ALBERT

Description: The US EPA regional emission model SMOKE was adopted and modified to create temporally and spatially distributed emission for Europe and surrounding countries based on official reports and public domain data only. The aim is to develop a flexible model capable of creating consistent high resolution emission data for long-term runs of Chemical Transport Models (CTM). This modified version of SMOKE, called SMOKE for EUROPE (SMOKE-EU) was successfully used to create hourly gridded emissions for the timespan 1970–2010. In this paper the SMOKE-EU model and the underlying European datasets are introduced. Emission data created by SMOKE-EU for the year 2000 are evaluated by comparison to data of three different state of the art emission models. Differences of SMOKE-EU to those models were in the same range as the differences amongst them. Further, concentrations of criteria pollutants calculated by the CTM CMAQ using the four different emission datasets were compared against EMEP measurements with hourly and daily resolution. Using SMOKE-EU emissions O3, NO2 and SO4 could be modelled most reliably. The amount of simulated concentrations within a factor of 2 (F2) of the observations for these species are: O3 (F2=0.79 N=329 197), NO2 (F2=0.55 N=11 465), and SO4 (F2=0.62 N=17 536). The lowest values were found for NH4 (F2=0.34 N=7400) and NO3 (F2=0.25 N=6184). NH4 concentrations were generally overestimated, leading to a fractional bias (FB) averaged over 22 measurement stations of (FB=0.83±0.41) while better agreements with observations were found for SO4 (FB=0.06±0.38, 51 stations) and NO3 (FB=0.13±0.75, 18 stations). CMAQ simulations using the three other emission datasets were similar to those modelled using SMOKE-EU emissions. Highest differences where found for NH4 while O3 concentrations were almost identical. The results of this comparison confirm that it is adequate to use emissions created by SMOKE-EU as input for CTMs.

Description: The evaluation of regional air quality models is a challenging task, not only for the intrinsic complexity of the topic but also in view of the difficulties in finding sufficiently abundant, harmonized and time/space-well-distributed measurement data. This study, conducted in the framework of AQMEII (Air Quality Model Evaluation International Initiative), evaluates 4-D model predictions obtained from 15 modelling groups and relating to the air quality of the full year of 2006 over the North American and European continents. The modelled variables are ozone, CO, wind speed and direction, temperature, and relative humidity. Model evaluation is supported by the high quality in-flight measurements collected by instrumented commercial aircrafts in the context of the MOZAIC programme. The models are evaluated at five selected domains positioned around major airports, four in North America (Portland, Philadelphia, Atlanta, Dallas) and one in Europe (Frankfurt). Due to the extraordinary scale of the exercise (number of models and variables, spatial and temporal extent), this study is primarily aimed at illustrating the potential for using MOZAIC data for regional-scale evaluation and the capabilities of models to simulate concentration and meteorological fields in the vertical rather than just at the ground. We apply various approaches, metrics, and methods to analyze this complex dataset. Results of the investigation indicate that, while the observed meteorological fields are modelled with some success, modelling CO in and above the boundary layer remains a challenge and modelling ozone also has room for significant improvement. We note, however, that the high sensitivity of models to height, season, location, and metric makes the results rather difficult to interpret and to generalize. With this work, though, we set the stage for future process-oriented and in-depth diagnostic analyses.