Novel method for in situ monitoring of organophosphorus flame

Subscriber access provided by Kaohsiung Medical University

Article

Novel method for in situ monitoring of organophosphorus flame retardants in waters Yitao Zou, Zhou Fang, Yuan Li, Runmei Wang, Hao Zhang, Kevin C Jones, Xinyi Cui, Xinyao Shi, Daixia Yin, Chao Li, Zhaodong Liu, Lena Q. Ma, and Jun Luo Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.8b02480 • Publication Date (Web): 24 Jul 2018 Downloaded from http://pubs.acs.org on July 26, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Analytical Chemistry

1

Novel method for in situ monitoring of organophosphorus flame

2

retardants in waters

3

Yi-Tao Zou1, Zhou Fang1, Yuan Li1, Runmei Wang2, Hao Zhang2, Kevin C. Jones2,

4

Xin-Yi Cui1, Xin-Yao Shi1, Daixia Yin1, Chao Li1, Zhao-Dong Liu1, Lena Q. Ma1,3,

5

Jun Luo1*

6 7

1

8

Environment, Nanjing University, Nanjing, Jiangsu 210023, P. R. China

9

2

State Key Laboratory of Pollution Control and Resource Reuse, School of the

Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, United

10

Kingdom

11 12 13 14 15 16

3

Soil and Water Science Department, University of Florida, Gainesville, Florida 32611, United States

* Corresponding authors, 0086-25-89680632, [email protected]

ACS Paragon Plus Environment

Analytical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

17

Abstract

18

Widespread use of organophosphorus flame retardants (OPFRs) and their

19

ubiquity in waters results in the need for a robust and reliable monitoring technique to

20

better understand their fate and environmental impact. In situ passive sampling using

21

the diffusive gradients in thin-films (DGT) technique provides time-integrated data

22

and is developed for measuring OPFRs here. Ultrasonic extraction of binding gels in

23

methanol provided reliable recoveries for all tested OPFRs. Diffusion coefficients of

24

TCEP, TCPP, TDCPP, TPrP, TBP, and TBEP in the agarose diffusive gel (25 oC) were

25

obtained. The capacity of an HLB binding gel for OPFRs was >115 µg per disc and

26

the binding performance did not deteriorate with time up to 131 d. DGT performance

27

is independent of typical environmental ranges of pH (3.12–9.71), ionic strength (0.1–

28

500 mmol L-1) and dissolved organic matter (0–20 mg L-1), and also of diffusive layer

29

thickness (0.64–2.14 mm), and deployment time (3–168 h). Negligible competition

30

effects between OPFRs was found. DGT-measured concentrations of OPFRs in a

31

wastewater treatment plant (WWTP) effluent (12–16 d) were comparable to those

32

obtained by grab sampling, further verifying DGT’s reliability for measuring OPFRs

33

in waters.


Page 2 of 29

Page 3 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


34

Introduction

35

Organophosphorus flame-retardants (OPFRs) are emerging contaminants which

36

have been widely utilized in polyurethane foam plastic, resin, paint, textiles and

37

building materials.1 OPFRs are relatively water-soluble organic contaminants and

38

many OPFRs are used as additives incorporated into polymer products, rather than

39

chemically bonded to them. They can therefore easily transfer to environmental media,

40

particularly to water. However, some OPFRs, such as chlorinated compounds

41

tris(2-chloroethyl) phosphate (TCEP), tris(2-chloroisopropyl) phosphate (TCPP), and

42

tris(1,3-dichloro-2-propyl) phosphate (TDCPP) cannot be effectively removed from

43

wastewaters by activated sludge treatment and are quite recalcitrant to advanced

44

oxidation process.2 OPFRs concentrations were reported to be around 4 µg L-1 in

45

municipal wastewater effluent in Germany,3 and 7.9–39 µg L-1 in sewage treatment

46

plants effluents in Sweden.4 Consequently, most of these OPFRs were then discharged

47

to the environment through effluent and sludge. OPFRs are therefore ubiquitous in

48

surface water, and have even been reported in tap water and bottled drinking water in

49

many countries.5-9 The concentration of OPFRs were around 5000 ng L-1 in River Aire

50

in United Kingdom,9 from 7.3±4.5 ng L-1 in Lake Huron to 96±43 ng L-1 in Lake Erie

51

in the Great Lakes in America,10 190–2820 ng L-1 in River Oder in Germany,11 and

52

around 1 µg L-1 in Songhua River in Northeast China.12 Tris(2-butoxyethyl) phosphate

53

(TBEP) and TCEP are the most prominent OPFR compounds in some aquatic

54

systems.10,12 Total concentrations of OPFRs have been reported from 85 ng L-1 to 325

55

ng L-1 in tap water and up to 1660 ng L-1 in drinking water.6,13 The most frequently

56

detected compounds in tap water were TBEP, and TCPP and TCEP, TCPP and TBEP

57

in bottled drinking water.

58

Although there has been no report on OPFRs regulations in aquatic system in



59

legislative frameworks, many investigations have focused on their negative effects on

60

human health and ecological systems. This suggests that they may become

61

incorporated in regulatory frameworks in future. TCEP, TCPP, tri-n-butyl phosphate

62

(TBP), and TBEP can be bioaccumulated in fish and be transferred through the

63

aquatic food web.14-17 Concerns over human exposure to OPFRs has focused on

64

endocrine disruption via disturbing steroidogenesis,18 inducing oxidative stress,19 or

65

influencing thyroxine.20 Hence, accurate measurement and monitoring of OPFRs in

66

aquatic systems is necessary to better understand their fate and biogeochemical

67

behavior and to further evaluate their potential effect on ecosystems and human

68

health.

