FUNDAMENTAL STUDY FOR RIVER WATER QUALITY MONITORING USING FLUORESCENCE EEM-PARAFAC: BOD PREDICTION

Abstract

 In this study, a fundamental study was conducted for developing new river water quality monitoring system using fluorescence EEM-PARAFAC which had advantages in real time detection and pollution source tracking. Data set including 1219 EEMs was acquired by periodical sampling from 38 sites of the rivers in Saitama Prefecture. Eight PARAFAC components were successfully identified from the data set, in which each fluorophore represented three types of humic substances, two types of amino acids, degradation product of phytoplankton, fluorescent brightener (DSBP) and substance rich in sewage effluent. Multiple regression models using fluorescence components were created for high precise prediction of BOD. In this models, significant indices were found to separately detect and quantify the pollutions from sewage effluent and phytoplankton caused by eutrophication.