Comparison of atmospheric modelling systems simulating the flow,turbulence and dispersion at the microscale within obstacles

Three different modelling techniques to simulate the pollutant dispersion in the atmosphere at the microscale and in presence of obstacles are evaluated and compared. The Eulerian and Lagrangian approaches are discussed, using RAMS6.0 and MicroSpray models respectively. Both prognostic and diagnostic modelling systems are considered for the meteorology as input to the Lagrangian model, their differences and performances are investigated. An experiment from the Mock Urban Setting Test field campaign observed dataset, measured within an idealized urban roughness, is used as reference for the comparison. A case in neutral conditions was chosen among the available ones. The predicted mean flow, turbulence and concentration fields are analysed on the basis of the observed data. The performances of the different modelling approaches are compared and their specific characteristics are addressed. Given the same flow and turbulence input fields, the quality of the Lagrangian particle model is found to be overall comparable to the full-Eulerian approach. The diagnostic approach for the meteorology shows a worse agreement with observations than the prognostic approach but still providing, in a much shorter simulation time, fields that are suitable and reliable for driving the dispersion model.     

A stochastic Lagrangian micromixing model for the dispersion of reactive scalars in turbulent flows: role of concentration fluctuations and improvements to the conserved scalar theory under non-homogeneous conditions

Several reaction schemes, based on the conserved scalar theory, are implemented within a stochastic Lagrangian micromixing model to simulate the dispersion of reactive scalars in turbulent flows. In particular, the formulation of the reaction-dominated limit (RDL) reaction scheme is here extended to improve the model performance under non-homogeneous conditions (NHRDL scheme). The validation of the stochastic model is obtained by comparison with the available measurements of reactive pollutant concentrations in a grid-generated turbulent flow. This test case describes the dispersion of two atmospheric reactant species (NO and O₃) and their reaction product (NO₂) in an unbounded turbulent flow. Model inter-comparisons are also assessed, by considering the results of state-of-the-art models for pollutant dispersion. The present validation shows that RDL reaction scheme provides a systematic overestimation (relative error of ca. 85% around the centreline) in computing the local reactant consumption/production rate, whereas the NHRDL scheme drastically reduces this gap (relative error lower than 5% around the centreline). In terms of NO₂ production (or reactant consumption), neglecting concentration fluctuations determines overestimations of the product mean of around 100% and a NO₂ local production of one order of magnitude higher than the reference simulation. In terms of standard deviations, the concentration fluctuations of both the passive and reactive scalars are generally of the same order of magnitude or up to 1 or 2 orders of magnitudes higher than the corresponding ensemble mean values, except for the background reactant close to the plume edges. The study highlights the importance of modelling pollutant reactions depending on the instantaneous instead of the mean concentrations of the reactants, thus quantifying the role of the turbulent fluctuations of concentration, in terms of scalar statistics (mean, standard deviation, intensity of fluctuations, skewness and kurtosis of concentration, segregation coefficient, simulated reaction rate). This stochastic particle method represents an efficient numerical technique to solve the convection–diffusion equation for reactive scalars and involves several application fields: micro-scale air quality (urban and street-canyon scales), accidental releases, impact of odours, water quality and fluid flow industrial processes (e.g. combustion).     

Plume rise and spread in buoyant releases from elevated sources in the lower atmosphere

This study focuses on the influence of emission conditions—velocity and temperature—on the dynamics of a buoyant gas release in the atmosphere. The investigations are performed by means of wind tunnel experiments and numerical simulations. The aim is to evaluate the reliability of a Lagrangian code to simulate the dispersion of a plume produced by pollutant emissions influenced by thermal and inertial phenomena. This numerical code implements the coupling between a Lagrangian stochastic model and an integral plume rise model being able to estimate the centroid trajectory. We verified the accuracy of the plume rise model and we investigated the ability of two Lagrangian models to evaluate the plume spread by means of comparisons between experiments and numerical solutions. A quantitative study of the performances of the models through some suitable statistical indices is presented and critically discussed. This analysis shows that an additional spread has to be introduced in the Lagrangian trajectory equation in order to account the dynamical and thermal effects induced by the source conditions.     

