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Assessing the passage of small pesticides through reverse osmosis membranes
Journal Pre-proof Assessing the passage of small pesticides through reverse osmosis membranes Takahiro Fujioka, Hitoshi Kodamatani, Wang Yujue, Koh Dan Yu, Elvy Riani Wanjaya, Han Yuan, Mingliang Fang, Shane Allen Snyder PII:
S0376-7388(19)32185-4
DOI:
https://doi.org/10.1016/j.memsci.2019.117577
Reference:
MEMSCI 117577
To appear in:
Journal of Membrane Science
Received Date: 22 July 2019 Revised Date:
9 October 2019
Accepted Date: 16 October 2019
Please cite this article as: T. Fujioka, H. Kodamatani, W. Yujue, K.D. Yu, E.R. Wanjaya, H. Yuan, M. Fang, S.A. Snyder, Assessing the passage of small pesticides through reverse osmosis membranes, Journal of Membrane Science (2019), doi: https://doi.org/10.1016/j.memsci.2019.117577. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier B.V.
Rejection [%]
100 80 60 40 Diuron
20 0
20
25
30
35
Minimum projection area [Å2]
(Hydrogen bonding)
1
Assessing the passage of small pesticides through reverse osmosis
2
membranes
3
Takahiro Fujioka 1,*, Hitoshi Kodamatani 2, Wang Yujue 3, Koh Dan Yu 3,
4
Elvy Riani Wanjaya 3, Han Yuan 3, Mingliang Fang 3,4, Shane Allen Snyder 3,4
5
1
Graduate School of Engineering, Nagasaki University, 1-14 Bunkyo-machi, Nagasaki 852-8521,
6 7
Japan 2
Division of Earth and Environmental Science, Graduate School of Science and Engineering,
8 9 10 11 12
Kagoshima University, 1-21-35 Korimoto, Kagoshima 890-0065, Japan 3
Analytics Cluster, Nanyang Environment & Water Research Institute (NEWRI), Nanyang
Technological University, 1 Cleantech Loop, CleanTech One, Singapore 637141, Singapore 4
School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
13
_______________________
14
* Corresponding author: Takahiro Fujioka, Email: [email protected], Ph +81 95 819 2695
15
Abstract
16
Attenuation of trace organic chemicals (TOrCs), including pesticides, by reverse osmosis (RO)
17
membrane treatment is critical for ensuring public health protection in potable water reuse. This
18
study aimed to elucidate the mechanisms underlying the poor rejection of small pesticides by
19
polyamide-based RO membranes. Rejection of the selected TOrCs (four N-nitrosamines and 158
20
pesticides) was primarily governed by size exclusion, charge interactions, and dipolar
21
interactions when evaluated at high water temperatures. Further investigation indicated that small
22
and uncharged secondary amide pesticides showed low and highly variable rejections, compared
23
to similarly sized counterparts with no amide functional groups. Remarkably, three secondary
24
amide pesticides that have no other atoms holding a high partial negative charge showed very
25
low rejections (34–65%), likely due to the cooperativity of hydrogen bonding which occurs
26
between amide functional groups of the pesticides and RO membranes. In contrast, secondary
27
amide pesticides that have an atom holding a high partial negative charge showed higher
28
rejections (72–98%) which is due to the inducted electrostatic repulsion. This study proposed
29
that secondary amide pesticides that have no other atoms holding a high partial negative charge
30
can be poorly rejected. The findings are useful to predict the rejection level of unregulated
31
TOrCs.
32
Keywords: secondary amides; trace organic chemicals; NDMA; hydrogen bonding; potable
33
water reuse.
34
1
35
1
INTRODUCTION
36
Potable water reuse has been increasingly adopted in many regions of the world that have been
37
plagued by droughts [1]. It is typically carried out by converting municipal wastewater to highly
38
pure water through advanced wastewater treatment. The majority of recent advanced wastewater
39
treatment systems for potable water reuse include microfiltration (MF) or ultrafiltration (UF),
40
reverse osmosis (RO), and ultraviolet (UV) or UV-based advanced oxidation processes [2].
41
Advanced wastewater treatment using RO plays a role in attenuating salts, pathogens, and trace
42
organic chemicals (TOrCs), which include pesticides, disinfection by-products (DBPs),
43
endocrine disrupting compounds, and pharmaceuticals and personal care products (PPCPs) [3, 4].
44
The attenuation of these TOrCs by an RO process can be ensured through periodical water
45
quality testing by approved analytical methods. However, for continuously ensuring regulatory
46
compliance, the infrequent and costly analysis remains a challenge. To date, no monitoring
47
technique has been fully established to continuously and conservatively ensure the attenuation of
48
TOrCs by the RO process or the integrity of RO membranes for TOrC removal [5].
49
As a surrogate indicator for TOrC removal by RO, the authors have recently suggested a low
50
molecular weight (MW) DBP, N-nitrosodimethylamine (NDMA; MW of 74 g/mol), which can
51
be monitored online using high-performance liquid chromatography followed by photochemical
52
reaction and chemiluminescence detection [6, 7]. The NDMA can be considered as a
53
conservative surrogate because it is not well rejected by RO membranes and is typically
54
identified at higher concentrations than the method detection limit (e.g., 1–2 ng/L) in both RO
55
feedwater and permeate [8]. Previous pilot-scale studies conducted by the authors demonstrated
56
that online monitored NDMA rejection was always lower than the rejection of PPCPs [7].
57
Nevertheless, the reliability of NDMA as a conservative surrogate for TOrC removal is still
2
58
questionable, since its conservativeness cannot be guaranteed with the current knowledge about
59
the rejection mechanisms.
60
Despite many studies addressing the rejection mechanisms of TOrCs over the past decade [9-15],
61
the cause of some poorly rejected TOrCs has not been adequately understood. The rejection of
62
TOrCs at high temperatures is of great interest, because wastewater temperature can vary
63
seasonally and TOrC rejection decreases according to an increase in temperature due to the
64
increasing diffusivity of the solutes [16, 17]. According to the previous studies, the transport of
65
TOrCs through nanofiltration (NF) and RO membranes is governed by three major interactions
66
(i.e., size, charge, and hydrophobicity) that occur between compounds and membranes. The
67
rejection of TOrCs by polyamide-based membranes is primarily governed by size interaction and
68
charge interaction, whereas highly hydrophobic TOrCs (e.g., LogD = ≥ 2) can show lower
69
rejection than hydrophilic TOrCs (e.g., LogD = < 2) [18, 19]. As a result, pesticides, most of
70
which are highly hydrophobic, are of great interest [20, 21]. One notable pesticide is diuron,
71
which is an aromatic pesticide with a relatively high molecular weight of 233 g/mol. For
72
example, Chen et al. [22] reported that the rejection of diuron by a polyamide NF membrane
73
element (50%) was the lowest among 11 selected pesticides with molecular weights of 198–286
74
g/mol (60–100%). Similar observations associated with the low rejection of diuron have been
75
reported elsewhere [23-27]. However, to the best of our knowledge, no basic theory for
76
clarifying the mechanisms of the poorly rejected pesticides has been established.
77
This study aimed to elucidate the mechanisms underlying the poor rejection of several pesticides
78
by polyamide-based RO membranes. The rejection mechanisms were comprehensively assessed
79
by analyzing the role of molecular interactions (i.e., size exclusion, and electrostatic,
3
80
hydrophobic, dipolar, and hydrogen bond interactions) using a diverse range of compounds (four
81
N-nitrosamines and 158 pesticides).
82
2
83
2.1 Chemicals
84
Analytical grade solutions of four N-nitrosamines – NDMA, N-nitrosomethylethylamine
85
(NMEA), N-nitrosopyrrolidine (NPYR), and N-nitrosomorpholine (NMOR) – were purchased
86
from Ultra Scientific (Kingstown, RI, USA). A stock solution containing the N-nitrosamines was
87
prepared at 10 mg/L in pure methanol. In addition to N-nitrosamines, a total of 158 analytical
88
grade pesticides (Agilent Technologies, Singapore) covering a wide range of molecular weights
89
(MWs) and other molecular properties were used in this study (Table 1 and Table S1).
90
Commercial Marvin (version 18.30, ChemAxon, Budapest, Hungary) was used for drawing and
91
characterizing chemical structures, and calculating molecular properties (minimum projection
92
area, LogD, pKa, dipole moment, and counts of hydrogen bond acceptor or donor). The
93
minimum projection area (MPA) of a compound is a two-dimensional projected area of the
94
chemical calculated based on the van der Waals radius (Figure S1). LogD, which is the octanol-
95
water coefficient of the chemical, was calculated at a test solution pH of 8.0. The selected
96
chemicals were determined to be uncharged (≤50% ionized) or charged (>50% positively or
97
negatively charged, or zwitterion). The total dipole moment of a chemical was calculated as a
98
vector expressed in the principal axis frame. Counts of hydrogen bond acceptor or donor were
99
determined at pH 8. Analytical grade NaCl was purchased from Merck KGaA (Darmstadt,
100
Germany) and analytical grade NaHCO3 was purchased from VWR Singpapore Ltd (Singapore).
