Comprehensive Target Analysis for 484 Organic Micropollutants in

Subscriber access provided by Bethel University

Article

Comprehensive Target Analysis for 484 Organic Micropollutants in Environmental Waters by the Combination of Tandem Solid-Phase Extraction and Quadrupole Time-of-Flight Mass Spectrometry with Sequential Window Acquisition of All Theoretical Fragment-Ion Spectra Acquisition Kiwao Kadokami, and Daisuke Ueno Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.9b01141 • Publication Date (Web): 27 May 2019 Downloaded from http://pubs.acs.org on May 29, 2019

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 37 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

Comprehensive

Target

Analysis

for

484

Organic

Micropollutants

in

2

Environmental Waters by the Combination of Tandem Solid-Phase Extraction

3

and Quadrupole Time-of-Flight Mass Spectrometry with Sequential Window

4

Acquisition of All Theoretical Fragment-Ion Spectra Acquisition

5 6

Kiwao Kadokami,1* Daisuke Ueno2

7

1 Institute

8

Hibikino, Wakamatsu, Kitakyushu, Japan

9

2 Graduate

10

of Environmental Science and Technology, The University of Kitakyushu, 1-1

School of Agriculture, Saga University, 1 Honjyo, Honjyo-machi, Saga,

Japan

11 12

*Corresponding author. Phone: +81 93 695 3739

13

E–mail addresses: kadokami@kitakyu–u.ac.jp

14 15 16 17 18 19 20

1 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

21

Abstract: There are many thousands of chemicals in use for a wide range of purposes,

22

and highly efficient analytical methods are required to monitor them for protection of

23

the environment. In order to cope with this difficult task, we have developed a novel,

24

comprehensive method for 484 substances in water samples. In this method target

25

chemicals were extracted by tandem SPE, and then were determined by

26

LC-QTOF-MS-SWATH. Targets were unambiguously identified using retention times,

27

accurate masses of a precursor and two product ions, their ion ratios and accurate

28

MS/MS spectrum. Quantitation was achieved by the internal standard method using a

29

precursor ion. Results of recovery tests at two concentrations (50 and 500 ng L-1)

30

showed average recoveries of 87.5 and 87.0% (RSD, 9.1 and 9.4%), respectively.

31

Limits of detection of half of the targets were below 1.0 ng L-1. The method was applied

32

to the influent and effluent of a sewage treatment plant, and around 100 chemicals were

33

detected. Results of examination on matrix effects using their extracts spiked with 209

34

pesticides showed that the ratios of detected amounts between the extracts and the

35

standard solution were 89.8% (influent) and 91.7% (effluent), respectively. In addition,

36

investigation on stability of calibration curves by injecting the same standards for one

37

year showed that their quantitative results did not change; average accuracy was

38

103.3 % (RSD, 10.0%), indicating that the calibration curves can be used for an

39

extended period of time without calibration and quantitative retrospective analysis can

40

be done after creating calibration curves for new targets.

41 42

Keywords: Comprehensive analysis; pesticides; pharmaceutical and personal care

43

products; SWATH; hybrid tandem mass spectrometer

44


Page 2 of 37

Page 3 of 37 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


45

Accompanying the desire for a wealthy and comfortable life, the number and volume of

46

chemical substances used worldwide have been rapidly increasing.1,

47

chemicals make their way into aquatic ecosystems. As a result, there are concerns about

48

the adverse effects of organic micro-pollutants (OMPs), especially agricultural

49

chemicals, pharmaceuticals and personal care products (PPCPs), and their metabolites

50

and decomposition products on aquatic organisms.3,

51

situation, it is important to understand the occurrences of as many OMPs as possible in

52

the aquatic environment.3, 5-7 Waterways managers are often reluctant to do the required

53

monitoring because of the cost, time and effort required to screen the huge number of

54

OMPs; this highlights the need for highly efficient, simultaneous determination

55

analytical methods. 3, 5-7

4

2

Many of these

In order to cope with this

56 57

We have developed highly efficient simultaneous analytical methods for ca. 1000

58

semi-volatile organic chemicals (SVOCs) by gas chromatography-mass spectrometry

59

(GC-MS).8 Many OMPs, however, have limited volatility and are thermally

60

decomposable substances and so are difficult to measure by GC-MS. Liquid

61

chromatography-MS (LC-MS) may be applied to analysis of such chemicals. However,

62

LC-MS has poor in-peak resolution and retention time reproducibility compared to

63

GC-MS. Moreover, although electro-spray ionization (ESI) is suitable for ionization of

