Predicting size-resolved particle behavior in multizone buildings

We compare model predictions to measurements of SF₆ and environmental tobacco smoke particle concentrations in a three-room chamber experiment. To make predictions of multi-room aerosol transport and fate, we linked a multizone airflow model (COMIS) with an indoor aerosol dynamics model (MIAQ4). The linked models provide improved simulation capabilities for predicting aerosol concentrations and exposures in buildings. In this application, we found that the multizone air flow model was vital for predicting the inter-room airflows due to temperature differences between the rooms and when air-sampling pumps were operating during the experiment. Model predictions agree well with measurements, as shown by several comparison metrics. However, predictions of airborne ETS concentrations are slightly lower than measurements. This is mostly attributable to under-stating the source release amount, which we specified independently from literature estimates. Model predictions of ETS particle-size distributions agree with measurements; size bins with the peak concentrations are slightly over-predicted initially, but agree thereafter.     

Evaluation of results of a numerical simulation of dispersion in an idealised urban area for emergency response modelling

WinMISKAM is evaluated from an emergency response perspective. Comparisons are made between ground level concentrations observed during selected Mock Urban Setting Test (MUST) field trials and predictions generated by the model. The model was driven by 5 min averaged on-site meteorological data, and used minimum grid spacing of 0.5 m in both the horizontal and vertical. The code was found to perform well, with 46% of all predictions (paired in time and space) and 83% of arc maxima predictions within a factor of two of observed concentrations. The model was found to perform better for neutral cases than stable cases with 27% of stable case predictions and 57% of neutral case predictions within a factor of two when compared in time and space.     

Field scale characterization and modeling of contaminant release from a coal tar source zone

A coal tar contaminated site was characterized using traditional and innovative investigation methods. A careful interpretation of hydrogeological and hydrogeochemical data allowed for the conceptualization of the heterogeneous coal tar distribution in the subsurface. Past and future contaminant release from the source zone was calculated using a modeling framework consisting of a three-dimensional steady-state groundwater flow model (MODFLOW) and two hydrogeochemical models (MIN3P). Computational time of long-term simulations was reduced by simplifying the coal tar composition using 3 composite and 2 individual constituents and sequential application of a 2D centerline model (for calibration and predictions) and a 3D model (only for predictions). Predictions were carried out for a period of 1000 years. The results reveal that contaminant mass flux is governed by the geometry of zones containing residual coal tar, amount of coal tar, its composition and the physicochemical properties of the constituents. The long-term predictions made using the 2D model show that even after 1000 years, source depletion will be small with respect to phenanthrene, 89% of initial mass will be still available, and for the moderately and sparingly soluble composite constituents, 60% and 98%, respectively.     

Volatilisation of o-xylene from sandy soil

The diffusive release of o-xylene from two soils with different contents of organic carbon (1.1 % and 0.11 % TOC) and with two different water contents (app. 5 % w/w and 15 % w/w was studied in the laboratory. The soils were spiked with o-xylene in the laboratory. The fluxes were measured over a period of 24 hours. The measured fluxes were compared to predictions by two models. Model I, which is an analytical model, assumed instant local equilibrium between soil air, water and solids. The distribution coefficients were measured for the two soils, and Henry's constant and the diffusion coefficient in air were taken from the literature. This model overestimated the flux for o-xylene for all the tested combinations. The ratios between estimated and observed fluxes at 1 h were between 1.7 and 7.3. Model II assumed that the mass transfer of o-xylene between the solids and the water phase was kinetically controlled and was solved numerically. However, the predictions by the more advanced model were not significantly better than the prediction by the simple analytical model. The results indicate that prediction of o-xylene volatilisation from unsaturated soil is associated with substantial uncertainty.     

