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Techno-economic analysis and life-cycle assessment of methanol synthesis plants using renewable hydrogen and carbon dioxide feedstocks
No full textThis paper presents a cradle-to-gate techno-economic analysis (TEA) and life-cycle assessment (LCA) of synthetic methanol production leveraging low-carbon electrolytic hydrogen and renewable CO2 captured from biomass- or biogas-powered bioenergy with capture (BEC) or direct air capture (DAC) facilities. Using a detailed chemical process model and a comprehensive cash flow analysis, we evaluate the mass and energy requirements for renewable methanol production plants using an integrated approach that couples scale effects, feedstock and energy prices, process emissions, and several other variables. In the baseline scenario, amortization of the total green methanol production costs reveals levelized costs of fuel (LCOF) equal to 1.19, and 1.50/kg can be attained. While the baseline TEA indicates that the considered renewable methanol synthesis process currently carries a green premium of 70% or more, the LCA reveals dramatic GHG reductions equal to 2.6-3.3 kg of CO2-e per kg of methanol relative to conventional methods. Overall, this research quantifies both a notable economic challenge and a considerable environmental incentive associated with low-carbon methanol production, which could inform future decarbonization efforts in the chemicals industry
The future of clean transportation:Hydrogen, batteries, ammonia, and green methane in perspective
No full textAmid growing efforts to decarbonize the transport sector, this review examines portable energy solutions for clean mobility, focusing on hydrogen, batteries, ammonia, green methane, methanol, biodiesel, and sustainable aviation fuel (SAF). We discuss the fundamentals, production routes, storage requirements, and application feasibility of each carrier, alongside recent advancements and persisting challenges. Ammonia, while valued for its favorable storage and carbon-free combustion, faces constraints such as toxicity, indirect carbon emissions, and ammonia slip, though emerging approaches like direct air capture offer promising mitigation pathways. Green methane, ethanol, biodiesel, and SAF are identified as complementary fuels suited for sector-specific deployment, whereas batteries and hydrogen show long-term promise. Cradle-to-Grave emission analyses indicate that battery technologies deliver the lowest overall greenhouse gas footprint among the cleaner energy options, while hydrogen and methanol–gasoline blends also demonstrate notably competitive performance. Cost-per-kilometer analysis indicates the lowest value for methane (0.029 /km). Lithium-ion batteries, despite high efficiency, yield moderate cost benefits (0.058 $/km) under our 100 kg energy storage system model, though high-capacity batteries could improve real-world economics. Drawing on literature data and our own assessments, we underscore that the future of clean mobility will not hinge on a single technology, but on a synergistic, multi-fuel strategy integrating the strengths of diverse energy carriers to meet the evolving demands of sustainable transport.</p
Lewatit 1065 VP OC for direct air capture; an analysis of adsorption characteristics using dynamic column breakthrough
No full textDirect air capture based on solid sorbents (S-DAC) is increasingly being recognized as an essential part of climate change mitigation strategies. This work investigates the adsorption characteristics for Lewatit 1065 OC VP which is considered a benchmark sorbent for S-DAC processes. A novel dynamic column breakthrough (DCB) instrument suited for DAC compositions is developed and described. Using both DCB experiments and volumetric measurements, we have identified a significant intra-batch variability in the CO2 loading capacity. The observed difference in CO2 capacity is found to depend entirely on the particle size from the manufacturer; thus, highlighting the importance of standardized sample selections when evaluating the properties of amine-functionalized materials. This ensures a solid database for process modeling and avoids misleading performance results of S-DAC processes. The mass transfer kinetics has been evaluated from both adsorption and desorption breakthrough experiments combined with modeling. The modeling effort includes a comparison between the commonly used linear driving force (LDF) model and a dual-site (DS) model to describe the CO2 uptake. A significant dependence on macropore resistance is confirmed, though an additional transport resistance is required to fully describe the mass transfer kinetics. We hypothesize that the CO2-amine reaction is the key contributor to the added mass transfer resistance prompting the research on new amine-functionalized materials to focus on enhancing both the macropore resistance and reaction kinetics.</p
Conceptualizing the interplay between blue justice, blue economy, and blue governance
