We thank Inger Lise Nerland Bråte, Cecilie Singdahl-Larsen and Rachel Hurley at NIVA for laboratory work and method development. This study (FÍNPlast 2019:190002) was financed by Nordic Council of Ministers Ocean group and we are grateful for their support.
The Arctic and Sub-Arctic waters have historically been considered pristine environments with a relatively low pressure on the environment from a low population density (Kummu & Olli, 2010). However, economic activities in the Arctic have been occurring for centuries, especially since the whaling period in the 17th and 18th century (Kruse, 2016), resulting in changes to its natural environment. Presently, anthropogenic effects in the Arctic are increasing due to not only activities based in the Arctic, but also the global impacts of climate change - largely stemming from activities based outside of the Arctic (Huskey, Mӓenpӓӓ, & Pelyasov, 2014). These impacts are complex and link together non-Arctic and Arctic issues. As an example, between 2012-2019 there has been a slight overall increase in Arctic fisheries and cruise activity with trends of stretching operational seasons and expanding navigational areas for the fisheries and cruise ships (Stocker, Renner, & Knol-Kauffman, 2020).
Even though from a global perspective the population density decreases in the higher latitudes, the GDP (Gross Domestic Product) increases steadily towards the higher latitudes and only decreases again in the most northern latitudes between 80°N and 90°N (Kummu & Olli, 2010). The moderate increase of the population in the Arctic (Jungsberg et al., 2019) but moreover the anthropogenic development in these northern regions places pressures on the environment (Huntington et al., 2007). The growing development of human activities in the Arctic, plus the growing importance of understanding the interconnectedness of Arctic ecosystems has prompted further research on global to local aspects of anthropogenic impacts. One of the more recently discussed topics is the presence of microplastics in Arctic marine ecosystems (Halsband & Herzke, 2019; Tirelli, Suaria, & Lusher, 2020; Van Sebille et al., 2015).
The Nordic and Arctic are underrepresented in research regarding plastics in the marine environment (Halsband & Herzke, 2019; Tirelli et al., 2020). Even though relatively little is known about plastics in these remote regions it is evident that microplastics are also present in Arctic marine, terrestrial, and freshwater ecosystems. The origin of the plastics in the Arctic ranges from local to international (Cózar et al., 2017; Falk-Andersson & Strietman, 2019). An exploration into the origin of plastics from selected beaches on Svalbard indicated that the majority of identifiable litter originated from Norwegian and Russian fisheries (Falk-Andersson & Strietman, 2019). Additionally, objects were found with text indicating origins from Denmark, Germany, and England.
On land, plastics enter the natural environment and are then transported towards the oceans. This can be via sewage into nearby water bodies or rivers, from further inland by runoff into the rivers, or via airborne transport. In the Arctic, sewage is often not treated, leaving a high proportion of smaller non-compostable items being washed out into the nearby waterbodies which eventually lead into the oceans (Gunnarsdóttir et al., 2013; Magnusson et al., 2016; von Friesen et al., 2020). Rivers are seen as the main transporter of plastics from land to sea (Li, Tse, & Fok, 2016). Recent research has shown that larger debris of low-density polymers are transported all the way out to sea, while the smaller and higher density polymers are most likely retained within the river sediments or at the beaches due to the hydrodynamics of rivers (Schwarz et al., 2019). There is little or scarce research on Arctic rivers, but a pilot study has detected microplastic fibres in a Svalbard river (Carlsson and Lusher, in prep) as well as the rivers releasing into the Siberian Arctic (Yakushev et al., in press).
Figure 1: Washed up plastic debris on a beach at Hórnstrandir nature reserve in the northwest of Iceland. Collected pile of marine debris with mainly plastics (picture by Silja Rán Guðmundsdóttir).
Plastics can also be deposited directly into the sea from fishing, aquaculture, shipping and other activities in the offshore and coastal areas (GESAMP, 2020; Lusher & Pettersen, 2021). Once plastics enter the marine environment, they can either float or sink depending on the particle characteristics and environment conditions. Plastics that are denser than the surrounding seawater will sink when they enter the water. However, plastics that float due to their lower density can be subjected to biofouling, thereby increasing their weight and leading to sinking as well (Thevenon, Carroll, & Sousa, 2014). Photo-, mechanical or biological degradation can also influence the buoyancy of plastics (UNEP, 2016). When floating, plastic can be transported by the waves and currents (Van Sebille et al., 2020). Based on modelling data and field observations it is suspected that plastic debris can come to the Arctic from much farther away via the poleward branch of the Thermohaline Circulation (Cózar et al., 2017). From research it is now known that there is indeed marine litter observed throughout the Barents Sea, of which the majority is plastics (Grøsvik et al., 2018). The majority of the beached materials on Svalbard originated from the fishing industry (Falk-Andersson & Strietman, 2019). This was also observed during the annual OSPAR beach clean-up on Hórnstrandir in Iceland (Figure 1).
The impacts of plastics on marine ecosystems are varied and depend on the size of the plastic encountered (GESAMP, 2020). For example, a large plastic item might have more visible and physical effects on an organism, whereas smaller microplastics may be internalised and have sublethal impacts (e.g. Halsband & Herzke, 2019; Kühn & Van Franeker, 2020; Provencher et al., 2020). One of the more obvious issues is the entanglement of organisms in plastic waste (Figure 2). This might obstruct the organisms in their movement, which can lead to lower fitness, mobility and eventually death (Laist, 1987). Another possibility is that organisms would ingest the particles (e.g. Wesch et al., 2016). There have been several studies investigating the presence of plastics (mostly microplastics) in the digestive tracts of fish (reviewed in Collard et al., 2019; Markic et al., 2019) . As research progresses the number of different species identified to show some level of microplastic contamination is growing, for example, during their critical review Markic et al. (2019) found that of the 494 species examined, 65% presented plastic ingestion. Some of the criticisms surrounding field observations is that it is hard to determine consequences of ingestion, on the other hand laboratory studies on the effects of plastic ingestion often use concentrations of exposure materials which are not environmentally relevant. To add more complexity to the situation, plastics in the ocean might act as a passive sampler of (toxic) compounds present in the water and thereby increase the content of a suite of hydrophobic compounds in the plastics. Whether these compounds are delivered to the animal (when plastics are ingestion), or that plastics actually adsorb compounds from the animal will depend on physical-chemical factors (UNEP, 2016). However, in field studies it is argued that the current concentrations of plastics are not high enough to cause severe harmful effects to marine life and that it is more likely that plastics act as a passive sampler than vector for persistent organic pollutants (POP) (Herzke et al., 2016; Koelmans et al., 2014).
Figure 2: North Sea crab entangled in a ghost net (picture by Pernilla Carlsson).
So far the presence of plastics has been recorded in every possible marine environment from washing up on coastal areas worldwide (Browne et al., 2011), sinking to the deep sea (Peng et al., 2018; Taylor et al., 2016), floating in tropical and polar waters (Lebreton et al., 2018; Van Sebille et al., 2015), to being locked in and drifting with the sea ice (Obbard et al., 2014; Peeken et al., 2018). The Arctic is no different, marine plastics are widespread and at the same time there are many areas of research on marine plastics that lack basic information (Halsband & Herzke, 2019). One of these research areas is the limited knowledge on plastic ingestion in fish (Bråte et al., 2017; Halsband & Herzke, 2019).
Litter and microplastics have gained increasing interest and awareness during the last years. There is research on the ingestion of plastics by the Northern Fulmar that has shown that the further north one goes the fewer plastics are observed in their stomachs (Trevail et al., 2015). These records spanning multiple years are helpful in plotting trends in plastic occurrence in the marine environment over time. This sort of monitoring is not yet possible for all species due to the lack of a successful standardization of methodologies.
Methods for ingested microplastic analyses are under constant development. However, there are many reports on microplastics with low or lacking quality assurance of the data process, e.g. lack of contamination control (including surrounding air), replicates, data treatment and upscaling of recordings. Some of these problems come from the nature of developing a new method, some from little understanding of chemical analyses and the lack of sufficient amount of (financial) resources. There is a need for standardisation and establishing methods for analyses that are robust enough to give good data, also in small laboratories with little equipment, within set limits.
The extraction and identification of microplastics and other anthropogenic particles from biota samples can be a complex and challenging scenario (Lusher et al., 2020a,b). In the early days of microplastics research, visual sorting was the primary method for separating microplastics from biota samples (reviewed in Lusher et al., 2020c; Lusher et al., 2017a). In particular, there was a specific focus on stomach contents and intestines of fish (e.g. Lusher et al., 2013; Bråte et al., 2016; Murphy et al., 2017). The methods involved opening and visually sorting observed material with the use of a microscope. This method has also been adopted by the Marine Strategy Framework Directive Technical Subgroup of Marine Litter which recommend that the entire gastrointestinal tract (GI) is assessed under a dissecting microscope (MSFD-TSML, 2013).
Dissection followed by visual sorting is inexpensive and relatively easy for gastrointestinal tract (GI) and whole bodies of some organisms. Visual sorting is also advantageous as there are no chemical hazards and the cost is mostly minimal (apart from work hours). However, there are some limitations with this approach, firstly this method of investigation is relevant for microplastics >500 µm in size as isolation is limited to the visual acuity of the researcher carrying out the task (Isobe et al., 2019; Lusher et al., 2020b). Secondly, in some instances there is a large amount of undigested, or partially digested food items that can hinder visual sorting. Thirdly, visual sorting can lead to false positives or elevated particle counts because (i) samples can be at risk of procedural contamination and (ii) identification is dependent on the personal skills to separate anthropogenic from biological particles. Thus, visual identification (especially of particles < 500 µm) is not as reliable as chemical identification due to human error. Lastly, visual sorting is reliant on confirmation of isolated particles using further analytical techniques.