69

Usually OPFRs monitoring is by grab collecting large-volume water samples

70

followed by preconcentration using solid-phase extraction. However, this only

71

provides snapshots of OPFR concentrations at a certain sampling time.6-8,13 The

72

sample treatment is time-consuming and costly. The measurements cannot reflect

73

any daily or weekly concentration fluctuations.21 Passive sampling techniques, which

74

preconcentrate analytes from water to binding agents in situ during field deployment,

75

can overcome these drawbacks

76

better reflect environmental contamination levels and contribute to a more accurate

77

risk assessment of ecosystems and human health. The polar organic chemical

78

integrative sampler (POCIS) has been applied to monitoring organic contaminants,

79

including organophosphate pesticides and EDCs, in waters.22,23 However, a

80

significant limitation of POCIS is that its sampling rates largely depend on

81

hydrodynamic conditions. Calibration carried out in the laboratory, which was used

82

to assess the sampling rate in field conditions, cannot reflect the field conditions.

83

21

and provide time-averaged concentrations, which

The diffusive gradients in thin-films (DGT) technique is independent of


Page 4 of 29

Page 5 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


84

hydrodynamic conditions and hence no calibration is needed for in situ

85

measurements.24 (The principles of the DGT technique are given in the Supporting

86

Information, SI). DGT is well established for measuring various inorganic species in

87

aquatic systems.24-34 Recently DGT has been extended to measuring organic

88

pollutants, such as antibiotics,35,36 bisphenols,37 pesticides,38 house-hold and personal

89

care products (HPCPs),39 and some polar chemicals in waste water treatment

90

plants.40 These developments have made it feasible to use DGT for measuring

91

OPFRs in waters.

92

HLB (Hydrophilic-lipophilic-balanced) resin (N-vinyl pyrrolidone and divinyl

93

benzene copolymer) has been widely used in cartridges to extract polar organics.6,8

94

Here DGT devices containing HLB resin incorporated in agarose gel as binding

95

phase were prepared to effectively sample six frequently detected or studied OPFRs,

96

i.e., TCEP, TCPP, TDCPP, tri-n-propyl phosphate (TPrP), TBP and TBEP for the first

97

time. DGT was evaluated for its performance characteristics under various pH, ionic

98

strength, and dissolved organic matter concentrations which cover the range typically

99

found in the environment. The possible effects of binding kinetics, capacity of the

100

binding gels, deployment time, competition among different OPFRs, storage time of

101

the HLB binding gels, and diffusive gel thickness were also studied. DGT was

102

deployed in wastewater treatment plant effluent in Nanjing, China to evaluate its

103

performance in field conditions.

104

Method and Materials

105

Gel preparation. A standard DGT device consists of a binding gel, a diffusive

106

gel and a filter membrane held in a plastic molding (DGT Research Ltd, UK).37

107

Diffusive gels were prepared using agarose solution following previously published



108

procedures.36,37 Information on the evaluation of possible adsorption of OPFRs onto

109

filter membranes, diffusive gels and DGT moldings is given in the parts of Method

110

and Materials and Results and Discussion of the SI.

111

Binding gels were prepared by adding 3.6g (wet weight) of HLB resins into 18

112

mL of 2% agarose solution (dissolving 0.36 g of agarose in 18 mL of MQ water)

113

when the solution was heated to transparent. The resulting solution was then pipetted

114

into pre-heated glass plates separated by a 0.50 mm thick PTFE spacer. The diffusive

115

gels were made following the same procedure without the resin. When gels were set

116

at room temperature they were then cut into discs of 2.5 cm diameter and stored in

117

0.01 M NaCl solution at 4 ○C.

118

Uptake kinetics and elution efficiencies of HLB gels. Preparation of reagents,

119

materials, and solutions used in the following sections are detailed in the SI. HLB gel

120

discs were immersed in 10 mL of 100 µg L-1 OPFRs solutions and shaken horizontally

121

for various times, from 0.5 min to 24 h. The masses of OPFRs adsorbed by the HLB

122

gel discs was calculated by the difference between the original concentration and the

123

remainder in each sample.

124

Elution efficiencies of OPFRs were assessed by eluting HLB gels pre-loaded with

125

various amounts of OPFRs with 10 mL of methanol. Hence, HLB gels were immersed

126

in 10 mL of 10, 20, 50, 100, and 200 µg L-1 OPFRs solutions containing 0.01 M NaCl,

127

and shaken horizontally for 24h. The OPFRs-loaded HLB gels were extracted using

128

10 mL of methanol in an ultrasonic bath for 30min. The elution and immersion

129

solutions was then filtered using PTFE filter membranes with 0.22 µm pore size and


Page 6 of 29

Page 7 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


130

analyzed using UPLC–MS/MS (Qsight 210, PerkinElmer, USA). Detailed

131

information on instrumental analysis was summarized in SI.

132

Diffusion coefficients. Diffusion coefficients of OPFRs were measured following

133

a previously widely described method, but with a slight modification.27,29,41 In brief,

134

they were measured with two stainless steel compartments connected with a 1.5cm

135

diameter circle window holding a 0.75 mm thick diffusive gel. The source

136

compartment was filled with 50 mL of 0.01 M NaCl solution containing 1 mg·L-1

137

OPFRs, while the receptor compartment contained 50 mL of 0.01 M NaCl solution

138

without any OPFRs. The solution pH in both compartments was the same (5.91 ±

139

0.23). An aliquot of 0.2 mL was removed to glass vials, for further instrumental

140

analysis, from both compartments at intervals of 30 min each time. The experiments

141

were performed at 22.1 ± 0.2○C for 270 minutes. Diffusion coefficients, Dcell,

142

measured in this way were calculated using eq. 1: Dcell =slope

∆g CA

143

(1)

144

Where ∆g is the thickness of agarose diffusive gel, C means concentrations of

145

OPFRs in the source compartment, and A represents the area of the window

146

connecting the two compartments. The slope was obtained by plotting the diffused

147

masses of OPFRs versus diffusion time.

