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Elucidating the Behavior of Cyclic Volatile Methylsiloxanes in a Subarctic Freshwater Food Web: A Modeled and Measured Approach Ingjerd Sunde Krogseth, Emma Maria Undeman, Anita Evenset, Guttorm N. Christensen, Mick J. Whelan, Knut Breivik, and Nicholas A. Warner Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b03083 • Publication Date (Web): 05 Oct 2017 Downloaded from http://pubs.acs.org on October 9, 2017

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Environmental Science & Technology

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Elucidating the Behavior of Cyclic Volatile Methylsiloxanes in a Subarctic Freshwater Food Web: A Modeled and Measured Approach

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Dr. Ingjerd S. Krogseth,1,* Dr. Emma Undeman,2,3 Dr. Anita Evenset,4,5 Cand. Scient. Guttorm N.

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Christensen,4 Dr. Mick J. Whelan,6 Dr. Knut Breivik,7,8 Dr. Nicholas A. Warner1

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6 7 8 9 10 11 12 13

1 2

NILU – Norwegian Institute for Air Research, The Fram Centre, P.O. Box 6606 Langnes, 9296 Tromsø, Norway; Baltic Sea Centre, Stockholm University, SE-106 91 Stockholm, Sweden; 3Department of Environmental Science and Analytical Chemistry, Stockholm University, Svante Arrhenius väg 8, SE-106 91, Stockholm, Sweden; 4 5 Akvaplan-niva AS, The Fram Centre, P.O. Box 6606 Langnes, 9296 Tromsø, Norway; Faculty of Biosciences, Fisheries and Economics, UiT the Arctic University of Norway, Hansine Hansens veg 18, 9019 Tromsø, Norway; 6 School of Geography, Geology and the Environment, University of Leicester, Leicester LE1 7RH, United 7 8 Kingdom; NILU – Norwegian Institute for Air Research, P.O. Box 100, 2027 Kjeller, Norway; Department of Chemistry, University of Oslo, P.O. Box 1033, Blindern, 0315 Oslo, Norway.

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*Corresponding author: NILU – Norwegian Institute for Air Research, The Fram Centre, P.O. Box 6606 Langnes, 9296 Tromsø, Norway, tel: +47 63 89 80 00, [email protected]

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Abstract

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environments through wastewater effluents, and their bioaccumulation potential is debated. Here, a

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new bentho-pelagic version of the ACC-HUMAN model was evaluated for polychlorinated biphenyls

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(PCBs) and applied to cVMS in combination with measurements to explore their bioaccumulation

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behavior in a subarctic lake. Predictions agreed better with measured PCB concentrations in Arctic

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char (Salvelinus alpinus) and brown trout (Salmo trutta) when the benthic link was included than in

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the pelagic-only model. Measured concentrations of decamethylcyclopentasiloxane (D5) were 60 ±

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1.2 (Chironomidae larvae), 107 ± 4.5 (pea clams Pisidium sp.), 131 ± 105 (three-spined sticklebacks:

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Gasterosteus aculeatus), 41 ± 38 (char), and 9.9 ± 5.9 (trout) ng g-1 wet weight. Concentrations were

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lower for octamethylcyclotetrasiloxane (D4) and dodecamethylcyclohexasiloxane (D6), and none of

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the cVMS displayed trophic magnification. Predicted cVMS concentrations were lower than

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measured in benthos, but agreed well with measurements in fish. cVMS removal through ventilation

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was an important predicted loss mechanism for the benthic-feeding fish. Predictions were highly

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sensitive to the partition coefficient between organic carbon and water (KOC) and its temperature

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dependence, as this controlled bioavailability for benthos (the main source of cVMS for fish).

