Search Results (120)

Hourly PM_2.5 concentrations were measured from February to May 2025 by a network of low-cost sensors located in urban Kraków and its surrounding municipalities. Temporal variability associated with the transition from the heating period to the spring months, together with spatial contrasts, were assessed with principal component analysis (PCA), urban–rural difference curves, and a detailed examination of the most severe smog episode (12–13 February). Particle trajectories generated with the HYSPLIT dispersion model, run in a coarse-grained, 36-task parallel configuration, were combined with kernel density mapping to trace emission pathways. The results show that peak concentrations coincide with the heating season; rural sites recorded higher amplitudes and led the urban signal by up to several hours, implicating external sources. Time-series patterns, PCA loadings, and HYSPLIT density fields provided mutually consistent evidence of pollutant advection toward the city. Parallelizing HYSPLIT on nine central processing unit (CPU) cores reduced the runtime from more than 600 s to about 100 s (speed-up ≈ 6.5), demonstrating that routine episode-scale analyses are feasible even on modest hardware. The findings underline the need to extend monitoring and mitigation beyond Kraków’s administrative boundary and confirm that coarse-grained parallel HYSPLIT modeling, combined with low-cost sensor data and relatively basic statistics, offers a practical framework for rapid source attribution. Full article

The arrival of tracers at boundaries with defined distances from the origin of their motion in stochastically fluctuating advection processes is investigated. The advection model is a stationary one-dimensional integrated stochastic process with an arbitrary a priori known correlation and with possible mean drift. The current (direction-sensitive), the total flux (direction-insensitive) of tracers through a non-absorbing boundary, and the first-passage times of the tracers at an absorbing boundary are derived depending on the correlation function of the carrying flow velocity. While the general derivations are universal with respect to the distribution function of the advection’s increments, the current and the total flux are explicitly derived for a Gaussian distribution. The first-passage time is derived implicitly through an integral that is solved numerically in the present study. No approximations or restrictions to special cases of the advection process are used. One application is one-dimensional Gaussian turbulence, where the one-dimensional random velocity carries tracer particles through space. Finally, subdiffusive or superdiffusive behavior can temporarily be reached by such a stochastic process with an adequately designed correlation function. Full article

This study introduces the Double-Diamond Reactor (DDR), a novel planar passive microreactor designed to overcome the following conventional limitations: inefficient mass transfer, high flow resistance, and clogging. The DDR integrates splitting–turning–impinging (STI) hydrodynamic principles via CFD-guided optimization, generating chaotic advection to enhance mixing. Experimental evaluations using Villermaux–Dushman tests showed a segregation index ($X_s$) as low as 0.027 at 100 mL·min⁻¹, indicating near-perfect mixing. In BaSO₄ nanoparticle synthesis, the DDR achieved a 46% smaller average particle size (95 nm) and narrower distribution (${\sigma }_g=1.27$) compared to reference designs (AFR-1), while maintaining low pressure drops (<20 kPa at 60 mL·min⁻¹). The DDR’s superior performance stems from its hierarchical flow division and concave-induced vortices, which eliminate stagnant zones. This work demonstrates the DDR’s potential for high-throughput nanomaterial synthesis with precise control over particle characteristics, offering a scalable and energy-efficient solution for advanced chemical processes. Full article

Mineral dust plays a vital role in the Earth’s climate system, influencing radiation, cloud formation, biogeochemical cycles, and air quality. Accurately simulating dust transport in atmospheric models remains challenging, particularly for coarse and super-coarse particles, which are often underrepresented due to limitations in model physics and numerical treatment. Observations have shown that particles larger than 20 μm can remain airborne longer than expected, suggesting that standard gravitational settling formulations may be insufficient. One potential contributor to this discrepancy is the numerical diffusion introduced by advection schemes used to model sedimentation processes. In this study, we compare the commonly used first-order upwind advection scheme, which is highly diffusive, to a third-order scheme (UNO3) that reduces numerical diffusion while maintaining computational efficiency. Using 2-D sensitivity tests, we show that UNO3 retains up to 50% more dust mass for the coarsest particles compared to the default scheme, although overall dust lifetime shows little change. In 3-D simulations of the ASKOS 2022 dust campaign, both schemes reproduced similar large-scale dust patterns, with UNO3 yielding slightly lower dust. Overall, domain-averaged dust load differences remain small (less than 2%), with minor decreases in fine dust ~3% and slight increases in coarse dust ~2%, indicating that reducing numerical diffusion modestly enhances the presence of larger particles. Near the surface, UNO3 produces a ~4% increase in dust concentration, with local differences up to 50 μg/m³. These results highlight that while numerical diffusion does affect dust transport—especially for super-coarse fractions—its impact is relatively small compared to the larger underestimation of super-coarse dust commonly observed in models compared to measurements. Addressing the fundamental physics of super-coarse dust emission and lofting may therefore be a higher priority for improving dust model fidelity than further refining advection numerics. Future studies may also consider implementing more computationally intensive schemes, such as the Prather scheme, to further minimize numerical diffusion where highly accurate size-resolved transport is critical. Full article