148

Diffusion coefficients, DDGT, of OPFRs were also measured by deploying 8

149

DGT devices in 2.5 L of 20 µg L-1 well-stirred OPFRs solutions for 24 h, assuming

150

DGT-measured concentrations of OPFRs were equal to solution concentrations.



151

Page 8 of 29

DDGT was calculated using a previously reported equation (eq. 2):37 DDGT =

M·∆g C·A·t

152

(2)

153

Where M is the mass accumulated on the HLB binding gels, ∆g is the thickness of

154

the diffusive layer (a diffusive gel and a filter), C is the solution concentration of

155

OPFRs, A is the area of exposure window of the DGT device (2.51 cm2), and t is the

156

deployment time.

157

DGT performance under different conditions. Standard DGT devices

158

containing a 0.5 mm thick HLB binding gel, a 0.75 mm thick agarose diffusive gel,

159

and a 0.14 mm thick, 0.45 µm pore size hydrophilic PTFE filter membrane were

160

deployed in various OPFRs solutions for 24 h to evaluate the effects of pH, ionic

161

strength, and dissolved organic matter on DGT performance. The solutions were (a)

162

2.5 L of 20 µg L-1 OPFRs solutions containing 0.01 M NaCl with a range of pH from

163

3.1 to 9.5; (b) 2.5 L of 20 µg L-1 OPFRs solutions containing various NaCl

164

concentrations ranging from 0.0001 to 0.5 M; and (c) 2.5 L of 20 µg L-1 OPFRs

165

solutions (CNaCl = 0.01 M) with a range of humic acid (Aladdin, fulvic acid ≥ 90%)

166

concentrations, from 0 to 20 mg L-1.

167

To test the effect of deployment time on DGT performance, the DGT devices

168

were deployed in 6 L of 20 µg L-1 OPFRs solutions containing 0.01 M NaCl and

169

retrieved at different time (from 3 h to 168 h). To explore the dependence of mass

170

taken up by DGT on diffusive gel thicknesses, DGT devices with various thicknesses

171

of agarose diffusive gels were immersed in 2.5 L of 20 µg L-1 OPFRs solutions


Page 9 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


172

containing 0.01 M NaCl for 24 h.

173

Capacity and competition effect. To measure the capacity of DGT to

174

accumulate OPFRs, the DGT devices were deployed in 2.5 L of well-stirred solutions

175

containing 0.01 M NaCl with OPFRs concentrations ranging from 20 to 1800 µg L-1

176

for 24h.

177

To investigate potential competition effect among OPFRs, six studied OPFRs

178

were divided into 2 groups: alkyl OPFRs (TBP, TBEP, and TPrP) and chlorinated

179

alkyl OPFRs (TCEP, TCPP, and TDCPP). DGT devices were immersed in various

180

mixed solutions: (a) alkyl OPFRs were at 20 µg L-1, while the others were at 100 or

181

1000 µg L-1 respectively; (b) alkyl OPFRs were at 100 µg L-1, while the others were at

182

20 or 1000 µg L-1 respectively; (c) alkyl OPFRs were at 1000 µg L-1, while the others

183

were at 20 or 100 µg L-1, respectively.

184

DGT tests in situ in field trials. To further test the robustness of DGT for

185

measuring OPFRs in the real environment, the devices were applied to monitor

186

concentrations of OPFRs in a wastewater treatment plant (WWTP), which was mainly

187

for treating domestic sewage with anaerobic-anoxic-oxic (A2/O) treatment process in

188

Nanjing. The capacity of sewage treatment is about 100,000 m3 d-1. The DGT

189

deployments were carried out for 12–16 days. Six DGT devices were assembled into

190

hexahedral units to allow each DGT device to have the same chance to accumulate

191

OPFRs from water.27,37,42 A temperature button data logger was set with each

192

hexahedral unit to record the water temperature every 180 minutes. On retrieval, DGT

193

devices were immediately transported to the laboratory, HLB binding gels were eluted



194

with 10 mL methanol in an ultrasonic bath for 30 minutes. Water samples (0.5 L) were

195

collected from each sampling site every 2–3 days during the DGT deployment and

196

concentrated with HLB cartridges (Waters, 6 cc 150 mg), followed by elution twice

197

with 5 mL of methanol. The two eluents were merged. Both HLB binding gel eluents

198

and cartridge eluents were evaporated to near dryness under a gentle stream of

199

nitrogen, and then re-dissolved with 0.5 mL of methanol for further instrumental

200

analysis.

201

Results and Discussion

202

Uptake kinetics of OPFRs onto HLB gels. Accumulated OPFRs on HLB

203

binding gels increased almost linearly with time in the first 30 minutes. More than 80%

204

of OPFRs were bound onto the HLB gels after 60 minutes (Figure 1and Figure S3).

205

The average binding rates of the analytes over the first 30 minutes were 2.42, 2.20,

206

2.02, 2.06, 1.79, and 1.55 ng min-1 cm-2 for TCEP, TCPP, TDCPP, TPrP, TBP and

207

TBEP, respectively. They were much higher than those calculated from DGT devices

208

deployed in 200 µg L-1 OPFRs solutions for 24 h at 24 oC (1.02, 0.70, 0.73, 0.86, 0.74

209

and 0.66 ng min-1 cm-2 for TCEP, TCPP, TDCPP, TPrP, TBP and TBEP, respectively).

