A review of removal of microplastics

Environment International 146 (2021) 106277
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Environment International
journal homepage: www.elsevier.com/locate/envint
Review article
A review of the removal of microplastics in global wastewater treatment
plants: Characteristics and mechanisms
Weiyi Liu a, Jinlan Zhang a, Hang Liu a, Xiaonan Guo a, Xiyue Zhang a, Xiaolong Yao b,
Zhiguo Cao c, Tingting Zhang a, *
a
Department of Environmental Science and Engineering, Research Centre for Resource and Environment, Beijing University of Chemical Technology, Beijing 100029,
People’s Republic of China
Department of Environmental Science and Engineering, Beijing Technology and Business University, Beijing 100048, People’s Republic of China
c
School of Environment, Henan Normal University, Xinxiang 453007, People’s Republic of China
b
A R T I C L E I N F O
A B S T R A C T
Handling Editor: Frederic Coulon
Wastewater treatment plants (WWTPs) are considered to be the main sources of microplastic contaminants in the
aquatic environment, and an in-depth understanding of the behavior of microplastics among the critical treat­
ment technologies in WWTPs is urgently needed. In this paper, the characteristics and removal of microplastics in
38 WWTPs in 11 countries worldwide were reviewed. The abundance of microplastics in the influent, effluent,
and sludge was compared. Then, based on existing data, the removal efficiency of microplastics in critical
treatment technologies were compared by quantitative analysis. Particularly, detailed mechanisms of critical
treatment technologies including primary settling treatment with flocculation, bioreactor system, advanced
oxidation and membrane filtration were discussed. Thereafter, the abundance load and ecological hazard of the
microplastics discharged from WWTPs into the aquatic and soil environments were summarized. The abundance
of microplastics in the influent ranged from 0.28 particles L− 1 to 3.14 × 104 particles L− 1, while that in the
effluent ranged from 0.01 particles L− 1 to 2.97 × 102 particles L− 1. The microplastic abundance in the sludge
within the range of 4.40 × 103–2.40 × 105 particles kg− 1. In addition, there are still 5.00 × 105–1.39 × 1010
microplastic particles discharged into the aquatic environment each day Moreover, among the critical treatment
technologies, the quantitative analysis revealed that filter-based treatment technologies exhibited the best
microplastics removal efficiency. Fibers and microplastics with large particle sizes (0.5–5 mm) were easily
separated by primary settling. Polyethene and small-particle size microplastics (<0.5 mm) were easily trapped by
bacteria in the activated sludge of bioreactor system. The negative impact of microplastics from wastewater
treatment plant was worthy of attention. Moreover, unknown transformation products of microplastics and their
corresponding toxicity need in-depth research.
Keywords:
Microplastics
Wastewater treatment technology
Environmental toxicity
Fate
Meta-analysis
1. Introduction
Microplastics widely occur in the atmosphere (Abbasi et al., 2019),
soil (Guo et al., 2020), ocean (Wang et al., 2020b), freshwater (Han
et al., 2020) and even in the sediment of an Arctic freshwater lake
(González-Pleiter et al., 2020). They can adsorb pollutants, such as
polycyclic aromatic hydrocarbons (Sørensen et al., 2020), heavy metals
(Foshtomi et al., 2019), polybrominated diphenyl ethers (Singla et al.,
2020), pharmaceutical and personal care products (Liu et al., 2019a; Ma
et al., 2019c) from environmental media due to their small volume
(particle debris size usually smaller than 5 mm) and high specific surface
area (Thompson et al., 2004). As a result, microplastics always cause
chronic toxicity due to their accumulation in organisms (Li et al., 2018).
Wastewater treatment plants (WWTPs) are considered to be the main
recipients of terrestrial microplastics before entering natural aquatic
systems (Sun et al., 2019), which convert primary microplastics into
secondary microplastics. The microplastics occurring in municipal
wastewater commonly originate from daily human life activities. For
example, polyester and polyamide components are commonly shed from
clothing during the laundry process (Napper and Thompson, 2016), and
personal care products such as toothpaste, cleanser and shower gel enter
WWTPs resulting from our daily use (Magni et al., 2019). Moreover, the
* Corresponding author.
E-mail address: [email protected] (T. Zhang).
https://doi.org/10.1016/j.envint.2020.106277
Received 27 July 2020; Received in revised form 6 November 2020; Accepted 7 November 2020
Available online 20 November 2020
0160-4120/© 2020 The Author(s).
Published by Elsevier Ltd.
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(http://creativecommons.org/licenses/by-nc-nd/4.0/).
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W. Liu et al.
Environment International 146 (2021) 106277
plastics in garbage are decomposed by microorganisms in the leachate
and then are discharged into WWTPs (Durenkamp et al., 2016). In
addition, the microplastics floating in the atmosphere, which have been
emitted by plastics industries and vehicles, also converge in WWTPs via
atmospheric deposition (Liu et al., 2019c; Mintenig et al., 2017; Wright
et al., 2020). It has been proven that untreated microplastics are
commonly discharged from WWTPs, enter water bodies, and eventually
accumulate in the environment (Carr et al., 2016). Therefore, it is urgent
to study the performance of microplastic by different treatment tech­
nologies in WWTPs and understand the mechanism of removing
microplastics to reduce the amount of microplastics entering the natural
aquatic system. However, few pieces of research have been found to
summarize the microplastics removal mechanisms of the critical treat­
ment technologies in the WWTPs.
According to previous studies on the microplastic treatment tech­
nologies in WWTPs, microplastics were not completely removed from
wastewater by these treatment technologies. For example, after the
preliminary, primary, secondary and tertiary treatment processes in a
WWTP in the UK, the overall abundance decreased by 6%, 68%, 92%
and 96%, respectively (Blair et al., 2019). Mechanical, chemical, and
biological treatment processes removed approximately 99% of the
microplastics entering a WWTP (Ziajahromi et al., 2016). After treat­
ment, the removed microplastics were primarily transferred to the
sludge phase (Ngo et al., 2019).
Moreover, other noteworthy results, which are different from the
results mentioned above, were obtained. For the same treatment process
of microplastics, the microplastics removal efficiencies differed among
various WWTPs. For example, aeration grit chambers, anaerobic-anoxicoxic (A2O) and advanced oxidation (UV and O3) processes were adopted
as microplastic treatment methods in a Beijing WWTP, and their
microplastics removal efficiencies were 58.84%, 54.47% and 71.67%,
respectively (Yang et al., 2019). However, the microplastics removal
efficiencies for the same treatment processes in a Shanghai WWTP
decreased to 49.56%, 26.01%, and 0.78%, respectively (Jia et al., 2019).
These results indicate that it is very challenging to understand the role of
a given treatment process in microplastics removal in a WWTP via a
single investigation. Moreover, the conventional study methods on
microplastics removal are mainly based on qualitative analysis rather
than quantitative analysis (Ngo et al., 2019). Therefore, it is necessary to
develop new methods to qualitatively assess the removal performance of
microplastics in WWTPs.
In recent years, as a statistical method for the quantitative analysis of
a series of independent features of the same object, meta-analysis has
been increasingly applied to analyze wastewater problems in a more
scientific manner (Erni-Cassola et al., 2019). For example, meta-analysis
results indicated that photocatalysts generally attain the highest diaz­
inon elimination efficiency with an average efficiency of 79.2% (95%
confidence interval: 76.8%–81.5%) (Malakootian et al., 2020). Another
meta-analysis study revealed that membrane bioreactor systems might
present the highest removal efficiency of organic trace contaminants in
wastewater (Melvin and Leusch, 2016). To date, no qualitative assess­
ment of the removal of microplastics in WWTPs via meta-analysis has
been reported. It is believed that the meta-analysis approach can provide
a better understanding of the characteristics of microplastics in WWTPs
and a more accurate estimate of microplastics removal in critical
wastewater treatment technologies.
