Matrix and media extrapolation

FIGURE 2.1 Schematic overview of the properties and processes that govern matrix and media extrapolations. 

An array of extrapolation types for matrix and media extrapolations has been given, with specihc approaches being dependent on compound, medium and matrix, and species and ecosystem properties. Guidance to provide a systematic orientation in the array of methods is useful when considering their practical use in a regulatory context. Using a tiered approach (see Chapter 1), the tiers for media and matrix extrapolation listed in Table 2.11 are recommended. 

Tiering is often applied in risk assessment in order to reduce expenditures in time, money, and labor when the assessment requires only simple and possibly conservative output. Table 5.3 provides a suggested tiered approach in mixture extrapolation and is further described in the bulleted list below. The tiering is based on the way that mixture mechanisms are addressed in the approach. It is assumed that issues such as matrix and media extrapolation have been addressed according to the methods described in the pertinent chapters. 

Three general levels of complexity are recognized in matrix and media extrapolation. The simplest approach assumes that all toxicants are completely available to be taken up by the biota. In this case, no extrapolation is required. The second level of complexity requires the calculation of bioavailable fractions of toxicants, whereas at the highest level of complexity the influence of physiological responses to toxicant uptake is considered. 

Can matrix and media extrapolation techniques be of help to address bioavailability differences among test media and the field ... 

Finally, the overall major tiers (0 to 4) can be identified according to the characteristics given below. Note that further subtiering, as indicated in Table 10.3, is possible from Tier-2 onward. For example, in matrix and media extrapolation, one may apply statistical modeling to derive transfer functions that describe the entry of substances in organisms as a function of matrix characteristics. These models can be simple so as to address gross problems, such as the function... 

In Table 10.3, the overview is organized according to the generalized tiers, and thereafter to the subjects of extrapolation, so that one can select conceptually consistent sets of extrapolation methods (e.g., for matrix and media extrapolation and mixture extrapolation). 

In Table 10.4, the same overview is presented however, it is now organized from the perspective of the subjects of extrapolation (e.g., matrix and media extrapolations), so that one can inspect the presence of extrapolation methods, at different tiers, for a given extrapolation problem. 

Do we have data pertinent to the matrix or medium in which exposure takes place, or do we need to consider matrix and media extrapolation If so, is there a trigger to consider this quantitatively important ... 

Answers to these questions provide preliminary insight into the variables for which extrapolation can be considered most urgent, due to an estimated numerical influence on the assessment results. For example, matrix and media extrapolation might be identified as the most important modifying factor, and the risk assessment might fully focus on this factor in the lowest tier. Information on issues for which no extrapolation will be applied need to be kept in the dossier, for reporting which factors have been considered and what numerical influence (magnitude and direction) is expected. 

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