64

polar substances, it is less likely to generate fragment ions than the electron ionization

65

processes used in GC-MS. To overcome these deficiencies, LC-MS-MS-multiple

66

reaction monitoring (MRM) may be used in environmental analysis9-12 due to its high

67

selectivity and sensitivity. However, since setting of measurement conditions is

68

complicated and time-consuming, this method is not suitable for screening a large



Page 4 of 37

69

number of substances. To achieve comprehensive screening of numerous substances,

70

full-scan analysis by LC-high-resolution (HR)-MS such as LC-time-of-flight

71

(TOF)-MS5, 13-15 and LC-Orbitrap-MS3, 16 is used. However, even with the resolution of

72

LC-HR-MS, false detections occur frequently12-14 when analyzing trace amounts of

73

OMPs in complex matrices, which indicates the need to use additional fragment ions for

74

correct identification. To obtain fragments by LC-HR-MS, in-source fragmentation13-17

75

or collision-induced dissociation13, 14 in a collision chamber are used. When identifying

76

and quantifying OMPs using in-source fragmentation or collision-induced dissociation,

77

it is necessary to measure a sample twice for identification and quantitation.13-16 Also, if

78

multiple substances eluting out from a LC column at the same time are ionized, the

79

attribution of fragment ions to parent chemical is extremely difficult, which results in

80

mis-identification.15

81 82

Overall, LC-quadrupole (Q)TOF-MS is arguably one of the best instruments capable of

83

simultaneous analysis of many substances because sample identification and

84

quantitation are done using the same analytical run. There are three measurement modes

85

for simultaneous measurement in LC-QTOF-MS: all-ion-fragmentation (AIF),6,

86

data-dependent-acquisition (DDA),19, 20 and data-independent-acquisition (DIA)19, 20 but

87

the identification and quantitation of many substances using these modes have the

88

following problems. In AIF, since all precursor ions passing through a quadrupole mass

89

spectrometer

90

(mis-identification due to interference ions) as in-source fragmentation occurs

91

frequently.19, 20 With DDA only precursor ions having a minimum certain ion strength

92

are dissociated to generate product ions, which may result in environmental pollutants

are

dissociated

in

a

collision

chamber,


the

same

19, 20

problem

Page 5 of 37 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


93

with low concentrations not generating fragment ions from.19,

20Among

94

measurement modes, the most suitable one for comprehensive screening and

95

quantitation of OMPs in environmental samples and agricultural products is DIA.14, 19, 20

96

One DIA method is Sequential Window Acquisition of All Theoretical Fragment-Ion

97

Spectra Acquisition (SWATH) which has already been widely applied in proteomics,21,

98

22

99

after performing a TOF-MS scan for a fixed time, the TOF-MS scan range is divided

100

into smaller ranges by a quadrupole mass spectrometer, all precursor ions in each mass

101

range are sequentially dissociated in a collision chamber, and then product ions

102

generated are scanned in a TOF-MS. If the mass range separated is narrow, the

103

possibility of interference with co-eluted substances is low. Therefore, SWATH can

104

simultaneously perform TOF-MS scan and MS-MS scan for all peaks including small

105

peaks that DDA cannot perform, and also its selectivity is much better than that of AIF

106

due to very low interference of co-eluted substances, thus chance of miss identification

107

is low and sensitivity is high that are suitable for environmental analysis.

the three

metabolomics,23 and clinical and forensic toxicology research.24-26 In SWATH mode,

108 109

The aims of this study were to (1) develop a comprehensive screening method for 484

110

OMPs in environmental waters by LC-QTOF-MS-SWATH, and (2) to evaluate

111

performance and applicability of the method by using wastewater of a sewage treatment

112

plant (STP). We examined all the performance required for environmental analysis such

113

as selectivity, sensitivity, dynamic range, accuracy, precision, and matrix effects. In

114

addition, (3) we examined the stability of calibration curves for a year. If the slopes of

115

the calibration curves are stable, it is not necessary to update the calibration curves

116

when measuring samples, which saves cost and time, and also it is possible to create



117

quantitative methods for new substances, allowing for retrospective quantitative

118

analysis of stored LC-QTOF-MS data.

