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Record W4229458315 · doi:10.1021/acs.est.2c00264

Global Historical Production, Use, In-Use Stocks, and Emissions of Short-, Medium-, and Long-Chain Chlorinated Paraffins

2022· article· en· W4229458315 on OpenAlexaff
Chengkang Chen, Anna Chen, Faqiang Zhan, Frank Wania, Shaoxuan Zhang, Li Li, Jianguo Liu

Bibliographic record

VenueEnvironmental Science & Technology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersState Key Joint Laboratory of Environmental Simulation and Pollution Control
KeywordsChlorinated paraffinsEnvironmental scienceProduction (economics)Chain (unit)Waste managementEnvironmental chemistryChemistryEnvironmental protectionEconomicsEngineeringOrganic chemistry

Abstract

fetched live from OpenAlex

The last few decades have seen ubiquitous and increasing contamination of chlorinated paraffins (CPs) worldwide. Here, we develop the first global inventories of production, use, in-use stocks, and emissions of total CPs, including the short-, medium- and long-chain components (SCCPs, MCCPs, and LCCPs) during 1930-2020 using a dynamic substance flow analysis model named Chemical in Products Comprehensive Anthroposhpheric Fate Estimation. The model estimates that a total of ∼33 million metric tons of CPs have been produced and used globally, ∼40% of which still resided in in-use products by 2020 and is available for long-term emissions in the next decades. Global cumulative emissions of CPs have increased to ∼5.2 million metric tons by 2020, with SCCPs, MCCPs, and LCCPs accounting for ∼30, 40, and 30%, respectively. While the production, use, and emissions of CPs started declining in regions such as Western Europe, they remain high in China. The model also suggests that homologues with 10, 14, and 22-23 carbons were predominant in the cumulatively produced and emitted SCCPs, MCCPs, and LCCPs, respectively. The emission estimates were evaluated by generating environmental concentrations that are comparable to literature-reported environmental monitoring data. Our estimates provide opportunities to link the environmental fate and occurrence of CPs to emission sources and lay the basis for future risk-reduction strategies of CPs around the world.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.003
Scholarly communication0.0000.001
Open science0.0000.002
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 head0.011
GPT teacher head0.224
Teacher spread0.213 · 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.

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

Citations144
Published2022
Admission routes1
Has abstractyes

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