Microplastics in freshwaters and drinking water: Critical review and
assessment of data quality
Albert A. Koelmans
, Nur Hazimah Mohamed Nor
, Enya Hermsen
, Merel Kooi
Svenja M. Mintenig
, Jennifer De France
Aquatic Ecology and Water Quality Management Group, Wageningen University, the Netherlands
Copernicus Institute of Sustainable Development, Utrecht University, the Netherlands
KWR Watercycle Research Institute, Nieuwegein, the Netherlands
World Health Organisation (WHO), Avenue Appia 20, 1211, Geneva, Switzerland
Received 27 November 2018
Received in revised form
25 February 2019
Accepted 26 February 2019
Available online 28 February 2019
Microplastics have recently been detected in drinking water as well as in drinking water sources. This
presence has triggered discussions on possible implications for human health. However, there have been
questions regarding the quality of these occurrence studies since there are no standard sampling,
extraction and identiﬁcation methods for microplastics. Accordingly, we assessed the quality of ﬁfty
studies researching microplastics in drinking water and in its major freshwater sources. This includes an
assessment of microplastic occurrence data from river and lake water, groundwater, tap water and
bottled drinking water. Studies of occurrence in wastewater were also reviewed. We review and propose
best practices to sample, extract and detect microplastics and provide a quantitative quality assessment
of studies reporting microplastic concentrations. Further, we summarize the ﬁndings related to micro-
plastic concentrations, polymer types and particle shapes. Microplastics are frequently present in
freshwaters and drinking water, and number concentrations spanned ten orders of magnitude (1 10
) across individual samples and water types. However, only four out of 50 studies received
positive scores for all proposed quality criteria, implying there is a signiﬁcant need to improve quality
assurance of microplastic sampling and analysis in water samples. The order in globally detected poly-
mers in these studies is PE zPP >PS >PVC >PET, which probably reﬂects the global plastic demand and
a higher tendency for PVC and PET to settle as a result of their higher densities. Fragments, ﬁbres, ﬁlm,
foam and pellets were the most frequently reported shapes. We conclude that more high quality data is
needed on the occurrence of microplastics in drinking water, to better understand potential exposure
and to inform human health risk assessments.
©2019 Published by Elsevier Ltd.
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ........................411
2. Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ....................... 412
2.1. Literature search . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..................................................412
2.2. Quantitative quality assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . ..........................................412
2.3. Study characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . ..........................................412
3. Results and discussion . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ....................... 412
3.1. Quality assessment of studies reporting data on microplastics in water samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ......................412
3.1.1. Sampling methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . ..........................................412
3.1.2. Sample size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..........................................413
*Corresponding author. Aquatic Ecology and Water Quality Group, Wageningen University &Research, P.O. 47, 6700 AA, Wageningen, the Netherlands.
** Corresponding author.
E-mail addresses: firstname.lastname@example.org (A.A. Koelmans), email@example.com (J. De France).
Contents lists available at ScienceDirect
journal homepage: www.elsevier.com/locate/watres
0043-1354/©2019 Published by Elsevier Ltd.
Water Research 155 (2019) 410e422
3.1.3. Sample processing and storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................413
3.1.4. Laboratory preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................414
3.1.5. Clean air conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................414
3.1.6. Negative controls . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................414
3.1.7. Positive controls . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................414
3.1.8. Sample treatment . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................415
3.1.9. Polymer identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................415
3.1.10. Overall reliability of method aspects and studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................415
3.1.11. Implications of quality criteria and reliability of studies for human health risk assessment . . . . . . . . . . . . . . . . . . . .................417
3.2. Microplastics in freshwater . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................417
3.2.1. Global microplastic concentrations in different water types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................417
3.2.2. Microplastic shapes in global freshwaters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . .......................419
3.2.3. Polymer types reported in global studies on freshwater microplastics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................419
3.2.4. Sizes of microplastic particles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................420
4. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ................................................ 420
Declarations of interest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ................................................ 420
Conflicts of interest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . ................................................ 420
Author agreement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . ................................................ 420
Disclaimer ................................................................ ... .. .................................................. 420
Acknowledgment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................420
Supplementary data . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ................................................ 420
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................420
Microplastics are generally characterised as water-insoluble,
solid polymer particles that are 5 mm in size (Bergmann et al.,
2015). A formal deﬁnition for the lower size boundary does not
exist, but particles below 1
m are usually referred to as nano-
plastics rather than microplastic (Koelmans et al., 2015). Although
microplastics are often detected in the environment, the risks they
pose are debated and largely unknown. One key challenge in
assessing the risks of microplastics to humans and the environment
relates to the variability of the physical and chemical properties,
composition and concentration of the particles. Further, micro-
plastics in the environment are difﬁcult to identify and standard-
ized methods do not exist (Mintenig et al., 2018). The dominant
source of microplastics often is the fragmentation of larger plastics
or product wear, however the rate of fragmentation under natural
conditions is unknown (Eerkes-Medrano and Thompson, 2018).
These challenges and unknowns hamper the prospective assess-
ment of exposure and risk (Koelmans et al., 2017). In this uncertain
ﬁeld, regulatory efforts to examine microplastic safety have been
raised (SAM, 2018a,b).
The presence of microplastics has been reported for air samples,
food and drinking water (EFSA, 2016;Gasperi et al., 2018;Lusher
et al., 2017;Van Cauwenberghe and Janssen, 2014;Wright and
Kelly, 2017;Yang et al., 2015) and recently, the implications of
microplastics for human health have been reviewed (Wright and
Kelly, 2017). Although microplastic exposure via ingestion or
inhalation could occur, the human health effects are still unknown.
If inhaled or ingested, limited data from animal studies suggest that
microplastics may accumulate and cause particle toxicity by
inducing an immune response (Deng et al., 2017;Gasperi et al.,
2018). Chemical toxicity could occur due to leaching of plastic-
associated chemicals (additives as well as adsorbed toxins)
(Diepens and Koelmans, 2018;SAPEA, 2019). Such effects are likely
to be dose-dependent, however knowledge of exposure levels is
currently lacking. Furthermore, bioﬁlms growing on microplastics
may be a source of microbial pathogens (GESAMP, 2016). Hence,
although there are potential chemical, particle and microbial haz-
ards associated with microplastics, current exposure levels,
including through drinking water need to be assessed ﬁrst.
