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Record W7106014386 · doi:10.7939/83558

Evaluating the effectiveness of Clearflow treatment products in ameliorating effluent toxicity at an Alberta coal mine

2025· dissertation· en· W7106014386 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2025
Typedissertation
Languageen
FieldEnvironmental Science
TopicMine drainage and remediation techniques
Canadian institutionsnot available
Fundersnot available
KeywordsEffluentFlocculationTurbidityContaminationCationic polymerizationPhosphorusWater qualityFish <Actinopterygii>

Abstract

fetched live from OpenAlex

The purpose of this study was to evaluate the efficacy of a neutralizing agent developed by the Clearflow Group Ltd. in eliminating toxic effects associated with excess residues from cationic flocculant treatment, with the secondary objective of assessing the performance of a treatment train consisting of Clearflow cationic flocculant, neutralizing agent, and polishing blocks in removing environmentally harmful contaminants from effluent generated by a coal mine. I compared water quality between untreated effluent and effluent serially treated with cationic flocculant followed by Clearflow neutralizing agent. Results showed turbidity was reduced by 89 - 99% (avg. 96%; n = 6) while total phosphorus was reduced by 74 - 94% (avg. 82%; n = 6). Average removal of total metals (>0.5 µm) across six sampling months was at least 90% for Cd, Zn, Fe, Be, Al, Co, and Cr. Over 70% removal was observed for total V, Mn, Cu, Ni, Ba, and Pb, while over 50% removal was observed for total As, Se, Mg, and K. Average removal for Sb, Tl, St, Mo, Ca, and Na was below 50%. Silver was not observed in effluent either before or following treatment. Strong removal was also observed for certain dissolved metals (<0.5 µm), with Iron, Beryllium, Chromium, and Vanadium achieving close to 100% removal. In fish EC50 experiments, conducted monthly over six months, mortalities were observed only during May experiments in fish exposed to cationic only treated effluent. However, no mortalities were observed in fish exposed to cationic flocculant along with Clearflow neutralizing agent. Invertebrate surveys in the receiving environment showed similar community structure and taxonomic diversity in the upstream river control site and at 50m and 100m downstream sites. These communities were dominated by larval Ephemeroptera (mayflies) at proportions of 50% or greater. Only the area immediately surrounding the effluent discharge showed a significantly different community structure, with a greater predominance of dipterids (true flies) and trichopterans (caddisflies). Microbial communities showed some differences in taxonomic structure, taxonomic diversity, and metabolic activity patterns among sampled sites. However, there was no overall upstream vs downstream trend in these community parameters, and differences among samples were more strongly associated with sampling month compared to sampling site. Overall, the findings from this work indicate that multi-stage treatment of coal mining effluent using Clearflow cationic flocculant and neutralizer is effective at removing the majority of pollution in the initial effluent, and that use of Clearflow neutralizing agent prevents lethal toxicity to fish caused by excess cationic polymer residues.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.983
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.013
GPT teacher head0.247
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2025
Admission routes1
Has abstractyes

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