water
Article
Particle Size and Pre-Treatment Effects on Polystyrene
Microplastic Settlement in Water: Implications for
Environmental Behavior and Ecotoxicological Tests
Lars Eitzen 1,*, Aki Sebastian Ruhl 1,2 and Martin Jekel 1
1Technische Universität Berlin, Sekr. KF 4, Straße des 17, Juni 135, D-10623 Berlin, Germany;
2German Environment Agency (UBA), Section II 3.1, Schichauweg 58, D-12307 Berlin, Germany
*Correspondence: [email protected]
Received: 19 October 2020; Accepted: 4 December 2020; Published: 8 December 2020
Abstract:
Microplastic (MP) particle dispersions used in many recent publications covering adsorption
or toxicological studies are not characterized very well. The size distribution of polydisperse
dispersions is highly dependent on the agglomeration processes and influences experimental outcomes.
Therefore, pre-treatment is a prerequisite for reproducibility. In this study, manual/automated
shaking and ultrasonic treatment as different mechanical dispersion techniques were applied for
the dispersion of cryomilled polystyrene (PS). Particle numbers and size distribution of dispersions
were analyzed by a light extinction particle counter and the dispersion efficiency (E
D
) as the ratio
between calculated volume and theoretical volume of suspended particles was used to compare
techniques. PS dispersions (20 mg/L) treated for 90 min in an ultrasonic bath (120 W, 35 kHz) were
evenly dispersed with a particle concentration of 140,000 particles/mL and a high reproducibility
(
rel. SD =2.1%, n=6
). Automated horizontal shaking for 754 h (250 rpm) reached similar particle
numbers (122,000/mL) but with a lower reproducibility (rel. SD =9.1%, n=6). Manual shaking by
hand dispersed the lowest number of particles (55,000/mL) and was therefore found to be unsuitable to
counteract homo-agglomeration. E
D
was calculated as 127%, 104% and 69% for ultrasonic treatment,
horizontal shaking and manual shaking, respectively, showing an overestimation of volume assuming
spherical shaped particles.
Keywords:
microplastics; polystyrene; dispersion; ultrasonic; deagglomeration; size distribution;
sample preparation
1. Introduction
A great emphasis in microplastic (MP) research is put on the spatial distribution, transport and
behavior of microplastics in water. The interactions of MP in the aqueous phase are numerous:
leaching of potentially toxic additives, adsorption of organic compounds and metals to MP and
toxicological effects on organisms are being investigated. With a few exceptions, all these studies use
artificial MP dispersions to extrapolate laboratory findings to environmental behavior. For this reason,
meaningful results require attention during the preparation of MP dispersions.
MP exposure experiments conducted with only a few details on applied mass, particle size
distribution and concentration are hard to compare [
1
]. Prerequisites have been formulated for
particle characterization used in toxicology studies regarding surface area or size distribution but also
homogeneity of dispersion [
2
,
3
]. Only fully dispersed, stable dispersions with most particles existing
separately allow for correct extrapolations of mass/number concentration effects. Dispersion stability
is linked to particle size and specific surface area. However, pristine polymer particles as used in many
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Water 2020,12, 3436 2 of 12
studies are highly hydrophobic and poorly wettable if not chemically stabilized or further processed [
4
].
Depending on the material type and applied concentration of these particles, attachment to laboratory
glassware, accumulation at the liquid–gas interface, and formation of homo-agglomerates are the
consequences [
5
]. This reduces the availability of particles to participate in experiments and can strongly
bias outcomes. The OECD Guideline concerning stability of nanomaterials highlights the dispersion
stability as an important parameter affecting the environmental behavior of nanomaterials (with
nanoplastics already being studied by some research groups) [
6
]. In many cases, surfactants such as
sodium dodecyl sulfate or polysorbate (Tween) 20 or 80 are used and commercial particle dispersions are
thereby commonly stabilized [
7
,
8
]. Surfactants are also added during the synthesis of MP which could
alter the surface characteristics and thus the adsorption process [
8
,
9
]. Nevertheless, surfactants can
also bias experiments: Renzi et al. [
10
] recorded a higher mortality and immobilization in toxicological
experiments with MP when the surfactant Triton X-100 was used. The surfactant itself had negative
effects on the organisms but the more stable dispersion of particles could also lead to increased ingestion
and toxicity. Xia et al. [
11
] reported the effect of non-ionic surfactants on the sorption of organic
pollutants onto microplastics. Natural organic matter (NOM) is also used in some studies to stabilize
MP and mimic environmental conditions, but the effect of NOM on dispersion stability has not been
fully resolved yet. Reported results indicate a stabilizing as well as no effect using NOM standard
samples from the International Humic Substances Society (IHSS) in MP dispersions [12–16].
Oxidation of MP surfaces as an effect of weathering processes increases polarity, hydrophilicity
and induces charge [
17
,
18
]. Artificial weathering can be achieved by UV photodegradation or chemical
oxidation using hydrogen peroxide or ozone. Van der Esch used an alkaline oxidation with potassium
hydroxide to simultaneously fragment and oxidize polystyrene (PS), polyethylene terephthalate (PET)
and polyactic acid (PLA) polymers to obtain a stable dispersion [
3
]. The advantage of surface activation
lies in the mode of stabilization which can closely resemble environmental weathering processes and
thus create more realistic scenarios. Artificial weathering, however, is a time-consuming process,
especially when using UV radiation. Ozone has been applied to stabilize PS particles, but the oxidation
caused a size reduction of particles and a fraction of PS was dissolved [5].
The agglomeration behavior of dispersions has already been broadly studied for
nanoparticles [19,20]
, with a focus on ecological investigations [
21
]. Pre-treatment for deagglomeration
is an important step to ensure size/surface-dependent particle effects for specific applications. In the case
of nanoparticle research, pre-treatments for dispersing solids include hot air oxidation, application of
ozone, deep-freezing below 195 ◦C and the use of chemical stabilizers [22–24].
