Continuous Point Source Research Articles

Vertical mass exchange in wetland flows with shear layers

Vertical mass exchange hugely changes the solute distribution with the effects of shear layers and multiple-scale turbulent vortices, and then impacts the effectiveness of wetlands in purifying eutrophic water bodies. This study aims to investigate vertical mass exchange mechanisms in wetland systems and to provide theoretical guidance for optimizing the purification efficiency of wetland water quality. We simulate solute diffusion behaviors originating from a continuous point source with vegetated shear layers and bed absorptions through the adopted numerical simulation method, random walk method. The simulated results mainly contributed to three findings: (1) Vegetation features (density and height) inhibit solute diffusion, resulting in a prolonged steady time required for the cross-sectional concentration to reach equilibrium. (2) There is a threshold for the bed absorption probabilities to impact near-bed concentration distribution, that is the 10% absorption probability, over which the variation of bed absorption has few effects on the solute concentration. (3) The shear layer at the top of vegetation promotes vertical mass exchange while preventing solutes above the wake zone from being absorbed by the bed. In practice, the dual effects of submerged vegetation on vertical mass exchange should be comprehensively considered to ensure the effective functioning of wetland ecosystems.

Distinctive adsorption and transport behaviors of short-chain versus long-chain perfluoroalkyl acids in a river sediment.

Perfluoroalkyl acids (PFAAs) embrace perfluorooctanesulfonic acid (PFOS), perfluorooctanoic acid (PFOA), and other concerning chemicals of different chain length and terminal moieties. PFAAs can leach from municipal wastewater facilities as point sources discharging into rivers and receiving streams. In this study, we investigated the adsorption and transport behaviors of six select PFAAs in a Hudson River (USA) sediment in both batch and mesocosm studies. The adsorption capacities single and dual solute systems followed the order: PFBA < PFHxA ≈ PFBS < PFHxS < PFOA << PFOS. Mesocosm experiment that receives a continuous point source discharge of a mixture of these six PFAAs reached equilibrium after 4 weeks of operation. Total adsorbed PFAAs in the sediment was extracted and analyzed, following PFHxS (0.85 mg, 20.4%) ≈ PFBS (0.92 mg, 21.7%) < PFOA (1.02 mg, 27.3%) ≈ PFHxA (1.04 mg, 29.8%) < PFBA (1.12 mg, 30.1%) << PFOS (1.55 mg, 39.2%). PFOS showed highest adsorption, concentrating on the surface layer. Noticeably, two short-chain PFAAs, PFBA and PFHxA, were found with high vertical mobility, partitioning into deeper sediment. Two hotspots for PFAA sediment contamination were formed near the sediment surface downstream from the point source, providing new prospects to guide PFAA sediment cleanup and monitoring. Graphical abstract.

Coupled hydro-mechanical model for underground hydrogen storage undergoing cyclic injection and production

ABSTRACT Excess renewable energy can be used to generate and store hydrogen underground, offering a secure and econimical solution to the intermittency challenges of renewable energy sources. The success of underground storage relies on understanding and controlling the geo-mechanical integrity of storage sites during cyclic loadings. While geological deformation during natural gas and carbon dioxide storage is well studied, few have investigated pore pressure and in-situ stress variations during cyclic loading, which is unique to underground hydrogen storage sites. This paper presents a predictive analytical model for the pore pressure and stress changes during cyclic loading. The model was derived based on continuous point source injection, a basic hydro-mechanical model while applying the superposition to consider the cyclic loading. The developed model was evaluated for hydrogen and natural gas subjected to cyclic injection and production. Comparing hydrogen and natural gas storage cases can offer valuable insights into the behavior of hydrogen since the deformation of natural gas storage is more studied. Finally, analytical solutions for both storage cases were validated by numerical models with discrepancies between the models amounting to less than 1%. Comparative analysis of the results from 3 to 99 cycles of injection and production for both hydrogen and methane demonstrates that rise in cycle numbers leads to a corresponding rise in stress accumulation in the system. Neglecting the stress accumulation during these cycles can lead to significant geomechanical issues, potentially compromising the storage system’s safety and integrity.

