Search Results (716)

The maritime sector is under growing pressure to decarbonize, driving the adoption of alternative fuels such as methane, methanol, ammonia, and hydrogen. This study evaluates their thermal behavior and associated risks using Engineering Equation Solve software for heat transfer modeling and Areal Locations of Hazardous Atmospheres software for dispersion and explosion analysis in pipelines and storage scenarios. Results indicate that methane presents moderate and predictable risks, mainly from thermal effects in fires or Boiling Liquid Expanding Vapor Explosion events, with low toxicity. Methanol offers the safest operational profile, stable at ambient temperature and easily manageable, though it remains slightly flammable even when diluted. Ammonia shows the greatest toxic hazard, with impact distances reaching several kilometers even when emergency shutoff systems are active. Hydrogen, meanwhile, poses the most severe flammability and explosion risks, capable of autoignition and generating destructive overpressures. Thermal analysis highlights that cryogenic fuels require complex insulation systems, increasing storage costs, while methanol and gaseous hydrogen remain thermally stable but have lower energy density. The study concludes that methanol is the most practical transition fuel, when comparing thermal behavior and associated risks, while hydrogen and ammonia demand further technological and regulatory development. Proper insulation, ventilation, and automatic shutoff systems are essential to ensure safe decarbonization in maritime transport. Full article

Background/Objectives: Chemical and metabolic kinetics have historically been derived from mass balance differential equations expressed in terms of amounts, and this framework was later extended to pharmacokinetics by converting amount-based equations to concentration-based clearance relationships. That conversion is valid for fixed-volume in vitro experiments, but may be unreliable in vivo, where input, distribution, and elimination can occur in different volumes of distribution. The objective of this study is to present an alternate, mechanistically agnostic framework for deriving pharmacokinetic relationships by adapting Kirchhoff’s Laws to treat pharmacokinetic systems as networks of parallel and in-series rate-defining processes, and to identify where differential equation approaches fail in vivo. Methods: Clearance and rate constant equations were derived using the adapted Kirchhoff’s Laws by summing parallel rate-defining processes and summing inverses for in-series processes, explicitly incorporating organ blood flow, net transporter, and delivery site effects. The resulting expressions were compared with differential equation hepatic disposition elimination models (well-stirred, parallel tube, dispersion) and the Extended Clearance Concept (ECC). Mean residence time concepts were used to extend the framework to oral input, and the full approach was applied to a case study of a hypothetical drug (KL25A). Results: The adapted Kirchhoff-based approach reproduced standard pharmacokinetic analyses without mechanistic organ assumptions and yielded model-independent hepatic and renal clearance equations that include blood flow, net transport, and delivery kinetics. Inconsistencies with the traditional differential-based derivations were highlighted, including the interpretation of pharmacokinetics associated with slow absorption site clearance, as illustrated by KL25A. Conclusions: For linear drug metabolism and pharmacokinetics, clearance and rate constant relationships can be derived by summing parallel and in-series rate-defining processes, without differential equations. Differential equation methods may misestimate in vivo clearance and bioavailability when drug input is slow or when volumes of distribution differ across processes. The adapted Kirchhoff framework offers a simpler, model-independent basis for interpreting clinical data. Full article

This study investigates the dispersion and condensation behavior of tritiated water vapor released into the atmosphere using moist air as a carrier, with an emphasis on safety optimization for nuclear power plant effluent discharge. A coupled heat and mass transfer model was developed and implemented in CFD simulations to analyze the evolution of temperature and relative humidity during the mixing of exhaust moist air with ambient air. The effects of key atmospheric and operational parameters—including the ambient wind speed, turbulence intensity, ambient temperature, relative humidity, and exhaust velocity—were systematically examined. The results indicate that the temperature difference between the exhaust gas and ambient air is the primary factor governing condensation risk. Low wind speeds and weak turbulence favor near-field humidity accumulation, while higher wind speeds and turbulence intensities enhance mixing and dilution, thereby reducing local humidity peaks but extending the downwind impact range. Increasing exhaust velocity strengthens plume rise and long-range transport due to enhanced momentum and latent heat release, mitigating accumulation near the chimney outlet. Furthermore, high ambient temperatures significantly increase the air’s moisture-holding capacity, allowing higher exhaust humidity without inducing condensation. Full article