210

It suggests HLB gels can adsorb OPFRs rapidly enough to ensure OPFRs

211

concentration at the interface between the diffusive gel and HLB binding gel is

212

effectively zero, which is a requirement for the DGT technique.24

213

Elution efficiencies of OPFRs loaded on HLB gels. Reliable elution

214

efficiencies of OPFRs are required for accurate calculation of DGT-measured

215

concentrations using eq. S1. Consistent and stable elution efficiencies of 100% were


Page 10 of 29

Page 11 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


216

obtained for the OPFRs using 10 mL of methanol across a series of exposure

217

concentrations (10–200 µg L-1) by extraction in an ultrasonic bath for 30 min (Table

218

S3). High elution efficiencies here are consistent with XAD 18 binding gels for

219

antibiotics 35 and MIP binding gels for 4-chlorophenol.43 They are also comparable to

220

HLB binding gels for HPCPs

221

bisphenols (52–62%) 37 and MAX binding gels for pesticides (46–86%).38

39

and pesticides,38 but higher than AC binding gels for

222

DGT blanks and method quantitation limits. Table 1 summarizes DGT blank

223

concentrations, instrument quantitation limits (IQLs) and DGT method quantitation

224

limits (MQLs) of OPFRs. DGT blank concentrations of OPFRs were achieved by

225

measuring the mass of the analytes on HLB binding gels retrieved from DGT devices

226

which were assembled and left for 24h without deployment. Table 1 shows that 4 of

227

the studied OPFRs were detected in the HLB gels with quite low concentrations

228

(0.01–0.22 ng per disc), with a little higher detection of TCEP and TCPP (0.75 ± 0.32

229

and 1.51 ± 0.34 ng per disc). External standard calibration with six OPFRs (0.01–50

230

µg L-1) were used for quantification. IQL was defined as the lowest point on the

231

calibration curve which could be accurately measured within ±20% of its nominal

232

value. MQLs were calculated from IQLs, assuming a DGT device with a 0.75 mm

233

thick diffusive gel and a 0.14 mm thick filter membrane was deployed for 14 days at

234

25 oC. MQLs of the DGT method ranged from 0.25 to 0.32 ng L-1 for the studied

235

OPFRs (Table 1). OPFRs in fresh water were 7.3–96 ng L-1 in the North American

236

Great Lakes,10 0.6–0.8 µg L-1 in the River Tiber (Italy) 5 and ~1 µg L-1 in the Songhua

237

River, China.12 In WWTPs, reported concentrations of OPFRs were 3.67–150 µg L-1



Page 12 of 29

238

in Spain,2 3.3–16.3 µg L-1 in Germany,8 and 0.8–1.4 µg L-1 in China.44 Given the

239

much lower values of the MQLs for OPFRs than reported concentrations in surface

240

water and WWTPs, DGT coupled with UPLC-MS/MS have the required sensitivity

241

for measurement of OPFRs in waters. If the concentrations of OPFRs in some

242

samples were < MQLs, a longer deployment time or merging two or more HLB

243

binding gels into one sample will improve the measurable mass and reduce the MQLs.

244

Measurement of diffusion coefficient. For use of the DGT method it is vital to

245

accurately measure diffusion coefficients of targeted analytes. The measurements

246

were carried out and good linear relationships (r2 = 0.98–0.99) of diffused masses

247

versus time were obtained (Figure S4) using diffusion cell device. Dcell was calculated

248

using eq. 1 and calibrated to 25 ○C using eq. 336: log Dt =

1.37023t-25+8.36×10-4 t-252 D25 273+t + log 298 109+t

249

(3)

250

The Dcell diffusion coefficients at 25 ○C were 5.87×10-6, 5.56×10-6, 5.11×10-6,

251

5.53×10-6, 4.99×10-6 and 4.58×10-6 cm2 s-1 for TCEP, TCPP, TDCPP, TPrP, TBP and

252

TBEP, respectively. They are similar to the values of DDGT (6.37×10-6, 5.34×10-6, 4.63

253

×10-6, 5.82×10-6, 5.32×10-6 and 4.06×10-6 cm2 s-1 for TCEP, TCPP, TDCPP, TPrP,

254

TBP and TBEP, respectively) using DGT devices in a well-stirred OPFRs solutions

255

for 24h. The ratios of Dcell to DDGT for all selected OPFRs were in the range from

256

0.89–1.09, (Table S4) indicating the accuracy of diffusion coefficients measured by

257

diffusion cell.

258

Previous studies demonstrated that diffusion coefficients of chemicals are


Page 13 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


259

influenced by their octanol-water partition coefficient (log Kow).36,41 The Kow reflects

260

the hydrophilicity of analytes, which can influence the diffusion process through

261

diffusion layers. Thus, we further explored the relationship between D and log Kow. A

262

good linear relationship (eq. 4, r2 = 0.98) was obtained for chlorinated alkyl OPFRs

263

(TCEP, TCPP, and TDCPP) and two alkyl OPFRs (TPrP and TBP) (Figure 2), which

264

have similar chemical structures (Figure S1). Dcell = 6.411 - 0.344 log KOW

265

(4)

266

This relationship may apply to the calculation of D for other OPFRs, which were not

267

included in our study but have similar chemical structures. However, OPFRs with

268

different structures, such as TBEP, did not satisfy this equation.

269

DGT performance under different conditions. Solution pH could potentially

270

influence adsorbent surface properties and the diffusion of the target analytes and thus

271

affect the DGT measurement. Although changing solution pH (3.12–9.71) did not

272

significantly affect the DGT measurement of OPFRs, with CDGT/Csoln ranging from

273

0.87 to 1.09 (Figure 3), the variability of DGT measurement increased at either end of

274

the pH range, especially at pH 9.71. This could be caused by changes of OPFRs

275

species and accompanying diffusion coefficient change or uncertain effects on

276

adsorbent surface. Results indicate DGT can accurately measure OPFRs, but more

277

attention should be paid when deployment solutions are relatively acid or alkaline and

278

more replicates (not less than 3) are recommended.