To assist visual identification, there are several methods available such as digestion of organic matter prior to the analysis of plastic in fish digestive tracks as will be discussed in later sections. The digestion of organic matter facilitates the visual identification of anthropogenic particles. Currently a wide range of chemicals, procedures and technologies are used in microplastic research to assist in the visual identification of anthropogenic particles. The lack of methodology standardization complicates comparison between studies. Contributing to the development of a standardized method for microplastic analysis in fish digestive tracks was the main goal of the FINPlast (Faroes Iceland Norway Plastic ingestion in fish) project.
The study subject for the development of a standardized methodology was Atlantic cod (Gadus morhua). Cod was chosen due to its economic importance for many of the Nordic and Arctic countries. Pre-existing data from Norway were compared along with samples from Iceland and the Faroe Islands. In each sample location, the method was adjusted based on lessons learned from the previous sample location, starting with Norway and ending with the Faroe Islands. Microplastic in Atlantic cod in the North Atlantic and European Arctic has been recorded for eastern Canada where 2% of the examined cod contained plastics in their stomachs (Liboiron et al., 2016) and in Norway where no plastic particles were found in the samples from the Arctic region of the study but up to 27% of the sampled cod in Bergen harbour contained plastics (Bråte et al., 2016). With the variations in methodological approaches and concentrations of plastics observed in cod as elaborated on in the background, the FINPlast project aimed to:
The focus of this report is to come to a method that can be applicable from high tech laboratories to small rural (science) communities with minimal laboratory resources, which are quite common in Arctic areas. This was done by means of applying a method development strategy.
Based on previous research and our own experiences prior to the current project, we identified a base method that could be adapted to improve aspects such as digestion and filtration efficiency with the goal to have a more successful microplastic identification at the end of the process.
To evaluate whether the methodology fulfilled ours goals for this project there have been several criteria formulated to which the method should at least adhere, and some in which it should outperform other methodologies known to be suitable in microplastic analysis in digestive track samples.
The method should:
To achieve this, FINPlast build on existing knowledge which was implemented in different Nordic laboratories during the project.
At the start of the project a choice was made to do a full digestion of the stomach and intestines instead of visual identification of particles and manual separation from other stomach content as was done previously by Bråte et al. (2016) in Norway. The underlying idea was that in this way more and smaller particles would be captured due to a smaller human factor involved as the identification part of the study would be done on a ‘cleaner’ sample, i.e. with less organic material obscuring the particles. Therefore, this section will only discuss those methods which are used to digest organic materials in microplastics analysis.
In general, there are four ways to treat fish stomachs with the aim of digesting organic material, namely acid, alkaline, oxidizing or enzyme treatments. Acid treatments have been used on a wide range of biological tissues from cellulose, fatty to protein and calcareous based materials. Alkaline treatments on the other hand can degrade cellulose, fatty and protein-based tissues but does not work well on calcareous materials. The oxidizing treatment is also effective on cellulose, fatty and protein-based tissues. Finally, an enzyme treatment breaks down the widest range of ‘soft’ biological materials.
During an evaluation study of different treatments it was shown that acid was least effective (72–83% efficiency), followed by an optimized alkaline treatment of 10M NaOH at 60°C for 24h with an efficiency of 91.3±0.4% (Cole, et al., 2014). The significantly most efficient treatment was the optimized Proteinase-K treatment (>97%). However, this is much more expensive than the other treatments as well. Dehaut et al. (2016) looked at six chemical dissolvent treatments, including the NaOH treatment from Cole et al. (2014). Dehaut et al. (2016) showed that five of these resulted in degradation of the microplastic particles and/or insufficient tissue digestion. The protocol in the study with a 10% KOH solution incubated at 60°C for 24 hours resulted in efficient digestion and no significant damage to the tested polymers, although cellulose acetate (found for example in cigarette butts) was affected. KOH is cheaper compared to the enzymatic treatment and has minimum damage on a range of polymers (Dehaut et al., 2016).
Though all treatments will digest organic tissues, they each work differently. Below an overview is given regarding the advantages and limitations of each of these general methodologies (Table 1). One must remember that for each methodology there are several chemicals or enzymes available which can be used with each their own advantages and limitations. The overview here is focussed on the more general advantages and limitations.
|Alkaline||Degrades biological material|
Cheap and easily available
Easy to use
|Affects cellulose acetate|
Can bleach (viscose) fibres
|Acid||Degrades biological material |
Degrades calcareous material
Cheap and easily available
Easy to use
|Can severely affect plastics|
|Oxidization||Degrades biological material|
Easy to use
|Not as effective as the other treatments|
|Enzyme||Very effectively degrades biological material||Expensive|
(Often) complicated, requiring several steps
Table 1: Overview of the general known advantages and limitations of each of the four types of treatments for degradation of biological material. Based on several comparison studies (Cole et al., 2014; Dehaut et al., 2016; Enders et al., 2017; Karami et al., 2017; Lusher et al., 2020).
In the past years there have been multiple promising treatments up for consideration as an international standardized methodology. The KOH treatment has shown potential in this due to the relatively low cost, accessibility, effectiveness and minimal damage to the subject of study – plastic polymers - and is therefore the treatment of choice in this study (Table 1). However, there are still many issues to be considered. For example, the varying digestion efficiency among studies. There have been different attempts at using either a different KOH:sample ratio (de Vries et al., 2020; Dehaut et al., 2016; Foekema et al., 2013) or decreasing the incubation temperature and increasing exposure time (Thiele et al., 2019). There have been developments trying a multi-digestion methodology where the sample is first treated with KOH, then filtered and immediately afterwards treated with nitric acid (HNO3) which showed promising results (Schirinzi et al., 2020). Lessons were also learned from other methodologies developed for different matrices such as soil by means of a density separation (Hurley et al., 2018; Karlsson et al., 2017; Thompson et al., 2004). A density separation step could further clean-up the sample as is demonstrated later in this study. However, to be taken into consideration is that each new step complicates the process, can bring a higher contamination risk, becomes more time consuming and increases the costs.
The study described below was recently published (de Vries et al., 2020).
Cod digestive tracts (n=39) were sampled in July 2018 during a sampling campaign by MFRI (Icelandic Marine and Freshwater Research Institute) in cooperation with local fishermen. The cod originated from the Westfjords Fishing Grounds in northwest Iceland. The fish were caught by means of a commercial Danish seine with 135mm mesh size.
Before dissection, the length and weight of the fish were recorded. Thereafter, the digestive tracts were cut out at the throat and the anus, wrapped in aluminium foil, and put inside a plastic bag to be frozen until further processing.
The alkaline digestion method with a 10% KOH solution (100 g KOH in 900 ml prefiltered tap water) was chosen considering the available resources at the time. To get effective and efficient digestion the method was adapted from the study of Foekema et al. (2013) to a ratio of 1:6 (sample:KOH v/v). After adding the KOH the samples were placed in an oven for 24 hours at 60°C as suggested by (Dehaut et al., 2016). This was done to speed up the digestion process. As explained later a lower temperature of 40°C is nowadays advised due to damages to some plastic with higher temperatures. Following incubation, 7.7 g of citric acid was added per 100 mL 10% KOH to neutralize the sample with the aim of making the filtration process easier (Thiele et al., 2019) . The samples were placed in a dark storage room for approximately 24 hours prior to filtration over 47mm Whatmann glass fibre filters (GF/D: pore size 2.7 µm) (Figure 3).
Figure 3: Filtration unit with an electricity driven vacuum pump (picture by Anne de Vries).
After filtration, the samples were analysed under a stereomicroscope. The particles were classified as either sheets, beads, fibres or fragments and recorded with the colour of the particle. For the visual identification three criteria were used to rule out non-plastic compounds by establishing whether (Norén, 2007):
To minimise identification bias, dual identification was used where one researcher carried out the initial count and was verified by a second person. Following the visual identification of particles, the filters were sent to NIVA (Tromsø, Norway) for chemical identification by using an Agilent Cary 630 FTIR (Fourier Transformation Infrared). The FTIR sends light through an interferometer onto the sample which reflects and refracts the wavelengths. The resulting radiation is collected by a detector which registers the variations in energy versus time of the wavelengths. The results yield a graph which is the signature of the particle. This signature was matched with the MicroLite software libraries database. If the match was >60% and certain identifying peaks corresponded between the library and the particle signature, the type of plastics was considered confirmed. In total 10% of the observed particles were chemically confirmed by FTIR.
In microplastic research it is paramount to have a good quality control for potential contamination through the handling of the samples and airborne contamination (Torre et al., 2016; Wesch et al., 2017). This was done by implementing some preventive measures such as cleaning all materials with filtered water between samples and inspecting them under a microscope before use. In addition, clothes worn were made from near 100% non-polymer-based materials such as cotton or wool. Plastic materials for the laboratory were avoided to the largest extent possible. Finally, materials that are in contact with the samples and the air, such as the filtration unit and digestion jars, were covered with aluminium foil to avoid air-borne contamination (Bråte et al., 2016; Dehaut et al., 2016; Hermsen et al., 2017) (Figure 4).
Figure 4: Jars containing dissolved fish guts covered with aluminium foil to prevent air contamination (picture by Anne de Vries).
Besides these preventive measures there were three types of contamination controls in place throughout the processing of the samples from the catch of the fish until chemical identification:
Each of the field, environment and process controls were linked to an individual sample. Hence, the contamination per sample could be calculated by summing up any observations in the different controls and subtracting that from the observations in the corresponding sample. For example, if four black fibres were found in the sample, and one black fibre was found in the environment control and two black fibres in the process control but none in the field control the end result of the microplastic analysis of the sample will be one black fibre. Or, if there were four blue fibres in the sample and three black fibres in the controls the result will be four blue fibres.
