Application of Quantitative Structure-Property Relationship Predictive Models to Water Treatment: A Critical Review

The large number of pollutants in water requires the application of various water treatment techniques. However, it is time-consuming, costly, and laborious to experimentally determine effective techniques for pollutant removal. As an alternative solution, quantitative structure-property relationship (QSPR) modeling has been applied to water treatments, including adsorption, membrane filtration, coagulation, ozonation, the Fenton reaction, photolysis, and photocatalysis. This work is a critical review of the application of QSPR models to water treatment. This modeling approach has proven to be useful for both significantly reducing the experimental load and predicting the treatment characteristics and performance, which are based on the chemical structures involved, the availability of molecular properties with minimal computational cost, and the applicability for regulatory purposes. Although current studies can serve as a basis for further model development, methods of testing the applicability of QSPR models under environmentally relevant conditions have not been explored. We also examine current priorities in ongoing research and the potential development of QSPR models for water treatment applications.

Automated summary

QSPR modeling has been used in water treatment to reduce experimental load and predict treatment characteristics effectively. However, methods for testing the applicability of QSPR models under environmentally relevant conditions have not been explored.