation, concentrations measured at seven monitoring stations were used. Correaltion and bias were studied. Results: Mean concentrations expressed in μg/m3 range from 10.1 - 12.6 and 14 95th percentiles from 16.6 - 20.7 for PM < 2.5 μm in aerodynamic diameter (PM2.5), and between 15 14.0 - 18.8 and 22.6 - 27.0 for PM < 10 μm in aerodynamic diameter (PM10), respectively. Correlations (r2) ranged from 0.44 - 0.86 with mean bias from -8.99 - 0.10μg/m3 for PM2.5 and for PM10 from 0.83 - 0.46 with mean bias from -6.13 - 3.49 μg/m3. These correlations are in agreement with what has been found in studies using other methods such as land use regression, for assessment of air pollutant concentrations. Conclusions: In conclusion, we have a database of PM and BC concentrations based on a well-known dispersion model and detailed emission data evaluated and ready to be used for exposure assessment in epidemiological studies as well as health impact assessment studies.