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Enregistrement W2292860655 · doi:10.1007/978-3-319-03865-0_4

Exposures of Aquatic Organisms to the Organophosphorus Insecticide, Chlorpyrifos Resulting from Use in the United States

2014· review· en· W2292860655 sur OpenAlexaff
W. M. Williams, Jeffrey M. Giddings, John Purdy, Keith R. Solomon, John P. Giesy

Notice bibliographique

RevueReviews of Environmental Contamination and Toxicology · 2014
Typereview
Langueen
DomaineEnvironmental Science
ThématiquePesticide and Herbicide Environmental Studies
Établissements canadiensUniversity of SaskatchewanUniversity of Guelph
Organismes subventionnairesNanjing UniversityState Administration of Foreign Experts AffairsState Key Laboratory in Marine PollutionChinese Academy of SciencesCity University of Hong Kong
Mots-clésChlorpyrifosEnvironmental scienceAquatic ecosystemStewardship (theology)Environmental chemistryPesticideChemistryEcologyBiology

Résumé

récupéré en direct d'OpenAlex

Concentrations of CPY in surface waters are an integral determinant of risk to aquatic organisms. CPY has been measured in surface waters of the U.S. in several environmental monitoring programs and these data were evaluated to characterize concentrations, in relation to major areas of use and changes to the label since 2001, particularly the removal of domestic uses. Frequencies of detection and 95th centile concentrations of CPY decreased more than fivefold between 1992 and 2010. Detections in 1992-2001 ranged from 10.2 to 53%, while 2002-2010 detections ranged from 7 to 11%. The 95th centile concentrations ranged from 0.007 to 0.056 j.lg L -I in 1992-2001 and 0.006-0.008 j.lg L -I in 2002-2010.The greatest frequency of detections occurred in samples from undeveloped and agricultural land-use classes. Samples from urban and mixed land-use classes had the smallest frequency of detections and 95th centile concentrations, consistent with the cessation of most homeowner uses in 2001. The active metabolite of CPY, CPYO, was not detected frequently or in large concentrations. In 10,375 analyses from several sampling programs conducted between 1999 and 2012, only 25 detections (0.24% of samples) of CPYO were reported and estimated concentrations were less than the LOQ.Although the monitoring data on CPY provide relevant insight in quantifying the range of concentrations in surface waters, few monitoring programs have sampled at a frequency sufficient to quantify the time-series pattern of exposure. Therefore,numerical simulations were used to characterize concentrations of CPY in water and sediment for three representative high exposure environments in the U.S. Thefate of CPY in the environment is dependent on a number of dissipation and degradation processes. In terms of surface waters, fate in soils is a major driver of the potential for runoff into surface waters and results from a number of dissipation studies in the laboratory were characterized. Aerobic degradation of CPY exhibits hi-phasic behavior in some soils; initial rates of degradation are greater than overal rates by factors of up to threefold. Along with fate in water, these data were considered in selecting parameters for the modeling concentrations in surface waters. An assessment of vulnerability to runoff was conducted to characterize the potential for CPY to be transported beyond a treated field in runoff water and eroded sediment across the conterminous U.S. A sensitivity analysis was performed on use practices of CPY to determine conditions that resulted in the highest potential runoff of CPY to aquatic systems to narrow the application practices and geographical areas of the country for selecting watersheds for detailed modeling. The selected focus-watersheds were Dry Creek in Georgia (production of pecans), Cedar Creekin Michigan (cherries), and Orestimba Creek in California (intensive agricultural uses). These watersheds provided realistic but reasonable worst-case predictions of concentrations of CPY in water and sediment.Estimated concentrations of CPY in water for the three watersheds were in general agreement with ambient monitoring data from 2002 to 20 I 0 in the datasets from US Geological Survey (USGS), California Department of Pesticide Regulation(CDPR), and Washington State Department of Ecology (WDOE). Maximum daily concentrations predicted for the watershed in California, Georgia, and Michigan were 3.2, 0.04 I, and 0.073 Jlg L -I, respectively, with the 28-d aerobic soil metabolism half-life and 4.5, 0.042, and 0. I 22 Jlg L - 1, respectively, with the 96-d soil halflife.These estimated values compared favorably with maximum concentrations measured in surface water, which ranged from 0.33 to 3.96 Jlg L -1• For sediments,the maximum daily concentrations predicted for the watersheds in California,Georgia, and Michigan were I 1.2, 0.077, and 0.058 Jlg kg-1, respectively, with the 28-d half-life and 22.8, 0.080, and 0.087 Jlg kg-1, respectively, with the 96-d soil half-life. CYP was detected in 12 samples (I 0%) out of 123 sample analyses that existed in the USGS, CDPR, and WDOE databases. The concentrations reported in these detections were from <2.0, up to 19 Jlg kg- 1, with the exception of one value reported at 58.6 Jlg kg- 1• Again, the modeled values compared favorably with these measured values. Duration and recovery intervals between toxicity threshold concentrations of 0.1 and 1.0 Jlg L - 1 were also computed. Based on modeling with the half-life of 28 d, no exceedance events were identified in the focus watersheds in Georgia or Michigan. Using the half-life of 96 d, only three events of 1-d duration only were identified in the Michigan focus-watershed. Frequency of exceedancc was greater in the California focus watershed, though the median duration was only I -d.

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.

Comment cette classification a été obtenuedéplier

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)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Autre devis · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,974
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
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 Opus0,041
Tête enseignante GPT0,284
Écart entre enseignants0,243 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeAutre devis
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations42
Publié2014
Routes d'admission1
Résumé présentoui

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