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Supplemental Materials
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For
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Assessing Organic Contaminant Fluxes from Contaminated Sediments Following Dam
Removal in an Urbanized River.
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Mark G. Cantwell*1, Monique M. Perron2, Julia C. Sullivan3, David R. Katz1, Robert M.
Burgess1, John King4
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02882 USA
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USA
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Oak Ridge Institute for Science and Education, Narragansett, RI 02882 USA
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University of Rhode Island, Graduate School of Oceanography, Narragansett, RI 02882 USA
U.S. Environmental Protection Agency, Office of Research and Development, Narragansett, RI
U.S. Environmental Protection Agency, Office of Pesticide Program, Washington, DC 20460
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*Corresponding author; cantwell.mark@epa.gov; Phone 401.782.9604; Fax 401.782.3030
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Passive sampler theory and methodology. Measuring dissolved concentrations of organic
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contaminants can be challenging due to their relatively low solubilities and affinity to associate with
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particles in the water column (Farrington et al., 1983). In recent years, passive sampling has become a
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widely used technique for measuring dissolved concentrations of organic contaminants. Organic
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contaminants partition between the aqueous phase and a passive sampler, which is usually in the form of a
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synthetic organic polymer (e.g. Mayer et al., 2003). In North America, low-density polyethylene is one of
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the most commonly used polymers utilized for passive sampling (e.g., Adams et al., 2007; Fernandez et
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al., 2012; Perron et al., 2013; Sacks and Lohmann, 2011). Once equilibrium has been achieved between
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phases, accumulated contaminants in the passive sampler can be measured in order to calculate
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corresponding dissolved contaminant concentrations using polymer-water partition coefficients (e.g.,
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KPEW) (Adams et al., 2007). As compared to conventional sampling methods, passive samplers are cheap,
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accessible and easy to use and provide important information on the dissolved or potentially bioavailable
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fraction of a chemical. In addition to their logistical advantages, passive samplers have the capability to
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improve measurements of dissolved contaminant concentrations. There is less interference from other
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potential contaminant containing phases (e.g., small particles and colloids) and resulting analytical
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samples are relatively cleaner. Passive samplers also have the potential to increase detection limits
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through the concentration and accumulation of contaminants within the organic polymer. Lastly, passive
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samplers obtain an average measure of concentration over time rather than a cross-sectional or “snap-
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shot” concentration from an individual time point, which is provided by many forms of conventional
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water sampling techniques (Ells, 2010).
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Passive sampler and sediment trap deployments. During the study, a single sediment trap was
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deployed at each site, anchored to the bottom with concrete blocks. Water depths at sites 1 ,2,
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and 3 were approximately 3.0, 3.0 , and 4.0 meters, respectively. A small, bullet shaped,
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positive buoyancy buoy was rigged on the support rope to maintain the trap in a vertical posture,
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with a round buoy at the end of the line for marking sampling location. During recovery,
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sediment trap tops were drained and tightly sealed, leaving approximately three inches of
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overlying water above the sediment layer during transit. Sediment traps were fully drained and
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sediment removed immediately upon return to the lab and freeze dried prior to analysis. Passive
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sampler cages were deployed in a similar manner to the sediment traps, with the minnow traps
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maintained vertically at mid-depth at each site. Three polyethylene (PE) sample strips were
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deployed in each of the cages. Following recovery, PE strips were removed immediately from
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the cages, sealed in aluminum foil and placed on ice until processing back at the lab.
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Flow Model Information. A total of 13 water samples were collected below the dam at site 3
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during the course of the study. One liter water samples were collected and filtered through
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Whatman GF/F glass fiber filters (0.7 micron nominal retention), dried overnight at 25 °C and
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the TSS calculated gravimetrically. Flows during the sampling periods ranged from 5.7 to 34.9
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m3/sec with total suspended solids (TSS) ranging from 0.9 to 27 mg/L. Regressing the flow and
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TSS data resulted in a coefficient of determination (R2) of 0.75 and a linear relationship defined
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by the regression equation y=.9975x+9.2192 (Figure S1). Suspended particle concentrations for
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any particular day were calculated using the daily averaged flow (m3/sec) and the regression
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equation to estimate the daily TSS value. Particle fluxes were determined by taking the total
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calculated daily flow volume (L) and multiplying it by the daily TSS value (mg/L). Particulate
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contaminant fluxes were reported on a daily basis and calculated by multiplying the total
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sediment flux during the deployment period (g) by the concentration of either PAHs (ug/g) or
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PCBs (ng/g) and dividing by the deployment time (days). Dissolved contaminant information
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was determined by multiplying the individual compound concentration (ng/L) by the total flow
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volume (L) during the deployment period and dividing by the days deployed.
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Table S1. Analyte list of PAHs and PCBs measured in this study.
PAHs
Naphthalene
1-methylnaphthalene
2-methylnaphthalene
2,6-dimethylnaphthalene
2,3,5-trimethylnaphthalene
acenaphthylene
acenaphthene
Fluorene
phenanthrene
anthracene
fluoranthene
Pyrene
benz[a]anthracene
Chrysene
benzo[b]+[k]fluoranthene
benzo[e]pyrene
benzo[a]pyrene
Perylene
indeno[1,2,3-cd]pyrene
dibenz[a,h]anthracene
benzo[g,h,i]perylene
Phenanthrene-d10*
benz[a]anthracene-d12*
Perylene-d12*
*Internal standards
PCBs
CB8
CB18
CB28
CB52
CB44
CB70
CB66
CB101
CB99
CB81
CB77
CB110
CB123
CB118
CB114
CB153
CB105
CB138
CB126
CB156
CB157
CB180
CB169
CB170
CB189
CB198*
CB206
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Figure S1. Total suspended solids-flow model
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Flow (m3/s)
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y = 0.9979x + 9.2192
R² = 0.75
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TSS (mg/L)
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Figure S2. Grain size distribution from sediment trap at site 3 (below dam)
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% Clay (0 - 3.9 um)
% Silt (3.91 - 62.5 um)
% Sand (62.5-2000 um)
100%
Percentage (%)
80%
60%
40%
20%
0%
Date
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References
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