279

The effect of ionic strength (IS) on DGT performance for measuring OPFRs is



280

demonstrated in Figure S5. The result indicates that most of the OPFRs studied were

281

not significantly influenced by IS in solutions containing 0.0001-0.1 M NaCl, with

282

most ratios of CDGT/Csoln in the range of 0.9–1.1 (Figure S5). When IS concentration

283

increased to 0.5 M, the ratios of CDGT/Csoln for TCEP, TPrP and TBP remained in the

284

range of 0.9–1.1, but for other tested chemicals were slightly lower than expected. No

285

significant reduction in CDGT/Csoln was observed (ANOVA, p < 0.05). IS could

286

potentially change the charge density and thus influence the diffusion process of

287

tested chemicals.26 TDCPP and TBEP, with more chlorine atoms and oxygen atoms,

288

are more susceptible to charge density change. A similar phenomenon was previously

289

observed when XAD gels were used for illicit drugs and the possible reason was the

290

reduced hydrophilicity of tested chemicals at high IS.45

291

No significant effect of DOM on DGT measurement was observed in this study.

292

The ratios of CDGT/Csoln for most of the tested OPFRs in solution containing 0–20 mg

293

L-1 DOM were between 0.9–1.12 (Figure S6). DOM tends to bind more hydrophobic

294

organic compounds with higher log Kow,46,47 resulting in bound analytes with larger

295

chemical structures which are difficult to pass through the diffusion layer. Tested

296

OPFRs are relatively hydrophilic with lower log Kow, (Table S1) and thus were less

297

influenced. Similar phenomena were observed in Chen et al.’s39 study on DGT

298

performance for HPCPs, where the ratios of CDGT/Csoln of five HPCPs still stay within

299

acceptable range when DOM concentration increased. Our study indicates that DGT

300

is an effective tool for measuring OPFRs under typical environmental conditions

301

covering a wide range of pH, IS and DOM.


Page 14 of 29

Page 15 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


302

Effect of diffusive gel thickness and deployment time. Accumulated masses of

303

OPFRs by DGT devices containing diffusive gels of different thickness correlated

304

with the reciprocal of the thickness (0.64–2.14 mm) of the diffusive layers (Figure S7).

305

The data points are very close to the theoretical line for all the compounds tested. This

306

indicates the concentrations of OPFRs can be measured accurately using the DGT

307

technique.

308

Longer-time deployment of DGT can be used when relatively low concentrations

309

may occur in waters.36,37,39,45 The robustness and reliability of DGT in long-time

310

deployment is vital. DGT-measured masses of OPFRs had a linear correlation with the

311

increasing deployment time (3–168 h) and fitted well with the theoretical lines

312

calculated from the known concentrations of deployment solutions using eq. S1

313

(Figure S8). The results are in accordance with Chen et al.’s study on HPCPs with

314

DGT devices containing HLB gels, where the accumulated masses of HPCPs

315

increased linearly with increasing deployment time over 120 h.39

316

Binding capacity and competition among OPFRs. Enough capacity is critical

317

for deployments of long-time or in heavily polluted areas. Accumulated masses of

318

OPFRs measured by DGT linearly increased with their increasing solution

319

concentrations. As shown in Figure 4, DGT devices can simultaneously accumulate

320

25.5, 25.0, 19.9, 18.8, 12.9 and 11.9 µg of TCEP, TCPP, TDCPP, TPrP, TBP and TBEP,

321

respectively when the deployment solution concentrations reached around 1800 µg L-1.

322

The capacity of HLB gels for binding OPFRs is much higher than 115 µg per disc,

323

which is comparable to that of XAD 18 gels for antibiotics (0.18 mg per disc)35 and



324

AC gels for bisphenols (140-194 µg per disc).37 The total capacity for OPFRs here is

325

higher than reported capacities of HLB gels and MAX gels for anionic pesticides (52

326

and 50 µg per disc for HLB gel and MAX gel, respectively) prepared by Guibal et al..

327

38

328

concentration of OPFRs at deployment sites is 30 µg L-1, DGT could theoretically be

329

deployed for about 10 months. However, given that long-term deployments may be

330

hampered by practical problems, such as biofilm growth on filter membranes, it is

331

suggested deployment times should be shorter than the theoretical 10 months. When

332

the total concentration of OPFRs is up to 300 µg L-1, DGT can perform for 4 weeks.

333

Reported concentrations of OPFRs were usually at ng L-1 levels in surface waters

334

5,10,12

335

binding capacities of DGT devices are enough for monitoring OPFRs in aquatic

336

system.

The maximum effective capacities in this study were not reached. If the total

and from ng L-1 to several µg L-1 level in WWTPs.8,9,44 Therefore, the measured

337

DGT devices were deployed in a series of synthetic solutions with different

338

concentration ratios (20–1000 µg L-1) of OPFRs to evaluate whether they would

339

interfere each other through competitive binding. Table S5 lists the CDGT/Csoln values

340

of the studied OPFRs in solutions containing different concentration ratios of OPFRs.

341

No evident interferences among tested chemicals were found, indicating potential

342

competition effects between OPFRs are probably negligible for conditions tested.

