Chemical and bioanalytical assessment of coal seam gas associated water

A comprehensive study was undertaken involving chemical (inorganic and organic) and bioanalytical (a suite of 14 in vitro bioassays) assessments of coal seam gas (coal bed methane) associated water (CSGW) in Queensland, Australia. CSGW is a by-product of the gas extraction process and is generally considered as water of poor quality. This was done to better understand what is known about the potential biological and environmental effects associated with the organic constituents of CSGW in Australia. In Queensland, large amounts of associated water must be withdrawn from coal seams to allow extraction of the gas. CSGW is disposed of via release to surface water, reinjected to groundwater or reused for irrigation of crops or pasture, supplied for power station cooling and or reinjected specifically to augment drinking water aquifers. Groundwater samples were collected from private wells tapping into the Walloon Coal Measures, the same coal aquifer exploited for coal seam gas production in the Surat Basin, Australia. The inorganic characteristics of these water samples were almost identical to the CSGW entering the nearby gas company operated Talinga-Condabri Water Treatment Facility. The water is brackish with a pH of 8 to 9, high sodium, bicarbonate and chloride concentrations but low calcium, magnesium and negligible sulphate concentrations. Only low levels of polyaromatic hydrocarbons (PAHs) were detected in the water samples, and neither phenols nor volatile organic compounds were found. Results from the bioassays showed no genotoxicity, protein damage, or activation of hormone receptors (with the exception of the estrogen receptor). However, five of the 14 bioassays gave positive responses: an arylhydrocarbon-receptor gene activation assay (AhR-CAFLUX), estrogenic endocrine activity (ERα-CALUX), oxidative stress response (AREc32), interference with cytokine production (THP1-CPA) and non-specific toxicity (Microtox). The observed effects were benchmarked against known water sources and were similar to secondary treated wastewater effluent, stormwater and surface water. As mixture toxicity modelling demonstrated, the detected PAHs explained less than 5% of the observed biological effects.

Particle emissions, volatility, and toxicity from an ethanol fumigated compression ignition engine

Particle emissions, volatility, and the concentration of reactive oxygen species (ROS) were investigated for a pre-Euro I compression ignition engine to study the potential health impacts of employing ethanol fumigation technology. Engine testing was performed in two separate experimental campaigns with most testing performed at intermediate speed with four different load settings and various ethanol substitutions. A scanning mobility particle sizer (SMPS) was used to determine particle size distributions, a volatilization tandem differential mobility analyzer (V-TDMA) was used to explore particle volatility, and a new profluorescent nitroxide probe, BPEAnit, was used to investigate the potential toxicity of particles. The greatest particulate mass reduction was achieved with ethanol fumigation at full load, which contributed to the formation of a nucleation mode. Ethanol fumigation increased the volatility of particles by coating the particles with organic material or by making extra organic material available as an external mixture. In addition, the particle-related ROS concentrations increased with ethanol fumigation and were associated with the formation of a nucleation mode. The smaller particles, the increased volatility, and the increase in potential particle toxicity with ethanol fumigation may provide a substantial barrier for the uptake of fumigation technology using ethanol as a supplementary fuel.

Probabilistic subgroup identification using Bayesian finite mixture modelling : a case study in Parkinson’s disease phenotype identification

This article explores the use of probabilistic classification, namely finite mixture modelling, for identification of complex disease phenotypes, given cross-sectional data. In particular, if focuses on posterior probabilities of subgroup membership, a standard output of finite mixture modelling, and how the quantification of uncertainty in these probabilities can lead to more detailed analyses. Using a Bayesian approach, we describe two practical uses of this uncertainty: (i) as a means of describing a person’s membership to a single or multiple latent subgroups and (ii) as a means of describing identified subgroups by patient-centred covariates not included in model estimation. These proposed uses are demonstrated on a case study in Parkinson’s disease (PD), where latent subgroups are identified using multiple symptoms from the Unified Parkinson’s Disease Rating Scale (UPDRS).

