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Black Carbon measurements in Germany between 1994 and 2014, link to netCDF files (2017)

Kutzner, Rebecca D ; von Schneidemesser, Erika ; Kuik, Friderike ; [et al.]

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In: Supplement to: Kutzner, Rebecca D; von Schneidemesser, Erika; Kuik, Friderike; Quedenau, Jörn; Weatherhead, Betsy; Schmale, Julia (2018): Long-term monitoring of black carbon across Germany. Atmospheric Environment, 185, 41-52, https://doi.org/10.1016/j.atmosenv.2018.04.039

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Publication Date: 2023-01-13

Description: Lately, black carbon (BC) has received significant attention due to its climate-warming properties and adverse health effects. Nevertheless, long-term observations in urban areas are scarce, most likely because BC monitoring is not required by environmental legislation. This, however, handicaps the evaluation of air quality models which can be used to assess the effectiveness of policy measures which aim at reducing BC concentrations. Here, we present a new dataset of atmospheric BC measurements from Germany constructed from over six million measurements at over 170 stations. Data covering the period between 1994 and 2014 were collected from twelve German federal states and the federal Environment Agency (UBA), quality checked and harmonized into a database with comprehensive metadata. The final data in original time resolution are available for download (link will follow). Though assembled in a consistent way, the dataset is characterized by differences in (a) measurement methodologies for determining evolved carbon and optical absorption, (b) covered time periods, and (c) temporal resolutions that ranged from half hourly to 6-daily measurements. Usage of this dataset thus requires a careful consideration of these differences. Our analysis focuses on 2009, the year with the largest data coverage obtained with one single methodology, as well as on the relative changes in long-term trends over ten years. Stations are grouped into the following categories: urban background, traffic, industrial, and rural. For 2009, we find that BC concentrations at traffic sites were at least twice as high as at urban background, industrial and rural sites. Weekly cycles are most prominent at traffic stations, however, the presence of differences in concentrations during the week and on weekends at other station types suggests that traffic plays an important role throughout the full network. Generally higher concentrations and weaker weekly cycles during the winter months point towards the influence of other sources such as domestic heating. Regarding the long-term trends, advanced statistical techniques allow us to account for instrumentation changes and to separate seasonal and long-term changes in our dataset. Analysis shows a downward trend in BC at nearly all locations and in all conditions, with a high level of confidence for the period of 2005-2014. In depth analysis indicates that background BC is decreasing slowly, while the occurrences of high concentrations are decreasing more rapidly. In summary, legislation - both in Europe and locally - to reduce particulate emissions and indirectly BC appear to be working, based on this analysis. Human health and climate impacts are likely to be diminished because of the improvements in air quality.

Keywords: Germany; MULT; Multiple investigations

Type: Dataset

Format: application/zip, 20.7 MBytes

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Tropospheric Ozone Assessment Report, links to Global surface ozone datasets (2017)

Schultz, Martin G ; Schröder, Sabine ; Lyapina, Olga ; [et al.]

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In: Supplement to: Schultz, Martin G; Schröder, Sabine; Lyapina, Olga; Cooper, Owen R; Galbally, Ian; Petropavlovskikh, Irina; von Schneidemesser, Erika; Tanimoto, Hiroshi; Elshorbany, Yasin; Naja, Manish; Seguel, Rodrigo J; Dauert, Ute; Eckhardt, Paul; Feigenspan, Stefan; Fiebig, Markus; Hjellbrekke, Anne-Gunn; Hong, You-Deog; Kjeld, Peter Christian; Koide, Hiroshi; Lear, Gary; Tarasick, David; Ueno, Mikio; Wallasch, Markus; Baumgardner, Darrel; Chuang, Ming-Tung; Gillett, Robert; Lee, Meehye; Molloy, Suzie; Moolla, Raeesa; Wang, Tao; Sharps, Katrina; Adame, Jose A; Ancellet, Gerard; Apadula, Francesco; Artaxo, Paulo; Barlasina, Maria E; Bogucka, Magdalena; Bonasoni, Paolo; Chang, Limseok; Colomb, Aurelie; Cuevas-Agulló, Emilio; Cupeiro, Manuel; Degorska, Anna; Ding, Aijun; Fröhlich, Marina; Frolova, Marina; Gadhavi, Harish; Gheusi, Francois; Gilge, Stefan; Gonzalez, Margarita Y; Gros, Valérie; Hamad, Samera H; Helmig, Detlev; Henriques, Diamantino; Hermansen, Ove; Holla, Robert; Hueber, Jacques; Im, Ulas; Jaffe, Daniel A; Komala, Ninong; Kubistin, Dagmar; Lam, Ka-Se; Laurila, Tuomas; Lee, Haeyoung; Levy, Ilan; Mazzoleni, Claudio; Mazzoleni, Lynn R; McClure-Begley, Audra; Mohamad, Maznorizan; Murovec, Marijana; Navarro-Comas, Monica; Nicodim, Florin; Parrish, David; Read, Katie Alana; Reid, Nick; Ries, Ludwig; Saxena, Pallavi; Schwab, James J; Scorgie, Yvonne; Senik, Irina; Simmonds, Peter; Sinha, Vinayak; Skorokhod, Andrey I; Spain, Gerard; Spangl, Wolfgang; Spoor, Ronald; Springston, Stephen R; Steer, Kelvyn; Steinbacher, Martin; Suharguniyawan, Eka; Torre, Paul; Trickl, Thomas; Weili, Lin; Weller, Rolf; Xu, Xiaobin; Xue, Likun; Ma, Zhiqiang (2017): Tropospheric Ozone Assessment Report: Database and Metrics Data of Global Surface Ozone Observations. Elementa - Science of the Anthropocene, 5:58, 26 pp, https://doi.org/10.1525/elementa.244