A dispersion model for initial consequence analysis based on diffusion equations

Most factories use toxic or flammable chemicals in their industrial processes; this poses a risk of leakage due to accidents, which can sometimes result in mass casualties and considerable property damage. Therefore, quantitative risk prediction and assessment are necessary to protect the public and minimize losses in the event of a chemical release. Several methods can be used to evaluate chemical dispersion in the atmosphere, but most are based on the assumption of neutral buoyancy and far-field wind conditions. With this assumption, a model is valid only after a significant amount of time has elapsed from the moment chemicals are released or dispersed from a source. However, the most dangerous locations are typically close to a leak source. Therefore, a dispersion model for the initial phase of a leak is required to quantify the risk and predict the extent of damage. This study developed a dispersion model for initial consequence analysis using a three-dimensional unsteady convective diffusion equation. A continuous point source was assumed, and ethane was used as the leak material to minimize the effects of buoyancy. The unsteady concentration field developed rapidly as the diffusion coefficient and wind velocity increased, but the steady-state concentration field was not affected by wind velocity. This dispersion model also allows for the simple consideration of ground adsorption, making it scalable to real-world situations. The time to reach a steady state required for an effective emergency response was predicted, and the results were interpreted in terms of mathematical methods and physical characteristics.

Studying the Effect of the Instantaneous and Continuous Pollutants Sources on the Advection-diffusion Equation and Its Applications

This study investigates instantaneous and continuous sources as point, line, and area sources. Gaussian concentration in the case of the puff model with an instantaneous point source inhomogeneous longitudinal diffusion is investigated. The concentration is calculated using different dispersion parameters to get the proposed normalized concentration of the puff model at ground level around the centerline, which is compared with observed data by the Copenhagen experiment and previous work [1]. Also, the continuous point source is used to get the Gaussian plume model in three dimensions using dispersion parameters to compare with the observed concentration data measured by the Egyptian Atomic Energy Authority for Iodine-135 (I135) in an unstable condition.

A DiffeRential Evolution Adaptive Metropolis (DREAM)-based inverse model for continuous release source identification in river pollution incidents: Quantitative evaluation and sensitivity analysis

The identification of continuous pollution sources for rivers is of great concern for emergency response. Most studies focused on instantaneous river pollution sources and associated incidents. There is a dire need to address continuous pollution sources, as pollutant discharge may impose a major impact on the water ecosystem. Therefore, in this study, a novel inverse model is proposed to identify the continuous point sources in river pollution incidents that would estimate the source strength, location, release time, and spill time. The proposed inverse model combines the advanced DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm and the forward transport advection-dispersion equation to infer the posterior probability distribution of source parameters for quantifying uncertainties. In addition, the performance of the DREAM-based model is compared with those of the Metropolis-Hastings (MH)-based and genetic algorithm (GA)-based models. The results show that the DREAM-based model performs accurately for both the hypothetical and the field tracer cases. The comparative analysis shows that the DREAM-based model performs better in saving computation time, improving the accuracy of results, and reconstructing pollutant concentrations. Observation errors significantly influence the accuracy of the identification results from the DREAM-based model. In addition, a comprehensive sensitivity analysis of the DREAM-based model is conducted. The identification results from the DREAM-based model are sensitive to the dispersion coefficient and river velocity. The accuracy of the inverse model could be improved by increasing the monitoring number and by monitoring locations closer to the spill site. The findings of this study can improve decision-making during emergency responses to sudden river pollution incidents.

Steady State Dispersion of Non-buoyant Air Pollutants with Variable Wind Profile and Removal Mechanism

In this paper, a mathematical model is proposed to study the steady state dispersion of non-buoyant air pollutants emitted from a continuous point source. The effect of wind velocity is taken in the form of a power function that changes with downwind and crosswind distances. The concept of removal mechanism is also incorporated in the model. The concentration profile of non-buoyant air pollutants is computed and variations of the downwind and crosswind distances for a range of parametric values are analyzed. The results are explained graphically. It is found that the curves drawn demonstrate the consistent behavior with different vertical distances for 0 ≤ ≤ 1, while keeping the crosswind distance constant. Also, the downwind distance is increased with a consistent decrease in the concentration profile. The curves with different crosswind distance values and a constant vertical distance also show uniform behavior for 0 ≤ ≤ 1. Concentration profiles have been found to be symmetric for 1 ≤ ≤ 1 with varying downwind distance values while maintaining a constant vertical distance value.

