Risk Characterization

Although the preceding analyses examine all relevant data to describe hazards, dose-response, or exposure, no conclusions are drawn about the overall risk. The final analysis addresses overall risk by examining the preceding analyses to characterize the risk. This process fully describes the expected risk through examining exposure predictions for real-world conditions, in light of the dose-response information from animals, people, and special test systems.

Risk is usually identified as a number. When the risk concern is cancer, the risk number represents the probability of additional cancer cases. For example, an estimate for pollutant X might be expressed as 1 X 10 or simply 10~6. This means one additional case of cancer projected in a population of one million people exposed to a certain level of Pollutant X over their lifetimes.

A numerical estimate is only as good as the data it is based on. Scientific uncertainty is a customary and expected factor in all environmental risk assessment. Measurement uncertainty refers to the usual variances accompanying scientific measurement, such as the range (10 ± 1). Sometimes the data gap exists because specific measurements or studies are missing. Sometimes the data gap is more broad, revealing a fundamental lack of understanding about a scientific phenomenon.

The 1983 paradigm and EPA risk assessment guidelines stress the importance of identifying uncertainties and presenting them as part of risk characterization.

The major sources of uncertainty are: (1) difficulty in estimating the amount of chemical exposure to an individual or group; (2) limited understanding of the mechanisms determining chemical absorption and distribution within the body; and (3) reliance on animal experiment data for estimating the effects of chemicals on human organs. All of these areas rely upon scientific judgments even though judgments may vary significantly among experts.

Despite differing views within the scientific community on certain issues, a process has emerged for dealing with these differences. Beginning with peer reviews of each scientific study, this process assures accurate data interpretation by qualified specialists. The next step involves an interdisciplinary review of studies relevant to the risk assessment, where differences of interpretation are fully aired. This structured peer-review process is the best means available to resolve differences among experts.

In summary, despite the limitations of risk assessment, quantifying the best estimate of risk is important in preventing harmful chemical exposure. However, understanding the limits of such estimates and indicating the degree of uncertainty is equally important for sound decision-making.

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