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Revisiting chloroform emissions from the pulp and paper sector: a brief communication

2025· preprint· en· W4413187832 on OpenAlexaboutno aff
Andrea Mazzeo, Ryan Hossaini

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsnot available
FundersNatural Environment Research Council
KeywordsChloroformPulp (tooth)Pulp and paper industryPetroleum engineeringBusinessEngineeringChemistryDentistryChromatographyMedicine

Abstract

fetched live from OpenAlex

Halogenated Very Short-Lived Substances (VSLS) represent a growing source of chlorine to the stratosphere where they may contribute to ozone layer depletion. Chloroform (CHCl3) is a prominent VSLS with poorly constrained anthropogenic sources that include its unintentional production when wood pulp is bleached for paper production. Recent assessments of the global CHCl3 budget have relied on emission factors (EFs) for the pulp/paper sector derived some 35 years ago when industrial practices where markedly different. Here, we analysed data from the Pollutant Release and Transfer Registers of the USA, Canada and Japan. Combined with data on the national number of pulp mills and bleached wood pulp production volume, we derive plausible lower and upper limit EFs. These factors show a downward trend since the early 2000s which we attribute to a continued phase-down in the use of 'elemental chlorine' bleaching in favour of 'elemental chlorine free' bleaching. The derived mean EFs for the period 2000 to 2020, expressed as mass of CHCl3 per air-dried tons of (adt) of bleached pulp, are in close agreement for the regions considered: USA (39.8 ±32 g/adt), Canada (38.6 ±29.8 g/adt) and Japan (30.1 ± 8.6 g/adt). Assuming these factors are broadly representative of other world regions, a mean annual global CHCl3 source of 3 (1-6) Gg/yr from the pulp/paper sector is estimated for the approximate 2000 to 2020 period. We conclude the sector's contribution to the global CHCl3 budget has likely decreased considerably since the 1990s and that the use of older EFs to calculate present day emissions should be avoided.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.944
Threshold uncertainty score0.863

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.273
Teacher spread0.250 · 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 designNot applicable
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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