Person: Nordmann, Stephan
Loading...
Email Address
Birth Date
Research Projects
Organizational Units
Job Title
Last Name
Nordmann
First Name
Stephan
Name
9 results
Search Results
Now showing 1 - 9 of 9
Publication Improvement of the predictive quality of CAMS forecasts for ozone and PM10 in comparison with measured values(2019) Neunhäuserer, Lina; Diegmann, Volker; Breitenbach, Yvonne; Nordmann, StephanThe Copernicus Atmosphere Monitoring Service (CAMS) provides, inter alia, daily forecasts for the next 96 hours in hourly resolution for various pollutants. These forecasts are based on the results of chemical transport models and their ensemble. Due to their horizontal grid resolution, the CAMS ensemble usually provides too low maximum ozone concentrations in comparison with measurements at background stations. This has a negative impact on the correct prediction of threshold value exceedances at very high ozone concentrations. The project presented here explored to what extent the predictive quality of CAMS ozone forecasts for Germany can be improved by post-processing with different correction techniques, particularly with regard to the detection of limit value exceedances. In addition, interpolation of the correction factors derived at measurement locations onto the CAMS grid and subsequent correction of the CAMS forecasts are discussed. A corresponding study was carried out for CAMS PM10 forecasts. © 2019 Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes, HARMO. All rights reserved.Publication Luftqualität 2017(2018) Dauert, Ute; Feigenspan, Stefan; Himpel, Thomas; Kessinger, Susan; Minkos, Andrea; Nordmann, StephanDiese Auswertung der Luftqualität im Jahr 2017 in Deutschland basiert auf vorläufigen, noch nicht abschließend geprüften Daten aus den Luftmessnetzen der Bundesländer und des Umweltbundesamtes, Stand 23.01.2018. Aufgrund der umfangreichen Qualitätssicherung in den Messnetzen stehen die endgültigen Daten erst Mitte 2018 zur Verfügung. Die jetzt vorliegenden Daten lassen aber eine generelle Einschätzung des vergangenen Jahres zu. Betrachtet werden die Schadstoffe Feinstaub (PM10 und PM2,5), Stickstoffdioxid (NO2) sowie Ozon (O3), da bei diesen nach wie vor Überschreitungen der geltenden Grenz- und Zielwerte zum Schutz der menschlichen Gesundheit auftreten. Quelle: https://www.umweltbundesamt.dePublication Sea salt emission, transport and influence on size-segregated nitrate simulation: a case study in northwestern Europe by WRF-Chem(2016) Chen, Ying-Yuan; Barthel, Stefan; Cheng, Yafang; Birmili, Wolfram; Ma, Nan; Wolke, Ralf; Schüttauf, Stephanie; Ran, Liang; Wehner, Birgit; Nordmann, Stephan; Denier van der Gon, Hugo A.C.; Mu, Quing; 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 bridgeŁ (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.Quelle: http://www.atmos-chem-phys.netPublication Air quality 2017(2018) Dauert, Ute; Feigenspan, Stefan; Himpel, Thomas; Kessinger, Susan; Minkos, Andrea; Nordmann, StephanThis evaluation of air quality in Germany in the year 2017 is based on preliminary data which has not yet been conclusively audited from the air monitoring networks of the federal states and the UBA, valid on 23rd January 2018. Due to the comprehensive quality assurance within the monitoring networks, the final data will only be available in mid-2018. The currently available data allows for a general assessment of the past year. The following pollutants were subject to consideration: particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2) and ozone (O3), since, the limit and target values for the protection of human health are still exceeded for such substances. Quelle: https://www.umweltbundesamt.dePublication CEN-Normungsaktivitäten zur Qualitätssicherung von Ausbreitungsrechnungen und Verursacheranalysen(2017) Quass, Ulrich; Nordmann, Stephan; Schlünzen, K. Heinke; Müller, Wolfgang J.Publication Evaluation of the size segregation of elemental carbon (EC) emission in Europe: influence on the simulation of EC long-range transportation(2016) Chen, Ying-Yuan; Birmili, Wolfram; Cheng, Ya-Fang; Denier van der Gon, Hugo A.C.; Ma, Nan; Wolke, Ralf; Nordmann, Stephan; 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.Quelle: http://www.atmos-chem-phys.netPublication Ultrafeine Partikel(Umweltbundesamt, 2022) Birmili, Wolfram; Elsasser, Michael; Gerwig, Holger; Hellack, Bryan; Juhrich, Kristina; Langner, Marcel; Liesegang, Christian; Nordmann, Stephan; Rüdiger, Julian; Straff, Wolfgang; Tobollik, Myriam; Vitzthum von Eckstädt, Christiane; Wichmann-Fiebig, MarionDieser Text stellt den Stand und die Lücken des Wissens zu Ultrafeinen Partikeln aus regulatorischer Sicht dar. Obwohl bereits erste Schritte der Vereinheitlichung gemacht sind zeigt sich ein deutlicher Normungs-, Regelungs- und Untersuchungsbedarf. Quelle: Texte-BandPublication Evaluierung flächenhafter Daten der Luftschadstoffbelastung in Deutschland aus der Chemie-Transportmodellierung(2020) Mues, Andrea C.; Nordmann, Stephan; Feigenspan, StefanPublication Dynamic evaluation of modeled ozone concentrations in Germany with four chemistry transport models(2023) Thürkow, Markus; Schaap, Martijn; Minkos, Andrea; Kranenburg, Richard; Nordmann, StephanSimulating the ozone variability at regional scales using chemistry transport models (CTMs) remains a challenge. We designed a multi-model intercomparison to evaluate, for the first time, four regional CTMs on a national scale for Germany. Simulations were conducted with LOTOS-EUROS, REM-CALGRID, COSMO-MUSCAT and WRF-Chem for January 1st to December 31st, 2019, using prescribed emission information. In general, all models show good performance in the operational evaluation with average temporal correlations of MDA8 O3 in the range of 0.77-0.87 and RMSE values between 16.3 (micro)g m-3 and 20.6 (micro)g m-3. On average, better models' skill has been observed for rural background stations than for the urban background stations as well as for springtime compared to summertime. Our study confirms that the ensemble mean provides a better model-measurement agreement than individual models. All models capture the larger local photochemical production in summer compared to springtime and observed differences between the urban and the rural background. We introduce a new indicator to evaluate the dynamic response of ozone to temperature. During summertime a large ensemble spread in the ozone sensitivities to temperature is found with (on average) an underestimation of the ozone sensitivity to temperature, which can be linked to a systematic underestimation of mid-level ozone concentrations. During springtime we observed an ozone episode that is not covered by the models which is likely due to deficiencies in the representation of background ozone in the models. We recommend to focus on a diagnostic evaluation aimed at the model descriptions for biogenic emissions and dry deposition as a follow up and to repeat the operational and dynamic analysis for longer timeframes. © 2023 The Authors