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The clear-sky radiative effect of aerosol-radiation interactions is of relevance for our understanding of the climate system. The influence of aerosol on the surface energy budget is of high interest for the renewable energy sector. In this study, the radiative effect is investigated in particular with respect to seasonal and regional variations for the region of Germany and the year 2015 at the surface and top of atmosphere using two complementary approaches.
First, an ensemble of clear-sky models which explicitly consider aerosols is utilized to retrieve the aerosol optical depth and the surface direct radiative effect of aerosols by means of a clear sky fitting technique. For this, short-wave broadband irradiance measurements in the absence of clouds are used as a basis. A clear sky detection algorithm is used to identify cloud free observations. Considered are measurements of the shortwave broadband global and diffuse horizontal irradiance with shaded and unshaded pyranometers at 25 stations across Germany within the observational network of the German Weather Service (DWD). Clear sky models used are MMAC, MRMv6.1, METSTAT, ESRA, Heliosat-1, CEM and the simplified Solis model. The definition of aerosol and atmospheric characteristics of the models are examined in detail for their suitability for this approach.
Second, the radiative effect is estimated using explicit radiative transfer simulations with inputs on the meteorological state of the atmosphere, trace-gases and aerosol from CAMS reanalysis. The aerosol optical properties (aerosol optical depth, Ångström exponent, single scattering albedo and assymetrie parameter) are first evaluated with AERONET direct sun and inversion products. The largest inconsistency is found for the aerosol absorption, which is overestimated by about 0.03 or about 30 % by the CAMS reanalysis. Compared to the DWD observational network, the simulated global, direct and diffuse irradiances show reasonable agreement within the measurement uncertainty. The radiative kernel method is used to estimate the resulting uncertainty and bias of the simulated direct radiative effect. The uncertainty is estimated to −1.5 ± 7.7 and 0.6 ± 3.5 W m−2 at the surface and top of atmosphere, respectively, while the annual-mean biases at the surface, top of atmosphere and total atmosphere are −10.6, −6.5 and 4.1 W m−2, respectively.
The retrieval of the aerosol radiative effect with the clear sky models shows a high level of agreement with the radiative transfer simulations, with an RMSE of 5.8 W m−2 and a correlation of 0.75. The annual mean of the REari at the surface for the 25 DWD stations shows a value of −12.8 ± 5 W m−2 as average over the clear sky models, compared to −11 W m−2 from the radiative transfer simulations. Since all models assume a fixed aerosol characterisation, the annual cycle of the aerosol radiation effect cannot be reproduced. Out of this set of clear sky models, the largest level of agreement is shown by the ESRA and MRMv6.1 models.
The clear-sky radiative effect of aerosol–radiation interactions is of relevance for our understanding of the climate system. The influence of aerosol on the surface energy budget is of high interest for the renewable energy sector. In this study, the radiative effect is investigated in particular with respect to seasonal and regional variations for the region of Germany and the year 2015 at the surface and top of atmosphere using two complementary approaches.
First, an ensemble of clear-sky models which explicitly consider aerosols is utilized to retrieve the aerosol optical depth and the surface direct radiative effect of aerosols by means of a clear-sky fitting technique. For this, short-wave broadband irradiance measurements in the absence of clouds are used as a basis. A clear-sky detection algorithm is used to identify cloud-free observations. Considered are measurements of the short-wave broadband global and diffuse horizontal irradiance with shaded and unshaded pyranometers at 25 stations across Germany within the observational network of the German Weather Service (DWD). The clear-sky models used are the Modified MAC model (MMAC), the Meteorological Radiation Model (MRM) v6.1, the Meteorological–Statistical solar radiation model (METSTAT), the European Solar Radiation Atlas (ESRA), Heliosat-1, the Center for Environment and Man solar radiation model (CEM), and the simplified Solis model. The definition of aerosol and atmospheric characteristics of the models are examined in detail for their suitability for this approach.
Second, the radiative effect is estimated using explicit radiative transfer simulations with inputs on the meteorological state of the atmosphere, trace gases and aerosol from the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis. The aerosol optical properties (aerosol optical depth, Ångström exponent, single scattering albedo and asymmetry parameter) are first evaluated with AERONET direct sun and inversion products. The largest inconsistency is found for the aerosol absorption, which is overestimated by about 0.03 or about 30 % by the CAMS reanalysis. Compared to the DWD observational network, the simulated global, direct and diffuse irradiances show reasonable agreement within the measurement uncertainty. The radiative kernel method is used to estimate the resulting uncertainty and bias of the simulated direct radiative effect. The uncertainty is estimated to −1.5 ± 7.7 and 0.6 ± 3.5 W m−2 at the surface and top of atmosphere, respectively, while the annual-mean biases at the surface, top of atmosphere and total atmosphere are −10.6, −6.5 and 4.1 W m−2, respectively.
