Validating riverine transport and speciation models using nuclear reactor-derived radiocobalt

Chlorine Reduction Kinetics and its Mass Balance in Copper Premise Plumbing Systems During Corrosion Events

Hypochlorous acid has been reported as the main oxidant agent responsible for the corrosion of copper plumbing systems in chlorinated water supplies. However, there is little information about chlorine consumption kinetics in a combined system (i.e., with dissolved oxygen (DO) and free chlorine), as well as its complete mass balance within a copper pipe during stagnation. The results of our experiments using copper pipes filled with synthetic drinking water, with a moderate alkalinity (pH = 7.2; dissolved inorganic carbon = 80 mg as CaCO₃ /L), and tested under chlorine concentrations from 0 to 8 mg/L, show that chlorine depletion is associated with pipe wall reactions (i.e., copper oxidation and scale formation processes). Free chlorine was depleted after 4 h of stagnation and its kinetic constant depend on the initial concentration, probably due to diffusion processes. Surface analysis including scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS) and total reflection X-ray fluorescence (T-XRF) suggest chlorine precipitation, probably as CuCl. The obtained kinetics of chlorine and DO reduction would be critical for modeling and prediction of corrosion events of copper premise plumbing systems. In addition, our results indicate that the pipe's surface reactions due to corrosion induces a loss of free chlorine in the bulk water, decreasing chlorine added for disinfection and the subsequent effect on water quality.

Probabilistic distribution coefficients (K(d)s) in freshwater for radioisotopes of Ag, Am, Ba, Be, Ce, Co, Cs, I, Mn, Pu, Ra, Ru, Sb, Sr and Th: implications for uncertainty analysis of models simulating the transport of radionuclides in rivers

The objective of this study was to provide operational probability density functions (PDFs) for distribution coefficients (K(d)s) in freshwater, representing the partition of radionuclides between the particulate and the dissolved phases respectively. Accordingly, the K(d) variability should be considered in uncertainty analysis of transport and risk assessment models. The construction of PDFs for 8 elements (Ag, Am, Co, Cs, I, Mn, Pu and Sr) was established according to the procedure already tested in Durrieu et al. [2006. A weighted bootstrap method for the determination of probability density functions of freshwater distribution coefficients (K(d)s) of Co, Cs, Sr and I radioisotopes. Chemosphere 65 (8), 1308-1320]: (i) construction of a comprehensive database where K(d)s values obtained under various environments and parametric conditions were collected; (ii) scoring procedure to account for the 'quality' of each datapoint (according to several criteria such as the presentation of data (e.g. raw data vs mean with or without replicates), contact time, pH, solid-to-liquid ratio, expert judgement) in the construction of the PDF; (iii) weighted bootstrapping procedure to build the PDFs, in order to give more importance to the most relevant datapoints. Two types of PDFs were constructed: (i) non-conditional, usable when no knowledge about the site of concern is available; (ii) conditional PDFs corresponding to a limited range of parameters such as pH or contact time; conditional PDFs can thus be used when some parametric information is known on the site under study. For 7 other radionuclides (Ba, Be, Ce, Ra, Ru, Sb and Th), a simplified procedure was adopted because of the scarcity of data: only non-conditional PDFs were built, without incorporating a scoring procedure.

A weighted bootstrap method for the determination of probability density functions of freshwater distribution coefficients (Kds) of Co, Cs, Sr and I radioisotopes

The objective of the study was to provide global probability density functions (PDFs) representing the uncertainty of distribution coefficients (Kds) in freshwater for radioisotopes of Co, Cs, Sr and I. A comprehensive database containing Kd values referenced in 61 articles was first built and quality scores were affected to each data point according to various criteria (e.g. presentation of data, contact times, pH, solid-to-liquid ratio, expert judgement). A weighted bootstrapping procedure was then set up in order to build PDFs, in such a way that more importance is given to the most relevant data points (i.e. those corresponding to typical natural environments). However, it was also assessed that the relevance and the robustness of the PDFs determined by our procedure depended on the number of Kd values in the database. Owing to the large database, conditional PDFs were also proposed, for site studies where some parametric information is known (e.g. pH, contact time between radionuclides and particles, solid-to-liquid ratio). Such conditional PDFs reduce the uncertainty on the Kd values. These global and conditional PDFs are useful for end-users of dose models because the uncertainty and sensitivity of Kd values are taking into account.

Modelling the dispersion of radionuclides following short duration releases to rivers: Part 1. Water and sediment

This paper evaluates and generalises state-of-the-art approaches for modelling short duration liquid discharges of radionuclides ((3)H, (14)C, (60)Co, (134)Cs, (137)Cs, (65)Zn, (89)Sr, (90)Sr, (125)I, (131)I, (241)Am, isotopes of Pu and U) to rivers. An advection-dispersion model was parameterised and used to predict the concentrations of radionuclides in the river environment, i.e. in river water, river bed sediment and fish (Part II of this paper covers uptake to fish). The coupled transport and bio-uptake model was used to predict the concentrations of radionuclides in the River Thames, UK, and one of its tributaries as a result of hypothetical short duration discharges. A simplified version of this model was developed and presented as "look-up" graphs. The influence of various environmental parameters on model output was evaluated by sensitivity analysis. Time-integrated water and sediment concentrations and maximum sediment concentrations may be predicted for all rivers on the basis of the river volumetric flow rate only. Maximum concentration in water is, however, also dependent on other river characteristics. For this latter case, generalised modelling approaches are tested for use in situations where detailed hydrological and dispersion data are not available.