The ubiquity of microplastics of all sizes in surface water,
groundwater and wastewater (SAPEA, 2019), has raised the ques-
tion if pollution of drinking water occurs. To date, there is only a
limited number of studies that address this issue and they indeed
reported the presence of microplastics in tap water and bottled
water (Kosuth et al., 2018;Mason et al., 2018;Mintenig et al.,
2019b;Schymanski et al., 2018). Some of these studies triggered a
great deal of attention in the scientiﬁc community as well as the
media, putting the issue of human exposure to microplastics via
drinking water high on the agenda of public health agencies
worldwide. More broadly, ensuring safe drinking water is high on
the political agenda, with a dedicated target on safe and affordable
drinking water under the Sustainable Development Goals (SDG 6)
(WHO and UNICEF, 2017).
To date, about 50 studies exist that provide concentration data
for microplastics in drinking water or its freshwater sources, i.e.,
surface water and groundwater, as well as (indirectly) wastewater.
These studies provide data for speciﬁc types of water, but methods
of sampling, isolating, purifying and identifying microplastics vary
enormously among studies. A systematic review of methodologies
used and study characteristics is currently lacking. There are several
scoping reviews that emphasise the relevance of microplastics in
freshwaters (Eerkes-Medrano and Thompson, 2018;Li et al., 2018;
Wagner et al., 2014) or that speciﬁcally discuss processes or models
in freshwaters (Kooi et al., 2018). We are aware of only a limited
number of reviews that touch upon methodologies and concen-
tration data (Eerkes-Medrano and Thompson, 2018;Li et al., 2018).
Besides variation in methodologies used and concentrations
reported, existing studies are likely to vary with respect to the level
of quality assurance deployed. The quality of microplastic research
has been debated recently (Burton, 2017;Connors et al., 2017;
Koelmans et al., 2016) and has been quantitatively assessed for
studies on microplastic ingestion by biota (Hermsen et al., 2018).
However, a critical review of studies reporting concentration data
in freshwater and drinking water, which also evaluates the quality
of applied sampling methods, microplastic extraction and identi-
ﬁcation steps, is currently lacking.
For chemical risk assessments in a regulatory context, quality
criteria have been set in order to be able to evaluate the reliability of
data from toxicological studies (Kase et al., 2016;Klimisch et al.,
A.A. Koelmans et al. / Water Research 155 (2019) 410e422 411
1997;Schneider et al., 2009). Such criteria contribute to the
harmonization of the hazard and risk assessments of chemicals
across different regulatory frameworks. Recently, Hermsen et al.
proposed a weight-of-evidence scoring method for studies of
microplastic ingestion by marine biota (Hermsen et al., 2018). This
method deﬁned minimum quality criteria for various aspects of the
analytical procedure, such as sampling, sample treatment, use of
controls and polymer identiﬁcation. It assigns a score for each
aspect and provides a total reliability score for data reported in a
study. Such a method can also be developed for the analysis of
microplastics in freshwater samples, and can be applied to quantify
the relative reliability of reported concentration data.
The aim of the present paper is to critically review the available
literature on microplastics in drinking water and its freshwater
sources, from a quality assurance perspective and by using a
quantitative approach. Wastewater studies were also assessed as
these are discharged into the environment. Further aims are to
review data on concentration, polymer type, shape and size dis-
tribution data across studies. Guidance is provided to improve the
quality of future occurrence studies.
Our paper is organised as follows. We ﬁrst present the key areas
that should be assessed to determine the reliability of studies.
These areas are presented in separate sections and are: sampling
method, sample size, sample processing and storage, laboratory
preparation and clean air conditions, negative controls, positive
controls, sample treatment and polymer identiﬁcation. For each of
these areas we discuss quality assurance aspects, considerations for
scoring, and present the assessment scores for each of these
criteria. Subsequently, the combined overall reliability scores are
discussed, followed by a discussion on implications for human
health risk assessments. In the section thereafter we discuss the
outcomes of the reviewed studies. An overview of the concentra-
tions, shapes and polymer types measured is provided and trends
are discussed with respect to sample type, location or system
characteristics. Finally, we provide recommendations to improve
the analysis of microplastics in water samples and summarize the
2.1. Literature search
Fifty-ﬁve records from ﬁfty studies reporting microplastic con-
centrations in drinking water (2 tap, 3 bottled water) or its fresh-
water sources (1 groundwater, 30 surface water, 18 wastewater)
were reviewed. Some studies reported data on microplastics in
more than one water type. Most papers were retrieved from the
Scopus database. Search strings used were microplastic AND (bottle
OR surface OR tap OR wastewater OR groundwater). Three studies
were from the grey i.e. not peer-reviewed literature and were found
via Google searches, using the same or similar key word combi-
nations. Searches were performed until August 2018. Only those
studies that reported original concentration data were reviewed.
2.2. Quantitative quality assessment
The reliability of data in studies was evaluated based on criteria
originally developed for microplastic in biota samples by Hermsen
et al. (2018), and surface water samples by Mintenig et al. (2019a,in
prep.). The present approach further reﬁnes the method to different
categories of water samples, including tap or bottled drinking
water, surface water, groundwater and wastewater. The method
uses nine crucial criteria, which are detailed below. Criteria relate to
those that are common in analytical chemistry, such as reproduc-
ibility of described methods, precision, accuracy and sensitivity,
which together determine the robustness of an applied method.
Reproducibility does not imply that another researcher would
obtain the same result, which is due to the variability in conditions
inherent to nature. Reproducibility in the context of analytical
chemistry refers to minimizing the contribution of random or
systematic error to the total observed variability. For each criterion
a value of 2 (reliable), 1 (reliable to a limited extent) or 0 (unreli-
able) is assigned. A ‘Total Accumulated Score’(TAS) is calculated by
adding scores for individual criteria (maximum 18 points) (Tables 1,
S2, S3). For data to be considered sufﬁciently reliable, a study
should preferably have no ‘zero’values for any of the individual
scores (Hermsen et al., 2018).
2.3. Study characteristics
For each study the following characteristics were summarized in
tabular form (Table S1): Reference, Country (area), Source (water
type), Treatment applied (for wastewater treatment plants
(WWTP) or drinking water treatment plants (DWTP), bottled and
tap water), Sampling date, Size/shape (of microplastics detected),
Polymer types (of microplastics detected), Chemicals (analysed on
microplastic), Value (of microplastics detected in water sample),
Quality assurance applied (detection limit, positive controls,
negative controls), Sampling method, Analysis method, Comments.
