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Record W4236656692 · doi:10.32920/ryerson.14662317

Combined Granular Activated Carbon And UV/H₂O₂Processes For The Treatment Of Pharmaceutical Wastewater

2021· preprint· en· W4236656692 on OpenAlexaffabout
Kiran K. Shah

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicWater Quality Monitoring and Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsAdsorptionChemistryTotal organic carbonWastewaterActivated carbonDesorptionCarbon fibersNuclear chemistryHydraulic retention timeChromatographyEnvironmental chemistryEnvironmental engineeringOrganic chemistryMaterials science

Abstract

fetched live from OpenAlex

The treatment of pharmaceutical wastewater was performed at the lab scale using UV/H₂O₂, process granular activated carbon (GAC) adsorption and their combination to investigate the total organic carbon (TOC) removal efficiency for different inlet TOC loadings and treatment times. Experimental study revealed that GAC adsorption alone had 81% efficiency in TOC removal in 10 min breakthrough time for flow rate of 0.6 L/min with granular activated carbon dosage of 333.33 mgActivated Carbon/L whereas UV/H₂O₂ process alone showed 26 and 29% TOC reduction at with 21.7 g/LH₂O₂ concentration with 254 and 185 nm wavelength lamps a 6 h hydraulic retention time, respectively, with average feed concentration (TOC) of 1,7555.75 mgC/L and COD of 5,214.6 mg/L at 25 ± 5°C. Experimental results showed that the optimum H₂O₂ dosage for the UV/H₂O₂ process was 1:2 stoichiometric COD: H₂O₂ molar ratio to achieve up to 26 and 29% TOC reduction efficiency than that at pH 12.01 which resulted 15-20% TOC reduction efficiency. The Bohart-Adams rate constants (K) and maximum adsorption capacity of carbon (N) from column breakthrough studies for synthetic pharmaceutical wastewater at 81% were found to be 7.10 x 10⁻³ L/(min.mgC) and 1.06 x 10³ mgC/L, respectively. In combined processes, it was found that GAC adsorption followed by desorption of contaminants from GAC by steam and UV₂₅₄/H₂O₂ treatment of the condensed steam let to 81% of TOC removal from the wastewater. Out of 358.73 mgC/L of TOC desorbed 88.1% of TOC was degraded in the UV₂₅₄/H₂O₂ treatment was degradation. Total operating cost of GAC adsortpion followed by desorption of contaminants from GAC by steam and UV₂₅₄/H₂O₂ treatment of condensed steam were found to be $11/L. While the pre-treated wastewater by UV₂₅₄H₂O₂ treatment followed by GAC adsorption, along the desorption of contaminants from GAC using steam and UV₂₅₄/H₂O₂ treatment of the condensed steam, let to an overall 81% TOC removal and 75.1% of TOC degradation using UV₂₅₄/H₂O₂ process. The cost of this combined treatment was found to be $6/L of wastewater treated which led to an economical saving of $5/L with respect to the combined TOC removal and degradation efficiency achieved. The savings predictions were achieved due to the less carbon dosage requirement and ability of UV/H₂O₂ process to degrade the TOC present in the wastewater. Based on single and combined treatments, the minimum total cost and time for 81% TOC removal were determined for the combination of UV₂₅₄/H₂O₂ treatment followed by GAC adsorption, along with desorption of contaminants from GAC using steam and UV₂₅₄/H₂O₂ treatment of the condensed steam. The overall minimum cost and minimum time were found to be $6/L of wastewater treated and 114.5 h, respectively. The treatment parameters and conditions for treating 30 L of the synthetic pharmaceutical wastewater were at an average feed concentration of TOC = 1,755.75 mgC/L and COD = 5,214.6 mg/L leading to TOC = 333.5 mgC/L of the effluent concentration which was near to the industrial effluent disposal level in Canada.

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 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 score0.082
Threshold uncertainty score0.457

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 head0.045
GPT teacher head0.306
Teacher spread0.261 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2021
Admission routes2
Has abstractyes

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