343

Field Trial at a WWTP effluent. For field deployment, the storage of the DGT

344

devices was investigated for up to 131 days. DGT performance was not affected by

345

the storage time (Table S6). To verify DGT field performance, the devices were


Page 16 of 29

Page 17 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


346

deployed in situ in the effluent of a WWTP in Nanjing, China for 12–16 days in this

347

study (24 ○C, pH 7.14). All tested chemicals, except TPrP, were detected in the

348

effluent of the WWTP (Figure 5). Total OPFRs concentrations obtained by grab

349

sampling during 12-day and 16-day deployment campaigns were 267.9 ± 31.2 and

350

265.4 ± 30.9 ng L-1, respectively, indicating a relatively stable state of OPFRs

351

concentrations in the effluent of the WWTP. The concentrations of OPFRs are much

352

lower than those reported for other WWTPs, including WWTPs in Spain (µg L-1

353

level),2 Sweden (7.9–39 µg L-1),4 and Austria (several µg L-1).48 This could be because

354

the selected WWTP was located in a rural area and received less polluted discharges

355

than the industrial wastewaters received by other WWTPs reported with high

356

concentrations of OPFRs.3,4 However, OPFRs concentrations in selected WWTP

357

effluent are comparable to that in an industrial WWTP in Germany (397 ng L-1).3

358

Most of the DGT measured concentrations were within the maximum and minimum

359

grab-sampling measured values (Figure 5), demonstrating DGT is suitable for

360

measuring OPFRs in effluents of WWTPs.

361

Conclusions. This work established a novel method for in situ monitoring

362

OPFRs in waters and WWTP using DGT technique. The method provides stable and

363

reliable time-integrated recoveries for all tested OPFRs and is not limited by pH, ionic

364

strength and dissolved organic matters, showing capability in a wide range

365

environmental conditions. The capacity of DGT device is large enough for long-time

366

deployment without any competition effect or deterioration. Method quantitation

367

levels of sub ng L -1 make it an appropriate technique for measuring OPFRs in areas



368

with ultra-low concentrations. Compared to other passive samplers the ease-of-use

369

due to their independence of flow rate and no calibration needed would make the

370

DGT method an applicable technique for in situ monitoring OPFRs in various types

371

of waters and aquatic systems. The DGT method is rarely dependent of sample matrix,

372

thus can further be applied to various complicated environment, including highly

373

polluted wastewater and even seawaters.

374 375

376

Supporting Information

377

Detailed principles of DGT technique and detailed information on tested chemicals,

378

analytical methods and QA/QC are provided. Detailed information on methods to

379

check potential adsorption onto materials and aging effect; Results and discussion on

380

potential adsorption onto materials and aging effect; Tables and figures of potential

381

adsorption onto materials, elution efficiencies, diffusion coefficients, uptake kinetics,

382

effects of IS, DOM, diffusive gel thickness, deployment time, binding gel storage

383

time, and competition binding are provided as well.

ASSOCIATED CONTENT

384 385

ACKNOWLEDGEMENTS

386

This work was supported by Major Science and Technology Program for Water

387

Pollution Control and Treatment (Grant No. 2017ZX07302-001) and the National

388

Natural Science Foundation of China (No. 41771271) and the program for

389

Postgraduates Research and Innovation in Jiangsu Province (No. SJLX16_0023). We

390

are grateful to Ruiwen He from Utrecht University for help with the preparations of


Page 18 of 29

Page 19 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


391

this research and Chengyuan Cai from PerkinElmer for help with instrumental

392

analysis.

393 394

References

395

(1) Reemtsma, T.; Quintana, J. B.; Rodil, R.; Garcı´a-López, M.; Rodrı´guez, I. TrAC, Trends

396

Anal. Chem. 2008, 2008 27, 727-737.

397

(2) Cristale, J.; Ramos, D. D.; Dantas, R. F.; Machulek Junior, A.; Lacorte, S.; Sans, C.;

398

Esplugas, S. Environ. Res. 2016, 2016 144, 11-18.

399

(3) Fries, E.; Püttmann, W. J. Environ. Monit. 2003, 2003 5, 346-352.

400

(4) Marklund, A.; Andersson, B.; Haglund, P. Environ. Sci. Technol. 2005, 2005 39, 7423-7429.

401

(5) Bacaloni, A.; Cavaliere, C.; Foglia, P.; Nazzari, M.; Samperi, R.; Lagana, A. Rapid

402

Commun. Mass Spectrom. 2007, 2007 21, 1123-1130.

403

(6) Li, J.; Yu, N.; Zhang, B.; Jin, L.; Li, M.; Hu, M.; Zhang, X.; Wei, S.; Yu, H. Water Res. 2014, 2014

404

54, 53-61.

405

(7) Schreder, E. D.; La Guardia, M. J. Environ. Sci. Technol. 2014, 2014 48, 11575-11583.

406

(8) Rodil, R.; Quintana, J. B.; Reemtsma, T. Anal. Chem. 2005, 2005 77, 3083-3089.

407

(9) Cristale, J.; Katsoyiannis, A.; Chen, C. e.; Jones, K. C.; Lacorte, S. Environ. Pollut. 2013, 2013

408

172, 163-169.

409

(10) Venier, M.; Dove, A.; Romanak, K.; Backus, S.; Hites, R. Environ. Sci. Technol. 2014, 2014 48,

410

9563-9572.

411

(11) Fries, E.; Püttmann, W. J. Environ. Monit. 2001, 2001 3, 621-626.

412

(12) Wang, X.-W.; Liu, J.-F.; Yin, Y.-G. J. Chromatogr. A 2011, 2011 1218, 6705-6711.



413

(13) Lee, S.; Jeong, W.; Kannan, K.; Moon, H.-B. Water Res. 2016, 2016 103, 182-188.

414

(14) Wang, G.; Shi, H.; Du, Z.; Chen, H.; Peng, J.; Gao, S. Environ. Pollut. 2017, 2017 229,

415

177-187.

416

(15) Arukwe, A.; Carteny, C. C.; Moder, M.; Bonini, A.; Maubach, M. A.; Eggen, T. Environ.

417

Res. 2016, 2016 148, 63-71.