Cyclic volatile methylsiloxanes (cVMS) are used in personal care products and emitted to aquatic

1 ACS Paragon Plus Environment


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1. Introduction

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Cyclic

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decamethylcyclopentasiloxane (D5), and dodecamethylcyclohexasiloxane (D6), are used as

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ingredients in personal care products and are emitted to aquatic environments through wastewater

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effluents.1-3 D4 has been classified as a persistent, bioaccumulative, and toxic (PBT) substance and D5

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as a very persistent and very bioaccumulative (vPvB) substance in a European Chemical Agency

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Member State Committee opinion.4 A restriction on use in wash-off products is currently underway

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in Europe.5 However, their hazardous properties, particularly their bioaccumulation potential, are

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uncertain.6-8 Field studies of cVMS in aquatic food webs have demonstrated both trophic dilution9-12

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and trophic magnification,13,14 and the explanation(s) for this variability remains unclear. Possible

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influencing factors include behavioral and physiological characteristics of the investigated taxa, food

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chain composition, and the nature of the physical environment (including possible confounding

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effects such as spatial gradients in concentration).7,15

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As well as being very volatile, cVMS are very hydrophobic, and are expected to partition significantly

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to organic phases. Although it is now well established that the organic carbon (OC) to water partition

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coefficients (KOC) for cVMS are lower than those expected from their octanol to water partitioning

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(KOW),16-19 there is uncertainty in the temperature dependence of KOC which currently constrains our

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understanding of the behavior of cVMS in cold aquatic environments.20 Although a positive

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relationship between KOW and temperature has been reported (suggesting lower hydrophobicity at

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low temperatures),19,21,22 a negative relationship between KOC and water was recently reported

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(suggesting higher hydrophobicity at low temperatures).23 This will influence the behavior of these

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compounds in systems with low temperatures. In aquatic systems without continuous wastewater

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emissions, the exposure of pelagic organisms to these compounds is likely to be primarily via benthic

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links in the food web, as cVMS may be rapidly removed from water between emission events.20

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The combination of fugacity-based models and measurements has proved useful for developing an

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understanding of the environmental behavior of cVMS and the identification of key knowledge

volatile

methyl

siloxanes

(cVMS),

such

as

octamethylcyclotetrasiloxane


(D4),

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gaps.24-27 However, this approach has rarely been used for cVMS behavior in food webs. Exceptions

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include applications of the AquaWeb6 and ACC-HUMAN models.24,28 ACC-HUMAN predicted trophic

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dilution of cVMS in zooplankton, herring, and cod from the Inner Oslofjord (which receives high

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wastewater emissions), in accordance with measurements.24 However, given the importance of

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sediments as a reservoir of cVMS, there is a need for a benthic link in the model. This is particularly

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important for systems such as Storvannet where fugacities in sediment often exceed those in the

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water column due to intermittent emission events and rapid advection of the water column.20 Here,

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we explore the bioaccumulation behavior of cVMS using the ACC-HUMAN model, which was

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expanded to include a benthic link. Model performance was first evaluated for well-known PCBs, and

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the model was subsequently applied to explain measured cVMS concentrations in biota sampled

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from Lake Storvannet in Northern Norway. Lake Storvannet was chosen as (i) the lake and its food

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web is relatively well-studied,29,30 (ii) measurements of PCBs from lake water, sediments, and biota

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are available for model evaluation purposes,31 and (iii) a study of cVMS behavior in the physical

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environment of the lake has already been carried out.20

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2. Methods

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2.1. Study site

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Lake Storvannet is a small (0.2 km2, maximum depth 17 m), oligotrophic lake, located in a residential

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area of the town of Hammerfest in Northern Norway (70°N 23°E; 7000 inhabitants).20 The lake has a

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long history of local contamination with organic contaminants including PCBs.31 Untreated

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wastewater from Hammerfest is now emitted into the sea. However, sewers run along both sides of

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Storvannet, and the lake unintentionally receives wastewater through leaking pipes and combined

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sewer overflow events (CSOs), particularly during the snowmelt season and after heavy rainfalls.20 As

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a result, cVMS are present in sediments of the lake with concentrations comparable to much more

