Knowledge-based planning of groundwater treatment trains for an efficient drinking water supply system in urban areas

A knowledge-based planning of the proper treatment trains was applied to the drinking water supply system of Milan city, involving the application of statistical tools and experimental tests. As first step, multivariate statistical techniques were applied to groundwater monitoring data in order to identify specific contaminations of the captured groundwater and their spatial distribution. Starting from 88 quality parameters, 16 significant factors were extracted by Factor Analysis, identifying different kinds of groundwater contamination in the studied area. Then, Cluster Analysis allowed to recognize 8 typical compositions of captured groundwater and their distribution in DWS units. According to these results, different treatment processes were chosen to be adopted in DWS units and their performances were experimentally evaluated on specifically selected water samples. Heterotrophic denitrification has been tested at pilot-scale to treat water affected by nitrate contamination: results allowed to obtain the optimal operating parameters, such as organic carbon supply and volumetric loads, in order to comply with regulation limits. Activated carbon adsorption was tested at lab-scale for the removal of various VOCs (volatile organic carbon) and pesticides in different water mixtures: variable removal efficiencies were obtained towards different contaminants, depending on their physical-chemical properties and the occurrence of competition phenomena (as in the case of perchloroethylene, PCE, and trichloroethylene, TCE, simultaneous adsorption). Air stripping was tested at pilot-scale and it was found to be a suitable solution for removing the most volatile organic compounds (i.e. PCE). According to observed results, an air stripping step before adsorption phase could be a valid solution to increase the lifetime of GAC beds