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The research employed HPTLC Pro System and other HPTLC instruments from CAMAG® to conduct various laboratory tests, aiming to compile a database for subsequent analyses. Utilizing MATLAB, distinct codes were developed to reveal patterns within analyzed biomasses and pyrolysis oils (sewage sludge, fermentation residue, paper sludge, and wood). Through meticulous visual and numerical analysis, shared characteristics among different biomasses and their respective pyrolysis oils were revealed, showcasing close similarities within each category. Notably, minimal disparity was observed in fermentation residue and wood biomasses with a similarity coefficient of 0.22. Similarly, for pyrolysis oils, the minimal disparity was found in fermentation residues 1 and 3, with a disparity coefficient of 1.41. Despite higher disparity coefficients in certain results, specific biomasses and pyrolysis oils, such as fermentation residue and sewage sludge, exhibited close similarities, with disparity coefficients of 0.18 and 0.55, respectively. The database, derived from triplicate experimentation, now serves as a valuable resource for rapid analysis of newly acquired raw materials. Additionally, the utility of HPTLC PRO as an investigation tool, enabling simultaneous analysis of up to five samples, was emphasized, although areas for improvement in derivatization methods were identified.
Increasing global energy demand and the need to transition to sustainable energy sources to mitigate climate change, highlights the need for innovative approaches to improve the resilience and sustainability of power grids. This study focuses on addressing these challenges in the context of Morocco's evolving energy landscape, where increasing energy demand and efforts to integrate renewable energy require grid reinforcement strategies. Using renewable energy sources such as photovoltaic systems and energy storage technologies, this study aims to develop a methodology for strengthening rural community grids in Morocco.
Traditional reinforcement measures such as line and transformer upgrades will be investigated as well as the integration of power generation from photovoltaic systems, which offer a promising way to utilise Morocco's abundant solar resources. In addition, energy storage systems will be analysed as potential solutions to the challenges of grid stability and resilience. Using comprehensive data analysis, scenario planning and simulation methods with the open-source simulation software Panda Power, this study aims to assess the impact of different grid reinforcement measures, including conventional methods, photovoltaic integration, and the use of energy storage, on grid performance and sustainability. The results of this study provide valuable insights into the challenges and opportunities of transitioning to a more resilient and sustainable energy future in Morocco.
Based on a rural medium-voltage grid in Souihla, Morocco, three scenarios were carried out to assess the impact of demand growth in 2030 and 2040. The first scenario focuses on conventional grid reinforcement measures, while the second scenario incorporates energy from residential photovoltaic systems. The third scenario analyses the integration of storage systems and their impact on grid reinforcement in 2030.
The simulations with energy from photovoltaic systems show a reduction in grid reinforcement measures compared to the scenario without solar energy. In addition, the introduction of a storage system in 2030 led to a significant reduction in the required installed transformer capacity and fewer congested lines. Furthermore, the results emphasized the role of storage in stabilizing grid voltage levels.
In summary, the results highlighted the potential benefits of integrating energy from photovoltaics and storage into the grid. This integration not only reduces the need for transformers and overall grid infrastructure but also promotes a more efficient and sustainable energy system.
The growing threat posed by multidrug-resistant (MDR) pathogens, such as Klebsiella pneumoniae (Kp), represents a significant challenge in modern medicine. Traditional antibiotic therapies are often ineffective against these pathogens, leading to high mortality rates. MDR Kp infections pose a novel challenge in military medical contexts, particularly in Medical Biodefense, as they can be deliberately spread, leading to resource-intensive care in military centres. Recognizing this issue, the European Defence Agency initiated a prioritised research project in 2023 (EDF Resilience PHAGE- SGA 2023). To address this challenge, the Bundeswehr Institute of Microbiology (IMB) leads BMBF- (Federal Ministry of Education and Research) and EU-funded projects on the use of bacteriophages as adjuvant therapy alongside antibiotics. Since 2017, the IMB has isolated and characterised Kp phages, collecting over 600 isolates and optimizing their production for therapy, in compliance with the EMA (European Medicine Agency) guidelines. This involves in vitro phage genome packaging to minimize endotoxin load, reduce manufacturing costs, and shorten production times. The goal of this work was to establish MinION sequencing (Oxford Nanopore Technology) as a quick and reliable way for initial identification and characterisation of phage genomes. Especially as a quick screening method for isolated on Kp, prior to more precise but also more expensive and time consuming sequencing methods like Illumina. This characterisation is crucial for developing a personalized pipeline aimed at producing magistral or Good Manufacturing Practice (GMP) quality medicinal phage solutions tailored individually for each patient. DNA extraction methods were compared to identify suitable input DNA for sequencing purposes. Additionally, the quality of this DNA was as- sessed to determine its suitability for in vitro phage packaging, which was successfully done achieving a phage titer of 103, confirming that the DNA used for MinION sequencing could indeed be used for acellular packaging. The created genomes were annotated and compared with Illumina sequencing, revealing high similarity in all five individually tested cases. Between the generated sequences only a 4% maximal percentual difference in genome size was observed, while simultaneously showing high similarity in the actual sequence. Throughout the course of this study, a total of 645.15 GB of sequencing data were generated. In total, 38 phages were successfully characterised, with 21 phage genomes assembled and annotated, and saved in the IMB database.