Raw concentration data were pooled per water type: WWTP
inﬂuent, WWTP efﬂuent, lake, river, canal, groundwater, untreated
and treated tap water, and bottled water, and analysed for means,
ranges and signiﬁcance of differences among the water types. As
data were not normally distributed, the differences were assessed
with the Mann-Whitney-Wilcoxon test with Bonferroni correction.
3. Results and discussion
3.1. Quality assessment of studies reporting data on microplastics in
In this section, methodological aspects are reviewed in sub-
sections and the ﬁnal total quality scores are presented and dis-
cussed. Following Hermsen et al. (2018), for each aspect, scoring
criteria are provided and each criterion is explained and justiﬁed
(Table S2). Such a score based, quantitative evaluation does not
result in an absolute judgment but is an indicator of the reliability
of these studies for monitoring purposes and to inform risk as-
sessments of microplastics in the drinking water supply chain. The
quality criteria provided here are considered adequate for the
present assessment, yet may develop over time with increased
experience in sampling and analysing microplastics and better
understanding of global concentrations. Here we review the gen-
eral trends; for details on speciﬁc studies the reader is referred to
Tables S1 and S3.
3.1.1. Sampling methods
Sampling methods were reviewed to understand the variety of
approaches utilized, to assess whether sampling was described in
sufﬁcient detail, and to be able to deﬁne quality assessment criteria
for sampling (Tables S1 and S2). Surface water is sampled by
pumping, trawling or ﬁlling bottles or buckets, followed by sieving
to isolate particles of the desired size range (Table S1)(Li et al.,
2018). For wastewater, samples are either grabbed with bottles,
pumped directly or collected with automatic composite samplers,
then sieved, whereas tap and bottled water are directly sieved.
Residues in nets or sieves are typically ﬂushed into glass or metal
jars or bottles. To obtain a maximum score of 2, the date, location
and materials used should be reported. Speciﬁc further criteria
were deﬁned for wastewater, surface water, untreated and treated
A.A. Koelmans et al. / Water Research 155 (2019) 410e422412
tap water and bottled water. For wastewater, the applied treatment
type should be mentioned as this can impact the microplastic
concentrations and should be considered when assessing retention
or removal efﬁciencies of individual technologies. For the same
reason, this should be done when taking samples on DWTPs. For
surface water, the depth of sampling should be reported, as this
may affect concentration (Kooi et al., 2018). For tap water, when the
aim is to assess concentration in general, running the tap before
sampling is recommended (e.g. 1 min) in order to avoid incidental
contamination from air (Wesch et al., 2017), unless it is speciﬁcally
mentioned that the aim is to measure the ﬁrst portion of the water,
e.g., the ﬁrst glass. Furthermore, ﬂowrate and source of tap water
(e.g., storage tank, groundwater, surface water) should be reported,
as this may be relevant for data interpretation. For the same reason,
for bottled drinking water, the source, batch production lot and
bottled water type (sparkling vs still water) should be speciﬁed. To
maximize particle recovery from the bottle, the sample should be
shaken before ﬁltration and the emptied bottle should be ﬂushed
three times with ﬁltered water. A score of 1 was assigned if a study
provided a subset of the required characteristics (e.g. date, loca-
tion), but is still fairly reproducible. About half of the studies score 2
on this criterion whereas only three studies score 0.
3.1.2. Sample size
Different factors were considered when recommending an op-
timum water volume to be sampled. For microplastics, the limit of
detection can be seen as the methods’capability of reliably
detecting at least one particle with statistical rigor. A sample vol-
ume that is too low reduces the chance of ﬁnding particles, reduces
the power of a study and increases the margin of error. This means
that detection limits beneﬁt from large sample volumes. Similar
approaches i.e. sufﬁcient sample size are used when analysing
chemicals in environmental matrices (Einax et al., 2004). However,
for samples with particles, samples should be small enough to
prevent clogging of ﬁlters or sieves. This means that recommen-
dations for sample sizes will differ for different water types.
Because the actual concentration cannot be predicted, occurrence
of non-detects or ﬁlter clogging can never be fully prevented.
Detection limits also depend on the particle size range aimed for
in a study. Various studies have shown that smaller particles are
more abundant (Cabernard et al., 2018), implying that smaller
sample volumes are required when exclusively examining small
microplastics that are analytically challenging to detect (e.g.,
m). However, if such a study would also aim to detect
larger microplastics accurately, a large volume would still be
required. Establishing sample volume recommendations for studies
primarily aiming for larger (roughly >300
m) microplastics, should
consider both expected microplastic concentrations fora given water
type and practical considerations. Most studies reviewed belong to
this category that aimedto detect also larger microplastics. In surface
m microplastic concentrations span a wide range of
concentrations; roughly 1 10
to 10 particles per litre (Fig. 1).
Because of the low concentrations and ease of obtaining large vol-
umes from surface waters, we set 50 0 L as a minimum sample vol-
ume for surface water. However, given the often very low particle
number concentrations in some lakes and rivers, a volume greater
than 500 L is recommended for remote locations.
For tap water (range 1 10
to 100 particles per litre), a greater
sample volume is proposed compared to surface water. We advise a
minimum volume of 1000 L, because of the concentrations that can
be very low (Mintenig et al., 2019b), uncertainties with the repre-
sentativeness of this range given the low number of studies iden-
tiﬁed, and ease of sample collection. For bottled water, there were
also a limited number of studies available. Yet they all demonstrate
presence of at least several particles per litre, such that even a
minimum of 1 L would be defensible in case a 1 L bottle would be
the study unit and only very small particles (<10 0
m) would be
targeted. However, the study unit in such studies is often the brand
or production lot, and also larger particles are targeted, in which
case we recommend to sample >10 L for a more representative
result. As bottled water usually is provided in volumes smaller than
10 L, this would imply the need to either analyse multiple bottles or
to treat the total volume of multiple bottles as one sample. For
WWTP inﬂuents where concentrations of particles are expected to
be higher (Fig. 1), a sample volume of 1 L is considered sufﬁcient.
For WWTP efﬂuent, a sample volume greater than 500 L is rec-
ommended, or a reported clogging of the sieve e.g. (Carr et al., 2016;
Mintenig et al., 2017;Vollertsen and Hansen, 2017;Ziajahromi
et al., 2017). These volumes mentioned would lead to roughly 5
to 500 particles detected, which is considered sufﬁciently repre-
sentative if the detection limit would be 1 particle as mentioned
above. Use of these volumes would receive a maximum score of 2.
