Exposure assessment, which is an investigation of the extent of human exposure to a specific contaminant, must include estimates of the duration and frequency of exposure. For a groundwater system, the duration of exposure is controlled largely by the arrival time of the contaminant of concern at a drinking water well. This arrival time, which is normally estimated by using groundwater flow and transport models, can have a range of possible values due to the uncertainties that are typically present in real problems. Earlier arrival times generally represent low likelihood events, but play a crucial role in the decision-making process that must be conservative and precautionary, especially when evaluating the potential for adverse health impacts. Therefore, an emphasis must be placed on the accuracy of the leading tail region in the likelihood distribution of possible arrival times. To demonstrate an approach to quantify the uncertainty of arrival times, a real contaminant transport problem which involves TCE contamination due to releases from the Lockformer Company Facility in Lisle, Illinois is used. The approach used in this research consists of two major components: inverse modelling or parameter estimation, and uncertainty analysis. The parameter estimation process for this case study was selected based on insufficiencies in the model and observational data due to errors, biases, and limitations. A consideration of its purpose, which is to aid in characterising uncertainty, was also made in the process by including many possible variations in attempts to minimize assumptions. A preliminary investigation was conducted using a well-accepted parameter estimation method, PEST, and the corresponding findings were used to define characteristics of the parameter estimation process applied to this case study. Numerous objective functions, which include the well-known L2-estimator, robust estimators (L1-estimators and M-estimators), penalty functions, and deadzones, were incorporated in the parameter estimation process to treat specific insufficiencies. The concept of equifinality was adopted and multiple maximum likelihood parameter sets were accepted if pre-defined physical criteria were met. For each objective function, three procedures were implemented as a part of the parameter estimation approach for the given case study: a multistart procedure, a stochastic search using the Dynamically-Dimensioned Search (DDS), and a test for acceptance based on predefined physical criteria. The best performance in terms of the ability of parameter sets to satisfy the physical criteria was achieved using a Cauchy’s M-estimator that was modified for this study and designated as the LRS1 M-estimator. Due to uncertainties, multiple parameter sets obtained with the LRS1 M-estimator, the L1-estimator, and the L2-estimator are recommended for use in uncertainty analysis. Penalty functions had to be incorporated into the objective function definitions to generate a sufficient number of acceptable parameter sets; in contrast, deadzones proved to produce negligible benefits. The characteristics for parameter sets were examined in terms of frequency histograms and plots of parameter value versus objective function value to infer the nature of the likelihood distributions of parameters. The correlation structure was estimated using Pearson’s product-moment correlation coefficient. The parameters are generally distributed uniformly or appear to follow a random nature with few correlations in the parameter space that results after the implementation of the multistart procedure. The execution of the search procedure results in the introduction of many correlations and in parameter distributions that appear to follow lognormal, normal, or uniform distributions. The application of the physical criteria refines the parameter characteristics in the parameter space resulting from the search procedure by reducing anomalies. The combined effect of optimization and the application of the physical criteria performs the function of behavioural thresholds by removing parameter sets with high objective function values. Uncertainty analysis is performed with parameter sets obtained through two different sampling methodologies: the Monte Carlo sampling methodology, which randomly and independently samples from user-defined distributions, and the physically-based DDS-AU (P-DDS-AU) sampling methodology, which is developed based on the multiple parameter sets acquired during the parameter estimation process. Monte Carlo samples are found to be inadequate for uncertainty analysis of this case study due to its inability to find parameter sets that meet the predefined physical criteria. Successful results are achieved using the P-DDS-AU sampling methodology that inherently accounts for parameter correlations and does not require assumptions regarding parameter distributions. For the P-DDS-AU samples, uncertainty representation is performed using four definitions based on pseudo-likelihoods: two based on the Nash and Sutcliffe efficiency criterion, and two based on inverse error or residual variance. The definitions consist of shaping factors that strongly affect the resulting likelihood distribution. In addition, some definitions are affected by the objective function definition. Therefore, all variations are considered in the development of likelihood distribution envelopes, which are designed to maximize the amount of information available to decision-makers. The considerations that are important to the creation of an uncertainty envelope are outlined in this thesis. In general, greater uncertainty appears to be present at the tails of the distribution. For a refinement of the uncertainty envelopes, the application of additional physical criteria is recommended. The selection of likelihood and objective function definitions and their properties are made based on the needs of the problem; therefore, preliminary investigations should always be conducted to provide a basis for selecting appropriate methods and definitions. It is imperative to remember that the communication of assumptions and definitions used in both parameter estimation and uncertainty analysis is crucial in decision-making scenarios.