The retrieval of the aerosol radiative effect with the clear-sky models shows a high level of agreement with the radiative transfer simulations, with an RMSE of 5.8 W m−2 and a correlation of 0.75. The annual mean of the REari at the surface for the 25 DWD stations shows a value of −12.8 ± 5 W m−2 as the average over the clear-sky models, compared to −11 W m−2 from the radiative transfer simulations. Since all models assume a fixed aerosol characterization, the annual cycle of the aerosol radiation effect cannot be reproduced. Out of this set of clear-sky models, the largest level of agreement is shown by the ESRA and MRM v6.1 models.
Recent findings in South Africa have once again underlined the fact that the oldest people in the world obviously came from Africa. Thus, historically, this continent has a very special significance. However, its history in more recent times, especially from the mid-19th century onwards, was strongly influenced by colonisation by European states. Many deep wounds from that time still have an impact on society as a whole today. However, the continent is currently also confronted with a greater number of challenges of a different nature.
On the one hand, Africa is trying to strengthen internal cohesion by means of a number of regional organisations and the African Union as a globally active institution; on the other hand, the continent has been marked by political and military conflicts between neighbouring states over the past decades until the recent present. In addition, there are regular internal social upheavals in individual countries due to violent or manipulated political change.
Yet the continent could well be on a good development path, since it has a large number of important raw materials - also in comparison to other continents. However, the individual African states - and especially their citizens - often do not benefit from this to an adequate extent. This results in a social imbalance in large parts of the continent (data collection until the end of June 2023), which leads to considerable internal tensions. To make matters worse, Africa is the continent most affected by climate change.
A closer look at the partly very different economic, political and social situations of the large continent leads to an overall predominantly critical assessment of Africa's further development, which is explained in more detail in the final chapter with regard to the foreseeable consequences for the continent.
Neueste Funde in Südafrika haben nochmals unterstrichen, dass die ältesten Menschen der Welt offensichtlich aus Afrika abstammen. Somit kommt diesem Kontinent historisch gesehen ganz besondere Bedeutung zu. Allerdings war seine Geschichte in der jüngeren Zeit, insbesondere ab Mitte des 19. Jahrhunderts, von der Kolonialisierung durch europäische Staaten stark geprägt. Viele tiefe Wunden aus der damaligen Zeit haben noch heute Auswirkungen auf die Gesellschaft insgesamt. Allerdings ist der Kontinent derzeit auch mit einer größeren Zahl anders gelagerter Herausforderungen konfrontiert.
Zum einen versucht Afrika mittels einer Anzahl von Regionalorganisationen sowie der Afrikanischen Union als global agierender Institution den inneren Zusammenhalt zu stärken, zum anderen ist der Kontinent über die letzten Jahrzehnte bis in die jüngste Gegenwart durch politische und militärische Konflikte zwischen Nachbarstaaten geprägt. Hinzu kommen regelmäßig innere gesellschaftliche Umwälzungen einzelner Länder durch einen gewaltsamen oder manipulierten politischen Wechsel.
Dabei könnte der Kontinent sich durchaus auf einem guten Entwicklungspfad befinden, verfügt er doch – auch im Vergleich zu anderen Kontinenten – über eine Vielzahl von wichtigen Rohstoffen. Allerdings profitieren die einzelnen afrikanischen Staaten – und insbesondere ihre Bürgerinnen und Bürger - hiervon oft nicht in einem angemessenen Rahmen. Somit ergibt sich in großen Teilen des Kontinents ein soziales Ungleichgewicht, das zu erheblichen inneren Spannungen führt. Erschwerend kommt hinzu, dass Afrika weltweit am stärksten vom Klimawandel betroffen ist.
Bei näherer Betrachtung der z.T. sehr unterschiedlichen wirtschaftlichen, politischen und sozialen Situation des großen Kontinents (Datenerhebung bis Ende Juni 2023) führt die vorliegende Untersuchung zu einer insgesamt überwiegend kritischen Einschätzung hinsichtlich der weiteren Entwicklung Afrikas, die im Schlusskapitel bzgl. der absehbaren Konsequenzen für den Kontinent näher dargelegt wird.
