(632d) Reconciliation of Charge-Balance Discrepancies in Hanford High-Level Waste Supernatant Data

Physical models of Hanford nuclear waste behavior require charge-balanced chemical input data. Unfortunately, real laboratory data is not charge-balanced because of random analytical uncertainty, missing data, and other small errors or biases. Therefore, analytical data straight from the laboratory must be adjusted to force charge-balance prior to use in physical models. The way this data is adjusted, however, could impact the outcome of the physical model. This study evaluates a method to charge-balance Hanford waste supernatant data, and is applied to data from Hanford tank AW-101. This tank was selected because it has been sampled six times, yet has remained static, so all of the sample events are measuring the equivalent waste composition. The total charge-was within the analytical uncertainty for three of the six datasets, and when averaged across all six datasets. The three datasets with total charge-greater than the analytical uncertainty either had missing analytes or apparent gross errors. Gross errors were identified by comparing the charge contribution of each analyte from individual datasets to the average charge contribution across datasets. The results show that gross errors or missing analytes can be identified by individual charge-contributions that are larger than the analytical uncertainty. A method was developed to minimize the adjustments to the data to force charge-balance while ensuring the data stayed within the bounds of the analytical uncertainty.