QES-Plume v1.0: a Lagrangian dispersion model

Abstract. Low-cost simulations providing accurate predictions of transport of airborne material in urban areas, vegetative canopies, and complex terrain are demanding because of the small-scale heterogeneity of the features influencing the mean flow and turbulence fields. Common models used to predict turbulent transport of passive scalars are based on the Lagrangian stochastic dispersion model. The Quick Environmental Simulation (QES) tool is a low-computational-cost framework developed to provide high-resolution wind and concentration fields in a variety of complex atmospheric-boundary-layer environments. Part of the framework, QES-Plume, is a Lagrangian dispersion code that uses a time-implicit integration scheme to solve the generalized Langevin equations which require mean flow and turbulence fields. Here, QES-Plume is driven by QES-Winds, a 3D fast-response model that computes mass-consistent wind fields around buildings, vegetation, and hills using empirical parameterizations, and QES-Turb, a local-mixing-length turbulence model. In this paper, the particle dispersion model is presented and validated against analytical solutions to examine QES-Plume’s performance under idealized conditions. In particular, QES-Plume is evaluated against a classical Gaussian plume model for an elevated continuous point-source release in uniform flow, the Lagrangian scaling of dispersion in isotropic turbulence, and a non-Gaussian plume model for an elevated continuous point-source release in a power-law boundary-layer flow. In these cases, QES-Plume yields a maximum relative error below 6 % when compared with analytical solutions. In addition, the model is tested against wind-tunnel data for a uniform array of cubical buildings. QES-Plume exhibits good agreement with the experiment with 99 % of matched zeros and 59 % of the predicted concentrations falling within a factor of 2 of the experimental concentrations. Furthermore, results also emphasize the importance of using high-quality turbulence models for particle dispersion in complex environments. Finally, QES-Plume demonstrates excellent computational performance.

Numerical solution of non-linear advection-dispersion equation in a finite porous domain

This study presents a numerical simulation of the one-dimensional concentration-dependent convection-dispersion equation in a finite heterogeneous porous formation. The solution of the convection-diffusion equation with variable coefficients is obtained with the help of MATLAB pdepe solver. The groundwater flow velocity depends on the pollutant concentration, and the dispersion coefficient is proportional to the groundwater flow velocity. The effects of the zero-order production term and the first-order decay are also considered. The aquifer is assumed to be heterogeneous and finite, with sources concentrated in the flow direction. It is assumed that the porous media and the pollutant are chemically non-reactive. Initially porous domain is considered not solute free. The model assumes a uniform continuous input point source and a variable input point source released from the left end of the aquifer domain. The obtained results graphically describe the importance of the dispersion coefficient and other relevant parameters for solute transport in porous media. The developed numerical solution is verified with an analytical solution, and it is found that they are in good agreement.

The Upcoming GAMMA-400 Experiment

The upcoming GAMMA-400 experiment will be implemented aboard the Russian astrophysical space observatory, which will be operating in a highly elliptical orbit over a period of 7 years to provide new data on gamma-ray emissions and cosmic-ray electron + positron fluxes, mainly from the galactic plane, the Galactic Center, and the Sun. The main observation mode will be a continuous point-source mode, with a duration of up to ~100 days. The GAMMA-400 gamma-ray telescope will study high-energy gamma-ray emissions of up to several TeV and cosmic-ray electrons + positrons up to 20 TeV. The GAMMA-400 telescope will have a high angular resolution, high energy and time resolutions, and a very good separation efficiency for separating gamma rays from the cosmic-ray background and the electrons + positrons from protons. A distinctive feature of the GAMMA-400 gamma-ray telescope is its wonderful angular resolution for energies of &gt;30 GeV (0.01° for Eγ = 100 GeV), which exceeds the resolutions of space-based and ground-based gamma-ray telescopes by a factor of 5–10. GAMMA-400 studies can reveal gamma-ray emissions from dark matter particles’ annihilation or decay, identify many unassociated, discrete sources, explore the extended sources’ structures, and improve the cosmic-ray electron + positron spectra data for energies of &gt;30 GeV.

Wave Equation Modeling via Physics-Informed Neural Networks: Models of Soft and Hard Constraints for Initial and Boundary Conditions.

