This thesis is concerned with predicting the fate of contaminants using tracer and contaminant flushing datasets in otherwise poorly characterised heterogeneous media. A deductive approach towards constraining prediction uncertainty is adopted, by narrowing a 'pool' of plausible process models and associated parameter sets. Mathematical comparison of simple transport models is used to allow enhanced diagnosis. Transport models are put into a framework. Then they are compared using commonly used measures of breakthrough curves (least squares fitting, method of moments and late-time concentration gradients). Experimental data and models for transport in waste are then reviewed using this framework. Two new tracer datasets, at laboratory and lysimeter scales, are analysed and modelled. Strong evidence is shown of 'dual-porosity' diffusive exchange effects being an important component in transport in municipal solid waste. However, it is not possible to discriminate between contributions to dispersion through advective and diffusive effects. Approaches to enhance the diagnostic capability of future waste experiments are developed. One possible 'entrant' to the 'pool' of models is examined: a stochastic channel network model. Histograms of nodes and average heads are evaluated at different distances from a range of boundary conditions for large ensembles revealing key insights into network flow behaviour near different types of boundary. Key properties of the network are related to typical continuum analyses, including dimensionality of flow and genesis of apparent 'skins' near boundaries. 'Classical' percolation networks (with zero spatial correlation) are also analysed, revealing new insights into their network properties within finite boundaries. In summary, progress towards predicting the fate of contaminants in highly heterogeneous systems is made through a thorough delineation of the behaviour of simple models in tandem with adoption of a fertile approach to adding new conceptual models. The increased rigorousness of using multiple diagnostic criteria in conjunction with adopting a philosophy of working with multiple working hypotheses is commended as a methodology that provides a sound basis from which to employ multiple-model uncertainty analysis for predictive purposes in the future.

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This study was a joint project between the Environmental Engineering Group of the Department of Civil and Environmental Engineering - University College London and Anglian Water. The project was funded by an EPSRC CASE studentship (award No. 00800074) with Anglian Water. Cases of fuel oil contamination of groundwater are common throughout the world. The leakage of above and below-ground fuel storage tanks pose a significant threat to groundwater and in some cases potable water supply (PWS) boreholes. Although in-situ remediation methods are fundamental to a remediation strategy and can remove large amounts of hydrocarbon contamination, practical steps must sometimes be taken at PWS boreholes down- gradient of the contamination source to protect the supply. This study details the optimisation of a modular post-abstraction remediation system incorporating air-stripping and granular activated carbon (GAC) technologies. Emphasis throughout the experimental phase of the study is placed on methyl-tertiary-butyl-ether (MTBE) and benzene, toluene, ethylbenzene and xylene (BTEX) compounds. MTBE and BTEX compounds represent those most likely to reach the borehole after a contamination event, and also those which pose the greatest risk to human health. Stringent remedial targets were implemented, based upon world-wide drinking water standards. For benzene the remedial target was 1 ig/L and for MTBE the remedial target was 5pg/L. Utilising high performance stainless steel structured packing with air-to-water ratios ranging from 9 - 86, air-stripping removal efficiencies for MTBE ranged from 20 - 89%, whilst removal efficiencies for benzene ranged from 52 - 90%. The results of the study suggested that the removal efficiency of MTBE was dependent upon the air-to-water ratio, whilst the removal efficiency of benzene was independent of the air-to-water ratio. Utilising F400 GAC, the total adsorptive capacity for MTBE was 3.45 mg/g, whilst the adsorptive capacity for benzene was 2.72 mg/g. However, the general results suggested that benzene was adsorbed much more readily than MTBE. Utilising F600 GAC, the total adsorptive capacity for MTBE was 1.45 mg/g, whilst the adsorptive capacity for benzene was 1.96 mg/g.

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