Die vorliegende Forschungsarbeit setzt sich mit nachhaltigem Verhalten in Bezug auf die Nutzung von Kaffeebehältern an der HBRS auseinander. Anlass dafür ist, dass Pappbecher aufgrund einer Plastikbeschichtung nur schwer recycelbar sind und somit die Umwelt erheblich beeinträchtigen. In diesem Zusammenhang nahmen 204 Studierende an einer Online-Befragung teil. Den Ergebnissen zufolge kommen derzeit vor allem Einweg-Pappbecher zum Einsatz. Zur Modifizierung dieses umweltschädlichen Verhaltens bedarf es an geeigneten Interventionsstrategien. Basierend auf den Ergebnissen sind Maßnahmen zu implementieren, die dem Defizit an Handlungswissen und dem hohen Aufwand entgegenwirken, welcher mit der Verwendung eigens mitgebrachter Becher und den vorhandenen Porzellantassen assoziiert wird. Nach Sicherstellung der ökologischen Vorteile und finanziellen Umsetzbarkeit sollte das bestehende Pfandsystem um praktischere Becher sowie flexible Rückgabemöglichkeiten erweitert werden. Unterstützend ist eine Belohnung in Form von Freigetränken oder einem geringen finanziellen Rabatt sinnvoll, um den automatischen Verbrauch von Pappbechern zu unterbinden.
The implementation of the Sustainable Development Goals (SDGs) and the conservation and protection of nature are among the greatest challenges facing urban regions. There are few approaches so far that link the SDGs to natural diversity and related ecosystem services at the local level and track them in terms of increasing sustainable development at the local level. We want to close this gap by developing a set of indicators that capture ecosystem services in the sense of the SDGs and which are based on data that are freely available throughout Germany and Europe. Based on 10 SDGs and 35 SDG indicators, we are developing an ecosystem service and biodiversity-related indicator set for the evaluation of sustainable development in urban areas. We further show that it is possible to close many of the data gaps between SDGs and locally collected data mentioned in the literature and to translate the universal SDGs to the local level. Our example develops this set of indicators for the Bonn/Rhein-Sieg metropolitan area in North Rhine-Westphalia, Germany, which comprises both rural and densely populated settlements. This set of indicators can also help improve communication and plan sustainable development by increasing transparency in local sustainability, implementing a visible sustainability monitoring system, and strengthening the collaboration between local stakeholders.
The aim of this paper is to assess the objectives of farmers’ challenges in enhancing biodiversity. The so-called “trilemma” (WBGU 2021) of land use stems from the multiple demands made on land for the benefit of mitigating climate change, securing food and maintaining biodiversity. The agricultural sector is accused of maladministration: it is blamed for causing soil contamination, animal cruelty, bee mortality and climate change. That is why farmers are seen as key actors at all levels. They are, however, also key players when it comes to overcoming the problems of the future. Their supportive role is urgently needed, but farmers find themselves caught between a “rock” and a ”hard place”. Consumers are calling for sustainable, environmentally friendly production and inexpensive food products that do not contain pesticide residues, demanding enough food for all. Farmers are restricted by the wants and needs of consumers who are influenced by interest groups and are exposed to direct and indirect influencing factors and their interdependencies. They are also tasked with balancing the scrutiny of the critical public on the one hand, and the control exercised by eager authorities on the other.
As part of the DINA (Diversity of Insects in Nature protected Areas) project, a trans- and interdisciplinary research study, we collected and surveyed the data of farmers who are farming within or close to the 21 selected nature protected areas included in the DINA project. Data was collected as part of a mixed method approach using a semi-structured questionnaire. The methodological and strategic approach and interdependencies of issues demonstrate the complexity of today’s problems. To investigate this, we first used the data collection method using questionnaires with closed and open questions. The conflicts and obstacles farmers face were evaluated, and the results show farmers’ willingness and the importance of appreciation shown to farmers for implementation of biodiversity measures. The paper proposes some follow-up activities (quantitative study) to verify the objectives. The results will later lead to recommendations for policymakers and farmers in all German nature protected areas.
