Vertical flow constructed wetlands using expanded clay and biochar for wastewater remediation: A comparative study and prediction of effluents using machine learning.

This study evaluated and compared the performance of two vertical flow constructed wetlands (VF) using expanded clay (VF) and biochar (VF), of which both are low-cost, eco-friendly, and exhibit potentially high adsorption as compared to conventional filter layers. Both VFs achieved relatively high removal for organic matters (i.e. Biological oxygen demand during 5 days, BOD) and nitrogen, accounting for 9.5 - 10.5 gBODmd and 3.5 - 3.6 gNH-Nmd, respectively. The different filter materials did not exert any significant discrepancy to effluent quality in terms of suspended solids, organic matters and NO-N (P > 0.05), but they did influence NH-N effluent as evidenced by the removal rate of that by VF and VF being of 8.4 ± 5.7 and 84.6 ± 6.4%, respectively (P < 0.05). The results obtained from the designed systems were further subject to machine learning to clarify the effecting factors and predict the effluents. The optimal algorithms were random forest, generalized linear model, and support vector machine. The values of the coefficient of determination (R) and the root mean square error (RMSE) of whole fitting data achieved 74.0% and 5.0 mgL, 80.0% and 0.3 mgL, 90.1% and 2.9 mgL, and 48.5% and 05 mgL for BOD_VF, NHN_VF, BOD_VF, and NH-N_VF, respectively.