Carbon-14 degassing from surface waters: Experimental validation and numerical simulations using the film model

Abstract

This study aims to establish a comprehensive understanding of ¹⁴C degassing behavior in surface waters and to improve the accuracy of radiological safety assessments for disposal scenarios involving ¹⁴C-bearing waste. Although the RESRAD-ONSITE code is widely used for evaluating residual radioactivity and dose assessment, its current modeling framework neglects the degassing of ¹⁴C from surface water, resulting in conservatively high predictions of ¹⁴C concentration in surface water and subsequent ingestion doses. To address this limitation, a combined experimental and numerical framework was developed in this study. Laboratory-scale experiments were performed to quantify the rate of ¹⁴C degassing under various pH, temperature, and solution-depth conditions. The experiments revealed that ¹⁴C degassing is strongly governed by chemical speciation and boundary-layer diffusion, with lower pH and shallower water depth leading to faster degassing. The results were benchmarked against a COMSOL Multiphysics-based stagnant film model that considers both molecular diffusion and chemical equilibrium reactions within the aqueous boundary layer. The model reproduced the experimental trends with good agreement, validating its ability to simulate the dominant mechanisms controlling ¹⁴C transfer from water to air. Using the validated model, a series of simulations were conducted to quantify the degassing constant (k) across a wide range of environmental conditions, including pH (7-9), temperature (15-25 °C), water depth (1-20 m), and boundary-layer thickness derived from wind speed (3-10 m/s). The resulting dataset was fitted using an ordinary least squares (OLS) regression to develop a predictive equation for k, effectively capturing the nonlinear and interaction effects among variables such as pH–temperature. The regression model demonstrated high accuracy (R² > 0.99) and low error (RMSE < 0.05), confirming its suitability for practical applications. To evaluate its applicability, the regression-derived k values were integrated into the RESRAD-ONSITE code as a post-processing correction to account for time-dependent ¹⁴C degassing from surface water. Incorporating degassing resulted in a substantial reduction in both predicted ¹⁴C concentration in surface water and fish ingestion doses, thereby suggesting a more realistic and less conservative assessment of ¹⁴C exposure pathways. This study is expected to serve as a useful basis for improving the understanding of ¹⁴C transport and degassing behavior in surface waters and for supporting more reliable safety assessments of ¹⁴C waste disposal.