Transport parameter estimation and contaminant source identification are critical steps in the development of a physically based groundwater contaminant transport model. Due to the irreversibility of the dispersion process, the calibration of a transport model of interest is inherently ill-posed, and very sensitive to the simplification employed in the development of the lumped models. In this research, a methodology for the calibration of physically based computationally intensive transport models was developed and applied to a case study, the Reich Farm Superfund site in Toms River, New Jersey. Using HydroGeoSphere, a physically based transient three-dimensional computationally intensive groundwater flow model with spatially and temporally varying recharge was developed. Due to the convergence issue of implementing saturation versus permeability curve (van Genuchten equation) for the large scale models with coarse discretization, a novel flux-based method was innovated to determined solutions for the unsaturated zone for soil-water-retention models. The parameters for the flow system were determined separately from the parameters for the contaminant transport model. The contaminant transport and source parameters were estimated using both approximately 15 years of TCE concentration data from continuous well records and data over a period of approximately 30 years from traditional monitoring wells, and compared using optimization with two heuristic search algorithms (DDS and MicroGA) and a gradient based multi-start PEST. The contaminant transport model calibration results indicate that overall, multi-start PEST performs best in terms of the final best objective function values with equal number of function evaluations. Multi-start PEST also was employed to identify contaminant transport and source parameters under different scenarios including spatially and temporally varying recharge and averaged recharge. For the detailed, transient flow model with spatially and temporally varying recharge, the estimated transverse dispersivity coefficients were estimated to be significantly less than that reported in the literature for the more traditional approach that uses steady-state flow with averaged, less physically based recharge values. In the end, based on the Latin Hypercube sampling, a methodology for comprehensive uncertainty analysis, which accounts for multiple parameter sets and the associated correlations, was developed and applied to the case study.

Exposure assessment, which is an investigation of the extent of human exposure to a specific contaminant, must include estimates of the duration and frequency of exposure. For a groundwater system, the duration of exposure is controlled largely by the arrival time of the contaminant of concern at a drinking water well. This arrival time, which is normally estimated by using groundwater flow and transport models, can have a range of possible values due to the uncertainties that are typically present in real problems. Earlier arrival times generally represent low likelihood events, but play a crucial role in the decision-making process that must be conservative and precautionary, especially when evaluating the potential for adverse health impacts. Therefore, an emphasis must be placed on the accuracy of the leading tail region in the likelihood distribution of possible arrival times. To demonstrate an approach to quantify the uncertainty of arrival times, a real contaminant transport problem which involves TCE contamination due to releases from the Lockformer Company Facility in Lisle, Illinois is used. The approach used in this research consists of two major components: inverse modelling or parameter estimation, and uncertainty analysis. The parameter estimation process for this case study was selected based on insufficiencies in the model and observational data due to errors, biases, and limitations. A consideration of its purpose, which is to aid in characterising uncertainty, was also made in the process by including many possible variations in attempts to minimize assumptions. A preliminary investigation was conducted using a well-accepted parameter estimation method, PEST, and the corresponding findings were used to define characteristics of the parameter estimation process applied to this case study. Numerous objective functions, which include the well-known L2-estimator, robust estimators (L1-estimators and M-estimators), penalty functions, and deadzones, were incorporated in the parameter estimation process to treat specific insufficiencies. The concept of equifinality was adopted and multiple maximum likelihood parameter sets were accepted if pre-defined physical criteria were met. For each objective function, three procedures were implemented as a part of the parameter estimation approach for the given case study: a multistart procedure, a stochastic search using the Dynamically-Dimensioned Search (DDS), and a test for acceptance based on predefined physical criteria. The best performance in terms of the ability of parameter sets to satisfy the physical criteria was achieved using a Cauchy’s M-estimator that was modified for this study and designated as the LRS1 M-estimator. Due to uncertainties, multiple parameter sets obtained with the LRS1 M-estimator, the L1-estimator, and the L2-estimator are recommended for use in uncertainty analysis. Penalty functions had to be incorporated into the objective function definitions to generate a sufficient number of acceptable parameter sets; in contrast, deadzones proved to produce negligible benefits. The characteristics for