No full textRecent literature on blue justice underscores its growing relevance to legal instruments and state practices of blue governance. The blue economy, while promising sustainable development, often generates risks for coastal communities, including displacement, inequitable distribution of benefits and harms, and exclusion from governance processes. In response, states and international organizations have begun integrating environmental justice principles into ocean policies to promote equitable access and sustainable use of marine resources. However, much of the existing research remains largely descriptive. This paper advances the discourse by conceptualizing the interplay between blue justice, blue economy, and blue governance through three analytical lenses: (1) rigid and fluid, (2) global and local, and (3) plural and singular. The first lens highlights how static governance frameworks struggle to manage dynamic marine environments, leading to “governance inelasticity.” The second lens reveals the fragmented and often asymmetrical nature of decision-making across scales, resulting in “siloed justice approaches.” The third lens critiques dominant narratives that marginalize alternative histories and visions, leading to “singular perspectives”. Together, these lenses expose how justice risks emerge from mismatches between governance structures and the socio-ecological realities of blue spaces. By making these interconnections explicit, the paper offers a conceptual foundation for rethinking marine policy and governance. In doing so, it aims to support more inclusive, adaptive, and pluralistic approaches to governing the blue economy—contributing to ongoing efforts to ensure a just and sustainable ocean future
Magnetic Resonance Imaging Provides Accurate Measures of Cartilage Creep and Biomechanical Tissue Properties: Ex vivo Comparison to Ground Truth Mechanical Testing
Full text linkCartilage mechanical properties have been suggested to be more effective biomarkers for early-stage osteoarthritis (OA) than conventional clinical pain and image feature detection, when compared with OA grading methods. However, limited research exists evaluating the feasibility of alternative methods, such as magnetic resonance imaging (MRI) techniques, to determine biomechanical properties. Therefore, this study aimed to evaluate the feasibility of clinical MRI for non-invasive evaluation of cartilage creep behaviour and biomechanical properties. Bovine cartilage samples (n = 12, diameter = 6 mm) were loaded at 0.25 MPa/s until reaching 1 MPa, then held under constant stress for 1 h using a counterbalanced study design with two different configurations. The first configuration used a custom-made, hydraulic-based MRI-compatible device to apply the load to the sample. During loading, 2D proton density-weighted fast spin echo MR images with fat suppression (CHESS method) were captured every minute. The second configuration used a universal testing machine as a ground truth (GT) reference. Time-dependent creep deformation was assessed in both configurations, and the instantaneous and equilibrium moduli were calculated at 1 min and at the end of the creep test, respectively. In addition, sample-specific fibril-reinforced poroelastic (FRPE) material parameters were estimated for both configurations using inverse finite element analysis of the measured creep data. The FRPE model successfully simulated experimental data, with mean R2 values of 0.77 [95 % CI: 0.61, 0.92] for MRI and 0.98 [95 % CI: 0.95, 0.99] for GT. Results showed comparable deformation trajectories with no significant differences in the FRPE material properties between the configurations (i.e., Ef0,Efε,Enf,k0,M). Only the mean instantaneous modulus at 1 min of creep was higher (p < 0.001) with MRI 4.5 [95 % CI: 2.9, 6.1] MPa compared to GT 2.9 [95 % CI: 2.3, 3.5] MPa. These findings demonstrate that MRI can capture cartilage creep deformation and estimate biomechanical properties with reasonable accuracy in an ex vivo setting. This advocates towards further development of the workflow for creep compression experiments in vivo. Yet, the workflow requires load-controlled relaxation and considerations of 3D contact mechanics of the human knee. While this work does not yet establish clear clinical applicability, it represents important evidence for non-invasive quantification of cartilage biomechanics. It is conceivable that our advancements may contribute to subject-specific estimation of inherent biomechanical tissue properties in the future.</p
A Two-Stage Deep Learning Approach for Accurate Day-Ahead Electricity Price Forecasting
Full text linkParticipants in the energy market are at greater risk of making decisions due to the nonlinear and volatile characteristics of electricity prices. Accurate short-term electricity price forecasting (EPF) is essential to ensure improved resource allocation, grid stability and enable market participants to manage their decisions efficiently. This study proposes a novel two-stage forecasting framework for day-ahead EPF using time series decomposition methods and hybrid deep learning algorithms. In the first stage, features related to EPF at the next time step are predicted. In this stage, the highest-frequency component extracted via Empirical Mode Decomposition (EMD) is further decomposed using Variational Mode Decomposition (VMD) so as to better capture rapid fluctuations and improve the overall prediction accuracy. Moreover, a decentralized deep learning architecture is designed in which Gated Recurrent Unit (GRU) networks are employed for high-frequency components, while Long Short-term Memory (LSTM) networks are used for the remaining components. In the second stage, EPF is generated using a hybrid LSTM and GRU structure, which incorporates both features estimated in the first stage and historical electricity price data. Finally, hyperparameters of the deep learning models are optimized using Bayesian Optimization to enhance performance. To validate the proposed framework, real market data from the DK1 region of Denmark is used. The proposed hybrid prediction framework is evaluated against both machine learning methods and deep learning-based architectures. Experimental results demonstrate that the proposed method achieves approximately 27.15 % lower RMSE compared to traditional machine learning models, and around 28.24 % lower RMSE compared to LSTM-based models.<br/