In this study, the critical microplastic treatment technologies in
global WWTPs are reviewed. Meta-analysis was first performed to
identify the optimal microplastics removal technology. Thirty-eight
WWTPs in eleven countries worldwide were investigated in terms of
the occurrence, transfer, and removal mechanism of microplastics in
different critical treatment technologies. The discussion focused on the
removal behavior of various microplastic shapes, polymer types, and
particle sizes. In addition, the risks of microplastics to the aquatic and
soil environments were also evaluated. The results are instructive for a
scientific understanding of the fate of microplastics in WWTPs.
2. Methods
2.1. Data collection
The publications were obtained by searching all databases in the
China National Knowledge Infrastructure and Web of Science using
search terms such as microplastic, wastewater treatment plant, sewage
treatment plant, and sludge. The search included all available publica­
tions until April 2020. The search results indicated that microplastic was
first defined in Science by Thompson in 2004 (Thompson et al., 2004).
The first study on the occurrence and removal of microplastics in
WWTPs was published in 2015 by Talvitie et al. (2015). Relevant pub­
lications over the past three years (2018–2020) have been reviewed. The
publications were individually assessed to eliminate irrelevant articles
based on their abstracts, tables, and figures. Ultimately 23 highly rele­
vant papers covering microplastics in global WWTPs were considered
for meta-analysis. Data retention criteria in publications included: 1) the
name of the corresponding treatment process and microplastic abun­
dances of the influent and effluent; 2) polymer types, shapes and particle
sizes of microplastics and their abundances; 3) studies are independent
of each other and there are no duplicate studies; and 4) basic informa­
tion of WWTPs (location, daily capacity, serving population, etc.).
GetData Graph Digitizer (v.2.25) was used to extract the data of the
microplastic abundances (the influent and effluent of treatment tech­
nology) and removal efficiency presented in the graph.
Due to the difficulty in measuring the mass of microplastics, the
behavior from the perspective of the quantity abundance (particle L− 1)
was evaluated in this study. The microplastic abundance and removal
efficiency were generally provided in the publications. Otherwise, nondetection was assigned a zero value (Yang et al., 2018). It was clear that
the inconsistent microplastic shape nomenclatures and size classes were
discussed in the existing research publications. An ambiguous nomen­
clature inhibits research progress, leading to confusion and miscom­
munication (Hartmann et al., 2019). For analysis convenience, the film
or sheet, pellet or spherical or bead and particle or granule were
consistently renamed film, pellet and particle, respectively. The micro­
plastic size classifications were 100 μm, 500 μm, 1 mm and 5 mm in
previous studies (Wang et al., 2019). Thus, this study divided the size in
the meta-analysis as smaller than 0.5 mm, 0.5–1 mm and 1–5 mm.
2.2. Quantitative meta-analysis
Meta-analysis was performed in R-project for Statistical Computing
(version 3.6.2) using the meta package (Schwarzer, 2007). The micro­
plastic data obtained from each independent study was analyzed, and
the microplastics removal of different treatment technologies was
compared. The risk ratio (RR) value was assigned as the effect size in a
single study. The calculation method of the RR value can be found
elsewhere (Schwarzer, 2007). An RR value lower than 1 indicated that
microplastics could be removed, and lower the value is, the better the
removal is. The effect size in the meta-analysis was a weighted average
of each single study. A study with a higher weight value was supposed to
impose a greater influence on effect size. The weights were determined
by the random effects model of meta-analysis, due to the high hetero­
geneity among the studies (McKenzie et al., 2016).
RR =
AI
AE
(1)
where AI and AE denote the event probabilities for the experimental and
control groups, respectively.
In this study, meta-analysis was used to investigate the removal ef­
ficiency of microplastics in the primary, secondary, and tertiary treat­
ment processes, and also to compare the removal efficiency between
critical treatment technologies. Further, we also analyzed the removal
efficiency of different classifications of microplastics (shapes and
2
W. Liu et al.
Environment International 146 (2021) 106277
particle sizes) in these treatment processes.
τ2 =
2.3. Heterogeneity and publication bias
W=
The heterogeneity test aims to determine whether genuine differ­
ences exist between study results (Higgins et al., 2002). The heteroge­
neity can be expressed by I2, τ2, or the Cochran Q test (Higgins et al.,
2003; Langan et al., 2019). The I2 quantity, ranging from 0% to 100%,
describes the degree of inconsistency among studies in a meta-analysis
sense. The larger the I2 quantity is, the larger the difference between
studies is. The heterogeneity variance parameter is denoted as τ2, which
effectively reflects the heterogeneity among studies. The Cochran Q test
statistic is computed by summing the squared deviations of each study’s
estimate from the overall meta-analysis estimate, thereby weighting
each study’s contribution in the same manner as conducted in the metaanalysis. The p-value is obtained by evaluating the chi-square distribu­
tion with (k-1) degrees of freedom (df) (k: the number of studies). The
difference among studies is caused by random errors when the p-value is
smaller than 0.05.
∑
Q=
ωi (θi − θ)2
(2)
I2 =
Q − df
× 100%
Q
I2
W
1 − I2
df Σωi
∑
(Σωi )2 −
(4)
(5)
ωi 2
where ωi is the weight of each study, θi is the effect value (RR) of each
study, θ is the average of the effect value (RR), and df is the degree of
freedom (k-1).
Contour enhanced funnel plots were used to test for publication bias.
The funnel plots were performed in R-project using the meta package.
These plots showed effect sizes and standard errors in each metaanalysis. The effect sizes which were symmetrical and on the top of
the funnel proved there was no bias (Egger et al., 1997).
3. Characteristics of the microplastics in WWTPs
3.1. Microplastics in wastewater
Microplastics were frequently detected in the influent and effluent of
WWTPs. Table 1 lists the location, daily treatment capacity, serving
population, source of wastewater and main treatment technologies of
the WWTPs in this study. The microplastic abundances in the primary,
secondary, and tertiary treatment processes and effluent are
(3)
Table 1
Information of WWTPs in this study.
