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.
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 total NO2 column is retrieved from GOME solar back-scattered measurements in the visible wavelength region (425-450 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/
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/
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/
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.
In June 2010, the DLR Group of Systems Analysis started an investigation about innovative financing of Concentrating Solar Power Plants (CSP) in countries of the Middle East and North Africa. We found a possible strategy for the market introduction of concentrating solar power (CSP) plants in the Middle East and North Africa (MENA) that will not require considerable subsidization and will not constitute a significant burden for electricity consumers in the region. In the first section, the paper explains the need of MENA countries for sustainable supply of electricity and calculates the cost of electricity for a model case country. In the second part, the cost development of concentrating solar power plants is calculated on the basis of expectations for the expansion of CSP on a global level. After that, the challenges for the market introduction of CSP in MENA are explained. Finally, we present a strategy for the market introduction of CSP in MENA, removing the main barriers for financing and starting market introduction in the peak load and the medium load segment of power supply. The paper explains why long-term power purchase agreements (PPA) for CSP should be calculated on the basis of avoided costs, starting in the peak load segment. Such PPA are not yet available, the paper aims to convince policy makers to introduce them. The attached power point file shows some examples of time series of load and supply by CSP in the different load segments and shows the graphs used in the report. The attached Excel Sheet gives the time series of load and supply by CSP for the different load segments for a total reference year.
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