Sanne J Smith1, Karin Wiberg1, Philip McCleaf2, Lutz Ahrens1. 1. Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences (SLU), P.O. Box 7050, SE-750 07 Uppsala, Sweden. 2. Uppsala Water and Waste AB, P.O. Box 1444, SE-751 44 Uppsala, Sweden.
Abstract
Per- and polyfluoroalkyl substances (PFAS) are of concern for their ubiquity in the environment combined with their persistent, bioaccumulative, and toxic properties. Landfill leachate is often contaminated with these chemicals, and therefore, the development of cost-efficient water treatment technologies is urgently needed. The present study investigated the applicability of a pilot-scale foam fractionation setup for the removal of PFAS from natural landfill leachate in a novel continuous operating mode. A benchmark batch test was also performed to compare treatment efficiency. The ΣPFAS removal efficiency plateaued around 60% and was shown to decrease for the investigated process variables air flow rate (Q air), collected foam fraction (%foam) and contact time in the column (t c). For individual long-chain PFAS, removal efficiencies above 90% were obtained, whereas the removal for certain short-chain PFAS was low (<30%). Differences in treatment efficiency between enriching mode versus stripping mode as well as between continuous versus batch mode were negligible. Taken together, these findings suggest that continuous foam fractionation is a highly applicable treatment technology for PFAS contaminated water. Coupling the proposed cost- and energy-efficient foam fractionation pretreatment to an energy-intensive degradative technology for the concentrated foam establishes a promising strategy for on-site PFAS remediation.
Per- and polyfluoroalkyl substances (PFAS) are of concern for their ubiquity in the environment combined with their persistent, bioaccumulative, and toxic properties. Landfill leachate is often contaminated with these chemicals, and therefore, the development of cost-efficient water treatment technologies is urgently needed. The present study investigated the applicability of a pilot-scale foam fractionation setup for the removal of PFAS from natural landfill leachate in a novel continuous operating mode. A benchmark batch test was also performed to compare treatment efficiency. The ΣPFAS removal efficiency plateaued around 60% and was shown to decrease for the investigated process variables air flow rate (Q air), collected foam fraction (%foam) and contact time in the column (t c). For individual long-chain PFAS, removal efficiencies above 90% were obtained, whereas the removal for certain short-chain PFAS was low (<30%). Differences in treatment efficiency between enriching mode versus stripping mode as well as between continuous versus batch mode were negligible. Taken together, these findings suggest that continuous foam fractionation is a highly applicable treatment technology for PFAS contaminated water. Coupling the proposed cost- and energy-efficient foam fractionation pretreatment to an energy-intensive degradative technology for the concentrated foam establishes a promising strategy for on-site PFAS remediation.
Per-
and polyfluoroalkyl substances (PFAS) are a class of persistent,
bioaccumulative, and toxic chemicals that have become widespread in
the environment.[1] They are used in consumer
products, industrial applications, and firefighting foams for their
high water and oil resistance, as well as for their surfactant properties.[2−4] An increasing amount of research continues to show their extensive
prevalence in the environment as well as their toxicity to both humans
and animals.[5,6] The most well-known class of PFAS
are the perfluoroalkyl acids (PFAA), which encompass the perfluoroalkyl
carboxylates (PFCA) and perfluoroalkanesulfonates (PFSA).[7] These types of PFAS are commonly used as surfactants
and can also be classified on the basis of the length of their hydrophobic
perfluoroalkyl tail, with a total perfluorocarbon chain length below
six for PFSA and seven for PFAA generally being considered short-chained
(PFSA: CF2SO3H, n ≤ 5; PFCA: CF2COOH, n ≤ 6).[7,8]Point sources of contaminated
water are an important contributor
to the origin of PFAS in the environment,[2] implying that further pollution can be partially prevented by installing
appropriate treatment technologies. Examples of such point sources
include discharged leachate water from landfills, with total aqueous
concentrations ranging from 100 to >100 000 ng L–1.[2,9,10] PFAS in landfills originate
from discarded consumer and industrial waste or PFAS-contaminated
biosolids. Moreover, landfilled bottom ash from waste incinerators
may still contain incompletely combusted PFAS. Biological leaching
and physicochemical desorption of these PFAS result in their release
to the landfill leachate, leading to high aqueous PFAS concentrations.[9,11] Although the production and use of increasingly many PFAS are banned
or restricted,[12,13] landfills store previously produced
waste over large timespans; hence, PFAS release from landfills is
expected to remain a problem for the foreseeable future.[11]With PFAS under widespread international
scrutiny, limit values
for discharge to the environment are becoming more stringent. In 2020,
the European Food Safety Authority (EFSA) introduced a tolerably weekly
intake of 4.4 ng of perfluorohexanesulfonic acid (PFHxS), perfluorooctanesulfonic
acid (PFOS), perfluorooctanoic acid (PFOA), and perfluorononanoic
acid (PFNA) per kilogram body weight per week.[14] Consequently, to protect drinking water sources, many countries
are starting to define concentration limits in environmental waters
and hence enforcing treatment of contaminated effluents.[15−17] Common wastewater treatment technologies, such as activated sludge
or coagulation, are ineffective toward the removal of most PFAS.[18,19] The current state of the art for PFAS removal from water is adsorption
to granular activated carbon (GAC),[20] but
GAC needs to be regenerated often, is sensitive to matrix effects,
and is less effective in the removal of short-chained PFAS.[21,22] Hence, the development of alternative methods for the treatment
of PFAS contaminated water is urgently needed.Treatment methodologies
can be broadly divided into removal and
degradation techniques. Where removal technologies aim to concentrate
PFAS into a waste fraction that is sent to further treatment, degradation
