Monitoring and classification of wastewater quality using supervised pattern recognition techniques and deterministic resolution of molecular absorption spectra based on multiwavelength UV spectra deconvolution.

A field flow approach for the in situ monitoring of wastewater quality is developed and assessed in this work, based on a combination of methods employing deconvolution of molecular absorption spectra and in situ/on-line analysis of wastewater effluent of various origin. The approach involves in situ immersion probes to monitor basic physicochemical parameters followed by UV spectrum deconvolution in order to provide a rapid estimate of organic matter, suspended solids and nitrate and on-line analysis of phosphates in a fully automated setup. The collected data are then treated with a series of supervised pattern recognition techniques in order to classify wastewater effluent according to their origin in three major categories namely municipal, industrial and hospital. The results suggest that the method affords a good approximation of realistic concentrations, as determined by reference methods, while it affords a good classification among various wastewater effluents of different origin. In that manner, the method enables a rapid inference of treated wastewater quality and a robust assessment of treatment process state, especially with regards to violations of effluent quality parameters.