A new Lagrangian particle model for the simulation of dense gas dispersion

A Lagrangian stochastic model (MicroSpray), able to simulate the airborne dispersion in complex terrain and in presence of obstacles, was modified to simulate the dispersion of dense gas clouds. This is accomplished by taking into account the following processes: negative buoyancy, gravity spreading and the particle's reflection at the bottom computational boundary. Elevated and ground level sources, continuous and instantaneous emissions, time varying sources, plumes with initial momentum (horizontal, vertical or oblique in any direction), plumes without initial momentum are considered. MicroSpray is part of the model system MSS, which also includes the diagnostic MicroSwift model for the reconstruction of the 3-D wind field in presence of obstacles and orography. To evaluate the MSS ability to simulate the dispersion of heavy gases, its simulation performances are compared in detail to two field experiments (Thorney Island and Kit Fox) and to a chlorine railway accident (Macdona). Then, a comprehensive analysis considering several experiments of the Modelers Data Archive is presented. The statistical analysis on the overall available data reveals that the performance of the new MicroSpray version for dense gas releases is generally reliable. For instance, the agreement between concentration predictions and observations is within a factor of two in the 72% up to 99% of the occurrences for the case studies considered. The values of other performance measures, such as correlation coefficient, geometric mean bias and geometric variance, mostly set in the ranges indicated as good-model performances in the specialized literature.     

Identification of transport processes in column experiments using a frequency domain approach

When a solute transport process is viewed as a dynamic system with input and output, a system identification technique can be used to study it from input-output data. According to the design of excitation signals in the system identification approach, the commonly used rectangular pulse as input signal for column experiments is not optimum because it does not simultaneously meet the requirements for exciting the studied transport process, i.e., possessing frequency components with high enough amplitude and wide enough passband. In this article, stepped sine signals were proposed to replace the rectangular pulse because their amplitude and passband can be independently chosen. The stepped sine signals of concentration were generated by a High Performance Liquid Chromatography (HPLC) and used as the input for the column experiments to identify parameters of the convection-dispersion equation (CDE) and mobile-immobile model (MIM). In order to test the effect of noise on the identification of transport process, numerical experiments were carried out to identify the CDE under white noise when the input was designed as stepped sine functions and rectangular pulse. The results of the numerical experiments showed that the input signal of a sine function was more robust and accurate in process identification than that of a rectangular pulse.     

Solutions and verification of a scale-dependent dispersion model

In this paper, analytical solutions are derived for a one-dimensional scale-dependent dispersion model (SDM), considering linear equilibrium sorption and first-order degradation for continuous and pulse contaminant sources, with a constant input concentration in a semi-infinite uniform porous medium. In the SDM model, dispersivity alpha(x) is replaced with a constant epsilon multiplied by the transport distance x. The solution for a pulse source is verified experimentally in the analysis of tritium data obtained from an 8-m-long homogenous pea-gravel column with multiple sampling locations, and the results are compared with those analysed by a commonly used solution of a constant dispersion model (CDM). The SDM predicts concentrations satisfactorily at all sampling locations, while the CDM fits the experimental data well for only one location. Both models are then calibrated for each individual concentration breakthrough curve, using local values for either epsilon in the SDM or alpha(x) in the CDM. Both models give equally good fits for appropriate choices of individual epsilon and alpha(x) values, and both indicate a linear increase in alpha(x) with distance. The epsilon values tend to change little as x increases and are expected to approach a constant at relatively large distances downstream. Hence, predictions from the SDM should become more accurate as x increases.     

2,4-二氯苯酚在土壤中的吸附及其批实验与柱实验的分配系数比较

为了研究2,4-二氯苯酚在土壤中的吸附及比较其批实验与柱实验的分配系数Kd,开展了2,4-二氯苯酚的批实验（不同液固比条件下）和柱实验。通过分析结果可知,在批实验中,不同液固比条件下2,4-二氯苯酚达到平衡的时间类似,都在60～70 h,吸附动力学曲线符合伪二级动力学方程,吸附规律是：液固比越大,平衡吸附量增大,反应速率常数K2减小,初始吸附速率常数减小;Kd随液固比增大而降低,范围在2.91～2.12 L/kg。柱实验结果表明,2,4-二氯苯酚的贯穿曲线可以很好地用化学非平衡模型来拟合,通过模型拟合得到的Kd值要低于批实验的结果。该研究对表征2,4-二氯苯酚在环境中的行为、预测其对土壤和地下水的污染及其治理提供了依据。     