Steroid hormones (SHs) are a rising concern due to their high bioactivity, ubiquitous nature, and prolonged existence as a micropollutants in water, they pose a potential risk to both human health and the environment, even at low concentrations. Estrogens, progesterone, and testosterone are the three important types of steroids essential for human development and maintaining multiorgan balance, are focus to this concern. These steroid hormones originate
from various sources, including human and livestock excretions, veterinary medications, agricultural runoff, and pharmaceuticals, contributing to their presence in the environment. According to the recommendation of WHO, the guidance value for estradiol (E2) is 1 ng/L. There are several methods been attempted to remove the SH micropollutant by conventional water and wastewater technologies which are still under research. Among the various methods, electrochemical membrane reactor (EMR) is one of the emerging technologies that can address the challenge of insufficient SHs removal from the aquatic environment by conventional treatment. The degradation of SHs can be significantly influenced by various factors when treated with EMR.
In this project, the removal of SH and the important mechanism for the removal using carbon nanotube CNT-EMR is studied and the efficiency of CNT-EMR in treating the SH micropollutant is identified. By varying different parameters this experiment is carried out with the (PES-CNTs) ultrafiltration membrane. The study is carried out depending upon the SH removal based on the limiting factor such as cell voltage, flux, temperature, concentration, and type of the SH.
Decarbonisation Strategies in Energy Systems Modelling: APV and e-tractors as Flexibility Assets
(2023)
This work presents an analysis of the impact of introducing Agrophotovoltaic technologies and electric tractors into Germany’s energy system. Agrophotovoltaics involves installing photovoltaic systems in agricultural areas, allowing for dual usage of the land for both energy generation and food production. Electric tractors, which are agricultural machinery powered by electric motors, can also function as energy storage units, providing flexibility to the grid. The analysis includes a sensitivity study to understand how the availability of agricultural land influences Agrophotovoltaic investments, followed by the examination of various scenarios that involve converting diesel tractors to electric tractors. These scenarios are based on the current CO2 emission reduction targets set by the German Government, aiming for a 65% reduction below 1990 levels by 2030 and achieving zero emissions by 2045. The results indicate that approximately 3% of available agricultural land is necessary to establish a viable energy mix in Germany. Furthermore, the expansion of electric tractors tends to reduce the overall system costs and enhances the energy-cost-efficiency of Agrophotovoltaic investments.
As the population grows, so does the amount of biowaste. As demand for energy grows, biogas is a promising solution to the problem. Lignocellulosic materials are challenged of slow degradability due to the presence of polymers such as cellulose, lignin and hemicellulose. There are several pretreatment methods available to enhance the degradability of such materials, including enzymatic pretreatment. In this pretreatment, there are few parameters that can influence the results, the most important being the enzyme to solid ratio and the solid to liquid ratio. During this project, experiments were conducted to determine the optimal conditions for those two factors. It was discovered that a solid to liquid ratio of 31 g of buffer per 1 gram of organic dry matter produced the highest reducing sugar release in flasks when combined with 34 mg of protein per 1 gram of organic dry mass. Additionally, another experiment was carried out to investigate the impact of enzymatic pretreatment on biogas production using artificial biowaste as a substrate. Artificial biowaste produced 577,9 NL/kg oDM, while enzymatically pretreated biowaste produced 639,3 NL/kg oDM. This resulted in a 10,6% rise in cumulative biogas production compared to its use without enzymatic pretreatment. By the conclusion of the investigation, specific cumulative dry methane yields of 364,7 NL/kg oDM and 426,3 NL/kg oDM were obtained from artificial biowaste without and with enzymatic pretreatment, respectively. This resulted in a methane production boost of 16,9%. Additionally in case of the reactors with enzymatically pretreated substrate kinetic constant was lower more than double, where maximum volume of biogas increased, comparing to the reactors without enzymatic pretreatment.