MATERIALS AND METHODS
4
101
Two stock solutions containing the pesticides were prepared at 5 mg/L in Milli-Q water with 10
102
mM NaCl and 1 mM NaHCO3.
5
103
Table 1: Properties of four N-nitrosamines and 158 pesticides. Compound
104
MW MPA Compound MW MPA Compound 2 2 [g/mol] [Å ] [g/mol] [Å ] Uncharged Dimethachlor 255.7 50.5 Ipconazole NDMA 74.1 19.4 Propyzamide 256.1 39.7 Zoxamide NMEA 88.1 22.3 Ethidimuron 264.3 33.5 Fenbuconazole NPYR 100.1 25.0 Diethofencarb 267.3 53.4 Bitertanol NMOR 116.1 26.9 Silthiofam 267.5 49.6 Tepraloxydim Propham 179.2 32.4 Methoprotryne 271.4 48.6 Propiconazole Acephate 183.2 32.3 Metazachlor 277.8 52.4 Boscalid Fuberidazole 184.2 24.2 Oxadixyl 278.3 47.7 Azinphos-ethyl Molinate 187.3 37.3 Metalaxyl 279.3 53.2 Triflumizole Tricyclazole 189.2 27.7 Propetamphos 281.3 49.7 Tebufenozide Aldicarb 190.3 35.1 Fosthiazate 283.4 42.5 Beflubutamid Butocarboxim 190.3 38.8 Metolachlor 283.8 56.1 Triflumuron Carbendazim 191.2 25.5 Penconazole 284.2 51.1 Chlorfenvinphos DEET 191.3 41.2 Vamidothion 287.3 42.3 Clethodim Trimethacarb 193.2 35.1 Myclobutanil 288.8 50.9 Flufenacet Cycluron 198.3 34.6 Isoprothiolane 290.4 47.4 Benzoximate Pyrimethanil 199.3 31.3 Thiamethoxam 291.7 38.8 Picoxystrobin Thiabendazol 201.3 25.0 Cyproconazole 291.8 49.2 Methoxyfenozide Metamitron 202.2 28.5 Uniconazole-P 291.8 48.0 Tetraconazole Fenobucarb 207.3 44.2 Triadimefon 293.8 47.7 Spirotetramat Promecarb 207.3 38.8 Paclobutrazol 293.8 49.3 Profenofos Quinoclamine 207.6 25.2 Triadimenol 295.8 47.9 Fluquinconazole Aminocarb 208.3 35.5 Imazalil 297.2 46.0 Prochloraz Propoxur 209.2 40.6 Quinalphos 298.3 45.6 Bromuconazole Ethirimol 209.3 34.8 Phoxim 298.3 52.6 Fluopicolide Chlorotoluron 212.7 29.9 Phosphamidon 299.7 45.3 Sulfentrazone Metribuzin 214.3 34.4 Flutriafol 301.3 49.3 Pyraclostrobin Cymiazole 215.4 29.2 Furalaxyl 301.3 54.6 Dimethomorph Pyracarbolid 217.3 32.9 Methidathion 302.3 34.7 Alanycarb Thiofanox 218.3 39.9 Fenamiphos 303.4 49.6 Azoxystrobin Carbofuran 221.3 40.8 Diazinon 304.4 50.7 Difenoconazole Chloridazon 221.6 29.9 Pirimiphos-methyl 305.3 47.9 Trifloxystrobin Mexacarbate 222.3 41.9 Buprofezin 305.4 56.1 Metrafenone Acetamiprid 222.7 30.8 Tebuconazole 307.8 54.1 Mandipropamide Monocrotophos 223.2 41.2 Diflubenzuron 310.7 27.9 Bispyribac Mepanipyrim 223.3 38.0 Fenamidone 311.4 53.1 Fipronil Mevinphos 224.2 40.2 Triazophos 313.3 46.3 Fluoxastrobin Cyprodinil 225.3 37.7 Kresoxim-methyl 313.4 51.2 Chlorantraniliprole Prometon 225.3 46.3 Hexaconazole 314.2 53.0 Flubendiamide Secbumeton 225.3 42.9 Flusilazole 315.4 54.4 Charged (negative) Tebuthiuron 228.3 37.7 Bupirimate 316.4 54.6 Thidiazuron Flonicamid 229.2 27.1 Azinphos-methyl 317.3 29.2 Quinmerac Dimethoate 229.3 35.8 Triticonazole 317.8 51.5 Chlorsulfuron Trietazine 229.7 40.5 Metconazole 319.8 54.2 Amidosulfuron Fluometuron 232.2 32.7 Phenthoate 320.4 55.8 Thifensulfuron-methyl Diuron 233.1 28.6 Iprovalicarb 320.4 52.2 Tribenuron-methyl Lenacil 234.3 36.3 Cyazofamid 324.8 49.2 Triasulfuron Carboxine 235.3 34.0 Flumetsulam 325.3 50.7 Oxasulfuron Pirimicarb 238.3 44.0 Benalaxyl 325.4 57.8 Flazasulfuron Clomazone 239.7 40.1 Diniconazole 326.2 52.2 Nicosulfuron Methacrifos 240.2 36.0 Dimoxystrobin 326.4 62.2 Charged (positive) Ethoprophos 242.3 50.3 Pencycuron 328.8 49.9 Fenpropidin Fludioxonil 248.2 40.3 Epoxiconazole 329.8 48.5 Zwritterion Linuron 249.1 28.0 Halofenozide 330.8 54.9 Imidacloprid Prosulfocarb 251.4 39.1 Fenarimol 331.2 55.4 Thiacloprid 252.7 36.9 Isoxaben 332.4 51.8 * MPA was calculated using Marvin software (ChemAxon, Budapest, Hungary).
6
MW [g/mol] 333.9 336.6 336.8 337.4 341.8 342.2 343.2 345.4 345.8 352.5 355.3 358.7 359.6 359.9 363.3 363.8 367.3 368.5 372.2 373.4 373.6 376.2 376.7 377.1 383.6 387.2 387.8 387.9 399.5 403.4 406.3 408.4 409.3 411.9 430.4 437.2 458.8 483.2 682.4
MPA 2 [Å ] 60.0 46.3 53.8 49.5 42.3 55.4 49.3 46.3 53.2 67.6 54.7 54.8 53.4 50.1 42.2 47.5 54.3 49.1 54.1 57.4 50.1 47.8 58.3 48.7 42.4 45.6 52.3 66.3 73.8 63.5 60.9 58.0 60.8 58.0 54.7 44.1 63.7 68.0 84.2
220.3 221.6 357.8 369.4 387.4 395.4 401.8 406.4 407.3 536.8
25.0 27.7 49.6 50.7 51.1 48.1 55.3 63.7 46.8 57.2
273.5
46.1
255.7
36.9
105
2.2 Membranes and RO treatment
106
This study used a low pressure RO membrane – namely ESPA2, which is widely used in many
107
water recycling projects [8]. The RO membrane was supplied as flat sheet coupons by
108
Hydranautics/Nitto (Osaka, Japan). RO treatment was conducted using a bench-scale system
109
comprised of a stainless steel membrane cell (Iwai Pharma Tech, Tokyo, Japan), high-pressure
110
constant flow pump (KP-12, FLOM, Tokyo, Japan), pressure regulating valve (Swagelok, Solon,
111
OH, USA), and digital flow meter (F7M, Azbil Co., Tokyo, Japan) (Figure S2). The cross-flow
112
membrane cell has an integrated magnetic stirrer for mixing feed solution at the membrane
113
surface to minimize concentration polarization. The membrane cell held a circular flat-sheet
114
membrane coupon with effective surface area of 36.3 cm2. The RO concentrate and permeate
115
were recirculated into the reservoir.
116
Prior to each rejection test, each RO membrane coupon underwent a stabilization phase by
117
treating Milli-Q water at 1000 kPa. Thereafter, the Milli-Q water was replaced with a 200 mL
118
solution containing 10 mM NaCl and 1 mM NaHCO3. RO treatment was conducted at a constant
119
permeate flux of 20 L/m2h, a constant feed flow rate of 30 mL/min, and a constant feed
120
temperature of 35°C. The high temperature was determined to simulate the summer during a
121
long-term operation, which leads to the lowest performance for TOrC removal due to its high
122
temperature. In addition, a stock solution of N-nitrosamines or pesticides was added to the RO
123
feed to achieve 1.0 µg/L or 5.0 µg/L, respectively. It is noted that the rejection tests for four N-
124
nitrosamines and 158 pesticides were separately conducted to avoid interferences with their
125
analysis. The system was then continuously operated for approximately 70 h before collecting
126
samples from the RO feed and permeate. The RO feed and permeate samples were collected in
127
1.5 mL amber vials for the analysis of N-nitrosamines and pesticides. The extended treatment
7
128
period was determined to reach the steady state condition for adsorption, because most pesticides
129
used in this study are hydrophobic (LogD = > 2), and adsorption onto the membrane can cause
130
overestimation of their rejections [28].