technologies aim to mineralize the PFAS.[23] Examples of removal methods include adsorption, membrane filtration,
reverse osmosis, and ion exchange.[20,24−29] Degradation methods include electrochemical oxidation, ultrasonication,
advanced reduction processes, plasma treatment, and biological treatment.[20,24−31] Degradation methods have the obvious advantage that the PFAS are
destroyed rather than concentrated, but the formation of persistent
transformation products can be an issue.[31] Combining multiple removal and degradation approaches into a treatment
train process is generally considered the most promising approach
for future on-site PFAS remediation.[23]A removal method that could be highly suitable as a first step
in such a treatment train process is foam fractionation, which exploits
the surfactant properties of common PFAS and has been applied successfully
in full scale for the remediation of PFAS-contaminated groundwater.[32−34] In foam fractionation, PFAS are adsorbed on the surface of gas bubbles
rising through water. At the air–water interface, these bubbles
form a foam that is enriched in PFAS, so separation and collapse of
the foam results in a concentrated foamate and a relatively PFAS-free
retentate.[35] The process can be carried
out in both batch and continuous operation. In continuous operation,
stripping mode refers to operation with the liquid feed stream located
above the liquid surface, whereas the feed enters below the foam/water
interface in enriching mode.[35,36]Foam fractionation
is a suitable water treatment technology for
dilute solutions using only air, thereby eliminating the need for
chemicals, solvents, filter material, and adsorbents.[37] Leachate water is a particularly complex matrix to treat,
requiring extensive pretreatment before conventional PFAS treatment,
such as GAC, ion exchange, or membrane filtration, can be applied
successfully.[29] These matrix effects are
less problematic in the case of foam fractionation due to a beneficial
effect of high ionic strength on the process performance and no risks
of clogging or fouling of filter or membrane materials.[3,38,39] Hence, foam fractionation has
received increasing attention as a successful technology for PFAS
removal from landfill leachate.[36,40,41] However, its applicability is not limited to leachate water but
extends to PFAS-contaminated groundwater, process water, and wastewater.[33,34,36,40,42]An important limitation of foam fractionation
is the low removal
efficiency of short-chain PFAS.[3,33,38,40−42] Metal cation
activators can be used to increase the removal, but this effect has
not been shown for short-chain substances.[38,40,43] ΣPFAS removal has further been shown
to increase for increasing aeration time,[3,38,40,42] gas flow rate,[3,32,33,40] and ionic strength[3,38,42] and for decreasing initial PFAS concentration.[3,42,43] However, for low initial PFAS concentrations
(<50 ng L–1), removal was instead observed to
increase at increasing concentration for a wide range of compounds.[40] The effect of pH is ambiguous, with some studies
reporting more efficient treatment at low pH,[43] others at intermediate pH,[3] and others
at high pH.[32] Most probably, this is because
other operating conditions are more influential than pH. Finally,
the PFAS concentration in the foam has been shown to depend on the
collected foam volume.[3,41]Reported removal efficiencies
strongly depend on the types of PFAS
and water matrices under investigation but generally range between
0 and <50% for short-chain PFCA,[33,34,38,40−42] while for long-chain PFAS, efficiencies can reach up to >99%.[3,34,38,40−43] Most work on PFAS removal with foam fractionation has been done
in batch mode, with easy control of contact time and effluent quality.[3,32,40−43] However, recent exploratory work
by McCleaf et al.[40] has indicated that
similar removal efficiencies can be reached in continuous operation,
which comes with operational advantages in larger scale applications,
but until now no pilot-scale results have been presented in academic
literature.The present study aimed to assess the effect of
operational parameters
on PFAS removal from landfill leachate with continuous pilot-scale
foam fractionation. The specific objectives were to (i) determine
the effectiveness of this technology in a continuous setup, (ii) for
the first time, systematically evaluate the effect of different operating
parameters on this continuous pilot scale process, and (iii) test
real landfill leachate on-site and thereby avoid effects of sedimentation
and chemical or microbiological changes during transport. The findings
advance the understanding of the opportunities provided by the use
of foam fractionation for PFAS removal from contaminated water.
Materials and Methods
Treatment setup
A 19 cm diameter
polypropylene (PP) column was used for all experiments with the water
surface at 1.63 m height above the column bottom. Leachate water from
the Hovgården landfill in Uppsala, Sweden was collected in real
time from the inflow to the on-site water treatment plant. The influent
vessel (PP, 300 L) was mixed by the inflow of leachate. All leachate
originated from the same pumping station, thus excluding leachate
from an area of the landfill where sludge from a municipal wastewater
treatment plant is stored. All tests were done on days with similar
weather profiles to exclude effects due to fluctuations in water quality
as much as possible. A peristaltic pump with variable flow rate (Watson
Marlow, 630SN/RE with Pureweld Xl 12.7 mm tubing) supplied a steady
leachate flow to the column. The leachate entered the column under
the water surface in enriching mode, at a height of 1.43 m above the
column bottom (Figure ). In stripping mode, the influent entered above the water surface
at a height of 1.83 m above the column bottom. All experiments were
done at room temperature.
Figure 1
Process flow diagram of the continuous foam
fractionation treatment.
Column ø: 19 cm, water surface 1.63 m above column bottom. The
height of the effluent hose was adaptable, which was used to control
the foam and effluent flow rates. In enriching mode, the influent
entered the column below the water surface (solid line). In stripping
mode, the influent entered above the water surface (dotted line).
Process flow diagram of the continuous foam
fractionation treatment.
