Thesis (Ph. D.)--Joint Program in Oceanography (Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences; and the Woods Hole Oceanographic Institution), 2005. / Includes bibliographical references (p. 131-149).

No description available.

Η εργασία αυτή αποσκοπεί στην προσπάθεια ανασύνθεσης του παλαιοπεριβάλλοντος της περιοχής της Αρχαίας Ελίκης μέσω της ιζηματολογικής ανάλυσης των δειγμάτων του πυρήνα της δειγματοληπτικής γεώτρησης που πραγματοποιήθηκε σε συγκεκριμένη θέση. / The purpose of this paper is to attempt to reconstruct the palaeoenvironment of the area of Ancient Helike through Sedimentological analysis of samples from the core sample drilling held in a specific position.

The distribution of a range of artificial radionuclides, derived from the authorised discharges of the Sellafield nuclear fuel reprocessing plant, have been determined in a core sampled from the intertidal sediments in the Esk Estuary. The plutonium-alpha activity profiles qualitatively resemble the Sellafield discharge histories for these isotopes, suggesting that the plutonium is largely immobile in the sediments. The beta-emitting 241Pu isotope activity profile was also determined for the sediments using the beta/alpha discriminator on a low-level liquid scintillation counter and qualitatively resembles the Sellafield discharge history. The 241Am activity profile represents the sum of americium both from Sellafield discharges and from the decay of its parent isotope 241Pu. The 244Cm activity profile was examined to see if its relationship to 241Am could be used as a marker of the Sellafield "discharge only" 241Am but this proved to be unsuitable. The 241Pu measurements were therefore used to calculate the amount of 241Am ingrowth and a deconvolved 241Am profile was estimated. The presence of the short-lived isotope 242Cm in the core can only be due to the precursor isotope, 242mAM, supporting its production. The first direct environmental sample measurements of the anthropogenic isotope of uranium, 236U, have been made using accelerator mass spectrometry. Coupled with 238U/235U atom ratios, and the known operational history of Sellafield, these data provide evidence that uranium has limited movement within the core. 237Np activity profiles in cores from west Cumbrian area are limited and the concentrations determined here are very similar to findings of other authors who have sampled close to this sampling site. The profile does not resemble the known Sellafield discharges suggesting that some redistribution of neptunium in the core is occurring. Finally, a quantitative model has been developed to examine the relationship between the Sellafield discharge histories and the sediment profiles, in terms of transport to the sampling site via an offshore mud patch which acts as a buffer. A prediction of the Sellafield discharge history for 236U, which is unknown, has been made, and the model has also been used to evaluate the potential mobility of the actinides that have been studied. A long-term prediction of the transfer of radionuclides to the intertidal sediments has also been made.

No description available.

This study was directed towards the development of rigorous, systematic, computer-assisted statistical procedures for the interpretation of quantitative and qualitative data commonly encountered in practical exploration-oriented surveys. A suite of data analysis tools were developed to evaluate the quality of geochemical data sets, to investigate the value and utilization of categorical field data, and to recognize and rank anomalous samples. Data obtained from regional stream sediment surveys as undertaken by the British Columbia Ministry of Energy, Mines and Petroleum Resources in southern British Columbia were examined as a case history. A procedure based on a statistical analysis of field-site duplicates was developed to evaluate the quality of regional geochemical silt data. The technique determines: (1) whether differences in metal concentrations between sample sites reflect a real trend related to geological and geochemical features and not merely a consequence of sampling and analytical error, and (2) absolute precision estimates at any particular accumulation across a metal's concentration range. Results for metals Zn, Cu, Ni, Co, Fe and Mn indicated that combined variability due to local and procedural error averaged less than 5% of the total error and that precision estimates at the 95th percentile concentration value averaged less than 6.0%. Results presented indicate duplicates are more in accord with splits of individual samples (analytical duplicates) rather than separate field-site duplicates. This type of systematic approach provides a basis for interpreting geochemical trends within the survey area, while simultaneously allowing evaluation of the method of sampling and laboratory analysis. A procedure utilizing Duncan's Multiple Range Test examined the relationships between metal concentrations and class-interval and categorical observations of the drainage catchment, sample site and sediment sample. Results show that, many field observations can be systematically related to metal content of drainage sediments. Some elements are more susceptible than others to environmental factors and some factors influence few or many elements. For example, in sediments derived from granites there are significant relationships between bank type and concentration of 8 elements (Zn, Cu, Ni, Pb, Co, Fe, Mn and Hg). In contrast, the texture of these sediments, using estimates of fines contents as an index, did not significantly affect the concentration of any of the elements studied. In general, results indicate that groups of environmental factors acting collectively are more important than any single factor in determining background metal contents of drainage sediments. A procedure utilizing both a graphical and multiple regression approach was developed to identify and characterize anomalous samples. The procedure determines multivariate models based on background metal values which are used to describe very general geochemical relations of no interest for prospecting purposes. These models are then applied to sample subsets selected on the basis of factor/s known to strongly influence geochemical results. Individual samples are characterized after comparisons with relevant determined threshold levels and background multielemenmodels. One hundred and fifteen anomalous samples for zinc from seven provenance groups draining 1259 sample sites were identified and characterized by this procedure. Forty three of these samples had zinc concentrations greater than its calculated provenance threshold, while 72 of these anomalous samples were identified solely because their individual metal associations were significantly different than their provenance multivariate background model. The method provides a means to reduce the effects of background variations while simultaneously identifying and characterizing anomalous samples. The data analysis tools described here allow extraction of useful information from regional geochemical data, and as a result provide and effective means of defining problems of geological interest that warrant further investigation. / Science, Faculty of / Earth, Ocean and Atmospheric Sciences, Department of / Graduate