A Computational Fluid Dynamics Approach for Urban Area Transport and Dispersion Modeling

A simulation tool has been developed to model the wind fields, turbulence fields, and the dispersion of Chemical, Biological, Radiological and Nuclear (CBRN) substances in urban areas on the building to city blocks scale. A Computational Fluid Dynamics (CFD) approach has been taken that naturally accounts for critical flow and dispersion processes in urban areas, such as channeling, lofting, vertical mixing and turbulence, by solving the steady-state, Reynolds-Averaged Navier–Stokes (RANS) equations. Rapid generation of high quality cityscape volume meshes is attained by a unique voxel-based model generator that directly interfaces with common Geographic Information Systems (GIS) file formats. The flow and turbulence fields are obtained by solving the steady-state RANS equations using a collocated, pressure-based approach formulated for unstructured and polyhedral mesh elements. Turbulence modeling is based upon the Renormalization Group variant of the k–ε model (k–ε RNG). Neutrally buoyant simulations are made by prescribing velocity boundary condition profiles found by a power–law relationship, while turbulence quantities boundary conditions are defined by a prescribed mixing length in conjunction with the assumption of turbulence equilibrium. Dispersion fields are computed by solving an unsteady transport equation of a dilute gas, formulated in a Eulerian framework, using the velocity and turbulence fields found from the steady-state RANS solution. In this paper the model is explained and detailed comparisons of predicted to experimentally obtained velocity, turbulence and dispersion fields are made to neutrally stable wind tunnel and hydraulic flume experiments.     

Three-Dimensional Modelling of Concentration Fluctuations in Complicated Geometry

The strong fluctuating component in the measured concentration time series of a dispersing gaseous pollutant in the atmospheric boundary layer, and the hazard level associated to short-term concentration levels, demonstrate the necessity of calculating the magnitude of turbulent fluctuations of concentration using computational simulation models. Moreover the computation of concentration fluctuations in cases of dispersion in realistic situations, such as built-up areas or street canyons, is of special practical interest for hazard assessment purposes. In this paper, the formulation and evaluation of a model for concentration fluctuations, based on a transport equation, are presented. The model is applicable in cases of complex geometry. It is included in the framework of a computational code, developed for simulating the dispersion of buoyant pollutants over complex geometries. The experimental data used for the model evaluation concerned the dispersion of a passive gas in a street canyon between 4 identical rectangular buildings performed in a wind tunnel. The experimental concentration fluctuations data have been derived from measured high frequency concentrations. The concentration fluctuations model is evaluated by comparing the model's predictions with the observations in the form of scatter plots, quantile-quantile plots, contour plots and statistical indices as the fractional bias, the geometrical mean variance and the factor-of-two percentage. From the above comparisons it is concluded that the overall model performance in the present complex geometry case is satisfactory. The discrepancies between model predictions and observations are attributed to inaccuracies in prescribing the actual wind tunnel boundary conditions to the computational code.     

An ecological risk assessment model for a pulsed contaminant emission into a wetland channel flow

