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METOP GOME-2 - Cloud Optical Thickness (COT) - 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 optical thickness is computed using libRadtran [Mayer and Kylling (2005)] radiative transfer simulations taking as input the cloud-top albedo retrieved with ROCINN. 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/

Carbonate chemistry from laboratory incubation experiments using water samples from the Elbe conducted in 2023

This dataset comprises key carbonate chemistry parameters measured and calculated in incubation experiments under different experimental conditions. pH, water temperature, and salinity were measured with a WTW multimeter (MultiLine® Multi 3630 IDS). Total alkalinity was determined by open-cell titration with an 888 Titrando (Metrohm). Saturation state of calcite and aragonite were calculated using phreeqpython, a Python wrapper of the PhreeqC engine (Vitens 2021) with pH, water temperature, total alkalinity, and major ions as major input, and phreeqc.dat as database for the thermodynamic data (Parkhurst and Appelo 2013). As the original Elbe water was supersaturated with carbon dioxide (CO2) with respect to the atmosphere, its partial pressure of CO2 (pCO2) level decreased during the incubation period with open flasks, which caused an adjustment of calcite saturation state (ΩC) for ambient air conditions. To adapt for the impact of pCO2 variations during the experiment, saturation state of calcite and aragonite was calculated assuming an equilibrium with an atmospheric pCO2 of 415 ppm (normalized ΩC and normalized aragonite sautration state ΩA). Since ion concentrations were measured for only a small number of samples, the ion concentrations of the remaining samples were reconstructed using stoichiometry based on the initial solution composition and total alkalinity. The concentrations of conservative ions (Na+, K+, Cl-, SO42-) were assumed remain constant, while ions related to carbonate precipitation (Ca2+, Mg2+) were calculated based on changes in measured alkalinity (see Figure 5 of the associated paper). Detailed analysis and calculation procedures are described in the Method section of the associated paper.

METOP GOME-2 - Water Vapour (H2O) - 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 H2O 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 total H2O column is retrieved from GOME solar backscattered measurements in the red wavelength region (614-683.2 nm), using the Differential Optical Absorption Spectroscopy (DOAS) method. 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 - 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/

METOP GOME-2 - Cloud Fraction (CF) - 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. 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/

A Numerical Large-Scale Investigation of Gas Transport Processes in a Generic Nuclear Waste Repository in Argillaceous Porous Media

In this paper, we present the results of a large-scale numerical model of a generic nuclear waste repository situated in an argillaceous host rock formation. Modelling the evolution of an entire repository presents challenges due to the strong contrast in spatial and temporal scales at which the different processes take place, ranging from the centimetres to the kilometres and days to hundreds of thousands of years, respectively. From the view point of the physical processes, a further challenge originates from the different gas transport mechanisms: Gas advection as well as gas dissolution and diffusion jointly govern the efflux of gas from the repository and mitigate excess pore pressures, but there is a significant contrast between the rates of these two transport mechanisms. Using the TH2M implementation in the open-source finite element code OpenGeoSys-6 , we analyse the impact of gas transport via advection (in the partially saturated zones such as backfilled drifts, shafts and desaturated host rock) as well as gas transport via diffusion (in fully water-saturated media such as the undisturbed host rock and over- and underlying formations). Finally, this work outlines and discusses possible simplifications in modelling choices, such as mechanical surrogate models, geometrical simplifications as well as the impact of discretization. The work presented in this paper was carried out within the scope of the European Joint Programme EURAD, workpackage Gas, Task 4.

