Aerosol Index (AI) as derived from TROPOMI observations. AI is an indicator for episodic aerosol plumes from dust outbreaks, volcanic ash, and biomass burning. The TROPOMI instrument onboard the Copernicus SENTINEL-5 Precursor satellite is a nadir-viewing, imaging spectrometer that provides global measurements of atmospheric properties and constituents on a daily basis. It is contributing to monitoring air quality and climate, providing critical information to services and decision makers. The instrument uses passive remote sensing techniques by measuring the top of atmosphere 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. The operational trace gas products generated at DLR on behave ESA are: Ozone (O3), Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2), Formaldehyde (HCHO), Carbon Monoxide (CO) and Methane (CH4), together with clouds and aerosol properties. This product is created in the scope of the project INPULS. It develops (a) innovative retrieval algorithms and processors for the generation of value-added products from the atmospheric Copernicus missions Sentinel-5 Precursor, Sentinel-4, and Sentinel-5, (b) cloud-based (re)processing systems, (c) improved data discovery and access technologies as well as server-side analytics for the users, and (d) data visualization services.
Im Rahmen des Projektes wurde die Struktur der Waermegestehungskosten, des Primaerenergiebedarfs und der Treibhausgasemissionen, bewertet im CO2-Massstab fuer Waermeerzeugungsanlagen, wie sie fuer Contractingloesungen typisch sind untersucht und Optimierungsmoeglichkeiten dargestellt.
Zielsetzung: Untersuchungen ueber den Einfluss mikrobiologischer Prozesse im Boden und Oberflaechenwasser der Ozeane auf CO, H2, CFCl3, CF2Cl2, CCl4, Hg, H2CO, N2O und CH4. Bestimmung der Abbauraten und Produktionsraten als Funktion der Bodenart und Bodentemperatur. Messung der im Wasser geloesten Gasanteile im Ozean und Bestimmung ihrer vertikalen Verteilung bis in Wassertiefen von 1000 m. Methoden: in situ-Messungen am Boden sowie an verschiedenen Stellen der Ozeane; Laboruntersuchungen mit verschiedenen Mikroorganismen.
Ziel ist eine Geräteentwicklung für die unbeeinflusste Bestimmung von streckenintegrierten Aerosolparametern in einer anthropogen belasteten Atmosphäre. Das optische Messgerät wird in der Leipziger Stadtluft in 20 bis 40 m Höhe mit mehreren Lichtstrecken von einigen 100 m bis zu einigen Kilometern Länge gleichzeitig Messungen von Partikelextinktionsspektren bei Umgebungsfeuchte und für die Auswertung notwendige Spurengase durchführen. Aus den Extinktionsmessungen werden die Partikelgrößenverteilung und integrale Partikeleigenschaften im ungestörten Zustand mit Inversionsrechnungen berechnet.
Water, carbon and nitrogen are key elements in all ecosystem turnover processes and they are related to a variety of environmental problems, including eutrophication, greenhouse gas emissions or carbon sequestration. An in-depth knowledge of the interaction of water, carbon and nitrogen on the landscape scale is required to improve land use and management while at the same time mitigating environmental impact. This is even more important under the light of future climate and land use changes.In the frame of the proposal 'Uncertainty of predicted hydro-biogeochemical fluxes and trace gas emissions on the landscape scale under climate and land use change' we advocate the development of fully coupled, process-oriented models that explicitly simulate the dynamic interaction of water, carbon and nitrogen turnover processes on the landscape scale. We will use the Catchment Modelling Framework CMF, a modular toolbox to implement and test hypothesis of hydrologic behaviour and couple this to the biogeochemical LandscapeDNDC model, a process-based dynamic model for the simulation of greenhouse gas emissions from soils and their associated turnover processes.Due to the intrinsic complexity of the models in use, the predictive uncertainty of the coupled models is unknown. This predictive (global) uncertainty is composed of stochastic and structural components. Stochastic uncertainty results from errors in parameter estimation, poorly known initial states of the model, mismatching boundary conditions or inaccuracies in model input and validation data. Structural uncertainty is related to the flawed or simplified description of natural processes in a model.The objective of this proposal is therefore to quantify the global uncertainty of the coupled hydro-biogeochemical models and investigate the uncertainty chain from parameter uncertainty over forcing data uncertainty up the structural model uncertainty be setting up different combinations of CMF and LandscapeDNDC. A comprehensive work program has been developed structured in 4 work packages, that consist of (1) model set up, calibration and uncertainty assessment on site scale followed by (2) an application and uncertainty assessment of the coupled model structures on regional scale, (3) global change scenario analyses and finally (4) evaluating model results in an ensemble fashion.Last but not least, a further motivation of this proposal is to provide project results in a manner that they support planning and decision taking under uncertainty, as this proposal is part of the package proposal on 'Methodologies for dealing with uncertainties in landscape planning and related modelling'.
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/
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
In diesem Projekt sollen zeitlich hoch aufgelöste Spurengasmessungen und Messungen der Größenspektren der Aerosolpartikel an einem Verkehrsstandort zu einer deutlichen Weiterentwicklung unseres Verständnisses der Dynamik der Konzentrationen von Luftschadstoffen im städtischen Umfeld sowie der Emissionen aus dem Straßenverkehr beitragen. Neue, schnelle Techniken sollen das bereits gut entwickelte Grundlagenwissen zu Emissionsverhältnissen NO / NO2 / NOx einzelner Fahrzeuge und Fahrzeuggruppen entwickeln, den Einfluss auf die Ozonchemie und die Interaktion mit dem vorhandenen Ozon studieren, Emissionsverhältnisse NH3 / CO2 und NOx / CO2 unter realen Bedingungen quantifizieren, und vor allem die Emissionen der Aerosopartikel in einem weiten Größenspektrum (einige nm bis über 1 mym Durchmesser) detailliert quantifizieren. Dies bedeutet und ermöglicht eine neuartige Analyse der Emissionen von Partikeln im echten Straßenverkehr. Die vorgeschlagenen Konzepte und Messungen ergänzen sich mit anderen modernen Konzepten der Analyse von Luftverschmutzung und Emissionen wie z.B. multi-Sensoren-Anwendungen, Einsatz mobiler Plattformen, oder Eddy-Kovarianz. Hier wird Grundlagenforschung vorgeschlagen, die in Ergänzung mit anderen Anwendungen und Konzepten einschließlich Modellierung zu einer deutlichen Verbesserung unseres Verständnisses der städtischen Umwelt führen wird. Das Herzstück der experimentellen Forschung ist eine 18-monatige Messreihe am Straßenrand, die allerdings von zwei Intensivmesskampagnen (IOPs) um Kenntnisse zur räumlichen Representativität und zur chemischen Zusammensetzung der Partikel im Größenspektrum ergänzt werden.
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