Hydrogen is a versatile energy carrier. When produced with renewable energy by water splitting, it is a carbon neutral alternative to fossil fuels. The industrialization process of this technology is currently dominated by electrolyzers powered by solar or wind energy. For small scale applications, however, more integrated device designs for water splitting using solar energy might optimize hydrogen production due to lower balance of system costs and a smarter thermal management. Such devices offer the opportunity to thermally couple the solar cell and the electrochemical compartment. In this way, heat losses in the absorber can be turned into an efficiency boost for the device via simultaneously enhancing the catalytic performance of the water splitting reactions, cooling the absorber, and decreasing the ohmic losses.[1,2] However,integrated devices (sometimes also referred to as “artificial leaves”), currently suffer from a lower technology readiness level (TRL) than the completely decoupled approach.
Im Projekt wurde anhand medienanalytischer Verfahren, Befragungen und Experimenten untersucht, wie sich Verbrauchergruppen über das Thema Tierwohl informieren und welche Argumente die Diskussion bestimmen. Die Ergebnisse zeigen: Insgesamt herrscht eine positive Einstellung zu Tierwohl-Initiativen; finanzielle Aspekte sind ein zentrales Thema. Mehr Transparenz bei den Kosten wäre wünschenswert. Das Internet kann dies unterstützen. Aber nicht alle Zielgruppen werden damit erreicht.
Ghana suffers from frequent power outages, which can be compensated by off-grid energy solutions. Photovoltaic-hybrid systems become more and more important for rural electrification due to their potential to offer a clean and cost-effective energy supply. However, uncertainties related to the prediction of electrical loads and solar irradiance result in inefficient system control and can lead to an unstable electricity supply, which is vital for the high reliability required for applications within the health sector. Model predictive control (MPC) algorithms present a viable option to tackle those uncertainties compared to rule-based methods, but strongly rely on the quality of the forecasts. This study tests and evaluates (a) a seasonal autoregressive integrated moving average (SARIMA) algorithm, (b) an incremental linear regression (ILR) algorithm, (c) a long short-term memory (LSTM) model, and (d) a customized statistical approach for electrical load forecasting on real load data of a Ghanaian health facility, considering initially limited knowledge of load and pattern changes through the implementation of incremental learning. The correlation of the electrical load with exogenous variables was determined to map out possible enhancements within the algorithms. Results show that all algorithms show high accuracies with a median normalized root mean square error (nRMSE) <0.1 and differing robustness towards load-shifting events, gradients, and noise. While the SARIMA algorithm and the linear regression model show extreme error outliers of nRMSE >1, methods via the LSTM model and the customized statistical approaches perform better with a median nRMSE of 0.061 and stable error distribution with a maximum nRMSE of <0.255. The conclusion of this study is a favoring towards the LSTM model and the statistical approach, with regard to MPC applications within photovoltaic-hybrid system solutions in the Ghanaian health sector.
Unsachgemäß entsorgte Zigarettenkippen stellen aufgrund der in ihnen enthaltenen Giftstoffe ein relevantes, ökologisches Problem dar. Diese Forschungsarbeit untersucht den Einsatz von Nudging zur Bekämpfung der Problematik. In einer quantiativen Online-Befragung wurden zunächst die Gründe für das umweltschädliche Verhalten untersucht (N = 96). Hierbei konnte die Gegenwartstendenz von Personen als statistisch signifikanter Hauptgrund ermittelt werden. Viele Personen gaben an, die langfristigen ökologischen Kosten einer unsachgemäßen Entsorgung aufgrund des kurzfristigen persönlichen Nutzens zu ignorieren. Dieser entsteht durch die Gemütlichkeit des „Wegschnipsens“ einer Zigarettenkippe. Im Anschluss wurde ein auf die Gegenwartstendenz von Personen fokussierter Nudge entwickelt und in einem Feldexperiment auf seine Wirksamkeit überprüft, indem die Relation von unsachgemäß zu sachgemäß entsorgten Zigarettenkippen vor und nach dem Einsatz des Nudges dokumentiert wurde. Ohne Einsatz des Nudges (N = 92) wurden am Erhebungsort 64.1 Prozent und mit Einsatz des Nudges (N = 142) lediglich 38.0 Prozent der Zigarettenkippen unsachgemäß entsorgt. In dem Feldexperiment konnte der Nudge effektiv zur Förderung von nachhaltigem Verhalten eingesetzt werden.