Therapeutic ultrasound waves are the main instruments used in many noninvasive clinical procedures. They are continuously transforming medical treatments through mechanical and thermal effects. To allow for effective and safe delivery of ultrasound waves, numerical modeling methods such as the Finite Difference Method (FDM) and the Finite Element Method (FEM) are used. However, modeling the acoustic wave equation can result in several computational complications. In this work, we study the accuracy of using Physics-Informed Neural Networks (PINNs) to solve the wave equation when applying different combinations of initial and boundary conditions (ICs and BCs) constraints. By exploiting the mesh-free nature of PINNs and their prediction speed, we specifically model the wave equation with a continuous time-dependent point source function. Four main models are designed and studied to monitor the effects of soft or hard constraints on the prediction accuracy and performance. The predicted solutions in all the models were compared to an FDM solution for prediction error estimation. The trials of this work reveal that the wave equation modeled by a PINN with soft IC and BC (soft-soft) constraints reflects the lowest prediction error among the four combinations of constraints.

A Comparison of Advection Diffusion Equation Solutions, Observed Data, and Statistical Results

In this paper, the statistical procedure is compared to the analytical solutions of an advection-diffusion equation describing air pollution spread in a limited atmospheric boundary layer from a continuous point source. The equation is formulated by assuming the eddy diffusivity and wind velocity as the constant and the power law of vertical height. It has been observed that the expected concentration for eddy diffusivity and wind velocity as constants has a worse agreement with the actual concentration than the expected concentration for wind speed and eddy diffusivity as variables.

In situ 3D spatiotemporal measurement of soluble biomarkers in spheroid culture.

Advanced cell culture techniques such as 3D bioprinting and hydrogel-based cell embedding techniques harbor many new and exciting opportunities to study cells in environments that closely recapitulate in vivo conditions. Researchers often study these environments using fluorescence microscopy to visualize the protein association with objects such as cells within the 3D environment, yet quantification of concentration profiles in the microenvironment has remained elusive. Demonstrate an assay that enables near real-time in situ biomarker detection and spatiotemporal quantification of biomarker concentration in 3D cell culture. A distributed bead-based immuno-assay was used in 3D cell culture to continuously measure the time-dependent concentration gradient of various biomarkers by sequestering soluble target molecules and concentrating the fluorescence intensity of these tagged proteins. Timelapse confocal microscopy was used to measure the in situ fluorescence intensity profile and a calibration curve was separately generated. Application of a calibration transfer function to in situ data is used to quantify spatiotemporal concentration. Example assays utilize an osteosarcoma spheroid as a case study for a quantitative single-plexed gel encapsulated assay, and a qualitative multi-plexed 3D-bioprinted assay. In both cases, a time-varying cytokine concentration gradient is measured. An estimation for the production rate of the IL-8 cytokine per second per osteosarcoma cell results from fitting an analytical function for continuous point source diffusion to the measured concentration gradient and reveals that spheroid production approaches nearly 0.18fg/s of IL-8 after 18h in culture. Theoretical and experimental demonstration of bead-based immunoassays in diffusion-limited environments such as 3D cell culture is shown, and includes example measurements of various cytokines produced by an osteosarcoma spheroid. Proper calibration and use of this assay is exhaustively explored for the case of diffusion-limited Langmuir kinetics of a spherical adsorber.

Research and analysis of environmental legal compensation mechanisms related to waste incineration in the context of “double carbon”

In the context of “double carbon,” waste disposal has become a critical issue so far, and how to deal with it is the key to ensuring compliance with the double carbon target, the most practical treatment is still incineration, and how to establish the site selection and legal compensation mechanism is crucial. This paper establishes an environmental dynamic monitoring system for waste incineration power plants based on the Gaussian model and successfully solves the health risk of surrounding residents. Regarding the economic compensation issues, we first applied the AHP to analyze the pollutants comprehensively, constructed the judgment matrix, and conducted a consistency test, determined the weight of each index, and integrated various emissions into one pollutant, which is convenient for the concentration of pollutants. Then, by taking into account the effects of wind direction, rainfall, topography, and other factors on the diffusion of pollutants, we calculated the pollutants around the waste incineration power plant site based on the “elevated continuous point source” “diffusion model.” To obtain the concentration distribution, monitoring points were set up at representative locations, and the environmental monitoring system of the waste incineration power plant was established. Finally, Matlab software was used to draw the contour map of pollutant concentration, and the concentration level of pollutants was divided according to waste incineration. Given the income of the power plant, the economic level of the surrounding residents, the amount of compensation from the local government, and the pollution level, economic compensation plans for the surrounding residents were developed. Through analyzing the proposed compensation scheme, it can be known that the compensation scheme can satisfy the surrounding residents. The highlights of this paper can be described as follows: First, the analytic hierarchy process is used to comprehensively consider the pollutants, simplifying the establishment process of the model. Second, the pollutant concentration is graded, and the concentration equivalent map is drawn to make the monitoring point layout more representative. The economic compensation plan is more reasonable and more convincing to the public.