parameter sets were examined in terms of frequency histograms and plots of parameter value versus objective function value to infer the nature of the likelihood distributions of parameters. The correlation structure was estimated using Pearson’s product-moment correlation coefficient. The parameters are generally distributed uniformly or appear to follow a random nature with few correlations in the parameter space that results after the implementation of the multistart procedure. The execution of the search procedure results in the introduction of many correlations and in parameter distributions that appear to follow lognormal, normal, or uniform distributions. The application of the physical criteria refines the parameter characteristics in the parameter space resulting from the search procedure by reducing anomalies. The combined effect of optimization and the application of the physical criteria performs the function of behavioural thresholds by removing parameter sets with high objective function values. Uncertainty analysis is performed with parameter sets obtained through two different sampling methodologies: the Monte Carlo sampling methodology, which randomly and independently samples from user-defined distributions, and the physically-based DDS-AU (P-DDS-AU) sampling methodology, which is developed based on the multiple parameter sets acquired during the parameter estimation process. Monte Carlo samples are found to be inadequate for uncertainty analysis of this case study due to its inability to find parameter sets that meet the predefined physical criteria. Successful results are achieved using the P-DDS-AU sampling methodology that inherently accounts for parameter correlations and does not require assumptions regarding parameter distributions. For the P-DDS-AU samples, uncertainty representation is performed using four definitions based on pseudo-likelihoods: two based on the Nash and Sutcliffe efficiency criterion, and two based on inverse error or residual variance. The definitions consist of shaping factors that strongly affect the resulting likelihood distribution. In addition, some definitions are affected by the objective function definition. Therefore, all variations are considered in the development of likelihood distribution envelopes, which are designed to maximize the amount of information available to decision-makers. The considerations that are important to the creation of an uncertainty envelope are outlined in this thesis. In general, greater uncertainty appears to be present at the tails of the distribution. For a refinement of the uncertainty envelopes, the application of additional physical criteria is recommended. The selection of likelihood and objective function definitions and their properties are made based on the needs of the problem; therefore, preliminary investigations should always be conducted to provide a basis for selecting appropriate methods and definitions. It is imperative to remember that the communication of assumptions and definitions used in both parameter estimation and uncertainty analysis is crucial in decision-making scenarios.

Transport parameter estimation and contaminant source identification are critical steps in the development of a physically based groundwater contaminant transport model. Due to the irreversibility of the dispersion process, the calibration of a transport model of interest is inherently ill-posed, and very sensitive to the simplification employed in the development of the lumped models. In this research, a methodology for the calibration of physically based computationally intensive transport models was developed and applied to a case study, the Reich Farm Superfund site in Toms River, New Jersey. Using HydroGeoSphere, a physically based transient three-dimensional computationally intensive groundwater flow model with spatially and temporally varying recharge was developed. Due to the convergence issue of implementing saturation versus permeability curve (van Genuchten equation) for the large scale models with coarse discretization, a novel flux-based method was innovated to determined solutions for the unsaturated zone for soil-water-retention models. The parameters for the flow system were determined separately from the parameters for the contaminant transport model. The contaminant transport and source parameters were estimated using both approximately 15 years of TCE concentration data from continuous well records and data over a period of approximately 30 years from traditional monitoring wells, and compared using optimization with two heuristic search algorithms (DDS and MicroGA) and a gradient based multi-start PEST. The contaminant transport model calibration results indicate that overall, multi-start PEST performs best in terms of the final best objective function values with equal number of function evaluations. Multi-start PEST also was employed to identify contaminant transport and source parameters under different scenarios including spatially and temporally varying recharge and averaged recharge. For the detailed, transient flow model with spatially and temporally varying recharge, the estimated transverse dispersivity coefficients were estimated to be significantly less than that reported in the literature for the more traditional approach that uses steady-state flow with averaged, less physically based recharge values. In the end, based on the Latin Hypercube sampling, a methodology for comprehensive uncertainty analysis, which accounts for multiple parameter sets and the associated correlations, was developed and applied to the case study.