In the research project "MetPVNet", both, the forecast-based operation management in distribution grids and as well as the forecasts of the feed-in of PV-power from decentralized plants could be improved on the basis of satellite data and numerical weather forecasts. Based on a detailed network analyses for a real medium-voltage grid area, it was shown that both – the integration of forecast data based on satellite and weather data and the improvement of subsequent day forecasts based on numerical weather models – have a significant added value for forecast-based congestion management or redispatch and reactive power management in the distribution grid. Furthermore, forecast improvements for the forecast model of the German Weather Service were achieved by assimilating visible satellite imagery, and cloud and radiation products from satellites were improved, thus improving the database for short-term forecasting as well as for assimilation. In addition, several methods have been developed that will enable forecast improvement in the future, especially for weather situations with high cloud induced variability and high forecast errors. This article summarizes the most important project results.
Diversity of Insects in Nature protected Areas (DINA): an interdisciplinary German research project
(2021)
Insect declines and biodiversity loss have attracted much attention in recent years, but lack of comprehensive data, conflicting interests among stakeholders and insufficient policy guidance hinder progress in preserving biodiversity. The project DINA (Diversity of Insects in Nature protected Areas) investigates insect communities in 21 nature reserves in Germany. All selected conservation sites border arable land, with agricultural practices assumed to influence insect populations. We taught citizen scientists how to manage Malaise traps for insect collection, and subsequently used a DNA metabarcoding approach for species identification. Vegetation surveys, plant metabarcoding as well as geospatial and ecotoxicological analyses will help to unravel contributing factors for the deterioration of insect communities. As a pioneering research project in this field, DINA includes a transdisciplinary dialogue involving relevant stakeholders such as local authorities, policymakers, and farmers, which aims at a shared understanding of conservation goals and action pathways. Stakeholder engagement combined with scientific results will support the development of sound policy recommendations to improve legal frameworks, landscape planning, land use, and conservation strategies. With this transdisciplinary approach, we aim to provide the background knowledge to implement policy strategies that will halt further decline of insects in German protected areas.
The temperature of photovoltaic modules is modelled as a dynamic function of ambient temperature, shortwave and longwave irradiance and wind speed, in order to allow for a more accurate characterisation of their efficiency. A simple dynamic thermal model is developed by extending an existing parametric steady-state model using an exponential smoothing kernel to include the effect of the heat capacity of the system. The four parameters of the model are fitted to measured data from three photovoltaic systems in the Allgäu region in Germany using non-linear optimisation. The dynamic model reduces the root-mean-square error between measured and modelled module temperature to 1.58 K on average, compared to 3.03 K for the steady-state model, whereas the maximum instantaneous error is reduced from 20.02 to 6.58 K.
Als weltweit anspruchsvollstes Umweltmanagementsystem trägt EMAS auf Unternehmensebene als Baustein zur Nachhaltigen Entwicklung bei. EMAS ist ein Instrument der Europäischen Union, an dem Organisationen, unabhängig von ihrer Größe und Branche, weltweit auf freiwilliger Basis teilnehmen können. Die geplante EMAS-Validierung der UN-Klimakonferenz (COP 23) in Bonn (06. – 17.11.2017), hat das Interesse der Projektkoordination von „Sustainable Bonn – Konferenzort der Nachhaltigkeit“ geweckt, die EMAS-Einführung bei deren Projektteilnehmern untersuchen zu lassen. Daher liegt der Branchenfokus auf dem Gastgewerbe, aus denen die derzeitigen Teilnehmer des Bonner Projekts überwiegend stammen. Um Branchenspezifika bei EMAS besser zu berücksichtigen hat die Europäische Kommission im April 2016 hat ein Referenzdokument über bewährte Umweltmanagementpraktiken zur Steigerung der Öko-Effektivität mit einschlägigen Indikatoren zur Messung der Umweltleistung mit Richtwerten für die Tourismusbranche veröffentlicht, die im Rahmen einer EMAS-Einführung unter anderem von Gastgewerbebetrieben berücksichtigt werden müssen.
Education for Sustainable Development (ESD, SDG 4) and human well-being (SDG 3) are among the central subjects of the Sustainable Development Goals (SDGs). In this article, based on the Questionnaire for Eudaimonic Well-Being (QEWB), we investigate to what extent (a) there is a connection between EWB and practical commitment to the SDGs and whether (b) there is a deficit in EWB among young people in general. We also want to use the article to draw attention to the need for further research on the links between human well-being and commitment for sustainable development. A total of 114 students between the ages of 18 and 34, who are either engaged in (extra)curricular activities of sustainable development (28 students) or not (86 students), completed the QEWB. The students were interviewed twice: once regarding their current and their aspired EWB. Our results show that students who are actively engaged in activities for sustainable development report a higher EWB than non-active students. Furthermore, we show that students generally report deficits in EWB and wish for an improvement in their well-being. This especially applies to aspects of EWB related to self-discovery and the sense of meaning in life. Our study suggests that a practice-oriented ESD in particular can have a positive effect on the quality of life of young students and can support them in working on deficits in EWB.
