Abstract
Despite the significant benefits of aquatic passive sampling (low detection limits and time-weighted average concentrations), the use of passive samplers is impeded by uncertainties, particularly concerning the accuracy of sampling rates. This study employed a systematic evaluation approach based on the combination of meta-analysis and quantitative structure-property relationships (QSPR) models to address these issues. A comprehensive meta-analysis based on extensive data from 298 studies on the Polar Organic Chemical Integrative Sampler (POCIS) identified essential configuration parameters, including the receiving phase (type, mass) and the diffusion-limiting membrane (type, thickness, pore size), as key factors influencing uptake kinetic parameters. The incomplete availability of these details across studies potentially impacts data reproducibility and comparability. The subsequent meta-regression and subgroup analysis were performed to reveal the most significant factors contributing to sampling rate variability and inter-study heterogeneity. The flow rate and octanol-water partitioning (Kow or pH-dependent Dow) were identified from all environmental factors and chemical properties. Furthermore, the impact of chemical properties on the sampling rates of POCIS was predicted by Quantitative Structure-Property Relationship (QSPR) models using 2D descriptors and random forest regression. The analysis highlighted that the electrotopological state and molecular mass are the most important chemical properties influencing the sampling rate. This study systematically unraveled the most important impact factors on reliable estimates of passive sampling rates, and these causes of uncertainty should be further considered in aquatic monitoring and assessment with passive samplers.
Published Version
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