Disinfection by-product formation following chlorination of drinking water: Artificial neural network models and changes in speciation with treatment

Science of the Total Environment

Volumn 408, Issue 19, 2010, Pages 4202-4210

  Kulkarni, Pranav ^a   Chellam, Shankararaman ^a  

^a UNIVERSITY OF HOUSTON   (United States)

Author keywords

Artificial neural networks; Chlorine disinfection; Disinfection by products; Drinking water; Granular activated carbon; Haloacetic acids; Nanofiltration; Total organic halide; Trihalomethanes

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CHLORINE DISINFECTION; DISINFECTION BY-PRODUCT; DRINKING WATER; GRANULAR ACTIVATED CARBONS; HALOACETIC ACIDS; ORGANIC HALIDES; TRIHALOMETHANES;

ACTIVATED CARBON TREATMENT; BROMINE; BROMINE COMPOUNDS; BYPRODUCTS; CHLORINATION; CHLORINE; DISINFECTION; DISSOLUTION; EFFLUENT TREATMENT; ENVIRONMENTAL PROTECTION AGENCY; GRANULAR MATERIALS; NANOFILTRATION; NEURAL NETWORKS; ORGANIC CARBON; POTABLE WATER; QUALITY CONTROL; WATER FILTRATION; WATER POLLUTION; WATER QUALITY; WATER RECYCLING;

ACTIVATED CARBON;

ACETIC ACID DERIVATIVE; ACTIVATED CARBON; BROMIDE ION; CHLORINE; DISSOLVED ORGANIC MATTER; DRINKING WATER; HALOACETIC ACID DERIVATIVE; ORGANOHALOGEN DERIVATIVE; TRIHALOMETHANE; UNCLASSIFIED DRUG;

ACETIC ACID; ACTIVATED CARBON; ARTIFICIAL NEURAL NETWORK; BROMIDE; BROMINE; CHLORINATION; DISINFECTION; DISSOLVED ORGANIC CARBON; DRINKING WATER; FILTRATION; NUMERICAL MODEL; SPECIATION (CHEMISTRY); WATER QUALITY; WATER TREATMENT;

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; CHLORINATION; CONTROLLED STUDY; DISINFECTION; LIGHT ABSORPTION; NANOFILTRATION; PH; PREDICTION; PRIORITY JOURNAL; SIMULATION; SPECIES DIFFERENTIATION; WATER QUALITY; WATER TEMPERATURE; WATER TREATMENT;

ACETIC ACID; CHLORINE; DISINFECTION; HALOGENATION; MODELS, CHEMICAL; NEURAL NETWORKS (COMPUTER); TRIHALOMETHANES; WATER POLLUTANTS, CHEMICAL; WATER PURIFICATION; WATER SUPPLY;

EID: 77954622505     PISSN: 00489697     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.scitotenv.2010.05.040     Document Type: Article

References (38)

