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- ItemInsights into the deterministic skill of air quality ensembles from the analysis of AQMEII data(München : European Geopyhsical Union, 2016) Kioutsioukis, Ioannis; Im, Ulas; Solazzo, Efisio; Bianconi, Roberto; Badia, Alba; Balzarini, Alessandra; Baró, Rocío; Bellasio, Roberto; Brunner, Dominik; Chemel, Charles; Curci, Gabriele; van der Gon, Hugo Denier; Flemming, Johannes; Forkel, Renate; Giordano, Lea; Jiménez-Guerrero, Pedro; Hirtl, Marcus; Jorba, Oriol; Manders-Groot, Astrid; Neal, Lucy; Pérez, Juan L.; Pirovano, Guidio; San Jose, Roberto; Savage, Nicholas; Schroder, Wolfram; Sokhi, Ranjeet S.; Syrakov, Dimiter; Tuccella, Paolo; Werhahn, Johannes; Wolke, Ralf; Hogrefe, Christian; Galmarini, StefanoSimulations from chemical weather models are subject to uncertainties in the input data (e.g. emission inventory, initial and boundary conditions) as well as those intrinsic to the model (e.g. physical parameterization, chemical mechanism). Multi-model ensembles can improve the forecast skill, provided that certain mathematical conditions are fulfilled. In this work, four ensemble methods were applied to two different datasets, and their performance was compared for ozone (O3), nitrogen dioxide (NO2) and particulate matter (PM10). Apart from the unconditional ensemble average, the approach behind the other three methods relies on adding optimum weights to members or constraining the ensemble to those members that meet certain conditions in time or frequency domain. The two different datasets were created for the first and second phase of the Air Quality Model Evaluation International Initiative (AQMEII). The methods are evaluated against ground level observations collected from the EMEP (European Monitoring and Evaluation Programme) and AirBase databases. The goal of the study is to quantify to what extent we can extract predictable signals from an ensemble with superior skill over the single models and the ensemble mean. Verification statistics show that the deterministic models simulate better O3 than NO2 and PM10, linked to different levels of complexity in the represented processes. The unconditional ensemble mean achieves higher skill compared to each station's best deterministic model at no more than 60 % of the sites, indicating a combination of members with unbalanced skill difference and error dependence for the rest. The promotion of the right amount of accuracy and diversity within the ensemble results in an average additional skill of up to 31 % compared to using the full ensemble in an unconditional way. The skill improvements were higher for O3 and lower for PM10, associated with the extent of potential changes in the joint distribution of accuracy and diversity in the ensembles. The skill enhancement was superior using the weighting scheme, but the training period required to acquire representative weights was longer compared to the sub-selecting schemes. Further development of the method is discussed in the conclusion.
- ItemSea salt emission, transport and influence on size-segregated nitrate simulation: A case study in northwestern Europe by WRF-Chem(München : European Geopyhsical Union, 2016) Chen, Ying; Cheng, Yafang; Ma, Nan; Wolke, Ralf; Nordmann, Stephan; Schüttauf, Stephanie; Ran, Liang; Wehner, Birgit; Birmili, Wolfram; van der Gon, Hugo A.C. Denier; Mu, Qing; Barthel, Stefan; Spindler, Gerald; Stieger, Bastian; Müller, Konrad; Zheng, Guang-Jie; Pöschl, Ulrich; Su, Hang; Wiedensohler, AlfredSea salt aerosol (SSA) is one of the major components of primary aerosols and has significant impact on the formation of secondary inorganic particles mass on a global scale. In this study, the fully online coupled WRF-Chem model was utilized to evaluate the SSA emission scheme and its influence on the nitrate simulation in a case study in Europe during 10–20 September 2013. Meteorological conditions near the surface, wind pattern and thermal stratification structure were well reproduced by the model. Nonetheless, the coarse-mode (PM1 − 10) particle mass concentration was substantially overestimated due to the overestimation of SSA and nitrate. Compared to filter measurements at four EMEP stations (coastal stations: Bilthoven, Kollumerwaard and Vredepeel; inland station: Melpitz), the model overestimated SSA concentrations by a factor of 8–20. We found that this overestimation was mainly caused by overestimated SSA emissions over the North Sea during 16–20 September. Over the coastal regions, SSA was injected into the continental free troposphere through an “aloft bridge” (about 500 to 1000 m above the ground), a result of the different thermodynamic properties and planetary boundary layer (PBL) structure between continental and marine regions. The injected SSA was further transported inland and mixed downward to the surface through downdraft and PBL turbulence. This process extended the influence of SSA to a larger downwind region, leading, for example, to an overestimation of SSA at Melpitz, Germany, by a factor of ∼ 20. As a result, the nitrate partitioning fraction (ratio between particulate nitrate and the summation of particulate nitrate and gas-phase nitric acid) increased by about 20 % for the coarse-mode nitrate due to the overestimation of SSA at Melpitz. However, no significant difference in the partitioning fraction for the fine-mode nitrate was found. About 140 % overestimation of the coarse-mode nitrate resulted from the influence of SSA at Melpitz. In contrast, the overestimation of SSA inhibited the nitrate particle formation in the fine mode by about 20 % because of the increased consumption of precursor by coarse-mode nitrate formation.
- ItemKinetic modeling studies of SOA formation from α-pinene ozonolysis(München : European Geopyhsical Union, 2017) Gatzsche, Kathrin; Iinuma, Yoshiteru; Tilgner, Andreas; Mutzel, Anke; Berndt, Torsten; Wolke, RalfThis paper describes the implementation of a kinetic gas-particle partitioning approach used for the simulation of secondary organic aerosol (SOA) formation within the SPectral Aerosol Cloud Chemistry Interaction Model (SPACCIM). The kinetic partitioning considers the diffusion of organic compounds into aerosol particles and the subsequent chemical reactions in the particle phase. The basic kinetic partitioning approach is modified by the implementation of chemical backward reaction of the solute within the particle phase as well as a composition-dependent particle-phase bulk diffusion coefficient. The adapted gas-phase chemistry mechanism for α-pinene oxidation has been updated due to the recent findings related to the formation of highly oxidized multifunctional organic compounds (HOMs). Experimental results from a LEAK (Leipziger Aerosolkammer) chamber study for α-pinene ozonolysis were compared with the model results describing this reaction system. The performed model studies reveal that the particle-phase bulk diffusion coefficient and the particle-phase reactivity are key parameters for SOA formation. Using the same particle-phase reactivity for both cases, we find that liquid particles with higher particle-phase bulk diffusion coefficients have 310 times more organic material formed in the particle phase compared to higher viscous semi-solid particles with lower particle-phase bulk diffusion coefficients. The model results demonstrate that, even with a moderate particle-phase reactivity, about 61% of the modeled organic mass consists of reaction products that are formed in the liquid particles. This finding emphasizes the potential role of SOA processing. Moreover, the initial organic aerosol mass concentration and the particle radius are of minor importance for the process of SOA formation in liquid particles. A sensitivity study shows that a 22-fold increase in particle size merely leads to a SOA increase of less than 10%. Due to two additional implementations, allowing backward reactions in the particle phase and considering a composition-dependent particle-phase bulk diffusion coefficient, the potential overprediction of the SOA mass with the basic kinetic approach is reduced by about 40%. HOMs are an important compound group in the early stage of SOA formation because they contribute up to 65% of the total SOA mass at this stage. HOMs also induce further SOA formation by providing an absorptive medium for SVOCs (semi-volatile organic compounds). This process contributes about 27% of the total organic mass. The model results are very similar to the LEAK chamber results. Overall, the sensitivity studies demonstrate that the particle reactivity and the particle-phase bulk diffusion require a better characterization in order to improve the current model implementations and to validate the assumptions made from the chamber simulations. The successful implementation and testing of the current kinetic gas-particle partitioning approach in a box model framework will allow further applications in a 3-D model for regional-scale process investigations.
- ItemEvaluation of the size segregation of elemental carbon (EC) emission in Europe: Influence on the simulation of EC long-range transportation(München : European Geopyhsical Union, 2016) Chen, Ying; Cheng, Ya-Fang; Nordmann, Stephan; Birmili, Wolfram; van der Gon, Hugo A.C. Denier; Ma, Nan; Wolke, Ralf; Wehner, Birgit; Sun, Jia; Spindler, Gerald; Mu, Qing; Pöschl, Ulrich; Su, Hang; Wiedensohler, AlfredElemental Carbon (EC) has a significant impact on human health and climate change. In order to evaluate the size segregation of EC emission in the EUCAARI inventory and investigate its influence on the simulation of EC long-range transportation in Europe, we used the fully coupled online Weather Research and Forecasting/Chemistry model (WRF-Chem) at a resolution of 2 km focusing on a region in Germany, in conjunction with a high-resolution EC emission inventory. The ground meteorology conditions, vertical structure and wind pattern were well reproduced by the model. The simulations of particle number and/or mass size distributions were evaluated with observations at the central European background site Melpitz. The fine mode particle concentration was reasonably well simulated, but the coarse mode was substantially overestimated by the model mainly due to the plume with high EC concentration in coarse mode emitted by a nearby point source. The comparisons between simulated EC and Multi-angle Absorption Photometers (MAAP) measurements at Melpitz, Leipzig-TROPOS and Bösel indicated that the coarse mode EC (ECc) emitted from the nearby point sources might be overestimated by a factor of 2–10. The fraction of ECc was overestimated in the emission inventory by about 10–30 % for Russia and 5–10 % for Eastern Europe (e.g., Poland and Belarus). This incorrect size-dependent EC emission results in a shorter atmospheric life time of EC particles and inhibits the long-range transport of EC. A case study showed that this effect caused an underestimation of 20–40 % in the EC mass concentration in Germany under eastern wind pattern.