131
2.3 Analytical techniques
132
Concentrations of pesticides were analyzed using Agilent 1290 infinity II Binary liquid
133
chromatography (LC) system coupled with Agilent 6460 triple quadrupole (QqQ) mass
134
spectrometer (Agilent Technologies, Santa Clara, CA, USA). The mass spectrometer was fitted
135
with electrospray ionization (ESI) interface in positive and negative mode with Agilent jet
136
stream technology. Identification and quantification of all target compounds were conducted via
137
tandem mass spectrometry. Further information of the pesticide analysis is provided in Text S1
138
and Table S2. Concentrations of four N-nitrosamines were analysed using high-performance
139
liquid
140
chemiluminescence detection (HPLC-AEM-PR-CL) technique [6, 29]. The analysis was
141
performed with an eluent of 1 mM phosphate buffer (pH6.8) and methanol (95:5 v/v) and the
142
sample injection volume of 200 µL.
143
3
144
3.1 Size exclusion and electrostatic interaction
145
The importance of size exclusion on TOrC rejection by polyamide-based RO membranes was
146
evaluated using four N-nitrosamines and 158 pesticides. In general, the rejection of the tested
147
compounds increased with an increase in their molecular weight (Figure 1a). However, many of
148
the uncharged pesticides with molecular weights of 180–300 g/mol showed high variations in
149
rejection. Another two-dimensional parameter, referred to as the minimum projection area
chromatography-inline
anion
exchange
reaction-photochemical
reaction-
RESULTS AND DISCUSSION
8
150
(MPA), appeared to be more strongly correlated with the rejection of uncharged pesticides
151
(Figure 1b). The role of size exclusion can be explained by the phenomena that TOrCs with low
152
two-dimensional areas have more clearance with the free volume hole of the membrane structure,
153
resulting in lower rejection. In fact, when curve fitting with the monomolecular growth model
154
was used, MPA (R2adj = 0.6) showed a better fit than molecular weight (R2adj = 0.5). The results
155
indicate that MPA is a suitable parameter to describe the rejection level of uncharged compounds
156
such as pesticides and N-nitrosamines, which confirms the importance of size exclusion in the
157
rejection of uncharged TOrCs. However, large variations of rejection for uncharged pesticides at
158
an MPA of approximately 27–30 Å2 (e.g., diflubenzuron, diuron, chlorotoluron) (Figure 1b)
159
indicates that size exclusion is not the only mechanism governing TOrC rejection. Therefore, the
160
influence of other chemical properties on the rejection of uncharged TOrCs was further
161
evaluated in the following sections.
162
Evaluating the impact of electrostatic interactions on their rejection was difficult in this study,
163
because almost all of the charged pesticides were large in size and uncharged pesticides with
164
equivalent MPAs were also highly rejected. However, the rejection of negatively charged
165
pesticides was found to be higher than the fitted line of uncharged pesticides, with the exception
166
of the smallest charged pesticide (thidiazuron, 43%) (Figure 1b). In contrast, the rejections of a
167
positively charged pesticide (fenpropidin) and zwitterion (imidacloprid) were equivalent to those
168
of similarly sized uncharged pesticides. The rejection of negatively charged TOrCs by RO
169
membranes can be enhanced with electrostatic repulsion that occurs against the negatively
170
charged membrane surface. The skin layer of the polyamide RO membrane, which is formed by
171
a cross-linking of meta-phenylenediamine and trimesic acid trichloride monomers, has remaining
172
carboxyl functional groups (-COOH) that are dissociated (-COO-) and negatively charged at pH
9
173
8 [30, 31]. However, the cause of the poor rejection of thidiazuron remains unclear. Thus, other
174
molecular properties have been accounted for to explain thidiazuron rejection in Section 3.5.
100
(a) y = A×(1-exp(-k×(x-xc)))
Rejection [%]
80
R2adj = 0.50
60 40
Uncharged N-nitrosamines) Charged (-) Charged (+) Zwitterion
(
20 0 100
200
300
400
680
Molecular weight [g/mol] 100
(b) y = A×(1-exp(-k×(x-xc)))
Rejection [%]
80
R2adj = 0.60
Chlorotoluron
60
Diflubenzuron Thidiazuron
40
Diuron
20 0 20
175 176 177 178 179 180
30
40
50
60
70
80
Minimum projection area [Å2]
Figure 1 – Effect of (a) molecular weight and (b) minimum projection area (MPA) of four Nnitrosamines and 158 pesticides on their rejection by the ESPA2 reverse osmosis (RO) membrane (10 mM NaCl and 1 mM NaHCO3; feed temperature of 35 ºC, permeate flux of 20 L/m2h, and pH of 8.1; error bars show the range of duplicate RO treatment experiments). Rejection data is provided in Figure S3.
10
181
3.2 Hydrophobic interaction
182
Hydrophobicity of TOrCs can also be an important additional factor to vary rejection [20, 32, 33].
183
Rejection of TOrCs with strong hydrophobicity can be lower than that of hydrophilic TOrCs,
184
because the former can be concentrated at the RO membrane surface, leading to an increase in
185
their concentrations in the RO permeate. However, in this study, hydrophobicity alone did not
186
show any correlation with compound rejection (Figure S4), indicating that hydrophobicity
187
interactions are less preferential than size exclusion. Therefore, the impact of hydrophobic
188
interactions on pesticide rejection was evaluated by applying six classifications of
189
hydrophobicity and comparing their rejections at a given MPA (Figure 2). As a result, the
190
impact of hydrophobic interactions on pesticide rejection was not apparent for small and
191
uncharged pesticides (e.g., MPA = < 35 Å2). For example, several hydrophobic compounds
192
(LogD = ≥ 2.0) showed higher rejection than hydrophilic compounds (LogD = < 1.9) when
193
evaluated at equivalent MPAs. This indicates that the rejection of low MPA pesticides is also
194
influenced by factors other than size exclusion and hydrophobic interactions. Therefore, the roles
195
of other molecular interactions for the rejection of uncharged and low MPA compounds (MPA of
196
<35 Å2) were further evaluated in the following sections.
11
100
Rejection [%]
80 LogD 60
5.0–5.9 4.0–4.9 3.0–3.9 2.0–2.9 1.0–1.9 ≤0.9
40 20 0 20
30
40
50
60
70
80
2
Minimum projection area [Å ]
197 198 199 200
Figure 2 – Effect of hydrophobicity on the rejection of uncharged compounds by the ESPA2 reverse osmosis (RO) membrane. The results were obtained from Figure 1. Error bars show the range of duplicate RO treatment experiments.
201
3.3 Dipolar interaction
202
Dipole moment (DM), which is the level of charge separation in a compound, can also influence
203
the rejection of TOrCs [34-36]. Regarding the molecular interaction between dipole TOrCs and
204
the RO membrane surface, the positive end of the dipole TOrCs can be favorably attracted to the
205
negatively charged functional group of an RO membrane (i.e., COO–) (dipole-charge interaction),
206
which can cause an increase in the TOrC concentration at the RO membrane surface and
207
consequently lead to low rejection. The compounds tested in this study hold a diverse range of
208
DM; thus, its impact was comprehensively assessed. The results indicated that highly polar (DM
209
= ≥ 6) compounds, with the exception of diuron, showed a proportional increase in rejection as a
210
function of MPA (Figure 3). Compounds with lower polarity (DM = < 6) showed higher
211
rejections than their similarly sized counterparts, which is in line with the theory (i.e., dipole-
212
charge interaction). It is noted that DM was not the only parameter that determines rejection,
213
because the compounds with DM of 6–7 debye showed a considerable variation in rejection (14– 12
214
88%) (Figure S5). The results indicate that the rejection of uncharged TOrCs varies according to
215
their molecular size and DM. However, seven pesticides (chemicals circled with a dotted line in
216
Figure 3) showed substantially lower rejection than their similarly sized counterparts, indicating
217
that other parameters are involved in governing their rejection. Therefore, further evaluation was
218
conducted with a particular focus on these poorly rejected pesticides.
100 DM
80 Rejection [%]
Propham
≥ 6.0 3.5–5.9 1.0–3.4
60
Carboxine
NPYR
Chlorotoluron Diflubenzuron
40 20
Methi -dathion Pyra -carbolid
NMEA Diuron
NDMA
0 15
20
25
30
35
Minimum projection area [Å2]
219 220 221 222
Figure 3 – Effect of dipole moment (DM) on the rejection of small (MPA = < 35 Å2) and uncharged compounds by the ESPA2 reverse osmosis (RO) membrane. The results were obtained from Figure 1. Error bars show the range of duplicate RO treatment experiments.