1. Allgeier S.C., Shukairy H.M., Westrick J.J. ICR treatment studies. J Am Wat Wks Assn 1998, 90:70-82.
2. Allgeier S.C., Summers R.S. Evaluating NF for DBP control with the RBSMT. J Am Wat Wks Assn 1995, 87:87-99.
3. Bond R., DiGiano F.A. Evaluating GAC performance using the ICR database. J Am Wat Wks Assn 2004, 96:96-104.
4. Bowen W.R., Jones M.G., Yousef H.N.S. Prediction of the rate of crossflow membrane ultrafiltration of colloids: a neural network approach. Chem Eng Sci 1998, 53:3793-3802.
5. Chang E.E., Lin Y.P., Chiang P.C. Effects of bromide on the formation of THMs and HAAs. Chemosphere 2001, 43:1029-1034.
6. Chellam S., Krasner S.W. Disinfection by-product relationships and speciation in chlorinated nanofiltered waters. Environ Sci Technol 2001, 35:3988-3999.
7. Chellam S., Taylor J.S. Simplified analysis of contaminant rejection during ground- and surface water nanofiltration under the information collection rule. Wat Res 2001, 35:2460-2474.
8. Chen C., Zhang X., He W., Lu W., Han H. Comparison of seven kinds of drinking water treatment processes to enhance organic material removal: a pilot test. Sci Total Environ 2007, 382:93-102.
9. Chowdhury S., Champagne P., McLellan P.J. Models for predicting disinfection byproduct (DBP) formation in drinking waters: a chronological review. Sci Total Environ 2009, 407:4189-4206.
10. DBP/ICR analytical methods manual (EPA 814-B-96-002) 1996, EPA, Cincinnati, OH.
11. ICR treatment study database, version 1.0 (EPA 815-C-00-003) 2000, EPA, Cincinnati, OH.
12. Garson G.D. Interpreting neural network connection weights. AI Expert 1991, 6:47-51.
13. Goh A.T.C. Seismic liquefaction potential assessed by neural networks. J Geotech Eng 1994, 120:1467-1480.
14. Gould J.P., Fitchhorn L.E., Urheim E. Formation of brominated trihalomethanes: extent and kinetics. Water chlorination: environmental impact and health effects. 4 1983, 297-310. Ann Arbor Science Publishers, Ann Arbor, MI. R.L. Jolley, W. Brungs, J. Cotruva, J. Mattice, V. Jacobs (Eds.).
15. Haas C.N. Neural networks provide superior description of Giardia lamblia inactivation by free chlorine. Wat Res 2004, 38:3449-3457.
16. Hamidin N., Yu Q.J., Connell D.W. Human health risk assessment of chlorinated disinfection by-products in drinking water using a probabilistic approach. Wat Res 2008, 42:3263-3274.
17. Hong H.C., Liang Y., Han B.P., Mazumder A., Wong M.H. Modeling of trihalomethane (THM) formation via chlorination of the water from Dongjiang River (source water for Hong Kong's drinking water). Sci Total Environ 2007, 385:48-54.
18. Hua G., Reckhow D.A. DBP formation during chlorination and chloramination: effect of reaction time, pH, dosage, and temperature. J Am Wat Wks Assn 2008, 100:82-95.
19. Koch B., Krasner S.W., Sclimenti M.J., Schimpff W.K. Predicting the formation of DBPs by the simulated distribution system. J Am Wat Wks Assn 1991, 83:62-70.
20. Legube B., Parinet B., Gelinet K., Berne F., Croue J.-P. Modeling of bromate formation by ozonation of surface waters in drinking water treatment. Wat Res 2004, 38:2185-2195.
21. Liang L., Singer P.C. Factors influencing the formation and relative distribution of haloacetic acids and trihalomethanes in drinking water. Environ Sci Technol 2003, 37:2920-2928.
22. Massart D.L., Vandeginste B.G.M., Buydens L.M.C., De Jong S., Lewi P.J., Smeyers-Verbeke J. Handbook of chemometrics and qualimetrics: part A 1997, Elsevier Science, Amsterdam, The Netherlands.
23. McGuire M.J., McLain J.L., Obolensky A. Information Collection Rule Data Analysis 2002, Awwa Research Foundation, Denver, CO.
24. Milot J., Rodriguez M.J., Serodes J.B. Contribution of neural networks for modeling trihalomethanes occurrence in drinking water. J Water Resour Plann Manage 2002, 128:370-376.
25. Myllykangas T., Nissinen T.K., Mäki-Paakkanen J., Hirvonen A., Vartiainen T. Bromide affecting drinking water mutagenicity. Chemosphere 2003, 53:745-756.
26. Obolensky A., Singer P.C. Halogen substitution patterns among disinfection byproducts in the information collection rule database. Environ Sci Technol 2005, 39:2719-2730.
27. Obolensky A., Singer P.C. Development and Interpretation of Disinfection Byproduct Formation Models Using the Information Collection Rule Database. Environ Sci Technol 2008, 42(15):5654-5660.
28. Platikanov S., Puig X., Martín J., Tauler R. Chemometric modeling and prediction of trihalomethane formation in Barcelona's water works plant. Wat Res 2007, 41(15):3394-3406.
29. Rodriguez M.J., Milot J., Sérodes J.-B. Predicting trihalomethane formation in chlorinated waters using multivariate regression and neural networks. J Wat Supply Res Tech AQUA 2003, 52:199-215.
30. Sadiq R., Rodriguez M.J. Disinfection by-products (DBPs) in drinking water and predictive models for their occurrence: a review. Sci Total Environ 2004, 321:21-46.
31. Sadiq R., Rodriguez M.J. Fuzzy synthetic evaluation of disinfection by-products-a risk-based indexing system. J Environ Manage 2004, 73:1-13.
32. Shimazu H., Kouchi M., Sugita Y., Yonekura Y., Kumano H., Hashiwata K., Hirota T., Ozaki N., Fukushima T. Developing a model for disinfection by-products based on multiple regression analysis in a water distribution system. J Wat Supply Res Tech AQUA 2005, 54(4):225-237.
33. Singer P.C. Formation and control of disinfection by-products in drinking water 1999, American Water Works Association, Denver, CO.
34. Sohn J., Amy G., Cho J., Lee Y., Yoon Y. Disinfectant decay and disinfection by-products formation model development: chlorination and ozonation by-products. Wat Res 2004, 38:2461-2478.
35. Symons J.M., Krasner S.W., Sclimenti M.J., Simms L.A., Sorensen H.W., Speitel G.E., et al. Influence of bromide ion on trihalomethane and haloacetic acid formation. Disinfection by-products in water treatment: the chemistry of their formation and control 1996, 91-130. Lewis Publishers, Boca Raton, FL. R. Minear, G.L. Amy (Eds.).
36. Symons J.M., Krasner S.W., Simms L.A., Sclimenti M. Measurement of THM and precursor concentrations revisited: the effect of bromide ion. J Am Wat Wks Assn 1993, 85:51-62.
37. Uyak V., Ozdemir K., Toroz I. Multiple linear regression modeling of disinfection by-products formation in Istanbul drinking water reservoirs. Sci Total Environ 2007, 378:269-280.
38. Westerhoff P., Debroux J., Amy G.L., Gatel D., Mary V., Cavard J. Applying DBP models to full-scale plants. J Am Wat Wks Assn 2000, 92:89-102.