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APPENDIX K
UNCERTAINTIES ANALYSIS
K.1.0 INTRODUCTION

Uncertainty in risk analysis is a consequence of two factors: lack of data and natural variability (Figure K.1.0.1). The lack of data is reflected in the limited knowledge either about the value of constants, or about the statistical parameters (e.g., distribution shape, mean, variance) of things that are inherently variable (e.g., inhalation rates or body weights). Uncertainty due to the lack of data can be reduced in principle by more accurate measurements. Uncertainty due to natural variability cannot be reduced by improved measurement, but can be better estimated by acquiring data to characterize statistical distributions of measured variables and by using computer programs to simulate the effect of such variability in the components of equations on calculated values (e.g., risk estimates). These combined efforts can reduce systematic uncertainty in the Environmental Impact Statement (EIS) analyses and provide a more thorough understanding of the effects of the remaining uncertainty on the conclusions in the document.

The evaluation of systematic uncertainties is the most difficult aspect of determining the overall uncertainty of an analysis. A systematic error is the difference between the mean of an analysis and the true value. When true value is unknown, the systematic error only can be estimated. The estimated limit of the systematic error is called the systematic uncertainty of the analysis (Catland 1990). The systematic uncertainty is made up of multiple sources of systematic errors, each of which must be evaluated and quantified. When sources of systematic error are found and reduced, the systematic uncertainty is reduced.

Uncertainty in the conclusions of this EIS is a consequence of uncertainty in two major areas: the descriptions of the alternatives, with their associated assumptions about tank waste inventories, composition, and remediation technologies; and the consequences analyses, which include assumptions about waste source and release terms, future land uses, environmental transport parameters, and relationships between exposure and risk (Figure K.1.0.1). This appendix discusses the major sources of uncertainty in each of these areas. In addition, a less conservative (nominal) human health risk analysis is presented to illustrate the implications of relating some of the conservative assumptions made for the bounding case risk analyses in the EIS.

Section K.2 describes the uncertainties and assumptions in the alternative descriptions, including engineering, schedule, staffing, resources, and costs. Section K.3 discusses uncertainties and assumptions in the source terms and in the release terms for acute (accident) and chronic (routine) scenarios. Section K.4 describes the uncertainties and assumptions in estimating contaminant transport through soil, ground and surface water, and air. Sections K.5 and K.6 present the uncertainties and assumptions in the human health risk exposure assessment and risk characterization, respectively. Section 5.7 describes the results of a less conservative (nominal) human health risk analysis, focusing on the Ex Situ Intermediate Separations alternative as an example. Section K.7 describes the uncertainties in the ecological risk assessment (ERA) and their effects on the conclusions in the EIS.

Figure K.1.0.1 Sources and Types of Uncertainty in the TWRS EIS