The cod from the Faroe Islands were caught on Mýlingsgrunnur, located to the northwest of the Faroe Islands, using a 116 feet box trawl with a mesh size of 40 mm in the codend of the trawl. The fish were caught in October during an annual survey by the Faroe Marine Research Institute (FAMRI). Fish were of a consistent size range of 50 cm ± 10 cm conform the OSPAR guidelines.
During the survey the fish were frozen whole and dissection was done in the laboratory of the Faroese Environment Agency. The individual tissues were afterwards stored in the freezer for future research.
The selection of the stomach samples for this study from the archives was done randomly from three different years.
Based on the experiences in Iceland a list of proposed improvements to the processing of the samples was made with the aim to make the digestion and subsequently the filtration more successful. Other than these the processing of the stomach samples stayed the same as described in 3.1.2 Sample digestion and filtration. The following steps were changed and improved from the method applied on the Icelandic samples:
The stomach samples from the Faroe Islands are from archived samples. The fish were caught and frozen to be defrosted for the sampling of different tissues in the laboratory at a later stage. Microplastic research was at that time not the aim for collecting the stomachs which means that there was no control on air contamination during the collection of the stomach samples.
As will become clear in the next paragraphs the processing of the archived samples from the Faroe Islands required some additional adaptations. The first attempt described here was executed under the same quality control measures as adopted in the Iceland study and described in 3.1.3 Quality control with the exception of the air contamination control during the collection of the stomach samples.
Since the first attempt on processing archived stomachs from the Faroe Islands could not be continued a choice was made to move to a larger equipped laboratory with easier access to the necessary equipment, technologies and expertise to move the project forward.
When the operations moved to the laboratory of NIVA in Oslo, Norway there were several adaptations made compared to the first attempt based on previous experiences in the FINPlast project and the expertise in Norway on processing stomach samples for microplastic analyses.
During the second attempt the steps in the laboratory processing which could introduce procedural contamination were identified and monitored using blanks. As was noted earlier there are no environmental controls to account for contamination during the dissection of the fish.
The contamination verification controls were conducted as follows:
A 10% KOH solution (1.5–1.8 M, pH =14, 20°C) was prepared with pre-filtered reverse osmosis (RO) water. Once the solution was thoroughly mixed it was filtered again through a GF/C filter to remove any impurities introduced at the chemical preparation stage. The solution was maintained at room temperature until required.
The stomach samples were processed in batches (n = 3 batches) between August and September 2020. Stomachs were defrosted at room temperature prior to processing. It was noted that some of the stomachs were in different stages of decomposition (unforeseen delays in transport caused thawing, followed by refreezing until analyses). The level of decomposition was recorded for each stomach, where; (i) stomachs were solid, no decomposition was observed; (ii) stomachs were partially decomposed, with a proportion of the sample in liquid form no longer contained within the stomach; and (iii) sample was decomposed and the sample bag was filled mostly with liquid and no possibility to distinguish between different parts.
Further, it was unclear how clean the sample bags or the outside of the stomachs were before storage, and this process was identified as a possible source of conta|mi|na|tion. As mentioned before, no field blanks are available for these archived samples (the main aim was not to look for plastics), it was necessary to try ensuring that the outside of the stomach was treated differently to the inside. Therefore, partially de|composed stomachs should be treated with caution. As a result, some of the samp|les needed to be treated differently. Intact stomachs were taken from the bag and the outside of the stomach rinsed to remove any external contamination, this was combined with the bag rinse (C). The stomach was then opened and the con|tents flushed using KOH (A/B). Each sample bag was rinsed on the inside to ensure that all material was assessed (C). When samples were decomposed it often meant that the contents were just poured out only amounting to one sample (C). The volume of sample and KOH used was also recorded (see tables in Appendix A for details).
After preparation, additional KOH was added to each glass beaker to increase the volume and aid digestion. Samples were put in an incubator at 40°C, 120 rpm for 48 hours. Originally the time was 24 hours but digestion was incomplete in a number of samples.
Once samples were removed from the incubator, they were filtered through a 150 µm sieve to remove small particulate matter that could clog the filtering apparatus. This method was targeted at particles >200 µm.
Samples were rinsed with filtered RO water in the sieve. The remaining material was resuspended and filtered under vacuum (Büchner) onto 47mm Whatmann GF/C (1.2 µm) filter papers. The sides of the filter funnel were rinsed three times with filtered RO water ensure any particles adhering to the sides are washed onto the filter paper and sealed in a petri dish until dry for visual analysis.
Samples that could not be filtered due to excessive undigested biological material were put to one side for density separation. Samples were subject to two density separation steps, first a freshwater extraction using filtered RO water, and secondly a saltwater extraction (density of 1.4 g/cm3) with NaCl. For each density step the solution was added and the falcon tube containing the sample was vigorously shaken for 30 second. The sample was left to stand for 4 hours before filtering away the overlaying water.
Access to enough laboratory equipment (e.g. glassware) and an oven large enough for processing a suitable amount of samples was challenging in Iceland. A cooperation with a local company made it possible to process the samples in an industrial sized oven (Kerecis ehf).
In the Faroe Islands the local University provided access to glassware and two suitable ovens for the processing of the samples. The processing of the Faroe Islands samples was finalized in Norway. The successful processing of the samples in Norway was partly due to access to enough and suitable equipment. For example, the use of a filtration unit with sufficient power to process the digested solution.
In Iceland there were difficulties experienced with especially the filtration of the samples. In the oven some of the samples formed a thick jelly solution or had a brown (slightly burned) layer floating at the surface of the solution (Figure 5). The thickness of the solution was tried to be resolved by neutralizing the sample with citric acid, which worked to some extent. The brown layer however was difficult to remove or filter. It is thought that this is formed by the chemical reaction between the fatty stomach wall and the KOH.
For the first attempt on the samples in the Faroe Islands a change was made to only use the stomach contents (not the stomach wall), increase the sample:KOH ratio to 1:10 and change the oven temperature and duration to 48 hours at 40°C. These initial changes to the method improved the quality of the solutions prior to the filtration process. There were no more issues of a ‘thick’ solution or brown layer floating on top. Also, the organic material seemed to be better digested when using the higher sample: KOH ratio. Unfortunately, the metal filters did not work as sufficiently as was hoped. It was difficult to make a good seal for the filtration unit with the metal filters. This resulted in some leakage and the metal filters were no longer used furing the first attempt on the samples in the Faroes Island. Eventhough the solution was better digested there was still very fine organic material left that clogged the Whatmann GF/C filters (Figure 6).
On the Faroe Islands a choice was made to change to acetic acid to neutralize the samples as this would in addition dissolve any potential calcium carbonate particles such as bone or shell fragments. This additional step, however, doubled the amount of solution that needed to be filtrated, and thus increasing the load for the filters which did not work satisfactory. This step was therefore removed from the protocol as the issues outweighed the potential benefits.
Figure 5: Floating brown layer after oven incubation step (picture by Anne de Vries).
Figure 6: Very fine organic leftover after filtration (picture by Sjúrður Hammer).
Based on the experiences during the FINPlast project from the start in 2018 in Iceland to the processing of samples from the Faroe Islands in Norway in 2020 we summarize the proposed method for analyses of microplastics in fish digestive tracts in relatively simple equipped rural science communities. In Appendix B a list is included with an overview of the materials required for the execution of this methodology.
Samples should be worked in batches depending on the size of the oven and the amount of shakers that are available. The protocol can be done without a shaker, though this can result in a less effective digestion.
In case there is still leftover that cannot be filtered sufficiently a density separation step can be added. Assuming the sample has a salinity close to freshwater the following steps can be followed for a density separation. Additionally, it is assumed that most of the organic material has been dissolved, sieved or filtrated off during the previous two processing steps. The protocol is based on, and adapted from, the work from Hurley et al. (2018) and is suitable for sediment samples from 1–35 grams.
Any particles that have been visually identified as potentially plastic, or in case of many observation a randomly selected amount of samples, are afterwards analysed with for example an FTIR or Raman to confirm the chemical composition of the particle.
Unless all of the particles are chemically confirmed by for example FTIR, dual identification is required to decrease potential bias in the identifaction process. First, one person performs the entire visual analysis as explained in 4.4 Visual and chemical plastic analysis and then the second person verifies whether the same particles are observed based on category type of the particle and colour though one should not rely too heavily on colour as it is a subjective particle characteristic. In the event when only one person observes a particle it should not be included in the final database.
To test for the effectiveness of the method in capturing the microplastics from the samples a recovery test should be done. A 75g digestive tract sample is spiked with a known number of plastic particles and processed as described in the previous paragraphs.
During the sampling of the digestive tracts an environmental control is placed near the handling station (field air blank). The environmental control is a petri dish with a wetted filter placed inside it. Depending on the sampling method one can choose to have an environmental control per net raised, or per work shift.
Each batch of samples should have at least one environmental control (laboratory air blank), meaning at least one per approximately ten samples. The controls are wetted coffee filters in petri dishes. These controls should be used during the processing of the samples in the laboratory, and during the visual analysis every time samples are exposed to air.
Potential contamination occurring during the processing of the samples is accounted for by means of a procedural blank. The process control is handled the same as the samples, but without the addition of a digestive track sample.
In addition to the various contamination controls, measures should be taken aimed at preventing contamination.
Prior to the start of the FINPlast project a study was done on the microplastic ingestion by cod and saithe from the west coast of Iceland (de Vries et al., 2020). The results are shown as an example of implementation of a relatively simple methodology in a rural area with minimal laboratory resources. The methodology applied is the one described in 3.1 The Icelandic samples.
