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Sentinel-5P TROPOMI – Ozone (O3), Level 3 – Global

Ozone vertical column density in Dobson Units as derived from Sentinel-5P/TROPOMI observations. The stratospheric ozone layer protects the biosphere from harmful solar ultraviolet radiation. Ozone in troposphere can pose risks to the health of humans, animals, and vegetation. The TROPOMI instrument aboard the SENTINEL-5P space craft is a nadir-viewing, imaging spectrometer covering wavelength bands between the ultraviolet and the shortwave infra-red. TROPOMI's purpose is to measure atmospheric properties and constituents. It is contributing to monitoring air quality and providing critical information to services and decision makers. The instrument uses passive remote sensing techniques by measuring the Top Of Atmosphere (TOA) solar radiation reflected by and radiated from the earth and its atmosphere. The four spectrometers of TROPOMI cover the ultraviolet (UV), visible (VIS), Near Infra-Red (NIR) and Short Wavelength Infra-Red (SWIR) domains of the electromagnetic spectrum, allowing operational retrieval of the following trace gas constituents: Ozone (O3), Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2), Formaldehyde (HCHO), Carbon Monoxide (CO) and Methane (CH4). Daily observations are binned onto a regular latitude-longitude grid. Within the INPULS project, innovative algorithms and processors for the generation of Level 3 and Level 4 products, improved data discovery and access technologies as well as server-side analytics for the users are developed.

METOP GOME-2 - Ozone (O3) - Global

The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Currently, there are three GOME-2 instruments operating on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B, and -C, launched in October 2006, September 2012, and November 2018, respectively. GOME-2 can measure a range of atmospheric trace constituents, with the emphasis on global ozone distributions. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp level 2 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC-SAF). GOME-2 near-real-time products are available already two hours after sensing. The operational ozone total column products are generated using the algorithm GDP (GOME Data Processor) version 4.x integrated into the UPAS (Universal Processor for UV / VIS Atmospheric Spectrometers) processor for generating level 2 trace gas and cloud products. The new improved DOAS-style (Differential Optical Absorption Spectroscopy) algorithm called GDOAS, was selected as the basis for GDP version 4.0 in the framework of an ESA ITT. GDP 4.x performs a DOAS fit for ozone slant column and effective temperature followed by an iterative AMF / VCD computation using a single wavelength. For more details please refer to relevant peer-review papers listed on the GOME and GOME-2 documentation pages: https://atmos.eoc.dlr.de/app/docs/

Bruchfreie Modellierung atmosphärischer Zusammensetzung mit ICON-ART

METOP GOME-2 - Tropospheric Nitrogen Dioxide (NO2) - Global

The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Currently, there are three GOME-2 instruments operating on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B, and -C, launched in October 2006, September 2012, and November 2018, respectively. GOME-2 can measure a range of atmospheric trace constituents, with the emphasis on global ozone distributions. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp level 2 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC-SAF). GOME-2 near-real-time products are available already two hours after sensing. The operational NO2 total column products are generated using the algorithm GDP (GOME Data Processor) version 4.x integrated into the UPAS (Universal Processor for UV / VIS Atmospheric Spectrometers) processor for generating level 2 trace gas and cloud products. The operational NO2 tropospheric column products are generated using the algorithm GDP (GOME Data Processor) version 4.x for NO2 [Valks et al. (2011)] integrated into the UPAS (Universal Processor for UV / VIS Atmospheric Spectrometers) processor for generating level 2 trace gas and cloud products. The total NO2 column is retrieved from GOME solar back-scattered measurements in the visible wavelength region using the DOAS method. An additional algorithm is applied to derive the tropospheric NO2 column: after subtracting the estimated stratospheric component from the total column, the tropospheric NO2 column is determined using an air mass factor based on monthly climatological NO2 profiles from the MOZART-2 model. For more details please refer to relevant peer-review papers listed on the GOME and GOME-2 documentation pages: https://atmos.eoc.dlr.de/app/docs/

METOP GOME-2 - Bromine Monoxide (BrO) - Global

The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Currently, there are three GOME-2 instruments operating on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B and -C, launched in October 2006, September 2012, and November 2018, respectively. GOME-2 can measure a range of atmospheric trace constituents, with the emphasis on global ozone distributions. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp level 2 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC-SAF). GOME-2 near-real-time products are available already two hours after sensing. The operational BrO (Bromine monoxide) total column products are generated using the algorithm GDP (GOME Data Processor) version 4.x integrated into the UPAS (Universal Processor for UV / VIS Atmospheric Spectrometers) processor for generating level 2 trace gas and cloud products. For more details please refer to https://atmos.eoc.dlr.de/app/missions/gome2