Embracing the quantum frontier:Investigating quantum communication, cryptography, applications and future directions
No full textThe continuous technological revolution, driven by transformative innovations such as artificial intelligence, blockchain, and Internet of Things, has left an everlasting mark on the global market landscape. This has motivated multinational corporations to not only explore the possibilities of quantum technology but also actively implement high-qubit systems and promote democratized access, thereby catalyzing a quantum revolution. Additionally, the demand to harness the potential of quantum technology and its applications has reached unprecedented levels, while concerns about security and privacy have intensified. Consequently, this paper offers an extensive exploration of the emerging field of quantum communication and cryptography, unveiling the untapped possibilities of quantum technology while delving into its prospective applications and future pathways. Quantum communication presents compelling advantages over classical communication, as it does not rely on any hard problems, offering unconditional security. We delve into the fundamental principles of quantum communication and cryptography, encompassing quantum key distribution, quantum teleportation, and quantum-resistant cryptography that aims to develop encryption methods resilient to attacks from quantum computers, potentially utilizing quantum hard problems or principles of quantum mechanics to ensure security. Additionally, we explore the prospective applications of quantum technology in diverse areas, including quantum machine learning, quantum blockchain, the quantum metaverse, and extended reality. Furthermore, this paper discusses future directions in quantum communication and cryptography, highlighting the development of quantum-secured identity and access management, quantum-secure multi-party computations, and quantum-oblivious transfer. These pioneering avenues hold the promise to revolutionize information security and communication, opening up thrilling new possibilities for the advancement of technology and innovation. The transformative potential of quantum communication and cryptography beckons a future where security and communication intertwine seamlessly, ushering in a new era of cutting-edge advancements.</p
On the Control of Microgrids Against Cyber-Attacks:A Review of Methods and Applications
Full text linkNowadays, the use of renewable generations, energy storage systems (ESSs) and microgrids (MGs) has been developed due to better controllability of distributed energy resources (DERs) as well as their cost-effective and emission-aware operation. The development of MGs as well as the use of hierarchical control has led to data transmission in the communication platform. As a result, the expansion of communication infrastructure has made MGs as cyber-physical systems (CPSs) vulnerable to cyber-attacks (CAs). Accordingly, prevention, detection and isolation of CAs during proper control of MGs is essential. In this paper, a comprehensive review on the control strategies of microgrids against CAs and its defense mechanisms has been done. The general structure of the paper is as follows: firstly, MGs operational conditions, i.e., the secure or insecure mode of the physical and cyber layers are investigated and the appropriate control to return to a safer mode are presented. Then, the common MGs communication system is described which is generally used for multi-agent systems (MASs). Also, classification of CAs in MGs has been reviewed. Afterwards, a comprehensive survey of available researches in the field of prevention, detection and isolation of CA and MG control against CA are summarized. Finally, future trends in this context are clarified
Emotional capital in citizen agency:Contesting administrative burden through anger
No full textThe literature on administrative burden has focused on cognitive, material, and social resources, leaving emotional strategies and processes largely unexplored. This study begins to address this research gap by elaborating Illouz’ (2007) concept of emotional capital in the context of citizen agency. The article uses the concept emotional capital to analyze claimant anger in response to administrative burdens examining the question: how do citizens understand and maneuver the potential benefits and risks of expressing their anger when experiencing administrative burdens? The article is based on ethnographic fieldwork in Danish job centers involving interviews with 71 claimants and observations of 10 conversations between caseworkers and claimants. The article contributes to theorize the role of emotions in citizen-state encounters by showing that emotional capital works as a resource moderating the experience of and coping with administrative burdenThe literature on administrative burden has focused on cognitive, material, and social resources, leaving emotional strategies and processes largely unexplored. This study begins to address this research gap by elaborating the concept of emotional capital in the context of citizen agency. The article uses the concept of emotional capital to analyze claimant anger in response to administrative burdens examining the question: how do citizens understand and maneuver the potential benefits and risks of expressing their anger when experiencing administrative burdens? The article is based on ethnographic fieldwork in Danish job centers involving interviews with seventy-one claimants and observations of ten conversations between caseworkers and claimants. The article contributes to theorize the role of emotions in citizen-state encounters by showing that emotional capital works as a resource moderating the experience of and coping with administrative burden.</p