• Energy Research
• 2021-2025close
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Tree cores were sampled using increment borers. At each site three trees were chosen for coring, with two or three cores taken per tree. Cores were sanded and ring widths measured based on high-resolution images of the sanded cores. Cores were cross-dated and summary statistics used to compare cross-dating accuracy. The dataset contains the resulting dated ring width series. This dataset includes tree ring width data, derived from tree cores, that were sampled from sites across the Rhön Biosphere Reserve (Germany). At each chosen site three trees were cored, with two or three cores taken per cored tree. Data was collected in August 2021.

Bioplastics are alternatives of conventional petroleum-based plastics. Bioplastics are polymers processed from renewable sources and are biodegradable. This study aims at conducting an environmental impact assessment of the bioprocessing of agricultural wastes into bioplastics compared to petro-plastics using an LCA approach. Bioplastics were produced from potato peels in laboratory. In a biochemical reaction under heating, starch was extracted from peels and glycerin, vinegar and water were added with a range of different ratios, which resulted in producing different samples of bio-based plastics. Nevertheless, the environmental impact of the bioplastics production process was evaluated and compared to petro-plastics. A life cycle analysis of bioplastics produced in laboratory and petro-plastics was conducted. The results are presented in the form of global warming potential, and other environmental impacts including acidification potential, eutrophication potential, freshwater ecotoxicity potential, human toxicity potential, and ozone layer depletion of producing bioplastics are compared to petro-plastics. The results show that the greenhouse gases (GHG) emissions, through the different experiments to produce bioplastics, range between 0.354 and 0.623 kg CO2 eq. per kg bioplastic compared to 2.37 kg CO2 eq. per kg polypropylene as a petro-plastic. The results also showed that there are no significant potential effects for the bioplastics produced from potato peels on different environmental impacts in comparison with poly-β-hydroxybutyric acid and polypropylene. Thus, the bioplastics produced from agricultural wastes can be manufactured in industrial scale to reduce the dependence on petroleum-based plastics. This in turn will mitigate GHG emissions and reduce the negative environmental impacts on climate change.

The presented Solid Fuel Entrained Flow Gasification Database contains complete datasets on individual solid fuels considering the most important physical properties and conversion behavior analysis necessary for the simulation of pressurized high temperature entrained flow gasification. This includes their composition (proximate- and ultimate analysis, XRF of ash at 200, 450, 815 and 1500 °C) as well as physical properties such as original mineral phase composition (XRD), density (true and tap) and particle size distribution. The database also contains data on fuel behavior such as heating values, swelling factors, fragmentation index, slag viscosity, ash melting behavior and ash mineral phase evolution during heat-up and cool-down. Moreover, the database provides model parameters describing their pyrolysis behavior, gasification kinetics including product gas inhibition, thermal deactivation and surface area development. Chars produced and gasified in pressurized high temperature entrained flow reactors like the PiTER (located at the Chair of Energy Systems of the Technical University of Munich) and the KIVAN (operated by the Institute of Energy Process Engineering and Chemical Engineering of the TU Bergakademie Freiberg) were analyzed in thermogravimetric and structural analyzer. Since these reactors are designed for temperatures up to 1800 °C (PiTER) and pressures up to 100 bar (KIVAN), the resulting model parameters are relevant for the simulation of industrial scale applications. In order to validate the applied models for entrained flow gasification kinetics, the database refers to several publications describing the models and experimental setups as well as providing additional experimental data points.

This dataset contains a compilation of noble gas, hydrochemistry, stable water isotopes and radiocarbon from dissolved organic carbon data sampled from geothermal power plants and research wells screened in the deep Upper Jurassic Aquifer in the South German Molasse Basin in Bavaria. This dataset was used to calculate noble gas infiltration temperatures and reconstruct the paleoclimate in Southern Germany during the Late Pleistocene. More details on the methods used to calculate noble gas infiltration temperatures and radiocarbon dating can be found in the associated publication.

