Discussion of Environmental Quality Standards (EQS) and their development for the monitoring of impacts from the use of pesticides and drugs at marine aquaculture sites
Notice bibliographique
Résumé
Environmental Quality Standards (EQS) are numerical thresholds selected to protect ecosystems by limiting the release of a chemical to levels that will not result in irreparable harm or toxicity to sensitive aquatic species. They are an integral part of the design of an effective monitoring program and can have time (dispersion in water for bath pesticides) and spatial notions (allowable zone of deposition for in-feed drugs) embedded in their application process. EQS values exist for water and/or sediment compartments based on the targeted compounds n- Octanol/Water Partition Coefficient (KoW). Water EQS can be divided into two main types: one related to maximum acute chemical (MAC-EQS) exposure and one to chronic exposure (AA EQS). For sediment EQS there is no short-term versus long-term EQS considering the exposure route (i.e., organisms would be constantly exposed while living in the sediment). In this document, we tested a process for EQS value inference for a few in-feed drugs (emamectin benzoate (EMB), ivermectin, teflubenzuron and lufenuron) and pesticides (azamethiphos and hydrogen peroxide) used in Canadian finfish aquaculture operations by relying on relevant and accessible toxicological data. These EQS values are proposed to illustrate the method used for threshold determination and are related to active ingredients. The selection of the final thresholds will have to be guided by the determination of clear management goals to be defined by policy makers. The following points summarize the main approach and recommendations of this working paper: There are two different approaches for EQS setting based on the quality and quantity of available toxicity data: the species sensitivity distributions (SSD) applied when a minimum of ten similar ecotoxicity end-points on a minimum of eight taxonomic groups are available, and the deterministic approach applied in situations where these data requirements are not met (European technical guidance document (CCME, 2007; TGD, 2018). The toxicity data of the in-feed drugs (EMB, ivermectin, teflubenzuron and lufenuron) do not meet the requirements for the completion of SSD (other than lufenuron as per previously completed SSD). Therefore, only a deterministic approach can be used to derive EQS as per the accessible data. This approach was also used for azamethiphos and hydrogen peroxide. However, a recommendation to test the feasibility of a SSD in the future is made for deriving MAC-EQS values with special considerations for dispersion timelines. This step will also have to be guided by inter-departmental regulatory considerations for pesticide usage. Quality assessment of available toxicity studies, both critical and supporting data as determined by regulatory bodies and/or international expert groups, was compiled. In addition, quality assessment of recent studies was completed using the published Criteria for Reporting and Evaluating ecotoxicity (CRED) and supporting guidance (Moermond et al., 2015; TGD, 2018) but will require additional considerations by groups of experts. Adjustments to assessment factors were guided by information on specific mode of action for chemicals such as azamethiphos, ivermectin, teflubenzuron, and lufenuron and whether data on identified sensitive target organisms were available. In addition, the selection of time-relevant toxicological data was also applied in the case of EQS values suggested for azamethiphos based on previous work on dispersion patterns. The EQS values presented in this document illustrate the process employed for their derivation and provide an overview of the toxicity data readily available. Enhanced access to confidential data provided to regulators for marketing authorisation will have to be facilitated to ensure the appropriate derivation of environmental standards. Ultimately, defining clear management goals by policy makers and additional expert discussions will guide the selection of the final EQS thresholds and their regulatory usage.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,017 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,002 | 0,004 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».