abstract: This dissertation critically evaluated methodologies and devices for assessing and protecting the health of human populations, with particular emphasis on groundwater remediation and the use of wastewater-based epidemiology (WBE) to inform population health. A meta-analysis and assessment of laboratory-scale treatability studies for removing chlorinated solvents from groundwater found that sediment microcosms operated as continuous-flow columns are preferable to batch bottles when seeking to emulate with high fidelity the complex conditions prevailing in the subsurface in contaminated aquifers (Chapter 2). Compared to monitoring at the field-scale, use of column microcosms also showed (i) improved chemical speciation, and (ii) qualitative predictability of field parameters (Chapter 3). Monitoring of glucocorticoid hormones in wastewater of a university campus showed (i) elevated stress levels particularly at the start of the semester, (ii) on weekdays relative to weekend days (p = 0.05) (161 ± 42 μg d-1 per person, 122 ± 54 μg d-1 per person; p ≤ 0.05), and (iii) a positive association between levels of stress hormones and nicotine (rs: 0.49) and caffeine (0.63) consumption in this student population (Chapter 4). Also, (i) alcohol consumption determined by WBE was in line with literature estimates for this young sub-population (11.3 ± 7.5 g d-1 per person vs. 10.1 ± 0.8 g d-1 per person), whereas caffeine and nicotine uses were below (114 ± 49 g d-1 per person, 178 ± 19 g d-1 per person; 627 ± 219 g d-1 per person, 927 ± 243 g d-1 per person). The introduction of a novel continuous in situ sampler to WBE brought noted benefits relative to traditional time-integrated sampling, including (i) a higher sample coverage (93% vs. 3%), (ii) an ability to captured short-term analyte pulses (e.g., heroin, fentanyl, norbuprenorphine, and methadone), and (iii) an overall higher mass capture for drugs of abuse like morphine, fentanyl, methamphetamine, amphetamine, and the opioid antagonist metabolite norbuprenorphine (p ≤ 0.01). Methods and devices developed in this work are poised to find applications in the remediation sector and in human health assessments. / Dissertation/Thesis / Doctoral Dissertation Civil, Environmental and Sustainable Engineering 2018

The hidden state Markov (HSM) model is introduced as a new conceptual framework for modelling long-term persistence in hydrological time series. Unlike the stochastic models currently used, the conceptual basis of the HSM model can be related to the physical processes that influence long-term hydrological time series in the Australian climatic regime. A Bayesian approach was used for model calibration. This enabled rigourous evaluation of parameter uncertainty, which proved crucial for the interpretation of the results. Applying the single site HSM model to rainfall data from selected Australian capital cities provided some revealing insights. In eastern Australia, where there is a significant influence from the tropical Pacific weather systems, the results showed a weak wet and medium dry state persistence was likely to exist. In southern Australia the results were inconclusive. However, they suggested a weak wet and strong dry persistence structure may exist, possibly due to the infrequent incursion of tropical weather systems in southern Australia. This led to the postulate that the tropical weather systems are the primary cause of two-state long-term persistence. The single and multi-site HSM model results for the Warragamba catchment rainfall data supported this hypothesis. A strong two-state persistence structure was likely to exist in the rainfall regime of this important water supply catchment. In contrast, the single and multi-site results for the Williams River catchment rainfall data were inconsistent. This illustrates further work is required to understand the application of the HSM model. Comparisons with the lag-one autoregressive [AR(1)] model showed that it was not able to reproduce the same long-term persistence as the HSM model. However, with record lengths typical of real data the difference between the two approaches was not statistically significant. Nevertheless, it was concluded that the HSM model provides a conceptually richer framework than the AR(1) model. / PhD Doctorate

<p>The Bayesian approach to cluster analysis is presented. We assume that all data stem from a finite mixture model, where each component corresponds to one cluster and is given by a multivariate normal distribution with unknown mean and variance. The method produces posterior distributions of all cluster parameters and proportions as well as associated cluster probabilities for all objects. We extend this method in several directions to some common but non-standard situations. The first extension covers the case with a few deviant observations not belonging to one of the normal clusters. An extra component/cluster is created for them, which has a larger variance or a different distribution, e.g. is uniform over the whole range. The second extension is clustering of longitudinal data. All units are clustered at all time points separately and the movements between time points are modeled by Markov transition matrices. This means that the clustering at one time point will be affected by what happens at the neighbouring time points. The third extension handles datasets with missing data, e.g. item non-response. We impute the missing values iteratively in an extra step of the Gibbs sampler estimation algorithm. The Bayesian inference of mixture models has many advantages over the classical approach. However, it is not without computational difficulties. A software package, written in Matlab for Bayesian inference of mixture models is introduced. The programs of the package handle the basic cases of clustering data that are assumed to arise from mixture models of multivariate normal distributions, as well as the non-standard situations.</p>