Kinetics of peat soil dissolved organic carbon release to surface water. Part 2. A chemodynamic process model

Temporary water reservoirs built upon peat soil may exhibit water quality impairment from elevated dissolved organic carbon (DOC). Microbiological decay of the organic carbon in the bed with subsequent release produces "tea" colored water which may require treatment prior to use. This paper contains a process-based mathematical model that quantifies the DOC release from the bed and its build-up in the water column. The model elements are based on microbial DOC production rates and bed sediment transport kinetics describing its' release from the organic soil systems. It relies on laboratory data obtained from an experimental study, Part 1, designed to simulate the DOC chemodynamics of aquatic reservoirs built upon peat soils. A two-step DOC release process was structured based on the experimental findings. The model mechanism assumes a quick release fraction that characterizes the upper soil surface layers as a "tea bag" type release process. This is followed by a fraction that is continuously produced and then released at a constant rate overtime by on-going microbial processes within the upper soil layers. The depth of the active layer, selected as h* = 0.3 cm, is the single adjustable parameter in the model. Concentration predictions of the are consistent with the laboratory simulations and field observations. Measured vs. model-calculated DOC concentrations for both in the microcosm bed and water column are used to test critical features of the proposed model. As conceived and structured it appears to be a realistic first step in quantifying the DOC release consequences for the water column of a reservoir sited upon a peat-soil bed. The development ends with an application to a hypothetical reservoir in order to illustrate model strengths and uncertainties.     

Analysis of air pollution data at a mixed source location using boosted regression trees

This paper explores the use of boosted regression trees to draw inferences concerning the source characteristics at a location of high source complexity. Models are developed for hourly concentrations of nitrogen oxides (NO_X) close to a large international airport. Model development is discussed and methods to quantify model uncertainties developed. It is shown that good explanatory models can be developed and further, allowing for interactions between model variables significantly improves the model fits compared with non-interacting models. Methods are used to determine which variables exert most influence over predicted concentrations and to explore the NO_X dependency for each. Model predictions are used to estimate aircraft take-off contributions to total concentrations of NO_X and determine how these predictions are affected by annual variations in meteorological conditions and runway use patterns. Furthermore, the results relating to the aircraft contributions to total NO_X concentration are compared with those from a more detailed independent field campaign. Finally, we find empirical evidence that plumes from larger aircraft disperse more rapidly from the point of release compared with smaller aircraft. The reasons for this behaviour and the implications are discussed.     

Sensitivity Analysis of Dispersion Models for Point and Area Sources

The body of information presented in this paper is directed to air quality managers in industry and government contemplating modeling emissions from complex sources under the bubble concept.

Point and area source algorithms of PAL, RAM, and ISC-ST were analyzed to show the effect of various input assumptions on model output. Several important parameters were varied individually; receptor grid spacing, emission release height, area source size and source type. Each of these parameters was varied over a range of values while all other modeling parameters, both physical and meteorological, were held constant. The outputs of each model are plotted for easy comparison.

Results indicate that it would be inappropriate to make certain assumptions regarding source characteristics without knowing the behavior of each model. The graphs show how the model predictions can vary for different input parameters when applied to point and area sources. The paper presents general rules of thumb for evaluating model results for many applications such as the bubble concept, emissions banking, offsets, and new source reviews. The results serve as a guide in selecting and using models for both point and area sources.     

Modeling of metal binding in tropical Fluvisols and Acrisols treated with biosolids and wastewater

There is growing concern about the accumulation of metals in tropical agricultural soils. In this study, experimental results from batch studies were used to test whether multi-surface geochemical models could describe metal binding in selected Vietnamese soils. The multi-surface models considered metal binding to iron hydroxides (using the diffuse layer model), organic matter (Stockholm Humic model and NICA-Donnan model), and phyllosilicate clay (Gaines-Thomas equation) as well as complexation to dissolved organic and inorganic ligands in the solution phase. We found that for total dissolved Cd, Cu and Zn the two multi-surface models being tested provided very good model fits for all soils, as evidenced by low root-mean square errors between model predictions and observations. These results suggest that organic matter is an important sorbent for many metals in these soils. However, poor fits were obtained for Cr(III), Mn and Pb for all soils. The study also suggests that the pH is the main factor that controls the solubility of metals in tropical Fluvisols and Acrisols subjected to application of biosolids and wastewater, and that advanced multi-surface models can be used to simulate the binding and release of many trace metals.     