Application of modified Gaussian plume algorithm in hazard assessment of toxic chemicals in nuclear power plants

The leakage or explosion of hazardous chemicals will seriously affect the operation safety of nuclear power plants. Therefore, in the nuclear safety review, it has been clearly proposed that the environmental risks of off-site toxic chemicals should be evaluated. When calculating the toxic chemical leakage accident, as HABIT model calculation result is based on the 2 min concentration limit condition assumed in RG1.78, and the longest duration is only 7.5 min, so it cannot be applied to the safety assessment of offsite toxic hazards. This paper presents a detail analysis of the impact on toxic chemical release using modified Gaussian plume algorithm model in ALOHA. The Gaussian plume algorithm is mainly used to calculate the plume diffusion emitted by continuous point sources, assuming that its concentration distribution obeys the empirical model of normal distribution. The plume is transported downwind at an average wind speed, ignoring turbulent diffusion downwind, with vertical and horizontal lateral diffusion described by diffusion parameters. The Gaussian plume algorithm has many advantages such as high computational efficiency and simple calculation method. Therefore, it has a wide application in the field of atmospheric diffusion. Calculation shows for the chlorine and ammonia leakage accident, chlorine’s influence area is much larger than ammonia. For ammonia, safe distance is about 3.5 km, but for chlorine, hydrogen fluoride and hydrazine, with the increase of storage capacity, their safety distance change slower at 8 km, which is consistent with HAD101/04. The storage amount of liquid ammonia shows an exponential increase, indicating that for liquid ammonia, the chemical safety control distance will not exceed 3.5 km. Conclusion of this paper has a long last meaning to NPP environmental assessment and safety evaluation, and full filled area of toxic chemicals quantitative analysis.

Coupling remote sensing and particle tracking to estimate trajectories in large water bodies

Propelled by the rapid development of equipment, technology and computational power, the monitoring and simulation of the hydrodynamics in lakes have steadily advanced. In contrast, water quality simulations are more difficult to implement, due to the difficulty in obtaining large-scale, spatially resolved field observations for model validation and the number of interacting processes to be parameterized. Here we demonstrate that remote sensing data can be used to inform Lagrangian particle tracking in a large lake, and vice versa. We used total suspended matter (TSM) as a parameter that can be both estimated from the backscattering in satellite images and modelled in terms of particle abundance. Specifically, we compared TSM concentrations in Lake Geneva deduced from images taken by Sentinel-2 and Sentinel-3 satellites to those estimated from Delft3D hydrodynamic and particle tracking models. TSM concentrations obtained from both methods were compared over a time span of up to 5 days in several scenario studies, including instantaneous and continuous point sources and large-scale TSM simulations. The results demonstrate that remote sensing images can serve to calibrate and validate particle tracking models with independent observations. The model was able to capture both the position of a TSM cloud arising 5 days after an instantaneous point source release, and the direction of particle transport and TSM plume size resulting from a continuous source. Even when simulating the whole lake domain, model results closely approximated the satellite-derived TSM concentrations along lake transects within 9%. In return, the particle tracking model was able to complete partially impaired satellite images, and fill in a four-day image gaps between satellite revisits. The synergy of remote sensing techniques and particle tracking modelling allows a rapid, continuous and more accurate analysis on solute transport in lakes.

