Atmospheric and Oceanic Sciences

The global demand for Critical Raw Elements (CRE) has increased owing to their role in clean energy solutions. This demand is expected to double or quadruple by 2050; thus, there is need for enhanced exploration, including new sites, to enable new ore discoveries. This study investigates the distribution of CREs in the volcanic rocks of the Kenya Rift, based on a review of various geochemical and petrological studies. Notable concentrations of chromium (Cr), vanadium (V), rubidium (Rb), zirconium (Zr), niobium (Nb), and barium (Ba) occur in the volcanic rocks of the Kenya rift system. The northern Kenya rift volcanic centers are identified for the economic exploration of Cr and Nb within mafic rocks. Additionally, V concentration up to twice the average concentration of the upper continental crust, can be considered for pilot studies to identify ore minerals. Critical elements such as Rb, Nb, and Zr enriched through fractional crystallization processes, and ongoing geothermal, tectonic and volcanic activities within Olkaria region in CKR are potential sites for future explorations. The northern Kenya rift basalts exhibit elevated concentrations of light rare earth elements (LREE), particularly La and Ce. In contrast, more evolved volcanic rocks, such as trachytes and rhyolites, demonstrate increased overall rare earth elements (REE) and yttrium concentrations, highlighting different magmatic processes along the Kenya rift. La, Ce, Nd, and Y occur at concentrations above 100 mg/kg in felsic volcanic rocks within the Kenya Rift. Siderophile critical elements such as Co, Ni, W, and platinum group metals (PGMs) are notably depleted, suggesting that the magmas underwent substantial differentiation processes that preferentially removed these elements from the melt. Similarly, the low levels of chalcophile critical elements (Sb, Ga, Ge, and Bi) indicate limited sulfide saturation and minimal hydrothermal alteration during volcanic activity. Generally, tectonic, magmatic, and surficial processes facilitate the formation and evolution of critical elements, and sedimentary basins within the Kenya rift represent potential sites for the accumulation of these essential elements. These findings provide direction for resource exploration and evaluation within the Kenya rift system.

Abstract

Abstract Urban green spaces (UGSs) play an important role in improving urban ecological envi-ronments and social well-being. In this study, we selected Chengdu, China as the research area. By integrating urban big data with spatial autocorrelation analysis, we identified UGS distributions across different years and their spatial clustering patterns. Furthermore, eleven factors influencing UGS distribution were systematically selected from both city-scale and neighborhood-scale perspectives. The main factors influencing the kernel density of UGS in Chengdu were explored using geographical detectors, and the results showed that the quantity and area of UGS in Chengdu gradually increased from 2012–2021 through an unbalanced spatial distribution. All influencing factors had an interac-tive relationship with the UGS kernel density. As the UGS kernel density increased, transportation hub had the greatest impact, the influence of air pollution and urban pre-cipitation on the density of UGS increased, and the nighttime light index decreased. By categorizing the influencing factors into natural environmental and human activity di-mensions, the analysis revealed that human activities and natural environment served as primary drivers of UGS density before and after 2018, respectively. Furthermore, their ef-fects on UGS gradually expanded from the urban core to encompass the entire metropoli-tan area over time. By exploring the relationship between the evolution of UGS spatial patterns and changes in the urban ecological environment and social development using a quantifiable method, this study provides references and guidelines for the future plan-ning of cities to achieve high-quality development.

Currently, there is a significant intensification of technological processes during the operation of pipeline systems at marine oil terminals. In the context of a manifold increase in cargo flows, there is a rise in corresponding complications that require urgent solutions. It is important to note that the resolution of these problematic aspects must have a proper scientific basis, rather than blindly following the contemporary environmental agenda. In this regard, the issues of substantiating technical and technological solutions to ensure resource-efficient, environmentally friendly, and safe operation of pipeline systems at marine oil terminals are highly relevant. This study examines technological solutions aimed at reducing atmospheric emissions during tanker loading. Of particular importance during these operations is the initial stage of loading, when the pressure of the gas phase inside the tanker increases rapidly. The work demonstrates that at this stage, by processing data on the gas phase pressure value received from the tanker, it is possible to predict in advance how intensively the loaded cargo is evaporating. Thus, negative consequences such as the opening of the mast riser and the release of excess gas-air mixture into the atmosphere can be prevented by, for example, increasing the rotation speed of the gas blower on the berth. However, solving the inverse problem of identifying the process parameters is very difficult due to its ill-posed nature. In this regard, an algorithm is proposed, based on an equation derived in earlier works, involving series expansion and identification of the mass transfer parameter from the surface of the evaporating cargo. The proposed method will make it possible to implement in practice a warning system within the loading control system about a dangerous rate of pressure increase and to take preventive actions.