Freshwater ecosystems are increasingly threatened by pollution, hydromorphological alteration, invasive species, and loss of ecological connectivity, complicating the monitoring and conservation of native fish communities. Environmental DNA (eDNA) has emerged as a sensitive, non-invasive, and cost-effective tool for detecting species, including rare or low-abundance taxa, overcoming several limitations of traditional methods. However, its rapid expansion has generated methodological dispersion and heterogeneity in protocols. This systematic review and bibliometric analysis synthesize 131 articles published between 2020 and 2025 on the use of eDNA in freshwater fish conservation. Due to the strong methodological heterogeneity among studies, the evidence was synthesized through a structured qualitative approach under PRISMA standards. Results show rapid growth in scientific output since 2023. eDNA has proven highly effective in identifying key ecological patterns such as migration and spawning, detecting critical habitats, and supporting temporal and spatial assessments. It has also facilitated early detection of invasive species including Oreochromis niloticus, Oncorhynchus gorbuscha, and Chitala ornata, and improved monitoring of threatened native species, reinforcing conservation decision-making. Despite advances, challenges persist, including variability in eDNA persistence and transport, gaps in genetic reference databases, and a lack of methodological standardization. Future perspectives include detecting parasites, advancing trophic analyses, and integrating eDNA with ecological modeling and remote sensing. Full article

Drill-and-blast tunnel construction continuously releases high-intensity dust during drilling, blasting, and shotcreting, while conventional forced ventilation is often insufficient to control dust migration and worker exposure. This study develops three-dimensional Euler–Lagrange gas–solid two-phase models for these three typical processes to clarify the spatiotemporal dispersion of polydisperse dust and to explore effective control strategies. The simulations show that all processes generate a persistent high-concentration dust belt near the tunnel face, and a low-velocity recirculation zone at the crown acts as a structural hotspot of dust accumulation that is difficult to purge by longitudinal ventilation. Particle size strongly affects dispersion behaviour: coarse particles rapidly settle near the source under gravity, whereas fine and medium-sized particles remain suspended for long periods and can be transported over long distances, particularly after blasting. Based on these findings, a rail-mounted purification system with a dynamically adjustable position along the tunnel is proposed, and its preferred deployment zones are determined to work synergistically with the main airflow. The system is designed to perform near-source and crown-targeted removal, providing an engineering-oriented “dynamic local purification plus overall ventilation dilution” pathway for improving air quality in drill-and-blast tunnel construction. Full article

This study presents the development and implementation of a functional system that utilizes large language models (LLMs) to improve the identification, organization, and retrieval of mobility interoperability resources. The established framework assists novice and experienced implementers of mobility services such as planning organizations and multimodal transportation agencies to efficiently access interoperability resources, such as standards and case studies, which are often dispersed and difficult to navigate. The web-based system includes a backend that generates abstracts and tags and a frontend that supports manual or chatbot-based search. A prompt-refinement mechanism suggests improved queries within the context of mobility interoperability when no matches are found. To validate the quality of LLM-generated abstracts and tags, subject matter experts reviewed outputs from multiple prompt iterations to assess accuracy and clarity. Of the 82 resources evaluated, 72% of abstracts met expert expectations for relevance, while 91% of the tags were considered appropriate. A comprehensive case study of 330 representative user queries was also conducted to evaluate the chatbot’s output. Overall, the presented framework aims to reduce cataloging effort, improve classification consistency, and improve accessibility to relevant information. With minimal setup costs, the system offers a scalable and cost-effective solution for managing large, uncatalogued repositories. Full article