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populated areas (207 ± 30, 3775 ± 973, and 848 ± 211 ng g-1 OC for D4, D5, and D6, respectively).20

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However, cVMS were not detected in water samples from the lake (LOQ 19-40 ng L-1, 12-54 ng L-1,

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and 42-74 ng L-1 for D4, D5, and D6, respectively).20 The lake is ice covered for approximately six



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months of the year and the summer season and the plankton bloom is short. Benthic Chironomidae

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larvae (hereafter; chironomids) and pea clams (Pisidium sp.) are, consequently, important dietary

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items for resident fish.29,32,33 Populations of both stationary and anadromous Arctic char (Salvelinus

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alpinus) (hereafter; char) and brown trout (Salmo trutta) (hereafter; trout), as well as three-spined

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sticklebacks (Gasterosteus aculeatus) (hereafter; sticklebacks) inhabit the lake.29,30 While char mostly

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feed on benthos, the trout has a more pelagic diet including aquatic insects.29,34,35 Both the trout and

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char may be cannibalistic, but the trout tends to be more piscivorous than the char and also feed on

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sticklebacks (Figure 1, Table 1, Supporting Information (SI) 2.2). The sticklebacks feed on plankton

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and benthos in the littoral zone of the lake. Only stationary fish were included in this study.

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Char (n = 11) and trout (n = 13) were caught opportunistically in March, May, and June 2014 (Table

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S1). In March and May, the fish were caught with lines and hooks. In June, gill nets were used. In

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addition, traps, baited with fish roe (wrapped in fine mesh so the fish could not eat it), were

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deployed in shallow areas of the lake for collection of sticklebacks (n = 5). Benthic fauna

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(Chironomidae and Pisidium sp.) were collected by hauling a 500 µm trawl along the bottom. All

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samples were wrapped in aluminum foil, placed in zip-lock bags, and transported in chilled boxes to

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the lab where they were stored at -20 °C until sample preparation. All use of personal care products

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was avoided by field and lab personnel. Muscle and liver tissues from Atlantic cod (Gadus morhua)

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caught off the Norwegian coast were utilized as blank material. Prior to sample collection, the cod

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tissues were split into three separate portions to serve as field blanks, dissection blanks, and

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reference blanks, in order to assess if any contamination occurred during field work or sample

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dissection.

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Strict quality control procedures were enforced to limit cVMS contamination of samples (SI 1.1). The

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bodyweight and total length of each fish were recorded, gender and maturity were determined

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through visual inspection of the gonads, and stomach content was visually examined (Table S1, S2).

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Otoliths were retrieved to determine the age of the char and trout (Table S1). Liver and dorsal

2.2. Sample collection, preparation and analysis


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muscle tissue was taken out for analysis of cVMS, extractable organic matter (assumed

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representative for lipids),36 and stable isotope analysis (muscle only; δ15N, δ13C, δ14S) (SI 1.2, Table 2).

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Prior to analyses, both liver and muscle samples were homogenized with a metal scalpel on a clean

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glass surface. Due to the small size of the sticklebacks, the whole fish was homogenized and the

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homogenate was analyzed for cVMS and stable isotopes. The collected chironomids were pooled and

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homogenized in a mortar, giving two replicates for cVMS analysis and one for stable isotopes. The

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same procedure was followed with whole Pisidium samples (including the carbonaceous shell).

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All samples were extracted for cVMS using a biphasic cold solvent extraction, based on a previously

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published method for sediments,20 but adapted to biotic tissues (SI 1.3). Analysis of cVMS was carried

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out on an Agilent 7890A GC connected to an Agilent 5975C MS detector and a Gerstel MPS3

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autosampler. Method details have previously been published.20 Calculation of limits of detection

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(LOD) and quantification (LOQ) from blank samples is described in SI 1.1.

