Technical report 123

MULTIMEDIA MODELS TO DERIVE PEC USED FOR ERA OF IONISABLE ORGANICS

The main objective of an ERA is to provide an estimate regarding the potential for a chemical substance to cause an adverse effect following its release to the environment. The level of risk is measured by calculating the ratio of the PEC of a chemical to the PNEC. The emphasis of this report has focused on evaluating the parameters that will influence the PEC for ionisable organic compounds. The previous chapters highlighted potential concerns pertaining to tests and property estimation methods in relation to their applicability to ionisable organic compounds.

The PEC of a chemical substance is determined based on information about the emission rate of the chemical into the system in relation to a variety of removal processes, such as by sorption, volatilisation, and degradation, i.e. the PEC is based on calculating a mass balance for the model system, whereby the mass of the chemical in the system will be equivalent to the difference of the mass entering the system and the mass leaving the system. Whereas the emissions of a chemical into a system depend on how the chemical is used, the removal processes that influence the environmental fate of a chemical are largely influenced by how the physical-chemical properties of the chemical behave in the environment into which it has been emitted. Different regulatory jurisdictions utilise a variety of models to calculate PECs. In the EU, for instance, the TGD describes a set of methods and hypotheses that are to be used for the risk assessment of new and existing substances. The European Union System for the Evaluation of Substances (EUSES) represents a model framework within which several models may be used to derive information on the fate of chemicals, based on principles defined in the TGD. The modelling approach has been developed to represent a reasonable ‘worst-case’ risk assessment.

In a review of different modelling approaches used in the risk assessment of ‘down-the-drain’ chemicals, Keller (2006) effectively summarises how EUSES is utilised within a regulatory framework. EUSES includes three main modules that are used for projecting the PEC of a chemical substance, these include:

  1. Substance identification and chemical specific physical-chemical properties, specifically: Molecular weight, KOW, Water solubility, Boiling point and Melting point
  2. Release estimation, which is dependent on the use pattern and production volume of the chemical.
  3. Environmental distribution as defined based on output from various multimedia fugacity-based environmental fate models, such as SimpleTreat and SimpleBox.

Keller (2006) suggests that EUSES is an effective tool for ERA of chemicals in a generic environment, in that it can help decision-makers prioritise the environmental media in which the greatest potential for risk is most likely to occur. Chemicals with a ‘down-the-drain’ emission profile, however, are likely to result in the greatest risk to the aquatic environment, and therefore site-specific water quality models, such as GREAT-ER, may provide a more accurate projection of the PEC (Keller, 2006).

The main disadvantage of using a site-specific water quality model is that it does not typically include a multimedia component, and therefore may lead to an overestimation of the PEC in that it will not directly account for losses due to sorption. Whereas a multimedia fate model, such as the modules included within EUSES, have the capacity to account for sorption, they may not adequately project the behaviour of ionisable organic compounds, since they have been largely parameterised based on the fate and behaviour of neutral organic compounds.

Recently the European Medicines Agency has defined an approach to calculate PECs for APIs used for human use (EMEA, 2006). Similar to the EU TGD, the approach defined for the risk assessment of APIs also uses a ‘worst-case’ scenario assessment, based on a tiered-approach. Table 13 summarises the phased approach defined for APIs.

tab13

The Phase I estimate of the PEC starts with a ‘worst-case’ scenario for the aquatic environment, based on the dose, a default market penetration of 0.01 (1%) of the API, and amount of water per inhabitant per day and typical dilution factor: Specific market penetration supported by published epidemiology studies may be used at this point, if that information is available.

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In the Phase I pre-screening assessment, removal processes are not considered. Where the PEC value < 0.01 ìg/l it is assumed that the environmental risks associated with the use of the API are likely to be negligible, and no additional testing is required. Where the PEC value > 0.01 ìg/l a Phase II environmental fate and effect analysis should be performed. It is only during a Phase II risk assessment, however, where information regarding the removal of the API from a waste water treatment system, based on its physical-chemical properties, is considered along with more specific marketing information to better define the PEC. During this phase of the risk assessment output from the SimpleTreat model may be used to obtain the fraction of the API removed prior to being discharged to surface waters. Given the reliance of PEC estimates within the risk assessment framework on multimedia fate models, the issue regarding the applicability of models, such as SimpleTreat and SimpleBox, for ionisable organic compounds thus needs to be addressed.

Recently, there have been a number of studies that have attempted to improve the applicability domain of multimedia fate models to include ionisable organic compounds. Franco and Trapp (2010), for instance, have developed a multimedia fate model for ionisable organic compounds based on the use of chemical activities. The model includes pH and ionic strength dependence as well as species specific estimates of partition coefficients based on chemical specific pKa values, and estimates sorption behaviour based on both hydrophobic and electronic interactions (Franco and Trapp, 2010). Their “Multimedia Activity Model for Ionics” (MAMI) (Franco and Trapp, 2010) thus represents a promising framework for enhancing the applicability domain of multimedia fate models used for the ERA of ionisable organic compounds. This chapter explores how multimedia models based on the activity approach might be used to enhance the risk assessment of ionisable organic compounds.

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