Performance of a time-dependent dispersion model in elevated terrain

A study was conducted to evaluate the ability of the TVA quasi-steady model (QSM) to simulate plume dispersion over high terrain. QSM is a time-dependent, plume-segment model. The modeling results are compared with measured data obtained from a field study conducted at the Tennessee Valley Authority's (TVA) Widows Creek Steam Plant. Also, the results obtained using a steady-state Gaussian model are compared to give an indication of the advantages of a time-dependent method compared to a steady-state method.Although the results from both models agree well with the measured values, QSM, which provides better temporal and spatial resolution, more successfully modeled inversion-breakup and plume-impingement conditions.     

Reactive transport of 85Sr in a chernobyl sand column: static and dynamic experiments and modeling

The effects of nonlinear sorption and competition with major cations present in the soil solution on radioactive strontium transport in an eolian sand were examined. Three laboratory techniques were used to identify and quantify the chemical and hydrodynamic processes involved in strontium transport: batch experiments, stirred flow-through reactor experiments and saturated laboratory columns. The major goal was to compare the results obtained under static and dynamic conditions and to describe in a deterministic manner the predominant processes involved in radioactive strontium transport in such systems. Experiments under dynamic conditions, namely flow-through reactor and column experiments, were in very good agreement even though the solid/liquid ratio was very different. The experimental data obtained from the flow-through reactor study pointed to a nonlinear, instantaneous and reversible sorption process. Miscible displacement experiments were conducted to demonstrate the competition between stable and radioactive strontium and to quantify its effect on the 85Sr retardation factor. The results were modeled using the PHREEQC computer code. A suitable cation-exchange model was used to describe the solute/soil reaction. The model successfully described the results of the entire set of miscible displacement experiments using the same set of parameter values for the reaction calculations. The column study revealed that the stable Sr aqueous concentration was the most sensitive variable of the model, and that the initial state of the sand/solution system had also to be controlled to explain and describe the measured retardation factor of radioactive strontium. From these observations, propositions can be made to explain the discrepancies observed between some data obtained from static (batches) and dynamic (reactor and column) experiments. Desorbed antecedent species (stable Sr) are removed from the column or reactor in the flow system but continue to compete for sorption sites in the batch system. Batch experiments are simple and fast, and provide a very useful means of multiplying data. However, interpretation becomes difficult when different species compete for sorption sites in the soil/solution system. A combination of batches, flow-through reactor and column experiments, coupled with hydrogeochemical modeling, would seem to offer a very powerful tool for identifying and quantifying the predominant processes on a cubic decimeter scale (dm3) and for providing a range of radioactive strontium retardation factor as a function of the geochemistry of the soil/solution system.     

Determination of acute exposure guideline levels in a dispersion model

The U.S. Environmental Protection Agency (EPA) is in the process of establishing acute exposure guideline levels (AEGLs) for a number of toxic chemicals. These guidelines represent predictable human consequences from measured exposures of selected toxic chemicals over time. They are intended for emergency planning and regulatory purposes. This paper presents a method that can be used by atmospheric dispersion models to compute AEGL values and graphically display the regions exposed to each guideline level on area maps. EPA currently defines three levels of AEGLs corresponding to increasingly severe symptoms, ranging from notable discomfort (AEGL-1) to serious adverse health effects (AEGL-2) to life-threatening effects or death (AEGL-3). For each chemical's three AEGL levels, guideline concentrations are defined for five exposure durations: 10 min, 30 min, 1 hr, 4 hr, and 8 hr. Dispersion models can compute a chemical dosage (time-integrated concentration) and a peak concentration throughout the area exposed to the plume. The AEGL then can be computed by finding the effective duration of the plume at each location, computing the AEGL-equivalent dosages for these durations, and comparing the dosage at each point with the AEGL-equivalent dosages. AEGL contours then can be plotted and readily interpreted in terms of expected toxicity levels for each level of health impact.     

