The effect of wastewater effluent derived ligands on copper and zinc complexation.

The shift toward bioavailability-based standards for metals such as copper and zinc not only improves the ecological relevance of the standard but also introduces significant complexity into assessing compliance. This study examined differences in the copper and zinc complexation characteristics of effluents from a range of different sewage treatment works and in relation to so-called 'natural' samples. This information is essential to determine whether the inclusion of effluent-specific complexation characteristics within the regulatory framework could enhance the environmental relevance of compliance criteria. The data show that for copper, binding affinity was not greater than that measured for materials derived from the receiving water environment, with a mean log K of between 4.4 and 5.15 and mean complexation capacity ranging from 38 to 120 μg/mg dissolved organic carbon (DOC) for effluents compared with a log K of 5.6 and complexation capacity of 37 μg/mg DOC for the Suwannee River fulvic acid. For zinc, however, effluents exhibited a much higher complexation capacity, with effluent means ranging from 3 to 23 μg/mg DOC compared with the Suwannee River fulvic acid, for which the complexation capacity could not be determined. Synthetic ligands in sewage effluent, such as ethylenediaminetetraacetic acid (EDTA), are implicated as contributing to these observed differences. This suggests that the current biotic ligand models for zinc might overstate the risk of harm in effluent-impacted waters. The data also show that the copper and zinc complexation characteristics of effluent samples obtained from the same sewage treatment works were less different from one another than those of effluents from other treatment works and therefore that sewage source has an important influence on complexation characteristics. The findings from this study support the case that the contribution to complexation from effluent-derived ligands could enhance the environmental relevance of bioavailability-based compliance criteria, in particular for zinc, owing to the additional complexation capacity afforded by effluent-derived ligands

Parameterization of pharmaceutical emissions and removal rates for use in UK predictive exposure models: steroid estrogens as a case study.

Newly available prescription data has been used along with census data to develop a localised method for predicting pharmaceutical concentrations in sewage influent and effluent for England, and applied to a case study: the steroid estrogens estrone, 17β-estradiol, and 17α-ethinylestradiol in a selected catchment. The prescription data allows calculation of the mass consumed of synthetic estrogens, while use of highly localised census data improves predictions of naturally excreted estrogens by accounting for regional variations in population demographics. This serves two key purposes; to increase the accuracy of predictions in general, and to call attention to the need for more accurate predictions at a localised and/or catchment level, especially in light of newly proposed regulatory measures which may in the future require removal of steroid estrogens by sewage treatment facilities. In addition, the general lack of measured sewage works data necessitated the development of a novel approach which allowed comparison of localised predictions to average national measurements of influent and effluent. Overall in the case study catchment, estrogen predictions obtained using the model described herein were within 95% confidence intervals of measured values drawn from across the UK, with large improvements to predictions of EE2 being made compared with previous predictive methods

Predicting copper speciation in estuarine waters – Is dissolved organic carbon a good proxy for the presence of organic ligands?

A new generation of speciation-based aquatic environmental quality standards (EQS) for metals have been developed using models to predict the free metal ion concentration, the most ecologically relevant form, to set site-specific values. Some countries such as the U.K. have moved toward this approach by setting a new estuarine and marine water EQS for copper, based on an empirical relationship between copper toxicity to mussels (<i>Mytilus</i> sp.) and ambient dissolved organic carbon (DOC) concentrations. This assumes an inverse relationship between DOC and free copper ion concentration owing to complexation by predominantly organic ligands. At low DOC concentrations, the new EQS is more stringent, but above 162 μM DOC it is higher than the previous value. However, the relationship between DOC and copper speciation is poorly defined in estuarine waters. This research discusses the influence of DOC from different sources on copper speciation in estuaries and concludes that DOC is not necessarily an accurate predictor of copper speciation. Nevertheless, the determination of ligand strength and concentrations by Competitive Ligand Exchange Adsorptive Cathodic Stripping Voltammetry enabled the prediction of the free metal ion concentration within an order of magnitude for estuarine waters by using a readily available metal speciation model (Visual MINTEQ)

Development of a chemical source apportionment decision support framework for catchment management.

EU legislation, including the Water Framework Directive, has led to the application of increasingly stringent quality standards for a wide range of chemical contaminants in surface waters. This has raised the question of how to determine and to quantify the sources of such substances so that measures can be taken to address breaches of these quality standards using the polluter pays principle. Contaminants enter surface waters via a number of diffuse and point sources. Decision support tools are required to assess the relative magnitudes of these sources and to estimate the impacts of any programmes of measures. This work describes the development and testing of a modeling framework, the Source Apportionment Geographical Information System (SAGIS). The model uses readily available national data sets to estimate contributions of a number of nutrients (nitrogen and phosphorus), metals (copper, zinc, cadmium, lead, mercury, and nickel) and organic chemicals (a phthalate and a number of polynuclear aromatic hydrocarbons) from multiple sector sources. Such a tool has not previously been available on a national scale for such a wide range of chemicals. It is intended to provide a common platform to assist stakeholders in future catchment management

Modelling scenarios of environmental recovery after implementation of controls on emissions of persistent organic pollutants

Predictions of BaP concentrations in biota decreasing towards the EQS over time.</p

Determination and prediction of zinc speciation in estuaries

Lowering of the estuarine Environmental Quality Standard for zinc in the UK to 121 nM reflects rising concern regarding zinc in ecosystems and is driving the need to better understand its fate and behaviour and to develop and parameterise speciation models to predict the metal species present. For the first time, an extensive dataset has been gathered for the speciation of zinc within an estuarine system with supporting physico-chemical characterisation, in particular dissolved organic carbon. WHAM/Model VII and Visual MINTEQ speciation models were used to simulate zinc speciation, using a combination of measured complexation variables and available defaults. Data for the five estuarine transects from freshwater to seawater endmembers showed very variable patterns of zinc speciation depending on river flows, seasons, and potential variations in metal and ligand inputs from in situ and ex situ sources. There were no clear relationships between free zinc ion concentration [Zn2+] and measured variables such as DOC concentration, humic and biological indices. Simulations of [Zn2+] carried out with both models at high salinities or by inputting site specific complexation capacities were successful, but overestimated [Zn2+] in low salinity waters, probably owing to an underestimation of the complexation strength of the ligands present. Uncertainties in predicted [Zn2+] are consistently smaller than standard deviations of the measured values, suggesting that the accuracy of the measurements is more critical than model uncertainty in evaluating the predictions