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Analytical methodologies for monitoring micro(nano)plastics: Which are fit for purpose?
Accepted Manuscript Analytical Methodologies for Monitoring Micro(nano)plastics: Which are Fit for Purpose? Gerrit Renner, Torsten C. Schmidt, Jürgen Schram PII:
S2468-5844(17)30026-0
DOI:
10.1016/j.coesh.2017.11.001
Reference:
COESH 8
To appear in:
Current Opinion in Environmental Science & Health
Received Date: 24 August 2017 Revised Date:
2 November 2017
Accepted Date: 6 November 2017
Please cite this article as: Renner G, Schmidt TC, Schram J, Analytical Methodologies for Monitoring Micro(nano)plastics: Which are Fit for Purpose?, Current Opinion in Environmental Science & Health (2017), doi: 10.1016/j.coesh.2017.11.001. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT
Analytical Methodologies for Monitoring Micro(nano)plastics: Which are Fit for Purpose? Gerrit Rennera,b , Torsten C. Schmidtb , J¨urgen Schrama,∗ a Instrumental
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Analytical and Environmental Chemistry, Faculty of Chemistry, Niederrhein University of Applied Sciences, Frankenring 20, D-47798 Krefeld, Germany b Instrumental Analytical Chemistry and Centre for Water and Environmental Research (ZWU), University of Duisburg-Essen, Universit¨ atsstr. 5, D-45141 Essen, Germany
Abstract
Since 2004, when microplastics appears in literature, thousands of researchers focussed on this topic and analysed microplastics
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in almost every environmental compartment. However, there is still a lack of standardisation, and therefore, used methodologies varied widely. Most researchers performed controversially discussed visual examination, but it became more and more a supporting tool to reduce measuring effort. To that account, especially infrared or Raman microscopy were used for chemical characterisation. This indicates that dimensions of analysed microplastics changed to micrometre scaling. However, those microscopy technologies
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were used for particle by particle characterisation, and therefore, it is still challenging to handle the mass of data. Alternatively, thermal extraction and desorption gas chromatography is a useful integrating analysis approach, which allows a multicomponent characterisation of environmental samples without any complex sample preparation. Keywords: Microplastics, Nanoplastics, FTIR, Raman, Overview
1. Introduction
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article with a special focus on the key question: Which method can be used to analyse a certain type of microplastics and what
Since 2004, when Thompson [1] and colleagues pointed up
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marine microplastics as a new problem of high concern for our
kind of information can be obtained by its using?
global ecosystems, over 2100 researchers published approxi5
mately 600 scientific articles on this topic (web of science)1 .
2. Current State & Techniques of Microplastic Analysis
In this context, microplastics identification within a broad vari-
2.1. Microplastics 6= Microplastics: A Question of Size
ety of environmental compartments e.g. aquatic systems, sed-
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25
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iments or organisms is an important aspect [2]. However, re-
equate analytical methods, there exists not one but many dif-
searchers criticise the lack of standardised analysis techniques and protocols which lead to insufficient result comparability [3–
ferent approaches [7–11], which is not surprising as most microplastics are unique. However, there is one aspect, all re-
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5], or even worse, uncertain conclusions [4, 6]. Therefore, we
searchers can agree with: a practical identification method for
have worked through more than 170 peer reviewed research papers that were published between 2015 – 2017 and deal with
30
manding analysis will be. This means that in case of real mi-
croplastics is currently performed. However, before starting to
croparticles, spectroscopic measurements or comparable alter-
analyse microplastics, overriding objectives should be defined
natives are unavoidable [9]. Conversely, visual inspection of
in the first place, because each method provides different kinds of information. Respecting this, a representative cross-section
35
large microplastics often fits the purpose, and there exist suitable identification protocols that allow accurate analysis [7–11].
of analytical methods for microplastics is presented within this
Although accuracy should always be the most prioritized objective, analysis of microplastics is a high sample throughput task,
∗ Corresponding
author Email addresses: [email protected] (Gerrit Renner), [email protected] (J¨urgen Schram) 1 Keyword: microplastics, time range: 2004 – URL: http://www.webofknowledge.com
microplastics is always connected to their dimensions [6, 7, 9]. According to this, the smaller microplastics are, the more de-
microplastics analysis to figure out, how identification of mi15
When looking for a definition of microplastics to find ad-
and therefore, practicability becomes very important. All those 40
2017,
Preprint submitted to Current Opinion in Environmental Science & Health
aspects suggest that particle dimensions determine the identification method. November 2, 2017
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Table 1: Overview of the applied analytical methods for microplastic identification, common pretreatment steps and the corresponding environmental compartments. This table based on 170 research papers. The differences between summary and the broken down methods respect the fact that many research groups used more than one method to identify microplastics. Analytical Methods in % (n = 170) Pretreatment in % (n = 170) Source Visual µFTIR FTIR µRaman Raman Others In Manual Density (Bio)Chemical Total Separation Separation Treatment Sediments 29 11 5 5 1 3 36 16 26 6 Waters 27 8 8 5 1 1 32 17 12 10 24 10 5 4 0 2 31 15 6 16 Organisms Food 1 1 1 2 1 1 4 1 1 2 Others 4 4 0 0 0 4 9 2 2 1 In Total 79 28 18 13 2 7 100 48 39 31
2.2. Sample Pretreatment: Agony of Choice
Density Separation
In most cases, sampled microplastics are neither isolated nor purified, which denies direct analysis. Therefore, many
4%
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45
HClO4
KOH
researchers performed a two-step sample pretreatment [2, 5,
13 %
12–15], and considering that floating microplastics differ com-
NaOH
pletely from ingested ones, there exist many different concepts
12 %
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on this concern, which can be obtained from Fig. 1 and Tab. 1.