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Publication Date: 2023-11-18

Description: In support of the first Tropospheric Ozone Assessment Report (TOAR) a relational database of global surface ozone observations has been developed and populated with hourly measurement data and enhanced metadata. A comprehensive suite of ozone metrics products including standard statistics, health and vegetation impact metrics, and trend information, are made available through a common data portal and a web interface. These data form the basis of the TOAR analyses focusing on human health, vegetation, and climate relevant ozone issues, which are part of this special feature. By combining the data from almost 10,000 measurement sites around the world with global metadata information, new analyses of surface ozone have become possible, such as the first globally consistent characterisations of measurement sites as either urban or rural/remote. Exploitation of these global metadata allow for new insights into the global distribution, and seasonal and long-term changes of tropospheric ozone. Cooperation among many data centers and individual researchers worldwide made it possible to build the world's largest collection of in-situ hourly surface ozone data covering the period from 1970 to 2015. Considerable effort was made to harmonize and synthesize data formats and metadata information from various networks and individual data submissions. Extensive quality control was applied to identify questionable and erroneous data, including changes in apparent instrument offsets or calibrations. Such data were excluded from TOAR data products. Limitations of a posteriori data quality assurance are discussed. As a result of the work presented here, global coverage of surface ozone data has been significantly extended. Yet, large gaps remain in the surface observation network both in terms of regions without monitoring, and in terms of regions that have monitoring programs but no public access to the data archive. Therefore future improvements to the database will require not only improved data harmonization, but also expanded data sharing and increased monitoring in data-sparse regions.

Keywords: TOAR; Tropospheric Ozone Assessment Report

Type: Dataset

Format: application/zip, 7 datasets

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Exposure to air pollution in Germany for the decade 2010-2019 (APExpose_DE) (2021)

Caseiro, Alexandre ; von Schneidemesser, Erika

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Publication Date: 2024-02-12

Description: In this dataset we present metrics related to the exposure to air pollution in Germany for the decade 2010-2019. The sources used for the production of the dataset were Airbase, from the European Environmental Agency (https://www.eea.europa.eu/themes/air/explore-air-pollution-data) and the CAMS (Copernicus Atmosphere Monitoring Service) global reanalysis EAC4 (https://www.ecmwf.int/en/forecasts/dataset/cams-global-reanalysis). Stations of the types "Traffic" and "Industrial" were left out for being considered unrepresentative to long-term exposure, those of the type "Background" were included. Each station was geo-located within, and each computed yearly value associated to, a NUTS-3 unit. Within each NUTS-3 (Nomenclature of Territorial Units for Statistics) unit and for each metric, the yearly values per station were averaged in three ways, giving preference to different station sitings, each representing a different scenario: average, urban, remote. The monitoring data were produced for the NUTS-3 units and the years where monitoring data for a given pollutant is available. In order to complete the dataset for the NUTS-3 units where no monitoring data for a given pollutant is available, the Copernicus Atmospheric Monitoring Service (CAMS) EAC4 reanalysis (https://www.ecmwf.int/en/forecasts/dataset/cams-global-reanalysis) was used. The yearly-averaged rasters from CAMS were vectorized and scaled to available monitoring data to obtain values for each NUTS-3 units. As a final step, the Airbase and CAMS derived data were combined to produce the APExpose_DE dataset. Each record (each line in the file) corresponds to a NUTS-3 unit (identified by its name and its code), and a scenario, for a given year. There are 402 NUTS-3 units in Germany and 3 scenarios were developed, the total number of records in the dataset is 1206 per year, or 12060 for the entire study period. Each record includes a numeric value for each metric considered. The ASCII format of the provided dataset enables a simple access and workup. The NUTS-3 code, provided for each record, enables linking the dataset to other, possibly vectorized, datasets at the NUTS-3 or coarser level.

Keywords: Ahrweiler; Aichach-Friedberg; air pollution; Alb-Donau-Kreis; Altenburger_Land; Altenkirchen_(Westerwald); Altmarkkreis_Salzwedel; Altötting; Alzey-Worms; Amberg; Amberg-Sulzbach; Ammerland; Anhalt-Bitterfeld; Ansbach_city; Aschaffenburg_city; Augsburg_city; Aurich; Bad_Dürkheim; Bad_Kissingen; Bad_Kreuznach; Bad_Tölz-Wolfratshausen; Baden-Baden; Bamberg_city; Barnim; Bautzen_city; Bayreuth_city; Berchtesgadener_Land; Bergstraße; Berlin; Bernkastel-Wittlich; Biberach_city; Bielefeld; Birkenfeld; Böblingen; Bochum; Bodenseekreis; Bonn; Börde; Borken; Bottrop; Brandenburg_an_der_Havel; Braunschweig; Breisgau-Hochschwarzwald; Bremen; Bremerhaven; Burgenlandkreis; Calw; Celle; Cham; Chemnitz; Cloppenburg; Coburg_city; Cochem-Zell; Coesfeld; Cottbus; Cuxhaven; Dachau; Dahme-Spreewald; Danube catchment; Darmstadt; Darmstadt-Dieburg; DATE/TIME; Deggendorf; Delmenhorst; Dessau-Roßlau; Diepholz; Dillingen_an_der_Donau; Dingolfing-Landau; Dithmarschen; Donau-Ries; Donnersbergkreis; Dortmund_city; Dresden; Duisburg; Duration; Duration, number of days; Düren; Düsseldorf; Ebersberg; Eichsfeld; Eichstätt; Eifelkreis_Bitburg-Prüm; Eisenach; Elbe-Elster; Emden; Emmendingen; Emsland; Ennepe-Ruhr-Kreis; Enzkreis; Erding; Erfurt; Erlangen; Erlangen-Höchstadt; Erzgebirgskreis; Essen; Esslingen; Euskirchen; Event label; exposure; Flensburg; Forchheim_city; Frankenthal_(Pfalz); Frankfurt_(Oder); Frankfurt_am_Main; Freiburg_im_Breisgau; Freising; Freudenstadt; Freyung-Grafenau; Friesland; Fulda; Fürstenfeldbruck; Fürth_city; Garmisch-Partenkirchen_city; Gelsenkirchen; Gera_city; Germany; Germersheim; Gießen; Gifhorn; Göppingen; Görlitz; Goslar; Gotha; Göttingen; Grafschaft_Bentheim; Greiz; Groß-Gerau; Günzburg; Gütersloh; Hagen; Halle_(Saale); Hamburg; Hameln-Pyrmont; Hamm; Harburg; Harz_city; Haßberge; Havelland; Heidekreis; Heidelberg_city; Heidenheim; Heilbronn_city; Heinsberg; Helmstedt_city; Herford; Herne; Hersfeld-Rotenburg; Herzogtum_Lauenburg; Hildburghausen; Hildesheim; Hochsauerlandkreis; Hochtaunuskreis; Hof_city; Hohenlohekreis; Holzminden; Höxter; Identification; Ilm-Kreis; Ingolstadt; Jena; Jerichower_Land; Kaiserslautern_city; Karlsruhe_city; Karlsruhe_city2; Kassel_city; Kaufbeuren; Kelheim; Kempten_(Allgäu); Kiel_city; Kitzingen; Kleve_city; Koblenz_city; Köln; Konstanz; Krefeld; Kronach; Kulmbach; Kusel; Kyffhäuserkreis; Lahn-Dill-Kreis; Landau_in_der_Pfalz; Landsberg_am_Lech; Landshut_city; LATITUDE; Leer; Leipzig_city; Leverkusen; Lichtenfels; Limburg-Weilburg; Lindau_(Bodensee); Lippe; Location; LONGITUDE; Lörrach; Lübeck; Lüchow-Dannenberg; Ludwigsburg; Ludwigshafen_am_Rhein; Ludwigslust-Parchim; Lüneburg; Magdeburg_city; Main-Kinzig-Kreis; Main-Spessart; Main-Tauber-Kreis; Main-Taunus-Kreis; Mainz_city; Mainz-Bingen; Mannheim; Mansfeld-Südharz; Marburg-Biedenkopf; Märkischer_Kreis; Märkisch-Oderland; Mayen-Koblenz; Mecklenburgische_Seenplatte; Meißen; Memmingen; Merzig-Wadern; Mettmann; Miesbach; Miltenberg; Minden-Lübbecke; Mittelsachsen; MON; Mönchengladbach; Monitoring; Mühldorf_am_Inn; Mülheim_an_der_Ruhr; MULT; Multiple