Organophosphorus esters (OPEs) have been widely used as flame retardants and plasticizers and are globally ubiquitous. In the marine environment, OPEs primarily originate from continental sources and are initially confined to marginal seas before reaching remote oceans. However, their differing biogeochemical fates in these two regions remain unclear. This study investigated regional variations in the biogeochemical regulation mechanisms of OPEs (alkyl and aryl) across the Western Pacific and the South China Sea (112°E to 163°E) by analyzing their air-sea interface processes and vertical profiles. Results revealed that the South China Sea exhibited net inputs of OPEs (1.66 ± 1.36 μg m –2 d –1 ), while the Western Pacific mainly showed outputs (0.41 ± 1.15 μg m –2 d –1 ) to the atmosphere, forming patterns characterized by remote sources and marginal sinks. In vertical profiles, OPE consumption in the upper water column of the South China Sea was mainly driven by biodegradation, in contrast to the Western Pacific, where it was primarily controlled by the biological pump. This study reveals the distinct OPE fates in the remote ocean versus the marginal sea, highlighting the Western Pacific Warm Pool as a source of OPEs. Future research should address their marine coexistence with precursors and transformation products.

Near-miss incident reports provide valuable but underutilised insights for improving maritime safety. However, existing research emphasises failures, with limited focus on positive safety practices. This study addresses this gap by examining connections between incidents and preventive measures to identify what works and what doesn’t. To overcome the limitations of traditional topic modelling approaches, this study applies BERTopic, a transformer-based method. Using this method, we analysed 4360 near-miss reports spanning five years from a ferry operator to identify recurring risk patterns and the preventative measures linked to them. GPT-assisted labelling improved interpretability, with outputs validated through structured multi-expert review. Over 75 distinct incident topics were identified across operational, environmental, and human factors domains, aligning with existing categories and uncovering previously unclassified risk themes. Time-series analysis highlighted seasonal variations, with passenger-related risks peaking in summer and infrastructure failures more common in winter. Prevention measures were modelled separately, producing 87 topics, with association rule mining identifying clear linkages between incident types and mitigations; for example, navigation-related incidents were frequently linked to improved bridge communication. Overall, combining unsupervised topic modelling with LLM-assisted labelling produces interpretable and operationally meaningful outputs. This approach offers a scalable framework for prioritising preventative measures using data-driven evidence.

This study investigates the occurrence, distribution, and sources of titanium (Ti)-bearing and cerium (Ce)-bearing (nano)particles in the Seine River basin using single particle inductively coupled plasma time-of-flight mass spectrometry (ICP-TOFMS). Water samples and freshwater mussels ( Dreissena polymorpha ) were collected during three campaigns (2020, 2021, 2023) to assess colloidal concentrations and bioconcentration patterns. Ti-bearing particle concentrations ranged from 1.18 × 10 6 to 3.61 × 10 8 particles·L –1, while Ce-bearing particles ranged from 5.08 × 10 6 to 4.58 × 10 7 particles·L –1 . Calculated export rates were 0.3 – 1.1 kg·year –1 ·km –2 for Ti and 56.5 g·year –1 ·km –2 for Ce. Elemental ratio analysis (Ti:Fe and Ce:La) distinguished engineered from natural particles: approximately 60% of Ti-bearing particles were associated with engineered titanium dioxide (TiO 2 ), while 40% matched natural hematite-ilmenite minerals; similarly, 65% of Ce-bearing particles were associated with engineered cerium dioxide (CeO 2 ), while 35% resembled natural monazite. Ti- and Ce-bearing particle sizes ranged from 60 to 500 nm and 20 to 80 nm, respectively, reflecting aggregation and natural mineral contributions. Zebra mussels bioaconcentrated both particle types, with Ti concentrations correlating linearly with water concentrations, suggesting bioindicator potential. These findings demonstrate that engineered nanoparticle concentrations in the Seine River have reached levels comparable to natural colloids, highlighting their significant environmental presence in urbanized watersheds.