Location
Capacity
(m3/day)
Population
Treatment processes
Source of wastewater
Reference
R1
R2
R3
R4(W1)
R4(W2)
R5(W1)
R5(W2)
R5(W3)
R6
R7(W1)
Scotland, UK
Cartagena, Spain
Madrid, Spain
Hong Kong, China
Hong Kong, China
Daegu, Korea
Daegu, Korea
Daegu, Korea
Wuhan, China
M-City, Korea
166,422
35,000
28,400
93,000
2,400,000
26,545
469,249
20,840
20,000
–
1.8 × 105
2.1 × 105
–
–
–
–
–
–
–
–
Pri, Sec, Ter (Nitrification)
Pri, Sec
Sec (A2O)
Pri, Sec
Pri, Ter (Chlorination)
Pri, Sec, Ter (Coagulation, O3)
Pri, Sec, Ter (Coagulation, DF)
Pri, Sec, Ter (Coagulation, RSF)
Pri, Sec (A2O), Ter (Chlorination)
Pri, Sec (A2O)
Municipal
Municipal and Industrial
Municipal
Municipal
After primary treatment
Municipal and Industrial
Municipal and Industrial
Municipal and Industrial
Industrial, Agricultural, Municipal
Municipal
Blair et al., 2019
Bayo et al., 2020
Edo et al., 2020
Ruan et al., 2019
Ruan et al., 2019
Hidayaturrahman and Lee, 2019
Hidayaturrahman and Lee, 2019
Hidayaturrahman and Lee, 2019
Liu et al., 2019d
Lee and Kim, 2018
R7(W2)
R7(W3)
R8
R9(W1)
R9(W2)
R10(W1)
R10(W2)
R11(W1)
R11(W2)
R11(W3)
R11(W4)
R12
R13(W1)
R13(W2)
Y-City, Korea
S-City, Korea
Mikkeli, Finland
Sydney, Australia
Sydney, Australia
Wuxi, China
Wuxi, China
Helsinki, Finland
Turku, Finland
Hameenlinna, Finland
Mikkeli, Finland
Scotland, UK
Shanghai, China
Shanghai, China
–
–
10,000
17,000
48,000
50,000
70,000
–
–
–
–
260,954
–
–
–
–
–
6.7 ×
1.5 ×
–
–
–
–
–
–
6.5 ×
3.5 ×
2.9 ×
Sec (SBR)
Pri, Sec
Pri
Sec
Sec
Pri, Sec (OD), Ter (UV)
Pri, Sec (A2O + MBR)
Ter (DF)
Ter (RSF)
Ter (DAF)
Ter (MBR)
Pri, Sec
Pri, Sec (A2O), Ter (UV)
Pri, Sec (A/O), Ter (UV)
Municipal
Municipal
Municipal
Municipal
Municipal
Municipal
Municipal
Municipal
Municipal
Municipal
Municipal
Municipal
Municipal
Municipal
Lee and Kim, 2018
Lee and Kim, 2018
Lares et al., 2018
Ziajahromi et al., 2017
Ziajahromi et al., 2017
Lv et al., 2019
Lv et al., 2019
Talvitie et al., 2017a
Talvitie et al., 2017a
Talvitie et al., 2017a
Talvitie et al., 2017a
Murphy et al., 2016
Jia et al., 2019
Jia et al., 2019
R14
R15
R16
R17
R18
R19(W1)
R19(W2)
R20
R21(W1)
R21(W2)
R22
R23(W1)
Helsinki, Finland
Beijing, China
Vancouver, Canada
Helsinki, Finland
Northern, Italy
Detroit, USA
Detroit, USA
Paris, France
Xiamen, China
Xiamen, China
Xiamen, China
Los Angeles, USA
270,000
1,000,000
493,271
–
400,000
2,500,000
1700
240,000
75,000
245,800
257,936
–
8.0 ×
2.4 ×
1.3 ×
8.0 ×
1.2 ×
–
–
–
3.4 ×
1.2 ×
1.0 ×
–
Pri, Sec, Ter (BAF)
Pri, Sec (A2O), Ter (UF, UV, O3)
Pri, Sec
Pri, Sec, Ter (BAF)
Pri, Sec, Ter (SAF)
Pri, Sec, Ter (Chlorination)
Pri, Sec, Ter (Chlorination)
Pri, Sec (Biofilter)
Pri, Sec
Pri, Sec
Pri, Sec (Biofilter)
Ter (GF)
Municipal
Municipal
Municipal
Municipal
Combined sewers
Raw wastewater and stormwater
Raw wastewater and stormwater
Municipal and Industrial
Municipal and Industrial
Municipal and Industrial
Municipal and Industrial
–
Talvitie et al., 2017b
Yang et al., 2019
Gies et al., 2018
Talvitie et al., 2015
Magni et al., 2019
Michielssen et al., 2016
Michielssen et al., 2016
Dris et al., 2015
Wang et al., 2019
Wang et al., 2019
Long et al., 2019
Carr et al., 2016
R23(W2)
R24
Los Angeles, USA
Oldenburg, Germany
–
35,616
–
2.1 × 105
Ter (Centrata thickening)
Ter (PF)
–
Municipal and Industrial
Carr et al., 2016
Mintenig et al., 2017
104
105
105
106
106
105
106
106
105
106
105
106
106
(1) Pri, Sec, Ter refer to primary treatment, secondary treatment and tertiary treatment
(2) A2O: anaerobic-anoxic-oxic; A/O: anoxic oxic; OD: oxidation ditch; DF: disc filter; RSF: rapid (gravity) sand filter; DAF: dissolved air flotation; BAF: biologically
active filter; GF: gravity filter; PF: post-filtration; SAF: sand filter; UF: ultra-filtration
3
W. Liu et al.
Environment International 146 (2021) 106277
summarized in Table S1. The microplastic abundances in the influent of
the WWTPs ranged from 0.28 particles L− 1 to 3.14 × 104 particles L− 1
(mean value: 1.90 × 103 particles L− 1; median value: 57.60 particles
L− 1).
The differences in the microplastic abundance could be related to a
variety of complex factors, such as the population served, wastewater
sources (municipal or industrial), economy, and lifestyle. In the
municipal WWTPs, the microplastic abundance was lower, ranging from
0.28 particles L− 1 to 6.10 × 102 particles L− 1 (mean value: 1.27 × 102
particles L− 1; median value: 31.10 particles L− 1). In the municipal and
industrial WWTPs, the microplastic abundances ranged from 1.60 par­
ticles L− 1 to 3.14 × 104 particles L− 1 (mean value: 5.23 × 103 particles
L− 1; median value: 1.86 × 102 particles L− 1). However, few studies have
investigated the microplastic emissions directly from plastic processing
industrial WWTP. In terms of the serving population, the abundance of
the influent microplastics was positively correlated with the serving
population in most WWTPs (Mason et al., 2016). The microplastic
abundance was also influenced by the sampling and detection methods.
Limited wastewater sample volumes increased the uncertainty of the
microplastic abundance and experimental errors. These problems
enhanced the difficulties in the research on the microplastic fate in the
WWTPs.
As indicated in Table S1, microplastics were detected in all treatment
processes in the WWTPs. The microplastic abundance gradually
decreased from primary treatment to secondary treatment. The primary
treatment process based on physical mechanisms was considered the
first barrier to remove microplastics in WWTPs. Primary settling tank
was the most commonly implemented primary treatment method. The
microplastic abundance after primary treatment processes ranged from
0.22 particles L− 1 to 1.26 × 104 particles L− 1 (mean value: 6.87 × 102
particles L− 1; median value: 4.90 particles L− 1). Their abundance
decreased by 4.06–98.96% (mean value: 56.75%; median value:
54.88%), compared to the abundance of microplastics in the influent.
After the primary treatment process, biological treatment (secondary
treatment process) was the most critical technology in the WWTPs. In
biological treatment, A2O was the most widely used technology in
WWTPs. Meanwhile, the biofilter technology had a high biomass load
and a high volumetric reaction rates, which improved the pollutant
removal efficiency and gradually became more popular in WWTPs (Liu
et al., 2020a; Rocher et al., 2012). The abundances after secondary
treatment processes ranged from non-detection to 7.86 × 103 particles
L− 1(mean value: 4.67 × 102 particles L− 1; median value: 6.90 particles
L− 1), resulting in a decrease of abundance by 20.45–95.45% (mean
value: 66.63%; median value: 73.53%).
To further remove the contaminants, 61.76% of the WWTPs
employed tertiary treatment processes, such as advanced oxidation and
membrane filtration processes. After tertiary treatment processes, the
microplastic abundance further decreased in most of the investigated
WWTPs (85.71%), while in others, the abundance increased. The
abundance of the microplastics in effluent ranged from non-detection to
2.97 × 102 particles L− 1 (mean value: 19.26 particles L− 1; median value:
0.40 particles L− 1). Compared with the influent, the microplastic
abundance decreased by 50.00–99.57% (mean value: 85.58%; median
value: 90.34%). As a result, at most 50.00% of the microplastics in the
WWTPs was still discharged through the effluent and entered the
receiving water systems. Hence, microplastic-targeted treatment pro­
cesses are urgently needed.
the WWTPs.
3.2.1. Shape
The shape is an important classification factor of microplastics. The
shape of microplastics affects their removal efficiency in WWTPs
(McCormick et al., 2014). Nine shapes of microplastics were detected in
the influent and effluent of the WWTPs. The abundances of the different
microplastic shapes observed in the WWTPs are summarized in Table 2.
Fibers, pellets, fragments, and films were the most widely detected
microplastics in wastewater, and their highest abundances were
91.32%, 70.38%, 65.43%, and 21.36%, respectively (Bayo et al., 2020;
Hidayaturrahman and Lee, 2019; Lares et al., 2018).
