Known and unknown bioaccumulating per- and
polyfluoroalkyl substances in pilot whales
A timeline study of the PFAS concentrations and total organic fluorine in liver
tissue from pilot whales from the Faroe Islands
Datum: 18 / 06 / 2020
Kursnamn: Miljövetenskap, självständigt arbete för kandidatexamen
Författare: Victor Andréasson Handledare: Ulrika Eriksson
Godkänd den: 27/07/2020 Kursnummer: MX107G Betyg: VG
Summary
Per- and- polyfluoroalkyl substances (PFASs) are widely used in commercial and industrial products and leach into the environment from different applications. PFASs poses an issue to both wildlife and humans because of different toxic properties. Different PFASs have been found to effect different hormones, are possibly carcinogenic, or can affect metabolic function. Many initiatives have been started by countries, organisations, and companies to prevent PFASs from ending up in the environment. Aquatic environments are a sink for PFASs, and much research has been done on the marine environment and its residents to investigate the effects of these substances. In earlier research, the need for a time-line perspective combined with both a total fluorine analysis and mass spectrometry analysis has been pointed out. This study's objective was to investigate how the concentrations of known and unknown bioaccumulating organic fluorinated substances in pilot whales are evolving over time.
The results show fluctuating levels of PFASs for the different whales, making it hard to view any trends. There is a pattern of the unknown organic fluorine, that is increasing after 2009 when the phase-out of perfluorooctane sulfonate (PFOS) happened. The highest amount of unknown fluorine is 77% in one of the samples. Short-chain PFASs seems to be a good short-term solution as a replacement for the long-chain PFASs but could pose a threat over a longer time perspective. Both pilot whales and humans risk getting high concentrations of PFASs through biomagnification, the acceptable daily intake (ADI) that are in place regarding PFASs should possibly be on total organic fluorine (TOF) instead, due to the high percentage of unknown organic fluorine.
Table of Contents
Introduction ... 1
Per- and- polyfluoroalkyl substances (PFASs), the substance, their usage and environmental distribution ... 1
PFASs damage in the environment ... 1
Measures for controlling PFASs ... 2
Knowledge gaps ... 3
Marine environment ... 3
Aim and objectives of the study... 4
Method and materials ... 4
Chemicals ... 5
Samples ... 5
Extraction ... 5
Analysis... 6
Combustion ion chromatography ... 6
LC/MS... 7
Calculations... 7
Quality control/quality assurance ... 8
Results ... 8
Total organic fluorine ... 8
PFAS concentrations ... 11
Discussion ... 14
Total organic fluorine ... 14
PFAS concentrations ... 15
Generalization ... 17
PFAS in the food-chain ... 17
Acknowledgments... 18
References ... 19
Appendix 1 ... 1
Appendix 2 ... 2
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Introduction
Per- and- polyfluoroalkyl substances (PFASs), the substance, their usage and environmental distribution
PFASs is a shortening for two groups of fluorinated substances: per- and- polyfluoroalkyl substances (PFAS). Perfluoroalkyl substances have all hydrogen (H) connected to the carbon (C) backbone of a non-fluorinated substance replaced by fluorine (F), and polyfluoroalkyl have at least one but not all H replaced by F (Buck et al., 2011). PFASs are widely used in commercial- and industrial products such as building materials, aqueous film-forming foam (AFFF), textiles, insulation, plastics, impregnation agents and paint (Bečanová et al., 2016; Favreau et al., 2017; Jensen et al., n.d.). PFASs are often used because of the ability to repel both water and oil (Sunderland et al., 2019), or to lower the surface tension of a liquid (Kissa, 2001, p. 125-126).
Through the different applications, PFASs leach into the environment through different routes either directly from the products, through the use of AFFFs, or from waste management or industries (Sunderland et al., 2019). From the environment, PFASs then continue to spread to wildlife and humans, mainly through food and drinking water. PFASs have been detected in both air and in ocean water, which provides a way of spreading across the world either through the atmosphere or through water currents (Ahrens & Bundschuh, 2014; Rauert et al., 2018).