However in some cases lower volumes have been used with good
reason and may still yield fair results. In these cases a score of 1 is
assigned (Table S2). Studies that explicitly aim for only smaller
particles can use smaller volumes as long as detection limits are
met, and still receive the maximum score.
3.1.3. Sample processing and storage
For the transfer of a primary sample (e.g. material in a net or
sieve) to a storage bottle, or for preservation or storage of samples
before reaching the laboratory, certain criteria need to be met.
Some studies rinse jars, bottles or other materials with targeted
water e.g. (Kosuth et al., 2018;Talvitie et al., 2015). However, par-
ticles from that rinsing water could easily stick to surfaces and
remain, which thus would lead to contamination of the actual
sample. Ideally, sample containers should be rinsed in the labora-
tory with ﬁltered water before bringing them to the ﬁeld. In gen-
eral, samples should be stored shortly after sampling and further
handling avoided before arriving in the laboratory. When sampling,
use of plastic materials should be avoided as much as possible to
again minimize contamination. Many studies use a ﬁxative like
ethanol, formalin or methyl aldehyde (Anderson et al., 2017;
Baldwin et al., 2016;Eriksen et al., 2013;Fischer et al., 2016;Mason
et al., 2016a;Su et al., 2016;Wang et al., 2018;Xiong et al., 2018;
Zhang et al. 2015,2017). However, the effects of the ﬁxative on
different types of plastic should be evaluated before application, or
studies should report evidence from the literature (Hermsen et al.,
2018). Ethanol and formalin for instance, have been shown not to
affect polymer characteristics (Courtene-Jones et al., 2017). Some of
the studies reviewed here used volunteers for sampling and sample
processing (Christiansen, 2018;Kosuth et al., 2018). Citizen science
(CS) approaches have been used in environmental monitoring and
are increasingly being used in research on plastic debris (Liboiron
et al., 2016;Syberg et al., 2018). It has been argued that this may
improve risk perception within society and therefore improve the
foundation for timely and efﬁcient societal measures (Syberg et al.,
2018). There is also an economic incentive to collect data with
volunteers rather than by paid professionals, and some monitoring
research would even be impracticable if data were not collected by
volunteers (Brett, 2017). However, concerns with respect to the
quality of CS have been raised, and validation studies have shown
that the reliability of CS based data is highly uncertain (Brett, 2017).
Other than for macroplastics, quality assurance for sampling and
sample processing of microplastics is technically demanding and
the error rate can be expected to be higher for volunteers than for
professionals. Since no CS validation studies for microplastics
sampling and analysis exist to date, it is not clear to what extent the
quality of data is affected by having some of the crucial steps per-
formed by non-professionals. Therefore, as scientiﬁc quality
A.A. Koelmans et al. / Water Research 155 (2019) 410e422 413
assurance is the primary perspective of this paper, use of volunteers
for major parts of the sampling work was considered less reliable,
leading to a score of 1 in case of validation of the adequacy of the
protocols, and 0 in all other cases for this criterion.
3.1.4. Laboratory preparation
Contamination of samples due to airborne polymer particles
and ﬁbres has been described as a major problem in microplastic
analysis (Hermsen et al. 2017,2018;Torre et al., 2016;
Vandermeersch et al., 2015;Wesch et al., 2016). Therefore, to avoid
contamination and prior to actual sample preparation and analysis,
certain measures need to be taken. These include avoiding syn-
thetic components in clothing, wearing of cotton lab coats, and pre-
rinsing and cleaning of all materials used as well as laboratory
(bench, laminar ﬂow cabinet) surfaces. If precautions were not fully
reported but sufﬁcient blanks (i.e., three blanks, see section
‘negative controls’below) were included to keep track of back-
ground contamination, then a score of 1 was assigned (Table S2).
3.1.5. Clean air conditions
To avoid contamination with airborne microplastic particles or
ﬁbres, sample handling should be performed in a laminar ﬂow
cabinet or in a clean air laboratory to receive the maximum score
(Hermsen et al., 2018). Recent studies are increasingly using such
conditions (Mason et al., 2018;O
mann et al., 2018;Schymanski
et al., 2018;Wang et al., 2018;Zhang et al., 2017). In case clean
air conditions were not used but covering of samples and sufﬁcient
blanks were reported, a score of 1 was assigned (Cable et al., 2017;
Dris et al. 2015,2018b;Miller et al., 2017;Mintenig et al., 2019b;
Pivokonsky et al., 2018).
3.1.6. Negative controls
To verify and correct for contamination or to demonstrate
absence of contamination, replicated (n 3) procedural blanks
need to be analysed. All reviewed studies reported particles counts;
if the variability of contamination was quantiﬁed, and if it was
clearly indicated that actual sample results were corrected for
blank values, a score of 2 was assigned. Some precautions are less
reliable but still provide some useful information on the level of
contamination, like the ﬁltration of air, or the sole examination of
petri dishes/soaked papers placed next to the samples (Cable et al.,
2017;Dris et al. 2015,2018b;Estahbanati and Fahrenfeld, 2016;
Hendrickson et al., 2018;Lares et al., 2018;Mani et al., 2015;
McCormick et al., 2016;Rodrigues et al., 2018;Simon et al., 2018;
Ziajahromi et al., 2017). If these precautions were taken, a score of 1
3.1.7. Positive controls
Losses of particles may occur during various steps of sampling,
sample preparation and analysis and it is recommended to quantify
losses using positive controls. Estahbanati and Fahrenfeld (2016)
assessed particle losses during sampling with nets, by adding
plastic particles in distilled water. Subsequent sample handling in
the laboratory often includes complex steps to remove organic
matter from samples (see ‘sample treatment’below), particularly
from WWTP inﬂuent or efﬂuent or surface waters. To verify a suf-
ﬁciently high recovery of particles during ﬁltration, digestion,
transfer and analytical identiﬁcation steps, representative repli-
cated positive controls (n 3) should be performed (Hermsen et al.,
2018). If recoveries are low yet reproducible, the reported counts
should be corrected for this incomplete recovery. Positive controls
should be conducted for the targeted microplastics, covering
different size classes and polymer types. Microplastic sizes span a
wide range and it cannot be assumed that recoveries are constant
across the range of sizes and polymer types. In practice, it is
important to at least use small enough microplastics as controls, as
these are more difﬁcult to recover. In some cases, larger micro-
plastics still require separate controls, especially when different
Fig. 1. Box and whisker plot showing median and variation in microplastic number concentrations in individual samples taken from different water types. Data relate to individual
samples unless only means were reported, in which case the mean value was taken into account n times, with n being the number of samples which the mean was based on.