119 120

EXPERIMENTAL SECTION

121

Reagents and equipment. Chemical standards were purchased from Restek Japan

122

(Tokyo, Japan), Kanto Chemical (Tokyo, Japan) and Hayashi Pure Chemical (Osaka,

123

Japan). Analytical-grade pharmaceuticals were obtained from Kanto Chemical,

124

Funakoshi (Tokyo, Japan), Tokyo Chemical Industry (Tokyo, Japan), Wako Pure

125

Chemical Industries (Osaka, Japan), Dr. Ehrenstorfer GmbH (Augsburg ， Germany),

126

LKT laboratories (St Paul, MN, USA), Sigma-Aldrich Japan (Tokyo, Japan), Toronto

127

Research Chemicals (North York, ON, Canada) and Santa Cruz Biotechnology (Dallas,

128

TX, USA). LC-MS-grade methanol and pesticide-grade dichloromethane were

129

purchased from Kanto Chemical. Stock solutions (1 mg mL-1 when possible) of each

130

substance were prepared with methanol or acetonitrile and kept at –20 °C in a freezer.

131

Multi-residue pesticide standards obtained from reagent companies were used as stock

132

solution. Working mixed standard solutions were made by diluting the stock solutions

133

with methanol. The deuterium labeled standards that were used as internal standards

134

(IS), surrogates and matrix substances that were used for evaluating matrix effects were

135

purchased from Kanto Chemical, Wellington Laboratories Japan (Tokyo, Japan),

136

Hayashi Pure Chemical, Cambridge Isotope Laboratories (Andover, MA, USA), and

137

Sigma-Aldrich Japan. The HPLC-grade ammonium acetate (1 mol L-1) used for HPLC

138

mobile phase was obtained from Wako Pure Chemical Industries. Special-grade

139

disodium hydrogenphosphate (Na2HPO4) and anhydrous sodium dihydrogenphosphate

140

(NaH2PO4) were purchased from Kanto Chemical and used to prepare the 1 mol L-1 6 ACS Paragon Plus Environment

Page 6 of 37

Page 7 of 37 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


141

NaH2PO4 – Na2HPO4 (pH 7.0) buffer solution that was used for adjusting the pH of

142

samples. LC-MS-grade water was obtained by purifying tap water in an Elga Purelab

143

Chorus 1 Analytical Research (Veolia Water, Tokyo, Japan). The SPE cartridges used

144

were Oasis HLB Plus and Waters Sep-Pak Plus AC2 (Nihon Waters, Tokyo, Japan).

145

Whatman GF/C glass fiber filters (47 mm diameter) were purchased from GE

146

Healthcare Japan (Tokyo, Japan). Millex-LG syringe filters (4 mm) were purchased

147

from Merck Millipore (Darmstadt, Germany). A GL-SPE vacuum manifold system was

148

purchased from GL Sciences (Tokyo, Japan). A Sciex ExionLC with a Sciex X500R

149

QTOF System (AB Sciex, Tokyo, Japan) was used for chemical separation and

150

determination. All glassware and plastic ware were cleaned with detergent and water,

151

washed in an ultrasonic cleaner, dried and rinsed with methanol before use.

152 153

Target chemicals. The number of the target chemicals examined in this study is 484

154

that are categorized into Table 1 and are listed in Table S1. These are comprised of

155

substances with a wide range of physicochemical properties (log Pow -1.55 – 8.53).

156 157

Analytical procedures. Sample preparation was performed according to Chau et al.15

158

In short, phosphate buffer (0.4 mL; 1 mol L-1; pH 7.0) if necessary and surrogate

159

standards (4 μg mL-1, 50 μL, Table 1 and Table S1) were added to a water sample (200

160

mL), and the mixture was then filtered with a 47 mm glass fiber filter. The aqueous

161

filtrate was then passed sequentially through an Oasis HLB cartridge and a Sep-Pak

162

AC2 cartridge at a flow rate of 10 mL min-1. The cartridges were then washed with 20

163

mL of purified water and dried by passing nitrogen through the cartridges for 40 min,

164

and then the targets were eluted from the AC2 side with 5 mL of methanol and 3 mL of



165

dichloromethane. The suspended solids (SS) remaining on the filter paper were

166

subjected to sonication extraction (Ultrasonic cleaner USK-3R, AS ONE, Osaka, Japan)

167

with 3 mL of methanol twice. After combining the eluate and the extract from SS

168

extraction, the mixture was concentrated to 400 µL under a gentle stream of nitrogen.

