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Comparison of species sensitivity distribution modeling approaches for environmental risk assessment of nanomaterials - A case study for silver and titanium dioxide representative materials

Sorensen, S.N. und Wigger, Henning und Zabeo, A. und Semenzin, E. und Hristozov, D. und Nowack, B. und Spurgeon, D.J. und Baun, A. (2020) Comparison of species sensitivity distribution modeling approaches for environmental risk assessment of nanomaterials - A case study for silver and titanium dioxide representative materials. Aquatic Toxicology, 225, Seite 105543. Elsevier. doi: 10.1016/j.aquatox.2020.105543. ISSN 0166-445X.

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Offizielle URL: https://www.sciencedirect.com/science/article/abs/pii/S0166445X20302939#!

Kurzfassung

Species sensitivity distributions (SSDs) are used in chemical safety assessments to derive predicted-no-effect-concentrations (PNECs) for substances with a sufficient amount of relevant and reliable ecotoxicity data available. For engineered nanomaterials (ENMs), ecotoxicity data are often compromised by poor reproducibility and the lack of nano-specific characterization needed describe an ENM under test exposure conditions. This may influence the outcome of SSD modelling and hence the regulatory decision-making. This study investigates how the outcome of SSD modelling is influenced by: 1) Selecting input data based on the nano-specific “nanoCRED” reliability criteria, 2) Direct SSD modelling avoiding extrapolation of data by including long-term/chronic NOECs only, and 3) Weighting data according to their nano-specific quality, the number of data available for each species, and the trophic level abundance in the ecosystem. Endpoints from freshwater ecotoxicity studies were collected for the representative nanomaterials NM-300 K (silver) and NM-105 (titanium dioxide), evaluated for regulatory reliability and scored according to the level of nano-specific characterization conducted. The compiled datasets are unique in exclusively dealing with representative ENMs showing minimal batch-to-batch variation. The majority of studies were evaluated as regulatory reliable, while the degree of nano-specific characterization varied greatly. The datasets for NM-300 K and NM-105 were used as input to the nano-weighted n-SSWD model, the probabilistic PSSD+, and the conventional SSD Generator by the US EPA. The conventional SSD generally yielded the most conservative, but least precise HC5 values, with 95 % confidence intervals up to 100-fold wider than the other models. The inclusion of regulatory reliable data only, had little effect on the HC5 generated by the conventional SSD and the PSSD+, whereas the n-SSWD estimated different HC5 values based on data segregated according to reliability, especially for NM-105. The n-SSWD weighting of data significantly affected the estimated HC5 values, however in different ways for the sub-datasets of NM-300 K and NM-105. For NM-300 K, the inclusion of NOECs only in the weighted n-SSWD yielded the most conservative HC5 of all datasets and models (a HC5 based on NOECs only could not be estimated for NM-105, due to limited number of data). Overall, the estimated HC5 values of all models are within a relatively limited concentration range of 25−100 ng Ag/L for NM-300 K and 1−15 μgTiO2/L for NM-105.

elib-URL des Eintrags:https://elib.dlr.de/139670/
Dokumentart:Zeitschriftenbeitrag
Titel:Comparison of species sensitivity distribution modeling approaches for environmental risk assessment of nanomaterials - A case study for silver and titanium dioxide representative materials
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Sorensen, S.N.Department of Environmental Engineering, Technical University of Denmark, Bygningstorvet, Building 115, DK-2800 Kgs., Lyngby, DenmarkNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Wigger, HenningHenning.Wigger (at) dlr.dehttps://orcid.org/0000-0002-0610-0067NICHT SPEZIFIZIERT
Zabeo, A.GreenDecision, Via delle Industrie 21/8, 30175, Marghera, Venice, ItalyNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Semenzin, E.Department of Environmental Sciences, Informatics and Statistics, University Ca' Foscari Venice, Via delle Industrie 21/8, 30175, Marghera, Venice, ItalyNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Hristozov, D.GreenDecision, Via delle Industrie 21/8, 30175, Marghera, Venice, ItalyNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Nowack, B.Empa – Swiss Federal Laboratories for Materials Science and Technology, Technology and Society Laboratory, CH-9014, St. Gallen, SwitzerlandNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Spurgeon, D.J.Centre for Ecology and Hydrology, Library Avenue, Bailrigg, Lancaster, LA1 4AP, UKNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Baun, A.Department of Environmental Engineering, Technical University of Denmark, Bygningstorvet, Building 115, DK-2800 Kgs., Lyngby, DenmarkNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:12 Juni 2020
Erschienen in:Aquatic Toxicology
Referierte Publikation:Ja
Open Access:Nein
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:225
DOI:10.1016/j.aquatox.2020.105543
Seitenbereich:Seite 105543
Verlag:Elsevier
ISSN:0166-445X
Status:veröffentlicht
Stichwörter:Nanoecotoxicology Regulatory reliability Data weighting Risk assessment PNEC
HGF - Forschungsbereich:Energie
HGF - Programm:TIG Technologie, Innovation und Gesellschaft
HGF - Programmthema:Erneuerbare Energie- und Materialressourcen für eine nachhaltige Zukunft
DLR - Schwerpunkt:Energie
DLR - Forschungsgebiet:E SY - Energiesystemanalyse
DLR - Teilgebiet (Projekt, Vorhaben):E - Systemanalyse und Technikbewertung (alt)
Standort: Oldenburg
Institute & Einrichtungen:Institut für Vernetzte Energiesysteme > Energiesystemanalyse
Hinterlegt von: Wigger, Dr. Henning
Hinterlegt am:16 Dez 2020 11:49
Letzte Änderung:20 Jun 2021 15:54

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