The cytotoxic effects of exposure to low concentrations of the herbicide, 2,4-dichlorophenoxyacetic acid (2,4-D) that are typically found in groundwater were investigated, in vitro. Most 2,4-D toxicology studies use high concentrations of the herbicide that are above those typically found in groundwater and measure overt biological endpoints. In contrast, this thesis examines the effects of low concentrations of 2,4-D and measures more subtle and sensitive endpoints such as gene expression and the generation of reactive oxygen species. This work derives from recent cDNA microarray analysis conducted in our laboratory that revealed significant alterations in the expression of 238 genes in cells exposed to nanomolar (nM) concentrations of a commercial formulation of 2,4-D. These findings are extended in this thesis to include the in vitro cytotoxic effects of low concentrations of both technical and commercial 2,4-D on two cell lines. Cells derived from liver (HepG2) and kidney (HEK293) respectively, were chosen, since liver and kidney are known to metabolize 2,4-D in vivo. Cell viability was measured using the Resazurin assay, reactive oxygen species (ROS) were measured with 2,7-dichlorofluorescin diacetate (2,7-DCFH-DA), and real timepolymerase chain reaction (RT-PCR) was used to assess changes in mRNA expression while protein expression was examined by Western blot.<p>Cell viability studies revealed that low environmental concentrations (0.1 to 100 nM) of 2,4-D induced small, but statistically significant decreases in cell viability. No concentration or time-dependent decreases in cell viability were observed in cells exposed to either forms of low environmental 2,4-D concentrations. HEK293 cells were more susceptible than HepG2 cells to the toxic effects of both forms of 2,4-D, having statistically significant lower viability at all exposure concentrations and durations. Both forms of 2,4-D reduced cell viability in both cell lines, suggesting that cytotoxicity was induced directly by 2,4-D, and not by the inert ingredients in the commercial formulation.<p>The ROS assays illustrated that 2,4-D induced statistically significant ROS production in HepG2 and HEK293 cell cultures at concentrations greater than 10 µM and 100 nM respectively. This was both a concentration and time-dependent effect in both cell lines. Although HEK293 cells were more susceptible to 2,4-D, they had 50 to 70% less ROS production than HepG2 cells, at all exposure concentrations and times.<p>The RT-PCR and Western blot analyses showed that exposure of HepG2 and HEK293 cells to low 2,4-D concentrations induced (< 2 fold) alterations in mRNA and protein levels of FTL, FTH1 and PCNA however these changes did not consistently vary with concentration.<p>Taken together, cell viability, ROS and gene expression studies show that low environmental 2,4-D concentrations induced subtle in vitro cytotoxic effects. However we have no evidence that these subtle changes pose a serious health threat to exposed humans.

The cytotoxic effects of exposure to low concentrations of the herbicide, 2,4-dichlorophenoxyacetic acid (2,4-D) that are typically found in groundwater were investigated, in vitro. Most 2,4-D toxicology studies use high concentrations of the herbicide that are above those typically found in groundwater and measure overt biological endpoints. In contrast, this thesis examines the effects of low concentrations of 2,4-D and measures more subtle and sensitive endpoints such as gene expression and the generation of reactive oxygen species. This work derives from recent cDNA microarray analysis conducted in our laboratory that revealed significant alterations in the expression of 238 genes in cells exposed to nanomolar (nM) concentrations of a commercial formulation of 2,4-D. These findings are extended in this thesis to include the in vitro cytotoxic effects of low concentrations of both technical and commercial 2,4-D on two cell lines. Cells derived from liver (HepG2) and kidney (HEK293) respectively, were chosen, since liver and kidney are known to metabolize 2,4-D in vivo. Cell viability was measured using the Resazurin assay, reactive oxygen species (ROS) were measured with 2,7-dichlorofluorescin diacetate (2,7-DCFH-DA), and real timepolymerase chain reaction (RT-PCR) was used to assess changes in mRNA expression while protein expression was examined by Western blot.<p>Cell viability studies revealed that low environmental concentrations (0.1 to 100 nM) of 2,4-D induced small, but statistically significant decreases in cell viability. No concentration or time-dependent decreases in cell viability were observed in cells exposed to either forms of low environmental 2,4-D concentrations. HEK293 cells were more susceptible than HepG2 cells to the toxic effects of both forms of 2,4-D, having statistically significant lower viability at all exposure concentrations and durations. Both forms of 2,4-D reduced cell viability in both cell lines, suggesting that cytotoxicity was induced directly by 2,4-D, and not by the inert ingredients in the commercial formulation.<p>The ROS assays illustrated that 2,4-D induced statistically significant ROS production in HepG2 and HEK293 cell cultures at concentrations greater than 10 µM and 100 nM respectively. This was both a concentration and time-dependent effect in both cell lines. Although HEK293 cells were more susceptible to 2,4-D, they had 50 to 70% less ROS production than HepG2 cells, at all exposure concentrations and times.<p>The RT-PCR and Western blot analyses showed that exposure of HepG2 and HEK293 cells to low 2,4-D concentrations induced (< 2 fold) alterations in mRNA and protein levels of FTL, FTH1 and PCNA however these changes did not consistently vary with concentration.<p>Taken together, cell viability, ROS and gene expression studies show that low environmental 2,4-D concentrations induced subtle in vitro cytotoxic effects. However we have no evidence that these subtle changes pose a serious health threat to exposed humans.

The presence of micropollutants, particularly pesticides, in surface waters across Canada has been of concern not only for their environmental impact, but also for their potential effects on human health and recalcitrant nature to conventional water treatment methods. Although ozone has been mainly applied for disinfection of drinking water, oxidation of trace organics by ozonation has been considered potentially effective. In an effort to meet increasingly stringent drinking water regulations, different solid catalysts have been used to enhance the removal of water contaminants by ozonation. In spite of the increasing number of data demonstrating the effectiveness of heterogeneous catalytic ozonation, the influence of different factors on the efficiency of micropollutants oxidation is still unclear.<p> In the present work, application of three solid catalysts in ozonation of two model micropollutants in pure water was examined using a laboratory-scale reaction system over a range of operating conditions. The three catalysts investigated were activated carbon, alumina, and perfluorooctyl alumina, and the two model micropollutants were the pesticides atrazine and 2,4-dichlorophenoxyactic acid. The effects of solution pH, presence of a radical scavenger, pesticide adsorption on catalyst, and catalyst dose on micropollutant removal were investigated. Solution pH was found to significantly influence the catalyst ability to decompose ozone into free hydroxyl radicals. The effect of these free radicals was markedly inhibited by the radical scavenger resulting in a negative impact on pesticides degradation. In general, the removal rate of pesticides was found to increase with increasing doses of catalyst.<p> In the ozonation process in the presence of activated carbon, atrazine removal rates increased four and two times when using a catalyst dose of 0.5 g L-1 at pH 3 and 7, respectively, whereas observed reaction rates for 2,4-D increased over 5 times in the presence of 1 × 10-4 M tert-butyl alcohol at pH 3. In the ozonation system catalyzed by 8 g L-1 alumina, the observed reaction rate constant of atrazine removal notably improved at neutral pH by doubling the micropollutant removal rate. For the pesticide 2,4-D in the presence of 1 × 10-4 M tert-butyl alcohol at pH 5, the observed removal rate was over ten times higher than that for the non-catalytic ozonation process using also using a catalyst dose of 8 g L-1. Modification of alumina to produce perfluorooctyl alumina resulted in a material able to significantly adsorb atrazine, while not exhibiting affinity for adsorption of 2,4-D. In spite of its adsorptive properties, perfluorooctyl alumina was found to enhance neither molecular ozone reactions nor ozone decomposition into hydroxyl radicals. Thus, the observed removal rates for atrazine and 2,4-D by ozonation in the presence of perfluorooctyl alumina did not increase significantly.

The presence of micropollutants, particularly pesticides, in surface waters across Canada has been of concern not only for their environmental impact, but also for their potential effects on human health and recalcitrant nature to conventional water treatment methods. Although ozone has been mainly applied for disinfection of drinking water, oxidation of trace organics by ozonation has been considered potentially effective. In an effort to meet increasingly stringent drinking water regulations, different solid catalysts have been used to enhance the removal of water contaminants by ozonation. In spite of the increasing number of data demonstrating the effectiveness of heterogeneous catalytic ozonation, the influence of different factors on the efficiency of micropollutants oxidation is still unclear.<p> In the present work, application of three solid catalysts in ozonation of two model micropollutants in pure water was examined using a laboratory-scale reaction system over a range of operating conditions. The three catalysts investigated were activated carbon, alumina, and perfluorooctyl alumina, and the two model micropollutants were the pesticides atrazine and 2,4-dichlorophenoxyactic acid. The effects of solution pH, presence of a radical scavenger, pesticide adsorption on catalyst, and catalyst dose on micropollutant removal were investigated. Solution pH was found to significantly influence the catalyst ability to decompose ozone into free hydroxyl radicals. The effect of these free radicals was markedly inhibited by the radical scavenger resulting in a negative impact on pesticides degradation. In general, the removal rate of pesticides was found to increase with increasing doses of catalyst.<p> In the ozonation process in the presence of activated carbon, atrazine removal rates increased four and two times when using a catalyst dose of 0.5 g L-1 at pH 3 and 7, respectively, whereas observed reaction rates for 2,4-D increased over 5 times in the presence of 1 × 10-4 M tert-butyl alcohol at pH 3. In the ozonation system catalyzed by 8 g L-1 alumina, the observed reaction rate constant of atrazine removal notably improved at neutral pH by doubling the micropollutant removal rate. For the pesticide 2,4-D in the presence of 1 × 10-4 M tert-butyl alcohol at pH 5, the observed removal rate was over ten times higher than that for the non-catalytic ozonation process using also using a catalyst dose of 8 g L-1. Modification of alumina to produce perfluorooctyl alumina resulted in a material able to significantly adsorb atrazine, while not exhibiting affinity for adsorption of 2,4-D. In spite of its adsorptive properties, perfluorooctyl alumina was found to enhance neither molecular ozone reactions nor ozone decomposition into hydroxyl radicals. Thus, the observed removal rates for atrazine and 2,4-D by ozonation in the presence of perfluorooctyl alumina did not increase significantly.

The teratogenic potential of commercial formulations of atrazine (40.8%) and 2,4-D was evaluated using FETAX (frog embryo teratogenic assay--Xenopus). Because these herbicides have been detected in ground and surface water, this study was designed to determine the adverse effects in buffer and natural water for both herbicides. All treatments showed a significant concentration-response effect on exposed embryos, except for the 2,4-D natural water sample. Atrazine (solubility of the commercial formula used 70 mg/L at 20 degrees C), compared to 2,4-D (solubility = 311 mg/L at pH = 1 and 25 degrees C), had a significantly greater teratogenic effect in both the buffer (atrazine EC50 = 33 mg/L, LC50 = 100 mg/L, TI = 3.03; 2,4-D EC50 = 245 mg/L, LC50 = 254 mg/L, TI = 1.04) and natural water samples (atrazine EC50 < 8 mg/L, LC50 = 126 mg/L; 2,4-D EC50 and LC50 > 270 mg/L). The 2,4-D EC50 and LC50 values for the buffer were similar at 245 mg/L and 254 mg/L. These similar values and the teratogenic index (TI) of 1.04 suggested that 2,4-D was more embryotoxic than teratogenic to frog embryos at high concentrations. Atrazine in natural water demonstrated a significantly greater EC50 (100% abnormality at 8 mg/L, the lowest test concentration) to frog embryos than the buffer experiment (EC50 = 33 mg/L). The extrapolated lowest observable adverse effect concentration (LOAEC) for the natural water experiment was 1.1 mg/L. These results suggest that atrazine toxicity is enhanced by the synergistic or additive effects of some component of the water or atrazine was already present in the sample. In contrast to atrazine, 2,4-D was less toxic in natural water than buffer. These results suggest that both atrazine and 2,4-D pose little threat, since their embryotoxicity and teratogenicity to frog embryos occur at high concentrations approaching their maximum solubility levels in water.

Uncertainty is pervasive in risk assessment. In ecotoxicological risk assessments, it arises from such sources as a lack of data, the simplification and abstraction of complex situations, and ambiguities in assessment endpoints (Burgman 2005; Suter 1993). When evaluating and managing risks, uncertainty needs to be explicitly considered in order to avoid erroneous decisions and to be able to make statements about the confidence that we can place in risk estimates. Although informative, previous approaches to dealing with uncertainty in ecotoxicological modelling have been found to be limited, inconsistent and often based on assumptions that may be false (Ferson & Ginzburg 1996; Suter 1998; Suter et al. 2002; van der Hoeven 2004; van Straalen 2002a; Verdonck et al. 2003a). In this thesis a Generalised Linear Modelling approach is proposed as an alternative, congruous framework for the analysis and prediction of a wide range of ecotoxicological effects. This approach was used to investigate the results of toxicity experiments on the effect of 2,4-Dichlorophenoxyacetic Acid (2,4-D) formulations and 4-Chlorophenol (4-CP, an associated breakdown product) on Daphnia carinata. Differences between frequentist Maximum Likelihood (ML) and Bayesian Markov-Chain Monte-Carlo (MCMC) approaches to statistical reasoning and model estimation were also investigated. These approaches are inferentially disparate and place different emphasis on aleatory and epistemic uncertainty (O'Hagan 2004). Bayesian MCMC and Probability Bounds Analysis methods for propagating uncertainty in risk models are also compared for the first time. For simple models, Bayesian and frequentist approaches to Generalised Linear Model (GLM) estimation were found to produce very similar results when non-informative prior distributions were used for the Bayesian models. Potency estimates and regression parameters were found to be similar for identical models, signifying that Bayesian MCMC techniques are at least a suitable and objective replacement for frequentist ML for the analysis of exposureresponse data. Applications of these techniques demonstrated that Amicide formulations of 2,4-D are more toxic to Daphnia than their unformulated, Technical Acid parent. Different results were obtained from Bayesian MCMC and ML methods when more complex models and data structures were considered. In the analysis of 4-CP toxicity, the treatment of 2 different factors as fixed or random in standard and Mixed-Effect models was found to affect variance estimates to the degree that different conclusions would be drawn from the same model, fit to the same data. Associated discrepancies in the treatment of overdispersion between ML and Bayesian MCMC analyses were also found to affect results. Bayesian MCMC techniques were found to be superior to the ML ones employed for the analysis of complex models because they enabled the correct formulation of hierarchical (nested) datastructures within a binomial logistic GLM. Application of these techniques to the analysis of results from 4-CP toxicity testing on two strains of Daphnia carinata found that between-experiment variability was greater than that within-experiments or between-strains. Perhaps surprisingly, this indicated that long-term laboratory culture had not significantly affected the sensitivity of one strain when compared to cultures of another strain that had recently been established from field populations. The results from this analysis highlighted the need for repetition of experiments, proper model formulation in complex analyses and careful consideration of the effects of pooling data on characterising variability and uncertainty. The GLM framework was used to develop three dimensional surface models of the effects of different length pulse exposures, and subsequent delayed toxicity, of 4-CP on Daphnia. These models described the relationship between exposure duration and intensity (concentration) on toxicity, and were constructed for both pulse and delayed effects. Statistical analysis of these models found that significant delayed effects occurred following the full range of pulse exposure durations, and that both exposure duration and intensity interacted significantly and concurrently with the delayed effect. These results indicated that failure to consider delayed toxicity could lead to significant underestimation of the effects of pulse exposure, and therefore increase uncertainty in risk assessments. A number of new approaches to modelling ecotoxicological risk and to propagating uncertainty were also developed and applied in this thesis. In the first of these, a method for describing and propagating uncertainty in conventional Species Sensitivity Distribution (SSD) models was described. This utilised Probability Bounds Analysis to construct a nonparametric 'probability box' on an SSD based on EC05 estimates and their confidence intervals. Predictions from this uncertain SSD and the confidence interval extrapolation methods described by Aldenberg and colleagues (2000; 2002a) were compared. It was found that the extrapolation techniques underestimated the width of uncertainty (confidence) intervals by 63% and the upper bound by 65%, when compared to the Probability Bounds (P3 Bounds) approach, which was based on actual confidence estimates derived from the original data. An alternative approach to formulating ecotoxicological risk modelling was also proposed and was based on a Binomial GLM. In this formulation, the model is first fit to the available data in order to derive mean and uncertainty estimates for the parameters. This 'uncertain' GLM model is then used to predict the risk of effect from possible or observed exposure distributions. This risk is described as a whole distribution, with a central tendency and uncertainty bounds derived from the original data and the exposure distribution (if this is also 'uncertain'). Bayesian and P-Bounds approaches to propagating uncertainty in this model were compared using an example of the risk of exposure to a hypothetical (uncertain) distribution of 4-CP for the two Daphnia strains studied. This comparison found that the Bayesian and P-Bounds approaches produced very similar mean and uncertainty estimates, with the P-bounds intervals always being wider than the Bayesian ones. This difference is due to the different methods for dealing with dependencies between model parameters by the two approaches, and is confirmation that the P-bounds approach is better suited to situations where data and knowledge are scarce. The advantages of the Bayesian risk assessment and uncertainty propagation method developed are that it allows calculation of the likelihood of any effect occurring, not just the (probability)bounds, and that the same software (WinBugs) and model construction may be used to fit regression models and predict risks simultaneously. The GLM risk modelling approaches developed here are able to explain a wide range of response shapes (including hormesis) and underlying (non-normal) distributions, and do not involve expression of the exposure-response as a probability distribution, hence solving a number of problems found with previous formulations of ecotoxicological risk. The approaches developed can also be easily extended to describe communities, include modifying factors, mixed-effects, population growth, carrying capacity and a range of other variables of interest in ecotoxicological risk assessments. While the lack of data on the toxicological effects of chemicals is the most significant source of uncertainty in ecotoxicological risk assessments today, methods such as those described here can assist by quantifying that uncertainty so that it can be communicated to stakeholders and decision makers. As new information becomes available, these techniques can be used to develop more complex models that will help to bridge the gap between the bioassay and the ecosystem.