SLIDE 1
Advancing the use of passive sampling in risk assessment and management of contaminated sediments: Results of an international passive sampling ring test
Michiel T.O. Jonker, Stephan van der Heijden, Yongju Choi, Yanwen Wu, Loretta Fernandez, Robert M. Burgess, Upal Ghosh, Mehregan Jalalizadeh, Jennifer Apell, Phil Gschwend, Rainer Lohmann, Mohammed Khairy, Dave Adelman, Michael Lydy, Samuel Nutile, Amanda Harwood, Keith Maruya, Wenjian Lao, Amy Oen, Sarah Hale, Danny Reible, Magdalena Rakowska, Foppe Smedes, and Mark Lampi
SLIDE 2 Acknowledgments
Cefic-LRi; ECO22 project
Bruno Hubesch Mark Lampi
ILSI-HESI
Michelle Embry
ECETOC
Malyka Galay Burgos
Various funding agencies participants
SLIDE 3 Background (1)
- Numerous sediments & soils are contaminated with organic contaminants,
such as PAHs & PCBs
- Current risk assessment based on total, solvent-extractable concentrations
- Not the total, but only the ‘bioavailable’ concentration is available for
uptake in organisms and causing effects
- Improved risk assessment (less false positives) is possible, based on
bioavailable concentrations
SLIDE 4 Background (2)
- Several methods have been developed for measuring bioavailable
concentrations
- Most attention currently paid to ‘passive sampling’, i.e., using polymer
samplers to determine ‘freely dissolved concentrations’ in sediments/soils
- Passive sampling is a mature technique in science, but not yet fully
accepted in the regulatory community: there is no scientific consensus on which technique to apply (range of methods available)
- Need for:
- Scientific consensus: comparison study of different methods
- Information on robustness (variability/accuracy)
- Standardization of method(s)
SLIDE 5 Objectives
- Map the state of the science of passive sampling (performance) in
sediments: Quantify intermethod and interlab variability
- Investigate how any (unacceptable) variation can be reduced
- Recommend standard method(s)
SLIDE 6 Setup (1)
General setup
- 11 labs participating in ring test; 1 coordinating lab (UU)
- 14 passive sampling formats
- 3 different sediments
- 25 target compounds
SLIDE 7 Participants
- Established track record in passive sampling with sediments
- Netherlands, Norway, Czech Republic, Korea, USA
Setup (2)
SLIDE 8 Setup (3)
Passive sampling formats
- Polyethylene (PE): 6 suppliers; 2 thicknesses (25 and 50 µm)
- Polydimethylsiloxane (PDMS): 5 different SPME fibers (suppliers and
coating thicknesses – 10, 30, 100 µm)
- Polyoxymethylene (POM): 2 suppliers and 3 thicknesses (17, 55, 77 µm)
- Polyacrylate (PAc): 30 µm coated SPME fibers
- Silicone rubber (SSP): 100 µm thickness
SLIDE 9 Compounds
- 13 PAHs (3-6 rings) and 12 PCBs (tri- to heptachlorinated)
- Range in hydrophobicity, partitioning behavior, freely dissolved concs
Setup (4)
SLIDE 10 Setup (5)
Sediments 3 sediments differing in complexity: 1. Spiked sediment (SP): high concentrations spiked; low background; sandy; TOC=1.4 2. Field contaminated sediment (Dutch; Biesbosch area; BB): homogeneous; low concentrations PAHs and PCBs; TOC=4.3 3. ‘Composed’ sediment (FD): 2 field sediments mixed.
- French, sandy sediment; low-high PCB
levels (no PAHs)
- Dutch, clayey sediment; moderate PAH
levels (no PCBs); NAPLs (diesel) present; TOC=2.3
SLIDE 11 Setup (6)
Experiments 1. ‘Own procedure’: Participants followed their own approach 2. ‘Standardized procedure’: Participants followed standard protocols (UU) 3. Standardized procedure, but extracts analyzed by UU 4. ‘All @ UU’: all 14 formats applied (standardized) and analyzed by UU 5. Additional tests:
- analysis of analytical standard and weighing test (all participants)
- solvent extraction and recovery tests, homogeneity test (UU)
- Partition coefficients (Kpw’s) for all compd’s and polymers (UU)
SLIDE 12 Results (1)
- 1. Own procedure (State of the science in passive sampling)
Without PCB-77
Chemical-averaged variation range factor (95% percentile / 5% percentile)
10 29 9 10 9 BB FD SP
All chemicals
SLIDE 13 Results (2)
- 1a. Own procedure (Effect of standardizing Kpw’s)
BB FD SP
Without PCB-77
Chemical-averaged variation range factor (95% percentile / 5% percentile)
12 21 10 10 9
All chemicals
SLIDE 14 Results (3)
- 2. Standard procedure (Effect of standardizing protocols & Kpw’s)
BB FD SP
Without PCB-77
Chemical-averaged variation range factor (95% percentile / 5% percentile)
7 9 4 4 5
All chemicals
SLIDE 15 Results (4)
- 3. Standard procedure, analyzed @ UU (Impact of analytical
chemistry)
BB FD SP
Chemical-averaged variation range factor (95% percentile / 5% percentile)
2.4 2.4 2.6
SLIDE 16
Results (5)
Standard analytical solution
2.8
Averaged variation range factor (95% percentile / 5% percentile)
SLIDE 17 Results (6)
- 4. All @ UU (Intermethod variation)
BB FD SP
Chemical-averaged variation range factor (95% percentile / 5% percentile)
1.6 1.7 1.7
SLIDE 18
Summary (BB sediment)
Intralab / intermethod Interlab + intermethod
protocol s
1.6 10 10 4 2.4
Kpw analytics
SLIDE 19 Conclusions
- Variation in passive sampling results (current practice) is rather (too) large
- Important contribution to the variation by analytical chemistry!
Identification, integration, calibration
- Variation can be significantly reduced by standardizing protocols
Standardization: polymer washing procedures, polymer/sediment ratio, sediment/water ratio, way and time of mixing, extraction solvent and procedure
- Standardizing Kpw’s does not reduce variation, but is essential for precision of
Cfree
- Different polymers yield very similar results: Intermethod variability is small
(within a factor of 1.6)
- Passive sampling is a robust method - ready for use within regulatory
applications, provided that standard protocols are used and analytical chemistry is quality controlled
SLIDE 20