PFASs damage in the environment
The issue with PFASs in the environment is their high persistence due to the strong bond between carbon and fluorine (Banks et al., 2013, p. 57). They have also shown to be toxic to both humans and animals (Sunderland et al., 2019; Wang et al., 2011). There is an increased risk of cancer when drinking water contaminated with perfluorooctanoic acid (PFOA), which led The International Agency for Research on Cancer to list PFOA as possibly carcinogenic (Sunderland et al., 2019). Other health outcomes that correlated positively with different PFAS substances are metabolic with higher amounts of cholesterol and immuno-toxic effects for multiple animals. Perfluorooctane sulfonate (PFOS) can pass through the blood-brain-barrier (Wang et al., 2011), which has led to investigations of possible neurotoxic effects
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from PFASs. Zeng et al. (2019) showed five different effects PFOS have on neurons, two of them in the neuron cell body causing oxidative stress and inducing neuroinflammation. Then the last three in the synapse, where it alters the formation of the synapse, disturbing the calcium ion channels and alters the levels of transmitter substance. A review by Piekarski et al. (2020) lists the impact PFASs have on various hormones. PFOS has several impacts on many hormones in different animals, including fetal stress hormones, stress hormones, and thyroid hormones. Another example is perfluoroalkyl acids (PFAAs), which affects stress hormones, sex hormones, and thyroid hormones (Piekarski et al., 2020). A study made by Knox et al. (2011) showed that exposure to PFAS from drinking water is connected to elevated levels of thyroxine and reduced uptake of the T3 hormone. Due to its high
persistence and since PFASs are continuously emitted into the environment, bioaccumulation will continue in both wildlife and humans (Wang et al., 2015).
Measures for controlling PFASs
To act on the issues with PFASs, several initiatives have been created. The Stockholm Convention on persistent organic pollutants (POPs) was created in 2001, with the goal of decreasing the use of POPs and to eliminate emissions to the environment (Idowu et al., 2013). In 2009, PFOS was added to the list of POPs in the Stockholm Convention. The U.S. Environmental Protection Agency started the PFOA Stewardship program in 2006, together with eight companies (US EPA, 2016). The goal was to reduce the use of PFOA in the U.S. by 95% by 2015, which was achieved according to the participating companies. REACH is another way of trying to control the effects of PFAS created by the European Chemicals Agency (ECHA). REACH is an acronym for Registration, Evaluation, Authorization, and restriction of Chemicals. The goal is to protect human health and the environment from chemicals through identifying potential risks of different chemical substances (European Commission, 2019) One initiative was also driven by the U.S. chemical manufacture company 3M, who voluntarily phased out PFOS already in the year 2000 (3M, n.d.).
Mainly two alternatives to long-chain PFASs such as PFOS and PFOA have been presented. One is perfluoroethers, which is a fluorinated alkyl chain with one or more oxygen
incorporated in the fluorinated chain (Buck et al., 2011). This is hypothesized to enable the degradation of the PFAS once released into the environment. The other main alternative is short-chain PFASs, which is PFASs with a carbon-chain with seven or less carbon atoms.
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which has a shorter elimination time in humans and animals than the long-chain PFAS. The short-chain PFAS should not bioaccumulate as much as the long-chain PFAS. However, research has shown that even the short-chain PFAS is as persistent in the environment as the long-chain PFAS (Kärrman et al., 2019; Wang et al., 2013).
Knowledge gaps
Worldwide there are about 5000 different PFASs compounds in industrial use
(Naturvårdsverket, 2020); many of these substances are novel or unknown substances. Due to the large number of PFASs and new substances that come into use, the analysed PFASs in targeted analysis are only a part of the total amount of PFASs (Kärrman et al., 2019). Kärrman et al. (2019) found in their study that 70% of the total organic fluorine in marine mammals was from unknown sources, meaning that the target analysis does not need to explain the entire exposure to PFASs.
Fair & Houde, (2018) conclude in their study that there is a need for a time-line perspective, to gain knowledge of the impacts of the regulations that have been established to minimize the emissions of PFAS. Information on the unknown PFAS and novel PFAS in a time-line study, could help us understand the risks for the environment, wildlife, and humans and thus help to protect the health of both wildlife and humans (Fair & Houde, 2018; Kärrman et al., 2019). The study by Kärrman et al. (2019) discusses a way of executing a combination of mass spectrometry (MS) and a total organic fluorine (TOF) analysis. This might help identifying unknown PFAS and explain their impact.
Marine environment
PFAS in the marine environment and marine animals have been a focus for multiple studies, and PFAS has been found in many different marine animals all over the world (Fair & Houde, 2018). PFAS have been found in marine mammals such as polar bears, dolphins, seals, killer whales, beluga whales (Fair & Houde, 2018; Gebbink et al., 2016). Kärrman et al. (2019) showed higher levels of extractable organic fluorine in the marine mammals compared to other marine animals and terrestrial animals. Different species metabolize PFASs at varying speeds, some marine mammals cannot produce or have a very low production of one of the enzymes required to metabolize perfluorooctane sulfonamide (FOSA) into PFOS (Letcher et al., 2014).