418

(16) Giulivo, M.; Capri, E.; Kalogianni, E.; Milacic, R.; Majone, B.; Ferrari, F.; Eljarrat, E.;

419

Barcelo, D. Sci. Total Environ. 2017, 2017 586, 782-791.

420

(17) Greaves, A. K.; Letcher, R. J.; Chen, D.; McGoldrick, D. J.; Gauthier, L. T.; Backus, S. M.

421

Environ. Res. 2016, 2016 150, 255-263.

422

(18) Zhang, Q.; Wang, J.; Zhu, J.; Liu, J.; Zhao, M. Environ. Sci. Technol. 2017, 2017 51,

423

5803-5810.

424

(19) Chen, G.; Jin, Y.; Wu, Y.; Liu, L.; Fu, Z. Environ. Toxicol. Pharmacol. 2015, 2015 40, 310-318.

425

(20) Fernie, K. J.; Palace, V.; Peters, L. E.; Basu, N.; Letcher, R. J.; Karouna-Renier, N. K.;

426

Schultz, S. L.; Lazarus, R. S.; Rattner, B. A. Environ. Sci. Technol. 2015, 2015 49, 7448-7455.

427

(21) Chen, C.-E. Journal of Environment and Health Sciences 2015, 2015 1, 1-2.

428

(22) Petty, J. D.; Huckins, J. N.; Alvarez, D. A.; Brumbaugh, W. G.; Cranor, W. L.; Gale, R. W.;

429

Rastall, A. C.; Jones-Lepp, T. L.; Leiker, T. J.; Rostad, C. E.; Furlong, E. T. Chemosphere

430

2004, 2004 54, 695-705.

431

(23) Zhang, Z.; Hibberd, A.; Zhou, J. L. Anal. Chim. Acta 2008, 2008 607, 37-44.

432

(24) Davison, W.; Zhang, H. Nature 1994 1994, 94 367, 546-548.

433

(25) Luo, J.; Zhang, H.; Santner, J.; Davison, W. Anal. Chem. 2010, 2010 82, 8903-8909.

434

(26) Lucas, A.; Rate, A.; Zhang, H.; Salmon, S. U.; Radford, N. Anal. Chem. 2012, 2012 84,


Page 20 of 29

Page 21 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


435

6994-7000.

436

(27) Pan, Y.; Guan, D.-X.; Zhao, D.; Luo, J.; Zhang, H.; Davison, W.; Ma, L. Q. Environ. Sci.

437

Technol. 2015, 2015 49, 14267-14273.

438

(28) Guan, D.-X.; Williams, P. N.; Xu, H.-C.; Li, G.; Luo, J.; Ma, L. Q. J. Hazard. Mater. 2016, 2016

439

316, 69-76.

440

(29) Zhou, C.-Y.; Guan, D.-X.; Williams, P. N.; Luo, J.; Ma, L. Q. Water Res. 2016, 2016 99,

441

200-208.

442

(30) Zhang, H.; Davison, W. Anal. Chem. 1995, 1995 67, 3391-3400.

443

(31) Zhang, H.; Davison, W.; Gadi, R.; Kobayashi, T. Anal. Chim. Acta 1998, 1998 370, 29-38.

444

(32) Guan, D.-X.; Williams, P. N.; Luo, J.; Zheng, J.-L.; Xu, H.-C.; Cai, C.; Ma, L. Q. Environ.

445

Sci. Technol. 2015, 2015 49, 3653-3661.

446

(33) Luo, J.; Yin, D.; Cheng, H.; Davison, W.; Zhang, H. Environ. Sci. Technol. 2018, 2018 52,

447

5085-5093.

448

(34) Han, C.; Williams, P. N.; Ren, J.; Wang, Z.; Fang, X.; Xu, D.; Xie, X.; Geng, J.; Ma, L. Q.;

449

Luo, J. Water Res. 2018, 2018 137, 281-289.

450

(35) Chen, C.-E.; Zhang, H.; Jones, K. C. J. Environ. Monit. 2012, 2012 14, 1523-1530.

451

(36) Chen, C.-E.; Zhang, H.; Ying, G.-G.; Jones, K. C. Environ. Sci. Technol. 2013, 2013 47,

452

13587-13593.

453

(37) Zheng, J.-L.; Guan, D.-X.; Luo, J.; Zhang, H.; Davison, W.; Cui, X.-Y.; Wang, L.-H.; Ma, L.

454

Q. Anal. Chem. 2015, 2015 87, 801-807.

455

(38) Guibal, R.; Buzier, R.; Charriau, A.; Lissalde, S.; Guibaud, G. Anal. Chim. Acta 2017, 2017 966,

456

1-10.



457

(39) Chen, W.; Li, Y.; Chen, C.-E.; Sweetman, A. J.; Zhang, H.; Jones, K. C. Environ. Sci.

458

Technol. 2017, 2017 51, 13274-13281.

459

(40) Challis, J. K.; Hanson, M. L.; Wong, C. S. Anal. Chem. 2016, 2016 88, 10583-10591.

460

(41) Zhang, H.; Davison, W. Anal. Chim. Acta 1999, 1999 398, 329-340.

461

(42) Guan, D.-X.; Li, Y.-Q.; Yu, N.-Y.; Yu, G.-H.; Wei, S.; Zhang, H.; Davison, W.; Cui, X.-Y.;

462

Ma, L. Q.; Luo, J. Water Res. 2018, 2018 144, 162-171.

463

(43) Dong, J.; Fan, H.; Sui, D.; Li, L.; Sun, T. Anal. Chim. Acta 2014, 2014 822, 69-77.

464

(44) Liang, K.; Liu, J. Sci. Total Environ. 2016, 2016 544, 262-270.