In the study by de Vries et al. (2020) the Fulton’s Condition Index (CI) was used as an indication of the health of the fish with 1 being a fish in perfect health, <1 indicates a ‘slim’ fish, and >1 a ‘fat’ fish. This was calculated by the means of dividing the weight (W) in grams by the length (L) in centimetres to the power 3 and multiplying the outcome by 100 as shown in equation 1 (Nash, Valencia, & Geffen, 2006).
A total of 39 cod and 46 saithe were analysed for microplastic occurrence in their stomachs and intestines. The saithe were on average smaller (59 cm; 1.95 kg) than the cod (85.3 cm; 6.09 kg), and the cod were older (average: 7–8 years) than the saithe (4–5 years) (Table 2). Finally, the CI of cod was higher (0.96) compared to the saithe (0.86). Of the 39 cod digestive tracks that were analysed, 20.5% contained anthropogenic particles, while of the 46 saithe digestive tracks 17.4% contained anthropogenic particles (Table 2). On average there were 0.23 anthropogenic particles per individual in cod, and 0.28 anthropogenic particles per individual in saithe. Among the detected microplastics one polypropylene (PP) and one polyethylene (PE) particle were confirmed by FTIR in cod, and one particle of PP was confirmed in saithe. The other particles could not be confirmed by FTIR as they were too small for analysis, but they were confirmed through dual ID instead.
|Cod (n=39)||Saithe (n=46)|
|Length (cm)||85.3 (SD=8.7)||69–106||59 (SD=11.7)||40–83|
|Weight (kg)||6.09 (SD=1.80)||3.16–10.01||1.95 (SD=1.25)||0.54–5.47|
|Age (based on weight-age relationship data MFRI (2018))||7–8||6–12||4–5||<3–8|
|CI||0.96 (SD=0.09)||0.68–1.16||0.86 (SD=0.07)||0.71–1.00|
|Total number of fibres||5||8|
|Total number of fragments||4||5|
|Total number of sheets||0||0|
|Total number of beads||0||0|
|Particle occurrence per species (%)||20.5||17.4|
|Average number of particles/individual fish||0.23||0.28|
Table 2: Overview of the detection of anthropogenic particles in the cod and saithe from the west coast of Iceland (de Vries et al., 2020). The average length, weight, age, and condition index have been included.
As was indicated earlier the use of a contamination protocol is paramount in microplastics research. This has become evident when comparing the corrected and uncorrected results of the study (Figure 7). If the results would not have been corrected for the recorded (microplastic) contamination the particle occurrence would have undoubtedly been overestimated.
Figure 7: The relative distribution of microplastic in cod and saithe (in percentage) in the Iceland study (de Vries et al., 2020). The uncorrected results and corrected results are shown side-by-side to indicate the importance of using a contamination protocol.
The statistical analysis did not indicate a significant difference in particle occurrence between the two species. Neither did any of the biological parameters (length, weight, CI, digestive track fullness) explain the presence of particle or total number of particles observed. When highlighting solely the fish containing anthropogenic particles a difference was identified between the species. All cod containing anthropogenic particles were longer than the maturity length (i.e. length >71.4 cm (Marteinsdottir & Begg, 2002), while not all saithe with anthropogenic particles were longer than maturity length (i.e. length >58.4 cm (Tu et al., 2018).
From the Faroe Islands a total of 20 cod stomachs were analysed. The cod were on average 49.6 cm in length and weighed 1,44 kg. The cod had an average condition index of 1,13 and were 2 years old. See Table 3 for an overview of general information concerning the cod samples and the detected anthropogenic particles. To be noted is that only the data from (A) fluid stomach content and (B) solid stomach content is included in the overview due to the high likelihood of contamination from in the (C) bag +rinse and the “whole sample” category. The (C) the bag + rinse is specifically meant for removing any potential contamination that occurred during the handling of the samples prior to the laboratory processing. As for the “whole sample”, it was not possible to distinguish between content within the bag. This made it impossible to distinguish contamination from the actual particle occurrence in the digestive track samples.
|Length (cm)||49.6 (SD = 5.7)||40 – 58|
|Weight (kg)||1.44 (SD = 0.5)||0.63 – 2.30|
|Age (based on length-age relationships conform OSPAR guidelines)||2–3||2–4|
|CI||1.13 (SD = 0.10)||0.95 – 1.32|
|Sample category||Fluid stomach content (A) (n=15)||Solid stomach content (B) (n=12)|
|Total number of fibres||46||12|
|Total number of fragments||2||0|
|Average particle occurrence (%)||60||33|
|Particle length (µm)||150 – 5989||552 – 1831|
|Average number of particles/individual fish||3.3||1.0|
Table 3: Overview of the detection of anthropogenic particles in cod from the Faroe Islands. The average length, weight, age, and condition index of the fish samples have been included. Data from the A and B sample categories have been used for the anthropogenic particle information.
Only one of the air blanks (n=20) contained a single anthropogenic fibre, showing the work within the laminary air flow bench did not introduce airborne contamination of major impact at this stage of processing.
Three batches of procedural blanks were processed. Batch 1 (n=3) and Batch 2 (n=3) did not contain any anthropogenic particles. Batch 3 (n=3) contained a single fibre on each filter.
During density separation, none of the freshwater (n=3) nor saltwater blanks (n=3) contained anthropogenic particles.
The condition of the stomach samples varied with 60% of the samples (n=12) being in a solid condition meaning that the stomachs could be taken out of the bag, rinsed from the outside and then cut open to reveal stomach contents. A further 10% of the samples (n=2) were partially decomposed meaning that some of the stomach content was outside of the stomach. The remaining 30% of the samples (n=6) were very decomposed with much of the stomach content outside of the stomach, in 4 instances the stomach lining was no longer distinguishable from the sample, and thus these samples were processed as a “whole” sample.
See Table 4 for the number of particles per sample category. Of the 20 stomachs, 16 could be opened and the stomach assessed for anthropogenic particles with either fluid or solid stomach content.
(A) Of the stomach flushes containing liquid samples (n=15), 9 contained anthropogenic particle (range 0–10). There were 47 particles identified in total, two of these were fragments, the rest were fibres (96%). Sizes ranged from 150 µm to 5989 µm.
(B) Of the solid contents (n=12), only four of the samples contained anthropogenic particles (range 0–4). A total of 12 particles were identified. They were all fibres ranging in sizes from 552µm to 1831µm.
In total 16 of the bags were rinsed. (C) This includes those where there was some stomach content in the bag but the stomach was still distinguishable. A total of 99 particles were identified (range 0–19). The size of the particles ranged from 120 to 3666 µm.
Four of the bags were processed as whole samples. Two of these did not show any particles the remaining had 9 and 11 particles, of which were fibres in the size range from 207 to 7878 µm.
|Sample name||(A) Fluid stomach contents||(B) Solid stomach contents||(C) Bag Rinse/ |
external stomach rinse
|GM0404||5||-||6||Stomach was empty|
|GM0454||9||-||4||Stomach was empty|
|GM0455||10||-||13||Bag was leaking, poss. sample loss|
|GM1407||-||-||-||9||Extra KOH added - WHOLE|
|GM0624||-||-||-||11||Could not distinguish stomach – WHOLE|
|GM1409||-||-||-||0||Could not distinguish stomach – WHOLE|
Table 4: Number of particles identified in each sample with processing observations included. The “-“ indicates when no sample was available in this category.
See Figure 8 for a boxplot indicating the range of particles found per sample and the average number of particles per sample category.
Figure 8: Anthropogenic particles observed (n) per sample category. The coloured box shows where 50% of the data is located, with the whiskers indicating the lowest and highest value observed excluding the outliers. The outliers are indicated by points, and the mean are marked by X.
Based on the data available it was necessary to compare the values using an Attenuated Total Reflection (ATR)-FTIR. This allowed for identification of the polymer make-up of the particles. To avoid bias, all particles were assigned a unique number which were subsequently entered into a random number generator by one researcher. A proportion of the particles from each category (A, B, C, Whole) were subsequently run through chemical identification by another researcher.
A total of 37 (20%) particles were assessed. The polymer breakdown is displayed in Figure 9. Almost half of the particles (17) were identified as cellulose (45%), which is often hard to distinguish between natural cellulose and modified cellulose, a further 22% (8 particles) were viscose, a form of chemically modified cellulose, 16% (6 particles) were cotton, and 8% (3 particles) polyester. Finally, 2% (1 particle) was composed of acrylic – the only fully synthetic particles and the remaining 5% (2 particles) were of a cotton-elastane blend.
Figure 9: Chemical identification of 20% of the visually identified particles with 5 different polymers identified over the four different sample categories.
Plastics have been found in the marine environment for decades and have now become so widespread that it is observed in every ecosystem (Browne et al., 2011; Lebreton et al., 2018; Peeken et al., 2018; Peng et al., 2018). For scientists to be able to record data on plastic occurrence in this wide range of habitats and species there have been an equally vast array of methodologies developed. Each matrix requires its own considerations in terms of the methodology that is applied.
Studies concerning plastics in fish go back as far as the 1970s (e.g. Carpenter & Smith, 1972; Markic et al., 2019) and current research is fuelled in many cases by understanding the consequences that plastic could have on wild fish populations in terms of sustainable food production (Gamarro, et al., 2020; Lusher & Welden, 2020). With the need for, and will to, expand our knowledge on plastic ingestion by fish there has been a whole range of approaches developed to research the subject. There are many successful ways to gather data on microplastic ingestion by fish, however, the main problem with this is, that studies have become difficult to compare as there are too many things to consider for comparisons between studies. The first steps towards harmonising methodological approaches has begun by researchers striving to optimising methods (Avio, Gorbi, & Regoli, 2015; Cole et al., 2014; Dehaut et al., 2016; reviewed in Markic et al., 2019), but still a lot of questions remain especially in terms of validating different methods to ensure they can be compared effectively (Cowger et al., 2020; Lusher et al., 2020a,b; Markic et al., 2019).