Optical and microscopic study of a polymer-nanotube mixture for organic photovoltaic applications

Organic solar cells based on bulk heterojunction between a conductive polymer and a carbon nanostructure offer potential advantages compared to conventional inorganic cells. Low cost, light weight, flexibility and high peak power per unit weight are all features that can be considered a reality for organic photovoltaics. Although polymer/carbon nanotubes solar cells have been proposed, only low power conversion efficiencies have been reached without addressing the mechanisms responsible for this poor performance. The purpose of this work is therefore to investigate the basic interaction between carbon nanotubes and poly(3-hexylthiophene) in order to demonstrate how this interaction affects the performance of photovoltaic devices. The outcomes of this study are the contributions made to the knowledge of the phenomena explaining the behaviour of electronic devices based on carbon nanotubes and poly(3-hexylthiophene). In this PhD, polymer thin films with the inclusion of uniformly distributed carbon nanotubes were deposited from solution and characterised. The bulk properties of the composites were studied with microscopy and spectroscopy techniques to provide evidence of higher degrees of polymer order when interacting with carbon nanotubes. Although bulk investigation techniques provided useful information about the interaction between the polymer and the nanotubes, clear evidence of the phenomena affecting the heterojunction formed between the two species was investigated at nanoscale. Identifying chirality-driven polymer assisted assembly on the carbon nanotube surface was one of the major achievements of this study. Moreover, the analysis of the electrical behaviour of the heterojunction between the polymer and the nanotube highlighted the charge transfer responsible for the low performance of photovoltaic devices. Polymer and carbon nanotube composite-based devices were fabricated and characterised in order to study their electronic properties. The carbon nanotube introduction in the polymer matrix evidenced a strong electrical conductivity enhancement but also a lower photoconductivity response. Moreover, the extension of pristine polymer device characterisation models to composites based devices evidenced the conduction mechanisms related to nanotubes. Finally, the introduction of carbon nanotubes in the polymer matrix was demonstrated to improve the pristine polymer solar cell performance and the spectral response even though the power conversion efficiency is still too low.

Removal of toxic metals in a multi metal system using sorbents for potential application to urban stormwater treatment

In the context of increasing demand for potable water and the depletion of water resources, stormwater is a logical alternative. However, stormwater contains pollutants, among which metals are of particular interest due to their toxicity and persistence in the environment. Hence, it is imperative to remove toxic metals in stormwater to the levels prescribed by drinking water guidelines for potable use. Consequently, various techniques have been proposed, among which sorption using low cost sorbents is economically viable and environmentally benign in comparison to other techniques. However, sorbents show affinity towards certain toxic metals, which results in poor removal of other toxic metals. It was hypothesised in this study that a mixture of sorbents that have different metal affinity patterns can be used for the efficient removal of a range of toxic metals commonly found in stormwater. The performance of six sorbents in the sorption of Al, Cr, Cu, Pb, Ni, Zn and Cd, which are the toxic metals commonly found in urban stormwater, was investigated to select suitable sorbents for creating the mixtures. For this purpose, a multi criteria analytical protocol was developed using the decision making methods: PROMETHEE (Preference Ranking Organisation METHod for Enrichment Evaluations) and GAIA (Graphical Analysis for Interactive Assistance). Zeolite and seaweed were selected for the creation of trial mixtures based on their metal affinity pattern and the performance on predetermined selection criteria. The metal sorption mechanisms employed by seaweed and zeolite were defined using kinetics, isotherm and thermodynamics parameters, which were determined using the batch sorption experiments. Additionally, the kinetics rate-limiting steps were identified using an innovative approach using GAIA and Spearman correlation techniques developed as part of the study, to overcome the limitation in conventional graphical methods in predicting the degree of contribution of each kinetics step in limiting the overall metal removal rate. The sorption kinetics of zeolite was found to be primarily limited by intraparticle diffusion followed by the sorption reaction steps, which were governed mainly by the hydrated ionic diameter of metals. The isotherm study indicated that the metal sorption mechanism of zeolite was primarily of a physical nature. The thermodynamics study confirmed that the energetically favourable nature of sorption increased in the order of Zn < Cu < Cd < Ni < Pb < Cr < Al, which is in agreement with metal sorption affinity of zeolite. Hence, sorption thermodynamics has an influence on the metal sorption affinity of zeolite. On the other hand, the primary kinetics rate-limiting step of seaweed was the sorption reaction process followed by intraparticle diffusion. The boundary layer diffusion was also found to limit the metal sorption kinetics at low concentration. According to the sorption isotherm study, Cd, Pb, Cr and Al were sorbed by seaweed via ion exchange, whilst sorption of Ni occurred via physisorption. Furthermore, ionic bonding is responsible for the sorption of Zn. The thermodynamics study confirmed that sorption by seaweed was energetically favourable in the order of Zn < Cu < Cd < Cr . Al < Pb < Ni. However, this did not agree with the affinity series derived for seaweed suggesting a limited influence of sorption thermodynamics on metal affinity for seaweed. The investigation of zeolite-seaweed mixtures indicated that mixing sorbents have an effect on the kinetics rates and the sorption affinity. Additionally, the theoretical relationships were derived to predict the boundary layer diffusion rate, intraparticle diffusion rate, the sorption reaction rate and the enthalpy of mixtures based on that of individual sorbents. In general, low coefficient of determination (R2) for the relationships between theoretical and experimental data indicated that the relationships were not statistically significant. This was attributed to the heterogeneity of the properties of sorbents. Nevertheless, in relative terms, the intraparticle diffusion rate, sorption reaction rate and enthalpy of sorption had higher R2 values than the boundary layer diffusion rate suggesting that there was some relationship between the former set of parameters of mixtures and that of sorbents. The mixture, which contained 80% of zeolite and 20% of seaweed, showed similar affinity for the sorption of Cu, Ni, Cd, Cr and Al, which was attributed to approximately similar sorption enthalpy of the metal ions. Therefore, it was concluded that the seaweed-zeolite mixture can be used to obtain the same affinity for various metals present in a multi metal system provided the metal ions have similar enthalpy during sorption by the mixture.

Dirichlet process mixture models for unsupervised clustering of symptoms in Parkinson's disease

In this paper, the goal of identifying disease subgroups based on differences in observed symptom profile is considered. Commonly referred to as phenotype identification, solutions to this task often involve the application of unsupervised clustering techniques. In this paper, we investigate the application of a Dirichlet Process mixture (DPM) model for this task. This model is defined by the placement of the Dirichlet Process (DP) on the unknown components of a mixture model, allowing for the expression of uncertainty about the partitioning of observed data into homogeneous subgroups. To exemplify this approach, an application to phenotype identification in Parkinson’s disease (PD) is considered, with symptom profiles collected using the Unified Parkinson’s Disease Rating Scale (UPDRS). Clustering, Dirichlet Process mixture, Parkinson’s disease, UPDRS.

Metal ion levels post unilateral primary Exeter total hip replacement

There has been much discussion and controversy in the media recently regarding metal toxicity following large head metal on metal (MoM) total hip replacement (THR). Patients have been reported as having hugely elevated levels of metal ions with, at times, devastating systemic, neurolgical and/or orthopaedic sequelae. However, no direct correlation between metal ion level and severity of metallosis has yet been defined. Normative levels of metal ions in well functioning, non Cobalt-Chrome hips have also not been defined to date. The Exeter total hip replacement contains no Cobalt-Chrome (Co-Cr) as it is made entirely from stainless steel. However, small levels of these metals may be present in the modular head of the prosthesis, and their effect on metal ion levels in the well functioning patient has not been investigated. We proposed to define the “normal” levels of metal ions detected by blood test in 20 well functioning patients at a minimum 1 year post primary Exeter total hip replacement, where the patient had had only one joint replaced. Presently, accepted normal levels of blood Chromium are 10–100 nmol/L and plasma Cobalt are 0–20 nmol/L. The UK Modern Humanities Research Association (MHRA) has suggested that levels of either Cobalt or Chromium above 7 ppb (equivalent to 135 nmol/L for Chromium and 120 nmol/L for Cobalt) may be significant. Below this level it is indicated that significant soft tissue reaction and tissue damage is less likely and the risk of implant failure is reduced. Hips were a mixture of cemented and hybrid procedures performed by two experienced orthopaedic consultants. Seventy percent were female, with a mixture of head sizes used. In our cohort, there were no cases where the blood Chromium levels were above the normal range, and in more than 70% of cases, levels were below recordable levels. There were also no cases of elevated plasma Cobalt levels, and in 35% of cases, levels were negligible. We conclude that the implantation with an Exeter total hip replacement does not lead to elevation of blood metal ion levels.