References included: (Estahbanati and Fahrenfeld, 2016;Faure et al., 2015;Fischer et al., 2016;Hoellein et al., 2017;Kosuth et al., 2018;Leslie et al., 2017;Magnusson and Nor
2014;Mason et al. 2016a,2018;McCormick et al. 2014,2016;Michielssen et al., 2016;Mintenig et al., 2019b;O
mann et al., 2018;Pivokonsky et al., 2018;Rodrigues et al., 2018;
Schymanski et al., 2018;Simon et al., 2018;Talvitie et al. 2015,2017a,2017b;Vollertsen and Hansen, 2017;Wang et al. 2017,2018;Ziajahromi et al., 2017), with n ¼27. For statistical
signiﬁcances of differences among water types, see Table S4.
A.A. Koelmans et al. / Water Research 155 (2019) 410e422414
methods are applied. For instance, the method used by Mason et al.
(2018) for particles smaller than 100
m was different from that for
particles larger than 100
m, whereas positive controls were only
performed for the smaller particles. Only three studies provided full
data on positive controls (Simon et al., 2018;Vollertsen and
Hansen, 2017;Wang et al., 2018) and received maximum scores,
indicating that it is not yet a very common practice. Other studies
conducted positive controls but with no or insufﬁcient replicates
(Di and Wang, 2018;Dyachenko et al., 2017;Hendrickson et al.,
2018), or only for one step in the analysis (Rodrigues et al., 2018),
or for part of the targeted size range (Mason et al., 2018) and
received a score of 1.
3.1.8. Sample treatment
To assure the quality of visual inspection and subsequent poly-
mer identiﬁcation, which is especially critical for <300
and to enable the usage of more advanced identiﬁcation techniques
(see section ‘polymer identiﬁcation’), a sample digestion step
should be performed for surface and WWTP water samples in order
to score 2 points. Tap and bottled water do not require a digestion
step and thus were always assigned 2 points on this criterion.
Digestion should be done under conditions that do not affect the
microplastics weights, counts or shapes. In the context of biota
analysis, use of potassium hydroxide (KOH) or enzymes has been
demonstrated to be acceptable (Catarino et al., 2016;Cole et al.,
2014;Kühn et al., 2017;Munno et al., 2018). The reviewed studies
here commonly used hydrogen peroxide (H
) which is known to
affect some polymers (Hurley et al., 2018). However its effects have
been demonstrated to be minimal within an exposure of 48 h
oder et al., 2017) and was therefore deemed acceptable. Several
studies kept the temperature around 35e45
C, e.g. by using a
cooling or ice bath (Simon et al., 2018), however sometimes higher
temperatures up to 75
C(Anderson et al., 2017;Baldwin et al.,
2016;Estahbanati and Fahrenfeld, 2016;Hendrickson et al., 2018;
Hoellein et al., 2017;Pivokonsky et al., 2018)oreven80
used in some of the digestion steps (Vermaire et al., 2017), or even
C for drying (Estahbanati and Fahrenfeld, 2016;Hendrickson
et al., 2018;Ziajahromi et al., 2017). Effects of temperature in
combination with various digestion chemicals were studied by
Munno et al. (2018). Based on comparison of data on polymer mass
losses during heating and digestion, the authors concluded it was
best to stay below 60
C. We set 50
C as the safe upper limit, and as
a criterion to assign a maximum score as a precautionary measure
and since many of the reviewed studies were below 50
tion without such considerations of mass losses was assigned a
score of 1. A score of 1 was also assigned for surface water when it
was reported to be very clear and clean even without digestion
applied. Furthermore, studies that did not apply digestion but
explicitly were aiming for the detection of 300
m particles only,
were assigned a score of 1 (Hermsen et al., 2018).
3.1.9. Polymer identiﬁcation
To assure reliable assessment of plastic particles, the polymer
identity needs to be conﬁrmed, preferably by using (micro) FTIR or
Raman spectroscopy, pyrolysis-GCMS or TGA-GCMS techniques
(Hermsen et al., 2018;L€
oder and Gerdts, 2015;Mintenig et al.,
2018). Although subsampling should be avoided, these techniques
are so laborious that representative sub-sampling is often required.
Best practice for subsampling and subsequent polymer identiﬁca-
tion will differ for different microplastic size classes and technol-
ogies applied (Mintenig et al., 2018). The manual sorting and
subsequent identiﬁcation of microplastics has a bias compared to
the identiﬁcation of particles enriched on ﬁlters with FTIR or
Raman microscopy (i.e., avoid missing transparent or small parti-
cles), and is therefore discouraged when analysing particles
m. For manually sorted particles, following Hermsen et al.
(2018), we argue that analysis of all particles is feasible and
therefore recommended if the numbers of pre-sorted particles per
study are <100. For particle numbers >100, 50% should be identi-
ﬁed, with a minimum of 100 particles. If polymer identities are
reported on a per sample basis, we also advise to analyse all parti-
cles found, however with a minimum of 50. This minimum is
considered reasonable to represent the variety of particle shapes
and polymer types in environmental samples. Anyway, for such
hand-picked representative subsets, studies generally still should
describe how representativeness was assured. For smaller micro-
pastics and when applying FTIR or Raman microscopy, the repre-
sentativeness of subsampling (the area of a ﬁlter that was
measured) is relatively easy to assess. Particularly when coupling a
focal plane array detector to the microscope, many more particles
(especially the small and transparent particles) can be assessed in
one analysis. Although measurement times can be long, at least 25%
of the ﬁlter needs to be analysed (Mintenig et al., 2017;Redondo-
Hasselerharm et al., 2018). If these criteria for number of particles
and/or percentage of the ﬁlter are met, a score of 2 is assigned. If
polymers were identiﬁed for a too low number of particles or on a
smaller part of the ﬁlter, a score of 1 was assigned. Also, if SEM-EDS
or - EDX was applied to distinguish polymers from non-polymeric
materials (Anderson et al., 2017;Cable et al., 2017;Mason et al.,
2016b;Su et al., 2016), a score of 1 was assigned
3.1.10. Overall reliability of method aspects and studies
For each study, we assessed against all quality criteria and
calculated a total accumulated score (TAS) (Table S3). Whereas the
maximum achievable TAS score is 18, average (min emax) TAS
scores were 13.7 (13e14) for bottled water, 11.5 (8e15) for treated
tap water, 12.5 (11e14) for DWTP water, 7.9 (4e15) for surface
water, and 7.3 (3e13) for waste water studies, respectively (Table 1).
