Prediction of the removal efficiency of emerging organic contaminants based on design and operational parameters of constructed wetlands

Abstract

This study investigates the prediction of removal efficiency of pharmaceuticals (PhCs), personal care products (PCPs), and steroidal hormones (SHs) based on design and operational parameters (depth, area, hydraulic loading rate-HLR, organic loading rate-OLR, and hydraulic retention time-HRT) of constructed wetlands (CWs). A comprehensive statistical analysis was performed by applying principle component analysis, correlation and multiple linear regression analyses. The data used in this analysis was compiled from peer reviewed publications. The CWs design and operational parameters are good predictors of the removal efficiency of these emerging organic contaminants. Operational parameters (HLR, OLR, and HRT) are the most significant predicators and combination with design parameters (depth and area) often improved reliability of the predictions. The best predictive models for PhCs and PCPs were composed of depth, OLR, and HRT (root mean square errors-RMSEs: training set: 7–14 %; test set: 22–27 %). A combination of area, HLR, and OLR formed a credible model for predicting the removal efficiency of SHs (RMSEs: training set: 6 %; test set: 11 %). Similarly, generic models by combining data of PhCs and PCPs, PhCs and SHs, PCPs and SHs, and PhCs, PCPs, and SHs showed acceptable performance. The best performing combined model for the prediction of PhCs, PCPs, and SHs was based on area, HLR, OLR, and HRT (RMSEs: training set: 13 %; test set: 22 %). The information obtained by the use of these models may guide researchers, practitioners, policy makers, and citizens in enhancing knowledge and understanding for the design and operation of CWs in the field conditions.