Virus transport in physically and geochemically heterogeneous subsurface porous media

A two-dimensional model for virus transport in physically and geochemically heterogeneous subsurface porous media is presented. The model involves solution of the advection-dispersion equation, which additionally considers virus inactivation in the solution, as well as virus removal at the solid matrix surface due to attachment (deposition), release, and inactivation. Two surface inactivation models for the fate of attached inactive viruses and their subsequent role on virus attachment and release were considered. Geochemical heterogeneity, portrayed as patches of positively charged metal oxyhydroxide coatings on collector grain surfaces, and physical heterogeneity, portrayed as spatial variability of hydraulic conductivity, were incorporated in the model. Both layered and randomly (log-normally) distributed physical and geochemical heterogeneities were considered. The upstream weighted multiple cell balance method was employed to numerically solve the governing equations of groundwater flow and virus transport. Model predictions show that the presence of subsurface layered geochemical and physical heterogeneity results in preferential flow paths and thus significantly affect virus mobility. Random distributions of physical and geochemical heterogeneity have also notable influence on the virus transport behavior. While the solution inactivation rate was found to significantly influence the virus transport behavior, surface inactivation under realistic field conditions has probably a negligible influence on the overall virus transport. It was further demonstrated that large virus release rates result in extended periods of virus breakthrough over significant distances downstream from the injection sites. This behavior suggests that simpler models that account for virus adsorption through a retardation factor may yield a misleading assessment of virus transport in "hydrogeologically sensitive" subsurface environments.     

Applied tracer tests in fractured rock: Can we predict natural gradient solute transport more accurately than fracture and matrix parameters?

Applied tracer tests provide a means to estimate aquifer parameters in fractured rock. The traditional approach to analysing these tests has been using a single fracture model to find the parameter values that generate the best fit to the measured breakthrough curve. In many cases, the ultimate aim is to predict solute transport under the natural gradient. Usually, no confidence limits are placed on parameter values and the impact of parameter errors on predictions of solute transport is not discussed. The assumption inherent in this approach is that the parameters determined under forced conditions will enable prediction of solute transport under the natural gradient. This paper considers the parameter and prediction uncertainty that might arise from analysis of breakthrough curves obtained from forced gradient applied tracer tests. By adding noise to an exact solution for transport in a single fracture in a porous matrix we create multiple realisations of an initial breakthrough curve. A least squares fitting routine is used to obtain a fit to each realisation, yielding a range of parameter values rather than a single set of absolute values. The suite of parameters is then used to make predictions of solute transport under lower hydraulic gradients and the uncertainty of estimated parameters and subsequent predictions of solute transport is compared. The results of this study show that predictions of breakthrough curve characteristics (first inflection point time, peak arrival time and peak concentration) for groundwater flow speeds with orders of magnitude smaller than that at which a test is conducted can sometimes be determined even more accurately than the fracture and matrix parameters.     

Influence of surfactant-facilitated interfacial tension reduction on chlorinated solvent migration in porous media: observations and numerical simulation

The ability of a multiphase flow model to capture the migration behavior of chlorinated solvents under conditions of surfactant-facilitated interfacial tension (IFT) reduction is assessed through comparison of model predictions with observations from controlled laboratory experiments. Tetrachloroethene (PCE) was released in two-dimensional saturated systems, packed with sandy media that incorporated rectangular lenses of capillary contrast. Spatially uniform interfacial tension conditions were created in the tanks by pre-flushing the porous medium with either Milli Q water or an aqueous surfactant solution. Experimental observations showed that surfactant-facilitated IFT reductions substantially lowered capillary resistance to the vertical downward migration of PCE and enabled PCE to enter finer grained, less permeable lenses that were not penetrated in the absence of surfactant. An immiscible flow model was used to simulate the conditions of the laboratory experiments. Under higher IFT conditions (47.5 and 5 dyn/cm), the model could successfully predict the general migration behavior of the organic liquid. Model predictions, however, exhibited poorer agreement with observed migration pathways under low IFT conditions (0.5 dyn/cm). In all cases, the predicted PCE distributions were influenced by selection of the parametric model for capillary retention and relative permeability. Simulated migration rates were more consistent with observed behavior when the Brooks-Corey/Burdine model was employed. For low interfacial tensions, improved predictions of migration pathways were obtained through grid refinement and incorporation of small-scale packing variability. Simulations highlight the substantial sensitivity of model predictions to the capillary pressure-scaling factor, grid resolution, and small-scale porosity variations at interfaces of permeability contrast under reduced IFT conditions.     