Analysis of temporal and spatial distribution characteristics of ammonium chloride smoke particles in confined spaces

In response to the demand for short-range detection of anti-smoke environment interference by laser fuzes, this study proposes a smoke environment simulation of non-uniform continuous point source diffusion and investigates an experimental laboratory smoke environment using an ammonium chloride smoke agent. The particle size distribution, composition, and mass flow distribution of the smoke were studied. Based on a discrete phase model and a k-ε turbulence model, a numerical simulation was developed to model the smoke generation and diffusion processes of the smoke agent in a confined space. The temporal and spatial distribution characteristics of the smoke mass concentration, velocity, and temperature in the space after smoke generation were analyzed, and the motion law governing the smoke diffusion throughout the entire space was summarized. Combined with the experimental verification of the smoke environment laboratory, the results showed that the smoke plume changed from fan-shaped to umbrella-shaped during smoke generation, and then continued to spread around. Meanwhile, the mass concentration of smoke in the space decreased from the middle outward; the changes in temperature and velocity were small and stable. In the diffusion stage (after 900 s), the mass concentration of smoke above 0.8 m was relatively uniform across an area of smoke that was 12 m thick. The concentration decreased over time, following a consistent decreasing trend, and the attenuation was negligible in a very short time. Therefore, this system was suitable for conducting experimental research on laser fuzes in a smoke environment. Owing to the stability of the equipment and facilities, the setup could reproduce the same experimental smoke environment by artificially controlling the smoke emission of the smoke agent. Overall, this work provides a theoretical reference for subsequent research efforts regarding the construction of uniform smoke environments and evaluating laser transmission characteristics in smoky environments.

Evaluation of analytical solution of advection diffusion equation in three dimensions

AbstractThree‐dimensional advection–diffusion equation with steady state was evaluated from continuous point source taking the vertical and crosswind eddy diffusivities as power law of vertical height and downwind distance with constant wind speed to get the concentration in three dimensions. Separation of variables technique and Hankel transform were used to calculate this equation. The proposed analytical solution was compared with diffusion experiment of radioactive Iodine‐135 (I135) in unstable condition at Inshas, Cairo, Egypt. A good agreement achieved between calculated and observed concentration support our proposed model.

THE ANALYSIS OF THERMAL FIELDS AT THE PRIMARY STAGE OF THE STEAM-ASSISTED GRAVITY DRAINAGE PROCESS

This article analyzes the temperature distribution in a producer well at the primary stage of the steam-assisted gravity drainage process. The increase in share of hard-to-recover reserves requires using steam-assisted gravity drainage (SAGD). Its successful application, in turn, depends on warming up the inter-well zone, which demands steam circulation in both wells at the primary stage of the process. The duration of this stage affects the transition to oil production and the profitability of the process, which emphasizes the importance of analyzing thermal fields at this stage to assess its duration. The existing research does not allow estimating the temperature in the producer, using the correct formulation of the problem. This paper presents the temperature distribution in a producer for SAGD for classical and chess well patterns for the first time. The aim of the work is to choose a development system for the minimum duration of primary stage of SAGD. For this purpose, the fundamental solution of the non-stationary heat equation for a continuous stationary point source in an unbounded medium is used. The estimation of temperature, at which oil becomes mobile, allows determining the primary stage duration. The authors compare the classical and chess well patterns. In addition, they have obtained the temperature distribution in producer. The results show that classical well pattern provides faster heating of inter-well zone. It is determined that the closest injection well has the greatest influence on the temperature in the producing well.

Transient Flow Theory of Multiple-Fractured Horizontal Wells with Complex Mechanisms in Shale Gas Reservoirs

Shale reservoirs have the characterizations of low porosity, low permeability, and hydrocarbon organic matter self-generation and self-storage, resulting in its complex flow mechanisms. Compared with fractured vertical wells, multiple-fractured horizontal wells are widely used due to their advantages of effectively increasing the well control range and further expanding the drainage area. To further study the multiscale flow mechanisms of shale gas, a flow model was established that considered viscous flow in microfractures and inorganic pores, the diffusion of Knudsen in nanoscale porosity, the coexistence of slippage, adsorption-desorption effects under infinity, and closed outer boundary conditions; based on the continuous point source solution, a multiple-fractured horizontal well flow model was established and solved by MATLAB programming. Then, the effects of various factors were investigated. The results show that the Knudsen diffusion and slippage coefficients mainly affect the apparent permeability of the matrix pores. The more the Knudsen diffusion and slippage coefficients are, the earlier the turbulent flow occurs and the higher the gas production is.