Improved Models for Chromate Removal Using Ion Exchangers in Drinking Water Applications

• Published in: Journal of environmental engineering (New York, N.Y.) N.Y.), 2022-05, Vol.148 (5)
• Main Authors: Ghanem, Fred, Jerpoth, Swapana S, Yenkie, Kirti M
• Format: Article
• Language: English
• Subjects: Anion exchanging; Chromate; Chromates; Corrosion prevention; Decisions; Drinking water; Dynamic models; Ion exchange; Ion exchangers; Model accuracy; Parameters; Process control; Process controls; Resins; Sensitivity analysis; Technical Papers
• ISSN: 0733-9372; 1943-7870
• DOI: 10.1061/(ASCE)EE.1943-7870.0001997

AbstractChromates are widely used for their anticorrosive properties. Unfortunately, they are hazardous, with environmental agencies regulating their levels to below 10 parts per billion (ppb) in drinking water. Because single-use anion-exchange resins are the standard tools for chromate removal, accurate predictive dynamic models are necessary for quick decisions based on deviations of the inlet concentration to achieve the desired outlet purity requirements. To this end, we studied various dynamic models to simulate the ion exchange process for targeted chromate removal. Of those studied, we selected the Thomas model for its accuracy. The Thomas model has two parameters, which are estimated via minimization of the sum of square errors between the predicted model and the experimental data set with varying process conditions. In these analyses, the resulting model demonstrated large parameter fluctuations with contact times and inlet chromate concentrations. Therefore, relying on fixed-parameter values can lead to faulty predictions and, therefore, to poor controllability of the chromate removal ion-exchange system. Thus, in this work, we evaluated the variation of parameters with respect to resin contact times and inlet chromate concentrations and performed a detailed sensitivity analysis and confidence region studies. This work improves the accuracy of the modified Thomas model fivefold and demonstrates its potential for use in process control decisions.