As a continuation of the modelling on ecological degradation and hydraulic dispersion of pollutant emission into an idealized two-dimensional free-surface wetland flow (Zeng, L., Chen, G.Q., 2009b. Ecological degradation and hydraulic dispersion of contaminant in wetland. Ecol. Model., doi:10.1016/j.ecolmodel.2009.10.024), an ecological risk assessment model for the typical case of a pulsed contaminant emission into a realistic three-dimensional wetland channel flow is presented in this paper for the fate of cross-sectional mean concentration under environmental dispersion. An environmental dispersion model for the mean concentration is devised as an extension of Taylor’s classical analysis on dispersion in fluid flows. The velocity distribution and the environmental dispersivity in the fully developed steady flow through the wetland is found and illustrated with limiting cases covering various known solutions for the porous media flow between parallel plates, flow in a shallow wetland, sweeping flow in a densely vegetated wetland, and single phase flow in a channel. Obtained by Aris’s method of moments, the environmental dispersivity is shown characterized with multi-scale asymptotic time variations with stem dominated stage, transitional stage, and width-depth-stem dominated stage. Based on the solution for the evolution of contaminant cloud in the wetland channel flow, critical length and duration of the contaminant cloud with concentration beyond given environmental standard level are concretely illustrated for typical pollutant constituents in wastewater emission. Under the same emission intensity and environmental standard, the duration of contaminant cloud in the wetland channel is revealed shorter than that in a free surface wetland, due to the lateral effect.     

Using a sub-grid scale modeling approach to simulate the transport and fate of toxic air pollutants

Several air toxics are emitted from mobile sources on roadways and these emissions account for a significant fraction of the health risks to the population. In addition, health effect studies are now becoming more comprehensive and some account for the spatial heterogeneities of air pollutant concentration fields (as is the case near roadways). Standard models can simulate either the near-source concentration fields or the urban background, but no model can handle both spatial scales in the vicinity of roadways in a coherent and scientifically correct manner. Here, we present a model that provides such an integrated treatment by combining a grid-based air quality model of the urban background with a plume-in-grid representation of roadway emissions. The model is applied to simulate near-roadway concentrations due to emissions from a busy interstate highway in New York City. Qualitative comparisons with typical measured concentration profiles show that the model captures the observed features of toxic air pollutant concentrations near roadways.     

Ecological degradation and hydraulic dispersion of contaminant in wetland

For the typical case of a pulsed contaminant emission into a free surface wetland flow, a theoretical analysis is presented in this paper for the decay of the depth-averaged concentration under the combined action of ecological degradation and hydraulic dispersion. Based on a first-order reaction model extensively employed in related ecological risk assessment and environmental hydraulic design, the effect of ecological degradation is separated from the hydraulic effect via an exponential transformation for the general formulation for contaminant transport. The speed profile of a fully developed steady flow through the wetland is obtained. A hydraulic dispersion model for the depth-averaged concentration is devised as an extension of Taylor’s classical analysis on dispersion, and corresponding hydraulic dispersivity is obtained by Aris’s method of moments. Analytical solution of depth-averaged concentration is rigorously derived and characterized. For typical pollutant constituents in wastewater emission, the evolution of contaminant cloud in the wetland flow is illustrated by critical length and duration of influenced region with contaminant concentration beyond given environmental standard level, with essential implications for ecological risk assessment and environmental management.     

A CFD-based wind solver for an urban fast response transport and dispersion model

In many cities, ambient air quality is deteriorating leading to concerns about the health of city inhabitants. In urban areas with narrow streets surrounded by clusters of tall buildings, called street canyons, air pollution from traffic emissions and other sources may accumulate resulting in high pollutant concentrations. For various situations, including the evacuation of populated areas in the event of an accidental or deliberate release of chemical, biological and radiological agents, it is important that models should be developed that produce urban flow fields quickly. Various computational techniques have been used to calculate these flow fields, but these techniques are often computationally intensive. Most fast response models currently in use are at a disadvantage in these cases as they are unable to correlate highly heterogeneous urban structures with the diagnostic parameterizations on which they are based. In this paper, a novel variant of the popular projection method for solving the Navier–Stokes equations has been developed and applied to produce fast and reasonably accurate parallel computational fluid dynamics (CFD) solutions for flow in complex urban areas. This model, called QUIC-CFD represents an intermediate balance between fast (on the order of minutes for a several block problem) and reasonably accurate solutions. This paper details the solution procedure and validates this model for various simple and complex urban geometries.     

