Drinking water chlorination reduces the risk of pathogenic infection, but it may be harmful to human health because of disinfection by-product (DBP) formation. Available predictive models of DBP formation are almost exclusively calibrated at lab scale. The objective of the present research work is to apply two of them at full scale for the Santa Sofia aqueduct (Campania, Southern Italy), in order to predict DBP formation and evolution as function of the real water network characteristics. Live data, gathered continuously by a wireless network of multi-parametric probes, installed on the aqueduct, along with data measured in laboratory, are used for model calibration. The predictive scenarios are performed by using an open source integrated GIS-based platform (including Epanet, MSX, GIS uDig). © 2014 Springer International Publishing Switzerland.
|Titolo:||Use of kinetic models for predicting dbp formation in water supply systems|
|Data di pubblicazione:||2014|
|Appare nelle tipologie:||4.1 Contributo in Atti di convegno|