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Studies on the marine environment appear to have a focus on analysing PFOS,
perfluoroalkane (or -alkyl) sulfonic acids (PFSAs) and perfluoroalkyl carboxylic acids (PFCAs). Gebbink et al. (2016) studied PFOS, PFSA and PFCA along with a few other compounds on ringed seal, polar bear, and killer whales and found perfluorobutane sulfonic acid (PFBS), short-chain PFAAs and the PFOS replacement F-53B in all species. Dassuncao et al. (2017) studied levels of PFAS and included both PFOS and PFBS. According to Xiao (2017), many of the novel PFAS compounds seem to be water-soluble and non-volatile, these qualities make the aquatic environments a likely sink for PFASs. The study by Kärrman et al. (2019) showed higher levels of extractable organic fluorine in the marine mammals compared to other marine animals and terrestrial animals. Therefore, a study on marine mammals should be able to provide important information on the unknown and newly identified PFAS.
Aim and objectives of the study
The aim of this study is to view how the concentrations of known and unknown
bioaccumulating organic fluorinated substances in pilot whales are evolving over time. This will be achieved by answering these three questions:
How have the levels of total organic fluorine and PFASs changed in the liver tissue of pilot whales during the period 2009 – 2018?
How much of the total organic fluorine in the samples is known PFASs, and what amount is unknown organic fluorine?
Which PFASs contribute to the known organic fluorinated substances?
Method and materials
To investigate mass balance of the fluorine, a target analysis was performed through liquid chromatography (LC) and mass spectrometry (MS), in combination with total organic fluorine, analysis made with a combustion ion chromatography (CIC). Theses analysis were made on samples ranging from 2009-2018 (Table 1). The method in this study is following the same procedure as Kärrman et al, (2019) but also includes samples on multiple years.
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Methanol from Fisher Scientific (Loughborough, UK), 1-methylpiperidine, ammonium acetate (NH4Ac) and Multi-element Ion Chromatography Anion Standard Solution were used and obtained from Sigma Aldrich (Steinheim, Germany) to complete the experiment.
Samples
Liver samples from pilot whales (Globicephala melas) from the Faroe Islands, were collected between 2009 and 2018 (Table 1). Every second year was chosen with exception for 2017 and 2018 being the only consecutive years chosen with two samples from each year.
Table 1. The samples used for the analysis of per- and polyfluorinated alkyl substances, year and location on the Faroe Islands the pilot whales were caught.
Extraction
The extraction method was following the study of Kärrman, et al (2019) one gram sample was weighed into 15 mL PP tubes. Two mL of the 0.5 M tetrabutyl ammonium TBA in water was added to each sample followed by 5 mL of methyl-tert-butyl ether (MTBE). The samples were then shaken horizontally at 250 rpm for 15 min.,Thereafter the samples were
centrifuged for 10 min at 8000g. The top layer of the extracts was transferred to new PP
Year Location 2009 Göta 2009 Göta 2011 Vestmanna 2011 Vestmanna 2013 Fuglafjord 2013 Fuglafjord 2015 Midvágur 2015 Midvágur 2017 Torshavn 2017 Hvalvik 2018 Sandagerdi 2018 Sandagerdi
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tubes. This procedure was repeated two additional times using 3 mL MTBE instead of 5 mL MTBE and without adding TBA and then combined in the new PP tube.
The extracts were placed under a Reacti-VAP III, evaporation unit and evaporated to dryness using nitrogen gas and then reconstituted in 0,5 mL methanol. The PP tubes was centrifuged for 30 minutes at 8000g.
The vials for the LC and CIC analysis were weighed when empty. The extract was transferred to an LC vial using a pipette and weighed again. The extract was then split into three different fractions for the different analysis, 300 µL was transferred from the LC vial to the CIC vial and 100 µL to another LC vial leaving 100 µL in the first LC vial and all the vials were weighed again. The LC vials were then diluted with methanol until one containing 40% and the other 80% methanol.
The cloudier samples were moved to a new vial using a pipette and filtered using a syringe with a 13 mm 0,2 µm GHP filter attached, then centrifuged at 6000g for 20 min. Two of the samples were after the filtration still cloudy and approximately 20 mg ENVI-Carb was added, and the filtration process was repeated for these two samples.
Fractions for LC analysis were spiked using 25 µL IS (0,04 ng/mL) and five µL RS (0,2 ng/mL) after extraction, except for the control sample which already had been spiked with IS, to this sample only RS was added.
