December 4, 2009 by Adam Peters

The Environment Agency recently published a report by Graham, Bruce Brown and me on the use of biotic ligand models to help implement environmental quality standards for copper and zinc under the Water Framework Directive (follow this link to download the report). The Biotic Ligand Model (BLM) is a predictive tool that allows site-specific estimates of aquatic toxicity to be made based on the concentration of metal and the prevailing water chemistry (such as its pH or the concentrations of specific dissolved ions or dissolved organic matter). In essence, it models a metal’s bioavailability. The WFD requires EU Member States to ensure that all inland and coastal waters achieve ‘good’ ecological status by 2015. A component of ecological status is chemical status. This goal will be realised through a range of measures, including the use of environmental quality standards (EQSs) for a number of chemicals.

By accounting for bioavailability when assessing metal compliance against an EQS, it is possible to provide the most ecologically relevant measure of metal risk. The consideration of bioavailability removes, or at least reduces, many of the current confounding issues related to the assessment of metal compliance, such as ambient background concentrations and forms of differing toxicity. A BLM relates a measured dissolved concentration of metal to its potential to cause toxicity under the prevailing water chemistry, which can then be used to derive a site-specific EQS for the purposes of compliance assessment. Unlike many other speciation-based approaches, the copper and zinc BLMs have been rigorously tested in both the laboratory and the field, and routinely predict ecological effects to aquatic organisms across a wide range of water chemistries to within a factor of two, an acceptable level of variability within routine ecotoxicity testing.

While scientifically robust, the input requirements of conventional BLMs can be extensive. One aim of this collaborative project was to develop and test a simplified, user-friendly, version of the copper BLM with the purpose of providing a rapid screening tool that could be incorporated into the Environment Agency’s monitoring and assessment systems. This model is not intended to replace the full BLM, but to deliver a method requiring quick, low resource input, high data throughput and rapid interpretation of monitoring data. This project effectively transforms BLMs from the preserve of researchers into practical and accessible tools for regulators and stakeholders.

Several hydrometric area and waterbody based scenarios are used to examine the implications of using the potential EQSs and BLMs when compared with existing standards. Default input parameters have also been used in these scenarios and their performance relative to the use of matched data is assessed. Consideration has been given to the use of water column ambient metal background concentrations within a compliance regime. The use of metal background concentrations and the BLMs within a simple tiered approach is also assessed, and a ‘road map’ is provided for embedding these approaches and tools within a regulatory framework.

The adoption of the BLMs would represent a ‘step change’ in working practice for the Environment Agency, and while many of the technical and practical challenges associated with their use have been addressed in this project, there remain some key decisions to be made. These decisions are generally aimed at policy makers, with science providing a number of options for consideration. Policy makers need to consider the following points:

  1. The added risk approach was originally adopted for performing generic, large scale risk assessments, but may not necessarily be appropriate for application to EQSs. A more suitable approach for the initial tiers of an assessment may be to include a small contribution from the ambient background concentration in the generic predicted no-effect concentration (PNEC), for example the 5th percentile of dissolved metal concentrations taken from monitoring from the hydrometric area.
  2. There is a widely held view, amongst regulators and the regulated, that the new EQSs developed using WFD methodology are overly precautionary and shrouded in uncertainty. However, the most significant scientific evidence for Cu and Zn does not necessarily support this view. The production of ecotoxicity data for Zn for a range of aquatic species (beyond fish) since the current national standards were set has resulted in lower, but less uncertain and, therefore, less precautionary PNECs. Furthermore, the development of Cu and Zn BLMs has enabled bioavailability modification to be taken into account in compliance assessment in a scientifically robust manner. An account of bioavailability offers considerably greater ecological relevance than the hardness-based corrections that are currently applied. Nevertheless, an assessment factor of 2 was applied to the HC5 (hazardous concentration for 5 per cent of the ecosystem) taken from the Zn ecotoxicity dataset to derive a PNEC for generic risk assessment purposes. It is appropriate to consider whether or not the PNEC derived through the risk assessment process is directly applicable as an EQS. Algae were considered to be the most sensitive species to Zn, although a recent UK study found benthic macroinvertebrates to be more sensitive than diatoms to the effects of minewaters. It is appropriate to consider a validation of the PNEC values against available field data.
  3. A detailed assessment of compliance against standards for both Cu and Zn set on the basis of these bioavailability-based systems is required. This assessment would also include a comparison with the current situation of Cu and Zn compliance with existing EQSs. Such an assessment should provide information for policy makers to assess the potential impacts of such changes appropriately. This exercise will also provide a view as to which stages of the process should be considered as compliance assessment, and which stages as programmes of measures under the WFD.