Ultrasonic treatment is also commonly used in this field, as it is reported to break down
agglomerates in the nanoscale [
25
]. Acoustic cavitation as the main process leads to deagglomeration
and formation of OH-radicals with temperatures of up to 5000 K and pressures of 1000 atm after bubble
collapse. Cavitation and cavitation-induced shockwaves accelerate particles in dispersion which will
eventually collide. These interparticle collisions can change the surface morphology, composition and
reactivity [
26
]. Sonochemistry, therefore, offers interesting possibilities to stabilize MP dispersions
through a combination of physical and chemical interactions.
A stable and fully dispersed dispersion is characterized by stronger repulsive forces which
kinetically hinder the non-equilibrium state to reach equilibrium in an agglomerated state [
6
].
So, either the net forces in the dispersion have to be measured or the state of particles (isolated
or agglomerated) has to be monitored. In many studies, scanning electron microscopy (SEM) images
are provided to characterize particles used for dispersions [
8
]. Static imaging, however, may not be
suitable since particles are removed from the test matrix (usually water), dried and further prepared
(e.g., sputtered with gold) to meet prerequisites of the imaging process. SEM images still give valuable
insights concerning particle size and morphology [27].
Zeta potential measurements are widely used to study the effects of ion strength, pH and humic
substances on the stability of MP and nanoplastic (NP) dispersions [
12
,
13
,
15
,
16
]. This parameter is
essential to characterize dispersions, but measurements are elaborate and time-consuming and limited
Water 2020,12, 3436 3 of 12
to smaller particle sizes depending on the density of the particle. Particle concentration measurements,
on the other hand, are fast and can give an insight into the size distribution of a polydisperse system.
Through the simple measurement of light extinction, the particle concentration can be determined
directly in the liquid as an index of dispersibility. The number of particles per unit volume combined
with size measurements are good indicators for the state of a dispersion [21].
In this work, we evaluated additive-free methods of dispersion for cryomilled PS particles.
For this purpose, manual shaking by hand, long-term horizontal shaking and ultrasonic treatment
were compared regarding the suitability of dispersing particles, and the effects on particle numbers
and size fractions were investigated. Light extinction measurements were used as a quality indicator
for the degree of dispersion. By volume calculation of dispersed particles, the dispersion efficiency E
D
was determined to evaluate the methods of dispersing.
2. Materials and Methods
PS particles were produced by cryogenic ball milling (Cryomill, Retsch, Germany) of pristine
PS pellets (BASF, Ludwigshafen, Germany). The procedure was previously documented in detail [
5
].
The PS powder was then dry-sieved over a 100
µ
m stainless steel mesh (Retsch, Haan, Germany)
to exclude larger particles. Ultrapure water (ELGA, Celle, Germany) was used for all batches and
cleaning steps. In this process, 500 and 1000 mL glass bottles (Schott, Mainz, Germany) were used for
the preparation of the batches. Thorough cleaning of all glassware was achieved by multiple washing,
including the use of detergent and ultrasonic baths.
PS particle batches were prepared by weighing-in with a lab scale (A200S, Sartorius, Germany)
using an anti-static gun and carefully rinsing the particles into the bottles. Ultrapure water was added by
weight to obtain a particle concentration of 20 mg/L PS particles. Three different treatment approaches
were used to disperse the hydrophobic PS particles: manual shaking by hand, automated shaking on a
horizontal shaker and ultrasonic treatment.
Manual shaking was continuously done by hand with a consistent movement so that the water–gas
interface was disrupted. Each up and down movement of the bottle was counted as one agitation.
Particle measurements were made every 50 agitations up to a total of 250 agitations.
A horizontal shaker was used at 250 rounds per minute for automated shaking. Initially, the batches
were measured every 60–80 min, and this interval was increased throughout the experiment for, in total,
754 h to fully evaluate the impact of long-term agitation.
Ultrasonic treatment was done in an ultrasonic bath (Sonorex Super RK 106, Bandelin, Germany)
with a rated output of 120 W, and a frequency of 35 kHz was applied in 5–15 min intervals. Bottles were
submerged in a deionized/tap water mixture to approximately 2/3 of the height. The uniformity of the
ultrasonic field was not tested.
Particle size and number was determined by light extinction measurement using a particle counter
(SVSS, PAMAS, Rutesheim, Germany). For each measurement, 3 mL of the sample was analyzed and
every sample was measured in triplicate (mean value is shown, error bars are provided). The particle
counter groups detected particles into channels, the boundary settings for these channels are provided
in the SI, Section D. Batches were slightly stirred before measurement to resuspend deposited particles
and rinse-offparticles attached to the upper part and neck of the bottles. Previous experiments
showed that magnetic stir bars can increase particle concentration through abrasion of the bars or the
bottle bottom, and were therefore not used. For the settling experiment, the batch was not shaken
and only moved carefully for measurement purpose. All concentration values shown are averaged
from 3 measurements, and no particle settling could be detected between triplicate measurements.
Average particle diameter was about 3
µ
m and differences in the densities of PS and water is low,
therefore significant settling in the time frame of a measurement—(approximately 3 min for triplicate
analyses)was not expected. As illustrated in Figure 1, the timespan of measurement is too small for a
considerable settling process of particles expected in the size range of 1–20 µm.