Analysis
Two types of analysis were performed, CIC and LC/MS. The CIC analysis measures the TOF by heating the sample to 1000-1050 C° and catching the atoms in a liquid phase. The LC/MS analysis measures the m/z of the ionized target analytes.
Combustion Ion Chromatography
Total fluorine analysis was made using CIC. First a combustion module (Analytik Jena, Germany), then an absorption module and last a compact ion chromatograph flex (Metrohm, Switzerland). The absorption module was prepared with 2x2 L of MilliQ-water, the compact IC flex module was prepared with 1,9 L of MilliQ-water and 100 mL sodium carbonate. In
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the combustion module, combustion blanks were run until an even level below 0,05 ppb fluoride was established.
The analysis started with running an external standard of 100 ppb fluoride. The standard was validated against a calibration curve in the range from 10 ppb fluoride to 1000 ppb fluoride. In between every sample, including the standard solutions, combustion blanks were run, to prevent any carry over and to continuously monitor background levels of fluoride. The test then finished by running both the external standards a second time.
LC/MS
Mobile phases consisting of 5 mM 1-methylpiperidine and two mM NH4Ac in MilliQ-water and methanol (70:30) and 5 mM 1-methylpiperidine and 2 mM NH4Ac in MilliQ-water was used in the LC analysis. A XEVO TQ-S-micro (Waters Corporation, Milford, USA) was used for the perfluoroether analysis, while a XEVO TQ-S (Waters Corporation, Milford, USA) was used for the remaining analytes. Both operated in negative electrospray ionization mode. The same type of column was used for all the LC analysis, a 100 mm BEHC18 column, (1,7 µm) 2,1 mm i.d. As confirmation of the substances two transitions were monitored for the analytes.
Calculations
To calculate the isotope dilution a labelled internal standard was used. Several criteria for quantifications were used to analyse whether the concentration in the samples are above limit of detection (LOD), the relation between signal-to-noise had to be 1:3 for the analytes. To calculate the LOD the blank mean value plus three times the standard deviation of the three blanks was used. When there was no analyte in the blank, the lowest point on the calibration curve was used instead. The samples with a value higher than the LOD can be establish as quantified in the sample.
Blank subtraction was made by subtracting the sample area of fluorine with the combustion blank area that ran immediately before the specific sample, which creates a blank correction area. All the blank areas had a fluoride concentration of ≤0,04 ppb. Then the amount of fluoride in each sample was calculated against an external standard.
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The mass balance is the calculated through the combination of the LC/MS and CIC and show the difference between fluorine from known PFASs and fluorine from unknown organic sources. To calculate the mass balance, the number of fluorine atoms in the target analysis is multiplied by the molecular weight of fluorine divided by the molecular weight of the targeted PFAS and then multiplied with the concentration of the targeted PFAS: (𝐶 = 𝑁 𝑥 𝑥 𝐶 ).
A principal component analysis (PCA) was made in the software Past4, to statistically analyse any possible trends between the analytes.
Quality control/quality assurance
PP tubes and all material used were rinsed with methanol to avoid contamination. In the LC analysis a solvent blank was injected before and after analysis and after eight samples to control whether any carry-over was happening from the samples. A batch standard used for calculations was injected together with the samples, and also injected every 8th
sample to monitor the instruments performance
A control sample previously analysed by Kärrman et al. (2019) was included and analysed again in this study. The control sample was spiked with 25 µL internal standard (IS) before extraction.
The recovery for the control sample can be seen in Table A1 (Appendix 1) where it is
compared with the study by Kärrman et al., (2019). The recoveries in the present study (15.7 – 37.2%) is in similar range as the previous study (3,7 – 65,4%).
Results
In this study 16 different samples of liver tissue from pilot whale form the Faroe Islands between 2009 and 2018 were analysed. A total of 97 different PFAS substances were analysed (Appendix 3, table A3) in the target analysis. Other extractable organic fluorinated substances were analysed using CIC.
Total organic fluorine
Figure 1 is based on the mean value from each year to create a timeline showing the trend for the investigated samples. The highest amount of TOF can be seen in 2011 at a mean of
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244 ng F/g, and the lowest in 2018 at mean value 63,5 ng F/g. The R2-value show only a
linear correlation, the trend could display another pattern, for example a peak in some of the years (e.g. 2011 and 2017).
Figure 1. Mean value of fluorine in the liver samples from pilot whales for the years 2009-2018.