investigations; München_city; Münster; Neckar-Odenwald-Kreis; Neuburg-Schrobenhausen; Neumarkt_in_der_Oberpfalz; Neumünster; Neunkirchen; Neustadt_an_der_Aisch-Bad_Windsheim; Neustadt_an_der_Waldnaab; Neustadt_an_der_Weinstraße; Neu-Ulm; Neuwied; Nienburg_(Weser); Nitric oxide; Nitrogen dioxide; Nordfriesland; Nordhausen; Nordsachsen; Nordwestmecklenburg; Northeim; Nürnberg; Nürnberger_Land; Oberallgäu; Oberbergischer_Kreis; Oberhausen; Oberhavel; Oberspreewald-Lausitz; Odenwaldkreis; Oder-Spree; Offenbach; Offenbach_am_Main; Oldenburg_city; Olpe; Ortenaukreis; Osnabrück_city; Ostalbkreis; Ostallgäu; Osterholz_city; Osterode_am_Harz; Ostholstein; Ostprignitz-Ruppin; Ozone; Ozone, daily maximum; Paderborn; Particulate matter, 〈 10 µm; Particulate matter, 〈 2.5 µm; Passau_city; Peine; Pfaffenhofen_an_der_Ilm; Pforzheim; Pinneberg_city; Pirmasens; Plön_city; Potsdam; Potsdam-Mittelmark; Prignitz; Rastatt; Ravensburg; Recklinghausen; Regen; Regensburg_city; Region_Hannover; Regionalverband_Saarbrücken; Remscheid; Rems-Murr-Kreis; Rendsburg-Eckernförde; Reutlingen; Rhein-Erft-Kreis; Rheingau-Taunus-Kreis; Rhein-Hunsrück-Kreis; Rheinisch-Bergischer_Kreis; Rhein-Kreis_Neuss; Rhein-Lahn-Kreis; Rhein-Neckar-Kreis; Rhein-Pfalz-Kreis; Rhein-Sieg-Kreis; Rhön-Grabfeld; Rosenheim_city; Rostock_city; Rotenburg_(Wümme); Roth_city; Rottal-Inn; Rottweil; Saale-Holzland-Kreis; Saalekreis; Saale-Orla-Kreis; Saalfeld-Rudolstadt; Saarlouis; Saarpfalz-Kreis; Sächsische_Schweiz-Osterzgebirge; Salzgitter; Salzlandkreis; Scenario; Schaumburg; Schleswig-Flensburg; Schmalkalden-Meiningen; Schwabach; Schwäbisch_Hall; Schwalm-Eder-Kreis; Schwandorf; Schwarzwald-Baar-Kreis; Schweinfurt_city; Schwerin; Segeberg; Siegen-Wittgenstein; Sigmaringen; Soest; Solingen; Sömmerda; Sonneberg; Speyer; Spree-Neiße; St._Wendel; Stade; Städteregion_Aachen; Starnberg; Steinburg; Steinfurt; Stendal; Stormarn; Straubing; Straubing-Bogen; Stuttgart; Südliche_Weinstraße; Südwestpfalz; Suhl; Teltow-Fläming; Tirschenreuth; Traunstein; Trier; Trier-Saarburg; Tübingen; Tuttlingen; Uckermark; Uelzen; Ulm; Unna; Unstrut-Hainich-Kreis; Unterallgäu; Vechta; Verden; Viersen; Vogelsbergkreis; Vogtlandkreis; Vorpommern-Greifswald; Vorpommern-Rügen; Vulkaneifel; Waldeck-Frankenberg; Waldshut; Warendorf; Wartburgkreis; Weiden_in_der_Oberpfalz; Weilheim-Schongau; Weimar; Weimarer_Land; Weißenburg-Gunzenhausen; Werra-Meißner-Kreis; Wesel; Wesermarsch; Westerwaldkreis; Wetteraukreis; Wiesbaden; Wilhelmshaven; Wittenberg; Wittmund; Wolfenbüttel; Wolfsburg; Worms; Wunsiedel_im_Fichtelgebirge; Wuppertal; Würzburg_city; Zollernalbkreis; Zweibrücken; Zwickau

