Abstract. A system for source attribution of tropospheric ozone produced from both NOx and volatile organic compound (VOC) precursors is described, along with its implementation in the Community Earth System Model (CESM) version 1.2.2 using CAM4. The user can specify an arbitrary number of tag identities for each NOx or VOC species in the model, and the tagging system rewrites the model chemical mechanism and source code to incorporate tagged tracers and reactions representing these tagged species, as well as ozone produced in the stratosphere. If the user supplies emission files for the corresponding tagged tracers, the model will produce tagged ozone tracers which represent the contribution of each of the tag identities to the modelled total tropospheric ozone. Our tagged tracers preserve Ox. The size of the tagged chemical mechanism scales linearly with the number of specified tag identities. Separate simulations are required for NOx and VOC tagging, which avoids the sharing of tag identities between NOx and VOC species. Results are presented and evaluated for both NOx and VOC source attribution. We show that northern hemispheric surface ozone is dominated year-round by anthropogenic emissions of NOx, but that the mix of corresponding VOC precursors changes over the course of the year; anthropogenic VOC emissions contribute significantly to surface ozone in winter–spring, while biogenic VOCs are more important in summer. The system described here can provide important diagnostic information about modelled ozone production, and could be used to construct source–receptor relationships for tropospheric ozone.

Abstract. With NO2 limit values being frequently exceeded in European cities, complying with the European air quality regulations still poses a problem for many cities. Traffic is typically a major source of NOx emissions in urban areas. High-resolution chemistry transport modelling can help to assess the impact of high urban NOx emissions on air quality inside and outside of urban areas. However, many modelling studies report an underestimation of modelled NOx and NO2 compared with observations. Part of this model bias has been attributed to an underestimation of NOx emissions, particularly in urban areas. This is consistent with recent measurement studies quantifying underestimations of urban NOx emissions by current emission inventories, identifying the largest discrepancies when the contribution of traffic NOx emissions is high. This study applies a high-resolution chemistry transport model in combination with ambient measurements in order to assess the potential underestimation of traffic NOx emissions in a frequently used emission inventory. The emission inventory is based on officially reported values and the Berlin–Brandenburg area in Germany is used as a case study. The WRF-Chem model is used at a 3 km × 3 km horizontal resolution, simulating the whole year of 2014. The emission data are downscaled from an original resolution of ca. 7 km × 7 km to a resolution of 1 km × 1 km. An in-depth model evaluation including spectral decomposition of observed and modelled time series and error apportionment suggests that an underestimation in traffic emissions is likely one of the main causes of the bias in modelled NO2 concentrations in the urban background, where NO2 concentrations are underestimated by ca. 8 µg m−3 (−30 %) on average over the whole year. Furthermore, a diurnal cycle of the bias in modelled NO2 suggests that a more realistic treatment of the diurnal cycle of traffic emissions might be needed. Model problems in simulating the correct mixing in the urban planetary boundary layer probably play an important role in contributing to the model bias, particularly in summer. Also taking into account this and other possible sources of model bias, a correction factor for traffic NOx emissions of ca. 3 is estimated for weekday daytime traffic emissions in the core urban area, which corresponds to an overall underestimation of traffic NOx emissions in the core urban area of ca. 50 %. Sensitivity simulations for the months of January and July using the calculated correction factor show that the weekday model bias can be improved from −8.8 µg m−3 (−26 %) to −5.4 µg m−3 (−16 %) in January on average in the urban background, and −10.3 µg m−3 (−46 %) to −7.6 µg m−3 (−34 %) in July. In addition, the negative bias of weekday NO2 concentrations downwind of the city in the rural and suburban background can be reduced from −3.4 µg m−3 (−12 %) to −1.2 µg m−3 (−4 %) in January and from −3.0 µg m−3 (−22 %) to −1.9 µg m−3 (−14 %) in July. The results and their consistency with findings from other studies suggest that more research is needed in order to more accurately understand the spatial and temporal variability in real-world NOx emissions from traffic, and apply this understanding to the inventories used in high-resolution chemical transport models.

Abstract. We perform a source attribution for tropospheric and ground-level ozone using a novel technique that accounts separately for the contributions of the two chemically distinct emitted precursors (reactive carbon and oxides of nitrogen) to the chemical production of ozone in the troposphere. By tagging anthropogenic emissions of these precursors according to the geographical region from which they are emitted, we determine source–receptor relationships for ground-level ozone. Our methodology reproduces earlier results obtained via other techniques for ozone source attribution, and it also delivers additional information about the modelled processes responsible for the intercontinental transport of ozone, which is especially strong during the spring months. The current generation of chemical transport models used to support international negotiations aimed at reducing the intercontinental transport of ozone shows especially strong inter-model differences in simulated springtime ozone. Current models also simulate a large range of different responses of surface ozone to methane, which is one of the major precursors of ground-level ozone. Using our novel source attribution technique, we show that emissions of NOx (oxides of nitrogen) from international shipping over the high seas play a disproportionately strong role in our model system regarding the hemispheric-scale response of surface ozone to changes in methane, as well as to the springtime maximum in intercontinental transport of ozone and its precursors. We recommend a renewed focus on the improvement of the representation of the chemistry of ship NOx emissions in current-generation models. We demonstrate the utility of ozone source attribution as a powerful model diagnostic tool and recommend that similar source attribution techniques become a standard part of future model intercomparison studies.