Column ø: 19 cm, water surface 1.63 m above column bottom. The
height of the effluent hose was adaptable, which was used to control
the foam and effluent flow rates. In enriching mode, the influent
entered the column below the water surface (solid line). In stripping
mode, the influent entered above the water surface (dotted line).Air was dispersed at the bottom of the column using
four brass
diffusers, each with 18 mm diameter and 30 mm length, attached to
a stainless steel manifold. The airflow was controlled with a rotameter
(0–20 L min–1, ZYIA instrument company, FL3-1).
The column top was sealed and nearly airtight so all inlet air exited
the column at the foam exit surface, carrying with it foam accumulated
at the water surface. The foam collection was optimized by changing
the height of the effluent outlet, thereby controlling the effluent
flow as well. The foam flow was measured at least every 30 min with
a PP volumetric flask. A process overview of the treatment setup is
given in Figure .The independent variables in all experiments were contact time
(tc, min), air flow (Qair, L min–1), and foam fraction (%foam, %). The tc was assessed at
both constant Qair and at constant air-to-feed
ratio (AR). The tc and AR were not entirely
independent, since both are functions of the water flow rate (QW), as given in eqs and 2, with Vcolumn as the water volume in the column. The
foam fraction was defined as in eq , with QF as the foam flow
(L min–1).
Experimental
Approach
To confirm
the independence of sampling time on the removal in continuous operation
shown by McCleaf et al.,[40] a 30 min continuous
initial experiment was performed in triplicate at 10 min tc, 10 L min–1Qair, and 30% foam. In these tests, approximately 250 mL of
influent from the influent vessel was collected in clean PP bottles
initially, 150 mL of foam and 250 mL of effluent were sampled after
both 15 and 30 min treatment time from their respective exit hoses
(without the use of a vacuum pump), and 250 mL of water from directly
under the air/water interface was sampled after 30 min with a vacuum
pump (GAST, DOA-P704-AA) connected to a PVC hose that was inserted
approximately 5 cm below the water surface.In this initial
experiment, no significant differences between the effluent at 15
min and the effluent at 30 min were found in the concentrations of
individual compounds as well as groups (paired t test,
all p > 0.05). Detailed results, including the
difference
between sampling the effluent from the bottom as compared to the top
of the column, are given in the Supporting Information (SI) Section A (Figure S1). On the basis of this stability
in effluent over time, all subsequent continuous experiments (Table , all except Exp.
0 and 15) were run once for a total duration of 2 h, with replicate
influent, effluent, and foam samples taken at four different time
points (30, 60, 90, and 120 min) instead of in experimental triplicates.
Approximately 250 mL of influent and effluent and 150 mL of foam were
collected in clean PP bottles at each sampling time point. Average
influent, effluent, and foam concentrations were calculated from the
four different samples per type for each experiment to assess the
effects of tc, Qair and %foam. A detailed overview of all experiments
is given in Table , and the dates on which the experiments were performed are given
in Table S1.
Table 1
Overview
of All Experimentsa
Exp.
contact time
(min)
air flow (L min–1)
targeted
foam fraction (%)
water flow rate in (L min–1)
foam flow rate (L min–1)
effluent flow rate (L min–1)
air ratio
operating mode
0
10
10
30
4.6
0.46
4.2
2.2
enriching
1
10
20
10
4.6
0.46
4.2
4.3
enriching
2
30
6.7
10
1.5
0.15
1.4
4.3
enriching
3
10
20
10
4.6
0.46
4.2
4.3
stripping
4
30
13
20
1.5
0.31
1.2
8.7
stripping
5
30
13
20
1.5
0.31
1.2
8.7
enriching
6
20
20
10
2.3
0.23
2.1
8.7
enriching
7
20
10
10
2.3
0.23
2.1
4.3
enriching
8
20
10
20
2.3
0.46
1.8
4.3
enriching
9
20
10
30
2.3
0.69
1.6
4.3
enriching
10
20
5.0
20
2.3
0.46
1.8
2.2
enriching
11
20
20
20
2.3
0.46
1.8
8.7
enriching
12
30
20
10
1.5
0.15
1.4
13
enriching
13
15
13
10
3.1
0.31
2.8
4.3
enriching
14
20
10
5
2.3
0.12
2.2
4.3
enriching
15
20
20
3
batch mode - not
applicable
16
15
20
10
3.1
0.31
2.8
6.5
enriching
17
20
7.5
20
2.3
0.46
1.8
3.2
enriching
See Figure for the difference
between stripping and
enriching modes.
See Figure for the difference
between stripping and
enriching modes.Additionally,
a set of triplicate batch experiments was carried
out (Table , Exp.
15) to investigate the difference between continuous and batch operation.
Here, the column was filled up to 1.57 m height and an air flow of
20 L/min was applied for 20 min contact time. During the first 15
min, foam collection was identical to the continuous tests, but during
the final 5 min, foam was also collected with a vacuum pump to increase
the collected foam fraction. Effluent samples were taken from sampling
points on both the bottom and the top of the column, to compare the
effect of sampling height.