A significant wildfire event occurred in Korinthos, Greece, on 22 July 2020, releasing large amounts of smoke into the atmosphere. This episode provided the opportunity to develop and apply the methodology described in this work, where the synergistic use of ground data, satellite remote sensing data and dispersion modeling is utilized to demonstrate highly accurate source detection, emission transport, and dispersion of the smoke plumes. The Fire Radiative Power (FRP) data from SEVIRI, on board Meteosat Second Generation, are used to estimate hourly fire top-down emissions. These emissions are used as input for the FLEXPART Lagrangian particle dispersion model, driven by GFS meteorological data. Simulated smoke transport is compared with TROPOMI satellite CO observations and lidar profiles from the PANhellenic GEophysical observatory of Antikythera (PANGEA) station. The model includes key atmospheric processes such as advection and deposition, providing a framework for assessing wildfire impacts on air quality and transport. The results highlight the effectiveness of combining high temporal resolution FRP data with the WARM START configuration of FLEXPART versus the Standard FLEXPART Simulation. Full article

Various nature-based solutions (NbS)—such as constructed wetlands, drainage ditches, and vegetated buffer strips—have recently demonstrated strong potential for mitigating pollutant transport in open channels and river systems. Numerical modeling is a widely adopted and effective approach for assessing the performance of these interventions. This study presents the first development of a two-dimensional (2D) meshless advection–diffusion model based on an Eulerian smoothed particle hydrodynamics (SPH) framework, specifically designed to simulate passive pollutant transport in open channel flows. The proposed model marks a pioneering application of the ESPH technique to environmental pollutant transport problems. It couples the 2D depth-averaged shallow water equations with an advection–diffusion equation to represent both fluid motion and pollutant concentration dynamics. A uniform particle arrangement ensures that each fluid particle interacts symmetrically with eight neighboring particles for flux computation. To represent the pollutant transport process, the dispersion coefficient is defined as the sum of molecular and turbulent diffusion components. The turbulent diffusion coefficient is calculated using a prescribed turbulent Schmidt number and the eddy viscosity obtained from a Smagorinsky-type mixing-length turbulence model. Three analytical case studies, including one-dimensional transcritical open channel flow, 2D isotropic and anisotropic diffusion in still water, and advection–diffusion in a 2D uniform flow, are employed to verify the model’s accuracy and convergence. The model demonstrates first-order convergence, with relative root mean square errors (RRMSEs) of approximately 0.2% for water depth and velocity, and 0.1–0.5% for concentration. Additionally, the model is applied to a laboratory experiment involving 2D pollutant dispersion in a 90° junction channel. The simulated results show good agreement with measured velocity and concentration distributions. These findings indicate that the developed model is a reliable and effective tool for evaluating the performance of NbS in mitigating pollutant transport in open channels and river systems. Full article

Particle deposition is a phenomenon that occurs in many natural and industrial systems. Nevertheless, the modelling and understanding of such processes are still quite a big challenge. This study uses a discrete phase model (DPM) to determine the deposition constant for the particles in a liquid phase flowing in a horizontal pipe. This study also develops a steady-state population balance equation (PBE) for the particles in the flow involving deposition and aggregation and an unsteady-state PBE for particles depositing on the wall. This establishes a mathematical relationship between the deposition constant and velocity. An industrial setting of a 1000 m long pipe of 0.5 m in diameter was used for the population balance modelling (PBM). Based on the extracted deposition constant from the DPM, it was found that the particle deposition velocity increases with the continuous flow velocity. However, the number and volume of the deposit particles on the wall reduce with the increase of the continuous flow velocity. The deposition was found mainly taking place in the inlet region and reduces significantly towards the pipe outlet. The deposition was also found driven by advection of particles. Calculated deposit thickness showed that increasing the continuous flow velocity from 1 m s⁻¹ to 5 m s⁻¹, the thickness at the inlet would reduce to nearly 1/40th. With a 10 m s⁻¹ flow, this would be 1/80th. Full article