223
3.4 Hydrogen bonding
224
The cause of the variation in rejection among the small and uncharged pesticides was evaluated
225
by focusing on their molecular structure and functional groups. Overall, the presence of a
226
secondary amide functional group, −C(O)NH−, in pesticides was found to play a key role in
227
determining their removal. For example, the secondary amide pesticides that have atoms holding
228
a high partial negative charge showed the lowest rejection (34–65%) with the exception of
229
cyluron (Figure 4, Table 2). In contrast, the pesticides holding no amide functional groups were
230
highly rejected (83–96%) with the exception of methidathion (72%). The rejection of secondary
13
231
amide pesticides can be higher when they have an atom holding a high partial negative charge:
232
an ether functional group (−O−) (72–80%) or other strong electronegative (EN) atoms holding a
233
high partial negative charge (93–98%) (Table S3). The impact of a secondary amide group on
234
the rejection of pesticides can be explained by the role of hydrogen bonding. Hydrogen bonding
235
occurs between the hydrogen bond acceptor (HB-A), which has a basic electron lone pair, and
236
the hydrogen bond donor (HB-D), which is a partially stripped proton [37]. The secondary amide
237
of the pesticides contains a HB-A (oxygen atom) and HB-D (hydrogen atom); thus, hydrogen
238
bonding can commonly occur with a HB-D (hydrogen atom) and HB-A (oxygen atom) of the
239
membrane’s polyamide, respectively. Secondary amide pesticides that are attracted to polyamide
240
RO membranes through hydrogen bonding increase in concentration at the RO membrane
241
surface, which ultimately leads to low rejection. (d) No amide (c) 2° amide & an atom holding high PNC (b) 2° amide & an ether functional group (a) 2° amide & no other atoms holding high PNC
100
Fuberidazole
Acephate
Ethidimuron Cycluron
Rejection [%]
Fluometuron
80
Propham
Linuron
Pyracarbolid
60
Carboxine Methidathion
Chlorotoluron Diflubenzuron
40 Diuron
28 242 243 244 245 246 247
30
32
34
Minimum projection area [Å2] Figure 4 – Rejection of small (MPA = 27–35 Å2) and uncharged pesticides by the ESPA2 reverse osmosis (RO) membrane. The pesticides were classified into four categories: secondary (2°) amide pesticides that have (a) no atoms holding a high partial negative charge (PNC), (b) an ether group (high PNC), and (c) atoms holding a high PNC, and (d) pesticides that have no amides. Error bars show the range of duplicate RO treatment experiments. 14
248 249 250 251
Table 2 – Molecular properties of low minimum projection area (MPA) (27–35 Å2) and uncharged secondary amide pesticides that have (a) no atoms holding a high partial negative charge, (b) an ether group. The parameters were calculated using Marvin software (ChemAxon, Budapest, Hungary). Name Structure
Diflubenz uron
Diuron
Chlorotol Cycluron uron
Linuron
Propham Pyracarb Carboxin olid e
a
Classification 2 MPA [Å ] DM [Debye] HB donor HB acceptor Rejection [%]
├──────────(a)──────────┤ 27.9 28.6 29.9 34.6 1.0 6.2 4.3 4.8 2 1 1 1 2 1 1 1 53 34 65 95
├──────────(b)──────────┤ 28.0 32.4 32.9 34.0 6.4 2.3 4.5 4.8 1 1 1 1 2 2 2 2 77 79 72 80
252 253 254
a
–
255
The strength of hydrogen bonds in amide compounds can be reinforced by cooperativity via
256
resonance of the hydrogen bonds (Figure 5a) in a similar way to amides in proteins [38, 39],
257
which may have made the major difference in rejection between secondary amide and no amide-
258
containing pesticides. The cooperativity of hydrogen bonding is likely to be the main cause of
259
the very low rejections of three secondary amide pesticides that have no atoms holding a high
260
partial negative charge (i.e., diflubenzuron, diuron, and chlorotoluron) (34–65%). The only
261
exception was cycluron (rejection = 95%), which holds a cyclooctane in its structure in contrast
262
to the other chemicals with a benzene (Table 2). Unlike benzene that has a planar structure,
263
cyclooctane is conformationally complex and can have because many of its conformers have
264
comparable energy [40]. The chair conformer is the most stable structure of cyclooctane, and the
265
MPA of cycluron (34.6 Å2 in Table 2) was determined based on its stable structure with a chair-
266
like confirmation of cyclooctane (Figure S6). In other words, the MPA of cycluron with other
Hydrogen bond (HB) acceptors and donors with a partial charge of below -0.15 and above 0.15 e at pH 8 are presented with their partial charge in red and blue, respectively. Other atoms with a partial charge of – below -0.15 or above 0.15 e are presented in green.
15
267
conformations can be higher, which can result in a higher rejection of cycluron. However, these
268
speculated mechanisms cannot be further evaluated in this study, because cycluron was the only
269
small chemical that have a cyclooctane in its structure and an MPA of below 35 Å2. There could
270
be some other mechanisms underlying the high rejection of cycluron, thus, further investigation
271
is needed to decode its rejection mechanism.
272
It was also found that secondary amide pesticides can be highly rejected when another atom
273
holding a high partial negative charge is present in the secondary amide structure. The atoms
274
holding a high partial negative charge include an ether functional group (−O−) (e.g. propham)
275
(Table 2), a nitrile functional group (−C≡N) (e.g., flonicamid), trifluoromethyl functional group
276
(R−CF3) (e.g., flonicamid and fluometuron), and a sulfonyl functional group (R−S(=O)2−R’)
277
(e.g., ethidimuron) (Table S3). For example, linuron (C9H10Cl2N2O2, MPA = 28.6 Å2), which
278
has an ether functional group, is very similar to diuron (C9H10Cl2N2O, MPA = 28.0 Å2) in
279
structure and MPA (Table 2), whereas their rejection varied considerably (77% and 34% for
280
linuron and diuron, respectively). Although these functional groups are not dissociated, it can be
281
speculated that their high partial negative charge can cause electrostatic repulsion with HB-A
282
(oxygen atom) of the membrane’s amide that has a high partial negative charge (Figures 5b and
283
5c). The repulsion force may be greater than the attraction force induced by hydrogen bonding,
284
leading to high rejection.
16
285 286 287
Figure 5 – Cooperativity of hydrogen bonding and electrostatic repulsion between an amide functional group of an RO membrane and (a) diuron, (b) propham, or (c) flonicamid.
288
Similar to the uncharged secondary amide pesticides, cooperative hydrogen bonding may be
289
sufficiently strong to impact the rejection of charged secondary amide pesticides. Thidiazuron is
290
a secondary amide pesticide with a negatively charged nitrogen atom at pH 8.0 (Table S3);
291
however, its rejection (43%) was considerably lower than similarly sized counterparts as
292
reported in Figure 1. In contrast, another similarly sized pesticide with a negative charge
293
(quinmerac) holds no amide functional group and showed considerably high rejection (98%).
294
Despite the limited number of samples for small and negatively charged pesticides (i.e., two), the
295
results suggest that hydrogen bond interactions may play a role in the rejection of charged
296
pesticides. Overall, the results obtained in this study suggest that secondary amide pesticides can
297
be poorly rejected by RO membranes due to the electrostatic attraction through hydrogen
298
bonding, whereas their rejection can be sufficiently high depending on the presence of other
299
atoms holding a high partial negative charge.
17
300
4
Conclusions
301
The results of this study indicated that the rejection of small and uncharged pesticides is mainly
302
governed by size exclusion, dipolar interaction, and hydrogen bonding. The amide group of
303
secondary amide pesticides can have the cooperativity of hydrogen bonding with amide
304
functional groups of an RO membrane, which can considerably render their rejection. The
305
presence of an atom holding a high partial negative charge in the secondary amide pesticides
306
leads to higher rejection than pesticides that have no atoms holding a high partial negative charge.
307
This suggests that secondary amide pesticides may be poorly rejected depending on the
308
possession of atoms holding a high partial negative charge. The findings are useful to predict the
309
rejection of unregulated TOrCs, including pesticides, in potable water reuse. In addition, this
310
study confirmed that all 158 pesticides consistently showed higher rejection than NDMA due to
311
the size exclusion and hydrogen bonding, which suggests that NDMA can be a conservative
312
performance indicator for removal of pesticides by RO processes.
313
5
314
This work was supported by JSPS KAKENHI Grant Number JP16KK0132 and JP18H01572.
315
We thank Hydranautics/Nitto for providing RO membrane samples for this investigation. This
316
work is also funded by Singapore Ministry of Education Academic Research Fund Tier 1
317
(M4011732.030), Start Up Grant of Nanyang Technological University (M4081915), Singapore
318
National Environment Agency (M4061617) and Singapore Ministry of Health’s National
319
Medical Research Council under its Clinician-Scientist Individual Research Grant (CS-IRG)
320
(MOH-000141) and Open Fund - Individual Research Grant (OFIRG/0076/2018).