169

Mixed internal standards and matrix standards (standards for examining degree of the

170

matrix effects, 4 μg mL-1, 50 μL, Table 1 and Table S1) were added and the mixture

171

was reconstituted to 500 μL with methanol. The final extract was filtered with a syringe

172

filter prior to LC-QTOF-MS analysis.

173 174

Instruments and conditions. LC-QTOF-MS conditions are listed in Table 2 and Table

175

S2. LC conditions are the same as those of Chau et al.15 because the conditions are

176

suitable for measuring a large number of substances with broad physico-chemical

177

properties, although in this study we used Sciex X500R QTOF System and measured

178

the sample once only by SWATH to achieve reliable quantitation and identification

179

simultaneously. The TOF-MS scan range (m/z 50 to 1000 for 0.1 s) was divided into 22

180

ranges (SWATH window; Table S2) and each window was measured for 0.07 s by

181

MS-MS scan. The total cycle time was 1.768 s, so more than 10 sampling points for a

182

peak were obtained, which is enough for precise quantitative analysis. We can therefore

183

obtain accurate masses of a precursor ion and product ions without interference of

184

co-eluted peaks, which is most suitable for measuring a large number of substances at

185

the same time.19

186 187

Data processing. Sciex OS was used for from maintenance and control of the

188

LC-QTOF-MS instrument, measurement of samples to all data processing that is as


Page 8 of 37

Page 9 of 37 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

189


follows;

190 191

Building the in-house product ion mass spectral database. In order to reduce the

192

number of quantitation methods (calibration methods), seven 1 g mL-1 mixed standard

193

solutions were prepared. Each mixture was measured by Informed Data Acquisition

194

(IDA) with the LC-QTOF-MS. After measurement, each target chemical was found by

195

drawing extracted exact ion chromatograms of protonated ion [M + H] + or ammoniated

196

[M + NH4]+ adduct. Each target was manually identified using an accurate precursor ion

197

and accurate product ions. Where there were isomers in the mixture, it was difficult to

198

correctly identify the isomers using only an accurate precursor ion and accurate product

199

ions. For such cases, we distinguished the isomers using retention time obtained with an

200

ODS column and/or product ions obtained from mass spectral databases or reference

201

books and papers. After identification, the accurate product ion mass spectrum that was

202

obtained by experiment was registered in the in-house accurate mass spectral database.

203 204

Creating quantitation methods. The quantitation method for each mixed standard is

205

comprised of data for identification (retention times, a quantifier ion and two qualifier

206

ions and identification criteria) and data for quantitation (quantifier ions of targets and

207

internal standards) by using measurement data obtained by IDA. After creating

208

quantitation methods, mixed standard solutions (0.1, 1.0, 10, 100 and 1000 ng mL-1)

209

were measured by LC-QTOF-MS-SWATH. Then all targets contained in each mixed

210

standard solution were identified by a quantification method using retention times,

211

accurate masses of precursor and two product ions and their ion intensity ratios. Then

212

three internal standard calibration curves of a precursor and two product ions for each



213

target were created and registered in the quantitation method.

214 215

Identification and quantitation by quantitation methods. The software provides the

216

analyst with information to identify target substances based on retention time; accurate

217

mass precursor ion and its isotope pattern, two accurate mass product ions; and accurate

218

product ion mass spectra obtained by matching between the sample and a reference

219

product ion mass spectral database. Qualification rules are shown in Table 3. Although

220

the software provides these features, final chemical identification is under the purview

221

of the analyst and relies on the mass accuracies of a precursor and product ions, their

222

ratios, and retention time. Quantification of the identified target substance was

223

performed by the internal standard method using six internal standards (Table S1).

224

Precursor ions were usually used as the quantifier ion due to their typically having the

225

largest peak area of the three monitored ions, but if there were co-eluting peak

226

interferences, a fragment ion without interferences was used as the quantifier ion instead

227

of the precursor ion.

228 229

Recovery tests using reagent water. In order to evaluate accuracy and precision of this

230

multi-residue method, recovery tests were carried out according to the developed

231

analytical procedures at two concentrations (50 and 500 ng L-1) using reagent water.

