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.
Ziel des Projektes war die Entwicklung eines Tools zur Bereitstellung einer neuen Ozonvorhersage zur Information und ggf. Warnung der Öffentlichkeit. Dafür wurde zunächst die Vorhersagequalität des Modellensembles aus dem europäischen Copernicus Atmosphärendienst (CAMS) getestet. Im zweiten Schritt wurden einfache Korrekturverfahren anhand der CAMS-Daten erprobt und in einem Tool für den operationellen Betrieb implementiert. Die Ozonvorhersagen können somit täglich aufbereitet und der Öffentlichkeit über die Homepage des Umweltbundesamtes zur Verfügung gestellt werden.
The 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.
A portable Fourier transform spectrometer (FTS), model EM27/SUN, was deployed onboard the research vessel Polarstern to measure the column-average dry air mole fractions of carbon dioxide (XCO2) and methane (XCH4) by means of direct sunlight absorption spectrometry. We report on technical developments as well as data calibration and reduction measures required to achieve the targeted accuracy of fractions of a percent in retrieved XCO2 and XCH4 while operating the instrument under field conditions onboard the moving platform during a 6-week cruise on the Atlantic from Cape Town (South Africa, 34° S, 18° E; 5 March 2014) to Bremerhaven (Germany, 54° N, 19° E; 14 April 2014). We demonstrate that our solar tracker typically achieved a tracking precision of better than 0.05° toward the center of the sun throughout the ship cruise which facilitates accurate XCO2 and XCH4 retrievals even under harsh ambient wind conditions. We define several quality filters that screen spectra, e.g., when the field of view was partially obstructed by ship structures or when the lines-of-sight crossed the ship exhaust plume. The measurements in clean oceanic air, can be used to characterize a spurious air-mass dependency. After the campaign, deployment of the spectrometer alongside the TCCON (Total Carbon Column Observing Network) instrument at Karlsruhe, Germany, allowed for determining a calibration factor that makes the entire campaign record traceable to World Meteorological Organization (WMO) standards. Comparisons to observations of the GOSAT satellite and concentration fields modeled by the European Centre for Medium-Range Weather Forecasts (ECMWF) Copernicus Atmosphere Monitoring Service (CAMS) demonstrate that the observational setup is well suited to provide validation opportunities above the ocean and along interhemispheric transects.