ACKNOWLEDGEMENTS
18
321
6
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22
RESEARCH HIGHLIGHTS: •
Mechanisms underlying the poor rejection of small pesticides by RO were examined
•
Size exclusion, and charge & dipolar interactions play a role in pesticide rejection
•
2° amides holding no high partial negative charge atoms were poorly rejected
•
The low rejections were attributed to the cooperativity of hydrogen bonding
Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:
S0376-7388(19)32185-4
DOI:
https://doi.org/10.1016/j.memsci.2019.117577
Reference:
MEMSCI 117577
To appear in:
Journal of Membrane Science
Received Date: 22 July 2019 Revised Date:
9 October 2019
Accepted Date: 16 October 2019
Please cite this article as: T. Fujioka, H. Kodamatani, W. Yujue, K.D. Yu, E.R. Wanjaya, H. Yuan, M. Fang, S.A. Snyder, Assessing the passage of small pesticides through reverse osmosis membranes, Journal of Membrane Science (2019), doi: https://doi.org/10.1016/j.memsci.2019.117577. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier B.V.
Rejection [%]
100 80 60 40 Diuron
20 0
20
25
30
35
Minimum projection area [Å2]
(Hydrogen bonding)
1
Assessing the passage of small pesticides through reverse osmosis
2
membranes
3
Takahiro Fujioka 1,*, Hitoshi Kodamatani 2, Wang Yujue 3, Koh Dan Yu 3,
4
Elvy Riani Wanjaya 3, Han Yuan 3, Mingliang Fang 3,4, Shane Allen Snyder 3,4
5
1
Graduate School of Engineering, Nagasaki University, 1-14 Bunkyo-machi, Nagasaki 852-8521,
6 7
Japan 2
Division of Earth and Environmental Science, Graduate School of Science and Engineering,
8 9 10 11 12
Kagoshima University, 1-21-35 Korimoto, Kagoshima 890-0065, Japan 3
Analytics Cluster, Nanyang Environment & Water Research Institute (NEWRI), Nanyang
Technological University, 1 Cleantech Loop, CleanTech One, Singapore 637141, Singapore 4
School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
13
_______________________
14
* Corresponding author: Takahiro Fujioka, Email: [email protected], Ph +81 95 819 2695
15
Abstract
16
Attenuation of trace organic chemicals (TOrCs), including pesticides, by reverse osmosis (RO)
17
membrane treatment is critical for ensuring public health protection in potable water reuse. This
18
study aimed to elucidate the mechanisms underlying the poor rejection of small pesticides by
19
polyamide-based RO membranes. Rejection of the selected TOrCs (four N-nitrosamines and 158
20
pesticides) was primarily governed by size exclusion, charge interactions, and dipolar
21
interactions when evaluated at high water temperatures. Further investigation indicated that small
22
and uncharged secondary amide pesticides showed low and highly variable rejections, compared
23
to similarly sized counterparts with no amide functional groups. Remarkably, three secondary
24
amide pesticides that have no other atoms holding a high partial negative charge showed very
25
low rejections (34–65%), likely due to the cooperativity of hydrogen bonding which occurs
26
between amide functional groups of the pesticides and RO membranes. In contrast, secondary
27
amide pesticides that have an atom holding a high partial negative charge showed higher
28
rejections (72–98%) which is due to the inducted electrostatic repulsion. This study proposed
29
that secondary amide pesticides that have no other atoms holding a high partial negative charge
30
can be poorly rejected. The findings are useful to predict the rejection level of unregulated
31
TOrCs.
32
Keywords: secondary amides; trace organic chemicals; NDMA; hydrogen bonding; potable
33
water reuse.
34
1
35
1
INTRODUCTION
36
Potable water reuse has been increasingly adopted in many regions of the world that have been
37
plagued by droughts [1]. It is typically carried out by converting municipal wastewater to highly
38
pure water through advanced wastewater treatment. The majority of recent advanced wastewater
39
treatment systems for potable water reuse include microfiltration (MF) or ultrafiltration (UF),
40
reverse osmosis (RO), and ultraviolet (UV) or UV-based advanced oxidation processes [2].
41
Advanced wastewater treatment using RO plays a role in attenuating salts, pathogens, and trace
42
organic chemicals (TOrCs), which include pesticides, disinfection by-products (DBPs),
43
endocrine disrupting compounds, and pharmaceuticals and personal care products (PPCPs) [3, 4].
44
The attenuation of these TOrCs by an RO process can be ensured through periodical water
45
quality testing by approved analytical methods. However, for continuously ensuring regulatory
46
compliance, the infrequent and costly analysis remains a challenge. To date, no monitoring
47
technique has been fully established to continuously and conservatively ensure the attenuation of
48
TOrCs by the RO process or the integrity of RO membranes for TOrC removal [5].
49
As a surrogate indicator for TOrC removal by RO, the authors have recently suggested a low
50
molecular weight (MW) DBP, N-nitrosodimethylamine (NDMA; MW of 74 g/mol), which can
51
be monitored online using high-performance liquid chromatography followed by photochemical
52
reaction and chemiluminescence detection [6, 7]. The NDMA can be considered as a
53
conservative surrogate because it is not well rejected by RO membranes and is typically
54
identified at higher concentrations than the method detection limit (e.g., 1–2 ng/L) in both RO
55
feedwater and permeate [8]. Previous pilot-scale studies conducted by the authors demonstrated
56
that online monitored NDMA rejection was always lower than the rejection of PPCPs [7].
57
Nevertheless, the reliability of NDMA as a conservative surrogate for TOrC removal is still
2
58
questionable, since its conservativeness cannot be guaranteed with the current knowledge about
59
the rejection mechanisms.
60
Despite many studies addressing the rejection mechanisms of TOrCs over the past decade [9-15],
61
the cause of some poorly rejected TOrCs has not been adequately understood. The rejection of
62
TOrCs at high temperatures is of great interest, because wastewater temperature can vary
63
seasonally and TOrC rejection decreases according to an increase in temperature due to the
64
increasing diffusivity of the solutes [16, 17]. According to the previous studies, the transport of
65
TOrCs through nanofiltration (NF) and RO membranes is governed by three major interactions
66
(i.e., size, charge, and hydrophobicity) that occur between compounds and membranes. The
67
rejection of TOrCs by polyamide-based membranes is primarily governed by size interaction and
68
charge interaction, whereas highly hydrophobic TOrCs (e.g., LogD = ≥ 2) can show lower
69
rejection than hydrophilic TOrCs (e.g., LogD = < 2) [18, 19]. As a result, pesticides, most of
70
which are highly hydrophobic, are of great interest [20, 21]. One notable pesticide is diuron,
71
which is an aromatic pesticide with a relatively high molecular weight of 233 g/mol. For
72
example, Chen et al. [22] reported that the rejection of diuron by a polyamide NF membrane
73
element (50%) was the lowest among 11 selected pesticides with molecular weights of 198–286
74
g/mol (60–100%). Similar observations associated with the low rejection of diuron have been
75
reported elsewhere [23-27]. However, to the best of our knowledge, no basic theory for
76
clarifying the mechanisms of the poorly rejected pesticides has been established.
77
This study aimed to elucidate the mechanisms underlying the poor rejection of several pesticides
78
by polyamide-based RO membranes. The rejection mechanisms were comprehensively assessed
79
by analyzing the role of molecular interactions (i.e., size exclusion, and electrostatic,
3
80
hydrophobic, dipolar, and hydrogen bond interactions) using a diverse range of compounds (four
81
N-nitrosamines and 158 pesticides).
82
2
83
2.1 Chemicals
84
Analytical grade solutions of four N-nitrosamines – NDMA, N-nitrosomethylethylamine
85
(NMEA), N-nitrosopyrrolidine (NPYR), and N-nitrosomorpholine (NMOR) – were purchased
86
from Ultra Scientific (Kingstown, RI, USA). A stock solution containing the N-nitrosamines was
87
prepared at 10 mg/L in pure methanol. In addition to N-nitrosamines, a total of 158 analytical
88
grade pesticides (Agilent Technologies, Singapore) covering a wide range of molecular weights
89
(MWs) and other molecular properties were used in this study (Table 1 and Table S1).
90
Commercial Marvin (version 18.30, ChemAxon, Budapest, Hungary) was used for drawing and
91
characterizing chemical structures, and calculating molecular properties (minimum projection
92
area, LogD, pKa, dipole moment, and counts of hydrogen bond acceptor or donor). The
93
minimum projection area (MPA) of a compound is a two-dimensional projected area of the
94
chemical calculated based on the van der Waals radius (Figure S1). LogD, which is the octanol-
95
water coefficient of the chemical, was calculated at a test solution pH of 8.0. The selected
96
chemicals were determined to be uncharged (≤50% ionized) or charged (>50% positively or
97
negatively charged, or zwitterion). The total dipole moment of a chemical was calculated as a
98
vector expressed in the principal axis frame. Counts of hydrogen bond acceptor or donor were
99
determined at pH 8. Analytical grade NaCl was purchased from Merck KGaA (Darmstadt,
100
Germany) and analytical grade NaHCO3 was purchased from VWR Singpapore Ltd (Singapore).