232 233

Examination of the matrix effects using wastewater of a sewage treatment plant. It

234

is reported that the degree of the matrix effects varies according to retention times27

235

because eluted substances and their amounts also change in time. So we spiked 209

236

pesticides (100 ng each) covering all LC measurement time into the final extracts of an


Page 10 of 37

Page 11 of 37 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


237

STP influent and effluent sample and compared their detected concentrations to the

238

standard solution containing the same amounts of pesticides to examine the degree of

239

matrix effects.

240 241

Examination of stability of calibration curves. In conventional quantitative analysis,

242

calibration curves are usually updated when measuring samples. For instance, in an

243

official method for dioxin analysis,28 a representative concentration of dioxin standards,

244

usually the middle concentration of the range of calibration curve, is measured when

245

measuring samples. If the detected concentrations in this “check standard” are within ±

246

10% of the nominal concentration, update of the calibration curves is not needed.

247

Further, if the slopes of calibration curves do not change for a long time, it is also not

248

necessary to update calibration curves, which saves labor, time and cost. This

249

convention is very important for multi-residue methods because it is very difficult to

250

update calibration curves for hundred substances for every batch of samples analyzed.

251

In that context, in this study we examined stability of calibration curves by measuring of

252

209 pesticides (100 ng mL-1) using six columns including three used columns for one

253

year.

254 255

RESULTS AND DISCUSSION

256

Identification performance. In this study we divided the TOF-MS scan range (m/z 50

257

– 1000) into 22 smaller MS-MS scan ranges (Table S2), of which the MS-MS scan

258

ranges from m/z 200 to 400 are narrower than the others because more substances exist

259

in this range.19 By using this feature of SWATH, we can theoretically measure an

260

unlimited number of substances along with reducing the effects of interfering



261

substances and with high sensitivity. In addition, in order to reduce error of not

262

detection (false negative error), we used relatively loose identification criteria (Table

263

S3) because concentrations of OMPs in environmental samples are usually very low

264

compared to interfering substances. As a result, almost all of the chemicals detected in

265

the influent of a sewage treatment plant (STP) were able to be correctly identified

266

despite the sample containing a large amount of matrix by using retention times,

267

accurate precursor and two product ions, their ion ratios and precursor and product ions

268

mass spectra obtained by SWATH (Figure 1). Even with the high-resolution and smaller

269

MS-MS scan ranges provided by SWATH, a small number of target chemicals were

270

affected taken interference caused by co-eluting peaks; e.g. the precursor ion of

271

ampicillin (m/z = 350.117) (Figure 2) was interfered with, but since two product ions

272

(m/z = 160.043 and 114.037) had no interferences, the target was able to be easily

273

manually identified. In this case, quantitation was done using a product ion (m/z =

274

160.043) instead of the precursor ion. There were also some examples where a product

275

ion was interfered with, e.g. the product ion 2 of cotinine (m/z = 98.060) (Figure 3). In

276

such cases, if we used the strictest identification criteria, these substances would not be

277

found. Although almost of the targets can be correctly identified using accurate mass,

278

for some substances, particularly substances at low concentration, manual identification

279

is necessary for correct identification even when using SWATH.

280 281

Calibration curves and detection limits. The average of all coefficients of

282

determination was 0.972, and nearly 80% of the targets have dynamic range over three

283

orders of magnitude (Table S1). Method detection level (MDL) of each target was

284

estimated according to the relationship between the instrument detection level (IDL)


Page 12 of 37

Page 13 of 37 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


285

and MDL (IDL:MDL=1:4)29 and the concentration ratio (the ratio of the volume of a

286

sample (200 mL) to the volume of a final concentrate (0.5 mL): 400 times). The MDLs

287

of 236 substances out of 484 target substances were less than 1.0 ng L-1 with only 13

288

substances having a MDL higher than 100 ng L-1 (Table 3 and Table S1), showing that

289

the MLDs are good enough for environment analysis.

