@misc{hamer_the_urban_2020, author={Hamer, P.D.,Walker, S.-E.,Sousa-Santos, G.,Vogt, M.,Vo-Thanh, D.,Lopez-Aparicio, S.,Schneider, P.,Ramacher, M.,Karl, M.}, title={The urban dispersion model EPISODE v10.0 – Part 1: An Eulerian and sub-grid-scale air quality model and its application in Nordic winter conditions}, year={2020}, howpublished = {journal article}, doi = {https://doi.org/10.5194/gmd-13-4323-2020}, abstract = {This paper describes the Eulerian urban dispersion model EPISODE. EPISODE was developed to address a need for an urban air quality model in support of policy, planning, and air quality management in the Nordic, specifically Norwegian, setting. It can be used for the calculation of a variety of airborne pollutant concentrations, but we focus here on the implementation and application of the model for NO2 pollution. EPISODE consists of an Eulerian 3D grid model with embedded sub-grid dispersion models (e.g. a Gaussian plume model) for dispersion of pollution from line (i.e. roads) and point sources (e.g. chimney stacks). It considers the atmospheric processes advection, diffusion, and an NO2 photochemistry represented using the photostationary steady-state approximation for NO2. EPISODE calculates hourly air concentrations representative of the grids and at receptor points. The latter allow EPISODE to estimate concentrations representative of the levels experienced by the population and to estimate their exposure. This methodological framework makes it suitable for simulating NO2 concentrations at fine-scale resolution (<100 m) in Nordic environments. The model can be run in an offline nested mode using output concentrations from a global or regional chemical transport model and forced by meteorology from an external numerical weather prediction model; it also can be driven by meteorological observations. We give a full description of the overall model function and its individual components. We then present a case study for six Norwegian cities whereby we simulate NO2 pollution for the entire year of 2015. The model is evaluated against in situ observations for the entire year and for specific episodes of enhanced pollution during winter. We evaluate the model performance using the FAIRMODE DELTA Tool that utilises traditional statistical metrics, e.g. root mean square error (RMSE), Pearson correlation R, and bias, along with some specialised tests for air quality model evaluation. We find that EPISODE attains the DELTA Tool model quality objective in all of the stations we evaluate against. Further, the other statistical evaluations show adequate model performance but that the model scores greatly improved correlations during winter and autumn compared to the summer. We attribute this to the use of the photostationary steady-state scheme for NO2, which should perform best in the absence of local ozone photochemical production. Oslo does not comply with the NO2 annual limit set in the 2008/50/EC directive (AQD). NO2 pollution episodes with the highest NO2 concentrations, which lead to the occurrence of exceedances of the AQD hourly limit for NO2, occur primarily in the winter and autumn in Oslo, so this strongly supports the use of EPISODE for application to these wintertime events. Overall, we conclude that the model is suitable for an assessment of annual mean NO2 concentrations and also for the study of hourly NO2 concentrations in the Nordic winter and autumn environment. Further, in this work we conclude that it is suitable for a range of policy applications specific to NO2 that include pollution episode analysis, evaluation of seasonal statistics, policy and planning support, and air quality management. Lastly, we identify a series of model developments specifically designed to address the limitations of the current model assumptions. Part 2 of this two-part paper discusses the CityChem extension to EPISODE, which includes a number of implementations such as a more comprehensive photochemical scheme suitable for describing more chemical species and a more diverse range of photochemical environments, as well as a more advanced treatment of the sub-grid dispersion.}, note = {Online available at: \url{https://doi.org/10.5194/gmd-13-4323-2020} (DOI). Hamer, P.; Walker, S.; Sousa-Santos, G.; Vogt, M.; Vo-Thanh, D.; Lopez-Aparicio, S.; Schneider, P.; Ramacher, M.; Karl, M.: The urban dispersion model EPISODE v10.0 – Part 1: An Eulerian and sub-grid-scale air quality model and its application in Nordic winter conditions. Geoscientific Model Development. 2020. vol. 13, no. 9, 4323-4353. DOI: 10.5194/gmd-13-4323-2020}}