Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe – Part 2: Evaluation of chemical concentrations and sensitivity simulations
- ISSN: 1680-7324
- DOI: 10.5194/acp-13-6845-2013
An offline-coupled model (WRF/Polyphemus) and an online-coupled model (WRF/Chem-MADRID) are applied to simulate air quality in July 2001 at horizontal grid resolutions of 0.5° and 0.125° over western Europe. The model performance is evaluated against available surface and satellite observations. The two models simulate different concentrations in terms of domainwide performance statistics, spatial distribution, temporal variations, and column abundance. WRF/Chem-MADRID at 0.5° gives higher values than WRF/Polyphemus for the domainwide mean and over polluted regions in central and southern Europe for all surface concentrations and column variables except for TOR. Compared with observations, WRF/Polyphemus gives better statistical performance for daily HNO<sub>3</sub>, SO<sub>2</sub>, and NO<sub>2</sub> at the EMEP sites, max 1-h O<sub>3</sub> at the AirBase sites, PM<sub>2.5</sub> at the AirBase sites, max 8-h O<sub>3</sub> and PM<sub>10</sub> composition at all sites, column abundance of CO, NO<sub>2</sub>, TOR, and AOD, whereas WRF/Chem-MADRID gives better statistical performance for NH<sub>3</sub>, hourly SO<sub>2</sub>, NO<sub>2</sub>, and O<sub>3</sub> at the AirBase and BDQA sites, max 1-h O<sub>3</sub> at the BDQA and EMEP sites, and PM<sub>10</sub> at all sites. WRF/Chem-MADRID generally reproduces well the observed high hourly concentrations of SO<sub>2</sub> and NO<sub>2</sub> at most sites except for extremely high episodes at a few sites, and WRF/Polyphemus performs well for hourly SO<sub>2</sub> concentrations at most rural or background sites where pollutant levels are relatively low, but it underpredicts the observed hourly NO<sub>2</sub> concentrations at most sites. Both models generally capture well the daytime max 8-h O<sub>3</sub> concentrations and diurnal variations of O<sub>3</sub> with more accurate peak daytime and minimal nighttime values by WRF/Chem-MADRID, but neither models reproduce extremely low nighttime O<sub>3</sub> concentrations at several urban and suburban sites due to underpredictions of NO<sub>x</sub> and thus insufficient titration of O<sub>3</sub> at night. WRF/Polyphemus gives more accurate concentrations of PM<sub>2.5</sub>, and WRF/Chem-MADRID reproduces better the observations of PM<sub>10</sub> concentrations at all sites. The differences between model predictions and observations are mostly caused by inaccurate representations of emissions of gaseous precursors and primary PM species, as well as biases in the meteorological predictions. The differences in model predictions are caused by differences in the heights of the first model layers and thickness of each layer that affect vertical distributions of emissions, model treatments such as dry/wet deposition, heterogeneous chemistry, and aerosol and cloud, as well as model inputs such as emissions of soil dust and sea-salt and chemical boundary conditions of CO and O<sub>3</sub> used in both models. <br><br> WRF/Chem-MADRID shows a higher sensitivity to grid resolution than WRF/Polyphemus at all sites. For both models, the use of a finer grid resolution generally leads to an overall better statistical performance for most variables, with greater spatial details and an overall better agreement in temporal variations and magnitudes at most sites. The use of online BVOC emissions gives better statistical performance for hourly and max 8-h O<sub>3</sub> and PM<sub>2.5</sub> and generally better agreement with their observed temporal variations at most sites. Because it is an online model, WRF/Chem-MADRID offers the advantage to account for various feedbacks between meteorology and chemical species. The simulations show that aerosol leads to reduced net shortwave radiation fluxes, 2-m temperature, 10-m wind speed, PBL height, and precipitation and increases aerosol optical depth, cloud condensation nuclei, cloud optical depth, and cloud droplet number concentrations over most of the domain. However, this model comparison suggests that atmospheric pollutant concentrations are most sensitive in state-of-the-science air quality models to vertical structure, inputs, and parameterizations for dry/wet removal of gases and particles in the model.