MATERIALS AND METHODS
4
101
Two stock solutions containing the pesticides were prepared at 5 mg/L in Milli-Q water with 10
102
mM NaCl and 1 mM NaHCO3.
5
103
Table 1: Properties of four N-nitrosamines and 158 pesticides. Compound
104
MW MPA Compound MW MPA Compound 2 2 [g/mol] [Å ] [g/mol] [Å ] Uncharged Dimethachlor 255.7 50.5 Ipconazole NDMA 74.1 19.4 Propyzamide 256.1 39.7 Zoxamide NMEA 88.1 22.3 Ethidimuron 264.3 33.5 Fenbuconazole NPYR 100.1 25.0 Diethofencarb 267.3 53.4 Bitertanol NMOR 116.1 26.9 Silthiofam 267.5 49.6 Tepraloxydim Propham 179.2 32.4 Methoprotryne 271.4 48.6 Propiconazole Acephate 183.2 32.3 Metazachlor 277.8 52.4 Boscalid Fuberidazole 184.2 24.2 Oxadixyl 278.3 47.7 Azinphos-ethyl Molinate 187.3 37.3 Metalaxyl 279.3 53.2 Triflumizole Tricyclazole 189.2 27.7 Propetamphos 281.3 49.7 Tebufenozide Aldicarb 190.3 35.1 Fosthiazate 283.4 42.5 Beflubutamid Butocarboxim 190.3 38.8 Metolachlor 283.8 56.1 Triflumuron Carbendazim 191.2 25.5 Penconazole 284.2 51.1 Chlorfenvinphos DEET 191.3 41.2 Vamidothion 287.3 42.3 Clethodim Trimethacarb 193.2 35.1 Myclobutanil 288.8 50.9 Flufenacet Cycluron 198.3 34.6 Isoprothiolane 290.4 47.4 Benzoximate Pyrimethanil 199.3 31.3 Thiamethoxam 291.7 38.8 Picoxystrobin Thiabendazol 201.3 25.0 Cyproconazole 291.8 49.2 Methoxyfenozide Metamitron 202.2 28.5 Uniconazole-P 291.8 48.0 Tetraconazole Fenobucarb 207.3 44.2 Triadimefon 293.8 47.7 Spirotetramat Promecarb 207.3 38.8 Paclobutrazol 293.8 49.3 Profenofos Quinoclamine 207.6 25.2 Triadimenol 295.8 47.9 Fluquinconazole Aminocarb 208.3 35.5 Imazalil 297.2 46.0 Prochloraz Propoxur 209.2 40.6 Quinalphos 298.3 45.6 Bromuconazole Ethirimol 209.3 34.8 Phoxim 298.3 52.6 Fluopicolide Chlorotoluron 212.7 29.9 Phosphamidon 299.7 45.3 Sulfentrazone Metribuzin 214.3 34.4 Flutriafol 301.3 49.3 Pyraclostrobin Cymiazole 215.4 29.2 Furalaxyl 301.3 54.6 Dimethomorph Pyracarbolid 217.3 32.9 Methidathion 302.3 34.7 Alanycarb Thiofanox 218.3 39.9 Fenamiphos 303.4 49.6 Azoxystrobin Carbofuran 221.3 40.8 Diazinon 304.4 50.7 Difenoconazole Chloridazon 221.6 29.9 Pirimiphos-methyl 305.3 47.9 Trifloxystrobin Mexacarbate 222.3 41.9 Buprofezin 305.4 56.1 Metrafenone Acetamiprid 222.7 30.8 Tebuconazole 307.8 54.1 Mandipropamide Monocrotophos 223.2 41.2 Diflubenzuron 310.7 27.9 Bispyribac Mepanipyrim 223.3 38.0 Fenamidone 311.4 53.1 Fipronil Mevinphos 224.2 40.2 Triazophos 313.3 46.3 Fluoxastrobin Cyprodinil 225.3 37.7 Kresoxim-methyl 313.4 51.2 Chlorantraniliprole Prometon 225.3 46.3 Hexaconazole 314.2 53.0 Flubendiamide Secbumeton 225.3 42.9 Flusilazole 315.4 54.4 Charged (negative) Tebuthiuron 228.3 37.7 Bupirimate 316.4 54.6 Thidiazuron Flonicamid 229.2 27.1 Azinphos-methyl 317.3 29.2 Quinmerac Dimethoate 229.3 35.8 Triticonazole 317.8 51.5 Chlorsulfuron Trietazine 229.7 40.5 Metconazole 319.8 54.2 Amidosulfuron Fluometuron 232.2 32.7 Phenthoate 320.4 55.8 Thifensulfuron-methyl Diuron 233.1 28.6 Iprovalicarb 320.4 52.2 Tribenuron-methyl Lenacil 234.3 36.3 Cyazofamid 324.8 49.2 Triasulfuron Carboxine 235.3 34.0 Flumetsulam 325.3 50.7 Oxasulfuron Pirimicarb 238.3 44.0 Benalaxyl 325.4 57.8 Flazasulfuron Clomazone 239.7 40.1 Diniconazole 326.2 52.2 Nicosulfuron Methacrifos 240.2 36.0 Dimoxystrobin 326.4 62.2 Charged (positive) Ethoprophos 242.3 50.3 Pencycuron 328.8 49.9 Fenpropidin Fludioxonil 248.2 40.3 Epoxiconazole 329.8 48.5 Zwritterion Linuron 249.1 28.0 Halofenozide 330.8 54.9 Imidacloprid Prosulfocarb 251.4 39.1 Fenarimol 331.2 55.4 Thiacloprid 252.7 36.9 Isoxaben 332.4 51.8 * MPA was calculated using Marvin software (ChemAxon, Budapest, Hungary).
6
MW [g/mol] 333.9 336.6 336.8 337.4 341.8 342.2 343.2 345.4 345.8 352.5 355.3 358.7 359.6 359.9 363.3 363.8 367.3 368.5 372.2 373.4 373.6 376.2 376.7 377.1 383.6 387.2 387.8 387.9 399.5 403.4 406.3 408.4 409.3 411.9 430.4 437.2 458.8 483.2 682.4
MPA 2 [Å ] 60.0 46.3 53.8 49.5 42.3 55.4 49.3 46.3 53.2 67.6 54.7 54.8 53.4 50.1 42.2 47.5 54.3 49.1 54.1 57.4 50.1 47.8 58.3 48.7 42.4 45.6 52.3 66.3 73.8 63.5 60.9 58.0 60.8 58.0 54.7 44.1 63.7 68.0 84.2
220.3 221.6 357.8 369.4 387.4 395.4 401.8 406.4 407.3 536.8
25.0 27.7 49.6 50.7 51.1 48.1 55.3 63.7 46.8 57.2
273.5
46.1
255.7
36.9
105
2.2 Membranes and RO treatment
106
This study used a low pressure RO membrane – namely ESPA2, which is widely used in many
107
water recycling projects [8]. The RO membrane was supplied as flat sheet coupons by
108
Hydranautics/Nitto (Osaka, Japan). RO treatment was conducted using a bench-scale system
109
comprised of a stainless steel membrane cell (Iwai Pharma Tech, Tokyo, Japan), high-pressure
110
constant flow pump (KP-12, FLOM, Tokyo, Japan), pressure regulating valve (Swagelok, Solon,
111
OH, USA), and digital flow meter (F7M, Azbil Co., Tokyo, Japan) (Figure S2). The cross-flow
112
membrane cell has an integrated magnetic stirrer for mixing feed solution at the membrane
113
surface to minimize concentration polarization. The membrane cell held a circular flat-sheet
114
membrane coupon with effective surface area of 36.3 cm2. The RO concentrate and permeate
115
were recirculated into the reservoir.
116
Prior to each rejection test, each RO membrane coupon underwent a stabilization phase by
117
treating Milli-Q water at 1000 kPa. Thereafter, the Milli-Q water was replaced with a 200 mL
118
solution containing 10 mM NaCl and 1 mM NaHCO3. RO treatment was conducted at a constant
119
permeate flux of 20 L/m2h, a constant feed flow rate of 30 mL/min, and a constant feed
120
temperature of 35°C. The high temperature was determined to simulate the summer during a
121
long-term operation, which leads to the lowest performance for TOrC removal due to its high
122
temperature. In addition, a stock solution of N-nitrosamines or pesticides was added to the RO
123
feed to achieve 1.0 µg/L or 5.0 µg/L, respectively. It is noted that the rejection tests for four N-
124
nitrosamines and 158 pesticides were separately conducted to avoid interferences with their
125
analysis. The system was then continuously operated for approximately 70 h before collecting
126
samples from the RO feed and permeate. The RO feed and permeate samples were collected in
127
1.5 mL amber vials for the analysis of N-nitrosamines and pesticides. The extended treatment
7
128
period was determined to reach the steady state condition for adsorption, because most pesticides
129
used in this study are hydrophobic (LogD = > 2), and adsorption onto the membrane can cause
130
overestimation of their rejections [28].
