Comparative field study on bioassay responses and micropollutant uptake of POCIS, Speedisk and SorbiCell polar passive samplers

Routine water quality monitoring is generally performed with chemical analyses of grab samples, which has major limitations. First, snapshot samples will not give a good representation of the water quality. Second, it is not sufficient to analyze only a limited number of (priority) pollutants. These limitations can be circumvented by an alternative environmental risk assessment that combines time-integrated passive sampling (PS) with effect based methods. This study aimed to select which of three polar PS devices was best suited for effect-based monitoring strategies. In the first part of this study, Speedisk, SorbiCell and POCIS polar PS devices were compared by simultaneous deployment at five sites. Chemical analyses of 108 moderately polar compounds (-1.82 < log D < 6.28) revealed that highest number of compounds, with the widest range of log KOW, log D and pKa, were detected in extracts of POCIS, followed by Speedisk. SorbiCell samplers accumulated the lowest numbers and concentrations of compounds, so they were not further investigated. In a follow-up study, bioassay responses were compared in extracts of POCIS and Speedisk devices deployed at eight sites. The passive sampler extracts were subjected to bioassays for non-specific toxicity, endocrine disruption, and antibiotics activities. More frequent and higher responses were induced by POCIS extracts, leading to more exceedances of effect-based trigger values for environmental risks. As POCIS outperformed Speedisk, it is better suited as PS device targeting polar compounds for semi quantitative effect-based water quality monitoring.

Automated summary

This study compared three polar passive sampling (PS) devices - Speedisk, SorbiCell, and POCIS - for effect-based water quality monitoring. Chemical analysis and bioassay responses showed that POCIS outperformed Speedisk in detecting a wider range of polar compounds, making it better suited for semi-quantitative effect-based monitoring strategies.