Validation of an ecosystem modelling approach as a tool for ecological effect assessments

In ecotoxicology, derivation of a "safe" environmental concentration is usually achieved by the use of extrapolation factors or by statistical extrapolation from a set of single species toxicity data. These approaches ignore ecological interactions between species in the field. An ecology-based alternative to this pragmatic approach can be ecosystem modelling, which can account for ecological interactions. However, it is largely unexplored how well the predictions of these models quantitatively agree with large-scale experimental studies. Therefore, we evaluated the capacity of a flexible ecosystem model to predict population and ecosystem-level no observed effect concentrations (NOECs) of 7 organic toxicants. These NOECs were compared with population and ecosystem-NOECs observed in 11 micro- and mesocosm studies. For each of the latter studies, the model was customized to account for the specific ecological interactions within these systems and combined with appropriate single-species toxicity data from literature. Population-NOEC predictions were accurate, or at least protective, for 60, and 85% of all considered model populations, respectively. For all 11 studies, a protective ecosystem-NOEC could be derived, being accurate in 7 cases, and conservative in 4 cases. In general, it can be stated that this type of models can serve as an ecology-based alternative to current extrapolation techniques in EEAs and water quality standard setting.     

Assimilation of conventional and satellite wind observations in a mesoscale atmospheric model for studying atmospheric dispersion

A mesoscale atmospheric model PSU/NCAR MM5 is used to provide operational weather forecasts for a nuclear emergency response decision support system on the southeast coast of India. In this study the performance of the MM5 model with assimilation of conventional surface and upper-air observations along with satellite derived 2-d surface wind data from QuickSCAT sources is examined. Two numerical experiments with MM5 are conducted: one with static initialization using NCEP FNL data and second with dynamic initialization by assimilation of observations using four dimensional data assimilation (FDDA) analysis nudging for a pre-forecast period of 12 h. Dispersion simulations are conducted for a hypothetical source at Kalpakkam location with the HYSPLIT Lagrangian particle model using simulated wind field from the above experiments. The present paper brings out the differences in the atmospheric model predictions and the differences in dispersion model results from control and assimilation runs. An improvement is noted in the atmospheric fields from the assimilation experiment which has led to significant alteration in the trajectory positions, plume orientation and its distribution pattern. Sensitivity tests using different PBL and surface parameterizations indicated the simple first order closure schemes (Blackadar, MRF) coupled with the simple soil model have given better results for various atmospheric fields. The study illustrates the impact of the assimilation of the scatterometer wind and automated weather stations (AWS) observations on the meteorological model predictions and the dispersion results.     

Comparison of constant volume balloons, model trajectories and tracer transport during ETEX

In the field phases of the European Tracer EXperiment (ETEX), an inert tracer was released for 12 h into the atmosphere and samples taken at several locations downwind. During the same time, several Constant Volume Balloons (CVB) (10 and 6 for ETEX first and second release, respectively) were launched into different altitudes and followed as far as 21–188 km, to indicate the initial dispersion directions of the tracer puff. A model simulating the CVB behaviour in hydrostatic meso-scale model forecasts is applied to ETEX data to demonstrate its capability to predict the tracer puff mean axis over long distances (−2000 km). CVB model results are first compared to air parcels trajectories and 2D (i.e. isentropic, isobaric and isodensity) trajectories. Then they are compared to the measured CVB trajectories and finally to the tracer puff trajectories. As expected, the CVB model and isodensity model trajectories are found to be identical. The 16 CVBs calculated trajectories nearly overlap the real ones over 21–188 km with mean absolute horizontal transport deviations less than 20 km (average value of 8.2 km). The corresponding relative transport deviations are less than 45% with an average value of 20.6%. Better predictions are obtained for the ETEX second release. During the 60 h following ETEX’s first release start, the simulated CVBs are mainly found in the area of the maximum surface concentrations of the released tracer, up to 2000 km. Up to 36 h after ETEX second tracer release start, the simulated CVB trajectories predict well the mean axis of the tracer puff, but failed later.     