Prediction of the upper tail of concentration distributions of a continuous point source release in urban environments

The peak values observed in a measured concentration time series of a dispersing gaseous pollutant released continuously from a point source in urban environments, and the hazard level associated with them, demonstrate the necessity of predicting the upper tail of concentration distributions. For the prediction of concentration distributions statistical models are preferably employed which provide information about the probability of occurrence. In this paper a concentration database pertaining to a field experiment is used for the selection of the statistical distribution. The inverses of the gamma cumulative distribution function (cdf) for 75th–99th percentiles of concentration are found to be more consistent with the experimental data than those of the log-normal distribution. The experimental values have been derived from measured high frequency time series by sorting first the concentrations and then finding the concentration which corresponds to each probability. Then the concentration mean and variance that are predicted with Computational Fluid Dynamics-Reynolds Averaged Navier–Stokes (RANS) methodology are used to construct the gamma distribution. The proposed model (“RANS-gamma”) is included in the framework of a computational code (ADREA-HF) suitable for simulating the dispersion of airborne pollutants over complex geometries. The methodology is validated by comparing the inverses of the model cdfs with the observed ones from two wind tunnel experiments. The evaluation is performed in the form of validation metrics such as the fractional bias, the normalized mean square error and the factor-of-two percentage. From the above comparisons it is concluded that the overall model performance for the present cases is satisfactory.     

Description and preliminary validation of the PMSS fast response parallel atmospheric flow and dispersion solver in complex built-up areas

Noxious atmospheric releases may originate from both accidents and malicious activities. They are a major concern for public authorities or first responders who may wish to have the most accurate situational awareness. Nonetheless, it is difficult to reliably and accurately model the flow, transport, and dispersion processes in large complex built-up environments in a limited amount of time and resources compatible with operational needs. The parallel version of Micro-SWIFT-SPRAY (PMSS) is an attempt to propose a physically sound and fast response modelling system applicable to complicated industrial or urban sites in case of a hazardous release. This paper presents and justifies the choice of the diagnostic flow and Lagrangian dispersion models in PMSS. Then, it documents in detail the development of the parallel algorithms used to reduce the computational time of the models. Finally, the paper emphasizes the preliminary model validation and parallel performances of PMSS based on data from both wind tunnel (Evaluation of Model Uncertainty) and in-field reduced-scale (Mock Urban Setting Test) and real-scale (Oklahoma City) experimental campaigns.     

Sulfamethoxazole removal from polluted water by immobilized photocatalysis

The photocatalytic activity of TiO₂ deposits (Degussa P25 and Millennium PC500) has been studied using sulfamethoxazole (SMX) as a model water pollutant and a UV fluorescent lamp as a light source (365 nm). Both catalysts have shown very similar properties in the photocatalytic degradation of SMX. Special attention has been given to the effect of the irradiation time, pH, and pollutant concentration. No mass-transfer limitations are observed. The degradation of SMX is accelerated at low concentration, and the photocatalytic degradation kinetics obey the Langmuir–Hinshelwood model, allowing the adsorption and apparent rate constants to be determined for both catalysts.     

A dispersion model for traffic produced turbulence in a two-way traffic scenario

Low wind speed conditions are often associated with poor air quality in urban areas, especially near roadways. Predictions of pollutant concentration under such conditions, i.e. low wind-speeds and near road locations, are, however, complicated by the role of traffic produced turbulence (TPT) on pollutant mixing and dilution. Existing dispersion models consider the effect of TPT on pollutant concentrations near roadways, accounting for parameters such as vehicle intensity, vehicle speeds, etc, but do not explicitly account for the contribution of two-way traffic interaction on the pollutant dispersion parameter. The turbulent kinetic energy (TKE) resulting from a two-way traffic condition will be higher than that with a one-way traffic pattern. Here, we obtain a simple formulation for TKE under a two-way traffic pattern from the balance of production and dissipation of turbulence. Considering the vorticity generated by the two-way traffic and determining the equivalent drag coefficient, an expression for TKE due to the two-way traffic interaction was obtained for three different traffic density regimes: light, intermediate, and heavy. The model predictions are validated by comparison with published data from a field study. An improved parameterization of the TPT considering the two-way traffic interaction effect is seen to significantly improve predictions of near roadway pollutant concentrations.     