Strategic reverse logistics management is a key driver of sustainability in supply chains, where challenges in recyclable waste must be aligned with transportation systems to achieve optimal outcomes. A systematic review using the PRISMA methodology was conducted in December 2024 by searching Scopus, Google Scholar, and Thai Journals Online to examine the global research landscape and the strategic approaches applied in reverse logistics for recyclable waste and transportation. Analysis of 32 publications shows a steady rise in research, with most studies in Asia and dispersed across multiple journals, reflecting the field’s multidisciplinary nature. Four strategic approaches were identified. Model-driven approaches demonstrate strong capability through mathematical, computational, conceptual, and hybrid models, achieving reductions of 44% in climate impacts and 34% in costs. Technology-driven approaches contribute innovations to enhance battery transport safety. Exploratory approaches reveal contextual policy gaps and financial limitations. Hybrid approaches can improve efficiency and reduce CO₂ emissions. The future development of hybrid approaches still offers substantial room for broader application and deeper integration. This review supports the development of more effective systems, policies, and future research. Full article

With the growing heterogeneity of public transport systems, accurate representation of passenger service processes at bus stops shared by multiple operators has become increasingly important. This study develops and validates a microscopic model of passenger boarding and alighting at bus stops characterized by unstructured service patterns, diverse vehicle fleets, and irregular stopping positions. The approach focuses on individual passenger movements, enabling modeling of walking times from different waiting positions and assessing how passenger distribution and bus stopping positions affect total dwell time. Variables describing the boarding and alighting process, including waiting position, vehicle stopping position, individual boarding and alighting times, and passenger walking speed, were modeled as random variables following theoretical distributions (beta, logistic, log-normal, and normal). Bayesian estimation and bootstrap methods were applied to assess parameter stability and model fit. Field studies were conducted in two Polish cities (Kraków and Kielce) at 18 high-interference bus stop locations. Results indicate that the proposed probabilistic modeling approach enhances the accuracy of passenger flow representation and supports analysis of the effects of passenger dispersion and bus stopping position on service efficiency. The developed model can be used in microsimulation of bus stop operations, transport infrastructure design, and decision-making by transport management authorities. Full article

Occupant interactions with built environments significantly influence indoor airflow patterns. Among these interactions, door openings are common, which affect airflow fields and contribute to the dispersion of airborne contaminants. The wakes originating from alterations in airflow patterns contribute to the transport of pollutants and must be carefully considered for system design in critical environments to avoid cross-contamination of susceptible bodies (e.g., patients, precision manufacturing, etc.). Therefore, knowledge about the movement patterns of these wakes is crucial in the context of indoor air quality. In this study, a series of experiments were conducted in a controlled chamber under two different schemes of a swing door opening and three different flow regimes to study the turbulent vortices produced from door openings and their spatiotemporal propagation. Additionally, an enhanced event-based modeling (EBM) approach was employed to develop a data-driven prediction of the transient indoor air patterns resulting from door-opening activities. The results suggest a significant effect of a door opening on indoor airflow fields. The velocity fields demonstrate that consecutive openings under different ventilation conditions have a prolonged impact on the propagation of door-opening-induced wakes farther into the test chamber. The quantification of the change in kinetic energy from the door opening also shows that the level of ventilation governs the flow patterns resulting from human-induced perturbation of the steady-state flow fields. The EBM approach effectively approximated the airflow patterns and demonstrated its potential to predict transient airflow disturbances caused by door operations. Full article

