Ecological Risk Assessment of Diffuse and Local Soil Contamination Using Species Sensitivity Distributions - Dealing with Contaminated Sites: From Theory Towards Practical Application - page 666

Regarding the limitations, we acknowledge that various issues in the use of
SSDs are conceptually “not solvable”. For example, whatever the refinement of an
approach, it is conceptually impossible to protect all of the unknown species in the
soil by any approach or model, because they are unknown (except for a no-emission
approach). No single approach can be imagined in which a sensible solution can be
provided to “the unknown”. Hence, all conceivable models and approaches are weak
when extrapolating from conventional laboratory data to untested contaminated
sites. This is not a weakness of SSDs, it is a universal weakness.
It is our opinion that SSDs are currently among the best risk-ranking methods that
can be practically applied at low cost to many practical Ecological Risk Assessment
problems . They primarily help to explore the risk problem in quantitative terms. In
particular, they can be applied in scenario analyses, such as estimating the relative
risks from predicted exposures under different Risk Management scenario's (e.g.,
Fig. 14.12 ). When one wants to be sure about impacts at sites already contaminated,
the experimental and Biomonitoring approaches as described by Rutgers and Jensen
( Chapter 15 of this topic) will be of use, to circumvent the key assumptions of SSDs.
However, such approaches are not useful before an event has happened (one cannot
test a field effect before a contamination event occurs, and thus cannot prevent dam-
age of a possible event in this way), as when one needs to decide on deposition of
slightly contaminated sediment on land (see Section 14.14.3 ).
The strengths and weaknesses of SSDs may be summarized as:

• SSDs are versatile; they have proven to be useful tools for practical soil appraisal

and protection policies and for the evaluation of existing contaminated sites;

• however, the SSD-approach is not a panacea for all ecological soil contamination

problems, as appropriate, higher-tier models and approaches should be applied;

• the strengths of SSDs are fundamentally related to the idea that one can rank

relative risks, amongst contaminants and amongst contaminated sites (different
PAFs ) ;

• when needed, the output of SSDs can be used as decision criteria (like a soil

quality standard);

• the output of SSD-based explorations can be used to design a next step (tier)

in Ecological Risk Assessment in a cost-effective way (e.g., focus testing on
the most likely impacted hot spots, or the contaminant with likely the highest
impact); and

•

for many practical problems, the versatility and the low costs of exploratory SSD
modeling may outweigh scientifically sound but more difficult and expensive
alternatives.

14.13 Practices of SSD Use

14.13.1 Practical Approaches in this Chapter

The examples in this chapter are all based on fitting a log-Normal distribution model
to the data, except when stated otherwise. The software used in the examples is ETX ,