The fiber, a filamentary microstructure, was the dominant micro­
plastic shape in the WWTPs. The microplastic fibers originated from
domestic washings. The increasing amount of washing and textile con­
sumption resulted in the more frequent detection of fibers (Cesa et al.,
2017). During the textile production process, fibers are also produced in
shearing and splicing processes, after which they enter wastewater
(Hidayaturrahman and Lee, 2019; Napper and Thompson, 2016). The
microplastic fragments and pellets originated from cosmetics and per­
sonal care products, such as toothpaste, masks, and soaps (Carr et al.,
2016). The microplastic films originated from plastic packing bags
(Kazour et al., 2019). Moreover, other microplastic shapes, such as
foams, particles, ellipses, lines, and flakes, were also detected in the
WWTPs.
3.2.2. Particle size
Microplastics may end up in the food chain, and the size of micro­
plastics rather than their shape was a crucial factor influencing their
performance and transformation in the WWTPs (Lehtiniemi et al.,
2018). Therefore, it is important to highlight the particle size of
microplastics.
The distribution of the microplastic particle sizes in the WWTPs is
shown in Fig. S1. The abundance of the microplastics smaller than 1 mm
ranged 65.0–86.9% in the influent and 81.0–91.0% in the effluent. With
decreasing microplastic sizes, the primary microplastics were crushed
(physical, chemical, and biological processes) into secondary micro­
plastics (Magni et al., 2019). The smaller microplastic particles were
more likely to be ingested by plankton, filter-feeding organisms, and
fishes, which can cause a series of toxicological effects in these organ­
isms (Qiao et al., 2019). Therefore, the research of the particle size of
microplastics, especially the smaller particle size (smaller than 1 mm)
can be of guiding significance for the subsequent study of biological
toxicity and the environmental transformation of microplastics.
3.2.3. Polymer type
The abundances of the different microplastic polymer types in the
influent and effluent are listed in Table 3. Twenty-nine kinds of poly­
mers were detected in the influent and effluent of the WWTPs. Poly­
ethene (PE), polypropylene (PP), polyamide (PA), polyester (PES),
polystyrene (PS) and polyethene terephthalate (PET) were the top six
most widely detected microplastics in the wastewater, and their highest
Table 2
The abundance of different shapes of microplastics in WWTPs.
Shape
Fiber
Fragment
Film
Pellet
Foam
Particle
Ellipse
Line
Flake
3.2. Shape, particle size and polymer type distribution in the influent and
effluent
Microplastics are a type of polymer mixture with various shapes and
sizes. Different shapes and sizes of microplastics possessed different
physicochemical and toxicity properties (Lehtiniemi et al., 2018).
Therefore, this study emphasized the occurrence and removal of
microplastics with different shapes, particle sizes, and polymer types in
Influent (particles L− 1)
3
0.22–4.60 × 10
0.25–3.40 × 103
0.06–1.30 × 103
0.01–2.21 × 104
nd-2.33
nd-2.91 × 102
0.36
0.12
0.92
Note: nd means non-detection.
4
Effluent (particles L− 1)
Detection times
nd-35.00
nd-80.00
nd-12.00
nd-1.33 × 103
nd
nd-10.00
nd
0.12
nd
12
11
9
7
4
3
1
1
1
W. Liu et al.
Environment International 146 (2021) 106277
(Sun et al., 2019). Table 4 summarizes the microplastic abundance levels
in the sludge treated by different treatment technologies within the
range from 4.40 × 103 particles kg− 1 to 2.40 × 105 particles kg− 1. The
microplastic abundance in the sludge from the primary treatment pro­
cess was higher than that of the secondary treatment process. Gies et al.
(2018) estimated that 0.54–1.28 trillion microplastics occurred in pri­
mary sludge and 0.22–0.36 trillion microplastics occurred in secondary
sludge. In addition, Talvitie et al. (2017b) calculated that 20% of the
microplastics in the secondary sludge flowed back into the wastewater.
Sludge utilization has received much attention in recent years. The
sludge from the WWTPs was mainly utilized for agricultural purposes in
Norway (82%), Ireland (63%), the US (55%), China (45%) and Sweden
(36%), and it was incinerated in the Netherlands (99%), Korea (55%)
and Canada (47%), while the sludge was applied as soil compost in
Finland (89%) and Scotland (40%) (Fig. 1) (Rolsky et al., 2020). Soil
contaminated with microplastics represents a great threat to crops and
agricultural products. Corradini et al. (2019) reported that the average
microplastic abundance in agricultural soils originating from sludge
disposal was 3,500 particles kg− 1. Pyroplastics are a new type of
pollutant derived from the informal or more organized burning of
manufactured microplastics. After sludge incineration, pyroplastics
enter the environment and cause great threats (Turner et al., 2019). In
China, 35% of the sludge originating from WWTPs still enter landfills
(Fig. 1). Microplastics are further transferred into the soil and ground­
water through the leachate (Chen et al., 2012; Rolsky et al., 2020). In
general, soil contamination of microplastic is scarcely known and is thus
considered one of the pressing concerns related to microplastics.
Table 3
The abundance of different polymer types of microplastics in WWTPs.
Polymer
Abbreviation
Influent
(particles
L− 1)
Effluent
(particles
L− 1 )
Detection
times
Polyethene
Polypropylene
Polyamide
Polyester
Polystyrene
Polyethene
terephthalate
Polyurethane
Polyvinyl chloride
Polyvinyl acetate
Alkyd
Ethylenevinylacetate
Polyacrylates
Acrylic
Polyvinyl ethylene
Polyvinyl fluoride
Styrenebutadienestyrene
Styrene-ethylenebutadieneStyrene
Styrene
acrylonitrile
Polyvinyl alcohol
Acrylamide
Polyethene&
Polypropylene
Paint
Polystyrene acrylic
Polyvinyl acrylate
Styrenevinyltoluenebutylacrylate
Polyterpene
Acrylonitrilebutadiene
Ehtylene-acrylate
Ehtylenepropylene
PE
PP
PA
PES
PS
PET
0.03–1.05
0.02–1.42
0.06–0.71
0.22–6.31
0.00–0.41
0.01–0.63
0.00–0.67
0.00–0.22
0.00–0.06
0.07–1.33
0.00–0.08
0.00–0.16
9
8
6
6
5
5
PUR / PU
PVC
PVA
–
EVA
0.07–1.40
0.12–1.65
0.26–0.50
0.13–4.51
0.00–0.01
0.00–0.02
0.00
0.00–0.01
0.00–0.02
0.00
4
3
2
2
2
–
–
PVE
PVF
SBS
0.06–0.40
1.30
0.09
0.09
0.02
0.00–0.03
0.03
0.00
0.00
0.00
2
1
1
1
1
SEBS
0.06
0.00
1
SAN
0.01
0.00
1
PVAL
–
PE&PP
0.03
0.09
0.09
0.00
0.00
0.01
1
1
1
–
PS acrylic
PV acrylate
–
0.01
0.30
0.09
0.01
0.00
0.00
0.00
0.00
1
1
1
1
–
–
0.03
0.80
0.01
0.01
1
1
–
–
0.14
0.28
0.01
0.00
1
1
4. Removal of microplastics in the WWTPs
4.1. Comparison of the different treatment technologies for microplastics
removal
Previous studies reported the microplastics removal efficiency via
individual field sample collected from primary, secondary, and tertiary
treatment processes. However, these studies could not accurately
determine the optimal treatment process and mechanism of micro­
plastics removal. Therefore, this study compared the removal efficiency
of different treatment technologies in global WWTPs via meta-analysis.
The different treatment technologies applied in the WWTPs included
primary treatment processes (primary settling treatment, grit and grease
treatment), secondary treatment processes (A2O, biofilters, and other
bioreactors) and tertiary treatment processes (UV, O3, chlorination,
biologically active filters (BAFs), disc filters (DFs), and rapid sand filters
(RSFs)).