Simulating the dispersion of high-buoyancy pollutant is challenging because of the change in fluid density. A species transport (ST) model, which accounts for variable fluid density, was first validated by simulating light and heavy gas dispersion around a cubic building using computational fluid dynamics (CFD). This validated model was then employed to study wind flow and gas dispersion with varying plume buoyancies inside a two-dimensional street canyon. The applicability of a commonly used passive scalar transport (PST) model for simulating high-buoyancy gas dispersion was evaluated through comparisons with the ST model. The simulations demonstrated that the difference between the results of PST and ST models was negligible when a small amount of high-buoyancy pollutant was released, regardless of the gas type. However, when the emission rate was high, the fluid density was significantly altered, causing the results of the PST model to deviate substantially from those of the ST model. A clockwise recirculation was observed in all cases. This recirculation was strengthened when a large amount of light gas was released because of the positive buoyancy effect, resulting in low pollution levels. In contrast, the recirculation was suppressed, leading to high pollution levels in the case of heavy gas dispersion. This study indicated that both pollutant type and emission rate must be considered when using the PST model to simulate high-buoyancy gas dispersion. Full article

This systematic literature review explores the impacts of autonomous and connected mobility systems on sustainable road transportation. The evaluation process involves a multifaceted analysis, encompassing the assessment of their capacity to mitigate accidents, energy consumption, emissions, and urban traffic congestion. As a novel approach, this paper analyses the parameters of user acceptance of technology and how these are reflected in the overall impacts of automated and connected driving. Thus, based on a behavioral intention to use the new technology model, we aim to analyze the state of the art of the overall impacts that may be correlated with individual interests. To this end, a multi-factor approach is applied and potential interactions between factors that may arise are studied in a holistic and quantitative assessment of their combined effects on transportation systems. This impact assessment is a significant challenge, as numerous factors come into play, leading to conflicting effects. Since there is no significant penetration of vehicles with medium or high levels of automation, conclusions are often obtained through simulations or estimates based on hypotheses that must be considered when analyzing the results and can lead to significant dispersion. The results confirm that these technologies can substantially improve road safety, traffic efficiency, and environmental performance. However, their large-scale deployment will critically depend on the establishment of coherent regulatory frameworks, infrastructural readiness, and societal acceptance. Comprehensive stakeholder collaboration, incorporating industry, regulatory authorities, and society, is essential to successfully address existing concerns, facilitate technological integration, and maximize the societal benefits of these transformative mobility systems. Full article

This paper presents a comprehensive mathematical analysis of a novel compartmental model describing the dynamics of dispersed water pollutants and their interaction with two distinct host populations. The model is formulated as a system of integro-differential equations that incorporates multiple distributed delays to realistically account for time lags in the infection process and pollutant transport. We rigorously establish the biological well-posedness of the model by proving the non-negativity and ultimate boundedness of solutions, confirming the existence of a positively invariant feasible region. The analysis characterizes the long-term behavior of the system through the derivation of the basic reproduction number ${\mathcal{R}}_0^d$, which serves as a sharp threshold determining the system’s fate. For the model without delays, we prove the global asymptotic stability of the infection-free equilibrium (IFE) when ${\mathcal{R}}_0\le 1$ and of the endemic equilibrium (EE) when ${\mathcal{R}}_0>1$. These stability results are extended to the distributed-delay model by using sophisticated Lyapunov functionals, demonstrating that ${\mathcal{R}}_0^d$ universally governs the global dynamics: the IFE (${\mathcal{E}}_0^d$) is globally asymptotically stable (GAS) if ${\mathcal{R}}_0^d\le 1$, while the EE (${\mathcal{E}}_d^{\ast }$) is GAS if ${\mathcal{R}}_0^d>1$. Numerical simulations validate the theoretical findings and provide further insights. Sensitivity analysis identifies the most influential parameters on ${\mathcal{R}}_0^d$, highlighting the recruitment rate of susceptible individuals, exposure rate, and pollutant shedding rate as key intervention targets. Furthermore, we investigate the impact of control measures, showing that treatment efficacy exceeding a critical value is sufficient for disease eradication. The analysis also reveals the inherent mitigating effect of the maturation delay, demonstrating that a delay longer than a critical duration can naturally suppress the outbreak. This work provides a robust mathematical framework for understanding and managing dispersed water pollution, emphasizing the critical roles of multi-source contributions, time delays, and targeted interventions for environmental sustainability. Full article