In recent years, the demand for reliable power, driven by sensitive electronic equipment, has surged. Even minor deviations from the nominal supply can lead to malfunctions or failure. Despite technological advancements, power quality issues persist due to various factors like short circuits, overloads, voltage fluctuations, unbalanced loads, and non-linear loads.
This thesis extensively explores power quality anomalies in industrial and commercial sectors, using power system data as the primary analytical resource. It addresses the critical need for power supply reliability in today's evolving power grid industry, affected by non-linear loads, renewable energy integration, and electric vehicles. This field of study is paramount for ensuring power supply reliability and stability in the evolving power grid industry.
The core of this thesis involves a comprehensive investigation of power quality, with a focus on frequency, power, and harmonics in voltage and current signals. The research employs Python programming for advanced data analysis, utilizing techniques such as advanced Fast Fourier Transformation (FFT) analysis. The primary objective is to provide valuable insights aimed at elevating power supply quality and enhancing reliability in both industrial and commercial environments.
The cellulase-producing Trichoderma reesei strain RL-P37 exhibits significant potential, yielding 7.3 g/L of cellulase in 241 hours. Microscopic investigations reveal a link between spore formation and enzyme production, suggesting the need for research into the intricate relationship between enzyme production, stress responses, and the nutritional prerequisites of fungi. Comparatively, the use of sodium hydroxide (NaOH) treatment, as opposed to water treatment, results in the reduction of micronutrient content and carbon source extraction as filtrate. Despite these challenges, research by He et al. (2021) highlights NaOH's efficiency in cellulose extraction from plant-based sources. Using NaOH pretreatment can be proven as effective by designing a proper cultivation method. The selection of inducers for enzyme induction gains importance, with soluble inducers, as emphasized by Zhang et al. (2022), exhibiting superior effectiveness. Hence, adopting soluble inducers in designing cultivation methods for improved enzyme production in shaking flasks is recommended. Enzymatic treatment of bio-waste, as outlined by Hu et al. (2021), shows promise in augmenting essential component content by breaking down plant cell walls and intercellular compartments. However, the feasibility of using an artificial bio-waste medium for cultivating Trichoderma reesei is questioned. Investigating the impact of micronutrient levels, particularly the inhibitory role of zinc, on fungal growth becomes essential. These findings underscore the necessity for ongoing research and optimization in cellulase production, emphasizing both strain productivity and cultivation methodologies.
Estimation and projecting total steel industry production costs from 2019 to 2030 for Germany
(2023)
This thesis analyses the total production cost of the German steel industry from 2019 to 2022, as well as a projection of the German steel industry's total production cost until 2030. The research separates the costs of steel production into their primary components, such as raw materials, energy, CO2 cost, capital expenses and operating expenses. The cost of steel production is determined separately for primary steelmaking with the blast furnace and basic oxygen furnace (BF-BOF) and secondary steelmaking with the electric arc furnace (EAF).
The analysis indicates that, following the COVID-19 disaster and the fuel crisis, the overall cost of producing steel in Germany has progressively risen over the previous few years, reaching its peak in the first half of 2022. In addition, there are considerable disparities between the production costs of primary and secondary steelmaking processes, with primary steelmaking generally being more expensive.
In this analysis, the total cost of production for the German steel industry in the year 2030 has been estimated by taking into account historical trends as well as other predictions that are currently available.
This thesis provides overall insights on the economics of the German steel sector. By giving thorough information on production costs and changes over time, this research can assist guide crucial future investment decisions in this essential industry. To ensure long-term success, our findings emphasize the significance of investing in more sustainable and ecologically friendly steel production processes.
