Document ID: chunk:federal_register_of_legislation:F2013C00288:reg:2:p12
Version: federal_register_of_legislation:F2013C00288
Segment Type: reg
Provision Reference: reg 2 (pt 12/15)
Character Range: 1282782–1285751

or serves to fulfil the needs for micronutrients for the organisms in the environment' (Traas 2001). Therefore, the approach views only the effect of added contaminants to the environment as adverse. This approach is mostly relevant for ecological risk assessment (ERA) but less relevant for human risk assessment.

Evidence supporting the assumptions of the added risk approach has been provided by Posthuma (1997) and Crommentuijn et al. (2000b) and by work showing that the availability of metal salts decreases over time through aging processes (Posthuma 1997; Song et al. 2006). However, for microbial communities the background might be important regarding the development of tolerance to the metals (Díaz-Raviña & Bååth 1996; Bååth et al. 1998; Rutgers et al. 1998; McLaughlin & Smolders 2001; Rusk et al. 2004; Fait et al. 2006; Broos et al. 2007). Some of these studies found positive relationships between metal background concentration and effect concentrations, which could indicate that microbial communities in soils with relatively high background metals have evolved to be more tolerant to additional metal. Although these studies have shown that background concentration might not be completely inactive, adaptation of microbial communities does not lead to an underestimation of the ACL; rather, it is more likely to cause overprotection for microorganisms.

2.4.1         Collation and screening of data

2.4.1.1         Toxicity data collation
The first step in the methodology of deriving an EIL and/or SQG is to conduct a literature review and/or to search databases, such as the US EPA ECOTOX database (US EPA 2004), Australasian ecotoxicology database[5] (Warne et al. 1998; Warne & Westbury, 1999; Markich et al. 2002; Langdon et al. 2009) or the ECETOC database (ECETOC 1993), for available toxicity data for the contaminant in question. Unlike the situation in the derivation of HILs, it is not appropriate to have a hierarchy of data sources to be used in deriving EILs and/or SQGs. For most metals and well-known organic contaminants, toxicity data in addition to that found in the above databases will be available in the literature. Therefore, one should not rely solely on these databases.

For many organic contaminants there will be no toxicity data available. If there is no toxicity data available, models can be used to predict toxicity. These models include quantitative structureactivity relationships (QSARs) and quantitative activityactivity relationships (QAARs). The Australian and New Zealand WQGs (ANZECC and ARMCANZ 2000) used QSARs to derive trigger values (TVs) for narcotic organic contaminants (for example, ethanol for marine waters) when there was insufficient data. If QSARs or QAARs are not available, the equilibrium partitioning method (Van Gestel 1992; ECB 2003) can be used if toxicity data is available for aquatic species.

Figure 2. Schematic of the methodology for deriving ecological investigation levels