Abstract Long‐term scientific infrastructure, including physical archives, monitoring networks, and place‐based research facilities, is frequently described as important but is rarely protected by enforceable governance. When administrative reorganization or budget pressure threatens such infrastructure, the scientific community typically responds with legal action and public advocacy. These responses are necessary, but they address only the immediate harm. They do not close the underlying structural gap: the absence of any requirement that institutions name a responsible steward, fund continuity, or specify what happens to physical and human assets when administrative decisions are made. This piece argues for a distinct governance function, here termed stewardship intelligence, defined as the capacity to identify where scientific value is exposed to ordinary institutional pressures before that exposure becomes irreversible loss. Using a recent threat to long‐term ecological research infrastructure as a motivating case, the piece distinguishes legal protection, which addresses a specific administrative action, from structural stewardship, which addresses the conditions that make such actions possible. It concludes that public scientific value remains vulnerable until institutions convert moral importance into named responsibility, funded continuity, and accountable governance, rather than relying on goodwill and case‐by‐case advocacy after each threat emerges.

To investigate the coupled evolution of cavity morphology, hydrodynamic characteristics, and motion behavior during the wide-speed-range acceleration of an underwater hypervelocity vehicle, a numerical framework for supercavitating multiphase flow was established by coupling the Improved Delayed Detached Eddy Simulation (IDDES) turbulence model, the Schnerr–Sauer cavitation model, and the Volume of Fluid (VOF) method. Combined with the overset mesh technique and the DFBI six-degree-of-freedom model, the multiphase flow and motion characteristics during acceleration were systematically studied. The results show that the ventilated cavity strongly compresses the natural cavity, leading to a complex gas–vapor–liquid three-phase coexistence structure in the mid-body conical section and stern region, with the ventilated cavity eventually becoming dominant. The drag coefficient exhibits a three-stage evolution associated with cavity development over the conical section, cylindrical section, and the final formation of a supercavity. Once the vehicle is enveloped by the supercavity, pressure drag becomes dominant. Ventilation timing significantly affects supercavity formation and flow stability. Low-speed ventilation reduces drag earlier but prolongs the three-phase coexistence period and cavity formation process, whereas high-speed ventilation promotes the rapid formation of a stable supercavity. The supercavity formation time reaches 0.5 s under ventilation at 30 m/s, which is more than twice the value for ventilation at 70 m/s.

The distinct engineering advantages of Oscillating Water Column (OWC) systems have driven substantial academic interest lately. This work examines the onshore U-shaped OWC (U-OWC), selected for its cost-effective installation integrated with existing coastal infrastructure and its superior broadband response to diverse wave climates. Time-domain CFD simulations, incorporating the scaling-rematched approach, were conducted to quantify key hydrodynamic and air-compressibility coefficients, including the amplitude of the wave exciting force, fluid damping coefficient, added mass, absorption factor, and the effective PTO (power take-off) damping and air-compressibility coefficients. These parameters collectively elucidate the underlying hydrodynamics and how they are interwoven with the compressibility of the air in the plenum chamber, thereby impacting the U-OWC’s energy-capture performance under incident waves. A principal finding is the identification of a C+ interval wherein air compressibility enhances capture performance in the lower wave-period range examined (<8.0 s). The added mass of the present U-OWC exhibits a remarkably pronounced decrease around the wave period of 8.0 s, which can be verified by a simple resonance formula of heave buoys to underline its strong near-resonance behavior.

The Anthropocene is characterized by biodiversity and habitat loss that has developed over millennia. However, the more recent human-induced climate change requires humanity to take rapid actions to mitigate marine environmental change and adapt to its impacts. The analysis of global marine processes relies on reusable data as well as on methods that can handle the complexity and scale of these data, making data literacy a key component of ocean literacy. Here, we provide a perspective based on our experiences from the data competence center “DataNord” in Bremen, Germany, while considering the broader landscape of German initiatives and institutional support structures for data literacy and research data management in marine and environmental sciences. We identify common challenges, highlight practical needs, and discuss approaches in the context of the Ocean Decade, to make data literacy and research data management more accessible and practical for researchers. While rooted in marine sciences and the German research landscape, the insights presented here should also be relevant to other scientific disciplines and governments.