江苏近岸海域营养盐类污染分布特征与评价

江苏沿海大多属于淤泥质平原海岸,开发利用方式以农业为主,海水中的营养盐类污染物质量浓度分布与入海河流和海岸区域农田化肥施用强度有重要的关系,因此,了解和探讨江苏近岸营养盐类污染的污染程度及其分布有重要的意义。根据江苏近海区域特征,选择近岸海域19个站点作为研究地点,分别对这些地点的总氮、总磷、无机氮和磷酸盐等营养盐类污染物质量浓度进行了分析,首先探讨了这些营养盐污染物在分布江苏近岸海域沿岸方向和向海方向的空间分布特点,然后结合海水水质标准,利用等标污染指数和综合污染指数等方法进行了污染程度评价,得出了江苏沿海营养盐类污染物在空间分布上具有南北两端和中间部位都比较高,而中部辐射沙洲附近和南北两端之间的质量浓度较低的"W"形分布特征,在向海方向上具有营养盐污染物质量浓度基本上都表现为靠近海岸质量浓度高,远离海岸略低的变化趋势,在污染程度评价方面,总磷等标污染指数普遍超过1,总氮等标污染指数大多小于1,综合污染指数在1.63～14.08之间,差异比较明显,一般表现为南北高中间低的特点,最后结合江苏沿海地区河流排污入海情况以及农田化肥农药施用强度,对江苏近岸海域营养盐类污染分布状况进行了讨论。     

Two-phase SPH modelling of advective diffusion processes

This paper deals with a two-dimensional numerical model based on the smoothed particle hydrodynamics (SPH) technique for the evaluation of the concentration field of pollutants in water. A SPH model is formulated to solve the fickian diffusion equation applied to pollutants with the same density as the water. A lagrangian SPH formalism of the advective diffusion equation is also developed for pollutant-water, taking into account the effects of molecular diffusion and natural advection induced by differences between the fluid densities. These equations are coupled with the fluid mechanics equations. Attention is paid to the numerical aspects involved in the solution procedure and to the optimization of the model parameters. Environmental engineering problems concerning diffusion and natural advection phenomena occur in the presence of a pollutant in still water. Numerical tests referring to a strip and a bubble of contaminant in a water tank with different initial concentration laws have been carried out. The results obtained by the proposed SPH models are compared with other available SPH formulations, showing an overall better agreement with standard analytical solutions in terms of spatial evolution of the concentration values. Capabilities and limits of the proposed SPH models to simulate advective diffusion phenomena for a wide range of density ratios are discussed.     

A Multimedia Chemical Fate Model with Time-Dependent Air-Water Transfer Rates

A multimedia model for the temporal evolution of the concentration of chemical species in a water basin and its bottom sediment layer has been tested with time-dependent air-water transfer rates varying with the meteorological conditions over the basin. The multimedia model uses the chemical fugacity approach in a system of two ordinary differential equations for the chemical species partition in the two mentioned media, with transfer through the sediment-water and the air-water interfaces. The air-water transfer rates are estimated by a micrometeorological preprocessor. A scenario in which known concentrations in air of a soluble pollutant (benzene) induce water and sediment pollution is tested on both synthetic (MonteCarlo-simulated) and real series of meteorological data. It is found that the use of time-dependent transfer coefficients affects not only the relaxation time, but also the long term concentration of the pollutant in water and sediment, that differs between 10 and 40% in the examined cases when compared with the same multimedia model using average constant transfer rates as usual. This is shown to be due to the statistical correlations between meteorological parameters and air pollutant concentrations, which stresses the advantages of a time-dependent estimation of the transfer coefficients. Correction terms are proposed to take into account the correlation effects when a constant parameters multimedia model is used.     