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2.3. Bioaccumulation modeling

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2.3.1. Development of the bentho-pelagic ACC-HUMAN The aquatic part of the original ACC-HUMAN model represents a pelagic Baltic Sea food web

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consisting of zooplankton, a planktivorous fish (herring) and a piscivorous fish (cod).28 Here, a benthic

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link was included in the model by adding a sediment compartment, a benthic filter feeder, a benthic

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predator/deposit feeder, and up to three prey items for the latter. The model does not simulate

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chemical transfer between lake water and sediment. Rather, time-resolved concentrations or

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fugacities in sediment and lake water is provided as input to the model. Sediment pore water and

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sediment solids are assumed to be in equilibrium.

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The prey items are defined by their biochemical composition (fractions of water, lipid, and non-lipid

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organic matter), the fraction of time they spend buried in sediments, and assumed thermodynamic

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equilibrium with their surroundings. Bioaccumulation in the predator/deposit feeder and filter feeder

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are predicted using a dynamic version of the steady-state model of Arnot and Gobas.37 The fugacity

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capacity (Z-value) of the organism is calculated based on its biochemical composition. Chemical 5 ACS Paragon Plus Environment


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uptake occurs through feeding and ventilation (of sediment pore water and/or overlying water).

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Elimination of chemicals can occur through ventilation, fecal egestion and/or biotransformation. The

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predator/deposit feeder may feed on the prey items and/or sediment particles, while the filter

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feeder may feed on suspended or settled sediment particles and/or zooplankton. The fish in the

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model may prey on the benthic filter feeder and the deposit feeder, in addition to zooplankton and

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fish. The model assumes annual constant growth rate, lipid content, and dietary composition.

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However, a seasonal feeding pattern for the fish was included in the model, in which the fish are

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assumed not to eat during wintertime (November – February) as is the case in Storvannet. All

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equations, parameters, and assumptions for the new model are described in SI 2.1 and 2.2.

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To adapt the bentho-pelagic ACC-HUMAN to Storvannet, the model organisms were parameterized

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as key species of the Storvannet food web. Benthos were parameterized as chironomid larvae

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(deposit feeder) and Pisidium clams (filter feeder). The pelagic fish was re-parametrized based on

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sticklebacks, while the piscivorous fish was re-parametrized to represent either char or trout (SI 2.2,

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Table 1). Dietary composition of the organisms and overall structure of the food web was based on

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existing knowledge about the system aided by analysis of stable isotopes and gut content.

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Measurements of water temperatures (Table S11),38 fraction of solids in sediments (18 % v/v) and

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fraction of OC in sediment solids (5 % w/w)20 from Storvannet were used as model input.

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2.3.2. Model evaluation and application Many model aspects are independent of the compounds studied and are best constrained on the

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basis of data-rich chemicals like PCBs. To evaluate the performance of the new bentho-pelagic model

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version, it was compared with the pelagic-only version of ACC-HUMAN parameterized for the taxa

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present in Storvannet. Predicted concentrations in char and trout were compared to measurements

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from Storvannet for five PCB congeners (SI 2.3).

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Empirical data for exposure-relevant physical media are restricted to sediment for cVMS. Hence, only

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the bentho-pelagic model version was applied to cVMS, as the pelagic-only model needs


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concentrations in water as input. Average measured concentrations of cVMS in surface sediments (0-

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1 cm, OC-normalized) of Storvannet in 2014 were used as input to the model (Table S13).20 cVMS

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concentrations in Storvannet lake water sampled at the same time were below limits of

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quantification (LOQ).20 Given the lack of measured concentrations, a range of values for the fugacity

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in water was evaluated, and expressed relative to the fugacity in sediment derived by the model

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from the concentration in sediment (SI 2.4).