Alternative strategies involving in situ remediation technologies have been developed to assist with property clean up, however, cost-effectiveness and discrepancies in success rates and timeliness continue. The objective of my research was to critically demonstrate the application and usefulness of an in situ remediation technology at a petroleum hydrocarbon impacted site. This project was proposed as part of the research programs: Groundwater Plume Formation and Remediation of Modern Gasoline Fuels in the Subsurface and Enhancing In Situ Bioremediation at Brownfield Sites funded by the Ontario Centres of Excellence for Earth and Environmental Technologies as part of the multiphase project entitled “Enhancing in situ Bioremediation at Brownfield Sites”. This research focused on the demonstration of nitrate-enhanced in situ bioremediation at a decommissioned service station. Petroleum hydrocarbon impacted soil and groundwater is a common occurrence at gasoline distribution facilities, where toxicological effects are known for gasoline constituents of interest such as benzene, toluene, ethylbenzene and total xylenes (BTEX). These chemicals are volatile, readily soluble, and persistent in groundwater. In particular, residual contaminants present in the saturated zone were targeted for remediation as they serve as a long term source of contamination and contribute to mobile vapour phase and dissolved phase plumes. Site investigations characterized the complex hydrogeological conditions and contaminant distribution present in order to effectively design an in situ bioremediation treatment system. The addition of nitrate as a terminal electron acceptor (TEA) to an aquifer enhances in situ biodegradation of petroleum hydrocarbons, by providing the microbes with a sustainable energy source to promote cell maintenance and growth of the microbial population. The remediation strategy involved pulsed injections of remedial solution amended with a conservative bromide (200 mg/L Br-) and reactive nitrate (90 to 265 mg/L NO3-) tracers with the purpose of providing a continuous supply of TEA available to the indigenous microbial populations. Nitrate was selected as an alternative electron acceptor over the thermodynamically favoured O2 because of typical challenges encountered using O2 in bioremediation applications in addition to the existing anaerobic environment. In situ anaerobic degradation of BTEX compound using TEA amendments has been well documented; however benzene is often recalcitrant under denitrification conditions. The results of the Br- tracer breakthrough curves indicate that different preferential flow pathways were established under the transient saturated conditions present at the Site, although the behaviour of the injected remedial slug was generally consistent between the different units and the test solution was ultimately delivered to the target zone. The delivery of the remedial test solution was greatly influenced by the hydrogeological conditions present at the time of injection. The injectate was preferentially transported in the high permeability zone of sandy gravel aquifer Unit 3 under high saturated condition and background hydraulic gradients. However the seasonal decline in groundwater levels and hydraulic gradients resulted in the lower portion of Unit 4 comprised of higher permeable materials being able to transmit the test solution more effectively. Given the variable hydrogeological conditions present at the Site influenced by seasonal effects, the delivery of the remedial solution to target zones containing petroleum hydrocarbons at residual saturation is more effective under reduced saturated conditions. The delivery of TEA amended water to enhance the in situ biodegradation of petroleum contaminants is more effective when the treatment water has an increased residence time in the target remedial zone, attributed to low gradients and groundwater transport velocities at the Site. Longer residence periods enable the indigenous microbes to have increased contact time with the TEA which will be preferentially utilized to degrade the contaminants.   