Shared- and distributed-memory parallelization of a Lagrangian atmospheric dispersion model

This paper describes parallelization of a 3-D Lagrangian stochastic atmospheric dispersion model using both distributed- and shared-memory methods. Shared-memory parallelism is implemented through the use of OpenMP compiler directives. Distributed-memory parallelism relies on the MPI message-passing library. One or both (using MPI for inter-node and OpenMP for intra-node communication) of the parallel modes can be used depending upon the requirements of the problem and the computational platform available. The distributed-memory version achieves a nearly linear decrease in execution time as the number of processors is increased. As the number of particles per processor is lowered, performance is limited by the decrease in work per processor and by the need to produce one set of output files. The shared-memory version achieves a speedup factor of ∼1.4 running on machines with four processors.     

Online update of model state and parameters of a Monte Carlo atmospheric dispersion model by using ensemble Kalman filter

For an atmospheric dispersion model designed for the assessment of nuclear accident consequences, some uncertain model parameters, such as source term and weather conditions, may influence the reliability of model predictions. In this respect, good estimations of both model state and uncertain parameters are required. In this paper, an ensemble Kalman filter (EnKF) based method for simultaneous state and parameter estimation, using off-site radiation monitoring data, is presented. This method is based on a stochastic state space model, which resembles the parameter errors with stochastic quantities. Three imperfect parameters, including the source release rate, wind direction and turbulence intensity were perturbed simultaneously, and multiple parameter estimation were performed. Having been tested against both simulated and real radiation monitoring data, the method was found to be able to realistically reconstruct the real scene of dispersion, as well as the uncertain parameters. The estimated parameters given by EnKF nicely converge to the true values, and the method also tracks the temporal variation of those parameters.     

Effective rates of heavy metal release from alkaline wastes--quantified by column outflow experiments and inverse simulations

Column outflow experiments operated at steady state flow conditions do not allow the identification of rate limited release processes. This requires an alternative experimental methodology. In this study, the aim was to apply such a methodology in order to identify and quantify effective release rates of heavy metals from granular wastes. Column experiments were conducted with demolition waste and municipal waste incineration (MSWI) bottom ash using different flow velocities and multiple flow interruptions. The effluent was analyzed for heavy metals, DOC, electrical conductivity and pH. The breakthrough-curves were inversely modeled with a numerical code based on the advection–dispersion equation with first order mass-transfer and nonlinear interaction terms. Chromium, Copper, Nickel and Arsenic are usually released under non-equilibrium conditions. DOC might play a role as carrier for those trace metals. By inverse simulations, generally good model fits are derived. Although some parameters are correlated and some model deficiencies can be revealed, we are able to deduce physically reasonable release-mass-transfer time scales. Applying forward simulations, the parameter space with equifinal parameter sets was delineated. The results demonstrate that the presented experimental design is capable of identifying and quantifying non-equilibrium conditions. They show also that the possibility of rate limited release must not be neglected in release and transport studies involving inorganic contaminants.     

Prediction of gas diffusion in complicated terrain by a potential flow model

A numerical model was developed to simulate gaseous diffusion in complicated terrain. This model calculates the air flow as a potential flow by the Boundary Element Method, and gaseous diffusion by an analytical Gaussian equation in the potential flow. Plume spreads σ_y and σ_z are modified by multiregression equations derived from wind tunnel experiments, and the terrain height is elongated depending on the atmospheric stability.First, tracer data from Cinder Cone Butte in the U.S. measured by the U.S.-EPA were predicted by the model in order to examine the prediction accuracy under stable conditions. The averaged ratio of the observed concentration to predicted concentration for 12 runs was better than a factor of 10. Next, tracer data from the Geysers area in the U.S. measured by the U.S.-DOE were used to examine the prediction accuracy under neutral conditions. The ratio of the observed concentration to predicted concentration for two runs under neutral conditions was better than factor of two at most locations, but prediction capability is poor in blocked or separated flow conditions.     

