Description of the uEMEP_v5 downscaling approach for the EMEP MSC-W chemistry transport model

Abstract. A description of the new air quality downscaling model uEMEP and its combination with the EMEP MSC-W chemistry transport model is presented. uEMEP is based on well known Gaussian modelling principles. The uniqueness of the system is in its combination with the EMEP MSC-W model and the local fraction calculation contained within it. This allows the uEMEP model to be imbedded in the EMEP MSC-W model and downscaling can be carried out anywhere within the EMEP model domain, without any double counting of emissions, if appropriate proxy data is available that describe the spatial distribution of the emissions. This makes the model suitable for high resolution calculations, down to 50 m, over entire countries. An example application, the Norwegian air quality forecasting and assessment system, is described where the entire country is modelled at a resolution of between 250 and 50 m. The model is validated against all available monitoring data, including traffic sites, in Norway. The results of the validation show good results for NO2, which has the best known emissions, and moderately good for PM10 and PM2.5. In Norway the largest contributor to PM, even in cities, is long range transport followed by road dust and domestic heating emissions. These contributors to PM are more difficult to quantify than NO2 exhaust emission from traffic, which is the major contributor to NO2 concentrations. In addition to the validation results a number of verification and sensitivity results are summarised. One verification showed that single annual mean calculations with a rotationally symmetric dispersion kernel give very similar results to the average of an entire year of hourly calculations, reducing the run time for annual means by four orders of magnitude. The uEMEP model, in combination with EMEP MSC-W model, provides a new tool for assessing local scale concentrations and exposure over large regions in a consistent and homogenous way and is suitable for large scale policy applications.