The purpose of this master's thesis was to set up a test bed for the absorption of chemical compounds by carbon-based sorbents and polymers and to develop a method for the detection of these substances applied by liquid chromatography.
The study made it possible to demonstrate the effectiveness of both polymers and biochars sorbents for the adosorption of specific substances. The results obtained open new paths on the study of biochar for the treatment of contaminated water. Some biochars made from plant-based materials have been shown to be almost as effective as commercial products used in plants. The developed chromatography method allows efficient separation of substances and their detection.
Self-sufficient enzymes belong to the cytochrome P450 (CYP) group and are known for their superior hydroxylation catalytic activity. In the pursuit of identifying new pesticides to combat antimicrobial-resistant pathogens, we employed BM3 wild type (BM3-WT), the fastest monohydroxylating CYP, along with its seven homologs, to investigate the production of potential hydroxylated derivatives from the established pesticide, 4-oxocrotonic acid using high-pressure liquid chromatography (HPLC) method. Following the recombinant production of BM3-WT and three other homologs in E. coli, and their subsequent purification using Immobilized Metal Affinity Chromatography (IMAC), a novel enzyme assay approach was developed as a substitute for the carbon monoxide (CO) assay. This new method relied on the measurement of NADPH consumption at 340 nm by BM3-WT for palmitic acid. Leveraging this established technique, we explored the substrate specificity of BM3-WT and its homologs not only on palmitic acid but also on other structurally similar compounds, including 4-oxocrotonic acid. The results obtained from the established NADPH assay indicate that all tested enzymes displayed greater catalytic activity on 4-oxocrotonic acid in comparison to other substrates with similar structures. However, the impact of BM3-WT and its homologs on 4-oxocrotonic acid varied in terms of product specificity. Enzymes such as Poh, Trr and Bas-CYP D exhibited specificity in producing solely monohydroxylated products, while others tended to yield dehydroxylated and ketol metabolites.
The effects of climate change, including severe storms, heat waves, and melting glaciers, are highlighted as an urgent concern, emphasising the need to decrease carbon emissions to restrict global warming to 1.5°C. To accomplish this goal, it is vital to substitute fossil fuel-based power plants with renewable energy sources like solar, wind, hydro, and biofuels. Despite some progress being made, the proportion of renewables used in generating electricity is still lower than the levels needed for 2030 and 2050. Decarbonising the power grid is also critical in lowering the energy consumption of buildings, which is responsible for a substantial percentage of worldwide electricity usage. Even though there has been substantial expansion in the worldwide renewable energy market in the past 15 years, the transition to renewable energy sources also requires taking into account the importance of energy trading.
Peer-to-peer (P2P) electricity trading is an emerging type of energy exchange that can revolutionise the energy sector by providing a more decentralised and efficient way of trading energy. This research deals about P2P electricity trading in a carbon-neutral scenario. 'Python for Power System Analysis' (PyPSA) was used to develop models through which the P2P effect was tested. Data for the entire state of Baden-Württemberg (BW) was collected. Three scenarios were taken into consideration while developing models: 2019 (base), 2030 (coal phase-out), and 2040(climate neutral). Alongside this, another model with no P2P trading was developed to make a comparison. In addition, the use case of community storage in a P2P trading network is also presented.
The research concludes that P2P has a significant positive effect on a pathway to achieve climate neutrality. The findings show that the share of renewables in electricity generation is increasing compared to conventional sources in BW, which can be traded to meet the demand. From the storage analysis, it can be concluded that community storage can be effectively utilised in P2P trading. While the emissions are reduced, the operating costs are also reduced when the grid has P2P trading available. By highlighting the benefits of P2P trading, this research contributed to the growing body of research on the effectiveness of P2P trading in an electricity network grid.
Decarbonisation Strategies in Energy Systems Modelling: Biochar as a Carbon Capture Technology
(2022)
The energy system is changing since some years in order to achieve the climate goals from the Paris Agreement which wants to prevent an increase of the global temperature above 2 °C. Decarbonisation of the energy system has become for governments a big challenge and different strategies are being stablished. Germany has set greenhouse gas reduction limits for different years and keeps track of the improvement made yearly. The expansion of renewable energy systems (RES) together with decarbonisation technologies are a key factor to accomplish this objective.