Tropospheric ozone (O 3 ) is an important air pollutant that affects human health, ecosystems, and climate. The contributions of O 3 precursor emissions from different geographical source regions to the O 3 concentration can help to quantify the effects of local versus remotely transported precursors on the O 3 concentration in a certain area. This study presents a "tagging" approach within the WRF-Chem model that attributes O 3 concentration in several European receptor regions to nitrogen oxide (NO x ) emissions from within and outside of Europe during April-September 2010. We also examine the contribution of these different precursor sources to various O 3 metrics and their exceedance events. Firstly, we show that the spatial distributions of simulated monthly mean MDA8 from tagged O 3 source regions and types for late spring, summer, and early autumn 2010 varies with season. For summer conditions, O 3 production is dominated by national and intra-European sources, while in the late spring and early autumn intercontinental transported O 3 is an important contributor to the total O 3 concentration. We have also identified shipping activities in the Mediterranean Sea as an important source of O 3 for the Mediterranean countries, as well as the main contributor to high modelled MDA8 O 3 concentration in the Mediterranean Basin itself. Secondly, to have a better understanding of the origin of MDA8 O 3 exceedances, we compare modelled and observed values of MDA8 O 3 concentration in the Po Valley and Germany-Benelux receptor regions, revealing that the contribution from local sources is about 41 % and 38 % of modelled MDA8 O 3 during the exceedance days, respectively. By examining the relative contributions of remote NO x sources to modelled and observed O 3 exceedance events, we determine that model underrepresentation of long-range O 3 trans-port could be contributing to a general underestimation of modelled O 3 exceedance events in the Germany-Benelux receptor region. Thirdly, we quantify the impact of local vs. non-local NO x precursors on O 3 production for each European receptor region using different O 3 metrics. The comparison between mean, MDA8 and 95th percentile O 3 metrics accentuates the importance of large contributions from locally emitted NO x precursors to the high end of the O 3 distribution. When we compare the vegetation and health metrics, we notice that the SOMO35 and AOT40 indexes exhibit rather similar behaviour, while the W126 index accentuates the importance of local emissions. Overall, this study highlights the importance of a tagging approach to quantify the contribution of local and remote sources to the MDA8 O 3 concentration during several periods as well to different O 3 metrics. Moreover, this method could be applied to assess different mitigation options.Published by Copernicus Publications on behalf of the European Geosciences Union.

Abstract. An evaluation of the meteorology simulated using the Weather Research and Forecast (WRF) model for the region of south Asia and Nepal with a focus on the Kathmandu Valley is presented. A particular focus of the model evaluation is placed on meteorological parameters that are highly relevant to air quality such as wind speed and direction, boundary layer height and precipitation. The same model setup is then used for simulations with WRF including chemistry and aerosols (WRF-Chem). A WRF-Chem simulation has been performed using the state-of-the-art emission database, EDGAR HTAP v2.2, which is the Emission Database for Global Atmospheric Research of the Joint Research Centre (JRC) of the European Commission, in cooperation with the Task Force on Hemispheric Transport of Air Pollution (TF HTAP) organized by the United Nations Economic Commission for Europe, along with a sensitivity simulation using observation-based black carbon emission fluxes for the Kathmandu Valley. The WRF-Chem simulations are analyzed in comparison to black carbon measurements in the valley and to each other. The evaluation of the WRF simulation with a horizontal resolution of 3×3 km2 shows that the model is often able to capture important meteorological parameters inside the Kathmandu Valley and the results for most meteorological parameters are well within the range of biases found in other WRF studies especially in mountain areas. But the evaluation results also clearly highlight the difficulties of capturing meteorological parameters in such complex terrain and reproducing subgrid-scale processes with a horizontal resolution of 3×3 km2. The measured black carbon concentrations are typically systematically and strongly underestimated by WRF-Chem. A sensitivity study with improved emissions in the Kathmandu Valley shows significantly reduced biases but also underlines several limitations of such corrections. Further improvements of the model and of the emission data are needed before being able to use the model to robustly assess air pollution mitigation scenarios in the Kathmandu region.