5%
in European Seas by the European Commission in 2013 [9] and
H2O
further developments since 2015 [5, 16–20] are recommendable pretreatment steps.
55
Claessens 2013, Desforges 2015
HNO3
ZnCl2
13 %
7%
remove non-plastics, e.g. biofilms, sand or wood, but also to
Nuelle 2014, Masura 2015
conserve microplastics and avoid artificial generation of sec-
Enzyms 12 %
NaI 14 % Nuelle 2014, Rocha-Santos 2015
ondary microplastics [21]. On this account, we advise against
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41 %
NaCl 53 %
(Bio)Chemical Treatment
15 %
However, the key aspect of extraction and purification is to
H2O2
Nuelle 2014, Masura 2015
SPT
In this context, the Guidance on Monitoring of Marine Litter 50
van Franeker 2011, Foekema 2013
HCl 7%
Thompson 2004, Claessens 2011, Hidalgo-Ruz 2012, Galgani 2013
stressful techniques, e.g. ultrasonic bath, whereas hydrogen
peroxide treatment is a recommendable approach to purify microplastics. Next to this, strong acids [22, 23], bases [24–26] or 60
enzyme solutions [27] were frequently used to remove contami-
Figure 1: Overview of the most common density separation (outer ring) and (bio)chemical treatment (inner ring) protocols including their reference authors. The % values are related to 67, or 53 articles, respectively, in which density separation or a (bio)chemical treatment are described.
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nants. Although most reasearchers observed no or negligible ef-
the visual observation is done by naked eye or using a dissect-
extraction [19]. 65
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fects of these pretreatments Dehaut et al. partially contradicted in their study and only recommended KOH for microplastics
ing microscope, and as recommended, this is suitable down to 500 µm [4, 9]. In addition, some research groups used scanning electron microscopy (SEM) to describe even smaller fragments
However, it has to be mentioned that there is less known on this concern, because many observations on this topic stay
80
tion of the sample surface. However, the use of SEM lowers
unpublished. For this reason, we recommend to check, if the
practicability, because it requires complex and time consuming
pretreatment step fits the purpose and does not falsify the re-
sample preparations.
sults. To that account, quality control samples are highly rec70
While one half of visual inspections is performed to narrow
ommended. 85
other half is used as the standalone method of choice for mi-
Notwithstanding the fact that purely visual examination of
croplastic identification [33, 34]. To avoid subjectivity or hu-
microplastics is discussed controversially [5–7], it is the most
man errors there exist protocols for visual examination of en-
used technique (79 % of all studies) to identify environmental microplastics [9], which also can be seen in Tab. 1. In essence,
down the choice for possible microplastics that will be analysed with common measurement instruments [5, 31, 32], the
2.3. Visual Examination: Blessing or Curse?
75
[28–30], because SEM allows a much more detailed observa-
90
vironmental microplastics [7–11]. However, it is worrying that those were mentioned in only one quarter of all corresponding
2
ACCEPTED MANUSCRIPT research papers. In summary, all protocols define criteria to de-
Hit Quality Index that describes similarity of a measured sam-
cide if a fragment can be classified as microplastics. Therefore,
ple and reference spectrum, only some researchers work on this
properties of synthetic polymers are used, e.g. shape, colour,135 topic [15, 44, 45], while the majority does not mention any val-
105
idation parameters in this context. However, identification re-
geneity [7, 9]. Considering this list, the last update was pub-
sults are accepted or declined based on HQI and in some cases
lished within the Guidance on Monitoring of Marine Litter in
a threshold was defined, e.g. HQI≥ 0.7 [39, 46], which seems
European Seas by the European Commission in 2013 [9].
to be suitable [9] especially with increasing throughput.
In conclusion, visual identification of microplastics down to 500 µm is an acceptable tool, as it is cheap, relatively ac-140 2.5. Raman: The Spectroscopic Alternative In the past two years, many researchers identified micrcurate and fast, if the analysis is done in compliance with the
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100
response to physical stress, type, lack of cell structure or homo-
protocols. However, although visual examination is a popular
coplastics with Raman microscopy (14 % usage), hence this
technique, we share the opinion of many researchers [5–7] and
seems to be an alternative to Infrared spectroscopy/microscopy.
cannot recommend it as a standalone method. In our opinion, it
K¨appler et al. [47] compared both methods and recommended
is a supporting tool for further analytical applications due to its145 Raman especially for very small fragments (≤ 20µm). Analogously to FTIR, most Raman operators used their own system limitations in accuracy and polymer type determination.