131
2.3 Analytical techniques
132
Concentrations of pesticides were analyzed using Agilent 1290 infinity II Binary liquid
133
chromatography (LC) system coupled with Agilent 6460 triple quadrupole (QqQ) mass
134
spectrometer (Agilent Technologies, Santa Clara, CA, USA). The mass spectrometer was fitted
135
with electrospray ionization (ESI) interface in positive and negative mode with Agilent jet
136
stream technology. Identification and quantification of all target compounds were conducted via
137
tandem mass spectrometry. Further information of the pesticide analysis is provided in Text S1
138
and Table S2. Concentrations of four N-nitrosamines were analysed using high-performance
139
liquid
140
chemiluminescence detection (HPLC-AEM-PR-CL) technique [6, 29]. The analysis was
141
performed with an eluent of 1 mM phosphate buffer (pH6.8) and methanol (95:5 v/v) and the
142
sample injection volume of 200 µL.
143
3
144
3.1 Size exclusion and electrostatic interaction
145
The importance of size exclusion on TOrC rejection by polyamide-based RO membranes was
146
evaluated using four N-nitrosamines and 158 pesticides. In general, the rejection of the tested
147
compounds increased with an increase in their molecular weight (Figure 1a). However, many of
148
the uncharged pesticides with molecular weights of 180–300 g/mol showed high variations in
149
rejection. Another two-dimensional parameter, referred to as the minimum projection area
chromatography-inline
anion
exchange
reaction-photochemical
reaction-
RESULTS AND DISCUSSION
8
150
(MPA), appeared to be more strongly correlated with the rejection of uncharged pesticides
151
(Figure 1b). The role of size exclusion can be explained by the phenomena that TOrCs with low
152
two-dimensional areas have more clearance with the free volume hole of the membrane structure,
153
resulting in lower rejection. In fact, when curve fitting with the monomolecular growth model
154
was used, MPA (R2adj = 0.6) showed a better fit than molecular weight (R2adj = 0.5). The results
155
indicate that MPA is a suitable parameter to describe the rejection level of uncharged compounds
156
such as pesticides and N-nitrosamines, which confirms the importance of size exclusion in the
157
rejection of uncharged TOrCs. However, large variations of rejection for uncharged pesticides at
158
an MPA of approximately 27–30 Å2 (e.g., diflubenzuron, diuron, chlorotoluron) (Figure 1b)
159
indicates that size exclusion is not the only mechanism governing TOrC rejection. Therefore, the
160
influence of other chemical properties on the rejection of uncharged TOrCs was further
161
evaluated in the following sections.
162
Evaluating the impact of electrostatic interactions on their rejection was difficult in this study,
163
because almost all of the charged pesticides were large in size and uncharged pesticides with
164
equivalent MPAs were also highly rejected. However, the rejection of negatively charged
165
pesticides was found to be higher than the fitted line of uncharged pesticides, with the exception
166
of the smallest charged pesticide (thidiazuron, 43%) (Figure 1b). In contrast, the rejections of a
167
positively charged pesticide (fenpropidin) and zwitterion (imidacloprid) were equivalent to those
168
of similarly sized uncharged pesticides. The rejection of negatively charged TOrCs by RO
169
membranes can be enhanced with electrostatic repulsion that occurs against the negatively
170
charged membrane surface. The skin layer of the polyamide RO membrane, which is formed by
171
a cross-linking of meta-phenylenediamine and trimesic acid trichloride monomers, has remaining
172
carboxyl functional groups (-COOH) that are dissociated (-COO-) and negatively charged at pH
9
173
8 [30, 31]. However, the cause of the poor rejection of thidiazuron remains unclear. Thus, other
174
molecular properties have been accounted for to explain thidiazuron rejection in Section 3.5.
100
(a) y = A×(1-exp(-k×(x-xc)))
Rejection [%]
80
R2adj = 0.50
60 40
Uncharged N-nitrosamines) Charged (-) Charged (+) Zwitterion
(
20 0 100
200
300
400
680
Molecular weight [g/mol] 100
(b) y = A×(1-exp(-k×(x-xc)))
Rejection [%]
80
R2adj = 0.60
Chlorotoluron
60
Diflubenzuron Thidiazuron
40
Diuron
20 0 20
175 176 177 178 179 180
30
40
50
60
70
80
Minimum projection area [Å2]
Figure 1 – Effect of (a) molecular weight and (b) minimum projection area (MPA) of four Nnitrosamines and 158 pesticides on their rejection by the ESPA2 reverse osmosis (RO) membrane (10 mM NaCl and 1 mM NaHCO3; feed temperature of 35 ºC, permeate flux of 20 L/m2h, and pH of 8.1; error bars show the range of duplicate RO treatment experiments). Rejection data is provided in Figure S3.
10
181
3.2 Hydrophobic interaction
182
Hydrophobicity of TOrCs can also be an important additional factor to vary rejection [20, 32, 33].
183
Rejection of TOrCs with strong hydrophobicity can be lower than that of hydrophilic TOrCs,
184
because the former can be concentrated at the RO membrane surface, leading to an increase in
185
their concentrations in the RO permeate. However, in this study, hydrophobicity alone did not
186
show any correlation with compound rejection (Figure S4), indicating that hydrophobicity
187
interactions are less preferential than size exclusion. Therefore, the impact of hydrophobic
188
interactions on pesticide rejection was evaluated by applying six classifications of
189
hydrophobicity and comparing their rejections at a given MPA (Figure 2). As a result, the
190
impact of hydrophobic interactions on pesticide rejection was not apparent for small and
191
uncharged pesticides (e.g., MPA = < 35 Å2). For example, several hydrophobic compounds
192
(LogD = ≥ 2.0) showed higher rejection than hydrophilic compounds (LogD = < 1.9) when
193
evaluated at equivalent MPAs. This indicates that the rejection of low MPA pesticides is also
194
influenced by factors other than size exclusion and hydrophobic interactions. Therefore, the roles
195
of other molecular interactions for the rejection of uncharged and low MPA compounds (MPA of
196
<35 Å2) were further evaluated in the following sections.
11
100
Rejection [%]
80 LogD 60
5.0–5.9 4.0–4.9 3.0–3.9 2.0–2.9 1.0–1.9 ≤0.9
40 20 0 20
30
40
50
60
70
80
2
Minimum projection area [Å ]
197 198 199 200
Figure 2 – Effect of hydrophobicity on the rejection of uncharged compounds by the ESPA2 reverse osmosis (RO) membrane. The results were obtained from Figure 1. Error bars show the range of duplicate RO treatment experiments.
201
3.3 Dipolar interaction
202
Dipole moment (DM), which is the level of charge separation in a compound, can also influence
203
the rejection of TOrCs [34-36]. Regarding the molecular interaction between dipole TOrCs and
204
the RO membrane surface, the positive end of the dipole TOrCs can be favorably attracted to the
205
negatively charged functional group of an RO membrane (i.e., COO–) (dipole-charge interaction),
206
which can cause an increase in the TOrC concentration at the RO membrane surface and
207
consequently lead to low rejection. The compounds tested in this study hold a diverse range of
208
DM; thus, its impact was comprehensively assessed. The results indicated that highly polar (DM
209
= ≥ 6) compounds, with the exception of diuron, showed a proportional increase in rejection as a
210
function of MPA (Figure 3). Compounds with lower polarity (DM = < 6) showed higher
211
rejections than their similarly sized counterparts, which is in line with the theory (i.e., dipole-
212
charge interaction). It is noted that DM was not the only parameter that determines rejection,
213
because the compounds with DM of 6–7 debye showed a considerable variation in rejection (14– 12
214
88%) (Figure S5). The results indicate that the rejection of uncharged TOrCs varies according to
215
their molecular size and DM. However, seven pesticides (chemicals circled with a dotted line in
216
Figure 3) showed substantially lower rejection than their similarly sized counterparts, indicating
217
that other parameters are involved in governing their rejection. Therefore, further evaluation was
218
conducted with a particular focus on these poorly rejected pesticides.
100 DM
80 Rejection [%]
Propham
≥ 6.0 3.5–5.9 1.0–3.4
60
Carboxine
NPYR
Chlorotoluron Diflubenzuron
40 20
Methi -dathion Pyra -carbolid
NMEA Diuron
NDMA
0 15
20
25
30
35
Minimum projection area [Å2]
219 220 221 222
Figure 3 – Effect of dipole moment (DM) on the rejection of small (MPA = < 35 Å2) and uncharged compounds by the ESPA2 reverse osmosis (RO) membrane. The results were obtained from Figure 1. Error bars show the range of duplicate RO treatment experiments.
