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Monitoring of water quality from roof runoff: Interpretation using multivariate analysis
Authors:Vialle C  Sablayrolles C  Lovera M  Jacob S  Huau M-C  Montrejaud-Vignoles M
Affiliation:a Université de Toulouse, INP, LCA (Laboratoire de Chimie Agro-Industrielle), ENSIACET, 4 Allées Emile Monso, F-31030 Toulouse, France
b INRA, LCA (Laboratoire de Chimie Agro-Industrielle), F-31029 Toulouse, France
c Veolia Water North America, Technical Direction Group, 101, W Washington Street, Suite 1440 East, IN-46204 Indianapolis, USA
d Veolia Eau, Direction Technique, Immeuble Giovanni Battista B, 1, rue Giovanni Battista Pirelli, F-94410 Saint-Maurice, France
e Veolia Eau, Direction des collectivités publiques, 36-38 avenue Kleber, F-75016 Paris, France
Abstract:The quality of harvested rainwater used for toilet flushing in a private house in the south-west of France was assessed over a one-year period. Temperature, pH, conductivity, colour, turbidity, anions, cations, alkalinity, total hardness and total organic carbon were screened using standard analytical techniques. Total flora at 22 °C and 36 °C, total coliforms, Escherichia coli and enterococci were analysed. Overall, the collected rainwater had good physicochemical quality but did not meet the requirements for drinking water. The stored rainwater is characterised by low conductivity, hardness and alkalinity compared to mains water. Three widely used bacterial indicators - total coliforms, E. coli and enterococci - were detected in the majority of samples, indicating microbiological contamination of the water. To elucidate factors affecting the rainwater composition, principal component analysis and cluster analysis were applied to the complete data set of 50 observations. Chemical and microbiological parameters fluctuated during the course of the study, with the highest levels of microbiological contamination observed in roof runoffs collected during the summer. E. coli and enterococci occurred simultaneously, and their presence was linked to precipitation. Runoff quality is also unpredictable because it is sensitive to the weather. Cluster analysis differentiated three clusters: ionic composition, parameters linked with the microbiological load and indicators of faecal contamination. In future surveys, parameters from these three groups will be simultaneously monitored to more accurately characterise roof-collected rainwater.
Keywords:Rainwater harvesting system   Physicochemical quality   Microbiological quality   Principal component analysis   Cluster analysis
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