Effects of Ozone and Biological Degradation on the Removal and Transformation of Highly Hydrophilic DOC in a Conventional Water Treatment Process
Bibliographic record
Abstract
The application of ozone followed by biological active filters (BAFs) for treating high dissolved organic carbon (DOC) waters has shown limited efficacy in DOC removal and controlling trihalomethanes (THMs). The following effects of ozone on DOC characteristics were extensively studied and documented: substantial and rapid decrease in UV254 absorbance and SUVA, increase in the hydrophilic (HPI) DOC content, and transformation of high MW compounds such as biopolymers (BP) and humic substances (HS) into low MW and building blocks (LMWs&BB). All these changes imposed by ozone could increase DOC biodegradability since HPI, low SUVA, and low MW compounds have been reported to be more biodegradable. While the effects of ozone on DOC characteristics have been extensively studied, these investigations often focused on source waters rather than coagulated/softened water. Coagulated/softened water exhibits different chemical characteristics than source water, such as lower UV254 absorbance, lower hydrophobicity (HPO), and higher content of low MW DOC components. Given the prevalence of HPI DOC fractions in coagulated/softened water and the comparable THMFP of HPI and HPO DOC fractions in Manitoba, it is imperative to evaluate the impact of ozone treatment on the chemical characteristics and biodegradability of such water and to determine the required ozone dose for improved water quality in the following biological degradation process. Therefore, we first examined the removal and transformation of total DOC (tDOC) and its HPI fraction through full-scale coagulation/softening, ozonation, and BAFs. Second, we investigated the effect of different ozone doses on the characteristics of tDOC and HPI fractions. Our results revealed that the HPI fractions after coagulation/softening had a higher percentage of low MW compounds (< 1 kDa) and higher STHMFP than the raw HPI, indicating these treatment units induced distinct changes in characteristics of DOC fractions. Increasing the ozone dose from 0.4 to 1 mg O3/mg-C on highly-hydrophilic coagulated/softened water (HPI=73%) made all the DOC to be HPI, increased the DOC biodegradability from 5 to 27%, and reduced the STHMFP from 69.4 to 11.2 µg/mg-C. However, the 28-day biological degradation offset the impact of 1 mg O3/mg-C and increased the STHMFP to 60 ± 7 µg/mg-C, which was due to the formation of low-MW compounds.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".