For several decades, farmers have been mixing rock powders with livestock slurry to reduce its NH3 emissions and increase its nutrient content. However, mixing rock powders with slurry is controversial, and there is currently no scientific evidence for its effects on NH3 and greenhouse gas (GHG) emissions or on changes in its nutrient content due to element release from rock powders. The major aim of this study was therefore to analyse the effects of mixing two commercially established rock powders with cattle slurry on NH3, CO2, N2O and CH4 emissions, and on nutrient release over a course of 46 days. We found that rock powders did not significantly affect CO2 emission rates. NH3 and N2O emission rates did not differ significantly up until the end of the trial, when the emission rates of the rock powder treatments significantly increased for NH3 and significantly decreased for N2O, respectively, which coincided with a reduction of the slurry crust. Cumulative NH3 emissions did not, however, differ significantly between treatments. Unexpected and significant increases in CH4 emission rates occurred for the rock powder treatments. Rock powders increased the macro- and micronutrient content of the slurry. The conflicting results are discussed and future research directions are proposed.
Zur Milderung des Klimawandels sind Maßnahmen zur Förderung von Energieeinsparungen notwendig. Energiespartipps informieren über energiesparende Verhaltensweisen und Produkte. Zur Formulierung wirkungsvoller Energiespartipps untersucht die Arbeit, welchen Einfluss Ergänzungen von CO2-Angaben und Formulierungen der Konsequenzen auf die wahrgenommene Informationsqualität, Nützlichkeit und Verhaltensabsicht haben. Außerdem wird untersucht, ob es diesbezüglich Unterschiede zwischen verhaltens- und investitionsorientierten Tipps gibt. Dazu wurde ein Onlineexperiment (N = 352) im 4 x 4 x 2 Design mit den vierstufigen Zwischensubjektfaktoren Framing der Währung (alleinige CO2-Angabe, Jahresvergleichswert, äquivalente Fahrstrecke, äquivalente Laptopnutzung) und Framing der Konsequenz (erreichte Einsparung, vermiedener Ausstoß, entgangene Einsparung, verursachter Ausstoß) sowie der Art des Energiespartipps (verhaltens- vs. investitionsorientiert) als zweistufigen Innersubjektfaktor konzipiert. Varianzanalysen ergaben, dass der verhaltensorientierte Tipp positiver als der investitionsorientierte Tipp bewertet wurde und verhaltensnahe Ergänzungen die Nützlichkeit von CO2-Angaben sowie die Verhaltensintention erhöhen. Das Framing der Konsequenz hatte keinen Effekt. Die Ergebnisse zeigen die Relevanz, zwischen verhaltens- und investitionsorientierten Energiespartipps zu differenzieren und verhaltensnahe Ergänzungen von CO2-Angaben in Kilogramm zu berücksichtigen.
Ziel der vorliegenden Forschungsarbeit ist es, den Einfluss von Persönlichkeit auf nachhaltige Maßnahmen anhand des Streamingkonsums zu eruieren. Der allgemein steigende Streamingkonsum und die damit einhergehenden Umweltschäden einerseits und ein wachsendes gesellschaftliches Umweltbewusstsein andererseits stellen einen Widerspruch dar. An einer Online-Umfrage zu diesen und weiterführenden Aspekten nahmen 204 Probanden teil. Während sich die Eigenschaften Verträglichkeit und Offenheit in hoher Ausprägung positiv auf die Umwelteinstellung, das Umweltverhalten und die Umweltbesorgnis auswirkten, wurden die umweltfreundlichen Maßnahmen in einer Clusteranalyse hingegen stärker von der Gruppe bevorzugt, deren Verträglichkeit und Offenheit verhältnismäßig schwach ausgeprägt waren. Ein geringes Wissen über die streamingbedingten Umweltfolgen lag grundsätzlich vor und dient als möglicher Erklärungsansatz des genannten Widerspruchs. Die Probanden forderten, ein Bewusstsein für diese Thematik zu schaffen. Um Streamingkonsum umweltfreundlicher zu gestalten empfiehlt es sich, alle am Prozess beteiligten Akteure einzubeziehen. Die befragten Konsumenten bevorzugten dabei vor allem die Verwendung von Ökostrom und lehnten eine Umstellung der Bezahlstruktur vorwiegend ab.
