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Source-Receptor and Inverse Modelling to quantify urban PARTiculate emissions (SRIMPART)

image of Source-Receptor and Inverse Modelling to quantify urban PARTiculate emissions (SRIMPART)

Airborne particulate matter (PM) is considered to be a significant health risk for humans. Yet, concentration levels in much of Europe still remain high. One of the major emission sources of primary PM2.5 (airborne particle matter with a diameter < 2.5 m) in Nordic countries is wood burning due to domestic heating. Unfortunately, emission inventories for wood burning are difficult to determine and there is a large uncertainty in the impact of these emissions on air quality. In SRIMPART we have applied independent methods to assess the contribution of wood burning to the total PM2.5 concentrations in three Nordic cities (Oslo, Lycksele and Helsinki). These methods include receptor modelling, based on chemical analysis of filter samples, and inverse modelling using dispersion models. The results show that estimates of emissions based on wood consumption or based on the methods applied in SRIMPART have a similar level of uncertainty and so it is not possible to categorically state which is the most correct. However, both methods do agree within their respective uncertainties and this provides support that the long term average emissions from wood burning are correct to within a factor of two.

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Results of the dispersion modelling

In this section the results of the dispersion modelling, as well as sensitivity analysis of the models, are reported. Dispersion models have been applied in Oslo, Lycksele, Gävle and Helsinki. At all of these sites, with the exception of Gävle, monitoring data from other measurement sites were also available for assessment of the model and these are additionally used here. These observational data may not necessarily cover the same period as the receptor modelling. The results presented here are based on all the available PM2.5 data.

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