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parameters, and to that account, laser wavelengths of 532 nm 2.4. FTIR and µFTIR: The Spectroscopic Reference Method
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[47, 48] and 785 nm [20, 49, 50] were most common, while the measured Raman shift range varied widely from 200 ± 150 to
The most increasingly used method to identify microplas110
tics is FTIR microscopy (28 % usage). Therefore, it can be150 3000 ± 1000 cm−1 . In parallel to FTIR, there exist two setups: manual spot selection and imaging, but K¨appler et al. [47] figdeduced that the focus of interest changed to micrometre scaled plastics to look below the 500 µm limit. In principle, there exist
125
bility.
imaging using a focal plane array (FPA) detector that can mea-155 sure multiple spots simultaneously [2, 12, 15]. Most operators
In some research papers [32, 47, 51] laser induced fluorescence as a disturbing factor was mentioned, and the non-
used their own system parameters, but in consensus, a spectral
constant baseline that arises from this interference was cor-
resolution of 8 cm−1 and a spatial resolution between 50 – 150
rected numerically. The fluorescence itself is originated from
µm were most common.
colour pigments, additives or contaminants, e.g. algae [47].
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38 h), which is why Raman imaging is limited in its practica-
tively chosen fragments [5, 13, 14], or alternatively, chemical
After recording spectroscopic data, result evaluation fol-160 Furthermore, in comparison to FTIR, there is a much more pronounced lack of standardised methods for Raman, as there lows, which is the most critical step in microplastics analy-
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120
two setups: spectroscopic observation of randomly or subjec-
sis. There exist two common approaches: manual interpre-
are no accordance with any system parameters. Besides these
tation [35, 36] of relevant vibrational bands based on refer-
disadvantages, Raman microscopy is a suitable method for mi-
ence tables [37] and comparison of complete spectra [38–41]
croplastic identification as results are accurate and reliable [47],
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115
ured out that the latter one can be very time consuming (up to
with a reference spectra library. The latter can be home made165 and analogously to FTIR, library searching is a suitable evaluation tool3 . [12, 15] or commercially available [42]. Manual interpretation is time consuming and requires expert knowledge, and therefore, it suits only for a low throughput quantity. Neverthe-
2.6. From GC/MS to Fluorescence Microscopy: Notable Mentions
less, heavily weathered microplastics can still be identified ac-
During our study we found 12 (7 %) scientific articles that
curately [43]. 130
2
The major part of spectra evaluation is performed by li-170 describe other analytical methods to identify microplastics next visual examination, FTIR and Raman. brary searching, which is implemented in most FTIR software. One of those notable mentions is gas chromatography cou-
Although there exist many different algorithms to calculate the
pled with mass spectrometry (GC/MS) and its specifications, 2 Library searching is mentioned in 44 % of all FTIR and µFTIR microplastic investigations.
3 Library searching is mentioned in 52 % of all µRaman microplastic investigations.
3
ACCEPTED MANUSCRIPT Indicator Trends in Scienti c Quality Assurance
e.g. pyrolysis (py) or thermal extraction and desorption (TED). 175
In this context, Kwon et al. [52] analysed exposed styrene oligomer as microplastic indicators for polystyrene in waters.
62 %
In contrast to other microplastic identification methods, this approach is not a single particle concept, but an integrating
Spectra Evaluation Supported by Library Searching
method, which allows mass quantification.
38 %
Along similar lines are investigations of Dehaut et al. [19]
33 %
and Fischer et al. [53], who used py-GC/MS for identification. They analysed PE, PP, PS, PA, PVC, PMMA simulta-
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180
neously and compared pyrograms with a home made and comthat there is a risk of misinterpretation, because different poly-
10 %
13 %
mers have similar pyrolysis products. They also studied matrix
2015
2016
mercial database. In this context, Fischer et al. [53] pointed out 185
Figure 2: Since 2015, more and more spectroscopic data were evaluated by using a reference spectra library. In parallel, more and more research groups made use of quality assurance protocols to avoid sample contamination during laboratory analysis.
matic or chemical oxidation. However, one big disadvantage of py-GC/MS is the small sample mass input of 0.5 mg, which impede investigation of heterogeneous or complex samples, e.g.
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190
2017
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effects and recommend an extensive cleaning including enzy-
29 %
Anti-Contamination Protocol
soils, sediments or organisms [54].Therefore, D¨umichen et al.
is using an FPA detector that allows to measure multiple spots
[54, 55] developed a qualification and quantification method
simultaneously. However, this produces an unhandy mass of for TED-GC/MS. In contrast to py-GC/MS, TED-GC/MS can220 data (up to 1.8 million spectra) [15]. handle sample inputs up to 100 mg, and according to temperaAlternatively, a smart and automatable pre-selection of in195
ture control, no pre-separation steps are necessary. During their
teresting measurement spots decreases measuring effort, which
studies, D¨umichen et al. [54, 55] show that identification results
was worked out by Maes et al. [56] by using fluorescence
are not influenced by thermally initiated degradation, which
technology. To this account, there also exist fully automatic
200
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makes this method robust and suitable for environmental sam-225 commercial software solutions like HORIBA ParticleFinder for ples. µRaman measurements, which was used by Fr`ere et al. [57]. Maes et al. [56] took a completely different approach and
used Nile Red as fluorescence marker. They figured out that this
The software detects particles automatically for further µRaman measurements. Using this technology over 70 % of microplas-
identification method is suitable for density separated (ZnCl2 )
able. The method can be used as standalone, but there is noth-
Furthermore, Lenz et al. and Fr`ere et al. [32, 57] observed
ing wrong with applying this to enhance spot selection within
deliberately that success rate for microplastic identification de-
FTIR or Raman microscopy, because the concentration of Nile
creases significantly with particle size, which might be caused
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205
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tics within a seawater sample could be analysed in less than 3 h. microplastics and demonstrated that even in presence of algae,230 But even following this concept, in many cases, the number of seaweeds, wood or feathers, microplastics identification is relispectra is much to high for manual evaluation.
