Evaluation of operational on-line-coupled regional air quality models over Europe and North America in the context of AQMEII phase 2. Part I: Ozone

Abstract

The second phase of the Air Quality Model Evaluation International Initiative (AQMEII) brought together sixteen modeling groups from Europe and North America, running eight operational online-coupled air quality models over Europe and North America on common emissions and boundary conditions. With the advent of online-coupled models providing new capability to quantify the effects of feedback processes, the main aim of this study is to compare the response of coupled air quality models to simulate levels of O 3 over the two continental regions. The simulated annual, seasonal, continental and sub-regional ozone surface concentrations and vertical profiles for the year 2010 have been evaluated against a large observational database from different measurement networks operating in Europe and North America. Results show a general model underestimation of the annual surface ozone levels over both continents reaching up to 18% over Europe and 22% over North America. The observed temporal variations are successfully reproduced with correlation coefficients larger than 0.8. Results clearly show that the simulated levels highly depend on the meteorological and chemical configurations used in the models, even within the same modeling system. The seasonal and sub-regional analyses show the models' tendency to overestimate surface ozone in all regions during autumn and underestimate in winter. Boundary conditions strongly influence ozone predictions especially during winter and autumn, whereas during summer local production dominates over regional transport. Daily maximum 8-hour averaged surface ozone levels below 50-60 g m-3 are overestimated by all models over both continents while levels over 120-140 g m-3 are underestimated, suggesting that models have a tendency to severely under-predict high O 3 values that are of concern for air quality forecast and control policy applications.

Air quality modelling in the summer over the eastern Mediterranean using WRF-Chem: chemistry and aerosol mechanism intercomparison

“…During the second phase of the Air Quality Model Evaluation International Initiative (AQMEII), the majority of the modelling groups using the RMS and CM mechanisms with the WRF-Chem model also reported O 3 concentrations overestimation over the eastern Mediterranean (Im et al, 2015a). However, Mar et al (2016) reported an underestimation of about 5 ppbV on summertime O 3 concentrations WRF-Chem model using the RMS mechanism.…”

“…Model performance was strongly influenced from the boundary conditions, especially during autumn and winter. Regarding particulate matter 2.5 µm or less in diameter (PM 2.5 ) concentrations, large overestimations over Europe were reported (Im et al, 2015a). Tuccella et al (2012) compared WRF-Chem model output against ground-based observations over the European domain for the year 2007 with time-invariant boundary conditions.…”

Evaluation of the high resolution WRF-Chem (v3.4.1) air quality forecast and its comparison with statistical ozone predictions

“…Besides KRV, the Mediterranean KOP and OTL stations, as well as the rural ZAV site, are stations with comparatively high measured nighttime O 3 levels, which results in a low overall bias for all hourly O 3 values for these stations (from −2 to −7 µg m −3 ). Namely, the WRF-Chem model cannot capture well the profound nighttime O 3 reductions (shown also by Žabkar et al, 2013;Im et al, 2015a), which contributes to the overall overprediction of hourly O 3 concentrations (from 10 to 36 µg m −3 ) for stations with very low measured nighttime O 3 concentrations. For sites with the highest positive bias in 1 h O 3 concentrations (TRB, ZAG, HRA and ISK, with bias of 36, 31, 26 and 32 µg m −3 , respectively), this can also be partly explained by the too high altitude of the stations in model orography (Table 1), since the mean O 3 concentration increases with height.…”

“…4d) showing slight overprediction of daily PM 10 levels at all stations, which is somewhat surprising due to the fact that nearly all current offline and online coupled chemical transport models show large systematic PM 10 underestimations. For example, within the AQMEII exercise, where 17 modelling groups from Europe and North America were brought together, running eight operational online coupled air quality models over Europe and North America, the rural PM 10 concentrations over Europe were underestimated by all models (model configurations) by up to 66 % while for the urban PM 10 concentrations the underestimations were even much larger (up to 75 %) (Im et al, 2015b). The reason for slight overprediction of PM 10 levels could be to some extent attributed to the high model spatial resolution used in our study.…”

Impacts of aerosol-radiation feedback on local air quality during a severe haze episode in Nanjing megacity, eastern China

“…Because NO 2 mixing ratio is influenced by local effects, such as emission and diffusion, the model overestimation of NO 2 in this study may be caused by the uncertainties in emission inventory and boundary layer conditions. The underestimation of O 3 peaks, particularly on clean days before 14 October, might be because of the model inability to accurately represent the stable boundary layer (Holtslag et al, 2013), the overestimation of titration loss near the source regions (Im et al, 2015), and the model errors in temperature fields (Fig. 2).…”