Sedimentation velocity of morphologically diverse macrophytes and plastic particles

The dataset contains sedimentation velocity measurements for 22 morphologically diverse macroalgae species (n = 49), the seagrass Zostera marina (n = 3), and plastic particles of four distinct shapes (n = 16). Each sample was measured at least five times, with some measured up to seven times. Detailed morphological descriptions and images are available in the corresponding paper. Samples with a SampleID starting with "K" were collected in January 2023 from the Kiel Fjord, Germany (between Strande and Bülk light house, 54°26'57.4N 10°11'37.6E). U. gigantea was collected in June 2024 in Yerseke, Netherlands (51°30'09.0N, 4°02'39.7E). All other samples were collected in June 2024 at the same site from the Kiel Fjord as in 2023, as well as two additional locations (Schilksee, 54°25'16.3N 10°10'43.1E and Mönkeberg, 54°21'20.92N 10°10'41.97E). Sedimentation velocity measurements were conducted in plastic cylinders, allowing particles to sink 15 cm to reach their terminal sinking velocity before starting the measurements. The sinking time was recorded using a stopwatch, and sedimentation velocity was calculated by dividing the sinking distance by the elapsed time. Test with varying cylinder heights showed no significant differences in results. Macrophyte species measured: Fucus vesiculosus, Fucus serratus, Saccharina latissima, Gracilaria vermiculophylla, Ceramium virgatum, Vertebrata fucoides, Polysiphonia stricta, Spermothamnion repens, Ahnfeltia plicata, Furcellaria lumbricalis, Coccotylus truncatus, Delesseria sanguinea, Cladophora flexuosa, Cladophora sp., Rhodomela confervoides, Pyropia leucosticta, Ulva clathrata, Ulva linza, Kornmannia leptoderma, Bryopsis hypnoides, Acrosiphonia centralis, Ulva gigantea, and Zostera marina. The plastic particles include eight circular pieces of foil (disks), three table tennis balls, two plastic nets, and three rubber bands. The foil disks were cut to different diameters and some were punched with different numbers of small holes. The name of the foil circles indicates both their diameter and perforation level. For example, "Disk 40-1" had a diameter of 40 mm and was unpunched, where "1" denotes unpunched, "2" partially punched, and "3" heavily punched, "4" extremely heavily punched. The three tennis balls shared identical dimensions but had different mass densities due to the different level of replacement of air with seawater and glass beads in the tennis ball.

Transdisziplinäre Mehrfachnutzung von Rohfaser und Rohprotein klimaresilienter Fruchtarten über selektive Ernte- und Aufbereitungsverfahren in ressourcenschonenden Farming-Systemen mit Recycling des Stickstoffs (MEFAFUP), Teilvorhaben 4

Veredelung von Nassgrünland-Biomasse zu Plattformchemikalien, Verpackungen, Faserguss und Papier, Teilvorhaben 1: Koordination, Wissenstransfer, Öffentlichkeitsarbeit & Ökologische und Ökonomische Bewertung

EDELNASS fokussiert auf die stoffliche Verwertung von Aufwüchsen von wiedervernässten Moor-Grünland, welches heterogen in der Artenzusammensetzung ist und oft Bewirtschaftungseinschränkungen unterliegt (z.B. Erntezeitpunkt). Biomasse und ihre Standortparameter von 5 Moorstandorten in ganz Deutschland werden analysiert und hinsichtlich ihrer Anwendbarkeit in 2 Verwertungsverfahren untersucht, getestet und bewertet: (i) Umwandlung in Bioraffinerien zu den biobasierten, hochwertigen Basischemikalien HMF und Furfural und der Optimierung der Verfahren an der Universität Hohenheim. Ebenso wird Lignin als weiteres Produkt hergestellt. Das HMF kann zur Herstellung des recyclebaren, biobasierten Hochleistungskunststoff PEF weiterverarbeitet werden, woraus die Hochschule Albstadt-Sigmaringen nachhaltige Verpackungslösungen entwickelt, (ii) Das Leibniz-Institut für Agrartechnik und Bioökonomie stellt zusammen mit seinen Partnern Faserstoffe aus der Biomasse her und verarbeiten diese weiter zu Papieren und Fasergussformteilen. Kopplungspotentiale von Stoffströmen der Rohstofffraktionen zwischen den Verfahren untersucht, indem Zwischen- und Nebenprodukte der Verfahren in die jeweils anderen Prozesse eingespeist werden. Ziel der Untersuchungen ist es, neue Wertschöpfungsketten auf der Grundlage von Nasswiesen-Bewirtschaftung zu entwickeln, die eine produktive Nutzung von Nassgrünland mit dem Erreichen von Naturschutz- und Klimaschutzzielen verbindet. Für eine zukünftige Honorierung von Ökosystemdienstleistungen vernässter Moore werden Datengrundlagen erstellt: CO2-Bilanz der Verfahren und möglicher Produkte (inkl. bodenbürtiger Emissionen), Entwicklung von Artenvielfalt und Wasserqualität. Die Kosten von der Rohstoffbereitstellung bis zum Endprodukt werden analysiert, um geeignete Betriebsmodelle für die einzelnen Verfahren abzuleiten und beispielhaft in Moorregionen zu projektieren.