Standardization starts with the collection of the samples to be analysed. With the aim is to be able to monitor the status of the environment the question of which species to use as an indicator is important to explore. When considering a species for plastic monitoring in the marine environment, the feeding behaviour, habitat preferences and life stage should be taken into consideration. These components are closely interlinked and variations can create problems in standardizing data. For example, one species can have different habitat preferences and feeding behaviour at different stages of its life. As a fish grows continuously over its lifespan, length can be a substitute for life stage/age. Differences in length and thus lif stage/age within one species of different lengths, especially juveniles versus adults, could potentially yield different plastic ingestion rates due to their differences in behaviour. Selecting fish based on their length decreases the influence of different feeding behaviours. Young cod for example prefer the benthic environment and have a diet with more crustaceans compared to older cod, which are more benthic-pelagic dwellers and have a more fish based diet (FishBase, 2018). Similarly, different species have incredibly varied life histories, so the same amount of plastic in two similar-sized species can have a very different applied meaning. Therefore, putting a list together of suitable indicator species depending on their habitat choice and sampling a specific length will standardize the studied group.
Studies on plastic occurrence in the Northern Fulmar (Fulmarus glacialis) (Kühn & Van Franeker, 2012; Trevail et al., 2015) has become the standard for monitoring plastic pollution within OSPAR (Van Franeker, 2019). The Northern Fulmar was considered a suitable monitoring species as it is a surface feeder and therefore can tell something about the developments in the occurrence of floating plastics in the marine environment. To evaluate the occurrence of plastics in coastal waters there has been developments in studies with filter feeders such as muscles, oysters and clams (Bråte et al., 2020; Lusher et al., 2017a). As they are often sessile or have a small distribution range, and additionally are not selective in what they consume, the data is thought to give a good indication of plastic occurrence in coastal waters. However, further offshore it could be more prudent to consider a benthic fish species to research plastic occurrence at the seabed since filter feeders are less common in deeper water or on soft substrates.
Also to be considered is the continuous discussion regarding sample size. There is evidence that with an increased sample size there is a higher detection of plastics (Markic et al., 2019). There has been a significant positive correlation found between sample size up to 10 individuals and plastic detection. The Oslo/Paris Convention for the Protection of the Marine Environment of the North-East Atlantic and the MSFD-TSML recommended researchers to use 50 individuals per site and is supported by recent reviews (e.g. GESAMP, 2020; Markic et al., 2019; MSFD-TSML, 2013). However, the number of individuals chosen are often also linked to the complexity of processing samples.
The main method utilised for (micro)plastic ingestion research in fish was at first visual sorting by dissecting the fish (reviewed in Lusher et al., 2017b; Lusher et al., 2020b). In particular, there was a specific focus on stomach contents and digestive tracts of fish (e.g. Anastasopoulou et al., 2013; Bråte et al., 2016; Lusher et al., 2013; Murphy et al., 2017). In the past years especially, this has become less common (Markic et al., 2019). The desire to also investigate plastic particles <5mm (microplastics) required a different approach. This mainly because visual sorting is limited to the visual acuity of the researcher and thus only to be relevant to be considered for particles >500 µm (Isobe et al., 2019; Lusher et al., 2020b).
Digesting the organic matter and filtering the sample aims to provide the researcher with a ‘cleaner’ sample to analyse. This has resulted in a higher detection of (micro)plastics in fish (Markic et al., 2019). By observing a ‘cleaner’ sample it becomes easier to identify anthropogenic particles among the organic and other inorganic matter. Additionally, it allows for analysis of smaller particles. As became clear in section 3 there are many ways of digesting the samples. Some are relatively easy and needs minimal (financial) resources while others are complex and consequently requires more technological expensive materials and expertise.
For the filtration step, it is important to consider which size range to consider for monitor plastic occurrence in fish. Factors such as matrix, mesh size and filtration equipment need to be considered. Based on this a decision needs to be made on the lower size limit in the studies. When mesh size for sieves and/or filters in different studies varies, it becomes difficult to compare (micro)plastic findings between studies unless the size distributions of the particles are known (de Vries et al., 2020).
When choosing a suitable standardized sample processing method, the main goal should be a method that effectively digests organic biological matter with no or minimal damage to the subject of study – the plastic polymers - and separates remaining biological matter from the microplastics. As secondary goal, a relatively simple but robust method that requires minimal amount of (financial) resources is preferred. In keeping the methodology straightforward, it will increase the potential for smaller (scientific) communities to participate and provide their input into understanding and monitoring microplastics and not to keep the research within elite, financially well supported institutes.
There are many subjects to consider in making microplastic studies comparable and reproducible. It is paramount to provide as much information as possible. Cowger et al. (2020) published a checklist on guidelines curated by a global network of multi-disciplinary researchers actively participating in microplastics research. It included e.g. laboratory policies (clothing, glassware cleaning), calibration of instruments, data on study subject (length, catch location, date, time of collection), particle descriptions (length, shape, colour), controls (positive controls, replicates, contamination protocol), etc.
To the same extent as transparent reporting procedures, researchers must also strive to generate their data in a repeatable and comparable way. Currently, most of the plastic occurrence data in research is based on visual identification of microplastics after either visual sorting or chemical processing of the samples (Lusher et al., 2020a,b). Visual identification alone is highly subjective and relies solely on the visual acuity on an individual. Dual identification decreases the influence of subjective observations. The use of chemical identification provides a much higher level of confirmation regarding whether a particle is plastic and which kind of plastic material it is (Primpke et al., 2020). Unfortunately, it can be difficult to isolate and analyse small or thin particles, such as fibres with e.g. FTIR or Raman spectroscopy.
In addition, one should be cautious and minimise the dependence on and interpretation of colour and state of the particle in the assessment of plastic identification and contamination verification. Colour and state are subjective recordings and even with dual identification can lead to discussion on categorizing particles as plastic or not. Besides, these might be affected by the treatment such that the original colour is bleached, or the state of the particle is severely affected.
There have been developments regarding standardization on particle identification and data recording (Lusher et al., 2020a). The two main parameters to record about a particle are its size and shape. Among the many publications there is a lack of consistency in recording the sizes and shapes of plastics. In general, plastics can be placed into classes based on size from macro- (>5mm), micro- (<5000–0.1µm) to nanoplastics (<0.1µm) (Lusher, et al., 2017). When considering recording the sizes of particles measuring particles along their longest diameter can give a skewed image on how large particles are. For example, if a fibre is measured along its longest dimensions it can lead to categorizing them as large particles while measuring them over their diameter will place them in a much smaller size class. With this in mind it has been suggested to use Feret’s diameter as an appropriate measure (as reviewed in Lusher et al., 2020a). Feret’s diameter is based on the slide gauge principle where it is defined as the shortest possible length measurement of an object.
Besides size there are different shapes a plastic can occur as. Numerous terms to describe morphology are used such as sheets, beads, pellets, sphere, granule, fragment, films, fibres, filaments, and foams to name some of the common ones (Lusher et al., 2020a). In an attempt to standardize the recordings of this parameter it is suggested to record the main category as either bead, fibre, or fragment and within these categories further differentiate by using sub-categories.
The final subject consider is how to categorize and control for the occurrence of fibres in (micro)plastic studies. Fibres, whether they are plastic or not, are in general of anthropogenic origin, e.g. (treated) wool and cotton from textiles. Since these non-plastic fibres are not occurring naturally, it is important to report fibres in studies since it provides knowledge regarding their fate, occurrence, and distribution. However, instead of reporting them as plastic particles, the scientific community has begun to use ‘other anthropogenic particles’ or similar terms with subclasses such as fabrics, processed wood, and metalwork in scientific articles.
Contamination from surrounding air is of high concern in microplastic analysis (Hermsen et al., 2017; Torre et al., 2016; Wesch et al., 2017). The main problem in microplastics research is contamination by fibres from the working environment. As they are small and light, transportation through air occurs easily. In general, there are some common approaches adopted across studies regarding preventive measures such as (i) covering exposed samples with lids or foil, (ii) rinsing materials thoroughly with filtered water in between samples, (iii) wearing cotton during laboratory work, (iv) decreasing air flow or working in a clean-air cabinet and (v) decreasing handling of the samples as much as possible since each time a sample is exposed there is risk of (air) contamination. Besides preventive measures one must be able to verify the contamination that occurred. The best practice is implementation of environmental and procedural blanks in the same way as is the routine in trace chemical analysis.
One of the main issues observed during the Icelandic samples was the formation of a brownish layer floating on top of the solution which occasionally burned in the oven. This has also been observed during a study by Enders et al. (2017). This made the filtration especially difficult. It is thought that this is because of the fat in the cod stomach wall. KOH is known to have difficulties with digesting hard and fatty materials (Enders et al., 2017). Possible solutions are adding citric acid to neutralise the sample before filtration (Thiele et al., 2019), treating the leftover portion of the sample with nitric acid (HNO3) to digest the remaining organic matter and potential calcareous materials (Lusher et al., 2020b; Schirinzi et al., 2020), or removing the stomach wall and only using the stomach content as was adopted in this study.
In the Faroe Islands samples improvements were seen in the overall digestion of stomach samples by only using the stomach contents and intestines. Besides removing the problem of the fatty stomach wall, it also decreased the digestive load and consequently improved the digestion and therefore the filtration. The improvements in the digestion of the Faroe Islands samples were also due to the increase of the KOH:sample ratio and increase of the incubation period in the oven at a lower temperature.