The accurate forecasting of solar radiation plays an important role for predictive control applications for energy systems with a high share of photovoltaic (PV) energy. Especially off-grid microgrid applications using predictive control applications can benefit from forecasts with a high temporal resolution to address sudden fluctuations of PV-power. However, cloud formation processes and movements are subject to ongoing research. For now-casting applications, all-sky-imagers (ASI) are used to offer an appropriate forecasting for aforementioned application. Recent research aims to achieve these forecasts via deep learning approaches, either as an image segmentation task to generate a DNI forecast through a cloud vectoring approach to translate the DNI to a GHI with ground-based measurement (Fabel et al., 2022; Nouri et al., 2021), or as an end-to-end regression task to generate a GHI forecast directly from the images (Paletta et al., 2021; Yang et al., 2021). While end-to-end regression might be the more attractive approach for off-grid scenarios, literature reports increased performance compared to smart-persistence but do not show satisfactory forecasting patterns (Paletta et al., 2021). This work takes a step back and investigates the possibility to translate ASI-images to current GHI to deploy the neural network as a feature extractor. An ImageNet pre-trained deep learning model is used to achieve such translation on an openly available dataset by the University of California San Diego (Pedro et al., 2019). The images and measurements were collected in Folsom, California. Results show that the neural network can successfully translate ASI-images to GHI for a variety of cloud situations without the need of any external variables. Extending the neural network to a forecasting task also shows promising forecasting patterns, which shows that the neural network extracts both temporal and momentarily features within the images to generate GHI forecasts.
Solar energy is one option to serve the rising global energy demand with low environmental Impact [1]. Building an energy system with a considerable share of solar power requires long-term investment and a careful investigation of potential sites. Therefore, understanding the impacts from varying regionally and locally determined meteorological conditions on solar energy production will influence energy yield projections. Clouds are moving on a short term timescale and have a high influence on the available solar radiation, as they absorb, reflect and scatter parts of the incoming light [2]. However, modeling photovoltaic (PV) power yields with a spectral resolution and local cloud information gives new insights on the atmospheric impact on solar energy.
Anhand detaillierter Netzanalysen für ein reales Mittelspannungsnetzgebiet konnte gezeigt werden, dass sowohl die Einbindung von Prognosedaten auf Basis von Satelliten und Wetterdaten, als auch die Verbesserung von Folgetagsprognosen auf der Basis numerischer Wettermodelle einen deutlichen Mehrwert für ein prognosebasiertes Engpassmanagement bzw. Redispatch und Blindleistungsmanagement im Verteilnetz aufweisen. Auch Kurzfristprognosen auf der Basis von Satellitendaten haben einen positiven Effekt. Ein weiterer wichtiger Mehrwert des Projektes ist auch die Rückmeldung der kritischen Prognosesituationen aus Sicht der Anwendungsfälle, so dass wie bereits im Projekt gezeigt und darüber hinaus, Prognosen zielgerichteter auf die Anwendung im Verteilnetzbetrieb ausgelegt und optimiert werden können.
Weiterhin konnten Prognoseverbesserungen für das Vorhersagemodell des Deutschen Wetterdienstes durch die Assimilation von sichtbaren Satellitenbildern erreicht werden. Darüber hinaus wurden Wolken- und Strahlungsprodukte aus Satelliten verbessert und somit die Datenbasis für die Kurzfristprognose als auch für die Assimilation.
Darüber hinaus wurden verschiedene Methoden entwickelt, die zukünftig zu einer weiteren Prognoseverbesserung, insbesondere für Wettersituationen mit hohen Prognosefehlern, führen könnten. Solche Situationen wurden aus Sicht des Netzbetriebs und mithilfe von satellitenbasierten Analysen der Gesamtwetterlage für die Perioden der MetPVNet Messkampagnen identifiziert. Hierbei handelte es sich insbesondere um Situationen mit starker oder stark wechselhafter Bewölkung.
Für die MetPVNet Messkampagnen wurde auf der Basis eines Trainingsdatensatzes und in Abhängigkeit der Variabilitätsklasse die Abweichung der bodennahen Einstrahlung von Satellitendaten oder von Strahlungsprognosen quantifiziert. Diese Art der Informationen bietet zukünftig die Möglichkeit zur Bewertung der Prognosegüte.