290 291

Recovery tests using reagent water. Eighty-one and 89% of the substances had

292

recoveries between 70 – 130% at 50 and 500 ng L-1, respectively. Average recoveries of

293

the 50 and 500 ng L-1 spikes were 87.0 and 86.4 %, respectively (RSD, 9.1 and 9.5%,

294

respectively; Table 4, Table S4-1 and Figure S1). Average recoveries of the surrogate

295

(Surrogate in Table S1) and matrix substances (Matrix substance in Table S1), which

296

were used for evaluating the extent of matrix effects, were 102.5 and 108.4%,

297

respectively (Table S4-2), (RSD, 9.0 and 10.2%, respectively). This showed there were

298

no matrix effects from the reagent water and that the extraction ability of the tandem

299

SPE method is adequate for screening a large number of substances with a broad range

300

of physicochemical properties (Figure S1). Substances with short retention times clearly

301

had lower recovery. Because polarities of substances are in inverse proportion to

302

retention times of LC with an ODS column,30 the reason for these low recoveries

303

appears to be their high water solubility. Moreover, recoveries gradually decreased with

304

increasing retention times (Figure S1), probably due to low elution efficiency of highly

305

hydrophobic substances from AC-2.

306 307

Matrix effects of wastewater of a sewage treatment plant. Matrix effects are the

308

major problem in quantitation by LC-MS-ESI.27,

31, 32

Therefore, we spiked a set of



309

deuterium-labeled surrogate compounds (Table S1) into all samples before extraction to

310

validate sample analysis through all procedures including the matrix effects. In addition,

311

we also spiked another set of deuterium-labeled compounds as matrix substance (Table

312

S1) into a concentrated extract before filtration to only evaluate the degree of the matrix

313

effects. Their recoveries in actual samples (influent and effluent of a STP) and blank

314

samples are shown in Table S5. Comparison between mean values of blanks to influents

315

shows that only one surrogate, sulfamethoxazole-d4, in STP influents was significantly

316

(p < 0.05) lower than the blanks. Further, only three matrices and one surrogate of

317

effluents were significantly (p < 0.05) lower than the blanks. However, recoveries of the

318

substances in these matrices/surrogates were only 20 to 37% those without the

319

matrix/blank effect, which is not a fatal error in screening analysis. The data for the

320

degree of the matrix effects across all LC measurement times using wastewater extracts

321

are shown in Table 5 and Table S6. Average ratios of detected amounts between the

322

extracts and the standard solution were 89.9% (influent) and 91.7% (effluent) with

323

RSDs of 22.5 and 22.7%, respectively. Moreover, the numbers of substances in the

324

influent and the effluent samples that were confirmed at concentrations in the range of

325

70 to 130% of their concentration in the standard solution were 173 and 177,

326

respectively. These results show that matrix did not affect quantitation, probably due to

327

the compensatory effect of using the internal standards.

328 329

Stability of calibration curves and retrospective quantitative analysis. The results of

330

calibration curves stability tests are shown in Table 6 and Table S7. Average

331

intermediate precision of the test pesticides was 10.4%, which was worse than 4.2% of

332

average repeatability (n = 7) of the same pesticides. The good, if not perfect, stability of


Page 14 of 37

Page 15 of 37 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


333

calibration curves has two benefits. First, it is not necessary to update calibration curves

334

at every sample analysis, which saves analytical time and cost. Second, it is possible to

335

add new targets into the database, and also perform retrospective quantitative analysis.

336

This performance could be one of the solutions of the reference standard dilemma.33 If

337

once we register new substances that are hard to obtain or are very expensive in a

338

quantitative method, we can determine them for a long time without re-procurement,

339

and so theoretically analyze an unlimited number of OMPs. Overall, the stability of

340

calibration curves may not be sufficient for regulatory purposes, but is more than

341

adequate for finding substances of high risk to human and aquatic organisms, finding

342

causes of environmental incidents, and confirming environmental safety after disasters

343

and accidents.

344 345

Application to wastewater of a sewage treatment plant. In order to confirm the

346

applicability and usefulness of the comprehensive screening method, we analyzed the

347

influent and effluent of a Japanese STP in the summer 2017. STP samples were chosen

348

because such samples are one of the most difficult environmental waters to analyze due

349

to their high matrix levels. Ninety five and 106 substances, mainly PPCPs and

350

pesticides, were detected in the influent and the effluent, respectively (Table S8). Mean

351

recoveries of the surrogates and matrix substances in the influent and the effluent were

352

85.1% (RSD, 19.2%) and 76.6% (RSD, 22.7%), respectively, which is almost the same

353

as those of the blanks using reagent water (recovery: 89.0%, RSD: 11.9%). In addition,

354

by utilizing the long term stability of calibration curves, retrospective analysis for

355

organophosphorus flame retardants was performed on the initial measurement data. As a

356

result, 9 out of 17 substances were found in the measurement data (Table S9). From



357

these results, it was confirmed that the method has sufficient applicability for

358

environmental waters, and has high usefulness because of detection of many OPMs with

359

low cost, a short time and reliable identification and quantification.