While South African citizens expect their local municipalities to provide water services of the highest quality, several municipalities are struggling to deliver, leading to a significant rise in social protests, primarily over inadequate service delivery. Therefore, a customer-centered approach to understanding residents' perceptions of water service quality is essential for effective water management and for developing contextually tailored strategies. However, residents' perceptions of municipal water service quality, particularly through the lens of the Service Quality (SERVQUAL) model, remain poorly understood. This study, therefore, employs the SERVQUAL model to examine residents' perceptions of municipal water service quality in the Fairview community of the Harry Gwala District Municipality (HGDM). The study used the quantitative survey research approach to evaluate water service quality across the five dimensions: reliability, responsiveness, assurance, empathy, and tangibility. The study's findings reveal a pervasive sentiment of dissatisfaction among residents across all five water service quality dimensions, indicating that community members rate municipal water service quality poorly. Many residents feel neglected, uninformed, and unsupported in municipal efforts to address water supply issues. The study recommends that HGDM adopt concrete action plans to upgrade water supply infrastructure, enhance staff training to improve water service quality, engage residents in decision-making and regular reviews, and establish transparent communication channels with the community to foster trust and collaboration. Academia is encouraged to conduct further research on successful water management initiatives and to explore the underlying causes of dissatisfaction with municipal water service quality.

The studied localities within the Utuado Pluton in the Puerto Rico fossil island arc preserve a detailed record of enclave-host interaction and mid-crustal processes consistent with multi-stage assembly. Petrography, whole-rock geochemistry, amphibole major- and trace-elements, and thermobarometry reveal repeated rejuvenation of a vertically connected reservoir. Two enclave types are identified: intergranular Type 1 formed from hotter intermediate injections, and poikilitic Type 2 recording slower cooling and partial equilibration with the host. Amphiboles display well-developed patchy zoning defined by discrete compositional steps. When grouped by intra-crystal zones, amphiboles define systematic P-T fields: Zone 1 records the highest-T, deepest conditions (∼800-940 °C; 110-415 MPa), Zone 2 captures intermediate hybridized conditions (∼800-850 °C; 120-220 MPa), and Zone 3 reflects the shallowest, coolest crystallization (∼730-820 °C; 55–130 MPa) indicating episodic recharge rather than monotonic cooling. Calculated amphibole-equilibrium melts form a continuous array (∼60-80 wt.% SiO 2 ; 0.8-9 wt.% CaO) with zoning domains tracking melt evolution from hotter to more silicic compositions. Coupled whole-rock Eu/Eu*, Sr/Y, and Y variations indicate limited (∼5-10 wt.%) melt extraction from amphibole-plagioclase mushes. These results provide a framework where the Utuado Pluton was built through cyclic replenishment, incomplete mixing, mingling, and localized melt extraction within a vertically integrated arc reservoir.

Subsea tunnels constructed by the drill-and-blast method are increasingly required in modern infrastructure and are often exposed to high groundwater pressure and fractured rock conditions. In such environments, external water pressure acting on initial support strongly affects tunnel stability, durability, and construction safety. Because the initial support is temporary, discontinuous, and prone to cracking, evaluation of its water pressure response remains challenging. Current design practice relies on simplified assumptions and empirical approaches, inadequate for fractured rock masses under high water pressure. This review synthesizes research on external water pressure in tunnels, with emphasis on drill-and-blast subsea tunnels. Empirical reduction coefficient methods, theoretical analytical solutions, numerical techniques, and physical model testing are critically examined in terms of their theoretical basis, applicability, and limitations. Special attention is given to seepage behavior in fractured rock masses, including single-fracture seepage laws, equivalent continuum models, and discrete fracture network approaches, and their ability to represent fracture-controlled flow and water pressure redistribution. The review shows that conventional seepage or seepage–stress coupled methods are insufficient to capture stress redistribution, fracture evolution, and damage-induced permeability changes governing water pressure behavior. By contrast, advanced coupled stress–seepage–damage and stress–seepage–fracturing models provide more physically consistent frameworks for analyzing external water pressure acting on initial support. In addition, hydro-mechanical discrete lattice models are reviewed as a promising meso-scale framework for capturing crack initiation, crack coalescence, and crack-controlled seepage paths that may govern localized external water pressure redistribution behind initial support. However, their application to subsea tunnels remains limited, and current design codes still lack unified calculation methods. Major challenges remain, including the lack of consistent definitions of external water pressure, inadequate consideration of the interaction between tunnel support and surrounding rock, and insufficient validation through laboratory experiments and field observations. Future research should develop mechanism-based methods supported by monitoring and validation to improve subsea tunnel safety.

