Abstract. The EURODELTA III exercise has facilitated a comprehensive intercomparison and evaluation of chemistry transport model performances. Participating models performed calculations for four 1-month periods in different seasons in the years 2006 to 2009, allowing the influence of different meteorological conditions on model performances to be evaluated. The exercise was performed with strict requirements for the input data, with few exceptions. As a consequence, most of differences in the outputs will be attributed to the differences in model formulations of chemical and physical processes. The models were evaluated mainly for background rural stations in Europe. The performance was assessed in terms of bias, root mean square error and correlation with respect to the concentrations of air pollutants (NO2, O3, SO2, PM10 and PM2.5), as well as key meteorological variables. Though most of meteorological parameters were prescribed, some variables like the planetary boundary layer (PBL) height and the vertical diffusion coefficient were derived in the model preprocessors and can partly explain the spread in model results. In general, the daytime PBL height is underestimated by all models. The largest variability of predicted PBL is observed over the ocean and seas. For ozone, this study shows the importance of proper boundary conditions for accurate model calculations and then on the regime of the gas and particle chemistry. The models show similar and quite good performance for nitrogen dioxide, whereas they struggle to accurately reproduce measured sulfur dioxide concentrations (for which the agreement with observations is the poorest). In general, the models provide a close-to-observations map of particulate matter (PM2.5 and PM10) concentrations over Europe rather with correlations in the range 0.4–0.7 and a systematic underestimation reaching −10 µg m−3 for PM10. The highest concentrations are much more underestimated, particularly in wintertime. Further evaluation of the mean diurnal cycles of PM reveals a general model tendency to overestimate the effect of the PBL height rise on PM levels in the morning, while the intensity of afternoon chemistry leads formation of secondary species to be underestimated. This results in larger modelled PM diurnal variations than the observations for all seasons. The models tend to be too sensitive to the daily variation of the PBL. All in all, in most cases model performances are more influenced by the model setup than the season. The good representation of temporal evolution of wind speed is the most responsible for models' skillfulness in reproducing the daily variability of pollutant concentrations (e.g. the development of peak episodes), while the reconstruction of the PBL diurnal cycle seems to play a larger role in driving the corresponding pollutant diurnal cycle and hence determines the presence of systematic positive and negative biases detectable on daily basis.
information, but will cubically increase computational costs and pose additional challenges 35 concerning high resolution input data. The motivation for the present study was therefore to explore 36 the impact of using finer horizontal grid resolution for policy support applications of the European 37 variability. This study clearly shows that increasing model resolution is advantageous, and that 49 leaving a resolution of 50 km in favour of a resolution between 10 and 20 km is practical and 50worthwhile. As about 70% of the model response to grid resolution is determined by the difference 51 in the spatial emission distribution, improved emission allocation procedures at high spatial and 52 temporal resolution are a crucial factor for further model resolution improvements. 53 54
The CALIOPE-EU high-resolution air quality modeling system, namely WRF-ARW/HERMES-EMEP/CMAQ/BSC-DREAM8b, is developed and applied to Europe (12 km × 12 km, 1hr). The model performances are tested in terms of air quality levels and dynamics reproducibility on a yearly basis. The present work describes a quantitative evaluation of gas phase species (O 3 , NO 2 and SO 2 ) and particulate matter (PM2.5 and PM10) against ground-based measurements from the EMEP (European Monitoring and Evaluation Programme) network for the year 2004. The evaluation is based on statistics. Simulated O 3 achieves satisfactory performances for both daily mean and daily maximum concentrations, especially in summer, with annual mean correlations of 0.66 and 0.69, respectively. Mean normalized errors are comprised within the recommendations proposed by the United States Environmental Protection Agency (US-EPA). The general trends and daily variations of primary pollutants (NO 2 and SO 2 ) are satisfactory. Daily mean concentrations of NO 2 correlate well with observations (annual correlation r=0.67) but tend to be underestimated. For SO 2 , mean concentrations are well simulated (mean bias=0.5 µg m −3 ) with relatively high annual mean correlation (r=0.60), although peaks are generally overestimated. The dynamics of PM2.5 PM2.5 and PM10 is well reproduced (0.49 < r < 0.62), but mean concentrations * Corresponding author.
3 aerosol composition reveled that organic matter is the major component in PM10 and PM2.5, 63 except at rural background sites where secondary inorganic aerosol (SIA) contribution 64 prevailed. The dominant SIA species are ammonium sulfates ((NH 4 ) 2 SO 4 ) and ammonium 65 nitrates (NH 4 NO 3 ) salts. 66The formation of SIA is a two-step process. First, the primary emissions of NO x and SO 2 are 67 oxidized to form aerosol precursor nitric acid (HNO 3 ) and sulfuric acid (H 2 SO 4 ), respectively, 68 precursors of secondary aerosols. Second, a fraction of the H 2 SO 4 , HNO 3 and NH 3 partition 69 between the gas and particle phase according to thermodynamic equilibrium determined by 70 temperature, relatively humidity and molar concentration of SO 4 2-, total nitrate 71 (TNO 3 =HNO 3 + NO 3 -) and total ammonia (TNH 3 =NH 3 + NH 4 + ).
Abstract.The EURODELTA-Trends multi-model chemistry-transport experiment has been designed to facilitate a better understanding of the evolution of air pollution and its drivers for the period 1990-2010 in Europe. The main objective of the experiment is to assess the efficiency of air pollutant emissions mitigation measures in improving regional-scale air quality.The present paper formulates the main scientific questions and policy issues being addressed by the EURODELTATrends modelling experiment with an emphasis on how the design and technical features of the modelling experiment answer these questions.The experiment is designed in three tiers, with increasing degrees of computational demand in order to facilitate the participation of as many modelling teams as possible. The basic experiment consists of simulations for the years 1990, 2000, and 2010. Sensitivity analysis for the same three years using various combinations of (i) anthropogenic emisPublished by Copernicus Publications on behalf of the European Geosciences Union. Eight chemistry-transport models have contributed with calculation results to at least one experiment tier, and five models have -to date -completed the full set of simulations (and 21-year trend calculations have been performed by four models). The modelling results are publicly available for further use by the scientific community.The main expected outcomes are (i) an evaluation of the models' performances for the three reference years, (ii) an evaluation of the skill of the models in capturing observed air pollution trends for the 1990-2010 time period, (iii) attribution analyses of the respective role of driving factors (e.g. emissions, boundary conditions, meteorology), (iv) a dataset based on a multi-model approach, to provide more robust model results for use in impact studies related to human health, ecosystem, and radiative forcing.
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