Evaluation of a Gaussian and a Lagrangian model against a roadside data set,with emphasis on low wind speed conditions

The evaluation of the high percentiles of concentration distributions is required by most national air quality guidelines, as well as the EU directives. However, it is problematic to compute such high percentiles in stable, low wind speed or calm conditions. This study utilizes the results of a previous measurement campaign near a major road at Elimäki in southern Finland in 1995, a campaign specifically designed for model evaluation purposes. In this study, numerical simulations were performed with a Gaussian finite line source dispersion model CAR-FMI and a Lagrangian dispersion model GRAL, and model predictions were compared with the field measurements. In comparison with corresponding results presented previously in the literature, the agreement of measured and predicted data sets was good for both models considered, as measured using various statistical parameters. For instance, considering all NO_x data (N=587), the so-called index of agreement values varied from 0.76 to 0.87 and from 0.81 to 1.00 for the CAR-FMI and GRAL models, respectively. The CAR-FMI model tends to slightly overestimate the NO_x concentrations (fractional bias FB=+14%), while the GRAL model has a tendency to underestimate NO_x concentrations (FB=−16%). The GRAL model provides special treatment to account for enhanced horizontal dispersion in low wind speed conditions; while such adjustments have not been included in the CAR-FMI model. This type of Lagrangian model therefore predicts lower concentrations, in conditions of low wind speeds and stable stratification, in comparison with a standard Lagrangian model. In low wind speed conditions the meandering of the flow can be quite significant, leading to enhanced horizontal dispersion. We also analyzed the difference between the model predictions and measured data in terms of the wind speed and direction. The performance of the CAR-FMI model deteriorated as the wind direction approached a direction parallel to the road, and for the lowest wind speeds. However, the performance of the GRAL model varied less with wind speed and direction; the model simulated better the cases of low wind speed and those with the wind nearly parallel to the road.     

Electrokinetic ion transport through unsaturated soil: 2. Application to a heterogeneous field site

Results of a field demonstration of electrokinetic transport of acetate through an unsaturated heterogeneous soil are compared to numerical modeling predictions. The numerical model was based on the groundwater flow and transport codes MODFLOW and MT3D modified to account for electrically induced ion transport. The 6-month field demonstration was conducted in an unsaturated layered soil profile where the soil moisture content ranged from 4% to 28% (m3 m(-3)). Specially designed ceramic-cased electrodes maintained a steady-state moisture content and electric potential field between the electrodes during the field demonstration. Acetate, a byproduct of acetic acid neutralization of the cathode electrolysis reaction, was transported from the cathode to the anode by electromigration. Field demonstration results indicated preferential transport of acetate through soil layers exhibiting higher moisture content/electrical conductivity. These field transport results agree with theoretical predictions that electromigration velocity is proportional to a power function of the effective moisture content. A numerical model using a homogeneous moisture content/electrical conductivity domain did not adequately predict the acetate field results. Numerical model predictions using a three-layer electrical conductivity/moisture content profile agreed qualitatively with the observed acetate distribution. These results suggest that field heterogeneities must be incorporated into electrokinetic models to predict ion transport at the field-scale.     