Energetische Optimierung der Trockenpartie

Ausgangssituation/Problemstellungrn Die für Trocknung von Papier eingesetzte Energie wird - abgesehen von den durchaus nicht unbeträchtlichen Wärmeverlusten in der Trockenpartie - fast ausschließlich zur Erwärmung und - zu einem erheblich höheren Anteil - zur Verdampfung des Wassers benötigt, das die Bahn aus der Pressenpartie mitbringt.rnUm die hierfür aufgewendete, im abgeführten Dampf gebundene Energie zurückzugewinnen, muss der in der Haubenabluft enthaltene Dampfanteil möglichst vollständig kondensiert wer-den (was bedeutet, dass sich die Energie nach der Kondensation in dem Medium befindet, das die Haubenabluft gekühlt hat). Dabei ergeben sich eventuell eine operative und mit Ge-wissheit eine energetische Schwierigkeit:rn- Inhaltsstoffe der Haubenluft könnten Anbackungen oder Korrosion im Kondensator verursachen und dessen Wirkungsgrad reduzieren. rn- Die Qualität (also der technisch verwertbare Anteil der zurück gewonnenen Wärme = Exergie) und die Quantität der zurück gewonnenen Wärme folgen gegenläufigen Tendenzen: rn- Mit zunehmender Kondensationstemperatur steigt die Exergie der zurück gewonnen Wärme an. rn- Mit abnehmender Kondensationstemperatur steigt die - wegen ihrer tiefen Tempera-tur zunehmend wertlose - zurück gewonnene Wärmemenge an. rnrnForschungsziel/ForschungsergebnisrnZiele des Projekts sind rn- die Analyse und Bewertung des Problempotenzials der Inhaltsstoffe des Kondensats der Haubenluft auf die Arbeitsweise des Kondensators,rn- die Entwicklung und Erprobung eines Bilanzmodells auf Basis von Messwerten für die Papiertrocknung, rn- die Identifikation technisch-wirtschaftlich sinnvoller Lösungen des Zielkonflikts zwi-schen Menge und Qualität der rückgewinnbaren Energie, rn- die Bewertung des erreichbaren Potenzials an rückgewinnbarer Energie als Ersatz für Fremdenergie anhand von Fallbeispielen mittels dem Bilanzmodell und rn- die Abschätzung der technischen Realisierbarkeit sowie der Wirtschaftlichkeit der zur Nutzung dieses Potenzials erforderlichen Maßnahmen.rnrnAnwendungen/Wirtschaftliche BedeutungrnWärmeverluste über die Haubenabluft werden üblicherweise als unvermeidlich betrachtet und treten heute an allen Papier- und Kartonmaschinen auf. Die mittel- und langfristig zu er-wartende Entwicklung der Energiepreise legt es nahe, intensiv nach Möglichkeiten zu su-chen, dieses Energiepotenzial wirtschaftlich zu erschließen und damit den Fremdenergiebe-zug zu reduzieren. Betroffen von dieser Situation und damit potentieller Nutzer der ange-strebten Forschungsergebnisse ist also die gesamte Papier produzierende Industriern

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