Fig. 2 shows the meta-analysis results for the different treatment
technologies. The weighted average RR values of the primary, second­
ary, and tertiary treatment processes were 0.40, 0.39, and 0.48,
respectively (Fig. S2). The primary and secondary treatment processes
attained similar microplastics removal efficiencies. The tertiary treat­
ment process achieved limited removal efficiency. Especially, the
abundances were 64.07%, 32.92%, 10.34%, 75.36%, 24.17%, and
28.90%, respectively (Long et al., 2019; Mintenig et al., 2017; Talvitie
et al., 2017a; Ziajahromi et al., 2017). The PE, PP, and PS microplastics
originated from plastic products, including food packaging bags, plastic
bottles, and plastic cutlery (Lares et al., 2018; Mintenig et al., 2017;
Talvitie et al., 2017b). The PA, PET, and PES microplastics mainly
originated from textiles and synthetic clothing, which are the main
sources of household microplastics (Hernandez et al., 2017; Sun et al.,
2019; Wei et al., 2019). Furthermore, the mechanical crushing of plastic
products, the tire, and textile industries and the rubber particles in road
dust were also identified as potentially important sources of the PE, PP,
PS and PES microplastics (Hidayaturrahman and Lee, 2019; Nizzetto
et al., 2016; Talvitie et al., 2017a).
In addition to the polymer types mentioned above, specific polymers
were also identified in the WWTPs. For example, alkyds, which are
widely used in industrial coatings, exhibited the highest abundance in a
Glasgow WWTP (28.67%) (Murphy et al., 2016). Therefore, research
priority should be assigned to specific polymer types in addition to
common polymers.
Table 4
The abundance of microplastics in the sludge of different wastewater treatment
processes.
R6
R7
(a)
R7
(b)
R7
(c)
R16
R16
3.3. Microplastics in the sludge
Most of the microplastics removed from wastewater were retained in
the sludge (Mahon et al., 2017). It was found that the microplastic
abundance in the sludge was much higher than that in the wastewater
5
Treatment Process
Abundance (Particles
kg− 1)
Primary clarifier + A2O + Secondary clarifier
Primary settling tank + A2O + Secondary
settling tank
SBR
2.40 × 105
1.49 × 104
9.65 × 103
Primary settling tank + Secondary settling tank
1.32 × 104
Primary settling
Secondary clarifiers
1.49 × 104
4.40 × 103
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Environment International 146 (2021) 106277
poor efficiency in microplastics removal. But a recent study showed that
69–79% of microplastics entering WWTPs are removed by screening and
grit treatment (Ziajahromi et al., 2021). Only light floating microplastics
could be removed during the grease skimming process (Sun et al., 2019).
Grit and grease process combined with primary settle treatment could
improve the efficiency of removing microplastics. Bioreactor (except
A2O and biofilter) attained a notable microplastics removal efficiency.
Sequence batch reactor process (SBR) was found to have removal 98%
microplastics (Lee and Kim, 2018). However, A2O technology was not
suitable for the removal of microplastics because of the sludge returned.
Jiang et al. (2020) indicated that the anoxic-oxic process (A/O) captured
about 16.9% of microplastics in wastewater. The removal efficiency of
the same treatment process is closely related to the characteristics of
wastewater and the types of microplastic polymers. Advanced oxidation
processes showed the medium removal efficiency of microplastics. It can
be seen that the removal efficiencies of microplastics in critical treat­
ment technologies are quite different.
4.2. Influence of the microplastic shape, particle size and polymer type on
microplastics removal
Fig. 3 shows the meta-analysis results of microplastics removal for
four shapes by different treatment technologies which was calculated
with the data summarized in Section 3.2.1. Among the four microplastic
shapes, fibers were the most widely detected microplastics in waste­
water. Their weighted average RR values in the primary, secondary and
tertiary treatment processes were 0.31, 0.41, and 0.43, respectively
(Fig. S3). Primary treatment has superiority over secondary and tertiary
treatment for fiber microplastics removal. Fibers were easily trapped
during primary treatment due to flocculation and settling. After the
primary treatment process, most of the easily settled or skimmed par­
ticles were removed, but the remainder might exhibit a neutral buoy­
ancy (Sun et al., 2019). In contrast, fragments exhibited excellent
removal efficiency during the secondary treatment process. The
weighted average RR values of fragments were 0.41, 0.30, and 0.36,
respectively (Fig. S3). Fragments with a lamellar structure gradually
agglomerated and were ingested by the activated sludge (Jeong et al.,
2016). The weighted average RR values of the films in the primary,
secondary, and tertiary treatment processes were 0.35, 0.34, and 0.47,
respectively (Fig. S3). The microplastics removal efficiencies of the
primary and secondary treatment processes were higher than that of the
tertiary treatment processes. Pellets were easier to remove during the
tertiary treatment process. The weighted average RR values of the pel­
lets in the primary, secondary and tertiary treatment processes were
0.63, 0.76, and 0.35, respectively (Fig. S3). Both filter-based and
Fig. 1. Proportions of sludge utilization type in 12 countries (the remaining
utilization types were described as ‘others’).
Fig. 2. Meta-analysis results of microplastics removal by different treat­
ment processes.
tertiary treatment processes exhibited a wide range of the 95% CIs
(0.22–1.06) because of the difference between the advanced oxidation
process and filter technology. Among them, the advanced oxidation
treatment process removed pollutants via chemical methods, while filter
technology removed pollutants through physical methods. The micro­
plastics removal efficiency of the critical treatment technologies fol­
lowed the sequence of biofilters, filters, primary settling, bioreactors
(except for A2O and biofilters), grit and grease removal with primary
settling, advanced oxidation, grit and grease removal, and A2O, with
weighted average RR values of 0.32, 0.33, 0.39, 0.41, 0.42, 0.56, 0.61
and 0.73, respectively (Fig. S2).
Therefore, filter-based technologies (biofilter, ultrafiltration (UF),
rapid sand filter (RSFs), etc.) achieved the best performance in removing
microplastics. Among them, RSF technology provides rapid and efficient
removal of microplastics (Talvitie et al., 2017a). But in this process, the
microplastics will be broken into smaller particles (Prata, 2018; Sol
et al., 2020). Primary settling treatment attained an excellent efficiency
in removing microplastics, while grit and grease treatment exhibited a
Fig. 3. Meta-analysis results of microplastics removal with different shapes by
different treatment processes.
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Environment International 146 (2021) 106277
promising. The impact of different shapes, particle sizes, and polymer
types on microplastics removal in different treatment processes should
receive more attention. What’s more, the mechanisms of microplastics
removal by the critical treatment technologies should also be studied in
depth.
advanced oxidation treatment processes could effectively intercept
pellets. Moreover, the tertiary treatment process also presented an
extremely high efficiency in removing microplastics with specific
properties and very small particle sizes.
Fig. 4 shows the meta-analysis results of microplastics removal for
three particle sizes by the different treatment processes. During the
tertiary treatment process, the microplastics usually had a small particle
size (smaller than 0.5 mm), which was more difficult to detect and
remove (Hidalgo-Ruz et al., 2012). In addition, in the advanced oxida­
tion processes, microplastics were continuously crushed, resulting in a
negative removal (Lv et al., 2019; Ruan et al., 2019). Therefore, the
meta-analysis was only conducted on the primary and secondary treat­
ment processes. Microplastics with particle sizes smaller than 0.5 mm
were easily trapped during secondary treatment processes. The
weighted average RR values in the primary and secondary treatment
processes were 0.70 and 0.48, respectively (Fig. S4). Microplastics with
a particle size ranging from 0.5 mm to 1 mm were better removed during
primary treatment processes, as well as microplastics with a particle size
ranging from 1 mm to 5 mm. The weighted average RR values of the
microplastics in the 0.5–1 mm size range were 0.31 and 0.74, respec­
tively (Fig. S4). The weighted average RR values of the microplastics in
the 1–5 mm size range were 0.06 and 0.53, respectively (Fig. S4). On the
one hand, the fibers and films had a large particle size and low density,
and they were easily removed by flotation and grease removal processes.