In using a sieving step prior to filtration of the Faroe Islands samples some of the smaller (organic) matter was washed out. This decreased the load for the filtration unit. The pore size of the sieves is dependent on the lower detection limit in the study which is dependent on the aim of the study itself. By removing the smaller matter from the sample and using glass fibre filters with a larger pore size led to less clogging. Besides the selection of applicable filters for the study it is recommended to use a suitable filtration system with high enough capacity for this type of samples. Additionally, a density separation following the first filtration works well to separate particles from biological material. It allows to capture ‘locked’ particles in the leftover undigested material.
Especially fibrous particles are incredibly complex to work with when assessing them in environmental samples. As already discussed, they can come from procedural contamination through the settling of airborne fibres or from the clothing of the researcher performing the work.
The methodology used for this project was designed to target particles >200 µm, therefore visual ID could be suitable for fragments supported by ATR-FTIR, unfortunately the ATR-FTIR is not always suitable for fibres due to their thin shape. It is difficult to determine the difference between natural based fibres and plastic fibres by visual analysis alone. Visual analysis can be used to help differentiate, but it is less reliable compared to chemical analysis. From both studies described in this report it became evident that with a complete quility control protocol it is possible to include fibres in the study.
The aim of the present study was to provide a best practice guide for the standardization of the analysis of plastics in fish stomach. The method described can be applied in small-scale laboratory with minimal infrastructure, is relatively cheap and easy to implement.
The present study has contributed towards making studies comparable and facilitate monitoring of the Atlantic marine environment regarding plastic pollution. To achieve this, we have developed a methodological protocol which can be applied where laboratory resources are limited.
The method protocol is focused on small-scale laboratories and reducing the need for specialized equipment. Hence, the major equipment needed are an oven large enough to process a reasonable amount of samples in one, a sufficient filtration unit, a microscope and access to chemical analyses, e.g. FTIR, Raman or pyrolysis-gas chromatography. The chemical analyses can be performed in collaborating laboratories with such resources available.
The FINplast project has brought in new knowledge on plastic in cod stomachs from Iceland, the Faroe Island and Norway. Since Norway is one of the countries at the forefront of method development and data gathering on microplastics in the environment our focus was mainly on establishing a method in the Faroe Islands for microplastics in fish and share knowledge. A comparison between cod stomachs in these countries showed a distribution of microplastics particles ranging from 0–27% in detection frequency. The large range is mainly due to different site types included (e.g. open ocean versus harbour and coastal areas).
Finally, the FINPlast project aimed to transfer knowledge between countries and institutions. Despite the worldwide difficulties around the COVID-virus we have managed to keep a continuous dialogue among the participating institutions. The combined efforts led to a suitable proposed methodology which can be applied in small-scale laboratories.
Anastasopoulou, A., Mytilineou, C., Smith, C. J., & Papadopoulou, K. N. (2013). Plastic debris ingested by deep-water fish of the Ionian Sea (Eastern Mediterranean). Deep-Sea Research Part I: Oceanographic Research Papers, 74, 11–13.
Avio, C. G., Gorbi, S., & Regoli, F. (2015). Experimental development of a new protocol for extraction and characterization of microplastics in fish tissues: First observations in commercial species from Adriatic Sea. Marine Environmental Research, 111, 18–26. https://doi.org/10.1016/j.marenvres.2015.06.014
Bråte, I.L.N., Hurley, R., Lusher, A., Buenaventura, N., Halsband, C., & Green, N. (2020). Microplastics in marine bivalves from the Nordic environment. Norwegian Environment Agency Publication Series M-1629|2020, TemaNord r.
Bråte, Inger Lise N., Eidsvoll, D. P., Steindal, C. C., & Thomas, K. V. (2016). Plastic ingestion by Atlantic cod ( Gadus morhua ) from the Norwegian coast. Marine Pollution Bulletin, 112(1–2), 105–110. https://doi.org/10.1016/j.marpolbul.2016.08.034
Bråte, Inger Lise N., Huwer, B., Thomas, K. V., Eidsvoll, D. P., Halsband, C., Almroth, B. C., & Lusher, A. L. (2017). Micro-and macro-plastics in marine species from Nordic waters. https://doi.org/10.6027/TN2017-549
Browne, M. A., Crump, P., Niven, S. J., Teuten, E., Tonkin, A., Galloway, T., & Thompson, R. (2011). Accumulation of microplastic on shorelines woldwide: Sources and sinks. Environmental Science and Technology, 45(21), 9175–9179. https://doi.org/10.1021/es201811s
Carpenter, E. J., & Smith, K. L. (1972). Plastics on the Sargasso Sea Surface. Science, 175(4027), 1240–1241. https://doi.org/10.1126/science.175.4027.1240
Cole, M., Webb, H., Lindeque, P. K., Fileman, E. S., Halsband, C., & Galloway, T. S. (2014). Isolation of microplastics in biota-rich seawater samples and marine organisms. Scientific Reports, 4(4528), 1–8. https://doi.org/10.1038/srep04528
Collard, F., Gasperi, J., Gabrielsen, G. W., & Tassin, B. (2019). Plastic Particle Ingestion by Wild Freshwater Fish: A Critical Review. Environmental Science and Pollution Research, 53(22), 12974–12988.
Cowger, W., Booth, A. M., Hamilton, B. M., Thaysen, C., Primpke, S., Munno, K., … Nel, H. (2020). Reporting Guidelines to Increase the Reproducibility and Comparability of Research on Microplastics. In Applied Spectroscopy (Vol. 74). https://doi.org/10.1177/0003702820930292
Cózar, A., Martí, E., Duarte, C. M., García-de-Lomas, J., Van Sebille, E., Ballatore, T. J., … Irigoien, X. (2017). The Arctic Ocean as a dead end for floating plastics in the North Atlantic branch of the Thermohaline Circulation. Science Advances, 3(4). https://doi.org/10.1126/sciadv.1600582
de Vries, A. N., Govoni, D., Árnason, S. H., & Carlsson, P. (2020). Microplastic ingestion by fish: Body size, condition factor and gut fullness are not related to the amount of plastics consumed. Marine Pollution Bulletin, 151. https://doi.org/10.1016/j.marpolbul.2019.110827
Dehaut, A., Cassone, A.-L., Frère, L., Hermabessiere, L., Himber, C., Rinnert, E., … Paul-Pont, I. (2016). Microplastics in seafood: Benchmark protocol for their extraction and characterization. Environmental Pollution, 215, 223–233. https://doi.org/10.1016/j.envpol.2016.05.018
Enders, K., Lenz, R., Beer, S., & Stedmon, C. A. (2017). Extraction of microplastic from biota: recommended acidic digestion destroys common plastic polymers. ICES Journal of Marine Science: Journal Du Conseil, 74(1), 326–331. https://doi.org/10.1093/icesjms/fsw173
Falk-Andersson, J., & Strietman, W. J. (2019). Svalbard Beach Litter Deep Dive. Svolvaer, Norway.
FishBase. (2018). Gadus morhua, Linnaeus 1758, Atlantic cod. Retrieved from https://www.fishbase.de/Summary/SpeciesSummary.php?ID=69&AT=atlantic+cod
Foekema, E. M., De Gruijter, C., Mergia, M. T., van Franeker, J. A., Murk, A. J., & Koelmans, A. A. (2013). Plastic in North Sea Fish. Environmental Science & Technology, 47(15), 8818–8824. https://doi.org/10.1021/es400931b
Gamarro, G., Ryder, E., Elvevoll, E. O., & Olsen, R. L. (2020). Microplastics in Fish and Shellfish: A threat to seafood safety? Journal of Aquatic Food Production Technology, 29(4), 417–425. Retrieved from https://doi.org/10.1080/10498850.2020.1739793
GESAMP. (2020). Sea-based sources of marine litter – a review of current knowledge and assessment of data gaps. Second Interim Report, 4th June 2020, 120.
Grøsvik, B. E., Prokhorova, T., Eriksen, E., Krivosheya, P., Horneland, P. A., & Prozorkevich, D. (2018). Assessment of marine litter in the Barents Sea, a part of the joint Norwegian-Russian ecosystem survey. Frontiers in Marine Science, 5(72). https://doi.org/10.3389/fmars.2018.00072
Gunnarsdóttir, R., Jenssen, P. D., Jensen, P. E., Villumsen, A., & Kallenborn, R. (2013). A review of wastewater handling in the Arctic with special reference to pharmaceuticals and personal care products (PPCPs) and microbial pollution. Ecological Engineering, 50, 76–85.
