supplementary materials for The application of tape lifting for microplastic pollution monitoring.pdf

Full text

Appendices for the paper entitled “The application of tape lifting for microplastic pollution
monitoring”
Contents
Authors .......................................................................................................................................................... 2
Appendix A – Additional Figures and Tables ................................................................................................. 2
Additional Figures ...................................................................................................................................... 2
Additional Tables ....................................................................................................................................... 5
Appendix B – The simulation experiment ..................................................................................................... 8
B.1 The quantification of percentage target MP fibre recovery rates ...................................................... 8
B.2 Further details of the statistical analysis ............................................................................................. 9
B.3 Sample preparation for Figure 2........................................................................................................ 10
Appendix C – Post-recovery characterisation of microplastic particles ...................................................... 11
C.1 Polarised light microscopy. ................................................................................................................ 11
Method for Figure 3 ............................................................................................................................. 12
Method for Figure 4 ............................................................................................................................. 12
C.2 Confocal Raman spectroscopy........................................................................................................... 13
Method for Figure 5 ............................................................................................................................. 13
C.3 Fourier Transform Infrared spectroscopy ......................................................................................... 13
Method for Figure 6 ............................................................................................................................. 13
C.4 Interaction with unpolarised ultraviolet and visible light ................................................................. 14
Method for Figure 7 ............................................................................................................................. 14
Method for Figure 8 ............................................................................................................................. 14
Method for Figure 9 ............................................................................................................................. 15
Appendix D – The optical properties of filter fibres and the use of mountants ......................................... 15
Method for Figure D.1 ......................................................................................................................... 15
Method for Figure D.2 ......................................................................................................................... 16
The optical properties of filter fibres ................................................................................................... 16
The use of a mountant......................................................................................................................... 19
Appendix E – Limitations ............................................................................................................................. 20
References ................................................................................................................................................... 22
Declaration of interest ................................................................................................................................. 27
Acknowledgements ...................................................................................................................................... 27

Authors
Claire M. B. Gwinnett*, Amy O. Osborne and Andrew R W Jackson
Criminal Justice and Forensic Science Department, Staffordshire University, The Science Centre, Leek
Road, Stoke-on-Trent ST4 2DF, England, United Kingdom.
* corresponding author (C.Gwinnett@staffs.ac.uk)
Appendix A – Additional Figures and Tables
This Appendix contains materials that are additional to those presented in sections 2 and 3 in the paper.
Additional Figures
(a)
(b)
Figure A.1. Easylift®. Part (a) shows a diagram of one piece of Easylift®. Each piece of that tape has a
75 mm by 25 mm transparent portion, which is coated with adhesive on one side, with two,
blue-coloured non-adhesive handles – one at each end. The tape is supplied with its
adhesive protected by a backing paper, which it can be readily removed. Part (b) shows a
piece of Easylift® after it has been used to capture microplastics from a filter and it has
subsequently been adhered to a microscope slide and examined. The numbered markings
on its surface encircle items that have been identified as being of interest. Such
marking facilitates finding these items at a later time so, for example, they may be removed
by dissection for analysis by FTIR (see Section 3.2.2.2 of the paper for further information
on Easylift®’s compatibility with FTIR).

Figure A.2. A diagram to demonstrate how Easylift® is used to retrieve microplastics from a filter
paper.

(a)
(b)
(c)
(d)
Figure A.3. The dissection procedure used for the removal of microplastic particles from Easylift®
tape lifts. (a) Using a scalpel, the tape is cut through to the glass microscope slide below
to create a ‘V’-shaped flap which covers the particle of interest. (b) A drop of
TissueClear® solvent (available from Fisher Scientific) is added on top of the incision
using a glass pipette. It is then left to soften the tape’s adhesive for 3-5 seconds. (c)
Using metal jewellers’ tweezers, the ‘V’-shaped flap is lifted and (d) the particle of
interest is extracted from underneath the tape.

Additional Tables
Table A.1. Examples of filtration methods and filter papers/membranes as reported to have been
used in microplastic pollution studies.
Reference
Method of filtration (self-
reported description)
Filter used
Stanton et al (2019)
Millipore filtration apparatus
Mixed cellulose ester membrane
filter
Leslie et al (2017)
Filtered
Glass filter paper & Al2O3 filters
Miller et al (2017)
Filtered under vacuum
Mixed cellulose membrane filter
Dyachenko, Mitchell
& Arsem (2017)
Büchner filtration under vacuum
Membrane
Barrows et al (2017)
Glass Büchner funnel under
vacuum
Mixed cellulose nitrate
membrane filter
Lahens et al (2018)
Glassware filtration unit
Glass filter paper
Lusher et al (2015)
Büchner funnel under vacuum
Glass filter paper
Wang et al (2017).
Filtered under vacuum
Glass filter paper
Lusher et al. (2014)
Büchner funnel under vacuum
Glass filter paper
Cordova, Hadi & Prayudhu,
(2018).
Filtered under vacuum
Cellulose filter paper
Ebere et al (2019)
Glass funnel not filtered under
vacuum
Cellulose filter paper
Woodall et al (2014)
Filtered
Glass filter paper
Kanhai et al (2018).
Büchner funnel under vacuum
Glass filter paper
Schönlau et al (2020)
Filtered
Glass filter paper

Table A.2. (a) ANOVA summary for Model 1 and (b) ANCOVA summary for Model 2. The cut points
(i.e. benchmark or threshold values) of partial eta squared and omega squared used to
categorise the effect size magnitude are given in Appendix B.2. The covariate in (b) is the
absolute water content (in grams) of the filter at the point of tape lifting.
(a)
Term
Degrees
of
freedom
F
p
Significant
at
> 95%
confidence
Partial eta
squared
Omega
squared
Filter
1
31.130
0.001
Yes
0.796
(>large)
0.001 (<small)
Funnel
1
11.162
0.010
Yes
0.583
(>large)
0.000 (<small)
Filter:Funnel
1
7.015
0.029
Yes
0.467
(>large)
0.000 (<small)
Residuals
8
NA
NA
NA
NA (NA)
NA (NA)
(b)
Term
Degrees
of
freedom
F
p
Significant
at
> 95%
confidence
Partial eta
squared
Omega
squared
Covariate
1
0.691
0.433
No
0.090
(medium-
large)
0.000 (<small)
Filter
1
17.127
0.004
Yes
0.710
(>large)
0.021 (small-
medium)
Funnel
1
6.591
0.037
Yes
0.485
(>large)
0.007 (<small)
Filter:Funnel
1
7.417
0.030
Yes
0.514
(>large)
0.008 (<small)
Residuals
7
NA
NA
NA
NA (NA)
NA (NA)

Table A.3. The results of simple effects analyses of each of (a) the effect of funnel type at fixed levels
of filter type and (b) the effect of filter type at fixed levels of funnel type. The cut points
(i.e. benchmark or threshold values) of r used to categorise the effect size magnitude are
given in Appendix B.2.
(a)
(b)
Table A.4. ANOVA summary for Model 3, built to test the effect of filter type and funnel type on the
percentage recovery of the target MP particles from the water by filtration. The cut points
(i.e. benchmark or threshold values) of partial eta squared and omega squared used to
categorise the effect size magnitude are given in Appendix B.2.