Red (10 µg L−1 ) is negligible for these systems.
235
ual contaminants.
3. Trends & Future Challenges 210
In summary, there is an urgent need for robust automated microplastic identification tools. Currently, some researchers
3.1. Automated Identification: An Approach to Handle the Big
define an assignment threshold for HQI, but even high HQI can
Data Problem 240
While microscopic applications such as µFTIR or µRaman become more and more dominant for microplastics identifica-
lead to misclassifications [15, 58]. Therefore, it is necessary to develop new library searching algorithms that are more robust and can handle the problem that weathered microplastics will
tion, it is increasingly clear that these studies have to handle a 215
by a lower signal to noise ratio or higher interferences of resid-
be compared to virgin polymer references.
huge number of samples. Considering this, there are two challenges to master: all particles have to be measured and all spectra have to be evaluated. One approach to solve the first problem 4
ACCEPTED MANUSCRIPT bio-toxicity of ingested masked nanoplastics and model studies
3.2. Quantifying Microplastics: Still Controversial 245
Every year, current estimates of the exposure level are pub-
on nanoplastics are increasing research fields. However, these
lished [59, 60], while quantification of microplastics still con-
investigations were mostly based on controlled addition of syn-
tains many unresolved issues [3, 61, 62]. Once more the lack290 thetic fluorescing nanoplastics [71], and therefore, detection of these nanoplastics was performed by transmission electron miof standardisation increases this problem, as some researchers performed a physical/chemical separation and recorded the mass
tion about chemical structure, but in those applications this was
of microplastics [10, 65], while a third group used spectroscopy
not necessary.
for identification [31]. Additionally, microplastics are distributed295 resentative conclusions. Therefore, not only the identification and quantification have to be optimized, but this is also a ques-
cal structure of the nanoplastics, they found 1.26×108 nanopar-
tion of representative sampling.
ticles/ml, which was three times higher than the control blank. 300
Therefore, it should be clear that a ”particle by particle” analysis, which can be performed with microplastics is an illusory
3.3. Airborne Fibres: Risk of Contamination
goal for nanoplastics.
One laudable trend is sensitisation for contaminants during analysis, which can be seen in Fig. 2. Woodall et al. and Nuelle
In summary, it is known that nanoplastics are generated in
et al. [33, 66] demonstrated in their studies that background
huge numbers from mesoplastics and can be ingested by or-
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260
Lambert and Wagner [72] proved the generation of secondary nanoplastics with nanoparticle tracing analysis (NTA) within a model study. Although they could not identify chemi-
heterogeneously in the environment, which almost impedes rep255
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croscopy (TEM). This concept does not provide any informa-
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250
counted visually identified microplastics [34, 63, 64], others
concentration of airborne fibres reached a significant level as305 ganisms. To this day (2017) it is not known how to detect nanoplastics in real environmental samples, as they cannot be they found similar numbers of microfibres in their laboratory
265
blanks and environmental samples. Considering this, many re-
distinguished from natural nanoparticles without having infor-
searchers comply with recommendations from Woodall et al.
mation about chemical structure. Therefore, the big challenge
[33] or Foekema et al. [67] and covered samples and instru-
will be to develop methods for real nanoplastics analysis and
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ments with foils, measured laboratory blanks or excluded fibres310 break with concepts that base on simple counting statistics. from analysis. However, the latter means that there is a blind
spot for microfibres and only a few researchers work on this topic [33, 68, 69]. 270
3.4. Nanoplastics: The Next Big Challenge?
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With the look on even smaller fragments, we have to solve315 additional problems to analyse nanoplastics. An easy one is about new sampling and pretreatment methods, but there ex-
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ist some approaches for metal-nanoparticles that can be trans275
ferred. A much more difficult problem is the analysis itself,320 because a nano scaled chemical characterisation is needed for identification. It is not sufficient enough to analyse morphological properties of nanoparticles without having an accurate concept how to distinguish synthetic nanoplastics from natural325
280
non-plastic nanoparticles. Considering this, some concepts like infrared atomic force microscopy (AFM-IR) [70] are already available, but however, nanoplastics are much more heteroge330
neous than microplastics, and therefore, the suitability of this measurement system has not been proven yet. 285
In contrast to the rather small input of nanoplastics detection in real environmental compartments, e.g. seawater or soils, 335
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ACCEPTED MANUSCRIPT Graphical Abstract
Analysis of Microplastics 2015-2017 a Review of 170 Research Papers
1) Places to look at
Deep Water Waste Water Rivers
Manual Separation Density Separation (Bio)Chemical Treatment
48 %
Sediments Beaches 36 % Soils
32 %
Fish
31 %
39 %
31 %
18 % | Include AntiContamination Protocol
Zooplankton
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Highlights
Supporting Tool
Visual Only
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Seabirds Mussels
79
◦ Dimension of analysed microplastics changed from millimetre to micrometre scaling. ◦ FTIR microscopy is the most used analytical method for microplastic identification. ◦ Visual inspection changed more and more to a supporting tool.
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◦ Anti-Contamination control is applied more frequently.