Development of a simple, accurate SPME-based method for assay of VOCs in column breakthrough experiments

Solid-phase microextraction (SPME) with gas chromatography is to be used for assay of effluent liquid samples from soil column experiments associated with VOC fate/transport studies. One goal of the fate/transport studies is to develop accurate, highly reproducible column breakthrough curves for 1,2-cis-dichloroethylene (cis-DCE) and trichloroethylene (TCE) to better understand interactions with selected natural solid phases. For SPME, the influences of the sample equilibration time, extraction temperature and the ratio of volume of sample bottle to that of the liquid sample (V(T)/V(w)) are the critical factors that could influence accuracy and precision of the measured results. Equilibrium between the gas phase and liquid phase was attained after 200 min of equilibration time. The temperature must be carefully controlled due to variation of both the Henry's constant (K(h)) and the fibre/gas phase distribution coefficient (K(fg)). K(h) decreases with decreasing temperature while K(fg) increases. Low V(T)/V(w) yields better sensitivity but results in analyte losses and negative bias of the resultant assay. High V(T)/V(w) ratio yields reduced sensitivity but analyte losses were found to be minimal, leading to better accuracy and reproducibility. A fast SPME method was achieved, 5 min for SPME extraction and 3.10 min for GC analysis. A linear calibration function in the gas phase was developed to analyse the breakthrough curve data, linear between a range of 0.9-236 microgl(-1), and a detection limit lower than 5 microgl(-1).     

Modeling the mobility of glyphosate from two contrasting agricultural soils in laboratory column experiments

The method of single-strand conformational polymorphism (SSCP) was modified in our laboratories for the characterization of baculoviruses, insect viruses with great potential for use as bioinsecticides in biological protection programs. A series of primers were synthesized after the comparison of the polyhedrin gene sequences of over 20 baculoviruses. Polyhedrin is a highly conserved protein which is responsible for the persistence of the virus in the environment. Universal primers were designed which could be used in polymerase chain reactions (PCR) containing genomic DNA from an array of nucleopolyhedrosis viruses (NPVs) including these which are used as biopesticides against important pests of forests and crops, such as Anticarsia gemmatalis, Spodoptera frugiperda, Lymantria dispar, Lymantria monacha and many others. PCR products were denatured and subjected to single-strand DNA electrophoresis at variable temperatures (MSSCP) where, after silver staining, they gave ssDNA band patterns characteristic for each baculovirus species. This technique can be potentially applied to detect baculoviruses in insects collected in the field, as well as to plant tissues and the excrements or bodies of predators without need for sequencing the PCR products. Sometimes MSSCP can be used not only for species determination but also as an indication of genomic variability which can be related to infectivity.     

Unsteady characteristics of the dispersion process in the vicinity of a pig barn. Wind tunnel experiments and comparison with field data

Two complementary methods, field experiments and physical modelling in a wind tunnel, have been used to investigate the dispersion of tracer-gas released from the ventilation system of a pig barn, under near-neutral stability conditions. In both cases, concentration fluctuations were measured and the deduced statistical results were compared. The choice of data processing applied to the time series of concentration was motivated by special issues in the assessment of odour annoyances: “where, how often, how long and how strong does it smell?” These features were described by the mean concentration distribution, the intermittency factor, the persistence and the 90-percentile. The good agreement between field and wind tunnel data confirmed the ability to replicate in wind tunnel the unsteady properties of a dispersion process, if the unsteady turbulent behaviour of the atmospheric boundary layer was properly modelled.A parametrical study of the influence on the dispersion process of the ratio between the exhaust velocity from the stack and the wind speed was then performed in wind tunnel. The fundamental outcome was that the near-field dispersion process under neutral stability conditions, despite the strong influence of the building wake, was for the most part driven by the meandering behaviour of the plume and not so much by the diffusion process.This study was also focused on the influence of the averaging time on the statistical results. The scatter generated by using dimensionless averaging times 200<T_a^*<400 (used during field experiments) instead of T_a^*→∞ (averaging time to ensure reproducible statistic results) was quantified in the wind tunnel. A degree of representativity of the results obtained from short-term samples, compared to fully converged statistical results was therefore assessed.     

Utilization of fly ash to improve the quality of the acid mine drainage generated by oxidation of a sulphide-rich mining waste: column experiments

The production of Acid Mine Drainage (AMD) as a result of the oxidative dissolution of sulphides is one of the main pollution problems affecting natural watercourses in mining environments with sulphide-rich residues. In this work, the generation of AMD was prevented by means of the addition of fly ash to sulphide-rich residues in non-saturated column experiments. A column experiment filled with a pyrite-rich sludge with artificial irrigation leached acid drainages (pH approx. 2) containing high concentrations of sulphate, iron and other metals. However, non-saturated column experiments filled with pyritic-rich sludge and fly ash drained leachates characterized by alkaline pH (pH up to 10), low sulphate concentration, and lack of iron and other metals in solution. The pyrite oxidative dissolution at high pH, as a consequence of the leaching of fly ash, favours the metal precipitation inside the column (mainly iron), the coating of pyrite grains, and the attenuation of the oxidation process, resulting in a great improvement in the quality of the leachates.     