PFAS Analysis
In total, 29 PFAS were
included in analytical method, namely, 11 PFCA (PFBA, PFPeA, PFHxA,
PFHpA, PFOA, PFNA, PFDA, PFUnDA, PFDoDA, PFTriDA, PFTeDA), 7 PFSA
(PFBS, PFPeS, PFHxS, PFHpS, PFOS, PFNS, PFDS), 3 fluorotelomer sulfonates
(4:2 FTSA, 6:2 FTSA, 8:2 FTSA), the two components of F-53B (9Cl-PF3ONS
and 11Cl-PF3OUdS),[44] HFPO-DA (trade name
GenX), FOSA, MeFOSAA, EtFOSAA, NaDONA, and PFECHS. Twenty mass-labeled
internal standards (IS) were used, which were spiked to the samples
before extraction (Wellington Laboratories, MPFAC-24ES mixture with 13C3-HFPO-DA added individually): 13C4-PFBA, 13C5-PFPeA, 13C5-PFHxA, 13C4-PFHpA, 13C8-PFOA, 13C9-PFNA, 13C6-PFDA, 13C7-PFUnDA, 13C3-PFDoDA, 13C2-PFTeDA, 13C3-PFBS, 13C3-PFHxS, 13C8-PFOS, 13C2-4:2 FTSA, 13C2-6:2 FTSA, 13C2-8:2 FTSA, 13C3-HFPO-DA, 13C8-FOSA, D3-MeFOSAA, and D5-EtFOSAA (for full names and other details
of the native PFAS and IS see Tables S3 and S4).The collected samples were filtered through glass microfiber
filters (47 mm diameter, Whatman, China), weighed, and subsequently
analyzed for PFAS concentration using solid phase extraction (SPE)
followed by ultraperformance liquid chromatography tandem mass-spectrometry
(UPLC–MS/MS) analysis. The SPE method has been described previously[22,45] (see also Section C in the Supporting Information).A SCIEX Triple Quad 3500 UPLC–MS/MS system was used
for
PFAS analysis. Twenty microliters of extract was injected on a Phenomenex
Gemini 1.7 μm C18 HPLC column with a Phenomenex KJ0-4282 analytical
guard column and a Phenomenex Kinetix 1.7 μm C18 precolumn,
all at 40 °C. A gradient of 0.6 mL/min 10 mM ammonium acetate
in Milli-Q water and methanol was used for a total duration of 9 min
per run. The initial gradient was set to 5% methanol, which was increased
to 55% within the first 0.1 min. Then, it was further increased to
99% over 4.4 min, held there for 3.5 min, after which it was decreased
again to 5% over 0.5 min and held there for another 0.5 min. The MS/MS
was operated in scheduled multiple reaction monitoring (MRM) mode
with negative electrospray ionization. For compounds with branched
as well as linear isomers, only summed concentrations were reported.
Details and quality control data on the analytical method are given
in Tables S2–S4 in the SI Section C.
General Chemistry Analysis
For one
continuous experiment and the batch experiment, 1 L influent, effluent,
and foam samples were taken and shipped to ALS Scandinavian, Stockholm,
Sweden for general chemistry analysis. For the preliminary triplicate
continuous experiment and another continuous experiment, only influent
and effluent were sampled and analyzed. The parameters were included
in the analysis, and the results are given in Table S5.
Data Treatment
For each continuous
test, mean concentrations of the four collected influent, effluent,
and foam samples were calculated. The removal efficiency (RE) was
calculated as in eq , with the standard deviation (σRE) calculated as
in eq . Here, CEF, CIN, σEF, and σIN refer to the effluent and influent
mean PFAS concentrations and corresponding standard deviations, respectively.
The removal efficiency as a function of the independent variables
(x) was fitted to eq using the unweighted fit function
in Matlab (version R2017B), with k and REMax as dependent empirical variables. This equation was selected because
it converges to a horizontal asymptote and proved suitable for fitting
the data, but other equations may be appropriate as well.For PFCA and PFSA, the mean
RE as a
function of perfluoroalkyl chain length (Nc) was fitted to eq , with a as the dependent empirical variable. Furthermore,
a mass balance (MB) and its corresponding standard deviation (σMB) were calculated for each experiment as per eqs and 9, respectively,
with CFoam the mean concentration in the
foam and σFoam the corresponding standard deviation.
All statistical analyses, curve fitting, and plotting were done in
Matlab, version R2017b.Values below the limit of quantification were taken as zero,
which
is acknowledged to introduce an error. However, substituting a fraction
of the detection limit is known to introduce an equal level of inaccuracy.[46] In all analyzed samples, the highest possible
concentration of nondetect PFAS would contribute at most 0.4% to the
ΣPFAS concentration (see SI Section C for details). This fraction was deemed negligible; hence, nondetect
concentrations were set to zero. Some samples were contaminated or
lost during the analysis, in which case the results were based on
the remaining three samples. An overview of all tests for which samples
were excluded is given in Table S6.
Results and Discussion
Leachate Characteristics
The average
ΣPFAS concentration in the influent leachate was 2400 ±
400 ng L–1. Because the untreated leachate was collected
from the influent of an operating treatment plant and the tests were
carried out over different days, this level of variability falls within
the expectations. The influent ΣPFAS consisted of 46 ±
10% short-chain PFCA, 27 ± 6% long-chain PFCA, 7 ± 1% short-chain
PFSA, 15 ± 3% long-chain PFSA, and 4 ± 1% other types of
PFAS (for details on the PFAS classification see Table S7). The influent ΣPFAS concentration was not
found to affect the removal efficiency (Pearson’s r = −0.23 (95% CI: −0.71–0.40), p > 0.05). Of all PFAS included in the analysis, a statistically
significant
correlation between RE and influent concentration was only found for
PFECHS, with the RE increasing at higher influent concentrations (Pearson’s r = 0.74 (95% CI: 0.28–0.92), p <
0.05). All PFAS included in the method were detected in at least one
of the samples.For leachate samples taken on testing dates,
average influent dissolved organic carbon (DOC), conductivity, ammonium,
and bicarbonate alkalinity were 36 mg L–1, 440 mS
m–1, 59 mg L–1, and 1300 mg L–1, respectively. A selective overview of the mean general
chemistry characteristics of the influent, effluent, and foam is given
in Table , with the
complete data set given in Table S5. DOC,
iron, and aluminum were enriched in the foam, but otherwise no effects
of the treatment on the general chemistry were found. Samples were
not taken for each test, but the leachate composition from this pumping
station at Hovgården is known to be very stable in terms of general
chemistry characteristics. On the basis of 15 regularly distributed
measurements in 2021, relative variations of the mean iron concentration
(5.7 mg L–1), conductivity (510 mS m–1), pH (7.6), and total organic carbon (43 mg L–1) were only 15, 11, 3, and 10%, respectively.