The aim of this thesis work has been to investigate how miniaturization, such as microsystems technology, can potentially increase the scientific throughput in exploration of hard-to-reach underwater environments, such as the subglacial lakes of Antarctica, or other challenging environments, including cave systems and wrecks. A number of instruments and subsystems applicable to miniature submersibles have been developed and studied, and their potential to provide a high functionality density for size-restricted exploration platforms has been assessed. To provide an onboard camera system with measurement capabilities, simulation and design tools for diffractive optics were developed, and microoptics realized to project reference patterns onto objects to reveal their topography. The influence of murky water on the measurement accuracy was also studied. For longer-range mapping of the surroundings, and under conditions with even less visibility, the performance of a very small, high-frequency side-scanning sonar was investigated using extensive modeling and physical testing. In particular, the interference on the acoustic beam from tight mounting in a hull was investigated. A range in excess of 30 m and centimeter resolution were obtained. Besides these systems, which can be used to navigate and map environments, a two-dimensional, thermal sensor for minute flows was developed. Measuring speed and direction of water flows, this sensor can aid in the general classification of the environment and also monitor the submersible’s movement. As the flow of waters in subglacial lakes is estimated to be minute, the detection limit and sensitivity were investigated. Measurements of water properties are facilitated by the chip-based conductivity, temperature, and depth sensor system developed. Macroscopically, this is an essential oceanographic instrument with which salinity is determined. Contrary to what was expected, MHz frequencies proved to be advantageous for conductivity measurements. Finally, sampling of water using an acoustically enriching microdevice, and even enabling return of pristine samples via the use of integrated latchable, high-pressure valves, was realized and evaluated. Particularly, investigations of the device’s ability to capture and hold on to microorganisms, were conducted. Further developed and studied, these devices – as subsystems to miniature submersibles, or as stand-alone instruments – should enable exploration of previously unreachable submerged environments. / Deeper Access, Deeper Understanding (DADU)

Calibration methods for quantitative on-site sampling using solid phase microextraction (SPME) were developed based on diffusion mass transfer theory. This was investigated using adsorptive polydimethylsiloxane/divinylbenzene (PDMS/DVB) and Carboxen/polydimethylsiloxane (CAR/PDMS) SPME fiber coatings with volatile aromatic hydrocarbons (BTEX: benzene, toluene, ethylbenzene, and o-xylene) as test analytes. Parameters that affected the extraction process (sampling time, analyte concentration, water velocity, and temperature) were investigated. Very short sampling times (10-300 s) and sorbents with a strong affinity and large capacity were used to ensure a 'zero sink' effect calibrate process. It was found that mass uptake of analyte changed linearly with concentration. Increase of water velocity increased mass uptake, though the increase is not linear. Temperature did not affect mass uptake significantly under typical field sampling conditions. To further describe rapid SPME analysis of aqueous samples, a new model translated from heat transfer to a circular cylinder in cross flow was used. An empirical correlation to this model was used to predict the mass transfer coefficient. Findings indicated that the predicted mass uptake compared well with experimental mass uptake. The new model also predicted rapid air sampling accurately. To further integrate the sampling and analysis processes, especially for on-site or <i>in-vivo</i> investigations where the composition of the sample matrix is very complicated and/or agitation of the sample matrix is variable or unknown, a new approach for calibration was developed. This involved the loading internal standards onto the extraction fiber prior to the extraction step. During sampling, the standard partially desorbs into the sample matrix and the rate at which this process occurs, was for calibration. The kinetics of the absorption/desorption was investigated, and the isotropy of the two processes was demonstrated, thus validating this approach for calibration. A modified SPME device was used as a passive sampler to determine the time-weighted average (TWA) concentration of volatile organic compounds (VOCs) in air. The sampler collects the VOCs by the mechanism of molecular diffusion and sorption on to a coated fiber as collection medium. This process was shown to be described by Fick's first law of diffusion, whereby the amount of analyte accumulated over time enable measurement of the TWA concentration to which the sampler was exposed. TWA passive sampling with a SPME device was shown to be almost independent of face velocity, and to be more tolerant of high and low analyte concentrations and long and short sampling times, because of the ease with which the diffusional path length could be changed. Environmental conditions (temperature, pressure, relative humidity, and ozone) had little or no effect on sampling rate. When the SPME device was tested in the field and the results compared with those from National Institute of Occupational Health and Safety (NIOSH) method 1501 good agreement was obtained. To facilitate the use of SPME for field sampling, a new field sampler was designed and tested. The sampler was versatile and user-friendly. The SPME fiber can be positioned precisely inside the needle for TWA sampling, or exposed completely outside the needle for rapid sampling. The needle is protected within a shield at all times hereby eliminating the risk of operator injury and fiber damage. A replaceable Teflon cap is used to seal the needle to preserve sample integrity. Factors that affect the preservation of sample integrity (sorbent efficiency, temperature, and sealing materials) were studied. The use of a highly efficient sorbent is recommended as the first choice for the preservation of sample integrity. Teflon was a good material for sealing the fiber needle, had little memory effect, and could be used repeatedly. To address adsorption of high boiling point compounds on fiber needles, several kinds of deactivated needles were evaluated. RSC-2 blue fiber needles were the more effective. A preliminary field sampling investigation demonstrated the validity of the new SPME device for field applications.

