Derivation of Eq

A hierarchy of data requirements, which is an efficient way to approach the derivation of EQSs, can be considered for application in the following methods ... 

For the derivation of EQSs (and similar benchmarks), experimental toxicity data are considered essential. However, for many substances there will be insufficient reliable toxicity data available to meet the prescribed minimum data requirements. In their absence (or to supplement an existing data set), several extrapolative methods may potentially be of assistance. Nevertheless, we recommend extreme caution when extrapolating from calculated values to predicted real toxicity data. Most suggested calculation methods to supplement missing toxicological data are considered unacceptable in EQS derivation. 

Substances that are carcinogenic, mutagenic, or reproductively toxic (i.e., CMRs), for example, some endocrine disrupters, may pose special problems for derivation of EQSs (e.g., lack of internationally agreed tests in some cases difficulties with prediction of safe concentrations), but use of special tests for these properties is only justified for a small subset of chemicals that meet clear criteria. Furthermore, EQSs for these substances should not be derived directly from in vitro data or from biomarkers of exposure but from in vivo tests alone. 

This chapter deals with the derivation of aquatic environmental quality standards (EQSs), including standards for the protection of water dwellers, predators of water dwellers, and human water users. However, the main focus is on standards for the protection of organisms that live in water or aquatic sediment and are able to absorb contaminants directly via their gills, skin, and/or cell surfaces. In other words, the chapter primarily covers the derivation of standards for the protection of aquatic ecosystems. 

Chronic toxicity data are preferred for deriving an annual average EQS (AA-EQS). Acute data are used to calculate a maximum acceptable concentration EQS (MAC-EQS) and can be used to derive the AA-EQS if insufficient chronic data are available, but an AA-EQS should not be derived exclusively on the basis of acute data. Guides to efficient decision making about the testing requirements for derivation of short- and long-term EQSs based on modes of action and other considerations were provided by Verhaar et al. (1992), de Wolf et al. (2005), and Hutchinson et al. (2006). 

A range of other data is often required when deriving aquatic EQS values, particularly when deriving AA-EQSs. Examples of the data required by the EU Water Framework Directive (WFD) are shown in Table 4.3. Most of these are also required under other jurisdictions. 

Reference ANZECC/ARMCANZ (2000) CCME (1999a) Lepper (2005) and environmental quality standards (EQSs) Substance data sheets for the EU priority substances (available at http //forum.europa.eu.int/ Public/irc/env/wfd/library l= /framework directive/i-priority substances/supporting background/ substance sheets vm= detailed sb= Title) Procedures for the Derivation of Equilibrium Partitioning Sediment Benchmarks (ESBs) for the Protection of Benthic Organisms. Consult http // www.epa.gov/nheerl/ publications/ for these procedures for PAH mixtures, dieldrin, endrin, and heavy metals. 

One can rank the reliability of EQSs according to the method of derivation, as shown in Table 4.9 for long-term EQSs. Ideally, proposed EQSs should be accompanied by an explicit assessment of their reliability. 

Bioavailability should be considered when assessing compliance of a water body with an EQS, rather than modifying the derivation of the EQS as discussed, unless the EQS is calculated or designed to be calculated on a site-specific basis. Increasingly in the United States, EQSs are being presented as equations or models to be used on a site-specific basis rather than as a national number to be applied broadly thus, bioavailability is addressed within the derivation of the value rather than at the time of compliance comparison. 

Long-term AA-EQSs are intended to protect against long-term continuous exposure, and MAC-EQSs are intended to protect against short-term episodic events. It should be noted that the use of acute toxicity data for deriving AA-EQSs is considered permissible by some jurisdictions, for example, when suitable chronic toxicity data are not available (e.g., CCME, 2007), although the use of chronic data for this purpose is always preferable. 

Mesocosm no-effect data on a rapidly dissipating compound such as a pyrethroid insecticide may not be suitable for a chronic EQS applied to a river. Furthermore, most existing micro- and mesocosm studies are inappropriate for EQS derivation if fish are the most sensitive species because fish have generally been excluded from such tests. There is consequently a need for evidence-based decision making for interpretation of nonstandard mesocosm studies. Microcosm and mesocosm tests can, however, be used directly for EQS derivation if algae, macrophytes, and invertebrates are appropriately represented in the test systems and if they concern substances subject to transient exposure. They are then directly applicable for the derivation of M AC-EQSs. For this purpose, the NOEAEC can be used as it represents the highest initial concentration that causes no ecologically relevant effects. 

Microcosms and mesocosms can also directly be used to derive AA-EQSs if the test substance concentration was relatively constant over time (due to stability of the test item or due to experimental manipulation) and the study duration was long enough to detect possible long-term effects (usually at least 8 weeks, but this will depend on the life cycle of sensitive taxa). These test systems are more difficult to... 

These tools may be useful in assessing consistency of EQSs between media, but as they are not validated for all substances, they can only be applied in limited circumstances at present. In principle, a tentative value for some chemicals in sediments might be derived from their water EQSs by such extrapolation methods, but they are not yet sufficiently validated for routine use when calculating definitive... 

There is no systematic bias in chemical sensitivity between freshwater and marine species, but use of freshwater data to support the derivation of marine EQSs should be conducted with caution on a case-by-case basis. Marine EQSs based on read-across with freshwater data should be regarded as tentative rather than definitive. Furthermore, the somewhat higher biodiversity in the marine ecosystem as a whole should not automatically result in the use of higher AFs when deriving marine EQSs. 

In addition, the DoE proposed EQSs in a 1991 consultation document for those pesticides on the Red List (the UK s original priority hazardous substances list). Although non-statutory, the Government is committed to the reduction of Red List Substances discharging to the North Sea and the NRA uses the standards to assess the effects of these substances on the environment and to derive consents for point source discharges of these compounds. Failures for agricultural pesticides are rare. 

DDT total comprises die sum of die isomers l,l,l-trichloro-2,2 bis(p-chlorophenyl)ethane (CAS number 50-29-3 EU number 200-024-3) l,l,l-trichloro-2 (o-chlorophenyl)-2-(p-chlorophenyl)ethane (CAS number 789-02-6 EU number 212-332-5) l,l-dichloro-2,2 bis(p-chlorophenyl)ethylene (CAS number 72-55-9 EU number 200-784-6) and 1,1-dichlo-ro-2,2 bis(p-chlorophenyl)ethane (CAS number 72-54-8 EU number 200-783-0). h If Member States do not apply EQSs for biota, they shall introduce stricter EQSs for water in order to achieve the same level of protection as the EQSs for biota set out in Article 3(2). They shall notify the Commission and other Member States, through die Committee referred to in Article 21 of Directive 2000/60/EC, of the reasons and basis for using this approach, the alternative EQSs for water established, including die data and die methodology by which they were derived and the categories of surface water to which they would apply. 

CCME 2002, available from http //www.ec.gc.ca/ceqg-rcqe/English/Pdf/GAAG Fluoride e.pdf). This may need to be followed up by the verification of unusual and potentially critical data through repeated testing. It is also essential that evidence-based decision making when deriving EQSs is fully recorded, transparent, and as consistent as possible from case to case. The draft EQS should then be subject to scientific expert peer review followed by public consultation. ... 

If data have already been generated for risk assessments, it may be possible to use these without further quality assessment (as is done in the European Union), but any new and relevant information should be considered scientifically. Usually, the lowest acute and long-term toxicity data for a species should be used (if the endpoint is relevant at the population level and is derived from a validated study). If valid data for the same endpoints and the same species exist, the geometric mean should be taken. This value is then used together with other species values to calculate the EQSs. Use of a mean value in this situation minimizes cumulative conservatism that is, always using the most conservative data point, especially when additional valid data are available, will lead to too much conservatism, giving rise to an EQS that may be unrealistically low. 

There has been a large increase in recent years in the application of SSDs in ecotoxi-cology, as evidenced by the recent SETAC (Society of Environmental Toxicology and Chemistry) book by Posthuma et al. (2002). This approach is being or will shortly be applied in the European Union, Australia, United States, and Canada, with a general movement (where possible) toward the use of ECx in preference to the historical use of AFs and NOECs in deterministic PNEC calculations. The toxicity endpoint used will depend on the objective. For deriving a MAC-EQS, LC(EC)50 data are appropriate, while chronic NOECs (or preferably chronic ECx values, where available) are applicable for AA-EQSs. 

Predictions of PNECs or EQSs based on mesocosm or microcosm chronic NOEC data, if available, are probably of greatest reliability, and such data can be used as a benchmark for comparison with other EQS derivation methods (see Section 4.7). 

There is no consensus about the minimum amount of data required for deriving EQSs, but the use of very small data sets (e.g., toxicity data on 1 alga, 1 crustacean, and 1 fish species) is likely to result in unreliable predicted no-effect concentrations (PNECs) from which EQS limit values... 

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