Anti-diffusion and source identification with the ‘RAW’ scheme: A particle-based censored random walk

This paper presents a novel methodology for time reversal in advective-diffusive pollutant transport in groundwater systems and other environmental flow systems (specifically: time reversal of diffusive terms). The method developed in this paper extends previous particle-based approaches like the Reversed Time Particle Tracking Method of Bagtzoglou [6]. The reversal of the ‘diffusive’ and/or ‘macrodispersive’ component of pollutant migration is especially under focus here. The basis of the proposed scheme for anti-diffusion is a continuous time, censored, non-local random walk capable of tracking groundwater solute concentration profiles over time while conserving the (reverse) Fickian properties of the anti-diffusing particle cloud in terms of moments. This scheme is an alternative to the direct solution of the eulerian concentration-based diffusion PDE, which is notoriously unstable in reverse time. Our analysis leads to the conclusion that an adaptive time stepping scheme—with decreasing time step—is necessary in order to maintain a constant amount of anti-diffusion (the reverse form of Fick’s law). Specifically, we study the relations between the following parameters: time step evolution vs. time (or vs. number of steps); variance evolution (decrease rate); total time (or number of steps) required to reach a fully anti-diffused solution. The proposed approach is shown to be quite efficient; typically, for every ten time steps, one to two orders of magnitude reduction of the dispersion width of the plume can be attained. Furthermore, the method is shown to be asymptotically exact for reverse Fickian diffusion. The method is applied with success to several situations involving the diffusive transport of a conservative solute in the following cases: (i) Single source recovery in one-dimensional space with constant diffusion parameters (this example serves as a validation test for the theory); (ii) Single source recovery in two-dimensional space with constant isotropic diffusion (this example also serves as a test for the theory); (iii) Multiple source recovery in two-dimensional space, assuming isotropic diffusion. It is expected that the methodology tested in this paper is applicable more generally to complex environmental pollution problems involving multiple sources, anisotropic hydrodynamic dispersion, and space-time variable advection-diffusion flow systems; the modeling of reverse diffusion/dispersion in such systems is currently under investigation.     

Functional autoregressive forecasting of long-term seabed evolution

There is a need for decadal predictions of the seabed evolution, for example to inform resurvey strategies when maintaining navigation channels. The understanding of the physical processes involved in morphological evolution, and the viability of process models to accurately model evolution over these time scales, are currently limited. As a result, statistical approaches are used to supply long-term forecasts. In this paper, we introduce a novel statistical approach for this problem: the autoregressive Hilbertian model (ARH). This model naturally assesses the time evolution of spatially-distributed measurements. We apply the technique to a coastal area in the East Anglian coast over the period 1846 to 2002, and compare with two other statistical methods used recently for seabed prediction: the autoregressive model and the EOF model. We evaluate the performance of the three methods by comparing observations and predictions for 2002. The ARH model enables a reduction of 10% of the root mean squared errors. Finally, we compute the variability in the predictions related to time sampling using the jackknife, a method that uses subsamples to quantify uncertainties.     

Combined integral and particle model for describing the dispersion,dilution, terminal layer formation and influence area from a point source discharge into a water body

Contamination of coastal water is a persistent threat to ecosystems around the world. In this study, a novel model for describing the dispersion, dilution, terminal layer formation and influence area from a point source discharge into a water body is presented and compared with field measured data. The model is a Combined Integral and Particle model (CIPMO). In the initial stage, the motion, dispersion and dilution of a buoyant jet are calculated. The output from the buoyant jet model is then coupled with a Lagrangian Advection and Diffusion model describing the far-field. CIPMO ensures that both the near- and far-field processes are adequately resolved. The model either uses empirical data or collects environmental forcing data from open source hydrodynamic models with high spatial and temporal resolution. The method for coupling the near-field buoyant jet and the particle tracking model is described and the output is discussed. The model shows good results when compared with measurements from a field study.