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Using chlorine demand TO PREDICT TTHM and HAA9 formation
Author(s) -
Gang Daniel Dianchen,
Segar Robert L.,
Clevenger Thomas E.,
Banerji Shankha K.
Publication year - 2002
Publication title -
journal ‐ american water works association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.466
H-Index - 74
eISSN - 1551-8833
pISSN - 0003-150X
DOI - 10.1002/j.1551-8833.2002.tb09559.x
Subject(s) - trihalomethane , chlorine , chemistry , yield (engineering) , haloacetic acids , flocculation , organic chemistry , thermodynamics , physics
Because of an increasing need to balance health risks for pathogen control and disinfection by‐product (DBP) formation in water supplies, utilities are forced to closely examine and optimize their disinfection practices. The authors provide a simple mechanistic model to predict total trihalomethane (TTHM) and the sum of nine haloacetic acids (HAA9) formation based on chlorine demand. To evaluate this modeling approach, eight Missouri surface waters (raw and alum‐treated) were used in DBP formation and chlorine decay kinetic studies. A parallel first‐order reaction model was used to fit the chlorine decay data, and the model coefficients were used to predict THM and HAA formation. Yield coefficients for TTHMs and HAA9 were obtained from fitting the DBP kinetic data. On average, the TTHM and HAA9 yield coefficients for all raw surface waters tested were about 40 μg TTHM/mg Cl 2 and 25 μg HAA9/mg Cl 2 consumed, respectively. In waters subjected to alum coagulation, the average TTHM and HAA9 yield coefficients were 30 μg TTHM/mg Cl 2 and 17 μg HAA9/mg Cl 2 consumed, respectively. The DBP predictive model introduced in this study provided a simple, reliable basis to evaluate treatment options by focusing on chlorine demand. This model can be readily calibrated to local conditions.