The individual differences between the pilot whales can be seen in Figure 2. The sample with the highest TOF is from 2011 at 316,6 ng F/g, and the lowest amount of TOF is from 2018 at 47,1 ng F/g. 111.1 244.0 122.3 65.8 99.4 63.5 y = -20.811x + 190.51 R² = 0.3448 0.0 50.0 100.0 150.0 200.0 250.0 300.0 2009 2011 2013 2015 2017 2018 ng F /g
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Figure 2. The individual levels of total organic fluorine (TOF) for each of the Pilot whales in ng F/g.
The proportion between the known PFASs and the unknown fluorinated substances are seen in Figure 3, all the samples have fluorine which is not accounted for in the LC/MS analysis creating a partition of fluorine from unknown sources. The lowest proportion of unknown fluorine was found in 2009, at 7% and the highest proportion in 2013 at 77%.
104.7 117.5 316.6 171.3 196.7 47.9 55.1 76.5 92.5 106.2 47.1 79.8 0.0 50.0 100.0 150.0 200.0 250.0 300.0 350.0 2009 2009 2011 2011 2013 2013 2015 2015 2017 2017 2018 2018 ng F /g
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Figure 3. Individual differences of known PFASs and unknown organic fluorine compounds from pilot whale liver samples collected around the Faroe Islands between 2009 and 2018.
PFAS concentrations
A total of 97 analytes were analysed. In Figure 4, the trend of the known PFASs over the period can be seen, with an R2-value of 0,4167 indicating a weak correlation. The highest
amount of known PFAS is found in 2009 at 88,1 ng F/g and the lowest in 2015 at
25,1 ng F/g. In 2017, the concentrations increase to 69,0 ng F/g before dropping to 26,5 ng F/g in 2018. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 2009 2009 2011 2011 2013 2013 2015 2015 2017 2017 2018 2018
Individual distribution between known PFAS and unknown
fluorine
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Figure 4. The mean value of the known PFASs in liver samples of pilot whale from the Faroe Islands collected between 2009 and 2018.
In Table A2 (Appendix 2), the concentrations of the 17 analytes that were detected above LOD can be seen. Multiple analytes are found in all samples. PFOS, PFUnDA, and PFTrDA were found in all samples, and have the highest mean value overall (28 ng F/g PFOS, 24 ng F/g PFuNDA and 20 ngF/g PFTrDA) (Figure 5).
Figure 5. The mean value of PFAS in pilot whale samples detected above LOD from 2009 to 2018. 88.1 76.2 33.0 25.1 69.0 26.5 y = -9.6486x + 86.731 R² = 0.4167 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 2009 2011 2013 2015 2017 2018
Mean value of known PFAS (ng F/g)
-5.00 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 ng F /g
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To analyse different trends for the analytes, a PCA was made and can be seen in Figure 6. In the PCA, connections between the different years and the analytes can be seen. The analytes included in the PCA are found above LOD in four or more samples. Connections along PC1 are the primary correlations (85% of the variance) and the PC2 are secondary correlations (6% of the variance). The long-chain PFAS group is up at the right side of PC1 (PFOS, PFUnDA and PFTrDA). The short-chain group up at the left side of PC1 together with SAmPAP (PFBA and L-PFHxS). PFASs with even-chain length PFAS are grouping up in the middle (PFTDA, PFDoDA and PFDA). The odd-chain length PFAS are divided along the right side of PC1 (PFUnDA, PFNA). All the samples have grouped up on PC1 but are more spread out on PC2, all the samples are on the right side of the PC1 indicating elevated levels of the long-chain PFAS and the PFAS with even numbers of carbon. The samples from 2013, 2015 and 2017 seems to be grouping together higher on PC2, indicating some correlation with short-chain PFAS. The samples from 2009, 2011 and 2018 seems to be further apart. PFDS, and the PFOS precursor FOSAA seems to show some correlation with one of the samples from 2009, and both samples from 2018.
Figure 6. Princioal component analysis of pilot whale liver samples and PFASs that were found in at least four samples above LOD between 2009 - 2018. (PC1 vs PC2).
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In Figure 7 the time trend of PFOS concentrations through the period can be seen. The R2
-value here is 0,281, showing only a linear correlation. The levels of PFOS fluctuate with a peak in 2011 at 23,6 ng F/g, another peak in 2017 at 18,9 ng F/g and the lowest point at 6,8 ng F/g in 2015.
Figure 7. The mean value of PFOS in the pilot whales from the Faroe Islands from 2009-2018.
