Statistical modelling of organic matter and emerging pollutants removal in constructed wetlands.

Multiple regression models, clustering tree diagrams, regression trees (CHAID) and redundancy analysis (RDA) were applied to the study of the removal of organic matter and pharmaceuticals and personal care products (PPCPs) from urban wastewater by means of constructed wetlands (CWs). These four statistical analyses pointed out the importance of physico-chemical parameters, plant presence and chemical structure in the elimination of most pollutants. Temperature, pH values, dissolved oxygen concentration, redox potential and conductivity were related to the removal of the studied substances. Plant presence (Typha angustifolia and Phragmites australis) enhanced the removal of organic matter and some PPCPs. Multiple regression equations and CHAID trees provided numerical estimations of pollutant removal efficiencies in CWs. These models were validated and they could be a useful and interesting tool for the quick estimation of removal efficiencies in already working CWs and for the design of new systems which must fulfil certain quality requirements.