Table 2
Overview of General Chemistry Dataa
influent (n = 4)
effluent (n = 4)
foam (n = 2)
DOC (mg L–1)
36
36
45
phosphor (μg L–1)
140
120
190
calcium (mg L–1)
150
150
150
manganese (μgL-1)
520
530
610
sodium (mg L–1)
710
710
740
potassium (mg L–1)
240
240
260
iron (mg L–1)
5.3
4.8
9.7
aluminum (μg L–1)
27
25
44
copper (μg L–1)
54
28
77
magnesium (mg L–1)
56
57
60
COD-Mn (mg L–1)
27
29
31
ammonium (mg L–1)
59
60
61
nitrate (mg L–1)
18
18
17
chloride (mg L–1)
920
910
950
sulfate (mg L–1)
130
120
95
conductivity (mS m–1)
440
450
440
pH
7.9
8.0
8.0
alkalinity (mg L–1)
1300
1300
1400
TOC (mg L–1)
36
34
48
For the complete dataset, see Table S5.
For the complete dataset, see Table S5.
Effect
of Process Variables
The effect
of all investigated process variables on the ΣPFAS removal is
shown in Figure .
Both at constant air-to-feed ratio (AR) and at constant air flow (Qair), decreasing the contact time (tc) below 20 min was shown to decrease the ΣPFAS
removal efficiency (RE). Importantly, it was found that tc also limits the removal while the AR is kept constant,
although the effect may be different at higher AR values. This result
indicates that increasing the Qair cannot
make up for a too short tc. These results
are in good agreement with the results of Meng et al.,[3] who found total aeration time to be one of the most influential
variables in the performance of foam fractionation for PFAS removal
from aqueous firefighting foam concentrate.
Figure 2
Effect of (A) contact
time (tc) at
a constant air ratio (AR) of 4.3, 10% foam; (B) tc at a constant air flow (Qair) of 20 L min–1, 10% foam; (C) foam fraction (%foam) at constant tc = 20 min, Qair = 10 L min–1; AR = 4.3
and (D) Qair at constant tc = 20 min, 20% foam on the total PFAS removal. The red
lines and blue shading represent a least-squares fit of the mean data
to eq with the corresponding
95% confidence interval of the fit, respectively. The experiments
included in each plot in order of increasing x-value
were (A) 1, 13, 7, and 2; (B) 1, 16, 6, and 12; (C) 14, 7, 8, and
9; and (D) 10, 17, 8, and 11 (Table ).
Effect of (A) contact
time (tc) at
a constant air ratio (AR) of 4.3, 10% foam; (B) tc at a constant air flow (Qair) of 20 L min–1, 10% foam; (C) foam fraction (%foam) at constant tc = 20 min, Qair = 10 L min–1; AR = 4.3
and (D) Qair at constant tc = 20 min, 20% foam on the total PFAS removal. The red
lines and blue shading represent a least-squares fit of the mean data
to eq with the corresponding
95% confidence interval of the fit, respectively. The experiments
included in each plot in order of increasing x-value
were (A) 1, 13, 7, and 2; (B) 1, 16, 6, and 12; (C) 14, 7, 8, and
9; and (D) 10, 17, 8, and 11 (Table ).Altogether, the results
strongly indicate that RE is negatively
impacted by tc values below 15 min, but
the extent of decrease in RE is uncertain. The initial experiment
at 10 min tc (Exp. 0, Table , SI Section A) showed a higher RE of 47 ± 3% as compared to the RE
found in Exp. 1 of 42 ± 1%, which indicates that higher ΣPFAS
removal efficiencies may be achievable at a short tc than is now shown in Figure A, B. Nonetheless, for the experiment in
stripping mode at 10 min tc (Exp. 3, Table ), an even lower RE
of 29 ± 4.7% was observed (Section ), confirming the limited RE at low tc values.Collecting lower foam fractions
lead to higher foam concentrations,
as found from one-way ANOVA over the ΣPFAS concentration of
all collected foam samples divided into groups based on their %foam (F(4, 61) = 3.8, p < 0.05), which
has also been found previously.[3,41] Differences in foam
concentration were only statistically significant between 30% foam
as compared to 3% and 5% (p < 0.05) but statistically
insignificant between the other groups. Decreasing the %foam only affected the removal at fractions below 10%, which corresponds
to Robey et al.’s[41] finding that
most of the removal occurs in the first 14% of volume removed. This
is beneficial from a process design perspective, since achieving the
same removal at a low %foam leads to a lower volume of
concentrated foam that needs secondary treatment. Since the %foam is controlled by changing the effluent flow and the foam
outlet is directly above the water–air surface, the collected
foam was relatively wet. Strictly speaking, this mode of operation
is a mix of bubble fractionation and foam fractionation, as explained
by Lemlich.[35] However, since foaming was
observed in all tests, foam fractionation was chosen as terminology.Qair was shown to limit the removal
at values below 7.5 L min–1 (Figure D). Since the removal is highly dependent
on the surface area available for sorption, air flow is considered
a very influential process variable.[35] The
air–liquid surface area further relates to the size of the
introduced air bubbles.[35,42] In the current study,
the diffusers used generated relatively large air bubbles (up to approximately
5 mm diameter). Instead, the use of a membrane, glass frit, electrochemical
bubble generation, or other technologies may increase the available
surface area and thereby improve the removal.[40,42]For all process parameters, their effect on the ΣPFAS
RE
fits well with the empirical model given by eq . For each run, the ΣPFAS removal was
shown to plateau around 60%, with fitted REmax values ranging
between 56% and 61% for the effect of Qair (Figure D) and the
effect of tc at constant Qair (Figure B), respectively. The ΣPFAS RE is thus affected by all these
variables, but the effect is limited and REMax does not
reach 100%. Instead, it is also limited by the PFAS composition of
the inlet water. The leachate water used in this study contained on
average 46% short-chain PFCA, which were only marginally removed in
the foam fractionation process. Therefore, the ΣPFAS removal
reached a plateau at approximately 60%. It should be realized that
the fitted REMax and k parameters obtained
for each variable, given in Table S8, probably
depend strongly on the inlet water composition and parameters such
as PFAS composition and DOC concentration.