This research is done to analyse the effect of introducing biochar, a decarbonisation technology, and study how it will affect the energy system. Pyrolysis is the process from which biochar is obtained and it is modelled in an open-source energy system model. A sensibility analysis is made in order to assess the effect of changing the biomass potential and the costs for pyrolysis.
The role of pyrolysis is analysed in the form of different future scenarios to evaluate the impact. The CO2 emission limits from the years 2030 and 2045 are considered to create the scenarios, as well as the integration of flexibility technologies. Four scenarios in total are assessed and the result from the sensibility analysis considering pyrolysis are always compared to the reference scenario, where pyrolysis is not considered.
Results show that pyrolysis has a bigger impact in the energy system when the CO2 limit is low. Biochar can be used to compensate the emissions from other conventional power plant and achieve an energy transition with lower costs. Furthermore, it was also found that pyrolysis can also reduce the need of flexibility. This study also shows that the biomass potential and the pyrolysis costs can affect a lot the behaviour of pyrolysis in the energy system.
Global energy demand is still on an increase during the last decade, with a lot of impact on the climate change due to the intensive use of conventional fossil-based fuels power plants to cover this demand. Most recently, leaders of the globe met in 2015 to come out with the Paris Agreement, stating that the countries will start to take a more responsible and effective behaviour toward the global warming and climate change issues. Many studies have discussed how the future energy system will look like with respecting the countries’ targets and limits of greenhouse gases and their CO2 emissions. However, these studies rarely discussed the industry sector in detail even though it is one of the major role players in the energy sector. Moreover, many studies have simulated and modelled the energy system with huge jumps of intervals in terms of years and environmental goals. In the first part of this study, a model will be developed for the German electrical grid with high spatial and temporal resolutions and different scenarios of it will be analysed meticulously on shorter periods (annual optimization), with different flexibilities and used technologies and degrees of innovations within each scenario. Moreover, the challenge in this research is to adequately map the diverse and different characteristics of the medium-sized industrial sector. In order to be able to take a first step in assessing the relevance of the industrial sector in Germany for climate protection goals, the industrial sector will be mapped in PyPSA-Eur (an open-source model data set of the European energy system at the level of the transmission network) by detailing the demand for different types of industry and assigning flexibilities to the industrial types. Synthetically generated load profiles of various industrial types are available. Flexibilities in the industrial sector are described by the project partner Fraunhofer IPA in the GaIN project and can be used. Using a scenario analysis, the development of the industrial sector and the use of flexibilities are then to be assessed quantitatively.
The Lattice Boltzmann Method is a useful tool to calculate fluid flow and acoustic effects at the same time. Although the acoustic perturbation is much smaller than normal pressure differences in fluid flow, this direct calculation is a great advantage of the Lattice Boltzmann Method (LBM). But each border used in calculation produces a multitude of reflections with the acoustic waves, which lead to an unusable result. Therefore, it is worked on different absorbing techniques.
In this thesis three absorbing layer techniques are described, explained and reviewed with different simulations. The absorbing layers are implemented in a basic LBM code in C++, and with this umpteen simulations within a box were performed to compare the different absorbing layers. The Doppler effect and a cylinder flow are also examined to compare the damping efficiencies.
The three studied absorbing techniques are the sponge layer, the perfectly matched layer and a force based Term II absorbing layer. The sponge layer is easy to implement but gives worse results than a calculation without any absorbing layer. The perfectly matched layer and a force based absorbing term provide very good results but the perfectly matched layer has problems with instability. The force based absorbing layer represents the best compromise between the additional computation time due the absorbing layer and the achieved damping efficiency.
Quarz crystal microbalances allow the monitoring of the adsorption process of mass from a liquid to their surface. The adsorbed mass can be analysed regarding to its protein content using mass spectromety. To ensure the protein identification the results of several measurements can be combined. A high content QCM-D array was developed to allow up to ten measurements parallel. The samples can be routed inside the array distributing one sample to several chips. The fluidic parts were prototyped using 3D printing. The assembled array was tight and the sample routing function could be demonstrated. A temperature controller was developed and implemented. The parameters for the PID controller were determined and the controller was shown to be able to keep the temperature constant over long time with high accuracy.