METOP GOME-2 - Cloud Top Pressure (CTP) - Global

The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Currently, there are three GOME-2 instruments operating on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B and -C, launched in October 2006, September 2012, and November 2018, respectively. GOME-2 can measure a range of atmospheric trace constituents, with the emphasis on global ozone distributions. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp level 2 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC-SAF). GOME-2 near-real-time products are available already two hours after sensing. OCRA (Optical Cloud Recognition Algorithm) and ROCINN (Retrieval of Cloud Information using Neural Networks) are used for retrieving the following geophysical cloud properties from GOME and GOME-2 data: cloud fraction (cloud cover), cloud-top pressure (cloud-top height), and cloud optical thickness (cloud-top albedo). OCRA is an optical sensor cloud detection algorithm that uses the PMD devices on GOME / GOME-2 to deliver cloud fractions for GOME / GOME-2 scenes. ROCINN takes the OCRA cloud fraction as input and uses a neural network training scheme to invert GOME / GOME-2 reflectivities in and around the O2-A band. VLIDORT [Spurr (2006)] templates of reflectances based on full polarization scattering of light are used to train the neural network. ROCINN retrieves cloud-top pressure and cloud-top albedo. The cloud-top pressure for GOME scenes is derived from the cloud-top height provided by ROCINN and an appropriate pressure profile. For more details please refer to relevant peer-review papers listed on the GOME and GOME-2 documentation pages: https://atmos.eoc.dlr.de/app/docs/

Brackish water rewetting of a temperate coastal peatland in NE Germany: Effects on Biogeochemistry, Microorganisms and Greenhouse gas emissions