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143
Figure 1: Theoretical position of an exemplary PS particle with a density of 1.05 g/cm3 during settling 144
in the course of a measurement with PAMAS particle counter. Particle starts to sink at the water level. 145
Height = 0 cm: water level of glass bottle; height = -15.5 cm: bottom of glass bottle. Full, dashed and 146
dash-dotted lines: theoretical location of particles of different diameters. Horizontal dotted line: 147
suction height of tubing connected to PAMAS device 7 cm from water surface. Highlighted area 148
shows timespan of a measurement (less than 3 minutes). Stoke’s law with assumption of spherical 149
shape was used for calculations. 150
Suspended solid volume of PS particles was calculated using particle size data with the lower 151
channel boundary and using spherical shape (see SI, section A). In a previous study the irregular 152
morphology of cryogenic milled PS powder was shown [5]. The lower channel boundaries were 153
therefore used to partly compensate for overestimation of volume by assuming spherical shape of 154
particles. In order to compare the preparation methods, the parameter dispersion efficiency ED was 155
used (for formulae see SI, section C). ED is the ratio between calculated suspended solid volume Vcss 156
and theoretical suspended solid volume Vtss and indicates the state of the dispersion (fully dispersed 157
vs. agglomerated/attached to surfaces etc.). Vtss was calculated using suspended solid mass and a PS 158
density of 1.05 g/cm3. Vcss was calculated using the particle counter data and the lower channel 159
boundary (see SI, section D) and volume formula for spherical shape. 160
161
3. Results 162
3.1 Horizontal shaker vs. ultrasonic treatment 163
A set of six identically prepared batches was placed on a horizontal shaker for 754 h and particle 164
concentrations were repeatedly measured (Figure 2 (a)). After 754 h the batches were treated with 165
ultrasonic twice for 15 minutes. Initial particle concentrations varied between 27,000 and 33,000/mL 166
and increased to a plateau of about 102,000 – 134,000/mL after 410 h (mean = 120,000/mL, 167
rel. SD = 9.1%). Additional horizontal shaking did not significantly increase particle numbers. 168
Subsequent ultrasonic treatment, however, led to a further increase in particle numbers by 18% 169
(mean = 143,000/mL) possibly due to deagglomeration of particles through higher shear forces 170
compared to physical shaking. In addition, rel. SD decreased to 4.5% equalizing the batches. Mean 171
ED after 754 h was 104%, additional ultrasonic treatment decreased ED to 98%. Long-term horizontal 172
shaking only resulted in a partial deagglomeration. This has to be seen critically since usual contact 173
times of adsorption experiments are in the magnitude of 48-72 hours [28,29] with even less efficient 174
dispersion. 175
Figure 1.
Theoretical position of an exemplary cryomilled polystyrene (PS) particle with a density of
1.05 g/cm
3
during settling in the course of a measurement with PAMAS particle counter. The particle
starts to sink at the water level. Height =0 cm: water level of glass bottle; height =
−
15.5 cm: bottom of
glass bottle. Full, dashed and dash-dotted lines: theoretical location of particles of different diameters.
Horizontal dotted line: suction height of tubing connected to PAMAS device 7 cm from water surface.
Highlighted area shows timespan of a measurement (less than 3 min). Stoke’s law with assumption of
spherical shape was used for calculations.
The suspended solid volume of PS particles was calculated using particle size data with the lower
channel boundary and using spherical shape (see SI, Section A). In a previous study, the irregular
morphology of cryogenic milled PS powder was shown [
5
]. The lower channel boundaries were
therefore used to partly compensate for the overestimation of volume by assuming a spherical shape
of particles. In order to compare the preparation methods, the parameter dispersion efficiency E
D
was
used (for formulae see SI, Section C). E
D
is the ratio between calculated suspended solid volume V
css
and theoretical suspended solid volume V
tss
and indicates the state of the dispersion (fully dispersed
vs. agglomerated/attached to surfaces etc.). V
tss
was calculated using the suspended solid mass and a
PS density of 1.05 g/cm
3
. V
css
was calculated using the particle counter data and the lower channel
boundary (see SI, Section D) and volume formula for spherical shape.
3. Results
3.1. Horizontal Shaker vs. Ultrasonic Treatment
A set of six identically prepared batches was placed on a horizontal shaker for 754 h and
particle concentrations were repeatedly measured (Figure 2a). After 754 h, the batches were treated
ultrasonically twice for 15 min. Initial particle concentrations varied between 27,000 and 33,000 1/mL and
increased to a plateau of about 102,000–134,000 1/mL after 410 h (mean =120,000 1/mL,
rel. SD =9.1%
).
Additional horizontal shaking did not significantly increase particle numbers. Subsequent ultrasonic
treatment, however, led to a further increase in particle numbers by 18% (mean =143,000 1/mL)
possibly due to deagglomeration of particles through higher shear forces compared to physical shaking.
In addition, rel. SD decreased to 4.5%, equalizing the batches. Mean E
D
after 754 h was 104%,
additional ultrasonic treatment decreased E
D
to 98%. Long-term horizontal shaking only resulted
in a partial deagglomeration. This has to be seen critically since usual contact times of adsorption
experiments are in the magnitude of 48–72 h [28,29] with even less efficient dispersion.