Discussion
Total organic fluorine
This study's objective was to investigate how organic bioaccumulating fluorinated substances in pilot whales change over time. The total amount of organic fluorine compounds
accumulated in the pilot whales seems to fluctuate both individually, and from year to year. The trend is showing decreasing amounts of fluorinated substances, with an R2-value of
0,3448, indicating that the correlation with the trend is weak or does not exist. There is a peak for TOF in 2011, which might be caused by individual variations, however, both the whales in this year are, along with one of the whales from 2013, amongst the three whales with the highest levels of TOF. Indicating another reason for the increase, that the trend is going up between 2009 and 2011. If the overall downward going trend is accurate this could be the results of the restrictions set by ECHA, Stockholm Convention, The US EPA, and many other initiatives to decrease the amount of PFAS released to the environment
17.8 23.6 9.9 6.8 18.9 7.4 y = -1.9673x + 20.937 R² = 0.2807 0.0 5.0 10.0 15.0 20.0 25.0 2009 2011 2013 2015 2017 2018 ng F /g
PFOS trend
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(European Commission, n.d.; Idowu et al., 2013; US EPA, 2016). Dassuncao et al. (2017) investigated the amount of PFAS in pilot whales from 1994-2013, investigating 15 PFASs but not TOF. As in the present study, it was difficult to see any significant trend, and the levels of PFASs seems to vary between the pilot whales.
The amount of unknown PFASs differs, both from year to year and between the individual whales. Since the present study investigated 97 analytes (Table A3), and over 5000 PFASs are in commercial and industrial use (Naturvårdsverket, n.d.), this means less than 2% of the PFASs were analysed. Along with the results from Kärrman et al. (2019), who found 70% unknown PFASs in marine mammals, it is expected to find unknown PFASs. Despite the varying levels of unknown organic fluorinated substances, there is a pattern. After 2009 the unknown PFAS levels seem to increase. Since it was in 2009, PFOS was added to the Stockholm Convention (Idowu et al., 2013), many companies started to phase out PFOS and started using alternatives. The increase of unknown PFAS from 2009 until 2015 might be a consequence of this phase-out. If this is the case, it will create uncertainties on the effect this phase-out had on marine mammals, since some of the replacements might be as
bioaccumulative and as toxic as PFOS is.
The part of unknown fluorinated substances does not need to come only from unknown PFASs. In Fujiwara & O’Hagan, (2014), the use of fluorinated substances in herbicides is concluded to be an advantage. Some of the unknown fluorine in the present study might be from this type of fluorinated substance and not only from unknown PFAS. However, the high percentage of unknown fluorine indicates that there might be other bioaccumulative PFASs that are as common as those found in the target analysis and not only because of the high number of unknown fluorinated substances.
PFAS concentrations
For the PFASs, a downward trend can be seen, with an R2-value of 0,4167 indicating a weak
trend (Figure 4). Rotander et al. (2012) reported indications that PFAS concentrations
between 1984 and 2009 in marine mammals are increasing. It could be possible that the trend that is seen in this study indicates that there is a turning point for the emission of
bioaccumulating PFASs in marine mammals and that the prior increasing levels of PFAS are now levelling off. There is an increase in 2017 in the sum of PFAS, and a small spike caused by this can be seen in 2017 in the TOF trend (Figure 1). The spike in 2017 was caused by
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increased levels of PFNA, PFUnDA, PFTrDA, and PFOS. Dassuncao et al. (2017) discusses the variation between individuals within the species; for example, they concluded that juvenile female pilot whales who have not given birth to their first calf had the highest concentration of PFASs. The reason for the increase in 2017 might be the result of such a variation.
The main contributor to the sum of PFASs, even a decade after being phased out, is PFOS (Figure 5). Even though a decreasing trend of PFOS is seen in Figure 7, the R2-value is
0,2807, indicating almost no correlation, which means that the trend is inconclusive. A small amount of the other phased out compound PFOA is found in one of the samples (Table A2), which could imply that the phase-out of PFOA has worked. However, the compounds that are replacing PFOA might make up some part of the unknown fluorine and, therefore, with unknown attributes and health effects. Many of the regulations that exist, only target the long-chain PFASs, leaving the short-long-chain PFASs uncontrolled. They are not as bioaccumulative as the long-chain PFASs but might still impact the environment around us. Since they are as persistent as the long-chain PFAS (Kärrman et al., 2019; Wang et al., 2013), they might accumulate in the environment until they reach a level that is toxic to plants, animals, or humans. Perfluorobutane sulfonic acid (PFBS), which is considered safe because it does not bioaccumulate as much as the long-chain PFAS and has low toxicity (Wang et al., 2013), was found in one of the samples. Along with Gebbink et al. (2016), who also found PFBS in ringed seal, polar bear and killer whale, this should raise concern for whether PFBS is
reaching toxic levels. Li et al., (2020) also concludes that the short-chain PFASs pose a threat to both humans and ecosystems due to high mobility in aquatic environment and high
persistence.