Calibration methods for quantitative on-site sampling using solid phase microextraction (SPME) were developed based on diffusion mass transfer theory. This was investigated using adsorptive polydimethylsiloxane/divinylbenzene (PDMS/DVB) and Carboxen/polydimethylsiloxane (CAR/PDMS) SPME fiber coatings with volatile aromatic hydrocarbons (BTEX: benzene, toluene, ethylbenzene, and o-xylene) as test analytes. Parameters that affected the extraction process (sampling time, analyte concentration, water velocity, and temperature) were investigated. Very short sampling times (10-300 s) and sorbents with a strong affinity and large capacity were used to ensure a 'zero sink' effect calibrate process. It was found that mass uptake of analyte changed linearly with concentration. Increase of water velocity increased mass uptake, though the increase is not linear. Temperature did not affect mass uptake significantly under typical field sampling conditions. To further describe rapid SPME analysis of aqueous samples, a new model translated from heat transfer to a circular cylinder in cross flow was used. An empirical correlation to this model was used to predict the mass transfer coefficient. Findings indicated that the predicted mass uptake compared well with experimental mass uptake. The new model also predicted rapid air sampling accurately. To further integrate the sampling and analysis processes, especially for on-site or <i>in-vivo</i> investigations where the composition of the sample matrix is very complicated and/or agitation of the sample matrix is variable or unknown, a new approach for calibration was developed. This involved the loading internal standards onto the extraction fiber prior to the extraction step. During sampling, the standard partially desorbs into the sample matrix and the rate at which this process occurs, was for calibration. The kinetics of the absorption/desorption was investigated, and the isotropy of the two processes was demonstrated, thus validating this approach for calibration. A modified SPME device was used as a passive sampler to determine the time-weighted average (TWA) concentration of volatile organic compounds (VOCs) in air. The sampler collects the VOCs by the mechanism of molecular diffusion and sorption on to a coated fiber as collection medium. This process was shown to be described by Fick's first law of diffusion, whereby the amount of analyte accumulated over time enable measurement of the TWA concentration to which the sampler was exposed. TWA passive sampling with a SPME device was shown to be almost independent of face velocity, and to be more tolerant of high and low analyte concentrations and long and short sampling times, because of the ease with which the diffusional path length could be changed. Environmental conditions (temperature, pressure, relative humidity, and ozone) had little or no effect on sampling rate. When the SPME device was tested in the field and the results compared with those from National Institute of Occupational Health and Safety (NIOSH) method 1501 good agreement was obtained. To facilitate the use of SPME for field sampling, a new field sampler was designed and tested. The sampler was versatile and user-friendly. The SPME fiber can be positioned precisely inside the needle for TWA sampling, or exposed completely outside the needle for rapid sampling. The needle is protected within a shield at all times hereby eliminating the risk of operator injury and fiber damage. A replaceable Teflon cap is used to seal the needle to preserve sample integrity. Factors that affect the preservation of sample integrity (sorbent efficiency, temperature, and sealing materials) were studied. The use of a highly efficient sorbent is recommended as the first choice for the preservation of sample integrity. Teflon was a good material for sealing the fiber needle, had little memory effect, and could be used repeatedly. To address adsorption of high boiling point compounds on fiber needles, several kinds of deactivated needles were evaluated. RSC-2 blue fiber needles were the more effective. A preliminary field sampling investigation demonstrated the validity of the new SPME device for field applications.