A reducing zone enriched with TEA in the anaerobic aquifer was established following consecutive injections of remedial test solution. A cumulative mass of 4 kg of NO3- was added to the target aquifer during the course of the remedial injections. Evidence demonstrating NO3- utilized as a terminal electron acceptor in the bioremediation of the petroleum-contaminated aquifer include: laboratory microcosm study confirming local indigenous microbial population’s ability to degrade hydrocarbons using NO3- as the TEA in addition to observed decrease in NO3- relative to a conservative Br- tracer and generation of nitrite, an intermediate product in denitrification in the pilot-scale operation. Contaminant mass removal likely occurred as Br- tracer evidence indicates that NO3- was utilized in the study area based on the inference of denitrification rates. Post-injection groundwater sampling indicate declining concentrations of toluene, however long term monitoring is recommended in order to evaluate the success of the remediation activity and assess the potential for rebound. Post-injection soil core results are unable to demonstrate the reduction in individual toluene, let alone BTEXTMB hydrocarbon levels, as a result of insufficient quantities of nitrate delivered to the target zone relative to the significant but heterogeneously distributed residual mass in the subsurface.

As the world population increases, the demand increases for quality drinking water. The harvesting of rainwater has the potential to assist in alleviating pressures on current water supplies and storm water drainage systems. Diversion of a portion of the collected water away from storage is a technique used to improve harvested rainwater water quality prior to storage. Six configurations of a downspout first flush diverter were constructed and tested in the laboratory. The configurations of diverters were evaluated for their affinity to allow diverted water in the diverter chamber to interact with the flow of water to storage. Experiments were conducted at flow rates ranging from 0.76 L/min to 113.56 L/min. This range of flow rates adequately represents a wide range of common storm intensity patterns across the United States to which downspout first flush diverters are subjected. The diverter chamber to downspout transition fittings tested on a 10.16 cm diameter diverter chamber, upward and downward oriented sanitary and straight tee, do not have a significant impact on the mean difference in initial and final total dissolved solids concentrations observed at multiple sample ports. No statistical difference was observed when comparing upward and downward oriented sanitary tees used as diverter chambers to downspout transition fittings on 10.16 and 15.24 cm diverter chambers. Utilizing a straight tee as a transition fitting with a floating ball, acting as a barrier between water collected in the diverter chamber of a downspout first flush diverter and the flow passing through the transition fitting, limited diverted water from interacting with the subsequent flow of harvested rainwater. There is not a significant difference between the use of a downspout first flush diverter with diverter chamber diameters of 10.16 and 15.24 cm utilizing upward and downward oriented sanitary tees as downspout to diverter chamber transition fittings. Tests at flow rates less than or equal to 12.11 L/min exhibited limited changes in total dissolved solids concentrations in the downspout first flush diverters with 15.24 cm diameter diverter chambers. Tests at flow rates less than or equal to 1.51 L/min exhibited limited changes in total dissolved solids concentrations in the downspout first flush diverters with 10.16 cm diameter diverter chambers. The diverter chamber drain flow rate and volume impacts the observed differences in initial and final TDS concentrations at all sample ports on the diverter chamber of a downspout first flush diverter regardless of flow rate. The diverter chamber drain flow rate impacts the flow rate of water entering the diverter chamber through the transition fitting.

NTO (3-nitro-1,2,4-triazol-5-one) is one of the new explosive compounds used in insensitive munitions (IM) and developed to replace traditional explosives, TNT and RDX. Data on NTO fate and transport is needed to determine its environmental behavior and potential for groundwater contamination. In this study, we measured how NTO in solution interacts with different types of soils and related soil properties to transport and fate behavior. We conducted a series of kinetic and equilibrium batch soil sorption experiments and saturated column transport studies under steady-state and transient conditions. NTO adsorbed very weakly to the studied soils. Adsorption coefficients (Kds) measured for NTO in a range of soils in batch experiments were less than 1 cm³ g⁻¹. There was a highly significant negative relationship between measured NTO adsorption coefficients and soil pH (P = 0.00011). In kinetic experiments, first order transformation rate estimates ranged between 0.0004 h⁻¹ and 0.0221 h⁻¹. There was a general agreement between batch and column-determined fate and transport parameters. However, transport studies showed an increase in the NTO transformation rate as a function of time, possibly indicating microbial growth.