The PCA show some correlations, both positive and negative, between samples and PFASs. The long-chain PFASs show the highest levels in all samples, and the short-chain PFAS are amongst the PFAS with the lowest concentrations. That the short-chain PFASs are among the lowest concentrations could indicate that they do not bioaccumulate as much as the long-chain PFAS and are working as replacements regarding the current health of animals and humans. As stated in the paragraph above, this does not mean that it will be a sustainable solution if these short-chain replacements grow to toxic concentrations in the environment. Nevertheless, this should be a positive result with consideration of the current health of the pilot whales.
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Just as in the study by Dassuncao et al. (2017), there are considerable differences for the individual whales in the present study both regarding TOF and PFASs. These individual differences create uncertainties in the trends. The trends might look different with more information about the whales, or with more samples from each year. As concluded in Dassuncao et al. (2017), gender and age of the whales are important factors to the levels of PFAS found; this makes it more difficult to generalize the results from experiments that might be comparing an old male to a young female. With more information about the whales, e.g., age and gender, the trends might have a higher R2-value and give more reliable results of
the development.
PFAS in the food-chain
Pilot whales are a part of the diet for the population on the Faroe Islands. With all the health risks from PFAS, concluded by Piekarski et al. (2020), Knox et al. (2011), Sunderland et al. (2019) and Wang et al. (2011), this tradition constitutes a direct health threat to the
population on the Faroe Islands. Through biomagnification, the species at the top of the trophic levels (e.g., humans and pilot whales) get the highest levels of PFAS and other environmental POPs (Klaassen & Watkins, 2015). Because of this, PFASs should constitute an issue not only to the population on the Faroe Island; they should be a health risk to all humans and animals with a diet consisting of much fish. The Faroese food and veterinary Authority recommends the population on the Faroe Islands not eat pilot whale more than once a month, and liver should never be consumed (Faroese Food and veterinary Authority., 2011). PFAS concentrations have been found to be about ten times higher in liver compared to muscle in pilot whales (Dassuncao et al., 2019). Dassuncao et al. (2017), show a range from about 1,5 – 8 ng F/g in PFOS in the muscle tissue of pilot whale they investigated, which can be compared to the range from 4,7 – 37 unit in the present study (Appendix 2, table A2). Even as these two studies have different extraction methods and analysis methods this indicates one reason for the total ban on consumption of liver from pilot whales in the Faroe Islands. EU has established a tolerable daily intake (TDI) for PFOS and PFOA (Knutsen et al., 2018). It is good that there are restrictions in place, but it could be time to review whether the TDI should be on TOF instead of a few targeted PFASs.
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Conclusion
The short-chain PFASs may be working as a replacement for the long-chaind PFAS at present, but in the long run, they are posing a threat due to high insecurity of their effects in ecosystems, animals, and humans. Maybe replacements for PFAS altogether needs to be identified to eliminate the health risks that they may pose.
For future research on PFAS in aquatic mammals, more information about the individuals is necessary; this would bring clarity in the trends and whether the concentrations are declining, increasing, or staying the same. Pooling samples and only analysing whales of the same gender and about the same age would be a good way to make the results of a study easier to generalize and secure trends over the development. Research comparing the environmental levels to that of aquatic mammals such as the study by Kärrman et al. (2019) but in a time-line perspective would be interesting to view the correlation between the PFAS
concentrations in animals and the water where they live.
Acknowledgments
I would like to thank Ulrika Eriksson who have been my supervisor throughout the work with this paper, her help in the lab and feedback on the text has been essential to the completion of this study. I would also like to thank Rudolf Aro for his support in the lab with performing the analysis. Finally, I would like to show my gratitude to my classmates for all the support you have given me by reading the text, giving feedback, and keeping my motivation on top, thank you!
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Appendix 1
Table A1. Recovery of IS from this study and the study by Kärrman et al. (2019). Recovery internal standard This study Kärrman et al
FTSA 30-59,5 136,3-155,5 PFCA 15,7-37,2 3,7-65,4 PFSA 28,4-45,4 32,2-46,5 FTUCA 22,4-24,3 18-26,7 diPAPs 6,2-10,7 PFOSA 2,8 N-EtFOSAA 11,4 34,9
2
Appendix 2
Table A2. Analytes above limit of detection (LOD) in ng F/g.