This study utilized the FVCOM model to establish a hydrodynamic model for the waters from Haikou to Danzhou. Based on this framework, a numerical model for oil spill drift and diffusion was developed using the Lagrangian particle method, incorporating processes such as advection, diffusion, spreading, emulsification, dissolution, volatilization, and shoreline adsorption. Sea experiments involving drifters and dye were conducted to validate the oil spill model. The model was subsequently applied to analyze the impacts of tidal phases and wind fields on oil spill trajectories, predict affected areas, and assess risks to environmentally sensitive zones. The results demonstrate that the hydrodynamic model accurately reproduces the tidal current characteristics of the study area. Validation using drifter and dye experiments confirmed that the model’s predictive error remains within 20%, meeting operational forecasting standards. Potential sources of error include uncertainties in wind–wave–current interactions and discrepancies in windage coefficients between oil spills and drifters. Tidal currents and wind fields were identified as the dominant drivers of oil spill drift and diffusion. Under southerly wind conditions, the oil spill exhibited the largest spatial extent, covering 995.25 km² with a trajectory length of 226.92 km. A sensitivity analysis highlighted the Lingao Silverlip Pearl Oyster Marine Protected Area and Shatu Bay Beach as high-risk regions. The developed model provides critical technical support for oil spill emergency response under diverse environmental conditions, enabling proactive pathway forecasting and preventive measures to mitigate ecological damage. Full article

The purpose of the study is to develop a general method to predict local temperature changes from mitigating the urban heat island effect using local climate engineering. Specifically, the effects of a plume of calcite particles above cities have been found. Previous modeling work has been carried out with supercomputers, but those models have limited geographies and timelines. The main goal of this work is to produce a method that can be applied more generally and more quickly. This overcomes limited modeling data in arid regions. Arid cities show the most effective use of calcite plumes for local solar radiation management, but those areas have limited data. The new method is to use numerical fit techniques using actual weather data. The default heating and cooling rates are fit to historic rates, and then the radiative properties of the calcite are used to predict the change in the heat transfer rates. Air temperatures at a standard height of 2 m are predicted. The key findings are that the numerical fit gives comparable results to the full supercomputer model, but the numerical fit gives predictions of greater temperature change. This was explained as primarily due to how advection is handled differently by the methods. Adjustments in the methods are discussed so that the effect of advection is included. The conclusion is that numerical fit provides a method that can easily be applied to arid regions. Full article

A two-dimensional periodic Stokes flow of viscous incompressible fluid in a rectangular cavity with constant velocities applied to the top and bottom walls is considered. The study of advection regimes is reduced to the sequential solving of two problems. To solve the first problem, the analytical method of superposition, which allows one to obtain any desired accuracy of the velocity field, is used. To solve the second problem, which is associated with obtaining the trajectories of individual fluid particles, numerical calculations of the Cauchy problem were performed. An analysis of the boundary conditions accuracy was performed based on the control of local integration. The advection of the selected volume of fluid in the rectangular cavity under the periodic motion of walls for a finite period time based on piecewise spline cubic interpolation is modeled. The obtained numerical results agree with well-known experimental data. Full article

Monotonously stratified porous medium, where the layered medium changes its hydraulic conductivity with depth, is present in various systems like tilled soil and peat formation. In this study, the flow pattern within a monotonously stratified porous medium is explored by deriving a non-dimensional number, $F_{hp}$, from the macroscopic Darcian-based flow equation. The derived $F_{hp}$ theoretically classifies the flow equation to be hyperbolic or parabolic, according to the hydraulic head gradient length scale, and the hydraulic conductivity slope and mean. This flow classification is explored numerically, while its effect on the transport is explored by Lagrangian particle tracking (LPT). The numerical simulations show the transition from hyperbolic to parabolic flow, which manifests in the LPT transition from advective to dispersive transport. This classification is also applied to an interpolation of tilled soil from the literature, showing that, indeed, there is a transition in the transport. These results indicate that in a monotonously stratified porous medium, very low conducting (impervious) formations may still allow unexpected contamination leakage, specifically for the parabolic case. This classification of the $F_{hp}$ to the flow and transport pattern provides additional insight without solving the flow or transport equation only by knowing the hydraulic conductivity distribution. Full article