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Measured partition coefficients (KOW and KAW (air-water partitioning)) and their temperature

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dependencies (ΔUOW and ΔUAW) were used as input (Table S13).19,20,39 The KOC values for cVMS are

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known to be significantly overestimated by empirical relationships with KOW.19,39 This deviation may

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also apply for ΔUOC versus ΔUOW. The most recently measured values of KOC and ΔUOC for cVMS were,

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therefore, used as direct inputs, rather than relying on relationships based on affinity to octanol

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(Table S13).18,23 That said, partitioning to lipids was still assumed to be represented by partitioning to

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octanol,40,41 although there is limited evidence to justify this assumption. cVMS may undergo

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biotransformation in aquatic biota, but few measurements are available. Here, a fish

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biotransformation rate constant (kM) of 4 · 10-4 h-1 (corresponding to a half-life of 72 days) was

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applied for all cVMS (Table S13), following Whelan and Breivik.24,42 In the absence of evidence, cVMS

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were assumed to not biotransform in benthos or zooplankton.

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The model was run for 10 years with a 1 hour simulation time step. Predicted median lipid-

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normalized concentrations in year 10 across all age classes at the time of year when the samples

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were collected, as well as the annual range (min-max), were compared to measured lipid-normalized

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concentrations in whole-body homogenates (chironomids, Pisidium, and sticklebacks) and in muscle

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tissue (char and trout). As the model does not provide gender- and/or maturity-specific results for

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fish, measurements were grouped irrespective of gender and maturity for comparison to model

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results. Additional simulations were carried out to test the sensitivity of model results to changes in



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cVMS physical-chemical properties and biotransformation rates (properties were changed

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individually by ± 10 % and ± 20 %).

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3. Results and discussion 3.1. Measured concentrations of cVMS

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All cVMS concentrations in benthos were above LOQ (Table S3). The D4, D5, and D6 whole body

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concentrations (pooled duplicates) in chironomids were 9.9 ± 0.3, 60 ± 1.2, and 9.3 ± 0.1 ng g-1 wet

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weight (ww), and in Pisidium 4.7 ± 0.4, 107 ± 4.5, and 11.8 ± 1.2 ng g-1 ww, respectively (Table 2). The

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measured concentrations in benthos are within the range of measured concentrations in benthos

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reported elsewhere, including chironomids and burrowing mayfly in Lake Pepin, ragworm in the

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Humber Estuary, and polychaets from the Oslofjord (Table S8).9,10,43,44 Lipid content for benthos was

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not measured due to insufficient sample material. Instead this was derived from literature (Table 2).

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Hence, the lipid-normalized concentrations have added uncertainty, particularly for Pisidium which

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has a very low lipid content. This does not matter for model comparison purposes as the lipid

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content assumed for normalization was used as model input and hence errors in lipid-content will

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cancel out in model-measurement comparisons. The benthic samples may also have contained traces

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of sediment particles, as they were not depurated after sampling. This means that measured

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concentrations of (i) D4 in chironomids and D5 in Pisidium could have been diluted by presence of

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sediment particles (concbenthos > concsed (ng g-1 ww)), while (ii) D5, D6 in chironomids and D4, D6 in

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Pisidium could have been contaminated by presence of sediment particles (concbenthos ≤ concsed (ng g-1

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ww)).20 Hence, cVMS concentrations in benthos should be considered approximate and are only used

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for model-measurement comparison.

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All cVMS concentrations in whole-body homogenates of sticklebacks were above LOQ (Table S3),

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with concentrations of 12.6 ± 9, 131 ± 105, and 6.3 ± 3.6 ng g-1 ww for D4, D5, and D6, respectively

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(309 ± 226, 3203 ± 2584, and 155 ± 89 ng g-1 lipid weight (lw)) (n = 5) (Table 2). In muscle of char and

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trout, D4, D5, and D6 were above LOQ in 37 %, 97 %, and 14 % of the samples, respectively (Table

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S3). D4 and D6 were below LOQ in trout, while D5 ranged between 3.9 – 22.0 ng g-1 ww (383 – 2434 8 ACS Paragon Plus Environment

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ng g-1 lw) (n = 13). In char, D4, D5, and D6 ranged between

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