Type: Dataset

Format: text/tab-separated-values, 192960 data points

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Spatial Variability of Carbonaceous Aerosol Concentrations in East and West Jerusalem (2010)

von Schneidemesser, Erika ; Zhou, Jiabin ; Stone, Elizabeth A. ; [et al.]

American Chemical Society

In: Environmental Science & Technology. 2010; 44(6): 1911-1917. Published 2010 Mar 15. doi: 10.1021/es9014025.

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Publication Date: 2010-03-15

Print ISSN: 0013-936X

Electronic ISSN: 1520-5851

Topics: Chemistry and Pharmacology , Energy, Environment Protection, Nuclear Power Engineering

Published by American Chemical Society

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An assessment of perceptions of air quality surrounding the implementation of a traffic-reduction measure in a local urban environment (2018)

Schmitz, Seán ; Weiand, Laura ; Becker, Sophia ; [et al.]

Elsevier

In: Sustainable Cities and Society. 2018; 41: 525-537. Published 2018 Aug 01. doi: 10.1016/j.scs.2018.06.011.

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Publication Date: 2018-08-01

Print ISSN: 2210-6707

Topics: Architecture, Civil Engineering, Surveying , Sociology

Published by Elsevier

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Tropospheric Ozone Assessment Report: Present-day ozone distribution and trends relevant to human health (2018)

Fleming, Zoë L. ; Doherty, Ruth M. ; Von Schneidemesser, Erika ; [et al.]

University of California Press

In: Elementa: Science of the Anthropocene. 2018; 6(1): 12. Published 2018 Feb 05. doi: 10.1525/elementa.273.

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Publication Date: 2018-02-05

Description: This study quantifies the present-day global and regional distributions (2010–2014) and trends (2000–2014) for five ozone metrics relevant for short-term and long-term human exposure. These metrics, calculated by the Tropospheric Ozone Assessment Report, are: 4thhighest daily maximum 8-hour ozone (4MDA8); number of days with MDA8 〉 70 ppb (NDGT70), SOMO35 (annual Sum of Ozone Means Over 35 ppb) and two seasonally averaged metrics (3MMDA1; AVGMDA8). These metrics were explored at ozone monitoring sites worldwide, which were classified as urban or non-urban based on population and nighttime lights data. Present-day distributions of 4MDA8 and NDGT70, determined predominantly by peak values, are similar with highest levels in western North America, southern Europe and East Asia. For the other three metrics, distributions are similar with North–South gradients more prominent across Europe and Japan. Between 2000 and 2014, significant negative trends in 4MDA8 and NDGT70 occur at most US and some European sites. In contrast, significant positive trends are found at many sites in South Korea and Hong Kong, with mixed trends across Japan. The other three metrics have similar, negative trends for many non-urban North American and some European and Japanese sites, and positive trends across much of East Asia. Globally, metrics at many sites exhibit non-significant trends. At 59% of all sites there is a common direction and significance in the trend across all five metrics, whilst 4MDA8 and NDGT70 have a common trend at ~80% of all sites. Sensitivity analysis shows AVGMDA8 trends differ with averaging period (warm season or annual). Trends are unchanged at many sites when a 1995–2014 period is used; although fewer sites exhibit non-significant trends. Over the longer period 1970–2014, most Japanese sites exhibit positive 4MDA8/SOMO35 trends. Insufficient data exist to characterize ozone trends for the rest of Asia and other world regions.

Electronic ISSN: 2325-1026

Topics: Geosciences

Published by University of California Press

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