This ranking in average scores for the different water types prob-
ably reﬂects the relative ease of analysing these different water
types. For instance, bottled and tap water require no digestion,
which means that 2 points were always assigned to the sample
digestion criteria. It should be noted though that the number of
studies examining DWTP and treated tap water (each n ¼2), and
bottled water studies (n ¼3) was very low, rendering the averages
to be less rigorous. On average, studies were assigned roughly half
(8.41/18) of the maximum score for data quality, a result which is
very similar to the average score assigned to studies reporting data
on ingestion of microplastic by biota (Hermsen et al., 2018).
Only four studies received non-zero scores for all criteria. These
were the study on surface water by (Wang et al. 2018)(TAS¼15),
the study on bottled water by Mason et al. (2018) (TAS ¼14), and
two studies on wastewater by Ziajahromi et al. (2017) (TAS ¼12)
and Hendrickson et al. (2018) (TAS ¼11). For the ranking of such
non-zero studies, a multiplied score X can be calculated (Hermsen
et al., 2018), followed by a
Log X transformation in order to obtain
a linear scale for a maximum score of 9. This would lead to a score of
6 for the data provided by Wang et al. (2018), a score of 5 for the
data provided by Mason et al. (2018), a score of 3 by Ziajahromi
et al. (2017), and a score of 2 for the data provided by
Hendrickson et al. (2018). These four studies were published in the
years 2017 or 2018, which may reﬂect recent progress in the quality
of applied methods to analyse microplastics in environmental
samples. With only four studies having all non-zero scores, it can be
concluded that the majority of the reviewed studies (46 studies or
92%) cannot be considered fully complete or reliable on at least one
crucial aspect of quality assurance. This does not mean that studies
may not be useable or important as a more speciﬁc consideration of
scores and study outcomes in hindsight, can still make a study very
well ﬁt for certain research questions.
A.A. Koelmans et al. / Water Research 155 (2019) 410e422 415
Overview of individual and accumulated scores
of papers reporting microplastic concentrations in surface water and drinking water.
Author Type Sampling
Total Accumulated Score
(TAS, max ¼18)
Mason et al. (2018) Bottle 122 1 2 212114
Schymanski et al.
Bottle 112 2 2 202214
mann et al. (2018) Bottle 112 2 2 202113
Mintenig et al.
Tap 222 2 1 202215
Kosuth et al. (2018) Tap 000 2 2 20208
Mintenig et al.
DWTP 212 2 1 202214
Pivokonsky et al.
DWTP 112 1 1 201211
Mintenig et al.
Ground 212 2 1 202214
Wang et al. (2018) Surface 211 22 222115
Hendrickson et al.
Surface 212 1 1 111111
Di and Wang (2018) Surface 202 20 012110
Mani et al. (2015) Surface 221 1 1 101110
Wang et al. (2017) Surface 101 21 202110
Baldwin et al. (2016) Surface 211 1 1 20109
Cable et al. (2017) Surface 211 1 1 10119
Dris et al. (2018a) Surface 220 1 1 10119
Lares et al. (2018) Surface 101 2 1 20119
Rodrigues et al.
Surface 221 1 0 10119
Su et al. (2016) Surface 211 1 1 10119
Zhang et al. (2017) Surface 211 1 2 00029
Dris et al. (2015) Surface 212 1 1 10008
Surface 221 0 0 11108
Hoellein et al. (2017) Surface 212 0 0 10118
Mason et al. (2016b) Surface 211 0 0 20118
Sighicelli et al.
Surface 221 0 0 00218
Vermaire et al.
Surface 212 0 0 20108
Xiong et al. (2018) Surface 210 11 10118
Anderson et al.
Surface 211 0 0 10117
Faure et al. (2015) Surface 121 1 0 00117
McCormick et al.
Surface 111 0 0 20117
Miller et al. (2017) Surface 101 1 1 20017
McCormick et al.
Surface 111 0 0 20106
Fischer et al. (2016) Surface 211 0 0 00105
Free et al. (2014) Surface 211 00 00105
Lahens et al. (2018) Surface 111 0 0 00115
Leslie et al. (2017) Surface 102 0 1 10005
Eriksen et al. (2013) Surface 211 0 0 00004
Zhang et al. (2015) Surface 210 0 0 00014
Mintenig et al.
WWTP 222 1 1 201213
Ziajahromi et al.
WWTP 221 1 1 111212
Simon et al. (2018) WWTP 110 11 222111
Lares et al. (2018) WWTP 201 2 1 201110
Talvitie et al. (2017a) WWTP 211 1 1 200210
Murphy et al. (2016) WWTP 112 2 1 10019
Mason et al. (2016a) WWTP 221 0 0 20108
WWTP 021 0 0 02117
Carr et al. (2016) WWTP 221 00 00016
WWTP 221 0 0 00016
Michielssen et al.
WWTP 212 0 0 10006
Talvitie et al. (2017b) WWTP 201 0 0 20016
Vermaire et al.
WWTP 102 0 0 20106
Dyachenko et al.
WWTP 101 0 0 01115
Leslie et al. (2017) WWTP 102 0 1 10005
A.A. Koelmans et al. / Water Research 155 (2019) 410e422416
Besides insights in methodological differences among individual
studies, the scores allow for a cross comparison of reliability dif-
ferences per criterion (Table 1)(Hermsen et al., 2018). Average
scores per criterion were all lower than 2, which means there is
room for improvement of quality assurance in this ﬁeld of research.
The average scores per criterion across 55 records were lower than
1 for the criteria sample treatment (0.93), polymer identiﬁcation
(0.89), laboratory preparation (0.77), clean air conditions (0.64), and
positive controls (0.21). Therefore, signiﬁcant improvements are
needed especially for these ﬁve out of nine quality aspects. Our
analysis further illustrates that besides actual quality assurance,
also full reportage of method details is important, to assure trace-
ability and reproducibility of data. Reporting is a quality aspect in
itself and some studies may have scored higher had they been re-
ported better. In this respect we recommend to also include
detection limits in terms of number and mass concentrations, but
also in terms of minimum and maximum detectable particles sizes
inherent to the applied methodology.