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176
Figure 2: (a) Left: Particle concentration of six batches (20 mg/L PS particles) during 750 h horizontal 177
shaking (HS). Right: Particle concentration of the same 6 batches during 30 min ultrasonic treatment 178
(UT). (b) Particle concentrations of two batches (20 mg/L PS particles); batch G was manually shaken 179
(MS) for 250 times (left diagram, full squares) and subsequently sonicated (right diagram, empty 180
squares), batch H was directly sonicated (UT; right diagram, empty circles). Error bars show standard 181
deviation of n = 3. 182
3.2 Manual shaking vs. ultrasonic treatment 183
To analyse the effect of manual shaking compared to sonication two batches (20 mg/L PS) were 184
prepared. Initial particle concentrations of both batches were 25,000/mL after slight mixing. Batch G 185
was then repeatedly shaken 50 times and measured up to 250 agitations (Figure 2 (b) left diagram, 186
full squares), then sonicated for in total 45 minutes (Figure 2 (b) right diagram, empty squares). Batch 187
H (right diagram, empty circles) was directly sonicated without manual shaking. 188
Manual shaking of batch G reached 55,000/mL after 250 agitations with only little increase in 189
particle numbers. Sonication for 45 minutes increased particle concentration of batch G to 190
135,000/mL. After 45 minutes of sonication batch H as well reached a concentration of 133,000/mL. 191
Manual shaking achieved an ED of 69% after 250 agitations. After ultrasonic treatment batches G and 192
H reached ED of 106% and 104%, respectively. Almost complete dispersion was reached after 193
25 minutes of ultrasonic treatment. Measurements at ultrasonic durations of 5, 10, 15 and 30 minutes 194
show that manual shaking before sonication did not improve dispersibility. The final particle 195
concentrations of both batches are almost identical after sonication, showing the reproducibility of 196
ultrasonic treatment. This strongly emphasizes that manual shaking only is not a sufficient way of 197
dispersing particles that tend to agglomerate. 198
3.3 Reproducibility of ultrasonic treatment 199
Reproducibility of the dispersion preparation is an essential requirement. Therefore, a set of six 200
batches (20 mg/L PS particles) was sonicated consecutively and particles were measured after every 201
15 minutes of treatment. Initial particle concentrations varied from 2,600 to 6,500/mL 202
(mean = 4,800/mL, rel. SD = 26.4%) without any treatment. Particle concentrations reached a mean of 203
120,000/mL with rel. SD of 3.5% after 120 minutes of sonication. An additional relatively small 204
increase to 126,000/mL occurred after treatment for 180 minutes, indicating that ultrasonic treatment 205
did not further erode particles. Ultrasonic treatment broke up agglomerates to a specific limit which 206
is likely a function of applied power, as was suggested in another work [30]. This pre-treatment 207
technique produced comparable dispersions, but attention has to be paid on the extent of interparticle 208
bonding (which depends on material, size, shape and surface groups). In contrast to prior 209
experiments the discrepancy between the batches after 30 minutes is greater compared to the batch 210
Figure 2.
(
a
) Left: Particle concentration of six batches (20 mg/L PS particles) during 750 h horizontal
shaking (HS). Right: Particle concentration of the same 6 batches during 30 min ultrasonic treatment (UT).
(
b
) Particle concentrations of two batches (20 mg/L PS particles); batch G was manually shaken (MS) for
250 times (left diagram, full squares) and subsequently sonicated (right diagram, empty squares), batch H
was directly sonicated (UT; right diagram, empty circles). Error bars show standard deviation of n=3.
3.2. Manual Shaking vs. Ultrasonic Treatment
To analyze the effect of manual shaking compared to sonication, two batches (20 mg/L PS)
were prepared. Initial particle concentrations of both batches were 25,000 1/mL after slight mixing.
Batch G was then repeatedly shaken 50 times and measured up to 250 agitations (Figure 2b left
diagram, full squares), then sonicated for a total of 45 min (Figure 2b right diagram, empty squares).
Batch H (right diagram, empty circles) was directly sonicated without manual shaking.
Manual shaking of batch G reached 55,000 1/mL after 250 agitations with only a small increase in
particle numbers. Sonication for 45 min increased particle concentration of batch G to 135,000 1/mL.
After 45 min of sonication, batch H also reached a concentration of 133,000 1/mL. Manual shaking
achieved an E
D
of 69% after 250 agitations. After ultrasonic treatment, batches G and H reached
E
D
of 106% and 104%, respectively. Almost complete dispersion was reached after 25 min of
ultrasonic treatment. Measurements at ultrasonic durations of 5, 10, 15, and 30 min show that manual
shaking before sonication did not improve dispersibility. The final particle concentrations of both
batches are almost identical after sonication, showing the reproducibility of ultrasonic treatment.
This strongly emphasizes that manual shaking only is not a sufficient way of dispersing particles that
tend to agglomerate.
3.3. Reproducibility of Ultrasonic Treatment
Reproducibility of the dispersion preparation is an essential requirement. Therefore, a set of
six batches (20 mg/L PS particles) was sonicated consecutively and particles were measured after
every 15 min of treatment (Figure 3). Initial particle concentrations varied from 2600 to 6500 1/mL
(
mean =4800 1/mL,
rel. SD =26.4%) without any treatment. Particle concentrations reached a mean of
120,000 1/mL with rel. SD of 3.5% after 120 min of sonication. An additional relatively small increase to
126,000 1/mL occurred after treatment for 180 min, indicating that ultrasonic treatment did not further
erode particles. Ultrasonic treatment broke up agglomerates to a specific limit which is likely a function
of applied power, as was suggested in another work [
30
]. This pre-treatment technique produced
comparable dispersions, but attention has to be paid on the extent of interparticle bonding (which
depends on material, size, shape and surface groups). In contrast to prior experiments, the discrepancy
between the batches after 30 min is greater compared to the batch from Figure 2b (right diagram)
and full dispersibility was reached within 90–120 min. The mean E
D
after 90–120 min was 125%,
which implies an overestimation of the suspended solid volume.
