Off-campus UMass Amherst users: To download campus access dissertations, please use the following link to log into our proxy server with your UMass Amherst user name and password.
Non-UMass Amherst users: Please talk to your librarian about requesting this dissertation through interlibrary loan.
Dissertations that have an embargo placed on them will not be available to anyone until the embargo expires.
Author ORCID Identifier
https://orcid.org/0000-0002-3810-4812
AccessType
Open Access Dissertation
Document Type
dissertation
Degree Name
Doctor of Philosophy (PhD)
Degree Program
Civil and Environmental Engineering
Year Degree Awarded
2021
Month Degree Awarded
September
First Advisor
David A Reckhow
Second Advisor
John E. Tobiason
Third Advisor
Youssef Oulhote
Fourth Advisor
J Michael Wright
Abstract
Among the regulated disinfection byproducts (DBPs) with the current Stage 2 Disinfectant and Disinfection Byproduct Rule (the Stage 2 D/DBPR), trihalomethanes (THMs) and haloacetic acids (HAAs) are two DBP classes that have been widely studied. Currently, the summation of concentrations of all four THMs (CHCl3, CHCl2Br, CHClBr2, and CHBr3) were regulated as total trihalomethanes (THM4), but without control of individual species. The summation of concentrations of five out of nine HAAs (monochloroacetic acid, monobromoacetic acid, dichloroacetic acid, dibromoacetic acid, and trichloroacetic acid) were regulated as HAA5. The other four HAA species were known as unregulated HAAs. Recent studies have directed attention to the unregulated HAA species due to their higher potential for carcinogenicity. At present, it is hard to evaluate the health risks from unregulated DBP species as they are mostly not measured or monitored.
The core of this research is a kinetic binomial model that predicts the unregulated HAA species. We used a simple precursor, acetone, to test the reaction rate constants of natural organic matter halogenation reactions and to build the chemistry foundation of the model. By using the reaction rate constants derived from acetone halogenation, we predicted the formation of all for THM species with high accuracy.
The kinetic model was then developed and resulted showed very high accuracy between predicted and measured unregulated HAAs (R2>0.98). We also provided a set of equations for the application of the model. The model was then applied to utility data (i.e., DBP data collected by public water suppliers) to verify the reliability in more complicate conditions and received results with high accuracy (R2>0.95).
Lastly, the model was used to predict the concentration of unregulated HAAs in the state of Ohio. The predictions were connected with collected birth records to evaluate the association between the DBP exposure and the adverse birth outcomes. Chlorinated DBPs showed higher exposure risks. We believe that the result reflected the limitation from the currently used DBP surrogates. We also compared the state-of-art DBP surrogates in the field of epidemiology and suggested the usage of a more toxicity based approach, instead of simply summation of concentrations approach.
DOI
https://doi.org/10.7275/24412584
Recommended Citation
Ma, Xian, "Prediction of the Formation, Speciation, and Health Risks of Unregulated Disinfection Byproducts in Drinking Water using a Kinetic Binomial Model" (2021). Doctoral Dissertations. 2247.
https://doi.org/10.7275/24412584
https://scholarworks.umass.edu/dissertations_2/2247