Appendix B – The simulation experiment
This Appendix (i.e. Appendix B) provides further details of aspects of the methods used in the
experimental and statistical work covered in Section 2 of the paper.
B.1 The quantification of percentage target MP fibre recovery rates
There were three repeat procedures for each of the four unique combinations of the levels of the IVs
(details of the IVs are given in Section 2.2 of the paper). For each such procedure, the following actions
were taken:
Firstly, between 121 and 394 (inclusive) target MP fibres were placed into a pre-weighed, clean, dry
evaporating basin and their exact number (c1) was counted. The basin was reweighed, the mass of
fibres (f) was found by difference and the fibres were transferred by washing into 10 L of tap water
which was divided into ten clean 1 L glass bottles.
A previously unused air-dry filter of one of the two types under test (see Section 2.2 of the paper for
details) was placed in a clean, dry glass Petri dish and the mass of this combination (p1) was determined
by weighing. The filter was then placed in one or the other of the Büchner funnels under test (detailed
in Section 2.2 of the paper). The filter plus funnel assembly was then observed under the light of the
torch (i.e. flashlight) to ensure that assembly was not contaminated with any of the target MP fibres.
The water in each bottle was then vacuum filtered through that assembly. The inside of each bottle was
rinsed with 100 mL of tap water and this rinse water was also passed through the filter used. After all of
the water from the bottles and that rinse water had been passed through the filter, the inner sides of
the Büchner funnel were rinsed with 50 mL of tap water. That rinse water was also passed through the
filter. The vacuum was only broken between 3 and 7 seconds (inclusive) after the last disappearance of
visibly fluid water from the top of the filter.
The filter was then immediately removed from the funnel and returned to its Petri dish, which was then
re-weighed, thereby allowing the combined mass of that dish, the damp filter and the target MP fibres
on it to be known (p2). Also, the number of those target MP fibres on the filter at this point (c2) was
counted.
Then, for each filter, an unused piece of Easylift® was removed from its backing paper and its adhesive-
coated side was then applied to and then withdrawn from the surface of the filter on which the target
MP fibres were residing. This application and withdrawal process were repeated using the same piece
of tape until the entire surface of the filter had been in contact with the tape. For a visual
representation of this tape-lifting process, please see Figure A.2 of Appendix A. The number of target
MP fibres present on the tape (c3) was then counted with the aid of the previously-mentioned torch.
The mass of water present in each filter at the point of tape lifting (w) could not be found by oven drying
the filter concerned to constant mass. This is because, as discussed in Section 3.1.1 of the paper, tape
lifting target particles from a filter also lifts some of the material from which that filter is made.
Therefore, in order to estimate the total mass of water in each filter at the point of tape lifting, 20 of
each of the Cellulose and Glass fibre filters were weighed whilst air dry, oven dried for 16 hours at 105°C
and then re-weighed. The mean mass difference for each filter (d) found by this means for each filter
type was then used in the calculation of w, thus:

w = (p2 - p1 - f) + d
where, as previously defined, p1 is the combined mass of the air-dry filter and the Petri dish, p2 is the
combined mass of that dish, the damp filter and the target MP fibres that were removed from the water
by that filter and f is mass of the target MP fibres that were added to that water prior to filtration.
As described in Sections 2.2.1 and 3.1.1 of the paper, w was used as a covariate in one of the models
used to test the effect of filter type and funnel type on the percentage recovery of the target MP fibres
from the filter by tape lifting with Easylift®.
As described in Section 2.2 of the paper, for each repeat, the target MP fibre count data allowed the
calculation of both:
• the percentage of such fibres present on the filter that were recovered on the tape [i.e. (c3/c2) x
100%] and
• the percentage of such fibres present in the water that were extracted by filtration prior to tape
lifting [i.e. (c2/c1) x 100%].
B.2 Further details of the statistical analysis
As detailed in Section 2.2.1 of the paper:
• two ANOVA models (labelled Model 1 and Model 3) and one ANCOVA (Model 2) were built from
the data generated by the simulation experiment;
• two sets of simple effects tests were completed as a follow up to Model 1.
For Models 1, 2 and 3, the data were checked for deviation from the assumptions that underpin the
veracity of the models concerned and no such deviation was found. For all three of these models, these
checks included the global testing of the assumptions of linear models via a call to the gvlma() function
from the gvlma package for the R programming language (Pena and Slate, 2019), and the Shapiro-Wilk
test of normality plus Levene’s test of homogeneity of variance. For Model 2, the covariate was tested
for independence from the IVs and ANOVA testing was carried out to check for evidence of the violation
of ANCOVA’s assumption of homogeneity of regression slopes. For details of these tests and other
checks completed, and their outputs, see Jackson et al., 2021.
Within each of the two sets on simple effects tests, Bonferroni adjustment was made to the p values to
control the familywise error rate. It was also recognised that these two sets of tests constitute a family.
To allow for this, two values of alpha were used, one without Bonferroni correction (i.e. 0.05) and one
with (0.025). This created the following significance categories: if adjusted p > 0.05 then not significant,
if 0.05 ≥ adjusted p > 0.025 then discussable, and if adjusted p ≤ 0.025 then significant. Any discussable
p values would be those that would have demonstrated significance had only one set of simple effects

tests been carried out. In the event, there were no discussable p values found (see Table A.3, above, for
details).
The effect size measures used were partial eta squared and omega squared for Models 1, 2 and 3, and r
for the simple effects tests. The threshold (i.e. benchmark) values that were used as cut points when
categorising effect sizes are as follows:
• For partial eta squared, small = 0.0099, medium = 0.0588 and large = 0.1379 (Richardson, 2011;
citing Cohen, 1969 pp. 278-280).
• For omega squared, small = 0.01, medium = 0.06, and large = 0.14 (Field et al., 2012 p 455).
• For r, small = 0.10, medium = 0.30 and large = 0.50 (Cohen, 1988 pp. 79-81).
The analysis was performed using RStudio Desktop Open Source Edition version 1.2.5033 (RStudio, n.d.),
running R version 3.5.1 (R Core Team, 2018), with the following packages loaded for use in statistical
testing: gvlma version 1.0.0.3 (Pena and Slate, 2019), effects version 4.1-1 (Fox and Weisberg, 2019), car
version 2.1-5 (Fox and Weisberg, 2011) and phia version 0.2-1 (De Rosario-Martinez, 2015).
All of the raw data, the code that was used to analyse it and the output from that code have been
published as a data set (Jackson et al., 2021).
B.3 Sample preparation for Figure 2
Figure 2 of the paper contains six images. Three of these are of microscope slides prepared using
cellulose filter papers and three using glass fibre filter papers. Respectively, these are the same types of
filter that are denoted Cellulose and Glass fibre in Section 2.2 of the paper.
For each of the six images, the adhesive side of a different piece of Easylift® tape was brought into
repeated contact with the filter concerned such that the whole surface of that filter was tape lifted
once. In each case, the tape was then adhered to a previously unused glass microscope slide, which was
then photographed to produce one of the six images. In all six cases, the filter concerned was one that
was previously unused. For each of the two images labelled ‘Air-dry filter’, there was no pre-treatment
of either of the filters prior to tape lifting. However, immediately prior to tape lifting, for each of the
two images labelled:
• ‘Damp filter’, each of the filters was separately pre-treated by placing it in a ceramic
Büchner funnel and filtering one litre of tap water through it under vacuum. That vacuum
was then broken five seconds after the last of the visibly fluid water had passed through the
filter;
• ‘Wet filter’, each of the filters was separately pre-treated by saturating it with distilled water
until a thin layer of water was visible over the whole surface of the filter concerned.