A first-order linear and numerically non-diffusive Eulerian transport algorithm, minVAR, was recently developed for preservation of correlations between interrelated tracers during advective transport. The present study extends this work by: (1) providing further investigation of several interesting geometric constructions found in contours of constant minVAR, short for minimum variance, through extension to three coordinate dimensions. These contours capture point-by-point representations of thousands of individual atmospheric aerosol and/or cloud particles as they evolve and are rendered on Eulerian grids at a level of sub-grid resolution limited only by numerical precision; and (2) exploration of geometric similarities between the Arakawa C-grid, used to obtain interpolated values of the wind field at grid scale and minVAR. In particular, we consider interpolation of the u and v horizontal components of wind velocity from grid to sub-grid scales. The last results are motivated by recent applications of the Weather Research and Forecasting (WRF) model applied in the coastal Houston region, where the recent TRacking Aerosol Convection Interactions ExpeRiment (TRACER) field campaign was organized. A unique and fully consistent mapping is obtained between particles moving along meteorological wind trajectories and the non-diffusive, non-dispersive representation of such trajectories on an Eulerian grid. Full article

Air pollution is a situation that negatively affects the health of humans and all living things in nature and causes damage to the environment. The most important cause of air pollution is the amount and density of substances called “particulate matter” above guidelines. Particulate matter (PM) are mixed liquid droplets and solid particles with advective diameters less than 2.5 μm (PM_2.5—fine particles) and between 2.5 and 10 μm (PM_2.5–10—coarse particles). PM₁₀ is defined as one that can remain in the air for a long time and settle in the respiratory tract, damaging the lungs. It is important to identify the underlying causes of air pollution caused by PM₁₀. In this context, these criteria need to be evaluated to minimize the negative effects of PM₁₀. In the study, monthly average PM₁₀ data obtained from the Air Quality Monitoring Station in Kocaeli, Türkiye, between 2017 and 2023 are used. After determining the criteria for PM₁₀, the criteria are prioritized with the Intuitionistic Fuzzy AHP (IF-AHP) method by taking decision-maker opinions. The proposed decision-making model aims to guide obtaining and focusing on the important causes of out-of-limit and dangerous PM₁₀ concentrations in the air. Additionally, PM₁₀ data is analyzed in the context of COVID-19 and a statistical analysis is conducted. One-way Analysis of Variance (ANOVA) is used to evaluate whether there is a significant difference in average monthly data over the years. The Games–Howell test, one of the post-hoc tests, is used for determining differences between groups (years). In addition, monthly PM₁₀ values for the future are estimated using the Expert Modeler tool in the software IBM^® SPSS^® Statistics 22. The study is important in that it provides a focus on the criteria affecting PM₁₀ with an intuitionistic fuzzy perspective, along with statistical analysis. Full article

The fractional advection–dispersion equation is used in groundwater hydrology for modeling the movements of contaminants/solute particles along with flowing groundwater at the seepage velocity in porous media. This model is used for the prediction of the transport of nonreactive dissolved contaminants in groundwater. This paper establishes the existence and the uniqueness of solutions represented as fractional bi-variate power series of some initial-value problems and boundary-value problems for the fractional advection–dispersion equation. Moreover, a method to approximate the solutions using fractional polynomials in two variables and to evaluate the errors in a suitable rectangle is designed. Illustrative examples showing the applicability of the theoretical results are presented. Full article

The movement and biomass fluctuations of sargassum across the Tropical Atlantic have profound implications when influxes reach the Eastern Caribbean. These influxes have cross-cutting impacts across ecological, economic, and social systems. The objective of this work is to quantify sargassum biomass accumulation in the Eastern Caribbean, accounting for the spatial variability in sea surface temperature and morphotype diversity. A parallel implementation of a climatological drifter-based model was used to simulate advection of sargassum across the model domain. After determining the trajectory of virtual sargassum particles, Monte Carlo simulations using 1000 realizations were run to quantify biomass accumulations along these tracks. For simulations with a single morphotype, the biomass accumulation as predicted by the model effectively reproduced the seasonal distributions of sargassum for the simulated period (May 2017 to August 2017). The model closely approximated an observed increase during the period from May to July 2017, followed by a subsequent decline in sargassum abundance. A major factor that led to the discrepancy between the simulated and observed biomass accumulation is the occlusion of the optical satellite signal from cloud cover, which led to underestimates of sargassum abundance. The mean maximum growth rate required to reproduce the observed sargassum biomass was 0.05 day⁻¹, which is consistent with other published experimental and computational studies that have reported similar growth rates for sargassum populations under comparable environmental conditions. An innovative aspect of this study was the investigation of the biomass dynamics of the three dominant morphotypes found in the study area. The results from these simulations show that the accumulation of the fastest growing morphotype, Sargassum fluitans var. fluitans, closely approximates the profiles of the overall prediction with a single morphotype. Full article