8
%
isu |V
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Surface Water
3) Methods to classify
2) How to pretreat
al
IR FT |µ R % an TI m 28 |F Ra rs % µ | e 18 % th |O 13 % 7
26 % | Reference Library
S2468-5844(17)30026-0
DOI:
10.1016/j.coesh.2017.11.001
Reference:
COESH 8
To appear in:
Current Opinion in Environmental Science & Health
Received Date: 24 August 2017 Revised Date:
2 November 2017
Accepted Date: 6 November 2017
Please cite this article as: Renner G, Schmidt TC, Schram J, Analytical Methodologies for Monitoring Micro(nano)plastics: Which are Fit for Purpose?, Current Opinion in Environmental Science & Health (2017), doi: 10.1016/j.coesh.2017.11.001. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT
Analytical Methodologies for Monitoring Micro(nano)plastics: Which are Fit for Purpose? Gerrit Rennera,b , Torsten C. Schmidtb , J¨urgen Schrama,∗ a Instrumental
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Analytical and Environmental Chemistry, Faculty of Chemistry, Niederrhein University of Applied Sciences, Frankenring 20, D-47798 Krefeld, Germany b Instrumental Analytical Chemistry and Centre for Water and Environmental Research (ZWU), University of Duisburg-Essen, Universit¨ atsstr. 5, D-45141 Essen, Germany
Abstract
Since 2004, when microplastics appears in literature, thousands of researchers focussed on this topic and analysed microplastics
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in almost every environmental compartment. However, there is still a lack of standardisation, and therefore, used methodologies varied widely. Most researchers performed controversially discussed visual examination, but it became more and more a supporting tool to reduce measuring effort. To that account, especially infrared or Raman microscopy were used for chemical characterisation. This indicates that dimensions of analysed microplastics changed to micrometre scaling. However, those microscopy technologies
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were used for particle by particle characterisation, and therefore, it is still challenging to handle the mass of data. Alternatively, thermal extraction and desorption gas chromatography is a useful integrating analysis approach, which allows a multicomponent characterisation of environmental samples without any complex sample preparation. Keywords: Microplastics, Nanoplastics, FTIR, Raman, Overview
1. Introduction
20
article with a special focus on the key question: Which method can be used to analyse a certain type of microplastics and what
Since 2004, when Thompson [1] and colleagues pointed up
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marine microplastics as a new problem of high concern for our
kind of information can be obtained by its using?
global ecosystems, over 2100 researchers published approxi5
mately 600 scientific articles on this topic (web of science)1 .
2. Current State & Techniques of Microplastic Analysis
In this context, microplastics identification within a broad vari-
2.1. Microplastics 6= Microplastics: A Question of Size
ety of environmental compartments e.g. aquatic systems, sed-
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25
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iments or organisms is an important aspect [2]. However, re-
equate analytical methods, there exists not one but many dif-
searchers criticise the lack of standardised analysis techniques and protocols which lead to insufficient result comparability [3–
ferent approaches [7–11], which is not surprising as most microplastics are unique. However, there is one aspect, all re-
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5], or even worse, uncertain conclusions [4, 6]. Therefore, we
searchers can agree with: a practical identification method for
have worked through more than 170 peer reviewed research papers that were published between 2015 – 2017 and deal with
30
manding analysis will be. This means that in case of real mi-
croplastics is currently performed. However, before starting to
croparticles, spectroscopic measurements or comparable alter-
analyse microplastics, overriding objectives should be defined
natives are unavoidable [9]. Conversely, visual inspection of
in the first place, because each method provides different kinds of information. Respecting this, a representative cross-section
35
large microplastics often fits the purpose, and there exist suitable identification protocols that allow accurate analysis [7–11].
of analytical methods for microplastics is presented within this
Although accuracy should always be the most prioritized objective, analysis of microplastics is a high sample throughput task,
∗ Corresponding
author Email addresses: [email protected] (Gerrit Renner), [email protected] (J¨urgen Schram) 1 Keyword: microplastics, time range: 2004 – URL: http://www.webofknowledge.com
microplastics is always connected to their dimensions [6, 7, 9]. According to this, the smaller microplastics are, the more de-
microplastics analysis to figure out, how identification of mi15
When looking for a definition of microplastics to find ad-
and therefore, practicability becomes very important. All those 40
2017,
Preprint submitted to Current Opinion in Environmental Science & Health
aspects suggest that particle dimensions determine the identification method. November 2, 2017
ACCEPTED MANUSCRIPT
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Table 1: Overview of the applied analytical methods for microplastic identification, common pretreatment steps and the corresponding environmental compartments. This table based on 170 research papers. The differences between summary and the broken down methods respect the fact that many research groups used more than one method to identify microplastics. Analytical Methods in % (n = 170) Pretreatment in % (n = 170) Source Visual µFTIR FTIR µRaman Raman Others In Manual Density (Bio)Chemical Total Separation Separation Treatment Sediments 29 11 5 5 1 3 36 16 26 6 Waters 27 8 8 5 1 1 32 17 12 10 24 10 5 4 0 2 31 15 6 16 Organisms Food 1 1 1 2 1 1 4 1 1 2 Others 4 4 0 0 0 4 9 2 2 1 In Total 79 28 18 13 2 7 100 48 39 31
2.2. Sample Pretreatment: Agony of Choice
Density Separation
In most cases, sampled microplastics are neither isolated nor purified, which denies direct analysis. Therefore, many
4%
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45
HClO4
KOH
researchers performed a two-step sample pretreatment [2, 5,
13 %
12–15], and considering that floating microplastics differ com-
NaOH
pletely from ingested ones, there exist many different concepts
12 %
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on this concern, which can be obtained from Fig. 1 and Tab. 1.