Different sources of uncertainties have been inevitably induced into the environmental modeling due to different reasons such as the variability in the future climate state, incomplete knowledge and complexity of the nature system, and randomness in the system properties. These uncertainties make the model predictions inherently uncertain, and uncertainty becomes an important obstacle in environmental modeling. This dissertation presents a general framework for purpose of uncertainty quantification and it provides quantitative measures for relative importance of different uncertain factors to model outputs. The framework includes two parts: uncertainty analysis which implements variance decomposition technique to decompose and quantify different types of input uncertainty sources (i.e., scenario, model and parametric uncertainties); global sensitivity analysis which develops a new set of variance-based global sensitivity indices for measuring importance of model parameters with considering multiple future climate scenarios and plausible models. To demonstrate the usage and compatibility of the uncertainty quantification framework with different types of models, it was applied into two distinct cases: a synthetic groundwater reactive transport case and a barrier island morphological case. In the groundwater case, a Bayesian network integrated groundwater reactive transport model was built and studied for a synthetic case. Different uncertainty sources are described as uncertain nodes in the Bayesian network. All the nodes are characterized by multiple states, representing their uncertainty, in the form of continuous or discrete probability distributions that are propagated to the model endpoint, which is the spatial distribution of contaminant concentrations. In the barrier island case, a new Barrier Island Profile (BIP) model which simulates the barrier island cross-section morphological evolution was developed and studied. For a series of barrier island cross-sections derived from the characteristics of Santa Rosa Island, Florida, BIP was used to evaluate their responses to random storm events and five potential accelerated rates of sea-level rise projected over a century. Monte Carlo simulation is used to decompose and quantify the predictive uncertainties for uncertainty analysis of both cases. In the global sensitivity analysis, besides quasi-Monte Carlo simulation, sparse grid collocation method was also implemented to estimate the global sensitivity index to save the computational cost in the groundwater case. The study of BIP model demonstrates that BIP is capable of simulating realistic patterns of barrier island profile evolution over the span of a century using relatively simple representations of time- and space-averaged processes with consideration of uncertainty of future climate impacts. The results of uncertainty quantification for both cases demonstrate different types of model input uncertainty sources and the relative importance of model parameters can be quantified using the developed uncertainty quantification framework. And the global sensitivity indices may vary substantially between different models and scenarios. Not considering the model and scenario uncertainties, may result biased identification of important model parameters. The framework will be very useful for environmental modelers to prioritize different uncertainties and optimize expanse of limited resources to more efficiently decrease predictive uncertainty. Although only two applications are demonstrated, this uncertainty quantification framework is mathematically general and it can be applied to a wider range of hydrologic and environmental problems. / A Dissertation submitted to the Department of Scientific Computing in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Fall Semester, 2014. / November 5, 2014. / Barrier Island Modeling, Coastal Modeling, Groundwater Reactive Transport Modeling, Multiple Scenarios and Models, Sensitivity Analysis, Uncertainty Analysis / Includes bibliographical references. / Ming Ye, Professor Directing Dissertation; Anke Meyer-Baese, Committee Member; Tomasz Plewa, Committee Member; Dennis Slice, Committee Member.

Abstract Not Provided / Thesis / Bachelor of Science (BSc)

No description available.

No description available.