Verunreinigtes Grundwasser stellt eine ernsthafte Bedrohung für die Trinkwasser-Ressourcen auf der ganzen Welt dar. Verunreinigte Grundwasser können zwar in Brunnen detektiert werden, eine ordnungsgemäße Sanierung ist jedoch häufig nur erfolgreich, wenn die Quelle der Verunreinigung erfasst und entfernt wird. Wenn von Anbeginn eines Sanierungsprojektes ein Schwerpunkt auf die Erkennung und Eingrenzung des Verunreinigungsherdes gelegt wird, kann die Sanierung direkt an dieser Stelle ansetzen und zudem hohe Grundwasser-Sanierungskosten verringert werden. ModBack ist eine Software, die mehrere bestehende Modellierungs-Werkzeuge in einer, ein-fach zu verwendenden, ESRI ArcGIS 10-basierten Schnittstelle vereinigt und hilft mögliche Schadstoffquelle Zonen im Untergrund abzugrenzen. Diese Software ist in Visual Basic 3.5 geschrieben und verwendet ArcObjects Bibliotheken, um die erforderlichen GIS-Anwendungen zu implementieren. Es kann ohne Änderung auf allen Microsoft Windows-basierten PC‘s mit ausreichend RAM und mindestens Microsoft. NET Framework 3.5 verwendet werden. Die Nutzung von ModBack erfordert zusätzliche Installation der folgenden Software: Processing Modflow Pro 7.0 (PMWin), MODPATH, CSTREAM (Bayer-Raich et al., 2003a, Bayer-Raich et al., 2003b, Bayer-Raich et al., 2004), Golden Software Surfer, Microsoft Excel und NAS (eine Software zur Berechnung des natürlichen Schadstoffabbaus). Die grafische Benutzeroberfläche (GUI) von ModBack ist in vier Verfahrensschritte Dateneingabe, Grundwassermodellierung, Partikel Backtracking und Analysen getrennt. Geographischen Eingangsdaten werden für eine geografische Übersicht des Testfeldes benötigt. Sie bestehen meist aus georeferenzierten Informationen des Testfeldes und Informationen zur unterirdischen Grundwasserverunreinigungen. Grundwasseranalysen werden entweder durch konventionelle Probennahme aus Grundwassermessstellen oder durch die Durchführung integraler Pumpversuche an Kontrolleben mit eine bestimmten Konzentration/Zeit- Serie (CT-series) gesammelt. Aus den Pumpversuchen resultierende hydraulische Daten werden zusammen mit allen anderen verfügbaren Informationen zur Erstellung eines grundlegenden Grundwasserströmungsmodells des Testfeldes verwendet. Nachfolgende Backtracking Verfahren, als auch die Berechnung von advektivem Schadstofftransport beziehen sich auf die-ses Strömungsfeld und werden entlang einer zuvor definierten Kontrollebene berechnet. Eine Analyse der Backtracking-Ergebnisse erfolgt innerhalb ModBack. Die potenzielle Quelle von Kontaminationen oder deren Abwesenheit werden basierend auf dem Verfahren nach Jarsjö et al. (2005) bestimmt. Die Länge einer Schadstofffahne kann anhand von Fahnenlängen Statistiken und /oder dem Abbau erster Ordnung Abbau Gleichungen oder Berechnungen auf ortsspezifische hydraulischen und chemischen Parametern beruhen. Ferner ist ein analytisches Instrument enthalten, um die Verteilung der Verunreinigungen über eine Steuerebene zu identifizieren. Alle relevanten Ergebnisse können als Vektordaten in ModBack graphisch dargestellt und gespeichert werden und sind somit kompatibel mit weiteren GIS-Software Produkten. ModBack wurde bereits an Testgebieten in Slowenien und Süddeutschland angewendet, um die möglichen Zonen der Verunreinigungsquelle oder deren Abwesenheit zu begrenzen. Auf dem Testgelände in Süddeutschland sind diese Abgrenzungen vergleichbar mit früheren Untersuchungen vor Ort und unterstützt somit die Funktionalität der Software ModBack. Mit ModBack, steht ein Werkzeug zur Verfügung, die bereits jetzt Um-welt-Beratern, Ingenieuren und Umwelt-Agenturen ermöglicht denkbare Quellen der Verunreinigung bei der Planung der Untersuchungen vor Ort und Sanierungsmaßnahmen abzugrenzen, und hilft Kosten deutlich zu senken.