An inverse approach for estimating the initial distribution of volatile organic compounds in dry building material

A model for the prediction of emission of volatile organic compounds (VOCs) from dry building material was developed based on mass transfer theory. The model considers both diffusion and convective mass transfer. In addition, it does not neglect the fact that, in most cases, the initial distribution of VOCs within the material is non-uniform. Under the condition that the initial amount of VOCs contained in the building material is the same, six different types of initial VOC distributions were studied in order to show their effects on the characteristics of emission. The results show that, for short-term predictions, the effects are significant and thus cannot be neglected. Based on the fact that the initial distribution of VOCs is very difficult to directly determine, a conjugate gradient method with an adjoint problem for estimating functions was developed, which can be used to inversely estimate the initial distribution of VOCs within the material without a priori information on the functional form of the unknown function. Simulated measurements with and without measurement errors were used to validate the algorithm. This powerful method successfully recovered all of the aforementioned six different types of initial VOC distributions. A deviation between the exact and predicted initial condition near the bottom of the material was noticed, and a twin chamber method is proposed to obtain more accurate results. With accurate knowledge of the initial distribution of VOCs, source models will be able to yield more accurate predictions.     

Particulate air quality model predictions using prognostic vs. diagnostic meteorology in central California

Comparisons were made between three sets of meteorological fields used to support air quality predictions for the California Regional Particulate Air Quality Study (CRPAQS) winter episode from December 15, 2000 to January 6, 2001. The first set of fields was interpolated from observations using an objective analysis method. The second set of fields was generated using the WRF prognostic model without data assimilation. The third set of fields was generated using the WRF prognostic model with the four-dimensional data assimilation (FDDA) technique. The UCD/CIT air quality model was applied with each set of meteorological fields to predict the concentrations of airborne particulate matter and gaseous species in central California. The results show that the WRF model without data assimilation over-predicts surface wind speed by ～30% on average and consequently yields under-predictions for all PM and gaseous species except sulfate (S(VI)) and ozone(O₃). The WRF model with FDDA improves the agreement between predicted and observed wind and temperature values and consequently yields improved predictions for all PM and gaseous species. Overall, diagnostic meteorological fields produced more accurate air quality predictions than either version of the WRF prognostic fields during this episode. Population-weighted average PM_2.5 exposure is 40% higher using diagnostic meteorological fields compared to prognostic meteorological fields created without data assimilation. These results suggest diagnostic meteorological fields based on a dense measurement network are the preferred choice for air quality model studies during stagnant periods in locations with complex topography.     

On performing long-term predictions of ozone using the SOMS model

This study examined the potential of using the Simplified Ozone Modeling System (SOMS) (Venkatram et al., 1994. Atmospheric Environment 28, 3665–3678) to generate long-term ozone predictions that may be used to complement the results from more complex air quality models for creating control strategies and establishing long-term trends. A sensitivity study was performed using SOMS to study the application of a model, which is an exponential function of temperature, to estimate the intra-annual biogenic VOC concentration at the receptor in a 1-year run (i.e. 1988). The predictions were made for a core urban site in Baltimore, Maryland. After the sensitivity analyses was completed, the daily maximum ozone concentration (DMOC) was predicted for a 3-year (1987–1989) period for the Baltimore site. The results of the 3-year model prediction were compared with observations.     

Validation of the operational emergency response model at the Swedish Meteorological and Hydrological Institute using data from etex and the chernobyl accident

The Eulerian atmospheric tracer transport model MATCH (Multiscale Atmospheric Transport and Chemistry model) has been extended with a Lagrangian particle model treating the initial dispersion of pollutants from point sources. The model has been implemented at the Swedish Meteorological and Hydrological Institute in an emergency response system for nuclear accidents and can be activated on short notice to provide forecast concentration and deposition fields.The model has been used to simulate the transport of the inert tracer released during the ETEX experiment and the transport and deposition of ¹³⁷Cs from the Chernobyl accident. Visual inspection of the results as well as statistical analysis shows that the extent, time of arrival and duration of the tracer cloud, is in good agreement with the observations for both cases, with a tendency towards over-prediction for the first ETEX release. For the Chernobyl case the simulated deposition pattern over Scandinavia and over Europe as a whole agrees with observations when observed precipitation is used in the simulation. When model calculated precipitation is used, the quality of the simulation is reduced significantly and the model fails to predict major features of the observed deposition field.