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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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Case study selection and description of sites

Two Nordic cities and one combination of two cities, where both measurement and modelling activities have been undertaken, are selected for this paper. These are Oslo (Norway), Helsinki (Finland) and Lycksele and Gävle (Sweden). In regard to the last the city of Gävle, this is only included in the study for the uncertainty assessment of the dispersion modelling as no measurements of PM2.5 are available there. All of these cities have been found in previous studies (Hedberg et al., 2006; Krecl, et al. 2007; Krecl et al, 2008a; Krecl et al. 2008b; Kauhaniemi et al., 2008, Laupsa et al., 2008; Larssen et al. 2007) to have a significant proportion of their PM2.5 contribution originating in domestic wood burning. A brief description is provided in this section of the cities, the study periods and the available data for use in this paper.

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