ABSTRACT MONITORING AND STATISTICAL MODELLING OF DUST CONCENTRATION OF SOME TURKISH LIGNITES UNDER LABORATORY CONDITIONS Karakas, Ahmet Ph.D., Department of Mining Engineering Supervisor: Prof. Dr. Tevfik G&uuml / yag&uuml / ler September 2010, 171 pages Although technological developments enable maximum safety, high dust formation is still a crucial problem in coal mining sector. This study is aimed to investigate the relationship between amount of coal dust produced during cutting operation and some important coal properties together with cutting parameters for different particle size ranges in laboratory conditions. For this purpose, six Turkish lignite samples were used in the experiments. Two experiment sets were designed to generate coal dust by using cutting action of the saw. First group of experiments were conducted in large scale saw system by using saws having three different diameters and dust concentration measurements were done for three group of particle size namely: 0-2.5 &mu / m, 0-5 &mu / m and 0-10 &mu / m. Second group of experiments were done in small scale saw system by changing the table advancing speed and tip speed of the system. For this group of experiments, only one type of lignite samples were used. These measurements were carried out only 0-10 &mu / m particle size range by using a saw with 30 cm in diamater. In this study, to characterize the lignite samples / proximate, petrographic and grindability analysis (HGI) were made. During the experiments, dust concentrations were measured by using Microdust Pro real time dust monitoring equipment. At the end of the study, the relationship between coal dust concentration and some coal properties and cutting operating parameters were expressed by using four different regression equations. Also it has been found that tip speed of saw, fixed carbon, ash and huminite content, vitrinite reflectance and hardgrove grindability index are very important parameters in coal dust generation. Keywords: Respirable Coal Dust, Dust Generation, Real Time Dust Sampler, Coal Dust Diseases, Coal Cutting Operation.

對於使用貝氏法來處理部份區分(partially-classified)或是失去部分訊息資料的類別抽樣(categorical sampling with censored data)，大多建立在「誠實回答」(truthful reporting)以及「無價值性失去部分訊息」(non-informative censoring)的前提下。Jiang(1995)及Jiang and Dickey(2006)取消以上兩個限制，提出貝氏解並利用準貝氏法(quasi-Bayes)來求近似解，而Jiang and Ko(2004)也利用吉氏取樣器(Gibbs sampler)來近似這類問題的貝氏解。本文首先嘗試利用Kuroda, Geng and Niki(2001)所提的“平均變異數和(average variance sum)”估計法 來應用到我們問題的貝氏解。在小樣本時，數值上我們可求得貝氏解，因此本文另一個重點為在小樣本時比較以上三種方法估計值的準確性，並考慮先驗參數(prior)的選取對估計的影響。 本文更進一步證明若選取到某種特殊的先驗參數時，利用“平均變異數和”的方法所計算出來的結果會和 準貝氏法的估計結果相同，而且皆等於用貝氏法計算出的結果。

Benzene is an important toxic chemical in urban air and known human carcinogen released substantially by mobile sources. It's important to understand the spatial variation of benzene concentrations in order to understand exposures of susceptible sub-populations such as children and minority groups. Current monitoring networks use large and expensive air samplers that require electricity and restrict the location and number of samplers, not allowing for fine spatial resolution data. The goals of this study are to develop and evaluate protocols for passive sampling and analysis of ambient benzene concentrations, and conduct a pilot study investigating small-scale variations over an area where children are likely to be exposed. Protocols were developed for the use and analysis of the Radiello RAD130 passive sampler for field sampling over the spatial scale of a city park adjacent to an elementary school. A pilot study was conducted from 4/27/11-5/4/11, where 11 samplers were exposed for a seven day sampling period at the park. After sampler exposure, benzene concentrations were determined through solvent desorption followed by analysis using a Varian gas chromatograph with mass spectrometer. Co-location with the existing regulatory active sampler in the county and of two samplers at the same site was done to evaluate the accuracy and precision of the methods, respectively. Health risk estimates were calculated using risk assessment guidance from the U.S. and California Environmental Protection Agencies. Concentrations over the park were found to range from 0.23 0.34 µg m^-3 with a coefficient of variation of 11%. A relative percent difference of 3% was found between the co-located sampler and the active sampler, and a 14% relative percent difference was found between the two duplicate samplers. The variation in health risk from concentration variation due to sampler placement contributed less to the overall uncertainty in the estimates than the uncertainty built in to the calculation parameters of inhalation unit risk and cancer potency factor, as estimated by the U.S. EPA and California EPA, respectively. These results suggest that the exposure of an individual at the park would be characterized sufficiently for standard health risk analysis through the use of one sampler. Further research is necessary into using passive samplers over both the same spatial scale in other areas, as well as on a larger scale to determine intra-urban benzene concentration distributions. The protocols developed here will be used in a future planned study of benzene concentration measurements to characterize neighborhood-scale exposures in Hillsborough County.

Perfect slice sampling is a method to turn Markov Chain Monte Carlo (MCMC) samplers into exact generators for independent random variates. The originally proposed method is rather slow and thus several improvements have been suggested. However, two of them are erroneous. In this article we give a short introduction to perfect slice sampling, point out incorrect methods, and give a new improved version of the original algorithm. (author's abstract) / Series: Preprint Series / Department of Applied Statistics and Data Processing