Modeling Chromate Removal Using Ion Exchangers in Drinking Water Applications

TL;DR

This study improves the predictive accuracy of the Thomas ion exchange model for chromate removal in drinking water by fixing the resin capacity and modeling the rate constant as a function of contact time and concentration.

Contribution

It introduces a linear relationship for the Thomas model's rate constant, enhancing its predictive accuracy for chromate removal processes.

Findings

Fixing resin capacity improves model stability.

Linear KT relationship increases accuracy five-fold.

Model better suited for process control applications.

Abstract

Chromates are widely used for their anticorrosive properties. Unfortunately, they are highly hazardous with environmental agencies regulating their levels to below 10 ppb in drinking water. As anion exchange resins are typically used for removal, predictive dynamic models are necessary to make quick decisions rather than relying on experimental data that could take several days to implement. With various dynamic models currently applied to simulate the ion exchange process, the Thomas model was picked for its simplicity and better accuracy when compared to other models. The Thomas model contains two parameters, the constant (KT) and the maximum resin capacity (qm), which are empirically calculated. Unfortunately, the model demonstrated large parameter fluctuations with no correlation to varying contact times or inlet chromate concentrations. Therefore, fixing both parameters will lead to failed model predictive behavior. By fixing the value of qm and proposing a linear relationship of KT with resin contact time and inlet chromate concentration, the accuracy of the model was improved five-fold, demonstrating its potential for better process controls.