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Record W4376637887 · doi:10.1021/acs.iecr.2c04393

A Comprehensive Review on Pulp and Paper Industries Wastewater Treatment Advances

2023· review· en· W4376637887 on OpenAlex
A Esmaeeli, Mohammad‐Hossein Sarrafzadeh, Siavash Zeighami, Masoud Kalantar, Saeed Ghasemzade Bariki, Alireza Fallahi, Hashem Asgharnejad, Seyed‐Behnam Ghaffari

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

VenueIndustrial & Engineering Chemistry Research · 2023
Typereview
Languageen
FieldEnvironmental Science
TopicAdvanced oxidation water treatment
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsSewage treatmentWastewaterEnvironmental scienceLigninChemical oxygen demandPulp (tooth)PollutantPaper millWaste managementHazardous wastePulp and paper industryAdvanced oxidation processBiochemical engineeringChemical industryChemistryEnvironmental engineeringEffluentEngineering

Abstract

fetched live from OpenAlex

The pulp and paper industry generates vast amounts of wastewater, and its character heavily depends on various factors (raw material, the undertaken process, the final product, etc.). The wastewater from this sector, which originates from several sources in each mill and are mostly combined, is polluting and hazardous. This paper presents a state-of-the-art review of the physical, chemical, biological, and advanced hybrid treatment techniques, concerning their effectiveness in removing specific pollutants, namely, chemical oxygen demand, lignin, color, and adsorbable organo-halogens. Throughout the manuscript, at the end of each section, a conclusive comparison has been presented and the proper method is introduced. Furthermore, numeric data regarding the effectiveness of each technique toward each pollutant are gathered from the literature and are available in the Supporting Information of the paper. Biological treatment processes using anaerobic–aerobic treatment mostly cure organic biodegradable contaminants (75–90% COD removal). Moreover, biological treatment using a consortium of microorganisms can potentially increase color removal efficiency (from 65 to 97%). Hybrid treatment is also among the candidates for color removal. To treat complex matters (lignin and AOX), physical and chemical treatments have shown promising performance, but they are generally expensive and impractical to treat huge amounts of wastewater. For the treatment of high molecular weight contaminants (lignin) advanced oxidation processes (AOPs), including ozonation and Fenton-based treatment, have shown great performance (90–99%); however, they are limited due to their maintenance and operation costs. To overcome these challenges, source separation of the wastewater streams in the pulp and paper industry is recommended. AOPs or membrane technologies or hybrid processes are suggested for the bleaching effluent (80% AOX removal), which is relatively low in amount, and a combination of conventional treatment processes would be preferred to treat wastewater streams that are more biodegradable. The biological performance can also be enhanced using granular activated carbon on the sequence. Finally, for treating black liquor, adsorption processes have proven to be the prime candidate.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.216
GPT teacher head0.403
Teacher spread0.188 · 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