On the other hand, the pellets in personal care products had high den­
sity, and they generally sank to the bottom of pools due to gravity
(Lehtiniemi et al., 2018).
Common polymer analytical methods included gas chromatography
coupled to mass spectrometry (Dümichen et al., 2017), liquid chroma­
tography (Elert et al., 2017), Fourier transform infrared spectroscopy
(Mintenig et al., 2017) and Raman spectroscopy (Lares et al., 2018).
However, it was still difficult to identify individual microplastic polymer
type due to the limitation of these analytical methods (Hidalgo-Ruz
et al., 2012). Thus, a meta-analysis for the different polymer types could
not be conducted until now. PE, as the most frequently detected
microplastic polymer type in the WWTPs, was efficiently removed
during the secondary treatment process, which was also true for PS
polymer. The positively charged PE and PS microplastics had a high
affinity for the negatively charged activated sludge mass (Bhattacharya
et al., 2010).
In a word, fibers and microplastics with large particle sizes (0.5–5
mm) were easily separated by primary settling. Polyethene (PE) and
small-particle size microplastics (smaller than 0.5 mm) were easily
trapped in the activated sludge by bacteria. Therefore, choosing suitable
treatment technologies for microplastics removal in WWTPs is quite
4.3. Mass of microplastics
The quantification of microplastics focused on determining the
number of particles, because the influence and behavior of microplastics
is closely related to the number of particles (Andrady, 2011). Because of
the aging of the microplastics in the environment, the microplastics
were broken into small particles. Therefore, using the mass of micro­
plastics to supplement the description of the occurrence of microplastics
could scientifically and accurately quantify the load of microplastics in
the environment (Rocha-Santos and Duarte, 2015). Mass balance was
used as an intuitional way to explore the fate of microplastics in WWTPs.
From a mass point of view, the WWTP has shown excellent perfor­
mance in the removal of microplastics. Simon et al. (2018) investigated
the mass of microplastics in the influent and effluent of 10 WWTPs in
Denmark for the first time. The mass of microplastics in the influent
ranged from 61 μg L− 1 to 1189 μg L− 1 (mean value ± standard deviation:
352 ± 324 μg L− 1; median value: 240 μg L− 1). The mass of microplastics
in the effluent ranged from 0.5 μg L− 1 to 11.9 μg L− 1 (mean value ±
standard deviation: 4.4 ± 4.3 μg L− 1; median value: 3.7 μg L− 1). Through
the mass balance of the microplastics in the WWTP, it can be found that
only 0.22–6.23% of the microplastics will enter the natural aquatic
system through the effluent. Furthermore, Lv et al. (2019) systematically
evaluated the mass of microplastics in the effluent of each critical
treatment process from two WWTPs in Wuxi, Jiangsu Province, China.
The mass of the microplastics in the influent of two WWTPs was 280 ±
4.5 kg per day and 392 ± 4.5 kg per day, respectively. After the primary
treatment process (aerated grit chamber/ rotary grit chamber), the mass
of the microplastics was reduced to 271.6 ± 2.5 kg and 388 ± 2.5 kg per
day, respectively. After the secondary treatment process (oxidation
ditch/ anaerobic-anoxic-oxic), the mass of the microplastics was
reduced to 225 ± 5.0 kg and 329 ± 3.5 kg per day, respectively. After the
tertiary treatment process (UV disinfection/ Membrane tank), the mass
of microplastics in the effluent was 8.4 kg and 1.96 kg per day,
respectively. Mass of microplastics accumulated in excess sludge was
0.51 kg per day from oxidation ditch system and 0.033 kg per day from
anaerobic-anoxic-oxic-membrane tank system. It can be seen that only
3% or less of the microplastics in the wastewater treatment plant were
discharged into the aquatic environment and 1% of the microplastics
were retained in the sludge produced by the biochemical treatment
process. The remaining 96% of the microplastics were degraded, skim­
ming or retained by the membrane. Among them, membrane retention
occupied a larger proportion, which can be seen from the high removal
rate of the filter-based process.
4.4. Publication bias
Contour enhanced funnel plots of the microplastics removal by pri­
mary, secondary, and tertiary treatment processes were presented in
Fig. S5. Contour enhanced funnel plots of the different shapes and par­
ticle sizes microplastics removal by different treatment processes were
presented in Fig. S6 and Fig. S7, respectively. Collectively, although the
extractable studies are relatively few in some of the meta-analysis, no
evidence of publication bias was observed in the funnel plots.
4.5. Mechanisms of critical treatment technologies in microplastics
removal
4.5.1. Primary settling with flocculation
Fig. 5 showed the schematics of flocculation and primary settling
technologies in microplastics removal. In the flocculation process, flocs
Fig. 4. Meta-analysis results of microplastics removal with different particle
sizes by different treatment processes.
7
W. Liu et al.
Environment International 146 (2021) 106277
Fig. 5. The schematics of primary settling with flocculation technologies in microplastics removal (Lapointe et al., 2020).
Fig. 6. The schematics of the bioreactor system in microplastics removal. (A) Activated sludge process (Zhang et al., 2020); (B) MBR (Adapted from Li et al., 2020);
(C) Biofilter; (D) A2O (Liu et al., 2020b).
8
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Environment International 146 (2021) 106277
interacted with microplastics via hydrogen bonds, van der Waals forces,
or electrostatic forces (Duan and Gregory, 2003; Lapointe et al., 2020).
Like-charged microplastic particles maintain stability due to the repul­
sive inter-particle electrostatic forces. Flocculants possessing opposite
charges with microplastics effectively reduced the repulsive potential
between microplastic particles. It was possible for the Brownian motion
and mechanical agitation to become operative, leading to microplastics
and flocs aggregation (Larue et al., 2003).
Both iron-based salts and aluminum-based salts are widely used
flocculants in wastewater treatment (Ma et al., 2019a). The flocculation
of microplastics with iron was caused by the adsorption of iron hy­
droxide aggregates (Larue et al., 2003). Small aggregates with high
positive charge were locally adsorbed on the microplastic surfaces at low
pH media. In this case, flocs neutralized microplastic charges and
eliminated repulsion forces between microplastics. At neutral and basic
pH media, the floc aggregates size increased, and aggregated form
bridges between microplastics (Larue et al., 2003; Ma et al., 2019b).
Microplastics interacted with aluminum-based flocculants via hydrogen
bonds. Cationic aluminum flocculant was also electrostatically attached
to anionic carboxyl groups in the weathered microplastics. The presence
of new functional groups (such as hydroxyl group (OH), carboxyl group
– C)) on the weathered
(COOH), and carbon-carbon double bond (C–
microplastic surface promoted interactions between the flocs and
microplastics (Lapointe et al., 2020).
Subsequently, the primary settling technology mainly removed the
settable parts in the suspended microplastics. Most of the non-sinkable
floating microplastics adhered to the flocs and precipitated together,
others were skimmed as scum (Lee et al., 2012). These microplastics
were discharged as primary sludge (Murphy et al., 2016). Existing
studies proposed the mechanisms for the removal of microplastics in
flocculation technology and primary settling technology but lack of
identification of the degradation products of microplastics and their
physiochemical properties. The toxicity of the substances generated
after the flocculation and the impact of settling time on settling effi­
ciency of primary settling technology are less known.
microplastics removal in the MBR system. What’s more, the removal of
microplastics could be related to the size of microplastics. The mem­
brane applied in the MBR system usually has a pore size of 0.1 μm. Thus,
the microplastics could be removed in the MBR system theoretically. (Li
et al., 2020).