Effect
of PFAS Composition and Chain Length
On the basis of the
results presented in Figure , all experiments representing the lowest
removal efficiencies in Figure A–D were deemed process-limited. Therefore, 12 continuous
experiments without process-induced limitations on the RE were selected
for statistical analysis (experiments 2, 4–9, 11–13,
16, and 17 in Table ). All these 12 experiments have a tc, %foam, and Qair of at least
15 min, 10%, and 7.5 L min–1, respectively.On the
basis of these experiments, a significant negative correlation (Pearson’s r = −0.63 (95% CI: −0.88 to −0.09), p < 0.05) between the fraction short-chain PFCA in the
influent ΣPFAS and the ΣPFAS RE was found, as illustrated
in Figure . Hence,
water types with a high fraction of long-chain compounds may thus
be more suitable for foam fractionation treatment than the leachate
water used in the current study. Even commercially available batch
foam fractionation processes have a lower removal of short-chain PFAS
in comparison to long-chain PFAS.[36,47]
Figure 3
ΣPFAS
removal efficiency (%) as a function of fraction short-chain
PFCA in total influent PFAS. The correlation fit is only based on
experiments without process limitations on the removal, represented
in blue in this plot (see Table ). Horizontal error bars represent the standard deviation
of the short-chain PFCA fraction, and vertical error bars represent
the standard deviation of ΣPFAS removal efficiency.
ΣPFAS
removal efficiency (%) as a function of fraction short-chain
PFCA in total influent PFAS. The correlation fit is only based on
experiments without process limitations on the removal, represented
in blue in this plot (see Table ). Horizontal error bars represent the standard deviation
of the short-chain PFCA fraction, and vertical error bars represent
the standard deviation of ΣPFAS removal efficiency.The relationship between perfluorocarbon chain length and
RE is
further illustrated in Figure . These results confirm the literature finding that PFAS removal
efficiencies decrease exponentially with perfluoroalkyl chain length
in foam fractionation,[3,33,40−42] with a fit as given in eq . For readability, only PFCA and PFSA were
included in Figure , but a more complete plot is given in Figure S2. Although the comparatively low influent concentrations
of most non-PFAA PFAS causes high variability in some of the results,
similar dependencies on perfluorocarbon chain length were found for
the RE of 4:2 FTSA, 6:2 FTSA, 8:2 FTSA, FOSA, MeFOSAA, and EtFOSAA,
as also shown in Figure S2.
Figure 4
PFCA and PFSA removal
as a function of perfluorocarbon chain length.
Only the results from experiments without process-induced limitations
were included in this plot (i.e., Exp. 2, 4–9, 11–13,
16, and 17, Table ). The solid lines are model fits to eq , with the optimized parameter a at
9400 and 5100 for PFCA and PFSA, respectively. Error bars represent
the standard deviation between experiments.
PFCA and PFSA removal
as a function of perfluorocarbon chain length.
Only the results from experiments without process-induced limitations
were included in this plot (i.e., Exp. 2, 4–9, 11–13,
16, and 17, Table ). The solid lines are model fits to eq , with the optimized parameter a at
9400 and 5100 for PFCA and PFSA, respectively. Error bars represent
the standard deviation between experiments.PFOS and PFOA had average removal efficiencies of 95 ± 2%
and 92 ± 3%, at mean influent concentrations of 230 ± 110
and 630 ± 150 ng L–1, respectively. The REs
for other C8 PFAS (8:2 FTSA, FOSA, MeFOSAA, and EtFOSAA)
were similarly high. PFNS was only detected at quantifiable concentrations
in two influent and 28 foam samples but not in any effluent samples
and was thus assumed to have a removal efficiency of 100%. These results
correspond well with the literature findings in other foam fractionation
studies of >90% removal for long-chain PFCA and PFSA but lower
or
no removal of short-chain compounds.[33,36,40,42] PFCA of the same carbon
number were removed to a lower extent than their PFSA equivalent,
which has also been shown previously.[33,34,40,42] This phenomenon is
due to PFSA having higher adsorption coefficients to water–air
interfaces because of their higher hydrophobicity.[33,34] This effect was more pronounced for shorter chain lengths, as visible
in Figure .