All photographs were taken using a Nikon AF-S Nikkor 10-70mm camera under identical illumination
conditions using the room’s ambient light, with each glass slide placed on dark card (to provide contrast)
with the Easylift® tape facing the camera.
Appendix C – Post-recovery characterisation of microplastic particles
This Appendix (i.e. Appendix C) provides information further to that given in Section 2.3 of the paper
and should be read in conjunction with that Section. Figures referred to by number (and not by a letter
and a number) are to be found in the paper.
C.1 Polarised light microscopy.
Polarised light microscopy (PLM) enables observations made with the human eye to allow the
birefringence and sign of elongation (SOE) of fibres to be established Palenik (2018). When taken
together, these parameters can be highly discriminating, often allowing the fibre’s polymer class to be
determined.
To establish these parameters, interference colours caused by birefringence are observed as are
changes to these colours consequent on the introduction of birefringent optical devices into the light
path. During use, these devices, which are known as compensation plates, are pushed into that path via
the microscope’s accessory plate slot. Common amongst these plates are the first-order red tint plate
(a.k.a. the full-wave retardation plate) and the quartz wedge. For an introduction to their use in the
characterisation of manmade fibres, see Jackson and Jackson (2008) and see Bradbury et al. [n.d.] for
details of these and other available compensation plates.
In PLM, the interference colours referred to in the previous paragraph can be observed when a
birefringent specimen is illuminated in transmitted light between two polarising filters. On their own,
each of these two would filter unpolarised light to produce plane-polarised light. When both are used,
one of these filters, called the polariser, is placed in the light path between the light source and the
specimen. The other, the analyser, is placed in that path on the specimen’s other side, commonly
between the objective and the eyepiece (or camera). The accessory plate slot is between the specimen
and the analyser.
In common PLM practice, the above-mentioned polarisers are crossed. Under this practice, the
polariser is oriented such that it only allows light with its electric field vector aligned East-West to pass
through it. Also, and in contrast, the analyser’s orientation is such that it only allows through light with
that vector aligned North-South. In the absence of a transparent birefringent material between these
polarisers, the light that is allowed through the first will be blocked by the second. Therefore, under
these conditions, the observed light intensity drops to approach zero and, consequently, the image is
black.
Birefringent materials each have either one or two optic axes. Except when propagated along such an
axis, light passing through such a material encounters double refraction. Double refraction means that,

on entering the material, unpolarised light is split into two beams that each experience a different
refractive index. Furthermore, the light in each of these beams is now plane polarised and its electric
field vector is perpendicular to the other.
Man-made fibres each have a single optical axis which runs down the fibre’s length. Therefore,
unpolarised light that enters the fibre in any other direction is split into two beams that each encounter
a different refractive index. The light in one of these beams has its electric field vector parallel
(symbolised ||) to the fibre’s optic axis; whereas the light in the other beam has that vector
perpendicular (⊥) to that axis. The maximum absolute difference between the refractive indices of
these beams is experienced by light that enters the fibre at right angles to that axis and is known as the
fibre’s birefringence.
Fibres in which the refractive index experienced by the || beam is greater than that experienced by the
⊥ beam, are said to have a positive sign of elongation (SOE). In fibres that have a negative SOE, the
opposite is true. In some texts, the birefringence of a fibre is stated as having a positive value if its SOE
is positive and a negative value if its SOE is negative.
Method for Figure 3
The fibre used in Figure 3 was number 82 (a colourless nylon fibre) from the Microtrace Forensic Fibre
Reference Collection (Microtrace n.d.) it was examined and imaged when viewed between crossed
polars using a Microtec polarised light microscope and, the camera used was a Nikon D80 DSLR with a
Nikkor 35mm 1:1 lens (settings were F stop of 1.8, a shutter speed of 1/20s, ISO of 1600, auto white
balance with no zoom applied). The fibre was orientated with its long axis positioned in the Northwest
to Southeast direction so that its interference colours are visible. In image (a) of Figure 3 there was no
Easylift® in the light path and the fibre was mounted in DPX on a glass microscope slide. To produce
image (b) of Figure 3, Easylift® was adhered to the underside of the microscope slide, after which the
fibre was re-examined and imaged in the same manner described above. This was undertaken to allow
the same fibre to be viewed with and without Easylift® without the need to extract the fibre from the
DPX mountant, which can result in loss of or damage to the sample.
Method for Figure 4
The fibre shown in Figure 4, is a fibre from the authors’ reference collection; its source and composition
are unknown. It was chosen because it exhibits clearly visible dichroism. The fibre was examined and
imaged in plane polarised light, not between crossed polars. That fibre was first imaged with its long
axis in the East-West position without Easylift® in the light path. A glass coverslip with Easylift® adhered
to it was then carefully placed over the top of the slide’s coverslip, the microscope was re-focussed and
a second image was taken with the fibre remaining in the East-West position as before. This process was
repeated, with refocusing as needs be, with the fibre in the North-South position - yielding two further
images, one with and one without Easylift®.
All four images of Figure 4 were taken using the camera of a Samsung SM-G973F (Samsung galaxy S10)
smartphone held with its principal lens approximately 1 cm away from the eyepiece. The camera