360 361

CONCLUSIONS

362

The experimental results clearly showed the effectiveness of the combination of the

363

tandem SPE and LC-QTOF-MS-SWATH method for the comprehensive target analysis

364

of 484 OMPs in environmental waters. Since the developed method utilizing SWATH

365

as the acquisition method that can measure all theoretical fragment-ion spectra, the

366

method has performance needed for future environmental monitoring34 and the

367

following advantages: ability (1) to simultaneously measure a large number of

368

substances in a short time with low cost and low labor requirements; (2) to perform

369

highly reliable identification using the excellent selectivity provided by SWATH; (3) to

370

provide reliable quantitative results by internal standard method using accurate ions

371

even high matrix samples; (4) to easily expand the number of targets until theoretically

372

an unlimited number of OMPs by utilizing the long term stability of calibration curves,

373

and to perform retrospective quantitative analysis after adding new targets. Many of the

374

target chemicals in our list are metabolized; adding metabolites and decomposition

375

products to the target list is urgently needed to enable the screening of the potentially

376

wide range of toxic metabolites in environmental waters. Such performance

377

characteristics will be very useful for finding substances posing high risk to human and

378

aquatic organisms, finding causes of environmental incidents, and confirming

379

environmental safety after disasters and accidents. In addition, the combination with

380

two comprehensive methods using LC-QTOF-MS and GC-MS,8 we can obtain a more


Page 16 of 37

Page 17 of 37 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

381


complete pollution picture of the environment.6

382 383

ASSOCIATED CONTENT

384

Supporting Information

385

The Supporting Information is available free of charge on the ACS Publications

386

website.

387

Table S1, List of target compounds; Table S2, SWATH windows; Table S3, Qualitative

388

rules; Table S4, Results of recovery test; Table S5, Recovery of surrogates and matrix

389

substances in influents and effluents in a sewage treatment plant; Table S6, Examination

390

results of matrix effects by comparing influent and effluent spiked with 209 pesticides

391

to pesticides standard solution; Table S7, Results of stability of calibration curves

392

(Intermediate precision); Table S8, Detected substances and their concentrations in

393

influent and effluent of a sewage treatment plant; Table S9, Results of retrospective

394

analysis of newly added substances; Figure S1, Relationship between recovery and

395

retention time.

396 397

AUTHOR INFORMATION

398

* E-mail: [email protected]. Phone: +81-93-695-3739.

399 400

Acknowledgements

401

This study was supported by JSPS KAKENHI Grant Number JP16H02964. We are

402

grateful to Associate Professor Graeme Allinson (RMIT University, Melbourne,

403

Australia) and Dr. Mayumi Allinson (University of Melbourne, Melbourne, Australia)

404

for their kind proofreading, useful comments, and constructive suggestions on this



405

manuscript. We thank Dr. Takashi Miyawaki (Fukuoka Institute of Health and

406

Environmental Sciences) for his help to prepare mixed standard solutions of target

407

substances. We express our appreciation to Dr. Toshinari Suzuki and Dr. Yuki Kosugi

408

(Tokyo Metropolitan Institute of Public Health) and Dr. Hidenori Matsukami (National

409

Institute for Environmental Studies, Japan) for offer of standard substances.

410

REFERENCES

411

(1) Binetti, R.; Costamagna, F. M.; Marcell, I. Exponential Growth of New Chemicals

412

and Evolution of Information Relevant to Risk Control. Ann Ist Super Sanita, 2008, 44,

413

13-15.

414

(2) Bernhardt, E. S.; Rosi, E. J.; Gessner, M. O. Synthetic Chemicals as Agents of

415

Global Change. Front Ecol. Environ. 2017, 15, 84-90.

416

(3) Moschet, C.; Wittmer, I.; Simovic, J.; Junghans, M.; Piazzoli, A.; Singer, H.;

417

Stamm, C.; Leu, C.; Hollender, J. How a Complete Pesticide Screening Changes the

418

Assessment of Surface Water Quality. Environ. Sci. Technol. 2014, 48, 5423-5432.