Underwater acoustic (UWA) sensor and control links carry mostly short messages (below ∼10 kB) over time-varying, low-SNR multipath channels, which is a regime where forward error correction (FEC) operates on short, finite blocks where a single static configuration is inefficient. Adaptive schemes for these links typically adjust the modulation order and code rate; the payload segment (block) size—which, together with the code rate, sets the coded block length that governs the finite-blocklength penalty for short messages—is seldom adapted per transmission jointly with the choice of FEC scheme on a like-for-like footing. We propose a per-transmission controller that jointly selects the FEC scheme, code rate, and segment size from a prediction of the near-term channel state, which is paired with a like-for-like short-block benchmark of LDPC, list-decoded polar, BCH, Reed–Solomon, convolutional, and turbo codes. No single code dominates: under a unified ARQ goodput metric, the reliability–throughput frontier has a crossover that shifts with the channel, so the optimal FEC choice is channel-dependent. Across our experiments, the segment-size degree of freedom is the dominant throughput lever, capturing essentially all of the adaptation gain at low-to-mid SNR and over fading; switching the FEC family adds a further, bounded gain only where the frontier crosses between families (up to 10% at high-SNR AWGN, polar to RS). The joint controller essentially matches a fair single-family adaptive baseline off the crossover (to within a negligible prediction-overhead margin) and exceeds it at that crossover, beats a fixed, no-CSI code by up to 16%, and captures 91–99% of an oracle; a lightweight persistence predictor matches a learned LSTM for the first-order channel-state model studied. A statistics-driven replay using measured-channel parameters, and a recorded-channel replay over the public Watermark benchmark, preserve the same family ordering.

Introduction With the rapid growth of the global cruise tourism industry, the demand for cruise ships has surged worldwide. As one of the leading countries with a significant number of cruise passengers, China faces an urgent need to independently construct cruise ships. Methods This paper presents an optimization model aimed at minimizing the total number of obstructive blocks while simultaneously maximizing space utilization within the stockyard. To solve this problem efficiently, an improved genetic algorithm is proposed. Results Numerical experiments demonstrate that the in-plant scheduling of blocks can be effectively derived based on the shipyard's work plan. Moreover, the study reveals that both the layout of the stockyard and its access configuration directly influence the percentage of obstructive blocks. Discussion Specifically, stockyards with a long, flat layout and four-sided access are found to result in a lower number of obstructive blocks, providing practical implications for stockyard design and block logistics management in cruise ship construction.

Abstract We introduce adaptive-basis physics-informed neural networks (AB-PINNs), an adaptive domain decomposition framework for PINNs in which learnable subdomains dynamically evolve during training to align with intrinsic features of the unknown solution. Local networks capture fine-scale features within each adaptive subdomain, while a global network learns large-scale solution structures. Furthermore, drawing inspiration from classical adaptive mesh refinement, we also modify the domain decomposition on-the-fly throughout training by introducing new subdomains in regions of high residual loss, thereby providing additional expressive power where needed. Our flexible approach to domain decomposition is well-suited for multiscale problems, as different subdomains can learn to capture different scales of the underlying solution. Moreover, the ability to introduce new subdomains during training helps prevent convergence to unwanted local minima and can reduce the need for extensive hyperparameter tuning compared to static domain decomposition approaches. Throughout, we present comprehensive numerical results demonstrating the rapid convergence of AB-PINNs compared with standard PINNs and existing, static PINN-based domain decompositions when solving multiscale differential equations.