Robustness of Indoor Aquatic Mesocosm Experimentations and Data Reusability to Assess the Environmental Risks of Nanomaterials

Mohammad Nassar,Armand Masion,Catherine Santaella,Mélanie Auffan,Jérôme Rose

doi:10.3389/fenvs.2021.625201

Abstract

Indoor aquatic mesocosms are increasingly used in nanosafety to assess the behavior, fate, and impacts of engineered nanomaterials (ENMs) in aquatic environments using relevant exposure scenarios. The robustness of 60 L freshwater mesocosm experimentation was tested on the basis of the reusability of the data collected in a database named MESOCOSM regarding mesocosm experiments examining the environmental risks of CeO2 ENMs. We observed high reliability of the measured variables across replicates. The sensitivity of this mesocosm methodology was evidenced by the contrasted ecosystem responses revealed by a multivariate analysis. We also observed that adding variables to the data set up to 15% did not affect the outcome of the analysis of the results. This ability to buffer this variability demonstrates that the indoor aquatic mesocosms are robust tools contributing to the environmental risk assessment of ENMs, and stresses the benefit of reusing the data stored in databases such as MESOCOSM adhering to the findable, accessible, interoperable, reusable (FAIR) data principles.

Highlights

The current strategies to assess the environmental safety of engineered nanomaterials (ENMs) are often based on standardized hazard-driven nano-ecotoxicological approaches (Kahru and Dubourguier, 2010; Skjolding et al, 2016; Lead et al, 2018)
The data selected for the multivariate analysis in this present work regard experiments performed in freshwater indoor mesocosms contaminated with CeO2 ENMs (Tella et al, 2014; Tella et al, 2015) and were extracted from the publicly available MESOCOSM database (Ayadi et al, 2021)
Using Procrustes analysis, we showed that data generated using analysis of covariance (ANCOVA) better reproduced the original measurements (m2 0.3) than those calculated by nonlinear iterative partial least squares (NIPALS) and Markov chain Monte Carlo (MCMC), which generated less accurate data (m2 0.95)

Summary

Introduction

The current strategies to assess the environmental safety of engineered nanomaterials (ENMs) are often based on standardized hazard-driven nano-ecotoxicological approaches (Kahru and Dubourguier, 2010; Skjolding et al, 2016; Lead et al, 2018). The data selected for the multivariate analysis in this present work regard experiments performed in freshwater indoor mesocosms contaminated with CeO2 ENMs (Tella et al, 2014; Tella et al, 2015) and were extracted from the publicly available MESOCOSM database (Ayadi et al, 2021).

Results

Conclusion