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Enregistrement W4210977565 · doi:10.1186/s13750-017-0114-y

What is the effect of phasing out long-chain per- and polyfluoroalkyl substances on the concentrations of perfluoroalkyl acids and their precursors in the environment? A systematic review

2018· review· en· W4210977565 sur OpenAlex

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Notice bibliographique

RevueEnvironmental Evidence · 2018
Typereview
Langueen
DomaineEnvironmental Science
ThématiquePer- and polyfluoroalkyl substances research
Établissements canadiensUniversity of Alberta
Organismes subventionnairesStockholms UniversitetUniversity of AlbertaStiftelsen för Miljöstrategisk Forskning
Mots-clésPerfluorooctanePerfluorooctanoic acidHuman healthNarrative reviewStakeholderEnvironmental healthEnvironmental scienceSulfonateEnvironmental chemistryChemistryPsychologyMedicinePolitical scienceOrganic chemistry

Résumé

récupéré en direct d'OpenAlex

Abstract Background There is a concern that continued emissions of man-made per- and polyfluoroalkyl substances (PFASs) may cause environmental and human health effects. Now widespread in human populations and in the environment, several PFASs are also present in remote regions of the world, but the environmental transport and fate of PFASs are not well understood. Phasing out the manufacture of some types of PFASs started in 2000 and further regulatory and voluntary actions have followed. The objective of this review is to understand the effects of these actions on global scale PFAS concentrations. Methods Searches for primary research studies reporting on temporal variations of PFAS concentrations were performed in bibliographic databases, on the internet, through stakeholder contacts and in review bibliographies. No time, document type, language or geographical constraints were applied in the searches. Relevant subjects included human and environmental samples. Two authors screened all retrieved articles. Dual screening of 10% of the articles was performed at title/abstract and full-text levels by all authors. Kappa tests were used to test consistency. Relevant articles were critically appraised by four reviewers, with double checking of 20% of the articles by a second reviewer. Meta-analysis of included temporal trends was considered but judged to not be appropriate. The trends were therefore discussed in a narrative synthesis. Results Available evidence suggests that human concentrations of perfluorooctane sulfonate (PFOS), perfluorodecane sulfonate (PFDS), and perfluorooctanoic acid (PFOA) generally are declining, while previously increasing concentrations of perfluorohexane sulfonate (PFHxS) have begun to level off. Rapid declines for PFOS-precursors (e.g. perfluorooctane sulfonamide, FOSA) have also been consistently observed in human studies. In contrast, limited data indicate that human concentrations of PFOS and PFOA are increasing in China where the production of these substances has increased. Human concentrations of longer-chained perfluoroalkyl carboxylic acids (PFCAs) with 9–14 carbon atoms are generally increasing or show insignificant trends with too low power to detect a trend. For abiotic and biological environmental samples there are no clear patterns of declining trends. Most substances show mixed results, and a majority of the trends are insignificant with low power to detect a trend. Conclusions For electrochemically derived PFASs, including PFOS and PFOA, most human studies in North America and Europe show consistent statistically significant declines. This contrasts with findings in wildlife and in abiotic environmental samples, suggesting that declining PFOS, PFOS-precursor and PFOA concentrations in humans likely resulted from removal of certain PFASs from commercial products including paper and board used in food packaging. Increasing concentrations of long-chain PFCAs in most matrices, and in most regions, is likely due to increased use of alternative PFASs. Continued temporal trend monitoring in the environment with well-designed studies with high statistical power are necessary to evaluate the effectiveness of past and continuing regulatory mitigation measures. For humans, more temporal trend studies are needed in regions where manufacturing is most intense, as the one human study available in China is much different than in North America or Europe.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Études des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,689
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0040,000
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,003
Communication savante0,0000,001
Science ouverte0,0020,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,038
Tête enseignante GPT0,315
Écart entre enseignants0,278 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle