Development of quantitative structure-property relationship model for predicting the field sampling rate (Rs) of Chemcatcher passive sampler

  • Yaqi Wang
  • Huihui LiuEmail author
  • Xianhai YangEmail author
Research Article


Passive sampling technology has been considered as a promising tool to measure the concentration of environmental contaminants. With this technology, sampling rate (Rs) is an important parameter. However, as experimental methods employed to obtain the Rs value of a given compound were time-consuming, laborious, and expensive. A cost-effective method for deriving Rs is urgent. In addition, considering the great dependence of Rs value on water matrix properties, the laboratory measured Rs may not be a good alternative for field Rs. Thus, obtaining the field Rs is very necessary. In this study, a multiparameter quantitative structure-property relationship (QSPR) model was constructed for predicting the field Rs of 91 polar to semi-polar organic compounds. The determination coefficient (R2Train), leave-one-out cross-validated coefficient (Q2LOO), bootstrap coefficient (Q2BOOT), and root mean square error (RMSETrain) of the training set were 0.772, 0.706, 0.769, and 0.230, respectively, while the external validation coefficient (Q2EXT) and RMSEEXT of the validation set were 0.641 and 0.253, respectively. According to the acceptable criteria (Q2 > 0.600, R2 > 0.700), the model had good robustness, goodness-of-fit, and predictive performances. Therefore, we could use the model to fill the data gap for substances within the applicability domain on their missing Rs value.


Field sampling rate (RsPassive sampling Chemcatcher Quantitative structure-property relationship (QSPR) Applicability domain 



The study was supported by National Natural Science Foundation of China (No. 41671489, No. 21507038, No. 21507061).

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The transparency document associated with this article can be found in the online version.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

11356_2020_7616_MOESM1_ESM.docx (31 kb)
ESM 1 (DOCX 31 kb)


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2020

Authors and Affiliations

  1. 1.Key Laboratory of New Membrane Materials, Ministry of Industry and Information Technology, School of Environmental and Biological EngineeringNanjing University of Science and TechnologyNanjingChina

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