Analyte 2009 2009 2011 2011 2013 2013 2015 2015 2017 2017 2018 2018
PFBA <LOD <LOD 0,29 <LOD <LOD 0,13 0,12 0,25 <LOD <LOD <LOD <LOD L-PFOA <LOD <LOD <LOD <LOD <LOD <LOD <LOD <LOD 0,19 <LOD <LOD <LOD PFNA 2,15 1,35 3,23 2,33 1,91 0,58 1,67 1,20 3,85 3,85 1,79 0,49 PFDA 6,91 5,59 8,77 3,36 4,05 1,17 1,84 2,23 7,14 6,60 3,44 1,79 PFUnDA 26,40 19,50 21,42 9,09 10,64 4,27 4,30 7,11 15,66 15,13 7,18 4,30 PFDoDA 4,09 2,87 3,12 1,47 1,75 0,82 0,60 1,16 2,36 2,47 0,94 0,73 PFTrDA 20,97 27,41 11,75 8,29 7,22 3,51 2,55 4,30 8,86 20,34 3,25 3,69 PFTDA 2,61 2,13 1,84 1,29 1,03 0,72 0,39 0,67 1,30 1,47 0,56 0,53 PFBS <LOD <LOD <LOD <LOD <LOD <LOD <LOD 0,19 <LOD <LOD <LOD <LOD L-PFHxS 0,06 <LOD 0,36 0,07 0,07 <LOD <LOD 0,18 0,07 0,09 <LOD <LOD PFHpS <LOD <LOD 0,13 <LOD <LOD <LOD <LOD <LOD <LOD <LOD <LOD <LOD L-PFOS 22,56 12,98 36,98 10,16 15,01 4,71 6,39 7,25 20,17 17,56 8,93 5,93 PFDS 0,31 0,24 0,17 0,10 0,10 0,00 0,02 0,08 0,16 0,17 0,04 0,04 7:3 FTCA 1,70 2,89 6,53 3,72 0,67 0,36 0,92 2,41 1,20 1,01 0,18 4,14 PFOSA 9,26 3,96 10,24 7,02 3,29 3,33 0,76 2,57 3,27 4,47 0,98 3,81 FOSAA 0,04 0,08 <LOD 0,01 <LOD 0,01 0,03 0,02 <LOD 0,01 0,10 0,02 SAmPAP 0,19 <LOD 0,34 0,25 0,34 0,25 0,65 0,28 0,25 0,27 0,09 <LOD
3
Appendix 3
A3. All analytes included in the LC analysis.
TFA N-MeFOSA PFDoPA
PFPrPA N-EtFOSA PFTePA
PFBA N-MeFOSE PFHxDPA
PFPeA N-EtFOSE 6:6 PFPiA
PFHxA PFOSA 6:8 PFPiA
PFHpA FOSAA 8:8 PFPiA
L-PFOA N-MeFOSAA 6:10 PFPiA
Br-PFOA N-EtFOSAA 8:10 PFPiA
PFNA SAmPAP 6:12 PFPiA
PFDA diSAmPAP 10:10 PFPiA
PFUnDA 6:2 monoPAP 8:12 PFPiA PFDoDA 8:2 monoPAP 6:14 PFPiA PFTrDA 10:2 monoPAP 10:12 PFPiA
PFTDA 4:2 diPAP 8:14 PFPiA
PFHxDA 4:2/6:2 diPAP 12:12 PFPiA PFOcDA 2:2/8:2 diPAP 10:14 PFPiA
PFetS 6:2 diPAP 14:14 PFPiA
PFPrS 4:2/8:2 diPAP 11ClPF3OUdS PFBS 2:2/10:2 diPAP 9ClPF3ONS
PFPeS 8:2 diPAP T-PFECHS
L-PFHxS 6:2/10:2 diPAP ADONA Br-PFHxS 4:2/12:2 diPAP HFPO-DA PFHpS 6:2/8:2 diPAP HFPO-TA L-PFOS 4:2/10:2 diPAP Br-PFOS 8:2/10:2 diPAP PFNS 6:2/12:2 diPAP PFDS 10:2 diPAP PFDoDS 8:2/12:2 diPAP 4:2 FTSA 6:2/14:2 diPAP 6:2 FTSA 10:2/12:2 diPAP 8:2 FTSA 8:2/14:2 diPAP 3:3 FTCA 12:2 diPAP 5:3 FTCA 10:2/14:2 diPAP 7:3 FTCA 8:2/16:2 diPAP 6:2 FTUCA PFHxPA 8:2 FTUCA PFOPA 10:2 FTUCA PFDPA