5%
in European Seas by the European Commission in 2013 [9] and
H2O
further developments since 2015 [5, 16–20] are recommendable pretreatment steps.
55
Claessens 2013, Desforges 2015
HNO3
ZnCl2
13 %
7%
remove non-plastics, e.g. biofilms, sand or wood, but also to
Nuelle 2014, Masura 2015
conserve microplastics and avoid artificial generation of sec-
Enzyms 12 %
NaI 14 % Nuelle 2014, Rocha-Santos 2015
ondary microplastics [21]. On this account, we advise against
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41 %
NaCl 53 %
(Bio)Chemical Treatment
15 %
However, the key aspect of extraction and purification is to
H2O2
Nuelle 2014, Masura 2015
SPT
In this context, the Guidance on Monitoring of Marine Litter 50
van Franeker 2011, Foekema 2013
HCl 7%
Thompson 2004, Claessens 2011, Hidalgo-Ruz 2012, Galgani 2013
stressful techniques, e.g. ultrasonic bath, whereas hydrogen
peroxide treatment is a recommendable approach to purify microplastics. Next to this, strong acids [22, 23], bases [24–26] or 60
enzyme solutions [27] were frequently used to remove contami-
Figure 1: Overview of the most common density separation (outer ring) and (bio)chemical treatment (inner ring) protocols including their reference authors. The % values are related to 67, or 53 articles, respectively, in which density separation or a (bio)chemical treatment are described.
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nants. Although most reasearchers observed no or negligible ef-
the visual observation is done by naked eye or using a dissect-
extraction [19]. 65
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fects of these pretreatments Dehaut et al. partially contradicted in their study and only recommended KOH for microplastics
ing microscope, and as recommended, this is suitable down to 500 µm [4, 9]. In addition, some research groups used scanning electron microscopy (SEM) to describe even smaller fragments
However, it has to be mentioned that there is less known on this concern, because many observations on this topic stay
80
tion of the sample surface. However, the use of SEM lowers
unpublished. For this reason, we recommend to check, if the
practicability, because it requires complex and time consuming
pretreatment step fits the purpose and does not falsify the re-
sample preparations.
sults. To that account, quality control samples are highly rec70
While one half of visual inspections is performed to narrow
ommended. 85
other half is used as the standalone method of choice for mi-
Notwithstanding the fact that purely visual examination of
croplastic identification [33, 34]. To avoid subjectivity or hu-
microplastics is discussed controversially [5–7], it is the most
man errors there exist protocols for visual examination of en-
used technique (79 % of all studies) to identify environmental microplastics [9], which also can be seen in Tab. 1. In essence,
down the choice for possible microplastics that will be analysed with common measurement instruments [5, 31, 32], the
2.3. Visual Examination: Blessing or Curse?
75
[28–30], because SEM allows a much more detailed observa-
90
vironmental microplastics [7–11]. However, it is worrying that those were mentioned in only one quarter of all corresponding
2
ACCEPTED MANUSCRIPT research papers. In summary, all protocols define criteria to de-
Hit Quality Index that describes similarity of a measured sam-
cide if a fragment can be classified as microplastics. Therefore,
ple and reference spectrum, only some researchers work on this
properties of synthetic polymers are used, e.g. shape, colour,135 topic [15, 44, 45], while the majority does not mention any val-
105
idation parameters in this context. However, identification re-
geneity [7, 9]. Considering this list, the last update was pub-
sults are accepted or declined based on HQI and in some cases
lished within the Guidance on Monitoring of Marine Litter in
a threshold was defined, e.g. HQI≥ 0.7 [39, 46], which seems
European Seas by the European Commission in 2013 [9].
to be suitable [9] especially with increasing throughput.
In conclusion, visual identification of microplastics down to 500 µm is an acceptable tool, as it is cheap, relatively ac-140 2.5. Raman: The Spectroscopic Alternative In the past two years, many researchers identified micrcurate and fast, if the analysis is done in compliance with the
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100
response to physical stress, type, lack of cell structure or homo-
protocols. However, although visual examination is a popular
coplastics with Raman microscopy (14 % usage), hence this
technique, we share the opinion of many researchers [5–7] and
seems to be an alternative to Infrared spectroscopy/microscopy.
cannot recommend it as a standalone method. In our opinion, it
K¨appler et al. [47] compared both methods and recommended
is a supporting tool for further analytical applications due to its145 Raman especially for very small fragments (≤ 20µm). Analogously to FTIR, most Raman operators used their own system limitations in accuracy and polymer type determination.