223
3.4 Hydrogen bonding
224
The cause of the variation in rejection among the small and uncharged pesticides was evaluated
225
by focusing on their molecular structure and functional groups. Overall, the presence of a
226
secondary amide functional group, −C(O)NH−, in pesticides was found to play a key role in
227
determining their removal. For example, the secondary amide pesticides that have atoms holding
228
a high partial negative charge showed the lowest rejection (34–65%) with the exception of
229
cyluron (Figure 4, Table 2). In contrast, the pesticides holding no amide functional groups were
230
highly rejected (83–96%) with the exception of methidathion (72%). The rejection of secondary
13
231
amide pesticides can be higher when they have an atom holding a high partial negative charge:
232
an ether functional group (−O−) (72–80%) or other strong electronegative (EN) atoms holding a
233
high partial negative charge (93–98%) (Table S3). The impact of a secondary amide group on
234
the rejection of pesticides can be explained by the role of hydrogen bonding. Hydrogen bonding
235
occurs between the hydrogen bond acceptor (HB-A), which has a basic electron lone pair, and
236
the hydrogen bond donor (HB-D), which is a partially stripped proton [37]. The secondary amide
237
of the pesticides contains a HB-A (oxygen atom) and HB-D (hydrogen atom); thus, hydrogen
238
bonding can commonly occur with a HB-D (hydrogen atom) and HB-A (oxygen atom) of the
239
membrane’s polyamide, respectively. Secondary amide pesticides that are attracted to polyamide
240
RO membranes through hydrogen bonding increase in concentration at the RO membrane
241
surface, which ultimately leads to low rejection. (d) No amide (c) 2° amide & an atom holding high PNC (b) 2° amide & an ether functional group (a) 2° amide & no other atoms holding high PNC
100
Fuberidazole
Acephate
Ethidimuron Cycluron
Rejection [%]
Fluometuron
80
Propham
Linuron
Pyracarbolid
60
Carboxine Methidathion
Chlorotoluron Diflubenzuron
40 Diuron
28 242 243 244 245 246 247
30
32
34
Minimum projection area [Å2] Figure 4 – Rejection of small (MPA = 27–35 Å2) and uncharged pesticides by the ESPA2 reverse osmosis (RO) membrane. The pesticides were classified into four categories: secondary (2°) amide pesticides that have (a) no atoms holding a high partial negative charge (PNC), (b) an ether group (high PNC), and (c) atoms holding a high PNC, and (d) pesticides that have no amides. Error bars show the range of duplicate RO treatment experiments. 14
248 249 250 251
Table 2 – Molecular properties of low minimum projection area (MPA) (27–35 Å2) and uncharged secondary amide pesticides that have (a) no atoms holding a high partial negative charge, (b) an ether group. The parameters were calculated using Marvin software (ChemAxon, Budapest, Hungary). Name Structure
Diflubenz uron
Diuron
Chlorotol Cycluron uron
Linuron
Propham Pyracarb Carboxin olid e
a
Classification 2 MPA [Å ] DM [Debye] HB donor HB acceptor Rejection [%]
├──────────(a)──────────┤ 27.9 28.6 29.9 34.6 1.0 6.2 4.3 4.8 2 1 1 1 2 1 1 1 53 34 65 95
├──────────(b)──────────┤ 28.0 32.4 32.9 34.0 6.4 2.3 4.5 4.8 1 1 1 1 2 2 2 2 77 79 72 80
252 253 254
a
–
255
The strength of hydrogen bonds in amide compounds can be reinforced by cooperativity via
256
resonance of the hydrogen bonds (Figure 5a) in a similar way to amides in proteins [38, 39],
257
which may have made the major difference in rejection between secondary amide and no amide-
258
containing pesticides. The cooperativity of hydrogen bonding is likely to be the main cause of
259
the very low rejections of three secondary amide pesticides that have no atoms holding a high
260
partial negative charge (i.e., diflubenzuron, diuron, and chlorotoluron) (34–65%). The only
261
exception was cycluron (rejection = 95%), which holds a cyclooctane in its structure in contrast
262
to the other chemicals with a benzene (Table 2). Unlike benzene that has a planar structure,
263
cyclooctane is conformationally complex and can have because many of its conformers have
264
comparable energy [40]. The chair conformer is the most stable structure of cyclooctane, and the
265
MPA of cycluron (34.6 Å2 in Table 2) was determined based on its stable structure with a chair-
266
like confirmation of cyclooctane (Figure S6). In other words, the MPA of cycluron with other
Hydrogen bond (HB) acceptors and donors with a partial charge of below -0.15 and above 0.15 e at pH 8 are presented with their partial charge in red and blue, respectively. Other atoms with a partial charge of – below -0.15 or above 0.15 e are presented in green.
15
267
conformations can be higher, which can result in a higher rejection of cycluron. However, these
268
speculated mechanisms cannot be further evaluated in this study, because cycluron was the only
269
small chemical that have a cyclooctane in its structure and an MPA of below 35 Å2. There could
270
be some other mechanisms underlying the high rejection of cycluron, thus, further investigation
271
is needed to decode its rejection mechanism.
272
It was also found that secondary amide pesticides can be highly rejected when another atom
273
holding a high partial negative charge is present in the secondary amide structure. The atoms
274
holding a high partial negative charge include an ether functional group (−O−) (e.g. propham)
275
(Table 2), a nitrile functional group (−C≡N) (e.g., flonicamid), trifluoromethyl functional group
276
(R−CF3) (e.g., flonicamid and fluometuron), and a sulfonyl functional group (R−S(=O)2−R’)
277
(e.g., ethidimuron) (Table S3). For example, linuron (C9H10Cl2N2O2, MPA = 28.6 Å2), which
278
has an ether functional group, is very similar to diuron (C9H10Cl2N2O, MPA = 28.0 Å2) in
279
structure and MPA (Table 2), whereas their rejection varied considerably (77% and 34% for
280
linuron and diuron, respectively). Although these functional groups are not dissociated, it can be
281
speculated that their high partial negative charge can cause electrostatic repulsion with HB-A
282
(oxygen atom) of the membrane’s amide that has a high partial negative charge (Figures 5b and
283
5c). The repulsion force may be greater than the attraction force induced by hydrogen bonding,
284
leading to high rejection.
16
285 286 287
Figure 5 – Cooperativity of hydrogen bonding and electrostatic repulsion between an amide functional group of an RO membrane and (a) diuron, (b) propham, or (c) flonicamid.
288
Similar to the uncharged secondary amide pesticides, cooperative hydrogen bonding may be
289
sufficiently strong to impact the rejection of charged secondary amide pesticides. Thidiazuron is
290
a secondary amide pesticide with a negatively charged nitrogen atom at pH 8.0 (Table S3);
291
however, its rejection (43%) was considerably lower than similarly sized counterparts as
292
reported in Figure 1. In contrast, another similarly sized pesticide with a negative charge
293
(quinmerac) holds no amide functional group and showed considerably high rejection (98%).
294
Despite the limited number of samples for small and negatively charged pesticides (i.e., two), the
295
results suggest that hydrogen bond interactions may play a role in the rejection of charged
296
pesticides. Overall, the results obtained in this study suggest that secondary amide pesticides can
297
be poorly rejected by RO membranes due to the electrostatic attraction through hydrogen
298
bonding, whereas their rejection can be sufficiently high depending on the presence of other
299
atoms holding a high partial negative charge.
17
300
4
Conclusions
301
The results of this study indicated that the rejection of small and uncharged pesticides is mainly
302
governed by size exclusion, dipolar interaction, and hydrogen bonding. The amide group of
303
secondary amide pesticides can have the cooperativity of hydrogen bonding with amide
304
functional groups of an RO membrane, which can considerably render their rejection. The
305
presence of an atom holding a high partial negative charge in the secondary amide pesticides
306
leads to higher rejection than pesticides that have no atoms holding a high partial negative charge.
307
This suggests that secondary amide pesticides may be poorly rejected depending on the
308
possession of atoms holding a high partial negative charge. The findings are useful to predict the
309
rejection of unregulated TOrCs, including pesticides, in potable water reuse. In addition, this
310
study confirmed that all 158 pesticides consistently showed higher rejection than NDMA due to
311
the size exclusion and hydrogen bonding, which suggests that NDMA can be a conservative
312
performance indicator for removal of pesticides by RO processes.
313
5
314
This work was supported by JSPS KAKENHI Grant Number JP16KK0132 and JP18H01572.
315
We thank Hydranautics/Nitto for providing RO membrane samples for this investigation. This
316
work is also funded by Singapore Ministry of Education Academic Research Fund Tier 1
317
(M4011732.030), Start Up Grant of Nanyang Technological University (M4081915), Singapore
318
National Environment Agency (M4061617) and Singapore Ministry of Health’s National
319
Medical Research Council under its Clinician-Scientist Individual Research Grant (CS-IRG)
320
(MOH-000141) and Open Fund - Individual Research Grant (OFIRG/0076/2018).
ACKNOWLEDGEMENTS
18
321
6
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RESEARCH HIGHLIGHTS: •
Mechanisms underlying the poor rejection of small pesticides by RO were examined
•
Size exclusion, and charge & dipolar interactions play a role in pesticide rejection
•
2° amides holding no high partial negative charge atoms were poorly rejected
•
The low rejections were attributed to the cooperativity of hydrogen bonding
Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: