An evaluation of biotic ligand models predicting acute copper toxicity to Daphnia magna in wastewater effluent

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2010 SETAC.The toxicity of Cu to Daphnia magna was investigated in a series of 48-h immobilization assays in effluents from four wastewater treatment works. The assay results were compared with median effective concentration (EC50) forecasts produced by the HydroQual biotic ligand model (BLM), the refined D. magna BLM, and a modified BLM that was constructed by integrating the refined D. magna biotic ligand characterization with the Windermere humic aqueous model (WHAM) VI geochemical speciation model, which also accommodated additional effluent characteristics as model inputs. The results demonstrated that all the BLMs were capable of predicting toxicity by within a factor of two, and that the modified BLM produced the most accurate toxicity forecasts. The refined D. magna BLM offered the most robust assessment of toxicity in that it was not reliant on the inclusion of effluent characteristics or optimization of the dissolved organic carbon active fraction to produce forecasts that were accurate by within a factor of two. The results also suggested that the biotic ligand stability constant for Na may be a poor approximation of the mechanisms governing the influence of Na where concentrations exceed the range within which the biotic ligand stability constant value had been determined. These findings support the use of BLMs for the establishment of site-specific water quality standards in waters that contain a substantial amount of wastewater effluent, but reinforces the need for regulators to scrutinize the composition of models, their thermodynamic and biotic ligand parameters, and the limitations of those parameters.EPSRC and Severn Trent Water

Realizing live sequence charts in SystemVerilog.

The design of an embedded control system starts with an investigation of properties and behaviors of the process evolving within its environment, and an analysis of the requirement for its safety performance. In early stages, system requirements are often specified as scenarios of behavior using sequence charts for different use cases. This specification must be precise, intuitive and expressive enough to capture different aspects of embedded control systems. As a rather rich and useful extension to the classical message sequence charts, live sequence charts (LSC), which provide a rich collection of constructs for specifying both possible and mandatory behaviors, are very suitable for designing an embedded control system. However, it is not a trivial task to realize a high-level design model in executable program codes effectively and correctly. This paper tackles the challenging task by providing a mapping algorithm to automatically synthesize SystemVerilog programs from given LSC specifications

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

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)

The PKU &amp; ME study: A qualitative exploration, through co-creative sessions, of attitudes and experience of the disease among adults with phenylketonuria in Italy

Background: Phenylketonuria (PKU) is a hereditary metabolic disease that can be diagnosed and successfully treated from birth with a lifelong phenylalanine-restricted dietary regimen. However, optimal adherence to diet remains an issue and often progressively decreases after adolescence. The study aimed to explore the experience of adults living with PKU in order to gain insights related to their adherence to diet and engagement in managing their condition. Methods: The study adopted a qualitative methodology in sessions that combined specifically designed co- creation exercises with focus group discussion. Adults with early-treated classic PKU were enrolled for 2 different sessions - one for adherent and one for non-adherent patients. The verbatim notes of both sessions and focus group were analyzed using content analysis. Results: Twelve adherent and nine non-adherent adults with PKU participated. Besides the behavioral dictates of following a strict diet, adherent adults reported a positive mental approach and organizational rigor; they seemed aware of the consequences of high-phenylalanine levels, reporting that it can affect mood and conse- quently social interactions which they value highly. In the non-adherent group, the individuals seemed to not fully accept their disease: they were aware of the consequences of non-adherence in children but not in adults, they felt the management of PKU was an individual burden and they experienced a feeling of \u2018diversity\u2019 in the social context (related to eating) that caused emotional distress. PKU seemed a very influential element of the identity both for adherent and non-adherent adults, but with different consequences for the two groups. Finally, all participants reported the desire to be assisted in a healthcare setting dedicated to adults. Conclusions: The findings expand the understanding of the psychological experience of adult patients with PKU in relation to their disease and its dietary requirements, highlighting specific factors that might drive tailored educational or psychological intervention to improve adherence and engagement in the care process

Big issues for big data: challenges for critical spatial data analytics

In this paper we consider some of the issues of working with big data and big spatial data and highlight the need for an open and critical framework. We focus on a set of challenges underlying the collection and analysis of big data. In particular, we consider 1) inference when working with usually biased big data, challenging the assumed inferential superiority of data with observations, n, approaching N, the population n -> N. We also emphasise 2) the need for analyses that answer questions of practical significance or with greater emphasis on the size of the effect, rather than the truth or falsehood of a statistical statement; 3) the need to accept messiness in your data and to document all operations undertaken on the data because of this, in support of openness and reproducibility paradigms; and 4) the need to explicitly seek to understand the causes of bias, messiness etc in the data and the inferential consequences of using such data in analyses, by adopting critical approaches to spatial data science. In particular we consider the need to place individual data science studies in a wider social and economic contexts, along with the role of inferential theory in the presence of big data, and issues relating to messiness and complexity in big data

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

A Template for a New Generic Geographically Weighted R Package gwverse

GWR is a popular approach for investigating the spatial variation in relationships between response and predictor variables, and critically for investigating and understanding process spatial heterogeneity. The geographically weighted (GW) framework is increasingly used to accommodate different types of models and analyses, reflecting a wider desire to explore spatial variation in model parameters and outputs. However, the growth in the use of GWR and different GW models has only been partially supported by package development in both R and Python, the major coding environments for spatial analysis. The result is that refinements have been inconsistently included within GWR and GW functions in any given package. This paper outlines the structure of a new gwverse package, that may over time replace GW model, that takes advantage of recent developments in the composition of complex, integrated packages. It conceptualizes gwverse as having a modular structure, that separates core GW functionality and applications such as GWR. It adopts a function factory approach, in which bespoke functions are created and returned to the user based on user-defined parameters. The paper introduces two demonstrator modules that can be used to undertake GWR and identifies a number of key considerations and next steps. Volume54, Issue