Investigating predictive tools for refinery effluent hazard assessment using stream mesocosms

Kevin Cailleaud, Anne Bassères, Clémentine Gelber, Jaap F. Postma, Anneke T.M. ter Schure, Pim E.G. Leonards, Aaron D. Redman, Graham F. Whale, Mike J. Spence, Markus Hjort*

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review


Hazard assessment of refinery effluents is challenging because of their compositional complexity. Therefore, a weight-of-evidence approach using a combination of tools is often required. Previous research has focused on several predictive tools for sophisticated chemical analyses: biomimetic extraction to quantify the potentially bioaccumulative substances, 2-dimensional gas chromatography, modeling approaches to link oil composition to toxicity (PETROTOX), and whole-effluent toxicity assessments using bioassays. The present study investigated the value of these tools by comparing predicted effects to actual effects observed in stream mesocosm toxicity studies with refinery effluents. Three different effluent samples, with and without fortification by neat petroleum substances, were tested in experimental freshwater streams. The results indicate that the biological community shifted at higher exposure levels, consistent with chronic toxicity effects predicted by both modeled toxic units and potentially bioaccumulative substance measurements. The present study has demonstrated the potential of the predictive tools and the robustness of the stream mesocosm design to improve our understanding of the environmental hazards posed by refinery effluents. Environ Toxicol Chem 2019;38:650–659.

Original languageEnglish
Pages (from-to)650-659
Number of pages10
JournalEnvironmental toxicology and chemistry
Issue number3
Early online date19 Dec 2018
Publication statusPublished - Mar 2019


  • Biomimetic extraction
  • Mesocosms
  • Refinery effluents


Dive into the research topics of 'Investigating predictive tools for refinery effluent hazard assessment using stream mesocosms'. Together they form a unique fingerprint.

Cite this