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MPT-PFAS-sampling-rates

Microporous polyethylene tube (MPT) passive sampler. Jupyter notebooks used to re-evaluate MPT PFAS sampling rates from five field campaigns. Associated publication:

tbd

sampling_rates.py

This python class initializes PFAS-specific physicochemical parameters and defines all core functions used to model PFAS transport through microporous polyethylene tube (MPT) passive samplers. Implemented functionality includes calculation of PFAS diffusion coefficients in water, estimation of sampling rates, and determination of times to half-equilibrium.

The functions defined in this module are used by downstream notebooks to evaluate field-derived and modeled sampling rates.

combine_data.ipynb

This notebook processes and cleans data from MPT passive sampler field deployments conducted across five independent studies. The studies are labeled by principal investigator and field site:

  • CG_RI: Christine Gardiner — Narragansett Bay, Rhode Island
  • JS_DU: Jarod Snook — Duluth, Minnesota
  • JS_ME: Jarod Snook — Maine
  • MD_CC: Matthew Dunn — Cape Cod, Massachusetts
  • MD_WE: Matthew Dunn — Westerly, Rhode Island

Instructions on where to locate the data for each study are provided in the README files within the corresponding subfolders. The associated compiled dataset is also available on Harvard Dataverse:

  • Ganglbauer, J.; Dunn, M.; Snook, J.; Becanova, J.; & Lohmann, R. 2025. PFAS Sampling Rates in Microporous Polyethylene Tube Samplers. Harvard Dataverse. https://doi.org/10.7910/DVN/DAH1SO.

The notebook generates two cleaned, compiled CSV files:

  • grab_samples.csv — PFAS concentrations measured in grab water samples
  • pe_tube.csv — PFAS measurements and derived parameters from MPT field deployments across all studies

create_plots.ipynb

This notebook reads the compiled CSV files generated by combine_data.ipynb and performs downstream analysis and visualization. Specifically, it:

  • generates plots for data exploration and interpretation,
  • conducts statistical analyses, including ANOVA, MANOVA, and PCA, to assess the relevance of different predictor variables, and
  • applies curve fitting (exponential and inverse linear) and summary statistics (mean and standard deviation) to derive PFAS sampling rates from field campaign data.

The notebook also imports reference sampling rate data from four additional studies (hard-coded):

  • Kaserzon, S. L.; Vijayasarathy, S.; Bräunig, J.; Mueller, L.; Hawker, D. W.; Thomas, K. V.; Mueller, J. F.
    Calibration and validation of a novel passive sampling device for the time integrative monitoring of per- and polyfluoroalkyl substances (PFASs) and precursors in contaminated groundwater.
    Journal of Hazardous Materials, 2019, 366, 423–431.

  • Mackie, R.; Hawker, D. W.; Ghorbani Gorji, S.; Booij, K.; Qu, X.; Bowles, K.; Shea, S.; Higgins, C. P.; Kaserzon, S.
    Application of a Microporous Polyethylene Tube Passive Sampler for Monitoring Per- and Polyfluoroalkyl Substances in Wastewater Influent and Effluent.
    ACS ES&T Water, 2024, 4, 2281–2291.

  • Beggs, C.; Mackie, R.; Vrana, B.; Prokeš, R.; Gorji, S. G.; Schulze, B.; Thomas, K. V.; Mueller, J. F.; Kaserzon, S. L.
    Estimation of per- and polyfluoroalkyl substances mass loads in the Danube River using passive sampling.
    Science of the Total Environment, 2023, 892, 164458.

  • Soriano, Y.; Alvarez-Ruiz, R.; Clokey, J. E.; Gorji, S. G.; Kaserzon, S. L.; Picó, Y.
    Determination of organic contaminants in L’Albufera Natural Park using microporous polyethylene tube passive samplers: An environmental risk assessment.
    Science of the Total Environment, 2023, 903, 166594.

The notebook generates two cleaned, compiled CSV files:

  • parameters_ground.csv — Sampling rates and water boundary layer transport coefficients for groundwater deployments from field campaigns and reference studies.

  • parameters_fresh_salt.csv — Sampling rates for freshwater and saltwater deployments (mean values and two fitting approaches), reference values, and values derived from the physical model. The file also includes performance metrics (R², MAE, RMSE) and coefficients of variation.

Contact

johanna.ganglbauer@uri.edu

Ackknowledgement

This work is supported by the National Institute of Environmental Health under grant P42ES027706 in superfund research project Sources, Transport, Exposure & Effects of PFAS (STEEP).

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