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Record W7132959496

Kinetics of the Chemistry and Photochemistry across Different Reaction Stages of UV/chlorine and UV/H2O2 in Water Treatment and Water Reuse

2024· dissertation· W7132959496 on OpenAlexafffundabout
Tianyi Chen

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldEnvironmental Science
TopicAdvanced oxidation water treatment
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaAlbert Einstein College of Medicine, Yeshiva UniversityUniversity of TorontoCalifornia State Water Resources Control Board
KeywordsChloramineChlorineWater treatmentReverse osmosisPollutantContext (archaeology)FoulingWater quality
DOInot available

Abstract

fetched live from OpenAlex

This thesis addressed four distinct (photo)chemical phenomena that are related by their importance to the design of UV-based advanced oxidation processes (AOPs) for water treatment. The first phenomenon was the impact of breakpoint chlorination chemistry on UV/chlorine AOPs in the context of potable reuse. In reverse osmosis-based treatment, chloramines are often applied to control fouling of the reverse osmosis (RO) membrane. Chloramine rejection by the RO is incomplete, so when free chlorine is applied for the UV/chlorine AOP, chlorine-chloramine breakpoint reactions will occur. These rapid reactions can affect the oxidant speciation and concentrations entering the UV reactor, and hence, the UV/chlorine performance. A model validated in this study showed the impracticality of eliminating the residual chloramines in RO permeate by dosing chlorine beyond the breakpoint Cl/N ratio. Operating parameters that limit monochloramine and favour dichloramine may slightly improve UV/chlorine performance, such as by increasing the water travel time prior to the UV reactor or increasing the applied Cl/N ratio. The second factor explored was related to radical scavenging capacity (Sc), which is a water quality parameter that directly affects the radical concentration and therefore the target pollutant decay kinetics in UV/AOP. To date, there have been very few studies of the variability of Sc within a water source, or across treatment trains. In this work, Sc was tracked at 5 surface and 1 ground drinking water treatment plants in Ontario over approximately one year. The variation in Sc was observed to range within 15–30%. The impact of this variation on pollutant removal efficiency in a UV/AOP was estimated to be comparatively smaller (±10% in pollutant removal rate) since pollutant removal is a function of the scavenging of not only the background water matrix (Sc), but also the oxidant (H2O2 or chlorine). Sc was not strongly correlated with total organic carbon, UV absorbance at 254 nm, or fluorescence excitation-emission matrix components. The third phenomenon examined relates to the design of UV/AOPs, and specifically how UV/chlorine is compared to UV/H2O2 in terms of predicted performance. Past studies have made such comparisons based on UV collimated beam testing or testing using small (pilot)-scale UV reactors. In this research, however, it was demonstrated that such small-scale tests are biased against UV/chlorine since UV/chlorine efficiency increases with longer UV path lengths (i.e., when using more powerful lamps that are spaced further apart, such as at full-scale). Modelling and experiments were conducted to examine mono- and polychromatic UV/H2O2 and UV/chlorine performance at 2–30 cm path lengths. For monochromatic (254 nm) UV light, the path length effect was not significant, but for medium pressure (polychromatic) lamps, the difference in such lamp spacing makes the pollutant removal efficiency of UV/chlorine relative to UV/H2O2 increase by 40%. The effects of natural water matrix absorbance, oxidant dose, and water pH were also discussed. The fourth phenomenon examined was a detailed study of H2O2 quenching kinetics using thiosulfate, bisulfite, and chlorine. When applying UV/H2O2 advanced oxidation, the majority of the H2O2 survives and need to be quenched since H2O2 exerts a significant downstream chlorine demand. It was determined that over the normal pH range of drinking water (7–8.5), chlorine is the most rapid quenching agent. The form of chlorine (hypochlorite vs. Cl2 gas) can impact H2O2 quenching rate, with gaseous chlorine slowing the reaction and hypochlorite having the opposite effect. These impacts diminish when water alkalinity increases to 80 mg/L as CaCO3.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.290
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes3
Has abstractyes

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