Water 2020,12, 3436 6 of 12
Water 2020, 12, x FOR PEER REVIEW 6 of 12
from Figure 2 (b, right diagram) and full dispersibility was reached within 90-120 minutes. The mean 211
ED after 90-120 minutes was 125% which implies an overestimation of suspended solid volume. 212
213
Figure 3: Particle concentrations of six batches (A-F = 20 mg/L PS particles) during ultrasonic 214
treatment of 180 min. Error bars show standard deviation of n = 3. 215
3.4 Changes in particle size distribution 216
To identify changes in the particle composition through deagglomeration, the particles were 217
grouped into the size fractions <5 µm, 5-10 µm and >10 µm since the majority of particles detected 218
are well below 10 µm. As can be seen from Figure 4 (a), physical agitation increased the particle 219
numbers of all size fractions (data shown here is for batch A of the horizontal shaker experiment, but 220
similar outcomes were achieved with all other batches). The increase in the size fraction <5 µm is 221
considerably larger than in the other two size fractions and increased from around 63.5% after 222
100 agitations by manual shaking to 83.7% after 754 h automated shaking and 0.5 h ultrasonic 223
treatment. The proportion of the fractions 5-10 µm and >10 µm decreased from 22.0% and 14.5% to 224
12.6% and 3.7%, respectively. 225
226
Figure 4: (a) Particle concentration of batch A during manual shaking (MS), horizontal shaking (HS) 227
and ultrasonic treatment (UT). (b) Particle concentration of batch A (20 mg/L PS particles) during 228
ultrasonic treatment (UT) for 180 min. Particles in all diagrams were grouped in size fractions <5 µm, 229
5-10 µm and >10 µm. Error bars show standard deviation of n = 3. 230
Figure 3.
Particle concentrations of six batches (A–F =20 mg/L PS particles) during ultrasonic treatment
of 180 min. Error bars show standard deviation of n =3.
3.4. Changes in Particle Size Distribution
To identify changes in the particle composition through deagglomeration, the particles were
grouped into the size fractions <5, 5–10, and >10
µ
m, since the majority of particles detected are
well below 10
µ
m in size. As can be seen from Figure 4a, physical agitation increased the particle
numbers of all size fractions (data shown here are for batch A of the horizontal shaker experiment,
but similar outcomes were achieved with all other batches). The increase in the size fraction <5
µ
m
is considerably larger than in the other two size fractions and increased from around 63.5% after
100 agitations by manual shaking to 83.7% after 754 h automated shaking and 0.5 h ultrasonic treatment.
The proportion of the fractions 5–10 and >10
µ
m in size decreased from 22.0% and 14.5% to 12.6%
and 3.7%, respectively.
Water 2020, 12, x FOR PEER REVIEW 6 of 12
from Figure 2 (b, right diagram) and full dispersibility was reached within 90-120 minutes. The mean 211
ED after 90-120 minutes was 125% which implies an overestimation of suspended solid volume. 212
213
Figure 3: Particle concentrations of six batches (A-F = 20 mg/L PS particles) during ultrasonic 214
treatment of 180 min. Error bars show standard deviation of n = 3. 215
3.4 Changes in particle size distribution 216
To identify changes in the particle composition through deagglomeration, the particles were 217
grouped into the size fractions <5 µm, 5-10 µm and >10 µm since the majority of particles detected 218
are well below 10 µm. As can be seen from Figure 4 (a), physical agitation increased the particle 219
numbers of all size fractions (data shown here is for batch A of the horizontal shaker experiment, but 220
similar outcomes were achieved with all other batches). The increase in the size fraction <5 µm is 221
considerably larger than in the other two size fractions and increased from around 63.5% after 222
100 agitations by manual shaking to 83.7% after 754 h automated shaking and 0.5 h ultrasonic 223
treatment. The proportion of the fractions 5-10 µm and >10 µm decreased from 22.0% and 14.5% to 224
12.6% and 3.7%, respectively. 225
226
Figure 4: (a) Particle concentration of batch A during manual shaking (MS), horizontal shaking (HS) 227
and ultrasonic treatment (UT). (b) Particle concentration of batch A (20 mg/L PS particles) during 228
ultrasonic treatment (UT) for 180 min. Particles in all diagrams were grouped in size fractions <5 µm, 229
5-10 µm and >10 µm. Error bars show standard deviation of n = 3. 230
Figure 4.
(
a
) Particle concentration of batch A during manual shaking (MS), horizontal shaking (HS)
and ultrasonic treatment (UT). (
b
) Particle concentration of batch A (20 mg/L PS particles) during
ultrasonic treatment (UT) for 180 min. Particles in all diagrams were grouped in size fractions <5
µ
m,
5–10 µm and >10 µm. Error bars show standard deviation of n =3.
For sonication, the first minutes of ultrasonic treatment sufficed to increase numbers of dispersed
particles and greatly change particle composition (Figure 4b, data shown for batch A). Particle numbers
Water 2020,12, 3436 7 of 12
of the fractions 5–10
µ
m and >10
µ
m did not further increase after 90 min of ultrasonic treatment,
whereas a slight increase for the fraction <5µm was observed.
Before ultrasonic treatment, the size fractions <5, 5–10, and >10
µ
m made up 66.5%, 18.6% and
14.8% of all particles, respectively. After 30 min, the size fraction ratios changed to 78.1%, 15.2%,
and 6.7% for <5, 5–10, and >10
µ
m, respectively. Subsequent ultrasonic treatment increased the number
of particles but only led to minor changes in the size composition. The size fractions after 180 min
ultrasonic were 82.5%, 12.5%, and 5.0% for <5, 5–10, and >10
µ
m, respectively. In terms of dispersion
characterization, horizontal shaking and sonication lead to a similar dispersion composition (see
Figure 4a,b). The initial increase in particle concentrations was caused by deagglomeration of larger
particles with weak coherence and the number of particles of fraction <5
µ
m increased, whereas particle
numbers of the two larger fractions decreased with increasing treatment time. Further disintegration of
larger particles or agglomerates could not be shown since the number of larger particles/agglomerates
(fraction >10
µ
m) remained constant. This is in accordance with Meissner et al. [
31
], who reported no
further deagglomeration/disintegration visible after thorough sonication of carbide nanoparticles.