Enriching versus Stripping Modes
Two experiments were
carried out in stripping mode, i.e., with the
water influent above the air/water interface, as well as in enriching
mode under otherwise identical conditions (experiments 3 and 4 (stripping)
and 1 and 5 (enriching) in Table ). In both comparisons, the mean ΣPFAS removal
was higher in enriching mode than in stripping mode (Figure ). These differences are not
in accordance with the literature, which predicts a higher removal
of contaminants in stripping mode compared to enriching mode, because
the liquid between the foam bubbles has a higher PFAS concentration
in stripping mode.[35,36] In the current system, the foam
layer was not sufficiently stable, so introduction of the influent
above the foam surface lead to an observable collapse of the foam.
Improvements of the column, such as introducing an inlet valve higher
above the interface on the opposite side of the foam outlet and a
foam outlet above this inlet valve, may prevent the foam from collapsing
and result in improved performance in stripping mode. Moreover, introducing
a vacuum pump for continuous foam collection may also increase the
removal, as shown by McCleaf et al.[40]
Figure 5
Comparison
between experiments in enriching (A) Exp. 1 and (B)
Exp. 5, Table )) and
stripping (A) Exp. 3 and (B) Exp 4, Table )) modes under otherwise identical conditions.
(A): 10 min contact time (tc), 10% foam,
air ratio (AR) 4.3. (B): 30 min tc, 20%
foam, AR 8.7. Error bars represent the standard deviation of the ΣPFAS
concentration. For the classification of all PFAS, see SI Section F.
Comparison
between experiments in enriching (A) Exp. 1 and (B)
Exp. 5, Table )) and
stripping (A) Exp. 3 and (B) Exp 4, Table )) modes under otherwise identical conditions.
(A): 10 min contact time (tc), 10% foam,
air ratio (AR) 4.3. (B): 30 min tc, 20%
foam, AR 8.7. Error bars represent the standard deviation of the ΣPFAS
concentration. For the classification of all PFAS, see SI Section F.
Batch Mode
The ΣPFAS RE of
the benchmark test in batch mode was 66 ± 7%, as shown in Figure . This result was
not significantly different from the continuous test with the highest
removal (Figure B, p > 0.05, Welch t test). Furthermore,
as
shown in Figure ,
the fraction short-chain PFAS was lowest of all experiments in the
batch test, which may have increased the ΣPFAS RE. Moreover,
the removal in batch mode strongly depended on where the effluent
samples are taken. After turning off the air flow, effluent taken
from the bottom of the column had lower PFAS concentrations than effluent
taken from the top of the column, which only had a removal of 48 ±
14%. It may thus be possible to increase the batch-mode removal by
collecting a higher foam fraction, but the limitation of low short-chain
PFCA removal was not reduced in batch operation.
Figure 6
Removal efficiency in
batch test (tc 20 min, Qair 20 L min–1, 3% foam).
Error bars represent the standard deviation of the ΣPFAS concentration.
For the classification of all PFAS, see SI Section F.
Removal efficiency in
batch test (tc 20 min, Qair 20 L min–1, 3% foam).
Error bars represent the standard deviation of the ΣPFAS concentration.
For the classification of all PFAS, see SI Section F.
Mass
Balance
The mass balance did
not close for all experiments. The mass balance for the continuous
tests ranged from 66 ± 7% to 104 ± 10%, for experiments
12 and 10 (Table ),
respectively. For the batch experiment, the mass balance only closed
to 42 ± 15% when considering the bottom effluent samples or 59
± 22% when considering the top effluent samples. The preliminary
continuous experiment showed an enrichment of some PFAS in the water
layer at the top of the column relative to the effluent, as shown
in Figure S1. These PFAS will not show
up in the mass balance, since they are neither in the foam nor in
the effluent, and their accumulation may thus lead to a lower mass
balance closure. It could be hypothesized that collecting higher foam
fractions would thus improve the mass balance closure, but no significant
effect of the %foam on the mass balance was found (one-way
ANOVA, p > 0.05), and in the batch test, the mass
balance did not close either when only considering the top layer concentrations.The overall mass balance did not correlate with ΣPFAS removal
either, but individual balances closed significantly better for compounds
with a lower removal, i.e., short-chain compounds (Pearson’s r = −0.95 (95% CI: −0.96 – −0.94), p < 0.05). For perfluorocarbon chain lengths up to 10
for PFCA and up to 8 for PFSA, one-way ANOVA showed a statistically
significant difference in mass balance closure with increasing chain
length (F(7,88) = 14 for PFCA, F(4,55) = 21 for PFSA, p < 0.05 for both). PFAS with perfluorocarbon chain lengths above
the specified numbers were excluded because of their relatively low
influent concentrations of <5 ng L–1, and only
the results from experiments without process-induced limitations (Exp.
2, 4–9, 11–13, 16, and 17, Table ) were included in these calculations. Box
plots and details on the statistical calculations are given in SI Section I.Since long-chain PFAS were
removed better and were thus more enriched
at the air–water surface, these strong correlations indicate
that PFAS accumulating at the air–water interface may also
escape to the air as aerosols rather than being captured in the foam.
This hypothesis is supported by the work of Ebersbach et al.,[42] who demonstrated the aerosol-mediated removal
of 6:2 FTSA, PFOS, and PFOA from concentrated water. Moreover, aerosol
enrichment with PFAS is a well-documented phenomenon, both in nature
and in engineered systems.[48−50] The presence of aerosols in the
current system was visible from the bursting of foam bubbles, leading
to the formation of droplets and bubbles on the lid and upper walls
of the column. However, McCleaf et al.[40] found no significant PFAS concentrations in their aerosol trap after
foam fractionation, which may be related to their use of a vacuum
pump for foam collection. In addition to loss of PFAS in aerosols,
the complex water matrix may have caused transformation of certain
compounds as a result of oxidation, which could have further skewed
the mass balance.
