Removal of trihalomethanes precursors from surface waters typical for Canadian prairie and shield
Bibliographic record
Abstract
Many Canadian water treatment plants supplied by surface waters of the Canadian Prairie and Shield have elevated concentrations of trihalomethanes (THMs), which exceed the provincial standards. These water sources are characterized by elevated levels of dissolved organic carbon (DOC) and varying levels of calcium hardness, which causes a challenge for the removal of THMs precursors. The objective of this study was to investigate the effect of two treatment methods: chemical coagulation and pre-ozonation-coagulation on the removal of DOC as the main THMs precursor. Surface waters typical for the Canadian Prairie and Canadian Shield were used in the experiments which includes Assiniboine River, Red River, and Rainy River. The effects of different experimental conditions such as coagulant dose, coagulant type, and solution pH as well as ozone dosage on THMs removal were investigated. The structural and chemical characteristics of natural organic matter and isolated humic substances, before and after the reaction with ozone, were studied using spectroscopic techniques. The results illustrated that the quality of source water (DOC characteristics, concentration of water DOC and Calcium) has a significant impact on THMs reduction by chemical coagulation and ozonation. Coagulation results showed that reduction of total DOC does not guarantee THMFP reduction and chemical coagulation should be optimized to remove the hydrophobic acid fraction which forms most THMs. The removal of DOC by aluminum-based coagulants was affected more by the concentration of polymeric and colloidal aluminum speciation. This finding is especially important for plants supplied by high alkalinity waters where pH adjustment is a serious challenge. The effect of pre-ozonation on coagulation varies depending on the concentration of calcium, which has the ability to form complexes with DOC compounds promoting their removal in coagulation. For the surface water with high levels of organic carbon and calcium hardness, ozonation prior to coagulation was beneficial in terms of DOC reduction. However, it showed the opposite effect on water with high levels of DOC accompanied with low level of calcium hardness. Spectroscopic results showed that ozonation of NOM and humic substances cause a significant reduction of aromatic and highly conjugated compounds (constituting primarily the hydrophobic acid fraction).
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 | 0.000 | 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".