settings were: F2.4, 1/90 s, 4.32 mm, ISO 125, auto white balance and no flash. The width of the fibre
was measured using a calibrated eyepiece graticule and was found to be 35.4 µm. Microsoft paint was
used to add a scale bar to each of the images shown in that Figure.
C.2 Confocal Raman spectroscopy
Method for Figure 5
To collect the raw spectra for Figure 5, the method used was adapted from that of Lepot et al. (2008).
Using a Renishaw inVia Raman Microscope with Leica microscope, a ×20 objective lens was used for
simultaneous illumination and data collection. The excitation wavelength used was 514 nm with the
laser intensity and integration time were set to 50 mW and 4 seconds, respectively.
To create Figure 5, the raw spectra obtained by the method described in the previous paragraph were
imported into R version 3.6.3 (R Core Team, 2020) as x, y coordinate data using RStudio Desktop Open
Source Edition version 1.2.5033 (RStudio, n.d.). These spectra were processed using the hyperSpec
package version 0.99-20200213 (Beleites and Sergo, 2020) to correct baseline drift and to enhance the
signal to noise ratio via LOESS smoothing. The raw spectra and the R code used to process them are
available in the public domain (Jackson et al., 2020).
To produce the two central traces shown in Figure 5, a translucent, colourless, cylindrical polyolefin
fibre, taken from sample number 123 of the Microtrace Forensic Fiber Reference Collection (Microtrace,
n.d.), was analysed as described above. Spectral data were recorded first from the fibre in air, between
a glass slide and coverslip, thus producing the lower-central trace of Figure 5. The same analysis set-up,
with the same fibre but now mounted on the slide but under Easylift® was conducted to produce the
upper-central trace of that Figure. To mount the fibre in this way, the glass cover slip was carefully
removed from the slide and, without moving the fibre, a piece of Easylift® tape was placed on top.
Using the same conditions, a Raman spectrum was also recorded from each of a piece of Easylift® tape
adhered to a glass microscope slide and a glass coverslip on top of a glass slide, each with no fibre
present. Respectively, these samples produced the spectra shown in the uppermost and lowermost
traces of Figure 5.
The instrumental settings referred to above were chosen based on the results of initial optimisation
trials, during which the laser intensity and integration times were varied. It is perhaps noteworthy that,
during these trials, when these were respectively set to 100mW and 1 second, the fibre used visibly
deformed, but no deformation or melting was seen in the Easylift® tape.
C.3 Fourier Transform Infrared spectroscopy
Method for Figure 6
The purpose of the experimental work described here was to explore:
• the readiness with which a microplastic particle can be removed from an Easylift® tape lift
by dissection.

• whether a microplastic particle that has been dissected from such a tape lift can be
successfully characterised by Fourier Transform Infrared (FTIR) spectroscopy.
To achieve these goals, a control FTIR spectrum was obtained from a sample of blue polypropylene film
which served as the microplastic particle of interest. This film measured approximately 2mm by 2mm
square and was cut from a plastic bag using a scalpel. That particle was then encased under Easylift®
tape on a glass microscope slide as per a normal tape lifting process. It was then removed from that
environment using the dissection procedure shown in Figure A.3 of Appendix A. Once this microplastic
particle had been extracted from the Easylift® tape by this means, its FTIR spectrum was again obtained.
FTIR spectra were also obtained from both the adhesive and non-adhesive sides of a piece of Easylift®
tape.
All four of these spectra were obtained using the same instrumental settings and are shown in Figure 6.
They were all obtained using Attenuated Total Reflectance (ATR) FTIR spectroscopy. The instrument
used was a Thermo Nicolet, Avatar 370 spectrometer, which runs with OMNIC software. This was set up
to average over 32 scans with a resolution of 4 cm-1. It was equipped with a Specac Golden Gate single
reflection diamond ATR accessory with a ZnSe focusing element.
Before each sample was analysed, the sampling area of the ATR accessory was cleaned until the
spectrum obtained from it was as expected when that sampling area is free of contaminants. This
spectrum was then recorded to serve as the background reading.
C.4 Interaction with unpolarised ultraviolet and visible light
Method for Figure 7
The original transmission spectra used to plot the spectra shown in Figure 7 were recorded at the
Netherlands Forensic Institute by Linda Alewijnse as part of a research project led by Jaap van der
Weerd. Those spectra were recorded in the 200 to 700 nm wavelength range from a number of
specimens. These included each of Easylift®, a glass slide (Menzel-Gläser brand, 1 mm thick) and a
quartz slide (unknown brand, 0.5 mm thick), the spectra of which have been recreated in Figure 7. The
instrument used was a Perkin Elmer Lambda 35 spectrometer. In the case of glass and quartz, to allow
each spectrum to be recorded, the specimen in question was simply placed in the instrument’s
measuring beam. For Easylift®, the specimen was first held by its adhesive in a frame made from
cardboard. To allow its spectrum to be recorded, this frame was then placed in the instrument such
that the sample of interest intersected its measuring beam.
The research reported here only required a subset of the spectra that were originally recorded and so
the spectra of interest were replotted. This was done using R version 3.6.3 (R Core Team, 2020) through
RStudio Desktop Open Source Edition version 1.1.447 (RStudio, n.d.), calling on functions from the
packages jpeg version 0.1-8.1 (Urbanek, 2019), countcolors version 0.9.1 (Weller, 2019a), colordistance
version 1.1.0 (Weller, 2019b) and imager version 0.42.1 (Barthelme, 2020).
Method for Figure 8
The spectra shown in Figure 8 were recorded by Chris Hunter of SMCS Ltd (http://www.smcs.co.uk/)
using an SMCS mspt MicroSpec with 0.8 nm wavelength accuracy taken across the visible spectrum.

Both spectra were obtained from a red nylon trilobal fibre (taken from sample number 87 of the
Microtrace Forensic Fiber Reference Collection [Microtrace n.d.]) mounted in DPX, on a glass
microscope slide under a glass coverslip. The fibre was from BASF USA and the DPX was from Sigma
Aldrich (catalogue number 06522-100ML). A single piece of Easylift® tape was placed on top of the slide
prior to recording the spectrum labelled ‘With Easylift®’.
Method for Figure 9
The images shown in Figure 9 were captured using a LUMNIA-FLHS modular scientific microscope
developed and distributed by SPECTRICON http://www.spectricon.com/spectral-imaging-
products/lumnia-flhs/ (accessed on 28 March 2021) . Both images were taken by Nathanail
Kortsalioudakis of SPECTRICON with the microscope’s MuSES-HS hyperspectral camera using both its
sensors. For image (a) of that Figure, the specimen was illuminated with white LED light (wavelength
400-720 nm). For part (b), the image shows fluorescent light of wavelengths 445, 500 and 600 nm (Full
Width at Half Maximum (FWHM) ± 40 nm) excited by light of wavelengths 405, 473 and 532 nm. This
excitation radiation was provided from above by the microscope’s ring-shaped Polyline diode laser array
that surrounds its objective lens. The instrument’s notched filtering system, located in the light path
between the sample and the camera, was used to effectively eliminate a wavelength band 4 nm wide
that includes the wavelength of the laser light. This filtering system, coupled with the oblique
illumination geometry, allows this microscope to achieve high signal-to-noise ratios in fluorescence
imaging and to do so across almost the entire spectrum. These capabilities are, at least in part,
responsible for the high degree of contrast seen in part (b) of Figure 9.
The fibres shown in Figure 9 are red wool from a sweater, yellow polyester from a high visibility vest,
and peach-pink and white acrylic from a sweater. These were held on a glass microscope slide by a
piece of Easylift® tape.
Appendix D – The optical properties of filter fibres and the use of
mountants
As discussed in Section 3.1.1 of the paper, when Easylift® tape is used to recover microplastic particles
from either of the filter types described in Section 2.2 of the paper, it will remove fibres originating from
the filter paper along with the microplastics. This Appendix will touch on the properties of the filter
paper fibres used in the paper, how they can be differentiated from particulates of interest and methods
to make the microplastics more noticeable to help facilitate the new workflow.
Method for Figure D.1
Each image in Figure D.1 shows a colourless nylon fibre with fibres from either a glass-fibre filter [parts
(a) and (b)] or a cellulose filter [parts (c) and (d)], all viewed in transmitted light. The photomicrographs
in that Figure were taken either using plane-polarised light [parts (a) and (c)] or with the specimen
between crossed polars [parts (b) and (d)]. To prepare the samples, one nylon fibre was placed on each
of two glass microscope slides. The surface of each of a Glass fibre and a Cellulose filter paper of the
types described in Section 2.2 of the paper was then tape lifted with a different piece of Easylift®. Each
of these tapes was then placed over the nylon fibre on one of the microscope slides. Each fibre was
then imaged using a Microtec polarised light microscope using a x 20 objective lens with a Nikon camera