Halsband, C., & Herzke, D. (2019). Plastic litter in the European Arctic: What do we know? Emerging Contaminants, 5, 308–318. https://doi.org/10.1016/j.emcon.2019.11.001
Hermsen, E., Pompe, R., Besseling, E., & Koelmans, A. A. (2017). Detection of low numbers of microplastics in North Sea fish using strict quality assurance criteria. Marine Pollution Bulletin, 122(1–2), 253–258. https://doi.org/10.1016/j.marpolbul.2017.06.051
Herzke, D., Anker-Nilssen, T., Nøst, T. H., Götsch, A., Christensen-Dalsgaard, S., Langset, M., … Koelmans, A. A. (2016). Negligible Impact of Ingested Microplastics on Tissue Concentrations of Persistent Organic Pollutants in Northern Fulmars off Coastal Norway. Environmental Science and Technology, 50(4), 1924–1933. https://doi.org/10.1021/acs.est.5b04663
Huntington, H. P., Boyle, M., Flowers, G. E., Weatherly, J. W., Hamilton, L. C., Hinzman, L., … Overpeck, J. (2007). The influence of human activity in the Arctic on climate and climate impacts. Climatic Change, 82(1–2), 77–92. https://doi.org/10.1007/s10584-006-9162-y
Hurley, R. R., Lusher, A. L., Olsen, M., & Nizzetto, L. (2018). Validation of a Method for Extracting Microplastics from Complex, Organic-Rich, Environmental Matrices. Environmental Science and Technology, 52(13), 7409–7417. https://doi.org/10.1021/acs.est.8b01517
Huskey, L., Mӓenpӓӓ, I., & Pelyasov, A. (2014). 4.3.1 General causes of change in the Arctic economy. In Arctic Human Development Report (AHDR): Regional Processes and Global Linkages (pp. 160–161). https://doi.org/10.1007/978-94-007-0753-5_104
Isobe, A., Buenaventura, N. T., Chastain, S., Chavanich, S., Cózar, A., DeLorenzo, M., … Zhang, W. (2019). An interlaboratory comparison exercise for the determination of microplastics in standard sample bottles. Marine Pollution Bulletin. https://doi.org/10.1016/j.marpolbul.2019.07.033
Jungsberg, L., Turunen, E., Heleniak, T., Wang, S., Ramage, J., & Roto, J. (2019). Atlas of population , society and economy in the Arctic.
Karami, A., Golieskardi, A., Choo, C. K., Romano, N., Ho, Y. Bin, & Salamatinia, B. (2017). A high-performance protocol for extraction of microplastics in fish. Science of the Total Environment, 578(December), 485–494. https://doi.org/10.1016/j.scitotenv.2016.10.213
Karlsson, T. M., Vethaak, A. D., Almroth, B. C., Ariese, F., van Velzen, M., Hassellöv, M., & Leslie, H. A. (2017). Screening for microplastics in sediment, water, marine invertebrates and fish: Method development and microplastic accumulation. Marine Pollution Bulletin, 122(1–2), 403–408. https://doi.org/10.1016/j.marpolbul.2017.06.081
Koelmans, A. A., Besseling, E., & Foekema, E. M. (2014). Leaching of plastic additives to marine organisms. Environmental Pollution, 187, 49–54. https://doi.org/10.1016/j.envpol.2013.12.013
Kruse, F. (2016). Is Svalbard a pristine ecosystem? Reconstructing 420 years of human presence in an Arctic archipelago. Polar Record, 52(5), 518–534. https://doi.org/10.1017/S0032247416000309
Kühn, S., & Van Franeker, J. A. (2012). Plastic ingestion by the northern fulmar (Fulmarus glacialis) in Iceland. Marine Pollution Bulletin, 64(6), 1252–1254. https://doi.org/10.1016/j.marpolbul.2012.02.027
Kühn, S., & Van Franeker, J. A. (2020). Quantitative overview of marine debris ingested by marine megafauna. Marine Pollution Bulletin, 151, 110858.
Kummu, M., & Olli, V. (2010). The world by latitudes: A global analysis of human population, development level and environment across the north-south axis over the past half century. Applied Geography, 31(2), 495–507. https://doi.org/10.1016/j.apgeog.2010.10.009
Laist, D. W. (1987). An overview of the biological effects of lost and discharded plastic debris in the marine environment. Marine Pollution Bulletin, 18(6B), 319–326.
Lebreton, L., Slat, B., Ferrari, F., Sainte-Rose, B., Aitken, J., Marthouse, R., … Reisser, J. (2018). Evidence that the Great Pacific Garbage Patch is rapidly accumulating plastic. Scientific Reports, 8(1), 1–15. https://doi.org/10.1038/s41598-018-22939-w
Li, W. C., Tse, H. F., & Fok, L. (2016). Plastic waste in the marine environment: A review of sources, occurrence and effects. Science of The Total Environment, 566–567, 333–349. https://doi.org/10.1016/j.scitotenv.2016.05.084
Liboiron, M., Liboiron, F., Wells, E., Richárd, N., Zahara, A., Mather, C., … Murichi, J. (2016). Low plastic ingestion rate in Atlantic cod ( Gadus morhua ) from Newfoundland destined for human consumption collected through citizen science methods. Marine Pollution Bulletin, 113(1–2), 428–437. https://doi.org/10.1016/j.marpolbul.2016.10.043
Lusher, A. L., & Pettersen, R. (2021). Sea-based sources of microplastics to the Norwegian marine environment. NIVA Report 7568-2021 for the Norwegian Environment Agency, 104.
Lusher, A. L., & Welden, N. A. C. (2020). Microplastic Impacts in Fisheries and Aquaculture. In T. Rocha-Santos, M. Costa, & C. Mouneyrac (Eds.), Handbook of Microplastics in the Environment (p. 28). https://doi.org/10.1007/978-3-030-10618-8_30-1
Lusher, A. L., Bråte, I. L. N., Munno, K., Hurley, R. R., & Welden, N. A. (2020a). Is It or Isn’t It: The Importance of Visual Classification in Microplastic Characterization. Applied Spectroscopy, 74(9), 1139–1153. https://doi.org/10.1177/0003702820930733
Lusher, A. L., Munno, K., Hermabessiere, L., & Carr, S. (2020b). Isolation and Extraction of Microplastics from Environmental Samples: An Evaluation of Practical Approaches and Recommendations for Further Harmonization. Applied Spectroscopy, 74(9), 1049–1065. https://doi.org/10.1177/0003702820938993
Lusher, A. L., Welden, N. A., Sobral, P., & Cole, M. (2017a). Sampling, isolating and identifying microplastics ingested by fish and invertebrates. Analytical Methods, 9(9), 1346–1360. https://doi.org/10.1039/C6AY02415G
Lusher, A. L., Bråte, I. L. N., Hurley, R. R., Iversen, K., & Olsen, M. (2017b). Testing of methodology for measuring microplastics in blue mussels (Mytilus spp) and sediments, and recommendations for future monitoring of microplastics (R&D project).
Lusher, A. L., McHugh, M., & Thompson, R. C. (2013). Occurrence of microplastics in the gastrointestinal tract of pelagic and demersal fish from the English Channel. Marine Pollution Bulletin, 67(1–2), 94–99. https://doi.org/10.1016/j.marpolbul.2012.11.028
Magnusson, K., Jörundsdóttir, H., Norén, F., Lloyd, H., Talvitie, J., & Setälä, O. (2016). Microlitter in sewage treatment systems. https://doi.org/10.6027/TN2016-510
Markic, A., Gaertner, J. C., Gaertner-Mazouni, N., & Koelmans, A. A. (2019). Plastic ingestion by marine fish in the wild. Critical Reviews in Environmental Science and Technology, 50(7), 657–697. https://doi.org/10.1080/10643389.2019.1631990
Marteinsdottir, G., & Begg, G. A. (2002). Essential relationships incorporating the influence of age, size and condition on variables required for estimation of reproductive potential in Atlantic cod Gadus morhua. Marine Ecology Progress Series, 235(July 2002), 235–256. https://doi.org/10.3354/meps235235
MSFD-TSML. (2013). Guidance on Monitoring of Marine Litter in European Seas: A guidance document within the Common Implementation Strategy for the Marine Strategy Framework Directive. Retrieved from https://mcc.jrc.ec.europa.eu/documents/201702074014.pdf
Murphy, F., Russell, M., Ewins, C., & Quinn, B. (2017). The uptake of macroplastic & microplastic by demersal & pelagic fish in the Northeast Atlantic around Scotland. Marine Pollution Bulletin, 122(1–2), 353–359. https://doi.org/10.1016/j.marpolbul.2017.06.073
Nash, R. D. M., Valencia, A. H., & Geffen, A. J. (2006). The origin of Fulton’s condition factor - Setting the record straight. Fisheries, 31(5), 236–238.
Norén, F. (2007). Small plastic particles in Coastal Swedish waters. In N-Research, KIMO Sweden.
Obbard, R. W., Sadri, S., Wong, Y. Q., Khitun, A. A., Baker, I., & Thompson, R. C. (2014). Global warming releases microplastic legacy frozen in Arctic Sea ice. Earth’s Future, 2(6), 315–320. https://doi.org/10.1002/2014EF000240
Peeken, I., Primpke, S., Beyer, B., Gütermann, J., Katlein, C., Krumpen, T., … Gerdts, G. (2018). Arctic sea ice is an important temporal sink and means of transport for microplastic. Nature Communications, 9(1). https://doi.org/10.1038/s41467-018-03825-5
Peng, X., Chen, M., Chen, S., Dasgupta, S., Xu, H., Ta, K., … Bai, S. (2018). Microplastics contaminate the deepest part of the world’s ocean. Geochemical Perspectives Letters, 9, 1–5. https://doi.org/10.7185/geochemlet.1829
Primpke, S., Christiansen, S. H., Cowger, W., De Frond, H., Deshpande, A., Fischer, M., … Wiggin, K. J. (2020). Critical Assessment of Analytical Methods for the Harmonized and Cost-Efficient Analysis of Microplastics. Applied Spectroscopy, 74(9), 1012–1047. https://doi.org/10.1177/0003702820921465
Provencher, J. F., Liboiron, M., Borrelle, S. B., Bond, A. L., Rochman, C., Lavers, J. L., … Hammer, S. (2020). A Horizon Scan of research priorities to inform policies aimed at reducing the harm of plastic pollution to biota. Science of the Total Environment, 733, 139381.