3.1.11. Implications of quality criteria and reliability of studies for
human health risk assessment
Human health risks depend on exposure and it is well known
that drinking water is an uptake pathway for microplastics.
Consequently, quality in the analysis of microplastics in drinking
water and its sources is very relevant to accurately assess risks to
In this respect it should be mentioned that the proposed criteria
are related to concentrations in the water, which however may not
fully correlate with exposure. For instance, we recommended
running the tap before sampling to avoid contamination of the ﬁrst
portion of water, to assure reproducibility of results and further,
because many consumers would do this anyway. However, others
may not do this and addressing this variability may be relevant for
exposure assessment. Exposure to microplastics may also depend
on the level of shaking of a bottle before drinking, whereas our
criteria recommend shaking in order to maximize the chance that
all particles are measured, and to assure reproducibility of the
analysis. Exposure in drinking water can additionally be inﬂuenced
by direct contamination of drinking water through contact with air,
but to better understand contamination that is coming directly
from the water supply and to support comparability and reprodu-
ciblity, we recommend procedures to prevent airborne contami-
nation. Finally, exposure to microplastics would also include uptake
via inhalation or food (Wright and Kelly, 2017), which is not
covered in this paper that only addresses drinking water and its
The fact that high quality data are limited also has implications
for human health risk assessment, which considers both exposure
as well as health effects. Only four out of 50 studies (which were
published in 2017 and 2018) were of such a level of reliability (i.e.
having no zero scores) that they could be used conﬁdently for an
exposure assessment. Importantly, of these four studies, the recent
study on microplastic particles in bottled drinking water (Mason
et al., 2018) would be highly relevant for human health risk
assessment, based on the criteria used here, although the study
only had maximum scores in 5 out of 9 criteria. Therefore, this
uncertainty in the overall exposure data precludes the ability to
conduct a robust risk assessment, whether related to particle
toxicity, chemical toxicity or microbial toxicity. We therefore
conclude that more high quality data is needed on the occurrence
of microplastics in drinking water to more conﬁdently assess po-
tential exposure, as a critical piece for understanding the potential
human health risks.
3.2. Microplastics in freshwater
3.2.1. Global microplastic concentrations in different water types
We reviewed the available literature on microplastics in drink-
ing water, fresh water and wastewater. Monitoring has been con-
ducted in multiple locations in Asia, Australia, Europe and North
America. A selection of studies reporting particle number concen-
trations were used for a further analysis (Figs. 1 and 4), if they re-
ported means and/or raw data on a volume basis. These
microplastic concentrations, reported as number of particles,
spanned ten orders of magnitude (1 10
) across all
individual samples and water types, also when excluding waste-
waters (Fig. 1). The number of microplastic particles in samples per
water type was statistically different (p <0.05) for all pairwise
comparisons of water types, except for the comparisons between
ground water and all other water types, WWTP efﬂuent versus
(untreated) DWTP and tap water, and WWTP inﬂuent versus (un-
treated) DWTP water (Fig. 1,Table S4). As these concentration data
relate to numbers, they do not distinguish between particle size,
shape or material type; differences that will be discussed in the
sections below. Studies often do not mention a lower nor an upper
size limit, or only mention the targeted size class. The data include
particles reported as microplastics, that is, we did not take out
suspect non-polymer particles as identiﬁed either by authors
themselves or based on our quality assessment discussed above.
The range for 50% of the data per water type (the boxes in Fig. 1)is
1e2 orders of magnitude, and quite similar for inﬂuent, efﬂuent,
lake, river and bottled water data. For canal and tap water only a
few studies were available, which may have caused the variation to
be much smaller. For bottled water, the numberof studies was also
low (Mason et al., 2018;O
mann et al., 2018;Schymanski et al.,
2018), however there were many samples (bottled water brands)
for this water type available in these studies. The median concen-
trations per water type vary over four orders of magnitude.
Some general patterns exist in the concentration data (Fig. 1).
Surface waters have the lowest concentrations of all water types,
with, bottled water closer to the higher end. The lower concen-
trations observed in surface water, particularly compared to
drinking water, is likely attributed to the fact that most surface
water studies targeted only larger particles whereas smaller par-
ticles are more abundant (Cabernard et al., 2018). WWTP inﬂuent
shows the highest concentrations based on the median and
Table 1 (continued )
Author Type Sampling
Total Accumulated Score
(TAS, max ¼18)
Dris et al. (2015) WWTP 100 1 1 10004
Talvitie et al. (2015) WWTP 210 0 0 10004
Browne et al. (2011) WWTP 001 0 0 00023
Average 1.57 1.02 1.20 0.77 0.64 1.18 0.21 0.93 0.89 8.41
For the scoring criteria, the reader is referred to Table S2.
TAS values are underlined when all underlying scores are non-zero.
A.A. Koelmans et al. / Water Research 155 (2019) 410e422 417
interquartile range of reported concentrations (Fig. 1) although
WWTP studies generally did not monitor small particles. The high
concentrations therefore reﬂect direct domestic inputs and inputs
from those diffuse land-based sources that are routed via waste
water. WWTP efﬂuent has a lower median compared to WWTP
inﬂuent, which probably reﬂects the retention of microplastics in
WWTPs. Similarly, untreated tap water has higher concentrations
than treated tap water. Concentrations in bottled water are higher
than in tap water, which may reﬂect the higher inﬂux of airborne
particles in the factories, which are inherently more locked in, wear
Fig. 2. Number of studies reporting a particular shape of microplastic particles (from a total of 55 records).
Fig. 3. Number of studies reporting a particular polymer type of microplastic particles (32 out of 55 records reported polymer type).
A.A. Koelmans et al. / Water Research 155 (2019) 410e422418
from caps or bottle walls after production, or the fact that these
studies also included smaller sized particles. For instance,
Schymanski et al. (2018) used Raman microscopy and was thus able
to identify down to >5
m, which also explains the high number
concentrations. The general trends observed here (Fig. 1) still
remain when only the studies that received highest quality scores
are taken into account (Fig. S1). Still, the generalities listed here
should be interpreted with caution given the low number of bottled
water (n¼3), treated tap water (n ¼2), (untreated) DWTP water
(n ¼2) and ground water studies (1), although as noted earlier,
there were many bottled water samples available in the limited
number of studies.