465

(45) Guo, C.; Zhang, T.; Hou, S.; Lv, J.; Zhang, Y.; Wu, F.; Hua, Z.; Meng, W.; Zhang, H.; Xu, J.

466

Environ. Sci. Technol. 2017, 2017 51, 9101-9108.

467

(46) Pan, B.; Ning, P.; Xing, B. Environ. Sci. Pollut. Res. Int. 2008 2008, 08 15, 554-564.

468

(47) Bohm, L.; Schlechtriem, C.; During, R.-A. Environ. Sci. Technol. 2016, 2016 50, 8316-8323.

469

(48) Martinez-Carballo, E.; Gonzalez-Barreiro, C.; Sitka, A.; Scharf, S.; Gans, O. Sci. Total

470

Environ. 2007, 2007 388, 290-299.

471 472 473


Page 22 of 29

Page 23 of 29

1.0 Mass of TCEP(µg)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


1.0

0.5 0.5

0.0

0.0

0

474 475 476

0

20

200

40

1000

60

1500

Time (min)

Figure 1. Mass of TCEP accumulated by HLB gels in 10 mL solutions containing 0.01 M NaCl and 100 µg L-1 tested OPFRs for 0.5 min to 24 h.

477 478


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

479 480 481 482 483

Diffusion Coefficient (10-6 cm2 s-1)


Page 24 of 29

7 Dcell = 6.411 - 0.344 log KOW r2 = 0.98

6 TCEP

TCPP TPrP

5

TDCPP TBP TBEP

4 0

1

2 3 log KOW

4

5

Figure 2. Dependence of diffusion coefficients on log KOW, solid line was obtained from the linear regression between diffusion coefficients and log KOW values of TCEP, TCPP, TDCPP, TPrP and TBP.


Page 25 of 29

1.4

TCEP

TCPP

TDCPP

TPrP

TBP

TBEP

1.2 1.0

CDGT/Csoln

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


0.8 0.6 0.4 0.2 0.0 3.12

484 485 486 487 488 489 490 491

4.7

6.81 pH

8.36

9.71

Figure 3. Effects of pH on the ratio of DGT-measured OPFRs concentrations, CDGT, to their concentrations in the bulk solution, Csoln. All experiments were performed in solutions of nominally 20 µg L-1 OPFRs, containing 0.01 M NaCl. The solid lines represent the target value of 1.00. Values were expressed as mean ± standard deviation of at least three replicates.



492 493 494 495 496 497 498

Figure 4. Measured masses of TCEP, TCPP, TDCPP, TPrP, TBP, and TBEP accumulated by HLB binding gels within DGT devices deployed in well-stirred solutions at a wide range of concentrations (20–1800 µg L-1), containing 0.01 M NaCl. The solid line represents the theoretical values predicted from the known solution concentrations using eq. S1. Error bars were calculated from at least three replicates.


Page 26 of 29

Page 27 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


499 500 501 502 503 504 505 506 507 508 509 510

Figure 5. Concentrations of TCEP, TCPP, TDCPP, TPrP, TBP, and TBEP in a wastewater treatment plant in Nanjing measured by grab sampling method and DGT over a 12 d or 16 d sampling and deployment campaign. The solid line represents the average concentrations of analytes measured by DGT. The upper and the lower dash lines represent the maximum and minimum concentrations of analytes measured by DGT, respectively. The dots in different shapes and colors represent the concentrations of different analytes measured by grab sampling method at different time. Data in (a1-f1) represent the 12d DGT-measured concentrations of TCEP, TCPP, TDCPP, TPrP, TBP, and TBEP, respectively. Data in (a2-f2) represent the 16d DGT-measured concentrations of TCEP, TCPP, TDCPP, TPrP, TBP, and TBEP, respectively. TPrP was not detected by neither grab sampling nor DGT deployment.

511 512



513 514 515

516 517 518

Page 28 of 29

Table 1. DGT blank, instrument quantitation limits (IQLs) of OPFRs detected by UPLC-MS/MS and method quantitation limits (MQLs) for both water and DGT samples during field application. Blank, ng Recoveries MQL c, ng L-1 a o b per disc, IQL , D at 25 C , of SPE, % Compound -1 µg L 10-6 cm2 s-1 (mean ± (average ± Water DGT SD), n = 12 SD), n = 3 TCEP 0.75 ± 0.32 0.1 88.2 ± 8.2 5.87 0.25 0.11 TCPP 1.51 ± 0.34 0.1 102 ± 12.1 5.56 0.10 0.26 TDCPP 0.15 ± 0.07 0.1 93.9 ± 3.8 5.11 0.11 0.29 TPrP 0.22 ± 0.07 0.1 69.5 ± 4.1 5.53 0.14 0.26 TBP 0.11 ± 0.05 0.1 66.6 ± 1.7 4.99 0.15 0.29 TBEP 0.01 ± 0.00 0.1 82.4 ± 5.7 4.58 0.12 0.32 a IQLs: the lowest point of the calibration curve which can be accurately evaluated within ±20%; b D: Dcell values were used for assessing MQLs here;

IQL , R is R × CF

519

c

520 521

the recovery of SPE method for water and elution efficiency (1.0) for DGT. CF (concentration factor) was 1000 for water and calculated using following equation:

522

CF =

523

membrane, a 0.75 mm thick agarose-based diffusive gel and a 0.5 mm thick

524

HLB-based binding gel in waters for 14 d at 25○C. V is 0.5 mL for DGT.

MQLs: MQLs were calculated using following equation: MQL =

DAt for DGT, assuming deploying DGT with a 0.14 mm thick PTFE filter V∆g

525


Page 29 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


526 527 528 529

For TOC only


Novel method for in situ monitoring of organophosphorus flame

Recommend Documents