attachment. The nylon fibre used was number 109 from the Microtrace Forensic Fibre Reference
Collection (Microtrace n.d.)
Method for Figure D.2
All of the images shown in Figure D.2 were taken under the same conditions using un-polarised white
transmitted light with a Nikon Eclipse E400 microscope fitted with a Nikon camera attachment.
To create images (a) and (b), several white cotton fibres were placed on a glass microscope slide. Then
an air-dry glass fibre filter paper of the type described in Section 2.2 of the paper was lifted with an
Easylift® tape. This tape was then adhered to the glass microscope slide over the cotton fibres. A cotton
fibre was then located and photographed to create image (a). The slide was then transferred to a
dissecting stereomicroscope, where a ‘V’-shaped cut was made around that cotton fibre, using a scalpel.
Silicone immersion oil (manufactured by Cargille), with a refractive index of 1.5280, was then placed
onto the cut and allowed to seep under the tape and immerse the cotton fibre in question and its
surrounding filter paper fibres. A photomicrograph of that cotton fibre and those filter paper fibres in
the presence of that oil was then taken to create image (b).
Images (c), (d), (e) and (f) were taken in a directly analogous fashion but with fresh materials. The only
other differences being that for images:
• (c) and (d), a cellulose filter paper was used instead of a glass fibre one;
• (e) and (f), a cellulose filter paper was used instead of a glass fibre one and blue cotton fibres
were used instead of white cotton fibres.
As indicated in Figure D.2, each of images (c) and (e) were taken before the addition of the silicone oil
and (d) and (f) were taken after it had been added and allowed to immerse the fibres on the slide
concerned.
The cotton fibres used were from a laboratory coat (white cotton) and clothing of one of the authors
(blue cotton).
The optical properties of filter fibres and the use of mountants with Easylift®
As described in the paper, the use of Easylift® to recover MPs from filters on which they have been
isolated offers a number of potential benefits. Key amongst these are the highly discriminating optical
techniques that can be used to characterise MPs whilst they are in situ on the tape lifts that result from
this recovery process.
However, as noted above, the process of lifting MPs from the surface of a damp filter with Easylift® also
lifts some of the filter’s fibres onto the adhesive of the tape. This means that these fibres will be present
during any subsequent in situ characterisation of MP particles found on the tape. For this
characterisation to be successful, it must be possible to distinguish between the MPs and the fibres from
the filter.

Filter fibres are colourless and transparent whereas many MPs are not, allowing transmitted light
microscopy to make this problem trivial in such instances. Even for colourless, transparent MPs,
discernment between them and filter fibres is, in the main, straightforward when this technique is used.
This is because, as illustrated by parts (a) and (c) of Figure D.1, in the vast majority of cases, morphology
and/or relative size allow the human eye to readily distinguish the difference between these classes of
material. The vast majority of MPs exhibit interference colours when observed between crossed polars.
Parts (b) and (d) of that Figure illustrate how such colours can also be used to reveal the distinction
between MPs and filter fibres. As shown in part (b), this is particularly so when those filter fibres are
glass because glass is essentially non birefringent (Yang et al., 2012) and so does not appear when
viewed between crossed polars. In contrast, cellulose, being birefringent (Uetani, Koga and Nogi, 2019),
does not have this advantage of invisibility under these circumstances.
In plane-polarised light
Between crossed polars
A colourless nylon fibre
with glass filter paper
fibres.
(a)
(b)
A colourless nylon fibre
with cellulose filter paper
fibres.
(c)
(d)
Figure D.1. Photomicrographs of two nylon fibres from the same source. One of these is with glass
filter paper fibres, the other with cellulose filter paper fibres and are both shown as
observed in each of transmitted plane-polarised light and between crossed polars (also
using transmitted light). For each image of this Figure, the specimen is held between
Easylift® and a glass microscope slide. Please see earlier in Appendix D for details of how
these images were created.

As shown in part (a) of Figure D.2, when presented with suitable photomicrographs, humans find it easy
to see the difference between glass filter fibres of the type used in this study and cotton fibres.
However, cotton is cellulosic (De Wael & Lepot, 2012) and it can be difficult to differentiate between it
and cellulose fibres from a filter paper [see parts (c) and (e) of Figure D.2]. This is important for studies
of MP pollution that are also interested in the prevalence of anthropogenic cotton fibres in the natural
environment.
Without silicone oil
With silicone oil
A white cotton fibre with glass
filter paper fibres
(a)
(b)
A white cotton fibre with
cellulose filter paper fibres
(c)
(d)
Blue cotton fibres with
cellulose filter paper fibres
(e)
(f)
Figure D.2. Photomicrographs of cotton fibres with either glass or cellulose filter paper fibres, each
taken with and without a mountant. In these images, the mountant is a silicone oil with a
refractive index of 1.5280 and the light used to illuminate the specimens is transmitted and
not polarised. For each image of this Figure, the specimen is held between Easylift® and a
glass microscope slide. Please see earlier in Appendix D for details of how these images
were created.