The biofilter technology was applied as a deep treatment unit after
the bioreactor system. The microplastics entered the biofilter treatment
unit have smaller particle size and lower density. These increased the
difficulty in microplastics removal. But biofilter technology still
demonstrated the highest removal performance of microplastics (Fig. 2).
Biofilter technology integrated physical and biological purification
processes (Fig. 6C), and biofilm filtration and adsorption were the main
mechanisms for microplastics removal. The microbe film growing on the
surface of the inert filter material was in contact with the microplastics
and increased the contact area between microplastics and microorgan­
isms. Excess microbes and retained microplastics were easy to be
removed by backwashing in the ascendant water flow (Rocher et al.,
2012).
Microplastics are regarded as carriers of the microbes, so the
occurrence of microplastics will influence the community and activity of
microbial. Li et al. (2020) found that with the addition of PVC, the mi­
crobial community composition was reduced immediately and the
number of operational taxonomic units decreased from 1665 to 1533.
Subsequently, the number of operational taxonomic units increased to
1735. The percentage of each bacterial in the bacterial community
slightly changed with the operation time. Therefore, the existence of
microplastics PVC did not pose obvious operational taxonomic unit
reduction and has an insignificant effect on the microbial community
structure change. At the same time, it is gratifying that virgin micro­
plastics do not significantly affect the activities of ammonia oxidizing
bacteria, nitrite oxidizing bacteria, and phosphorus accumulating or­
ganisms (Liu et al., 2019b). Therefore, the effect of microplastics on the
performance of the bioreactor system should not be overemphasized.
However, the toxicity of additives contained in the microplastic to
bacteria was unclear. Subsequent research should consider the impact of
microbe containing microplastics on conventional pollutant removal.
Among them, the influence of microplastics on the function of microbe
after adsorption of conventional pollutants also needs in-depth study.
4.5.2. Bioreactor system
Fig. 6 showed the schematics of the bioreactor system in micro­
plastics removal. As shown in Fig. 6A, the bioreactor system removed
microplastics mainly through the ingestion of microbe and the forma­
tion of sludge aggregates. In particular, domesticated activated sludges
were likely to promote the accumulation of microplastics in WWTPs.
Sludge containing microplastics was removed during the subsequent
secondary settling process (Jeong et al., 2016).
A2O is the most widely used bioreactor system in WWTPs (Fig. 2).
However, it had a relatively poor microplastics removal efficiency owing
to the sludge return. Some of the microplastics (20%) transferred into
the sludge would flow back to the aqueous phase. Furthermore, the
degradation of microplastics in A2O was quite slow. Previous studies
reported several functional bacteria with microplastic degradation. The
bacterial strain Rhodococcus degraded 6.4% of the PP polymer mass in
40 days (Auta et al., 2018). And Ideonella sakaiensis complete degraded
PET film microplastics in 6 weeks (Yoshida et al., 2016). However, the
existing hydraulic retention time (7–14 h) cannot achieve the effective
degradation of microplastics only by microorganisms in WWTPs.
Therefore, the conventional activated sludge method is not ideal for
removing microplastics in WWTPs.
Membrane bioreactor (MBR) technology has recently become a
popular treatment process in WWTPs. It presents an excellent perfor­
mance in microplastics removal (removal efficiency 99.9%) (Talvitie
et al., 2017a) due to a high mixed-liqueur suspended solids concentra­
tion (range from 6000 mg L− 1 to 10000 mg L− 1) (Dvořák et al., 2013). As
shown in Fig. 6B, MBR technology integrated membrane separation and
traditional activated sludge method. Most the microplastics were
retained in the biofilm carrier side of the MBR system. This indicated
that the adsorption effect was one of the major contributors to
4.5.3. Advanced oxidation
Chlorination and UV-oxidation were the most popular advanced
oxidation processes in WWTPs. Chlorine is a widely used as disinfection
agent in WWTPs. Microplastics were not completely resistant to the
attack of chlorine (Kelkar et al., 2019). The chlorination process
increased the microplastic abundance because of the cracking of
microplastics (Lv et al., 2019; Ruan et al., 2019). The schematic of
microplastics degradation in chlorination was shown in Fig. 7A. Chlo­
rine potentially broke the existing bonds and introduced new bonds. The
new chemical structure of high-density polyethylene (HDPE) in chlori­
nation disinfection was C-C-C asymmetrical chain, C-C-C symmetrical
chain, CH2 twist, and CH2 bend (Kelkar et al., 2019), identified that
intense chlorination might result in a force of compression on the Raman
peaks. (Eichhorn et al., 2001). A new chlorine carbon bond (Cl-CH2-C-H)
was formed in chlorination. Carbon-chlorine bonds might increase
toxicity and hydrophobicity, which resulted in microplastics more easily
adsorbing and accumulating harmful contaminants (Wang et al., 2018).
Additionally, chlorine occurred on both the aliphatic and aromatic
during PS degradation (Zebger et al., 2003). Raman shifting of the
aliphatic C-H backbone towards a higher wavenumber (from 2901 cm− 1
to 2940 cm− 1) was observed. This shift signified the force of compres­
sion on the backbone bond towards higher energy (Eichhorn et al.,
2001). Chlorination also changed the physical and chemical properties
of microplastics due to its strong oxidizing nature (El-Shahawi et al.,
2010). However, PP was resistant to chlorination. Even at high dosage
and long exposure time, the change of chemical bond was scarcely
observed (Kelkar et al., 2019). Due to competitive reactions and chlorine
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Environment International 146 (2021) 106277
Fig. 7. The schematics of advanced oxidation technologies in microplastics removal. (A) Chlorination (Kelkar et al., 2019); (B) SEM images of the three types of
virgin and UV-oxidation microplastics (Cai et al., 2018); (C) UV-oxidation; (D) PVC UV-oxidation reaction (Shi and Zhang, 2006).
quenching, the coexistence of other pollutants, microorganisms and
biofilms might alter the impact of microplastics structure in
chlorination.
The schematic of removal microplastics in UV-oxidation was shown
in Fig. 7C. The UV-oxidation occurred on the surface of the micro­
plastics, resulting in the change of their topography and chemical
characteristics (Cooper and Corcoran, 2010). Virgin microplastics pre­
sent relatively homogeneous and compact textures. After UV-oxidation,
the surface of microplastics became relatively rough (Fig. 7B). Granular
oxidation/flakes, cracks/flakes, and flakes were common situations of
degradation for the PE, PP, and PS. However, microplastics with cracks
and flakes were easy to break, which produced smaller and even nanoscale plastics (Cai et al., 2018). Cracks as an extension of fractures were
considered as stress concentrators and fracture loci. The formation of
flakes embrittlement occurs on the brittle surface areas or layer of the
microplastics (Cooper, 2012). As shown in Fig. 7D, part of the peroxy
free radicals was formed by the cleavage of C-C bonds and C-H bonds
under the condition of UV irradiation (Cai et al., 2018; Gewert et al.,
2015; Wang et al., 2020a). What’s more, UV irradiation could initiate
hydroxyl groups (OH) and chromophore groups (including several
– C), carbonyl groups (C–
– O) and hydroperox­
unreacted monomers (C–
ide groups (ROOH)) in the microplastic surfaces to form oxygencontaining free radicals and initiate the chain reactions. (Fig. 7D) (Cai
et al., 2018; Singh and Sharma, 2008; Wang et al., 2020a; Zbyszewski
and Corcoran, 2011). These peroxy free radicals produced by the UV
irradiation would undergo secondary reactions to form crosslinking
compounds (Fig. 7D). And the molecular chain with a carbonyl group
will be broken to reduce the relative molecular mass (Cai et al., 2018).
However, the intermediates and the toxicity of UV-oxidation micro­
plastics were less known. The impact of UV irradiation time and envi­
ronmental differences on microplastic degradation requires in-depth
research. In addition, the influence of the salinity and dissolved organic
matter on the degradation of microplastics in WWTPs also needs to be
considered.