Soil column experiments used as a means to assess transport,sorption, and biodegradation of pesticides in groundwater

Soil column experiments are used to investigate the fate of three pesticides of high, intermediate, and low solubility in groundwater: N- phosphonomethyl glycine (glyphosate); O,O-diethyl-S-[(ethylthio)methyl]phosphorodithioate (phorate); (2,4-dichlorophenoxy)acetic acid (2,4-D). Feed solutions are prepared by adding each pesticide (100 mg/L glyphosate, 50 μ g/L phorate, 50 mg/L 2,4-D) along with conservative tracer, KBr, in synthetic groundwater. The concentration of the pesticides in effluents is detected by ion chromatography (glyphosate, 2,4-D) and GC-FID (phorate). The Br^? breakthrough curves are employed to estimate the dispersion coefficient and mean pore velocity in each column. Solute transport and reactive models accounting for equilibrium/non-equilibrium sorption and biodegradation are coupled with inverse modeling numerical codes to estimate the kinetic parameters for all pesticides.     

Soil column experiments used as a means to assess transport, sorption, and biodegradation of pesticides in groundwater

Soil column experiments are used to investigate the fate of three pesticides of high, intermediate, and low solubility in groundwater: N- phosphonomethyl glycine (glyphosate); O,O-diethyl-S-[(ethylthio)methyl]phosphorodithioate (phorate); (2,4-dichlorophenoxy)acetic acid (2,4-D). Feed solutions are prepared by adding each pesticide (100 mg/L glyphosate, 50 micro g/L phorate, 50 mg/L 2,4-D) along with conservative tracer, KBr, in synthetic groundwater. The concentration of the pesticides in effluents is detected by ion chromatography (glyphosate, 2,4-D) and GC-FID (phorate). The Br(-) breakthrough curves are employed to estimate the dispersion coefficient and mean pore velocity in each column. Solute transport and reactive models accounting for equilibrium/non-equilibrium sorption and biodegradation are coupled with inverse modeling numerical codes to estimate the kinetic parameters for all pesticides.     

Numerical modeling of humic colloid borne americium (III) migration in column experiments using the transport/speciation code K1D and the KICAM model

The humic colloid borne Am(III) transport was investigated in column experiments for Gorleben groundwater/sand systems. It was found that the interaction of Am with humic colloids is kinetically controlled, which strongly influences the migration behavior of Am(III). These kinetic effects have to be taken into account for transport/speciation modeling. The kinetically controlled availability model (KICAM) was developed to describe actinide sorption and transport in laboratory batch and column experiments. Application of the KICAM requires a chemical transport/speciation code, which simultaneously models both kinetically controlled processes and equilibrium reactions. Therefore, the code K1D was developed as a flexible research code that allows the inclusion of kinetic data in addition to transport features and chemical equilibrium. This paper presents the verification of K1D and its application to model column experiments investigating unimpeded humic colloid borne Am migration. Parmeters for reactive transport simulations were determined for a Gorleben groundwater system of high humic colloid concentration (GoHy 2227). A single set of parameters was used to model a series of column experiments. Model results correspond well to experimental data for the unretarded humic borne Am breakthrough.     

Air intake contamination by building exhausts: tracer gas investigation of atmospheric dispersion models in the urban environment

The establishment of a safe distance between sources of pollution and air intakes is based on a complex exercise that should take into account several wind, physical, and topographical factors. To estimate the maximum concentrations of the pollutants as a function of the distance from the emission source, some heating, ventilation, and air conditioning (HVAC) system designers use the atmospheric dispersion models suggested by the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE). Two of these models, the Halitsky and Wilson-Chui-Lamb models, have been developed and evaluated mainly with laboratory data. There have been relatively few evaluations with full-scale field data. The objective of this study, carried out on a building in downtown Montreal, Quebec, Canada, was to compare the measured concentrations of a tracer gas emitted by an exhaust stack with those predicted by these models. The results indicate that the Halitsky model gives lower than actual dilution, while the Wilson-Chui-Lamb model generally gives acceptable estimates, with occasional over-estimations of the dilution.