The rewetting of drained peatlands is a promising measure to mitigate carbon dioxide (CO2) emissions by preventing the further mineralization of the peat soil through aeration. While freshwater rewetted peatlands can be significant methane (CH4) sources in the short-term, in coastal ecosystems the input of sulfate-rich seawater could potentially mitigate these emissions. The purpose of the data collection was to examine whether the presence of sulfate, known as an alternative electron acceptor, can cause lower CH4 production and thus, emissions by favoring the growth of sulfate-reducers, which outcompete methanogens for substrate. We therefore investigated underlying variables such as the methane-cycling microbial community along with CH4 fluxes and set them in context with CO2 fluxes along a transect in a coastal peatland before and directly after rewetting. In this way, a conclusion about the short-term greenhouse gas mitigation potential of brackish water rewetting of coastal peatlands could be drawn. This data collection consists of six data sets, with direct comparisons before and after rewetting of CO2 and CH4 fluxes (Tab. 2) and associated microbial communities (Tab. 1) being the main data. Pore water geochemistry (Tab. 1 and 3) and surface water parameters (Tab. 4) were collected simultaneously to provide potential explanatory variables. The sampling of continuous water level (Tab. 5) within wells and atmospheric weather data (air and soil temperature, relative humidity, photosynthetic photon flux density; Tab. 6) from a weather station was done in addition. Measurements started in June/July/August 2019 after field installation was finalized and were conducted on the drained coastal fen "Polder Drammendorf" on the island of Rügen in North-East Germany. On 26th November 2019, the dike was opened and channeled in order to rewet the peatland with brackish water. Before, the dike separated the peatland from the adjacent bay "Kubitzer Bodden", which is part of a brackish lagoon system connected to the Baltic Sea. Therefore, the peatland was nearly completely flooded and now resembles a shallow lagoon with high fluctuating water levels. We measured along a humidity (pre-rewetting)/water level (post-rewetting) gradient (stations 0-8) towards and across the main North-South oriented drainage ditch, including four stations on the Eastern side of the ditch (1–4), two ditch stations (0, 5) and two stations (6, 7) on the Western side of the ditch. Station 8 was chosen as an additional station farther towards the adjacent bay on the Western side, but was only accessible before rewetting. CH4 and CO2 fluxes (stations 0-7) were calculated from online gas concentrations measurements using laser-based analyzers and manual closed chambers (Livingston, G. P., & Hutchinson, G. (1995). Enclosure-based measurement of trace gas exchange: Applications and sources of error. In P.A. Matson, & R.C. Harriss (Eds.). Biogenic trace gases: Measuring emissions from soil and water (pp. 14–51). Blackwell Science Ltd., Oxford, UK). Soil cores for microbial, dissolved gas concentrations and isotopic analysis were taken using a Russian type peat corer (De Vleeschouwer, F., Chambers, F. M., & Swindles, G. T. (2010). Coring and sub-sampling of peatlands for palaeoenvironmental research. Mires and Peat, 7, 1–10) before and after rewetting. Each time, we took duplicates at stations 1-8 for this rather labor-intensive process and divided the core into four depth sections: surface, 5–20, 20–40 and 40–50 cm. Subsamples for dissolved gases and stable carbon isotope analyses were taken with tip-cut syringes with a distinct volume of 3 ml (Omnifix, Braun, Bad Arolsen, Germany) and immediately placed into NaCl-saturated vials (20 ml, Agilent Technologies, 5182-0837, Santa Clara, USA) leaving no headspace and closed gas-tight using rubber stoppers and metal crimpers (both: diameter 20 mm, Glasgerätebau Ochs, Bovenden, Germany). Absolute abundances of specific functional target genes, including methane- and sulfate-cycling microorganisms, were measured with quantitative PCR (qPCR) after DNA was extracted (GeneMATRIX Soil DNA Purification Kit, Roboklon, Berlin, Germany) and quantified (Qubit 2.0 Fluorometer, ThermoFisher Scientific, Darmstadt, Germany). Surface and pore water parameters were measured in parallel to the gas measurements and soil coring for microbial analyses. Most surface water variables (pH, specific conductivity, salinity, nutrients, oxygen, sulfate and chloride concentrations, DOC/DIC) were measured in-situ using a multiparameter digital water quality meter or taken to the laboratory as water samples for further analysis. Likewise, pore water/soil variables (pH, specific conductivity, nutrients, metals, sulfate and chloride concentrations, CNS) were either measured in-situ or taken to the laboratory as soil samples. While surface water analysis was only conducted in the drainage ditch before rewetting, it was done along the entire transect after rewetting. In contrast, pore water/soil analysis was mostly conducted before rewetting and only repeated occasionally after rewetting where possible.

Quantifizierung des Einflusses der stratosphärischen Zirkulation auf die Abschätzung troposphärischer Emissionen

Neue Studien zeigen, dass die Emissionen eines der wichtigsten Fluochlorkohlenwasserstoffe (FCKWs), des CFC--11, seit 2012 wieder ansteigen, was eine ernste Bedrohung für die Ozonschicht bedeutet. Allerdings sind die Abschätzungen der FCKW Emissionen mit großen Unsicherheiten behaftet. Die größte Unsicherheit stammt von Änderungen der stratosphärischen Zirkulation und deren Darstellung in derzeitigen atmosphärischen Modellen und Reanalysen. Die Methodiken, um diese Zirkulationsänderungen in Modellen besser einzuschränken, sind unzureichend.Ziel des Projekts ist es den Einfluß von Jahr-zu-Jahr Variabilität und dekadischen Änderungen im stratosphärischen Transport auf troposphärische Änderungen langlebiger Spurenstoffe, mit Fokus auf FCKWs, besser zu verstehen. Dazu werden neue Methodiken entwickelt und verbessert, um das stratosphärische Altersspektrum abzuleiten, die Verteilung der Transportzeit durch die Stratosphäre. In einem ersten Schritt wird die Methoden-Evaluierung im Modell durchgeführt. Drei verschiedene Methodiken zur Berechnung des Altersspektrums aus Mischungsverhältnissen chemischer Spezies werden verglichen. Diese Methodiken basieren auf (i) einer inversen Gauss-Funktions Parametrisierung, (ii) einer verbesserten Parametrisierung, und (iii) einer direkten Inversions-Methode. Für einen "proof of concept" werden die Resultate aller drei Methoden mit Altersspektren aus dem Lagrangeschen Atmosphären-Modell CLaMS verglichen, die im Modell exakt mit einer Pultracer-Methode berechnet werden. Im zweiten Schritt werden die Methodiken angewendet auf hochaufgelöste in-situ Spurengas-Messdaten aus Luftproben von Flugzeug-Messungen und von neuesten AirCore Messungen. Die Kombination von neuartigen Simulations- und Berechnungs-Methoden mit neuesten Messdaten zur Bestimmung des stratosphärischen Altersspektrums wird zu bisher nicht dagewesenen Einschränkungen des stratosphärischen Transports in Modellen führen. Durch Vergleich der Modell-Altersspektren aus Simulationen die mit verschiedenen meteorologischen Reanalysen angetrieben wurden, einschließlich der neuesten ERA5 Reanalyse und älterer Produkte (ERA-Interim, MERRA-2, JRA-55), soll die Robustheit der Modell-Darstellung stratosphärischer Transportänderungen abgeschätzt werden. Schließlich werden die Variabilitäten im stratosphärischen Transport untersucht und quantifiziert, sowie die Effekte dieser Variabilität auf die Spurengaszusammensetzung der unteren Stratosphäre und auf troposphärische Trends. Die aus dem Projekt resultierenden verbesserten Methodiken zur Abschätzung troposphärischer Spurenstoff-Budgets sollen der wissenschaftlichen Community zugänglich gemacht werden, und werden einen wichtigen Schritt darstellen hin zu einer verbesserten Berechnung von Emissionen langlebiger ozonzerstörender Substanzen und Treibhausgase.