4.5.4. Membrane filtration
Membranes with a uniform pore distribution have been widely
applied during wastewater treatment. The schematic of removal
microplastics in membrane filtration was shown in Fig. 8. Membrane
filtration technologies intercepted microplastics in aqueous phase using
different forms of membrane filtration (Baker, 2012). Microplastic
particle size was larger than the ultrafiltration membrane pore size
(nano-scale). Thus, microplastics were completely rejected by the ul­
trafiltration membranes (Ma et al., 2019b). Microplastics filtration led to
a final water flux decline of 38% (Enfrin et al., 2020). This result showed
the existence of interactions between microplastics and the membrane
pores and surface. Microplastics were adsorbed within and onto the
pores, or onto the membrane surface at a high rate. With the increase of
exposure time, more and more microplastics were permeating across the
membrane. For some special membranes, such as polysulfone mem­
branes, were relatively hydrophilic. Microplastics and polysulfone
membranes were negatively charged and hydrophobic. Thus, attractive
polar forces were counterbalanced by the repulsive electrostatic forces
induced by the membrane surface charge and microplastics (Enfrin
10
W. Liu et al.
Environment International 146 (2021) 106277
Fig. 8. The schematic of ultrafiltration technology in microplastics removal (Enfrin et al., 2020).
et al., 2020).
However, in order to ensure the long-term stable operation of the
microfiltration and ultrafiltration membranes, fouling control must be
strictly enforced (Kumar and Ismail, 2015). At the same time, intermo­
lecular repulsion of microplastics and the electrostatic interactions be­
tween microplastics and the membrane surface were the main
mechanisms in microplastics removal by ultrafiltration technology. The
electrostatic interactions between microplastics and ultrafiltration
membranes were detrimental for the performance infiltration (Enfrin
et al., 2020). Meanwhile, membranes suffered from surface fouling due
to the formation of a concentration polarization layer during water
transfer across the membrane (Enfrin et al., 2020). This concentration
polarization induced the formation of the cake. It decreased the per­
formance of membrane filtration by adsorption and stacking of micro­
plastics or solutes onto the surface of the membrane (Baker, 2012).
Therefore, efficient and stable cleaning procedures need further
research to limit the influence of microplastics on membranes.
capacity of WWTPs. These microplastics likely cause harm to aquatic
organisms (Ma et al., 2020). Developing countries and areas with inef­
fective wastewater treatment processes should pay more attention to the
microplastics pollution of aquatic environments.
The microplastics in sludge are eventually retained in the soil envi­
ronment. Sludge is considered one of the most important sources of
microplastics in the soil environment (Bläsing and Amelung, 2018).
43,000–63,000 and 30,000–44,000 tons of microplastics yearly entered
European and North American agricultural soils, respectively (Nizzetto
et al., 2016). The decomposition of these microplastics lasts up to 1,000
years (Tudor et al., 2019). Microplastics absorb toxic compounds and
aggravate soil pollution (Li et al., 2019). The accumulation and trans­
portation of microplastics not only harms the growth of plants but also
affects the functions and microbial communities in soil (Guo et al.,
2020). The ecological toxicity effect and risk of compound pollution of
microplastics and other pollutants necessitates further study.
6. Conclusions and future perspectives
5. Environmental toxicity and risk of microplastics
A meta-analysis helps us to better understand the fate of micro­
plastics in WWTPs. The filter-based treatment process attained the
highest microplastic removal efficiency. Fibers and microplastics with
large particle sizes (0.5–5 mm) were easily separated by primary
settling. PE and small-particle size microplastics (<0.5 mm) were easily
trapped in the activated sludge and by bacteria in the WWTPs. The in­
teractions and removal mechanisms between microplastics and critical
treatment technologies were quite different. Conventional flocculation
interacted with microplastics via van der Waals forces, hydrogen bonds,
or electrostatic forces in flocculation technology. The bioreactor system
removed microplastics mainly through the ingestion of microbe and the
formation of sludge aggregates. Advanced oxidation process affected the
physical/chemical properties of microplastics, broke the existing bonds,
and introduced new bonds. In membrane filtration technology, in­
teractions between microplastics and the membrane pores and surface
made the microplastics easily adsorbed onto the membrane surface.
Some of the microplastics removed from the above technologies were
finally transferred into the sludge, the others released from the WWTPs
posed environmental toxicity and risks.
In current studies of the microplastics in WWTPs, certain problems
need to be resolved in future research. To better evaluate the fate of the
microplastics in WWTPs or other environmental media, further research
should focus on the development of standardized sampling and analysis
methods. Simultaneously, further research should prioritize the study of
specific microplastics, especially in industrial zones. The influencing
Microplastics enter aquatic and soil environments through waste­
water and sludge discharge. They are emerging pollutants as well as
carriers of heavy metals and organic contaminants. Microplastics
adsorbed heavy metals and polycyclic aromatic hydrocarbons could be
ingested by benthic animals, leading to bioaccumulation in marine food
chains (Foshtomi et al., 2019). Microplastics disrupt the soil structure
and microbe metabolism and thus affect the water holding capacity of
the soil (Machado et al., 2018). Certain properties (such as the structure)
of land plants might improve the uptake of microplastics and other
pollutants (He et al., 2018).
The microplastics in the effluent from WWTPs ultimately converge in
the aquatic environment (rivers and oceans). Primary microplastics are
broken into secondary microplastics via physical, chemical, and bio­
logical treatment processes (González-Pleiter et al., 2019). As a conse­
quence, WWTPs are considered to be the main sources of secondary
microplastics in the aquatic and soil environments. According to one
investigation from a WWTP in China, the mass of microplastics dis­
charged into the water is less than <10 kg per day (Section 4.3), but due
to its low density and small volume, the number of microplastics frag­
ments is still high (Lv et al., 2019). As listed in Tables 1 and S1, the
abundance of the microplastics in the effluent is 5.00 × 105–1.39 × 1010
particles on a daily basis (mean value: 7.20 × 109 particles; median
value: 2.00 × 108 particles). In other words, billions of microplastic
particles are discharged into rivers every day due to the high daily
11
Environment International 146 (2021) 106277
W. Liu et al.
factors of the treatment processes in removing microplastics in the
WWTPs also requires in-depth research, such as hydraulic retention
time, salinity and dissolved organic matter. In addition, the impact of
conventional pollutant removal, reaction intermediates and their
toxicity generated by the existing treatment process in the removal of
microplastics were less known. Particularly, the toxicity of additives
contained in the microplastic to bacteria. Microplastic-targeted treat­
ment technologies are also urgently needed to avoid emissions into
aquatic and soil environments. Moreover, the potential impact of the
subsequent utilization of sludge on the soil environment should be
investigated in the future. In particular, research on the effects of
different polymers on plant roots is necessary. This study provides
essential evidence on an in-depth understanding of the critical treatment
technologies of microplastics removal, as well as theoretical support for
the development of microplastic-targeted technology.
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CRediT authorship contribution statement
Weiyi Liu: Writing - original draft, Software. Jinlan Zhang: Data
curation, Software. Hang Liu: Data curation. Xiaonan Guo: . Xiyue
Zhang: . Xiaolong Yao: Validation, Visualization. Zhiguo Cao: Funding
acquisition, Supervision. Tingting Zhang: Funding acquisition, Writing
- review & editing.
Declaration of Competing Interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influence
the work reported in this paper.
Acknowledgement
This work was financially supported by the National Natural Science
Foundation of China (No. 41977142, 41977308), Major Science and
Technology Program for Water Pollution Control and Treatment (No.
2018ZX07111003), Key Technologies Research and Development Pro­
gram (No. 2019YFC1806104) and the Fundamental Research Funds for
the Central Universities (No. JD2006)
Appendix A. Supplementary material
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.envint.2020.106277.
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