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95
parameters, and to that account, laser wavelengths of 532 nm 2.4. FTIR and µFTIR: The Spectroscopic Reference Method
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[47, 48] and 785 nm [20, 49, 50] were most common, while the measured Raman shift range varied widely from 200 ± 150 to
The most increasingly used method to identify microplas110
tics is FTIR microscopy (28 % usage). Therefore, it can be150 3000 ± 1000 cm−1 . In parallel to FTIR, there exist two setups: manual spot selection and imaging, but K¨appler et al. [47] figdeduced that the focus of interest changed to micrometre scaled plastics to look below the 500 µm limit. In principle, there exist
125
bility.
imaging using a focal plane array (FPA) detector that can mea-155 sure multiple spots simultaneously [2, 12, 15]. Most operators
In some research papers [32, 47, 51] laser induced fluorescence as a disturbing factor was mentioned, and the non-
used their own system parameters, but in consensus, a spectral
constant baseline that arises from this interference was cor-
resolution of 8 cm−1 and a spatial resolution between 50 – 150
rected numerically. The fluorescence itself is originated from
µm were most common.
colour pigments, additives or contaminants, e.g. algae [47].
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38 h), which is why Raman imaging is limited in its practica-
tively chosen fragments [5, 13, 14], or alternatively, chemical
After recording spectroscopic data, result evaluation fol-160 Furthermore, in comparison to FTIR, there is a much more pronounced lack of standardised methods for Raman, as there lows, which is the most critical step in microplastics analy-
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120
two setups: spectroscopic observation of randomly or subjec-
sis. There exist two common approaches: manual interpre-
are no accordance with any system parameters. Besides these
tation [35, 36] of relevant vibrational bands based on refer-
disadvantages, Raman microscopy is a suitable method for mi-
ence tables [37] and comparison of complete spectra [38–41]
croplastic identification as results are accurate and reliable [47],
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ured out that the latter one can be very time consuming (up to
with a reference spectra library. The latter can be home made165 and analogously to FTIR, library searching is a suitable evaluation tool3 . [12, 15] or commercially available [42]. Manual interpretation is time consuming and requires expert knowledge, and therefore, it suits only for a low throughput quantity. Neverthe-
2.6. From GC/MS to Fluorescence Microscopy: Notable Mentions
less, heavily weathered microplastics can still be identified ac-
During our study we found 12 (7 %) scientific articles that
curately [43]. 130
2
The major part of spectra evaluation is performed by li-170 describe other analytical methods to identify microplastics next visual examination, FTIR and Raman. brary searching, which is implemented in most FTIR software. One of those notable mentions is gas chromatography cou-
Although there exist many different algorithms to calculate the
pled with mass spectrometry (GC/MS) and its specifications, 2 Library searching is mentioned in 44 % of all FTIR and µFTIR microplastic investigations.
3 Library searching is mentioned in 52 % of all µRaman microplastic investigations.
3
ACCEPTED MANUSCRIPT Indicator Trends in Scienti c Quality Assurance
e.g. pyrolysis (py) or thermal extraction and desorption (TED). 175
In this context, Kwon et al. [52] analysed exposed styrene oligomer as microplastic indicators for polystyrene in waters.
62 %
In contrast to other microplastic identification methods, this approach is not a single particle concept, but an integrating
Spectra Evaluation Supported by Library Searching
method, which allows mass quantification.
38 %
Along similar lines are investigations of Dehaut et al. [19]
33 %
and Fischer et al. [53], who used py-GC/MS for identification. They analysed PE, PP, PS, PA, PVC, PMMA simulta-
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180
neously and compared pyrograms with a home made and comthat there is a risk of misinterpretation, because different poly-
10 %
13 %
mers have similar pyrolysis products. They also studied matrix
2015
2016
mercial database. In this context, Fischer et al. [53] pointed out 185
Figure 2: Since 2015, more and more spectroscopic data were evaluated by using a reference spectra library. In parallel, more and more research groups made use of quality assurance protocols to avoid sample contamination during laboratory analysis.
matic or chemical oxidation. However, one big disadvantage of py-GC/MS is the small sample mass input of 0.5 mg, which impede investigation of heterogeneous or complex samples, e.g.
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190
2017
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effects and recommend an extensive cleaning including enzy-
29 %
Anti-Contamination Protocol
soils, sediments or organisms [54].Therefore, D¨umichen et al.
is using an FPA detector that allows to measure multiple spots
[54, 55] developed a qualification and quantification method
simultaneously. However, this produces an unhandy mass of for TED-GC/MS. In contrast to py-GC/MS, TED-GC/MS can220 data (up to 1.8 million spectra) [15]. handle sample inputs up to 100 mg, and according to temperaAlternatively, a smart and automatable pre-selection of in195
ture control, no pre-separation steps are necessary. During their
teresting measurement spots decreases measuring effort, which
studies, D¨umichen et al. [54, 55] show that identification results
was worked out by Maes et al. [56] by using fluorescence
are not influenced by thermally initiated degradation, which
technology. To this account, there also exist fully automatic
200
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makes this method robust and suitable for environmental sam-225 commercial software solutions like HORIBA ParticleFinder for ples. µRaman measurements, which was used by Fr`ere et al. [57]. Maes et al. [56] took a completely different approach and
used Nile Red as fluorescence marker. They figured out that this
The software detects particles automatically for further µRaman measurements. Using this technology over 70 % of microplas-
identification method is suitable for density separated (ZnCl2 )
able. The method can be used as standalone, but there is noth-
Furthermore, Lenz et al. and Fr`ere et al. [32, 57] observed
ing wrong with applying this to enhance spot selection within
deliberately that success rate for microplastic identification de-
FTIR or Raman microscopy, because the concentration of Nile
creases significantly with particle size, which might be caused
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tics within a seawater sample could be analysed in less than 3 h. microplastics and demonstrated that even in presence of algae,230 But even following this concept, in many cases, the number of seaweeds, wood or feathers, microplastics identification is relispectra is much to high for manual evaluation.