Several oil sands tailings from Suncor Energy Inc. were analysed with respect to the mobility and solubility of the petroleum hydrocarbon (PHC) contaminants. At sites where oil sands tailings materials have been disposed of and are covered with a growing medium, the PHCs from the tailings may slowly migrate into the reclamation cover, increasing their availability to the plants in the cover system, which could be detrimental to the development and establishment of the plant cover system. This study characterized the PHC content of the tailings and quantified the desorption and diffusion coefficients for F2 and F3 fraction PHCs. All tailings materials collected from Suncor were characterized for initial PHC content. Desorption coefficients were experimentally determined using batch tests for 9 tailings materials (MFT, LG MFT, PT MFT, Tailings Sand, P4 UB Surface, P4 UB Auger, 2:1 CT, 4:1 CT and 6:1 CT). The experimental results from the batch tests were fitted to a Langmuir hyperbolic isotherm model. Diffusion coefficients were determined by fitting the experimental results from a radial diffusion 1-dimensional experiment to a Finite Difference Model. Diffusion coefficients for F2 and F3 Fraction PHCs were developed for 7 tailings materials (MFT, LG MFT, PT MFT, Tailings Sand, 2:1 CT, 4:1 CT and 6:1 CT). The diffusion coefficients (D*) and the Langmuir desorption constants ( and ) developed from these experiments are included in Table A.1. The desorption coefficients resulting from this study are similar to those reported for the desorption of asphaltene, which is one of the components in oil sands tailings. The Langmuir isotherm model was found to be the best fit for the experimental desorption data; the Langmuir isotherm model is commonly used in sorption isotherms of organic chemicals. The results of the radial diffusion experiments agree with diffusion rates found by other researchers in similar porous media. More research may be needed to verify both of these preliminary results for the desorptive and diffusive transport of F2 and F3 PHC fractions in tailings. Tailings composition will continue to change as new technologies for fines settling and bitumen extraction are developed. The diffusion of PHCs from these new materials will need to be examined as it is probable that these changes will affect the transport and mobility of the contaminants.

Hydrogeologists collect data through studies that originate from a diverse and growing set of instruments that measure, for example, geochemical constituents of surface and groundwater. Databases store and publish the collected data on the Web, and the volume of data is quickly increasing, which makes accessing data problematic and time consuming for individuals. One way to overcome this problem is to develop ontology to formally and explicitly represent the domain (e.g., contaminant hydrogeology) knowledge. Using OWL and RDF, contaminant hydrogeology ontology (CHO) is developed to manage hydrological spatial data for Georgia, USA. CHO is a conceptual computer model for the contaminant hydrogeology domain in which concepts (e.g. contaminant, aquifer) and their relationships (e.g. pollutes) are formerly and explicitly defined. Cyberinfrastructure for exposing CHO and datasets (i.e., CHKb) as Linked Data on the Web is developed. Cyberinfrastructure consists of storing, managing, querying, and visualizing CHKb that can be accessed from URL: cho.gsu.edu.