3.5. Changes in Calculated Volume Distribution during Ultrasonic Treatment
As additional criteria for dispersion efficiency, suspended solid volumes were calculated from
particle numbers of each measurement channel. After 90 min of sonification, the calculated volume did
not further increase (Figure 5a). However, values from 90 to 180 min are scattered due to a few larger
particles still present in the batch which greatly affected the total calculated volume (which can also be
seen in Figure 6). The calculated particle volume of sonicated samples from ultrasonic experiments
increased to a mean of 24.1
×
10
6µ
m
3
/mL (calculated from values 120–180 min) with rel. SD of 3.2%,
whereas the total theoretical suspended volume of the PS is 19.6
×
10
6µ
m
3
/mL. E
D
calculated with
the mean volume of 120–180 min was therefore 127%, which indicates that calculation of the volume
overestimated the volume in dispersion.
Water 2020, 12, x FOR PEER REVIEW 7 of 12
For sonication the first minutes of ultrasonic treatment sufficed to increase numbers of dispersed 231
particles and greatly change particle composition (Figure 4 (b), data shown for batch A). Particle 232
numbers of the fractions 5-10 µm and >10 µm did not further increase after 90 minutes of ultrasonic 233
treatment whereas a slight increase for the fraction <5 µm was observed. 234
235
Before ultrasonic treatment, the size fractions <5 µm, 5-10 µm and >10 µm made up 66.5%, 18.6% 236
and 14.8% of all particles, respectively. After 30 minutes the size fraction ratios changed to 78.1%, 237
15.2% and 6.7% for <5 µm, 5-10 µm and >10 µm, respectively. Subsequent ultrasonic treatment 238
increased the number of particles but only led to minor changes in the size composition. The size 239
fractions after 180 minutes ultrasonic were 82.5%, 12.5% and 5.0% for <5 µm, 5-10 µm and >10 µm, 240
respectively. In terms of dispersion characterization, horizontal shaking and sonication lead to a 241
similar dispersion composition (see Figure 4 (a) and (b)). The initial increase in particle concentrations 242
was caused by deagglomeration of larger particles with weak coherence and the number of particles 243
of fraction <5 µm increased whereas particle numbers of the two larger fractions decreased with 244
increasing treatment time. Further disintegration of larger particles or agglomerates could not be 245
shown since the number of larger particles/agglomerates (fraction >10 µm) remained constant. This 246
is in accordance to Meissner et al. [31] who reported no further deagglomeration/disintegration 247
visible after thorough sonication of carbide nanoparticles. 248
3.5 Changes in calculated volume distribution during ultrasonic treatment 249
As additional criteria for dispersion efficiency, suspended solid volumes were calculated from 250
particle numbers of each measurement channel. After 90 minutes of sonification the calculated 251
volume did not further increase (Figure 5 (a)). However, values from 90-180 minutes scattered due 252
to few larger particles still present in the batch which greatly affected the total calculated volume 253
(which can also be seen in Figure 6). The calculated particle volume of sonicated samples from 254
ultrasonic experiments increased to a mean of 24.1·106 µm3/mL (calculated from values 120-180 min) 255
with rel. SD of 3.2% whereas the total theoretical suspended volume of the PS is 19.6·106 µm3/mL. ED 256
calculated with the mean volume of 120-180 minutes was therefore 127% which indicates that 257
calculation of the volume overestimated the volume in dispersion. 258
259
Figure 5: (a) Calculated suspended solid volume of six batches (A-F = 20 mg/L PS particles) during 260
ultrasonic treatment (UT). Dotted line at 19,048,000 µm3/mL indicates an ED of 100%. Highlighted area 261
was used for calculation of mean volume and ED. (b) Calculated volume per size channel of batch A 262
during 180 min of ultrasonic treatment. Values were normalized through division by channel width 263
Figure 5.
(
a
) Calculated suspended solid volume of six batches (A–F =20 mg/L PS particles) during
ultrasonic treatment (UT). Dotted line at 19,048,000
µ
m
3
/mL indicates an E
D
of 100%. Highlighted area
was used for calculation of mean volume and E
D
. (
b
) Calculated volume per size channel of batch A
during 180 min of ultrasonic treatment. Values were normalized through division by channel width
to compare smaller and larger channels. A non-normalized graph can be found in the SI, Figure S2.
Error bars show standard deviation of n=3.
Water 2020,12, 3436 8 of 12
Water 2020, 12, x FOR PEER REVIEW 8 of 12
to compare smaller and larger channels. A non-normalized graph can be found in the SI, Figure 2. 264
Error bars show standard deviation of n = 3. 265
To identify the cause of the increase in total suspended solid volume, the contributing volume 266
of each measurement channel is shown in Figure 5 (b). All channels up to 50 µm contribute to the 267
increase in total volume of 180 minutes of ultrasonic compared to the distribution after 15 minutes of 268
ultrasonic. A decrease in the volumes of particles >50 µm can be noted with prolonged treatment (see 269
inset diagram). Since total volume of particles <50 µm increased it can be concluded that breakdown 270
of larger particles occurred mostly for particles >50 µm. 271
272
To further elucidate the changes in volume Figure 6 shows the volume of batch A during 273
ultrasonic treatment of 180 min grouped in three size fractions <10 µm, 10-50 µm and >50 µm. The 274
untreated sample had a low initial volume which increased with further treatment. The fractions 275
<10 µm and 10-50 µm increased from 1.6% and 27.4% of total volume to a share of 13.3% and 63.4%, 276
respectively, whereas the fraction >50 µm decreased from 70.9% to 23.3% as was mentioned before. 277
Size fraction <10 µm remained relatively constant after 60 min of treatment, size fraction 10-50 µm 278
remained constant after 105 minutes. The volume of particles >50 µm, however, showed strong 279
fluctuation over the whole treatment duration. These larger particles/agglomerates were not 280
disintegrated with ultrasonic and explain the fluctuations in total calculated volume. 281
282
Figure 6: Calculated volume of batch A during ultrasonic treatment. Particles were grouped in size 283
fractions <10 µm, 10-50 µm and >50 µm (please note: different fractions were chosen for volume 284
fractions compared to number fractions). Error bars show standard deviation of n = 3. 285
3.6 Settling of particles after ultrasonic treatment 286
Small particles of a fully dispersed solution should follow Stoke’s law for settling and not re-287
agglomerate over time. Therefore, the settling behaviour of a dispersion (20 mg/L PS particles, 288
180 min sonicated) was monitored for one week (SI, Figure 3). Particle concentration decreased from 289
173,000/ml to 124,000/mL over 168 hours (= 30 % decrease). Settling was the main process of particle 290
loss and as expected, larger particles >10 µm settled faster and were not present in the dispersion 291
anymore after 168 hours (SI, Figure 4). Interestingly, particles of 3 µm diameter or larger should have 292
settled after this time according to Stoke’s law, however, still 20% of all particles were of this size 293
category (data not shown). No agglomeration could be monitored since volume of all size fractions 294
decreased over time (SI, Figure 5). 295
3.7 Environmental implications 296
Figure 6.