3.2.2. Microplastic shapes in global freshwaters
Microplastics of different shapes were reported. Several factors
limit a potential quantitative analysis of reported data on the
relative abundance of shapes among water types. First, many
studies typically only analysed shapes of a subset of all isolated
particles and it is not clear how representative these subsets were
when it comes to particle shape. Second, studies targeted different
size ranges which also limits their comparability. For instance, ﬁ-
bres are typically small (Cole, 2016), so easily missed when trawl-
ing. Third, studies differed in the extent their water samples were
representative of the studied water systems or water type, which in
turn is affected by spatial and temporal variability. Fourth, although
some particles’shapes were quite well-deﬁned and thus inter-
preted similarly across studies, some others are more ambiguous,
like nurdle, pellet, pre-production pellet, sphere, resin or granule.
Nevertheless, we can provide a relatively robust view of the relative
importance of particle shapes by showing the frequency of shapes
observed across studies (Fig. 2). The reviewed studies (n ¼50) re-
ported (in the order of decreasing reporting frequency): fragment,
ﬁbre, ﬁlm, foam, pellet, sphere, line, bead, ﬂake, sheet, granule,
paint, foil and nurdle (Fig. 2). We argue that this order also reﬂects a
relative order of importance of shapes, that is, the most frequent
shapes detected in a high number of locations globally, as the
reviewed studies concerned many different locations on the globe.
3.2.3. Polymer types reported in global studies on freshwater
For 32 out of 55 records, polymer types were assessed. Similar to
particle shape as discussed above, and ratherthan discussing relative
abundances per study, we consider the relative frequency of re-
ported polymer types observed in water types on a global level.
Often, relative abundances per study are not provided, or may not be
considered accurate due to limited or biased subsets of particles used
for the polymer identiﬁcation. Most frequently observed polymer
types across studies and records are PE zPP >PS >PVC >PET, with
Fig. 4. Size ranges used (A) and number concentrations per size range reported (B) in studies on microplastics in drinking, surface and waste waters (referenced in Fig. 1). Arrows
indicate that no upper or lower size limit was speciﬁed, in which case values of 5 mm or 1
m were assigned, respectively. Panel A: Size ranges per study are ordered alphabetically
per author name. Data points represent the average of the size range. Panel B: reported concentrations as a function of size range. Colours of arrows (Panel B) correspond tocolours
of the box and whiskers in Fig. 1. (For interpretation of the references to colour in this ﬁgure legend, the reader is referred to the Web version of this article.)
A.A. Koelmans et al. / Water Research 155 (2019) 410e422 419
Acrylic or acrylic-related compounds, PA, PEST and PMMA reported
in ﬁve or more records (Fig. 3). The order of the ﬁve most abundant
polymers can be roughly explained by two factors; global plastic
demand and polymer density (Andrady, 2011;Bond et al., 2018).
Global plastic demand would cause an order of
PE >PP >PVC >PET >PS (Bond et al., 2018;Geyer et al., 2017).
However, whereas PE and PP have densities below 1 g/cm
buoyant and PS has a densityclose to that of water, PVC and PET have
densities of 1.3e1.7 g/cm
. Therefore, a relatively high degree of
settling could explain the lower abundances of PVC and PET in the
surface water samples mostly assessed here. Speciﬁc subsets, i.e.
Lakes/Rivers versus WWTP samples were checkedfor differences in
relative abundances of polymer types, but no such differences were
found. For a more detailed analysis of polymers reported in studies,
the reader is referred to Table S1, which provides all observed
polymers on an individual record basis. Recently, Bond et al. (2018)
provided a review of polymer abundance data across environ-
mental compartments in Europe, including 3 surface water and 5
WWTP studies. Instead of providing the reporting incidence across a
large number of global studies, they averaged relative abundances
reported across these 8 European studies, yet found the same order
of abundances for the 5 most dominant polymers.
3.2.4. Sizes of microplastic particles
Studies generally did not report sizes or size distributions
relating to individual particles, which precludes a meta-analysis of
particle size across studies. However size classes were reported
(Table S1) as well as the number of particles observed per size class.
Still, this does not allow for a meaningful quantitative analysis,
because the size bins vary widely across studies (Fig. 4A).
Furthermore, often lower or upper size limits are not speciﬁed so
that it is not clear to what size class reported number concentra-
tions actually relate. Instead of plotting the reported size ranges
across studies (Fig. 4A), reported ranges can be plotted against
mean particle number concentrations (Fig. 4B). The latter graph
clearly shows that studies aiming for smaller particles, like some of
the bottled water and tap water studies, generally ﬁnd the higher
particle number concentrations.
We conclude that based on the limited number of high quality
studies identiﬁed, standardization of microplastic analysis in water
is needed. Quality assurance criteria that require the most im-
provements are sample treatment, polymer identiﬁcation, labora-
tory preparation, clean air conditions and positive controls. In
addition to ensuring that individual studies are of higher quality in
order to achieve more conﬁdence in study ﬁndings, standardized
methods will allow reproducibility and comparability of results and
will lead to the quality of data that are needed to conduct risk as-
sessments. Among water types, reported microplastic concentra-
tions differed widely, but the fact that studies target different size
classes contributes to this variability. Despite the quality limita-
tions, our analysis conﬁrmed that microplastic is frequently present
in freshwaters and drinking water. There is a high need to improve
the analysis of very small microplastics, and to identify them in
different water samples. Fragments, ﬁbers, ﬁlm, foam and pellets
were the most frequently found microplastic shapes in surface
water samples. Relative abundance of polymer types found across
studies reﬂected plastic production and polymer densities. Con-
clusions on size comparisons among studies and water types are
difﬁcult to draw due to the aforementioned differences in targeted
particle sizes. More studies are needed to better understand
occurrence, shape, polymer types, and particle sizes, particularly
for the small plastic particles.
Declarations of interest
Conﬂicts of interest
There is no conﬂict of interest.
AAK and JDF designed the study. NHMN, EH, MK, SM and AAK
performed the study. AAK wrote the article. NHMN, EH, MK, SM and
JDF commented on draft versions of the article. All authors have
approved the ﬁnal article.
The authors alone are responsible for the views expressed in this
publication and they do not necessarily represent the views, de-
cisions or policies of the World Health Organization.
This work was ﬁnancially supported by the World Health Or-
ganization (WHO contract registration 2018/825515-0). Peter
Marsden (Defra) is gratefully acknowledged for critical comments
on an earlier version of the manuscript.
Appendix A. Supplementary data
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