The promotion of electric vehicles (EVs) is an important measure for dealing with climate change and reducing carbon emissions, which are widely agreed goals worldwide. Being an important operating mode for electric vehicle charging stations in the future, the integrated photovoltaic and energy storage charging station (PES-CS) is receiving a fair amount of attention and discussion. However, how to optimally configure photovoltaic and energy storage capacity to achieve the best economy is essential and a huge challenge to overcome. In this paper, based on the historical data-driven search algorithm, the photovoltaic and energy storage capacity allocation method for PES-CS is proposed, which determines the capacity ratio of photovoltaic and energy storage by analyzing the actual operation data, which is performed while considering the target of maximizing economic benefits. In order to achieve the proposed capacity allocation, the method is as follows: First, the economic benefit model of the charging stations is established, taking the net present value and investment payback period as evaluation indicators; then, by analyzing the operation data of the existing charging station with the target of maximizing economic benefits, the initial configuration capacity is obtained; finally, the capacity configuration is verified through a comprehensive case analysis for the actual operation data. The results show that the capacity configuration obtained through the data analysis features an optimized economic efficiency and photovoltaic utilization. The proposed method can provide a theoretical and practical basis for newly planned or improved large-scale charging stations.

Background. Laws that enable a circular economy (CE) are being enacted globally, but reliable standardized and digitized CE data about products is scarce, and many CE platforms have differing exclusive formats. In response to these challenges, the Ministry of The Economy of Luxembourg launched the Circularity Dataset Standardization Initiative to develop a globalized open-source industry standard to allow the exchange of standardized data throughout the supply cycle, based on these objectives: (a) Provide basic product circularity data about products. (b) Improve circularity data sharing efficiency. (c) Encourage improved product circularity performance. A policy objective was to have the International Organization for Standardization (ISO) voted to create a working group. Methods. A state-of-play analysis was performed concurrently with consultations with industry, auditors, data experts, and data aggregation platforms. Results. Problem statements were generated. Based on those, a solution called Product Circularity Data Sheet (PCDS) was formulated. A proof of concept (POC) template and guidance were developed and piloted with manufacturers and platforms, thus fulfilling objective (a). For objective (b), IT ecosystem requirements were developed, and aspects are being piloted in third party aggregation platforms. Objective (c) awaits implementation of the IT ecosystem. The policy objective related to the ISO was met. Conclusions and future research. In order to fully test the PCDS, it is necessary to: conduct more pilots, define governance, and establish auditing and authentication procedures.

In this paper, a novel experimental setup to quantify the particle deposition during a lithium-ion battery thermal runaway (TR) is proposed. The setup integrates a single prismatic battery cell into an environment representing similar conditions as found for battery modules in battery packs of electric vehicles. In total, 86 weighing plates, positioned within the flow path of the vented gas and particles, can be individually removed from the setup in order to determine the spatial mass distribution of the deposited particles. Two proof-of-concept experiments with different distances between cell vent and module cover are performed. The particle deposition on the weighing plates as well as the particle size distribution of the deposited particles are found to be dependent on the distance between cell vent and cover. In addition, the specific heat capacity of the deposited particles as well as the jelly roll remains are analyzed. Its temperature dependency is found to be comparable for both ejected particles and jelly roll remains. The results of this study help researches and engineers to gain further insights into the particle ejection process during TR. By implementing certain suggested improvements, the proposed experimental setup may be used in the future to provide necessary data for simulation model validation. Therefore, this study contributes to the improvement of battery pack design and safety.

As the prospect of exceeding global temperature targets set forth in the Paris Agreement becomes more likely, methods of climate intervention are increasingly being explored. With this increased interest there is a need for an assessment process to understand the range of impacts across different scenarios against a set of performance goals in order to support policy decisions. The methodology and tools developed for Performance Assessment (PA) for nuclear waste repositories shares many similarities with the needs and requirements for a framework for climate intervention. Using PA, we outline and test an evaluation framework for climate intervention, called Performance Assessment for Climate Intervention (PACI) with a focus on Stratospheric Aerosol Injection (SAI). We define a set of key technical components for the example PACI framework which include identifying performance goals, the extent of the system, and identifying which features, events, and processes are relevant and impactful to calculating model output for the system given the performance goals. Having identified a set of performance goals, the performance of the system, including uncertainty, can then be evaluated against these goals. Using the Geoengineering Large Ensemble (GLENS) scenario, we develop a set of performance goals for monthly temperature, precipitation, drought index, soil water, solar flux, and surface runoff. The assessment assumes that targets may be framed in the context of risk-risk via a risk ratio, or the ratio of the risk of exceeding the performance goal for the SAI scenario against the risk of exceeding the performance goal for the emissions scenario. From regional responses, across multiple climate variables, it is then possible to assess which pathway carries lower risk relative to the goals. The assessment is not comprehensive but rather a demonstration of the evaluation of an SAI scenario. Future work is needed to develop a more complete assessment that would provide additional simulations to cover parametric and aleatory uncertainty and enable a deeper understanding of impacts, informed scenario selection, and allow further refinements to the approach.