Inefficient management of dissolved oxygen (DO) in intensive aquaculture systems limits fish welfare and productivity by creating oxygen-deficient zones and promoting hydrodynamic conditions that hinder their dispersion. Because water movement directly influences how oxygen is transported and mixed within the culture unit, inadequate flow management can allow localized hypoxia to persist even when total oxygen input appears sufficient. To address this issue, this study proposes an integrated methodology that combines in situ respirometry measurements with Computational Fluid Dynamics (CFD) simulations to evaluate the spatial distribution of DO and diagnose the operational performance of aquaculture systems. The methodology quantifies oxygen consumption using intermittent-flow respirometry, applies a three-dimensional two-phase CFD model (water–oxygen) incorporating experimental oxygen consumption rates as boundary conditions, and validates the model under real operating conditions, focusing on active metabolism as the most demanding physiological state. The model generates a spatial distribution of DO patterns that are significantly modified by pond geometry, water flow characteristics, the metabolism of the fish and fish positioning. The differences between experimental and simulated values ranged from 7.8% to 10.7%, confirming the accuracy of the proposed method. The integration of in situ metabolic measurements with CFD modeling provides a realistic representation of DO dynamics, enabling system optimization and promoting more efficient and sustainable aquaculture. Full article

Rural Sub-Saharan Africa (SSA) faces limited transport options, with many dispersed settlements dependent on poorly maintained roads. Light delivery vehicles (LDVs) can improve mobility, but conventional internal combustion engine vehicles are costly to operate and contribute to emissions. Electric vehicle (EV) conversions offer a practical alternative by extending vehicle life and reducing energy, maintenance, and environmental costs. This study presents a simulation-based framework to guide LDV conversion design for rural SSA. The framework includes component sizing, subsystem modeling, and full-vehicle benchmarking under representative conditions. Scenario-based simulations include trips ranging from shorter local access routes to longer remote trips on both paved and dirt roads, allowing the conversion’s performance to be quantified under representative conditions. A sensitivity analysis indicates that road grade, aerodynamic drag, and rolling resistance are the primary factors driving energy use variation. Using the Worldwide Harmonized Light Vehicles Test Procedure (WLTP) drive cycle, the conversion energy consumption (∼217 Wh/km) comparable to that of commercial electric vans, though the range is reduced relative to its battery capacity. The framework establishes a benchmark for EV conversion performance in SSA and supports broader adoption of sustainable rural mobility solutions. Full article

Glyphosate is the most widely used herbicide in the world for weed control; however, due to lixiviation, wind and runoff effects, an important fraction can reach the soil, aquifers and surface waters, affecting environmental and human health. The behavior of glyphosate in two agricultural soils (C1: silty clay texture, and C2: silty loam texture) was analyzed in this study using a laboratory-scale model. Water transfer was modeled with the Richards equation, while glyphosate transport was modeled using the advection–dispersion equation, with both solved using finite difference methods. The glyphosate dispersion coefficient was obtained from laboratory concentration data derived from the soil profile via inverse modeling using a non-linear optimization algorithm. The goals of this study were to (i) quantify glyphosate retention in soils with different physical and chemical properties, (ii) calibrate a numerical model for the estimation of dispersivity and simulation of short- and long-term scenarios, and (iii) assess vulnerability to groundwater contamination. The results showed that C1 retained a greater amount of glyphosate in the soil profile, while C2 was considered more vulnerable as it liberated the contaminant more easily. The model accurately reproduced the measured concentrations, as evidenced by the RMSE and R² statistics, thus supporting further scenario simulations allowing for prediction of the fate of the herbicide in soils. The approach utilized in this study may be useful as a tool for authorities in environmental fields, enabling better control and monitoring of soil contamination. These findings highlight potential risks of contamination and reinforce the importance of agricultural management strategies. Full article