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Estimation of the Maximum Consumption of Permanganate by Aquifer Solids Using a Modified Chemical Oxygen Demand Test

2008· article· en· W2141164933 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Environmental Engineering · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality Monitoring and Analysis
Canadian institutionsUniversity of Waterloo
FundersStrategic Environmental Research and Development Program
KeywordsPermanganateChemical oxygen demandChemistryAquiferPotassium permanganateEnvironmental sciencePulp and paper industryEnvironmental engineeringEnvironmental chemistryWastewaterInorganic chemistryGroundwaterGeologyEngineering

Abstract

fetched live from OpenAlex

Knowledge of the consumption of permanganate by naturally occurring reduced species associated with aquifer materials is required for site screening and design purposes to support permanganate in situ chemical oxidation (ISCO) applications. It has been established that this consumption is not a singled-valued quantity, but rather is kinetically controlled. Current methods to determine this permanganate natural oxidant demand (NOD) involve the use of well-mixed batch tests, which are time consuming and subject to test variables (e.g., concentration, mass of oxidant to solid ratio, reaction duration, and mixing conditions) that significantly affect the results. In this paper, we propose a modified chemical oxygen demand (COD) test using permanganate, which can be used to determine the maximum permanganate NOD of an aquifer material. As an initial point of comparison, we tested aquifer materials collected from eight potential ISCO sites using this modified or permanganate COD method, the traditional dichromate COD method, and a method based on well-mixed batch reactors. The results from this comparison indicated that there was no statistically significant difference (α=5%) between the results of the permanganate COD test and the maximum NOD from the well-mixed batch reactors, while on average the dichromate COD test overestimated the maximum NOD by 100%. The permanganate COD test results were highly correlated to the batch-test maximum NOD data (r=0.996), and to the total organic carbon and amorphous Fe content of the aquifer materials (r=0.91). A limited sensitivity investigation of this proposed permanganate COD test revealed that the suspected formation of manganese oxides, a reaction byproduct, may lead to increased experimental variability. However, in spite of this concern we recommend that this proposed permanganate COD method is a quick and economical approach for estimating the maximum permanganate NOD for aquifer materials to support permanganate ISCO site screening and initial design purposes.

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.

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 categoriesnone
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 score0.118
Threshold uncertainty score0.305

Codex and Gemma teacher scores by category

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 head0.014
GPT teacher head0.210
Teacher spread0.196 · 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