ASSESSMENT OF TRIHALOMETHANES BASED ON FLUORESCENCE MEASUREMENT

Abstract

The use of chlorine as a water disinfectant has come under scrutiny because of its potential to react with natural organic matter (NOM) and form disinfection by products (DBPs). In addition to being highly influenced by the type of organic and inorganic matter in the source water, the different species and concentration of DBPs vary according to the type of disinfectant use, the dose of the disinfectant, the concentration and nature of NOM, the time since dosing, temperature and pH of water. Trihalomethanes (THMs) and Haloacetic Acids (HAAs) are two most prevalent class of DBPs obtained during chlorination of drinking water. THM being more carcinogenic is measured by GC-MS and lacks any other method of on line measurement. Till now there is no way to get information about THM species formed by using fluorescence. The objective of the present work was to create a predictive model that allows the estimation of TI-IM-formation during chlorination on the basis of fluorescence measurements. To achieve this goal, fluorescence property which is a property of a material to absorb certain wavelength of energy and emit the higher wavelengths from excited singlets was exploited. The substances which show fluorescence are called fluorophores. NOM is a fluorophore. During chlorination, the degradation of the natural organic matter results in a shift in fluorescence which can be measured using fluorescence spectrophotometers and can be correlated with the THMs formed. The analysis was carried out comparing results from a predictive mathematical model developed using fluorescence shift against actual THMs measured from GC-MS. In addition to above, the impact of bromide pollution on formation of organic as well as inorganic DBPs after disinfection using electrolytical chlorination was studied. The advantage of this model would be easy handling of fluorescence measurements and its suitability for online measurements and therefore monitoring. The prediction model showed a high degree of accuracy in estimating the THMs and would facilitate easy monitoring in field conditions.