Calculated volume of batch A during ultrasonic treatment. Particles were grouped in size
fractions <10, 10–50, and >50
µ
m (please note: different fractions were chosen for volume fractions
compared to number fractions). Error bars show standard deviation of n=3.
To identify the cause of the increase in total suspended solid volume, the contributing volume
of each measurement channel is shown in Figure 5b. All channels up to 50
µ
m contribute to the
increase in total volume of 180 min of ultrasonic compared to the distribution after 15 min of ultrasonic
treatment. A decrease in the volumes of particles >50
µ
m can be noted with prolonged treatment (see
inset diagram). Since total volume of particles <50
µ
m increased it can be concluded that breakdown
of larger particles occurred mostly for particles >50 µm.
To further elucidate the changes in volume, Figure 6shows the volume of batch A during ultrasonic
treatment of 180 min grouped into three size fractions, <10, 10–50, and >50
µ
m. The untreated sample
had a low initial volume which increased with further treatment. The fractions <10 and 10–50
µ
m
increased from 1.6% and 27.4% of the total volume to a share of 13.3% and 63.4%, respectively,
whereas the fraction >50
µ
m decreased from 70.9% to 23.3%, as was mentioned before. Size fraction
<10
µ
m remained relatively constant after 60 min of treatment, and size fraction 10–50
µ
m remained
constant after 105 min. The volume of particles >50
µ
m, however, showed strong fluctuation over the
whole treatment duration. These larger particles/agglomerates were not disintegrated with ultrasonic
treatment, explaining the fluctuations in total calculated volume.
3.6. Settling of Particles after Ultrasonic Treatment
Small particles of a fully dispersed solution should follow Stoke’s law for settling and not
re-agglomerate over time. Therefore, the settling behavior of a dispersion (20 mg/L PS particles,
180 min sonicated) was monitored for one week (SI, Figure S3). Particle concentration decreased from
173,000 1/mL to 124,000 1/mL over 168 h (=30% decrease). Settling was the main process of particle loss
and, as expected, larger particles >10
µ
m settled faster and were not present in the dispersion anymore
after 168 h (SI, Figure S4). Interestingly, particles of 3 µm diameter or larger should have settled after
this time according to Stoke’s law—however, still 20% of all particles were of this size category (data
not shown). No agglomeration could be monitored since volume of all size fractions decreased over
time (SI, Figure S5).
3.7. Environmental Implications
Virgin PS particles are hydrophobic and do not independently disperse in water. The experiments
showed that an enormous energy input is needed to fully disperse virgin PS particles if no other processes
such as biofilm formation, adsorption of organic matter or weathering are involved. Through this
Water 2020,12, 3436 9 of 12
energy input, larger agglomerates broke up into smaller particles and the average particle size decreased.
Particles were stabilized for more than 168 h and a fraction of particles between 3 and 10
µ
m did not
settle, contrary to calculations with Stoke’s law.
4. Discussion
The aim of this study was to evaluate an additive-free method to disperse model MP particles
in water to realistically depict concentration-effect relations of MP particles. Primary MP particles
released into the environment most likely start out as a hardly dispersible material, as with the model
particles used in this study, and the dispersion of these is still unknown. Therefore, the preparation of
these virgin MP particle dispersions for laboratory studies is important to understand the behavior
and fate of virgin MP particles in the environment. Using ultrasonic pre-treatment for cryomilled
pristine polystyrene particles, reproducible dispersions of 20 mg suspended solid per liter were
obtained. The physical particle interactions induced by the ultrasonic bath after 90 min effectively
dispersed particles, while no substantial increase in dispersed particle numbers was observed with
longer treatment. With further sonication, the number of particles >50
µ
m fluctuated while particle
numbers <50
µ
m remained constant, showing that ultrasonic treatment did not further disintegrate PS
particles. Ultrasonic treatment as a dispersion technique thus increased the numbers of particles in the
dispersion and ensured the availability of particles for possible interaction. After 24 h, around 70% of
the particles of a dispersion (180 min of ultrasonic treatment) were still in dispersion.
In contrast to ultrasonic treatment, long-term horizontal shaking and manual shaking did not
suffice for fully dispersing all particles. Dispersion efficiency was 127%, 104%, and 69% for ultrasonic
treatment (180 min), long-term horizontal shaking (754 h) and manual shaking (250 agitations),
respectively. This is in accordance with a similar study implementing nanosized silica and alumina
particles in which ultrasonic homogenization as well as stirred media milling proved most effective for
deagglomeration [
32
]. E
D
values of above 100% indicated that the presumption of spherical shape
for cryogenically produced particles is a simplification, as cryomilled particles are more shard-like
fragments [
5
]. This overestimated the calculated volume of measured particles when using the
Feret diameter given by the particle counter, which was only partly counteracted by using the lower
boundaries of the measurement channels.