Abgasreinigung bei Schweinemastanlagen - ein Beitrag zur Senkung von Schadstoffemissionen aus der Landwirtschaft

Die aus der Emission von Schadstoffen aus Schweineställen resultierende Umweltbelastung ist vor allem auf Geruch, Staub, Methan, Kohlendioxid, Ammoniak, Schwefelwasserstoff und über 100 weitere Spurengase zurückzuführen. Zur Minderung dieser Emissionen dient eine Abgasreinigungsanlage, die modular aus einer chemischen Wäsche und einer Biofiltration im Pilotanlagen-Maßstab zusammengesetzt ist. In dem beantragten Projekt werden durch experimentelle und theoretische Untersuchungen die Erlangung von Kenntnissen über grundlegende Zusammenhänge dabei und die weiterführende Minimierung der Schad- und Geruchsstoffkonzentrationen im Abgas angestrebt. Die experimentellen Untersuchungen zur genaueren Charakterisierung des Anlagenverhaltens und der ablaufenden Prozesse gliedern sich in zwei Schwerpunktbereiche: Der erste umfasst die Prozesse im chemischen Wäscher, insbesondere Staubeintrag, -beschaffenheit, -Abscheidegrad und Adsorptionsvermögen des Staubes - dabei steht der Zusammenhang zwischen Staubeintrag und Geruchsminderungsgrad im Mittelpunkt - sowie die Parameterbestimmung für eine Modellierung und Simulation. Der zweite Schwerpunkt liegt auf dem Bereich Langzeitmonitoring der Abgasreinigungsanlage - insbesondere hinsichtlich der Wirkungsgradabhängigkeiten und der Einflussgrößen auf die Verfahrensstabilität. Die Modellierung und Simulation der gesamten Reinigungsanlage durch Adaption verfahrensspezifischer Zusammenhänge soll Vorhersagen für verschiedene apparative Ausgangssituationen und verfahrenstechnische Einstellungen liefern.

Spurengasflüsse und Stickstoffumsetzungen in stark verwitterten Böden unter Regenwaldtransformationssystemen

An allen 32 Standorten soll Folgendes durchgeführt werden: (a) bodenphysikalische und -chemische Analysen bis zu einer Tiefe von 2 m anhand einer Kombination aus falsche Zeitreihen- und longitudi-nalen Ansätzen; (b) Messungen mikrobiell gesteuerter Stickstoffumsetzungen im Boden und mikro-bieller Biomasse im Oberboden; (c) ganzjährige in-situ Messungen von NO, N2O, CH4 und CO2- Flüssen sowie Messungen der entsprechenden Einflussgrößen; (d) Entwicklung von Regressionsmo-dellen zwischen jährlichen Spurengasflüssen und einfach zu messenden Proxy- Variablen der Kont-rollgrößen im Boden; und (e) Messungen der Boden-CH4 und -CO2-Flüsse sowie in-situ Inkubationen von Epiphyten auf Ölpalmen.

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