Conclusions
This
study set out to examine the applicability of pilot-scale
continuous foam fractionation for treatment of PFAS-contaminated leachate
water. It was shown that treatment efficiency decreased with decreasing
contact time, air flow rate and collected foam fraction. Long-chain
compounds were removed better than short-chain PFAS, and PFSA were
removed more efficiently than PFCA. PFOS and PFOA had average removal
efficiencies of 95% and 92%, but no removal of PFBA and only 10% removal
of PFBS were found. No improvement in treatment efficiency was found
when operating in batch mode, which indicates that continuous operation
is a viable alternative for commercially available batch systems.
Despite the relatively low ΣPFAS removal of approximately 60%,
the results indicate a high applicability of continuous foam fraction,
especially for treatment of water types contaminated with mainly long-chain
PFAS. Further research is required to confirm if the high long-chain
PFAS removal extends to water types with different water quality matrixes
and PFAS concentrations than the investigated leachate.Currently,
most regulations for aqueous PFAS emissions to the environment
still include almost exclusively long-chain PFAS. For example, the
European Water Framework Directive defined an average annual PFOS
concentration in inland surface water of 0.65 ng L–1 as the environmental quality limit.[51] In The Netherlands, soil-washing facilities are allowed to discharge
4000 m3 of wastewater containing at most 500 ng L–1 PFOS, 500 ng L–1 PFOA, and 1000 ng L–1 HFPO–DA (GenX) annually.[52] In
the United States, efforts are underway to enforce remediation of
PFOS and PFOA releases into the environment.[16] In the most effective continuous experiment presented in this study,
mean PFOS and PFOA concentrations decreased from 230 and 580 to 7
and 20 ng L–1, respectively, which falls well within
the Dutch standards for soil washing wastewater. However, landfill
facilities often have specific individual discharge permits for PFAS,
so drawing generalized conclusions on the treatment performance with
respect to regulatory limits is difficult.The greatest advantage
of the presented technology is its simplicity.
Aeration is common in most wastewater treatment facilities, and for
plants, treating PFAS contaminated water introducing a foam fractionation
process is thus an easily implemented and economical way to decrease
PFAS emissions to the environment. Possibly, this technology can even
be integrated with aeration steps that are already applied on-site,
by installing an appropriate foam collection system. Naturally, the
collected foam would need further treatment, where the reduced volume
of approximately 10% of the total inlet volume allows relatively smaller
on-site degradative treatment of the coalesced foam, as exemplified
in previous studies.[32,33]Two of the most promising
degradative treatment technologies for
PFAS-contaminated water are plasma treatment and electrochemical oxidation.[53] Both these technologies have been applied successfully
to leachate water matrices similar to the foam produced in this study,
with ΣPFAS concentrations in the low μg L–1 range, albeit at higher TOC concentrations and conductivities.[54,55] Both these destructive technologies were more effective for the
removal of long-chain as compared to short-chain PFAS. A drawback
of electrochemical degradation was the formation of short-chain compounds
as degradation products, which was not observed in plasma treatment.
These results indicate that degradative treatment of the foam produced,
as described here, will most probably be possible.Further research
should focus on improving the removal of short-chain
compounds in the foam fractionation process. Alternative methods for
the introduction of air bubbles, such as electrochemical bubble formation,
may lead to higher available surface area and thus higher removal.
Possibly, this will increase the removal of short-chain compounds.
The use of image processing technologies for determining the size
distributions in bubbly flows could enhance the understanding of the
effect of bubble size on removal.[56,57] Alternatively,
additives such as metal activators may be tested, which have been
shown to increase the removal of long-chain compounds.[40,43] Enhanced foam collection, for example with a vacuum pump, may also
improve the removal of short-chain PFAS, as may combining several
foam fractionation steps in a row.Another area for future work
would be the variation in mass balance
closure that was found. Introducing air as well as aerosol sampling
and analyzing the PFAS concentrations in the exhaust air may be beneficial
toward closing the mass balance and could indicate if any PFAS escape
the system. Finally, testing other water matrixes with a higher fraction
of long-chain compounds could confirm the presented limitation of
low short-chain removal.
Authors: Pingping Meng; Shubo Deng; Ayiguli Maimaiti; Bin Wang; Jun Huang; Yujue Wang; Ian T Cousins; Gang Yu Journal: Chemosphere Date: 2018-03-29 Impact factor: 7.086
Authors: Siwen Wang; Jun Huang; Yang Yang; Yamei Hui; Yuxi Ge; Thorjørn Larssen; Gang Yu; Shubo Deng; Bin Wang; Christopher Harman Journal: Environ Sci Technol Date: 2013-08-29 Impact factor: 9.028
Authors: Lutz Ahrens; Sachi Taniyasu; Leo W Y Yeung; Nobuyoshi Yamashita; Paul K S Lam; Ralf Ebinghaus Journal: Chemosphere Date: 2010-02-23 Impact factor: 7.086
Authors: Robert C Buck; James Franklin; Urs Berger; Jason M Conder; Ian T Cousins; Pim de Voogt; Allan Astrup Jensen; Kurunthachalam Kannan; Scott A Mabury; Stefan P J van Leeuwen Journal: Integr Environ Assess Manag Date: 2011-10 Impact factor: 2.992
Authors: Suzanne E Fenton; Alan Ducatman; Alan Boobis; Jamie C DeWitt; Christopher Lau; Carla Ng; James S Smith; Stephen M Roberts Journal: Environ Toxicol Chem Date: 2020-12-07 Impact factor: 4.218