Using alkaline ultrasonic treatment van der Esch et al. [
3
] reported stable dispersions with aged
MP but with a high variability (1,5 log-orders) in particle concentrations. For PS, the toxicologically
interesting fraction <20
µ
m ranged from 40 to 80% within three replicates. This emphasizes the
need for appropriate production of particles and pre-treatment for dispersions. Chung et al. [
30
]
reported a maximum dispersing effect after 20–30 min for zinc oxide nanoparticles using ultrasonic
baths. Although the materials and therefore binding forces are not directly comparable, a maximum
was also found in this study for ultrasonic dispersion after 90 min. Treatment times can possibly be
shortened by using a higher input power; however, the potentially achievable deagglomeration is
a function of output power of the ultrasonic device and two different ultrasonic devices need to be
cautiously compared.
Van der Esch [
3
] reported eroded surfaces on 1 cm
2
polystyrene squares cut from larger sheets and
additional FTIR-bands mimicking weathering processes in the environment. We did not investigate
changes in the morphology through radical attack during sonification. Such changes were not expected
since the duration of ultrasonic treatment was much shorter (180 min compared to 15 h) and pH
(unbuffered) was around 5.5 (van der Esch: pH =13). Therefore, surface oxidation during sonication
in this study is unlikely. Nevertheless, it needs to be discussed whether polymers pre-treated in an
ultrasonic bath even for short periods can still be regarded as pristine if the surface of particles is
potentially altered.
Another challenge in dispersion preparation is the weighing-in: a precise execution is difficult
due to fine powder in the
µ
m area, low density materials and potential electrostatic forces. Air drafts
and charged surfaces of laboratory equipment can easily carry away the finer fraction of polydisperse
Water 2020,12, 3436 10 of 12
powders. The particle concentration of six batches of identical weight-in particles still showed
a rel. SD of 3.5% after 180 min of ultrasonic treatment. We therefore suggest preparing a more
concentrated dispersion which has to be thoroughly treated with ultrasound before further dilution to
targeted concentrations.
Concerning the stability of dispersions, no agglomeration behavior could be observed in a
dispersion after 168 h. This was expected since larger particles settled quickly while smaller
particles apparently remained as single particles in dispersion. Settling could have been disturbed
by the high number of particles in dispersion, this would explain particles of the size 3–10
µ
m
still present in the water column after 168 h. The settling of irregularly shaped particles does not
necessarily follow Stoke’s law applied on spherically shaped objects, as is the case for natural colloid
aggregates [
33
]. Ultrasound treatment is therefore suitable for pre-treatment of PS particle dispersions
for eco-toxicological studies since the stabilized particles are available for possible ingestion by aquatic
species. Nevertheless, the results point out the reluctance of microplastic particles to behave as
predicted by models—in laboratory studies as well as in environmental sampling.
Delmas and Barthe [
34
] claimed that addition of surfactant for stabilization is still required after
the use of ultrasound to stop agglomeration; however, this type of interparticle bonding is weaker
after ultrasonic treatment rendering the use of surfactant more effective. Whether the use of surfactant
is still required needs to be decided depending on the experiment. The time-dependent stability of
dispersions (the tendency to agglomerate) has to be evaluated individually for each experimental
setup since particle size and surface chemistry are key factors in agglomeration processes. This is
an important issue for toxicological studies as well as the transport behavior of particles during
experiments. Regarding a potential stability of over 168 h through ultrasonic treatment, we do not
suggest the use of surfactants for microplastic experiments due to possible side-effects, as stated above
by some other authors.
In the environment, the dispersion of virgin MP particles through energy input could be achieved
by strong currents and turbulence in rivers and other surface waters. Other processes influencing the
stabilization of virgin MP particles in natural environment include biofilm formation, adsorption of
organic substances and weathering. Once stabilized, these particles are mobile and do not necessarily
settle according to model calculations. As a consequence, MP particles are found throughout the water
column and not only in the sediment, aggravating possible remediation techniques. The removal
of virgin MP in wastewater treatment plants thus seems to depend on inclusion in flocs or foams.
Further research needs to focus on the concurrence of environmental processes contributing to the
stabilization of virgin MP particles and the resulting behavior in water to evaluate target-oriented
measures to remove MP particles from the environment.
This study provides valuable insights for research groups working with model suspensions.
Basic understanding of the behavior of model particles in aqueous suspensions is one of the
pre-requisites for systematic research and the transfer of laboratory investigations to environmental
research outcomes.
Supplementary Materials:
The following are available online at http://www.mdpi.com/2073-4441/12/12/3436/s1,
Figure S1: Calculated volume of six batches (A–F) of 20 mg/L polystyrene particles during ultrasonic treatment.
Batches were repeatedly placed for 15 min in ultrasonic bath and particle numbers measured through light
extinction; Figure S2. Calculated volume per size channel of batch ‘A’ during 180 min of ultrasonic treatment.
Values were non-normalized compared to Figure 5b; Figure S3. Particle settling of a 20 mg/L polystyrene dispersion
which was left to settle for one week and only moved for measuring purpose. Inlay shows particle concentration
during the first two hours. Dispersion was prepared with 180 min of ultrasonic treatment. Sample was measured
in triplicate; Figure S4. Size fractions of long-term particle settling dispersion (20 mg/L polystyrene) with 180 min
of ultrasonic treatment. Sample was measured in triplicate; Figure S5. Calculated volume of a long-term particle
settling dispersion (20 mg/L polystyrene) up to 180 min of ultrasonic treatment. Sample was measured in triplicate.
Author Contributions:
The article was written by L.E. within his project, with supervision by A.S.R. and M.J.
All authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Water 2020,12, 3436 11 of 12
Acknowledgments:
We acknowledge support by the German Research Foundation and the Open Access
Publication Fund of TU Berlin.
Conflicts of Interest:
The authors declare no conflict of interest. The funders had no role in the design of the
study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to
publish the results.
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