Risk Characterization

Risk characterization combines the exposure profiles with the exposure-response relationships to estimate ecological risks in ERA. A variety of methods and tools are available for risk estimation. For assessing risks posed by toxic chemicals, one simple method simply divides the exposure concentrations by the toxicity reference values (TRVs). A LOEC is an example of a TRV, as is an LC50 or EC50. Quotients equal to or greater than 1.0 imply risk; quotients less than 1.0 suggest minimal or no risk. Such quotients can prove useful in initial screening-level assessments to reduce the number of stressors that should be analyzed in greater detail. The screening assessments may be particularly effective if exposure estimates used in risk characterization are biased toward overestimating risk.

Depending on the availability of data, distributions of exposure and toxicity can be constructed and compared.

Risk can be estimated by statistically comparing the degree of overlap between these distributions: the greater the overlap, the higher the risk. Using comparisons of distributions in screening-level assessments can extend the single-value quotient approach by incorporating more information, including uncertainty, in the risk estimation.

Experiments under field conditions or more controlled conditions in the laboratory (e.g., microcosms, meso-cosms) can be used to characterize ecological risks. Experimental systems provide opportunities to physically impose the stressors of interest on the ecological resources of concern. Such experiments may be the only practical method for assessing risks posed by stressors not intended to be introduced into the environment. This approach may also prove essential in assessing risks posed by stressors that are virtually unknown or whose attributes are proprietary.

Mathematical and computer simulation models can be used to estimate ecological risks. Following decades of model construction in support of basic ecological research and development, it stands to reason that some of these models might prove useful in estimating ecological risks posed by various stressors on individual organisms, populations, communities, and ecosystems. To be useful in characterizing risk, the selected ecological model must include some representation of one or more of the assessment endpoints as a dependent variable. The model must also represent the stressor as an independent variable. The remaining critical aspect in selecting or adapting models for assessing risk is the ability to derive exposure-response relationships for the stressor(s) and ecological impacts of interest.

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