For such studies, fibres from the glass-fibre filters used in this study have a second property that can be
used to good advantage. This is that they have an essentially uniform refractive index. This is true both
from fibre to fibre and within any one fibre. These fibres are also colourless and of very low opacity. All
of this means that the addition of a mountant with a suitable refractive index can effectively make these
glass fibres disappear from view whilst retaining a clear outline around any cotton fibres present. This
effect is illustrated in part (b) of Figure D.2. This also means that any microplastic particles that are
present on such a slide that are either coloured and/or have a noticeably different refractive index to
that of the mountant will also be clearly visible against an uncluttered background. This will be so even
when the specimen is viewed in either unpolarised or plane polarised light. Furthermore, because the
fibres of the glass filter are essentially non-birefringent, this invisibility of those glass fibres will also be
maintained should the slide be viewed between crossed polars. This will allow microscopic birefringent
MP particles, such as the vast majority of clothing fibres, to be even more clearly visible when viewed
under such illumination conditions.
Cellulose fibres from the filters used in the work reported here differ from the glass fibres referred to in
the previous paragraph in that they have internal structures which differ in their refractive indices. This
means that the boundaries between these structures show relief, making them visible. Consequently,
these cellulose fibres cannot be made to entirely disappear by careful selection of mountant [see Figure
D.2, parts (d) and (f)].
By removing the necessity for dissection prior to PLM, the use of Easylift® saves time and significantly
reduces the opportunity for the loss of particles or the contamination of the sample. As with other tape
lifts, those made with Easylift® encapsulate the particles of interest in a secure environment such that it
can be safely stored for future study if needs be. In the case of Easylift®, this is currently done by
adhering the tape – together with the particulates of interest that are bound to it – onto a glass slide.
The Easylift® then acts in much the same way as does a glass coverslip in a traditional microscope slide.
Also, it restricts the particulates to lie in a sufficient approximation to a plane for the purposes of the
characterisation of MPs via PLM, microspectrophotometry, fluorescence microscopy, hyperspectral
imaging and confocal Raman spectroscopy.
When making traditional microscope slides, a mounting medium (mountant) – that, at least initially, is
liquid – is commonly placed between the slide and the coverslip, thereby surrounding the specimen
(Cook and Norton [1982] provide a review of the mountants in common use in forensic science). The
mountant serves a number of purposes, namely:
1. it adheres the coverslip to the slide, trapping the specimen between them;
2. if the specimen is thin enough, it restricts it to lie in what is essentially a plane;
3. it controls the refractive index (RI) of the specimen’s environment.
Easylift®’s adhesive performs the first two of these functions and Easylift® can be used without
mountant. However, it is compatible with both aqueous (Fluoromount™ and CC/Mount™) and

nonaqueous (Entellan®) mountants (Stuer, 2016), meaning that such media can be used when control
over the RI of the specimen’s environment is needed.
Appendix E – Limitations
This Appendix sets out the limitations to the work reported in the paper linked to this document. It
should be read in conjunction with that paper.
1. In the simulation experiment, there were two independent variables (IVs), namely the factors
funnel type and filter type – each with two levels. There were also two dependent variables
(DVs) of interest. DV1 is the percentage of target MP fibres present on the filter paper that were
recovered by tape lifting. DV2 is the percentage of such fibres present in the water that were
collected on the filter papers by filtration. In that experiment there were three repeat
determinations for each of the four unique combinations of its factor levels, giving a total
sample size of 12. Models 1 and 2 both tested the effect of the IVs on DV1. The only difference
between these models is that, in Model 2, the total mass of water present in the filter paper at
the point of tape lifting was included as a covariate. The sample size used was sufficient to
detect a significant interaction effect in each of these models (see Table A.2 of Appendix A). We
are confident, therefore, that despite the small sample size, this experiment is fit for purpose so
far as those models are concerned. However, we are mindful that its findings may be
contingent on the specific experimental set up that we employed. Model 3, which tested the
effect of the IVs on DV2, did not find any significant effects (see Table A.4 of Appendix A). As
detailed in Section 3.1.4 of the paper that had the sample size been larger – leading to greater
statistical power – this finding might have been different.
2. The effect of biofilms on the ease with which MPs can be characterised and classified has not
been part of the study reported here. Furthermore, in our simulation experiment, the only
suspended materials in the water were the target MP fibres, which may limit the generalisability
of its findings to real-world samples. The presence of biofilms and/or suspended materials
other than MPs might hinder the tape lifting of MPs using Easylift®. However, this was not found
to be a problem for any of the 224 water samples taken during the expedition mentioned in
Section 2.1 of the paper. It is also possible that the presence of such films and/or suspended
materials might hamper the subsequent in situ analysis of MPs whilst they are held in tape lifts.
We note that Käppler et al. (2015) report that biofilms can impair analysis via Raman
spectroscopy. Our experience with the samples taken during the expedition is that the presence
of biofilms is not problematic when observing MPs using PLM yet can cause some issues with
the quality of Raman spectra.
3. As outlined in Sections 1 and 3.2.1 of the paper, polarised light microscopy is an effective means
of characterising manmade textile fibres whilst they are held in situ in Easylift® tape lifts. To a
large degree, this is possible because:

• the range of the birefringence values of these fibres and their range of thicknesses are
such that measurable optical path differences (OPDs) are typically seen. This is less
likely to be the case with MPs such as microbeads and fragments that are substantively
thicker than typical clothing fibres.
• birefringence values can be an effective means of distinguishing between manmade
textile fibres of different polymer classes. For example, Palenik (2018) cites
polypropylene as typically having birefringence in the range 0.028 to 0.034, whilst that
range for polyethylene is 0.050 to 0.052. Unfortunately, such clear distinction is not
always possible. For example, that range for nylon 6 is 0.049 to 0.061 (ibid.), which
encompasses that of polyethylene. It should be noted, however, that when
birefringence does not offer sufficient discriminating power to distinguish between MPs,
there are other characteristics that can be used to do so. Many such characteristics –
such as shape, Raman spectroscopic profile, fluorescence, colour, and pleochroism – can
be readily determined from particles held in situ on Easylift® tape lifts.
The birefringence of a particle of interest can conveniently be calculated from its OPD
(a.k.a. retardation) and its thickness (Palenik, 2018). Provided that both of these
parameters are expressed in the same units, the birefringence is simply the former
divided by the latter. For any given cylindrical fibre viewed longitudinally, its thickness
at the midpoint across its width is the fibre’s diameter. Of course, because it has a
circular cross-section, that diameter is the same as the fibre’s width – making it easy to
measure. Naturally, this is true anywhere along that fibre’s length. For fibres with non-
circular cross-sectional shapes, methods have been devised by which thickness can be
estimated without recourse to cutting transverse cross-sections (Gorski and McCrone,
1998). This is also true for other classes of specimen (Korkmaz and Tümkaya, 1997),
which may allow such estimates to be obtained for many non-fibre MPs.
However, for non-fibre MPs, factors other than polymer type that affect birefringence
may make the relationship between that parameter and polymer type less clear cut
than is the case with man-made textile fibres. This is not a matter that we have
explored. Instead, to date, for samples gathered in our field work, we have analysed
each non-fibre MP particle in situ using Raman Spectroscopy and/or dissected it from its
Easylift® tape lift and used FTIR to help infer its polymer type.
4. As explored in Section 3.2 of the paper, Easylift® is designed to facilitate the characterisation of
microscopic particles using a range of optical techniques without the need for dissection. These
techniques offer great discriminating power. However, there are many other techniques that
cannot be performed on particles whilst they are held under Easylift® that can be brought to
bear to enhance that power further. Consider, for example, the analysis of colour and

colourants. In a forensic context, colour, as determined using microspectrophotometry (MSP),
can often be used to discriminate between fibres from difference sources (Palenik, Beckert and
Palenik, 2016; Biermann and Wiggins, 2018). As shown in Section 3.2.3 of the paper, Easylift® is
compatible with MSP. However, if the identification of colourants present (rather than colour)
is to be used for such discrimination purposes, and if the use of MSP is not sufficient for this
task, further testing – e.g. via thin layer chromatography (TLC) – will be needed (Biermann and
Wiggins, 2018). For a recent example of the sequential use of light microscopy, fluorescence
microscopy, MSP and TLC in source discrimination amongst fibres of similar colour, see Gora and
Was-Gubala (2019). TLC cannot be carried in situ in Easylift® tape lifts. However, TLC and other
techniques, such as infrared spectroscopy, that are not compatible with the presence of Easylift®
are not precluded by its use. This is because, as shown in Figure A.3 of Appendix A, particles
held under it can be readily removed by dissection.
References
Araujo, C.A., Nolasco, M.M., Ribeiro, A.M.P., Ribeiro-Claro, P.J.A., (2018) Identification of microplastics
using Raman spectroscopy: Latest developments and future prospects, Water Research, 142, pp. 426-
440.
Barrows, A. P., Neumann, C. A., Berger, M. L. & Shaw, S. D. (2017). Grab vs. neuston tow net: a
microplastic sampling performance comparison and possible advances in the field. Analytical Methods. 9
(9). pp. 1446-1453.
Barthelme, S. (2020). imager: Image Processing Library Based on 'CImg'. R package version
0.42.1. https://CRAN.R-project.org/package=imager. (Accessed: 30th April 2020).
Biermann T. W. & Wiggins K. (2018). ‘Colour analysis of fibres’ in Robertson, J., Roux, C. and Wiggins, K.
(eds). Forensic Examination of Fibres. 3rd edn. Boca Raton: CRC Press.
Beleites, C. & Sergo, V. (2020) `hyperSpec: a package to handle hyperspectral data sets in R', R package
version 0.99-20200213. https://github.com/cbeleites/hyperSpec. (accessed 30 April 2020)
Bradbury, S., Abramowitz, M. & Davidson, M. W. (n.d.). Polarized Light Microscopy - Microscope
Configuration. Olympus. https://www.olympus-lifescience.com/en/microscope-
resource/primer/techniques/polarized/configuration/ (Accessed: 22 April 2020)

Cohen, J. (1969). Statistical power analysis for the behavioural sciences. New York: Academic Press.
Cohen, J (1988). Statistical power analysis for the behavioural sciences. 2nd edn. Hillsdale: Lawrence
Erlbaum Associates.
Cook, R &Norton. D. (1982). An Evaluation of Mounting Media for Use in Forensic Textile Fibre
Examination, Journal of the Forensic Science Society, 22 (57) pp. 57-63.
Corami, F, Rosso, B, Bravo, B, Gambaro, A and Barbante, C (2020) A novel method for purification,
quantitative analysis and characterization of microplastic fibers using Micro-FTIR, Chemosphere 238
124564, https://doi.org/10.1016/j.chemosphere.2019.124564 (Accessed: 13th May 2020).
Cordova, M. R., Hadi, T. A. & Prayudha, B. (2018). Occurrence and abundance of microplastics in coral
reef sediment: a case study in Sekotong, Lombok-Indonesia. AES Bioflux. 10 (1). pp. 23-29.
De Rosario-Martinez, H. (2015). phia: Post-Hoc Interaction Analysis. R package version 0.2-1.
https://CRAN.R-project.org/package=phia (Accessed 24th July 2019).
Dyachenko, A., Mitchell, J. & Arsem, N. (2017). Extraction and identification of microplastic particles
from wastewater treatment plant (WWTP) effluent. Analytical methods. 9 (9). pp. 1412-1418.
Ebere, E. C., Wirnkor, V. A., Ngozi, V. E. & Chukwuemeka, I. S. (2019). Macrodebris and microplastics
pollution in Nigeria: first report on abundance distribution and composition. Preprints. pp. 1-19.
Available at: https://www.preprints.org/manuscript/201908.0255/v1. (Accessed: 6th September 2019).
Field, A., Miles, J. & Field, Z. (2012). Discovering Statistics Using R. London: SAGE.
Fox, J. & Weisberg, S. (2011). An {R} Companion to Applied Regression. 2nd edn. Thousand Oaks: Sage.
Available from: http://socserv.socsci.mcmaster.ca/jfox/Books/Companion. (Accessed 14 May 2018).
Fox, J. & Weisberg, S. (2019). An R Companion to Applied Regression. 3rd edn. Thousand Oaks: Sage.
Available from: http://tinyurl.com/carbook. (Accessed 12th July 2019)

Gora, P. & Was-Gubala, J. (2019). Enzymatic extraction of dyes for differentiation of red cotton fibres by
TLC coupled with VSC. Science and Justice. 59 (4). pp. 425-432.
Gorski, A. and McCrone, W. C., (1998). Birefringence of fibers. Microscope. 46. pp. 3–16.
Korkmaz, A and Tümkaya, L (1997) Estimation of the section thickness and optical dissector height with a
simple calibration method, Journal of Microscopy. 187 (2). pp 104-109
Jackson, A. R. W. and Jackson, J. (2008) Forensic Science. 3rd edn. Harlow: Pearson Education Ltd.
Jackson, A. R. W., Osborne, A. O., Gwinnett, C. M. B. (2021), Microplastic pollution isolation - a forensic
science approach, Mendeley Data, v1, http://dx.doi.org/10.17632/jzppg7h8j4.1
Kanhai, L. D. K., Gårdfelt, K., Lyashevska, O., Hassellöv, M., Thompson, R. C. & O’connor, I.
(2018). Microplastics in sub-surface waters of the artic central basin. Marine Pollution Bulletin. 130. pp.
8-18.
Käppler, A., Windrich. F., Löder, M. G., Malanin, M., Fischer, D., Labrenz, M., Eichhorn, K.J. & Voit, B.
(2015). Identification of microplastics by FTIR and Raman microscopy: a novel silicon filter substrate
opens the important spectral range below 1300 cm−1 for FTIR transmission measurements. Analytical
and Bioanalytical Chemistry. 407 (22). pp. 6791-6801.
Lahens, L., Strady, E., Kieu-Le, T. C., Dris, R., Boukerma, K., Rinnert, E., Gasperi, J. & Tassin, B.
(2018). Macroplastic and microplastic contamination assessment of a tropical river (Saigon River,
Vietnam) traversed by a developing megacity. Environmental Pollution. 236. pp. 661-671.
Lepot, L., De Wael, K., Gason, F. & Gilbert, B. (2008). Application of Raman spectroscopy to forensic fibre
cases. Science & Justice. 48 (3). pp. 109-117.
Leslie, H. A., Brandsma, S. H., Van Velzen, M. J. M. & Vethaak, A. D. (2017). Microplastics en route: Field
measurements in the Dutch river delta and Amsterdam canals, wastewater treatment plants, North Sea
sediments and biota. Environmental International. 101. pp. 133-142.