Accurate forecasting of solar irradiance is crucial for the integration of solar energy into the power grid, power system planning, and the operation of solar power plants. The Weather Research and Forecasting (WRF) model, with its solar radiation (WRF-Solar) extension, has been used to forecast solar irradiance in various regions worldwide. However, the application of the WRF-Solar model for global horizontal irradiance (GHI) forecasting in West Africa, specifically in Ghana, has not been studied. This study aims to evaluate the performance of the WRF-Solar model for GHI forecasting in Ghana, focusing on 3 health centers (Kologo, Kumasi and Akwatia) for the year 2021. We applied a two one-way nested domain (D1=15 km and D2=3 km) to investigate the ability of the WRF solar model to forecast GHI up to 72 hours in advance under different atmospheric conditions. The initial and lateral boundary conditions were taken from the ECMWF operational forecasts. In addition, the optical aerosol depth (AOD) data at 550 nm from the Copernicus Atmosphere Monitoring Service (CAMS) were considered. The study uses statistical metrics such as mean bias error (MBE), root mean square error (RMSE), to evaluate the performance of the WRF-Solar model with the observational data obtained from automatic weather stations in the three health centers in Ghana. The results of this study will contribute to the understanding of the capabilities and limitations of the WRF-Solar model for forecasting GHI in West Africa, particularly in Ghana, and provide valuable information for stakeholders involved in solar energy generation and grid integration towards optimized management of in the region.
Accurate global horizontal irradiance (GHI) forecasting is critical for integrating solar energy into the power grid and operating solar power plants. The Weather Research and Forecasting model with its solar radiation extension (WRF-Solar) has been used to forecast solar irradiance in different regions around the world. However, the application of the WRF-Solar model to the prediction of GHI in West Africa, particularly Ghana, has not yet been investigated. The aim of this study is to evaluate the performance of the WRF-Solar model for predicting GHI in Ghana, focusing on three automatic weather stations (Akwatia, Kumasi and Kologo) for the year 2021. We used two one-way nested domains (D1 = 15 km and D2 = 3 km) to investigate the ability of the fully coupled WRF-Solar model to forecast GHI up to 72-hour ahead under different atmospheric conditions. The initial and lateral boundary conditions were taken from the ECMWF high-resolution operational forecasts. Our findings reveal that the WRF-Solar model performs better under clear skies than cloudy skies. Under clear skies, Kologo performed best in predicting 72-hour GHI, with a first day nRMSE of 9.62 %. However, forecasting GHI under cloudy skies at all three sites had significant uncertainties. Additionally, WRF-Solar model is able to reproduce the observed GHI diurnal cycle under high AOD conditions in most of the selected days. This study enhances the understanding of the WRF-Solar model’s capabilities and limitations for GHI forecasting in West Africa, particularly in Ghana. The findings provide valuable information for stakeholders involved in solar energy generation and grid integration towards optimized management in the region.
Background:
Access to electricity is one of the enabling factors for healthcare service provision. From the sustainable development perspective, an essential requirement for improving health and caring for our environment is to assure that health facilities have sufficient and reliable access to the supply of clean and sustainable energy. The objective of this work is to investigate the users’ perceptions of electricity needs and electricity sources and the way those influence different attributes and their relevance for the diffusion of renewable electricity systems in healthcare facilities.
Methods:
To identify preferences and choices, Stated Choice modelling was applied as the use of solar PV systems in health facilities is not widespread in Ghana. This method allows to present the respondents with hypothetical options, which have attributes close to the real world. Four attributes were considered, namely electricity system configuration, initial investment cost, monthly costs, and improvements to the reliability of the electricity supply.
Results:
The largest share of the 200 health facilities interviewed reported services provision as outpatient treatment, provision of maternity services and family planning, which are relatively low electricity-intensive services. However, there was a general perception that increased reliability on the electricity supply can improve the health service provision and operation of the facilities. Moreover, despite that preferences towards the solar systems, the initial investment costs of the solar systems is still perceived as preventing the adoption of this technology
Conclusion:
From this study we can conclude that health facilities in Ghana rely greatly on the national supply which has issues with reliability, compromising the delivery of healthcare services. However, the adoption of alternative electricity technologies based on renewable sources is not likely to occur at the facility level without the engagement of other actors that can help bridging the barriers for adoption, as initial investment costs.