Schirinzi, G. F., Pedà, C., Battaglia, P., Laface, F., Galli, M., Baini, M., … Romeo, T. (2020). A new digestion approach for the extraction of microplastics from gastrointestinal tracts (GITs) of the common dolphinfish (Coryphaena hippurus) from the western Mediterranean Sea. Journal of Hazardous Materials, 397(April). https://doi.org/10.1016/j.jhazmat.2020.122794
Schwarz, A. E., Ligthart, T. N., Boukris, E., & van Harmelen, T. (2019). Sources, transport, and accumulation of different types of plastic litter in aquatic environments: A review study. Marine Pollution Bulletin. https://doi.org/10.1016/j.marpolbul.2019.04.029
Stocker, A. N., Renner, A. H. H., & Knol-Kauffman, M. (2020). Sea ice variability and maritime activity around Svalbard in the period 2012–2019. Scientific Reports, 10(1), 1–12. https://doi.org/10.1038/s41598-020-74064-2
Taylor, M. L., Gwinnett, C., Robinson, L. F., & Woodall, L. C. (2016). Plastic microfibre ingestion by deep-sea organisms. Scientific Reports, 6. https://doi.org/10.1038/srep33997
Thevenon, F., Carroll, C., & Sousa, J. (2014). Plastic Debris in the Ocean: The characterization of marine plastics and their environmental impacts. In UNEP Year Book 2014 emerging issues update. Gland, Switzerland.
Thiele, C. J., Hudson, M. D., & Russell, A. E. (2019). Evaluation of existing methods to extract microplastics from bivalve tissue: Adapted KOH digestion protocol improves filtration at single-digit pore size. Marine Pollution Bulletin. https://doi.org/10.1016/j.marpolbul.2019.03.003
Thompson, R. C., Olson, Y., Mitchell, R. P., Davis, A., Rowland, S. J., John, A. W. G., … Russell, A. E. (2004). Lost at Sea: Where Is All the Plastic? Science, 304(5672), 838. https://doi.org/10.1126/science.1094559
Tirelli, V., Suaria, G., & Lusher, A. L. (2020). Microplastics in Polar Samples. In T. Rocha-Santos, M. Costa, & C. Mouneyrac (Eds.), Handbook of Microplastics in the Environment (p. 42). https://doi.org/10.1007/978-3-030-10618-8_4-1
Torre, M., Digka, N., Anastasopoulou, A., Tsangaris, C., & Mytilineou, C. (2016). Anthropogenic microfibres pollution in marine biota. A new and simple methodology to minimize airborne contamination. Marine Pollution Bulletin, 113(1–2), 55–61. https://doi.org/10.1016/j.marpolbul.2016.07.050
Trevail, A. M., Gabrielsen, G. W., Kühn, S., & Van Franeker, J. A. (2015). Elevated levels of ingested plastic in a high Arctic seabird, the northern fulmar (Fulmarus glacialis). Polar Biology, 38(7), 975–981. https://doi.org/10.1007/s00300-015-1657-4
Tu, C. Y., Chen, K. T., & Hsieh, C. H. (2018). Fishing and temperature effects on the size structure of exploited fish stocks. Scientific Reports, 8(7132), 1–10. https://doi.org/10.1038/s41598-018-25403-x
UNEP. (2016). Marine plastic debris & microplastics: Global lessons and research to inspire action and guide policy change. Nairobi.
Van Franeker, J. A. (2019). Coordinated Environmental Monitoring Programme (CEMP) Guidelines for monitoring and assessment of plastic particles in stomachs of fulmars in the North Sea area.
Van Sebille, E., Aliani, S., Law, K. L., Maximenko, N., Alsina, J. M., Bagaev, A., … Wichmann, D. (2020). The physical oceanography of the transport of floating marine debris. Environmental Research Letters, 15(2), 23003. https://doi.org/10.1088/1748-9326/ab6d7d
Van Sebille, E., Wilcox, C., Lebreton, L., Maximenko, N., Hardesty, B. D., Franeker, J. A. Van, … Law, K. L. (2015). A global inventory of small floating plastic debris. Environmental Research Letters, 10(12), 124006. https://doi.org/10.1088/1748-9326/10/12/124006
Von Friesen, L. W., Granberg, M. E., Pavlova, O., Magnusson, K., Hassellöv, M., & Gabrielsen, G. W. (2020). Summer sea ice melt and wastewater are important local sources of microlitter to Svalbard waters. Environment International, 139(2020), 105511. https://doi.org/10.1016/j.envint.2020.105511
Wesch, C., Bredimus, K., Paulus, M., & Klein, R. (2016). Towards the suitable monitoring of ingestion of microplastics by marine biota: A review. Environmental Pollution, 218, 1200–1208.
Wesch, Charlotte, Elert, A. M., Wörner, M., Braun, U., Klein, R., & Paulus, M. (2017). Assuring quality in microplastic monitoring: About the value of clean-air devices as essentials for verified data. Scientific Reports, 7(5424), 1–8. https://doi.org/10.1038/s41598-017-05838-4
Yakushev, E., Gebruk, A., Osadchiev, A., Pakhomova, S., Lusher, A. L., Berezina, A., … Semiletov, I. (n.d.). Microplastics distribution in the Eurasian Arctic is affected by Atlantic waters and Siberian rivers. Communications Earth & Environment.
Table A1: Sample details. State of samples i – solid, ii – partially decomposed, some solid content still present, iii- decomposed and the bag content was pure liquid.
|Sample name||Date sampled||State of samples||(A) Fluid stomach contents||(B) Solid stomach contents||(C) Bag Rinse/ |
external stomach rinse
|Air blank||Density separation needed?||Comments|
|GM0404||Oct. 2008||ii||Yes||No||Yes||Yes||Stomach was empty|
|GM0405||Oct. 2008||i||Yes||Yes||Yes||Yes||Yes (B)|
|GM0407||Oct. 2008||i||Yes||Yes||Yes||Yes||Yes (A,B)|
|GM0415||Oct. 2008||i||Yes||Yes||Yes||Yes||Yes (B,C)|
|GM0454||Oct. 2010||i||Yes||No||Yes||Yes||Yes (B)||Stomach was empty|
|GM0455||Oct. 2010||iii||Yes||No||Yes||Yes||Bag was leaking, poss. sample loss|
|GM0625||Oct. 2016||i||Yes||Yes||Yes||Yes||Yes (A, B)|
|GM0458||Oct. 2010||i||Yes||Yes||Yes||Yes||Yes (A,B,C)|
|GM0465||Oct. 2010||i||Yes||Yes||Yes||Yes||Yes (B)|
|GM1407||Oct. 2018||iii||No||No||Yes||Yes||Yes (C)||Additional KOH added|
|GM1408||Oct. 2018||iii||No||No||Yes||Yes||Yes (B)|
|GM1410||Oct. 2018||i||Yes||Yes||Yes||Yes||Yes (B)|
|GM1411||Oct. 2018||i||No||Yes||Yes||Yes||Yes (A, B)|
|GM0416||Oct. 2008||ii||Yes||Yes||Yes||Yes||Yes (A, B)|
|GM0460||Oct. 2010||i||Yes||Yes||Yes||Yes||Yes (B)|
|GM0599||Oct. 2016||i||Yes||Yes||Yes||Yes||Yes (B)|
|GM0601||Oct. 2016||i||Yes||Yes||Yes||Yes||Yes (B)|
|GM0624||Oct. 2016||iii||No||No||No||Yes||Yes (C)||Could not distinguish stomach|
|GM1409||Oct. 2018||iii||No||No||No||Yes||Yes (C)||Could not distinguish stomach|
Table A2: Volume of sample and amount of potassium hydroxide (KOH) added (measured in g).
|Sample name||Date sampled||Liquid stomach contents||KOH||Solid stomach contents||KOH||Liquid in bag (+ bag rinse)||KOH||Comments|
|GM0404||Oct. 2008||15.40||95.40||-||-||20.45||64.79||Additional KOH was added to each glass beaker to supplement the digestion- a total of 150–250 ml combined sample went into the incubator. The additional volume was not recorded|
In the table below there is a list of the equipment and chemicals needed. The amounts can vary depending on the sample size and processing methodology. This list is based the methodology described in 4. Proposed methodology.
Table B1 List of materials for microplastic analysis in fish stomach.
|Weighing scale (g)|
|KOH and NaCL solution preparation|
|Beaker for weighing KOH|
|Funnel for preventing spilling and splashing|
|Mixing beaker for KOH solution (2L)|
|Demineralized/Reverse osmosis treated water (KOH, density separation, rinsing materials)|
|Digestion and density separation|
|Glass beakers or jars for digestion (600 mL)|
|Wash bottle for rinsing outside and inside of stomachs with KOH (100 ml)|
|Oven able to hold 20 jars at a time|
|Filtration and (visual and chemical) identification|
|Petri dishes for storing filters and controls|
|Sieve (mesh size depending on lower detection limit in study)|
|Glass fibre filters (pore size depending on study, here assumed 1.2 µm)|
|FTIR (or other, suitable instruments)|
|Weighing scale (g)|
|KOH and NaCL solution preparation|
|Beaker for weighing KOH|
|Funnel for preventing spilling and splashing|
|Mixing beaker for KOH solution (2L)|
|Demineralized/Reverse osmosis treated water (KOH, density separation, rinsing materials)|
|Digestion and density separation|
|Glass beakers or jars for digestion (600 mL)|
|Wash bottle for rinsing outside and inside of stomachs with KOH (100 ml)|
|Oven able to hold 20 jars at a time|
|Filtration and (visual and chemical) identification|
|Petri dishes for storing filters and controls|
|Sieve (mesh size depending on lower detection limit in study)|
|Glass fibre filters (pore size depending on study, here assumed 1.2 µm)|
|FTIR (or other, suitable instruments)|
Methods for laboratories in rural communities
Adriana N. de Vries, Amy L. Lusher, Pernilla Carlsson, Jórun D. Pólsdóttir, Sjúrður Hammer, Catherine Chambers
ISBN 978-92-893-7331-9 (PDF)
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