Lusher, A. L., Burke, A., O’connor, I. & Officer, R. (2014). Microplastic pollution in the Northeast Atlantic
Ocean: Validated and opportunistic sampling. Marine pollution bulletin. 88 (1-2). pp. 325-333.
Lusher, A. L., Hernandez-Milan, G., O’brien, J., Berrow, S., O’connor, I. & Officer, R. (2015). Microplastic
and macroplastic ingestion by deep diving, oceanic cetacean: The True’s beaked whale
Mesoplodon mirus. Environmental Pollution. 199. pp. 185-191.
Microtrace (n.d.) https://www.microtrace.com/service/forensic-fiber-reference-collection/. (Accessed:
11th February 2020).
Miller, Z. M., Watts, A. J. R., Windslow, B. O., Galloway, T. S. & Barrows, A. P. W. (2017). Mountains to
the sea: River study of plastic and non-plastic microfibre pollution in the northeast USA. Marine
Pollution Bulletin. 124 (1). pp. 245-251.
Murphy, F., Ewins, C., Carbonnier, F. & Quinn, B. (2016). Wastewater treatment works (WwTW) as a
source of microplastics in the aquatic environment. Environment of the Total Environment. 50 (11). pp.
5800-5808.
Palenik, S. J. (2018). Microscopic examination of fibres. In: Robertson, J., Roux, C. and Wiggins, K.
(eds). Forensic Examination of Fibres. 3rd edn, pp 145-177. Boca Raton: CRC Press.
Palenik, C. S., Beckert, J. C. and Palenik, S. (2016). Microspectrophotomerty of fibers: Advances in
analysis and interpretation. National Criminal Justice Reference Service, U. S. Department of Justice.
Pena, E.A and E. H. Slate (2019). gvlma: Global Validation of Linear Models Assumptions. R package
version 1.0.0.3. https://CRAN.R-project.org/package=gvlma. (Accessed: 12th July 2019)
R Core Team (2018). R: A language and environment for statistical computing. R Foundation for
Statistical Computing, Vienna, Austria, https://www.R-project.org/ (Accessed: 12 July 2019).
R Core Team (2020). R: A language and environment for statistical computing. R Foundation for
Statistical Computing, Vienna, Austria. URL https://www.R-project.org/ (accessed 30 April 2020).

Richardson, J. T. E. (2011). Eta squared and partial eta squared as measurements of effect size in
educational research. Educational Research Review. 6. pp. 135-147.
Robertson, J. and Roux, C. (2018), From crime scene to laboratory. In: Robertson, J., Roux, C. and
Wiggins, K. (eds). Forensic Examination of Fibres. 3rd edn. pp 99-143. Boca Raton: CRC Press.
Robertson, J., Roux, C. and Wiggins, K. (eds). (2018). Forensic Examination of Fibres. 3rd edn. Boca Raton:
CRC Press.
RStudio. https://www.rstudio.com/products/rstudio/, no date, (Accessed: 12th July 2019).
Schönlau, C., Karlsson, T.M., Rotander, A., Nilsson, H., Engwall, M., van Bavel, B., Kärrman, A.
(2020) Microplastics in sea-surface waters surrounding Sweden sampled by manta trawl and in-situ
pump, Marine Pollution Bulletin, Volume 153,
Stuer, N. (2016) Easylift: A novel tape lifting system for forensic evidence, Un-published internship
report.
Uetani, K., Koga, H. & Nogi, M. (2019) Estimation of the Intrinsic Birefringence of Cellulose Using
Bacterial Cellulose Nanofiber Films. ACS Macro Letters. 8 (3). pp. 250-254.
Urbanek, S. (2019). jpeg: Read and write JPEG images. R package version 0.1-8.1. https://CRAN.R-
project.org/package=jpeg. (Accessed: 30th April 2020)
Wang, W., Ndungu, A. W., Li, Z. & Wang, J. (2017). Microplastics pollution in inland freshwaters of China:
A case study in urban surface waters of Wuhan China. Science of the Total Environment. 575. pp. 1369-
1374.
Weller, H. (2019a). countcolors: Locates and Counts Pixels Within Color Range(s) in Images. R package
version 0.9.1. https://CRAN.R-project.org/package=countcolors. (Accessed: 30th April 2020).
Weller, H. (2019b). colordistance: Distance Metrics for Image Color Similarity. R package version
1.1.0. https://CRAN.R-project.org/package=colordistance. (Accessed: 30th April 2020).

Woodall, L. C., Sanchez-Vidal, A., Canals, M., Paterson, G. L. J., Coppock, R., Sleight, V., Calafat, A.,
Rogers, A. D., Narayanaswamy, B. E. & Thompson, R. (2014). The deep sea is a major sink for
microplastic debris. Royal Society Open Science. 1 (4). pp. 1-8.
Declaration of interest
The intellectual property that underpins Easylift® is owned by Staffordshire University where this work
was completed and two of the authors of this paper (AJ and CG) are named as the inventors in the
relevant patents. One of the authors (CG) is a professor at Staffordshire University, one (AJ) is an
emeritus professor of that institution and one (AO) holds a funded PhD research position paid for by
that University. Staffordshire University is interested in licencing the production and sale of Easylift®.
Outside the support listed in the Acknowledgements, this research has received no external funding.
Acknowledgements
The authors thank Rachael Z Miller and the Rozalia Project for a Clean Ocean for the opportunity to be
onboard the American Promise as part of the 2019 Hudson River Expedition supported by National
Geographic Society, Kilroy Realty Corporation and Schmidt Marine Technology Partners. The authors
also thank Kevin Porter from Tecman Ltd for manufacturing Easylift® and his continued support with its
development. They are thankful to Jaap van der Weerd and Linda Alewijnse of the Netherlands Forensic
Institute and to Chris Hunter of SMCS Ltd. for the acquisition of the data for the spectra shown in Figures
7 and 8 of the paper, respectively, and their permission to use those data. The authors are thankful to
SPECTRICON for permission to use the images shown in Figure 9 of the paper. The authors are also
grateful to Staffordshire University for supporting this work via funding, and the provision of research
facilities and technical support.