Red (10 µg L−1 ) is negligible for these systems.
235
ual contaminants.
3. Trends & Future Challenges 210
In summary, there is an urgent need for robust automated microplastic identification tools. Currently, some researchers
3.1. Automated Identification: An Approach to Handle the Big
define an assignment threshold for HQI, but even high HQI can
Data Problem 240
While microscopic applications such as µFTIR or µRaman become more and more dominant for microplastics identifica-
lead to misclassifications [15, 58]. Therefore, it is necessary to develop new library searching algorithms that are more robust and can handle the problem that weathered microplastics will
tion, it is increasingly clear that these studies have to handle a 215
by a lower signal to noise ratio or higher interferences of resid-
be compared to virgin polymer references.
huge number of samples. Considering this, there are two challenges to master: all particles have to be measured and all spectra have to be evaluated. One approach to solve the first problem 4
ACCEPTED MANUSCRIPT bio-toxicity of ingested masked nanoplastics and model studies
3.2. Quantifying Microplastics: Still Controversial 245
Every year, current estimates of the exposure level are pub-
on nanoplastics are increasing research fields. However, these
lished [59, 60], while quantification of microplastics still con-
investigations were mostly based on controlled addition of syn-
tains many unresolved issues [3, 61, 62]. Once more the lack290 thetic fluorescing nanoplastics [71], and therefore, detection of these nanoplastics was performed by transmission electron miof standardisation increases this problem, as some researchers performed a physical/chemical separation and recorded the mass
tion about chemical structure, but in those applications this was
of microplastics [10, 65], while a third group used spectroscopy
not necessary.
for identification [31]. Additionally, microplastics are distributed295 resentative conclusions. Therefore, not only the identification and quantification have to be optimized, but this is also a ques-
cal structure of the nanoplastics, they found 1.26×108 nanopar-
tion of representative sampling.
ticles/ml, which was three times higher than the control blank. 300
Therefore, it should be clear that a ”particle by particle” analysis, which can be performed with microplastics is an illusory
3.3. Airborne Fibres: Risk of Contamination
goal for nanoplastics.
One laudable trend is sensitisation for contaminants during analysis, which can be seen in Fig. 2. Woodall et al. and Nuelle
In summary, it is known that nanoplastics are generated in
et al. [33, 66] demonstrated in their studies that background
huge numbers from mesoplastics and can be ingested by or-
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Lambert and Wagner [72] proved the generation of secondary nanoplastics with nanoparticle tracing analysis (NTA) within a model study. Although they could not identify chemi-
heterogeneously in the environment, which almost impedes rep255
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croscopy (TEM). This concept does not provide any informa-
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250
counted visually identified microplastics [34, 63, 64], others
concentration of airborne fibres reached a significant level as305 ganisms. To this day (2017) it is not known how to detect nanoplastics in real environmental samples, as they cannot be they found similar numbers of microfibres in their laboratory
265
blanks and environmental samples. Considering this, many re-
distinguished from natural nanoparticles without having infor-
searchers comply with recommendations from Woodall et al.
mation about chemical structure. Therefore, the big challenge
[33] or Foekema et al. [67] and covered samples and instru-
will be to develop methods for real nanoplastics analysis and
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ments with foils, measured laboratory blanks or excluded fibres310 break with concepts that base on simple counting statistics. from analysis. However, the latter means that there is a blind
spot for microfibres and only a few researchers work on this topic [33, 68, 69]. 270
3.4. Nanoplastics: The Next Big Challenge?
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With the look on even smaller fragments, we have to solve315 additional problems to analyse nanoplastics. An easy one is about new sampling and pretreatment methods, but there ex-
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ist some approaches for metal-nanoparticles that can be trans275
ferred. A much more difficult problem is the analysis itself,320 because a nano scaled chemical characterisation is needed for identification. It is not sufficient enough to analyse morphological properties of nanoparticles without having an accurate concept how to distinguish synthetic nanoplastics from natural325
280
non-plastic nanoparticles. Considering this, some concepts like infrared atomic force microscopy (AFM-IR) [70] are already available, but however, nanoplastics are much more heteroge330
neous than microplastics, and therefore, the suitability of this measurement system has not been proven yet. 285
In contrast to the rather small input of nanoplastics detection in real environmental compartments, e.g. seawater or soils, 335
5
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ACCEPTED MANUSCRIPT Graphical Abstract
Analysis of Microplastics 2015-2017 a Review of 170 Research Papers
1) Places to look at
Deep Water Waste Water Rivers
Manual Separation Density Separation (Bio)Chemical Treatment
48 %
Sediments Beaches 36 % Soils
32 %
Fish
31 %
39 %
31 %
18 % | Include AntiContamination Protocol
Zooplankton
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◦ Dimension of analysed microplastics changed from millimetre to micrometre scaling. ◦ FTIR microscopy is the most used analytical method for microplastic identification. ◦ Visual inspection changed more and more to a supporting tool.
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◦ Anti-Contamination control is applied more frequently.
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Surface Water
3) Methods to classify
2) How to pretreat
al
IR FT |µ R % an TI m 28 |F Ra rs % µ | e 18 % th |O 13 % 7
26 % | Reference Library