419

(4) Eggen, R. I. L.; Hollender, J.; Joss, A.; Scharer, M.; Stamm, C. Reducing the

420

Discharge of Micropollutants in the Aquatic Environment: The Benefits of Upgrading

421

Wastewater Treatment Plants. Environ. Sci. Technol. 2014, 48, 7683-7689.

422

(5) Robles-Molina, J.; Lara-Ortega, F. J.; Gilbert-Lopez, B.; Garcia-Reyes, J. F.

423

Multi-residue Method for the Determination of Over 400 Priority and Emerging

424

Pollutants in Water and Wastewater by Solid-phase Extraction and Liquid

425

Chromatography-time-of-flight Mass Spectrometry. J. Chromatogr. A. 2014, 1350,

426

30-43.


Page 18 of 37

Page 19 of 37 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


427

(6) Moschet, C.; Lew, B. M.; Hasenbein, S.; Anumol, T.; Young, T. M. LC- and

428

GC-QTOF-MS as Complementary Tools for a Comprehensive Micropollutant Analysis

429

in Aquatic Systems. Environ. Sci. Technol. 2017, 51, 1553-1561.

430

(7) Schmidt, T. C. Recent Trends in Water Analysis Triggering Future Monitoring of

431

Organic Micro-pollutants. Anal. Bioanal. Chem. 2018, 410, 3933-3941.

432

(8) Jinya, D.; Iwamura, T.; Kadokami, K. Comprehensive Analytical Method for

433

Semi-volatile Organic Compounds in Water Samples by Combination of Disk-type

434

Solid-phase Extraction and Gas Chromatography-Mass Spectrometry Database System.

435

Anal. Sci., 2013, 29, 483-486.

436

(9) Rodil, R.; Quintana, J. B.; Lopez-Mahia, P.; Muniategui-Lorenzo, S.;

437

Prada-Rodriguez, D. Multi-residue Analytical Method for the Determination of

438

Emerging

439

Chromatography-tandem Mass Spectrometry. J. Chromatogr. A. 2009, 1216,

440

2958-2969.

441

(10) Shao, B.; Chen, D.; Zhang, J.; Wu, Y.; Sun, C. Determination of 76 Pharmaceutical

442

Drugs by Liquid Chromatography-tandem Mass Spectrometry in Slaughterhouse

443

wastewater. J. Chromatogr. A. 2009, 1216, 8312-8318.

444

(11) Gracia-Lor, E.; Sancho, J. V.; Hernandez, F. Simultaneous Determination of

445

Acidic, Neutral and Basic Pharmaceuticals in Urban Wastewater by Ultra High-pressure

446

Liquid Chromatography-tandem Mass Spectrometry. J. Chromatogr. A. 2010, 1217,

447

622-632.

448

(12) Gracia-Lor, E.; Sancho, J. V.; Hernandez, F. Multi-class Determination of Around

449

50 Pharmaceuticals, Including 26 Antibiotics, in Environmental and Wastewater

Pollutants

in

Water

by

Solid-phase


Extraction

and

Liquid


by

Ultra

450

Samples

451

Spectrometry. J. Chromatogr. A. 2011, 1218, 2264-2275.

452

(13) Gomez, M. J.; Gomez-Ramos, M. M.; Malato, O.; Mezcua, M.; Fernandez-Alba,

453

A. R. Rapid Automated Screening, Identification and Quantification of Organic

454

Micro-contaminants and Their Main Transformation Products in Wastewater and River

455

Waters using Liquid Chromatography–quadrupole-time-of-flight Mass Spectrometry

456

with an Accurate-mass Database. J. Chromatogr. A. 2010, 1217, 7038-7054.

457

(14) Wang, Z.; Chang, Q.; Kang, J.; Cao, Y.; Ge, N.; Fan, C.; Pang, G. F. Screening and

458

Identification Strategy for 317 Pesticides in Fruits and Vegetables by Liquid

459

Chromatography-quadrupole Time-of-flight High Resolution Mass Spectrometry. Anal.

460

Methods, 2015, 7, 6385-6402.

461

(15) Chau, H. T. C.; Kadokami, K.; Ifuku, T.; Yoshida, Y. Development

462

Comprehensive Screening Method for More Than 300 Organic Chemicals in Water

463

Samples

464

Chromatography-time-of-flight-mass Spectrometry. Environ. Sci. Pollu. Res. 2017, 24,

465

26396-26409.

466

(16) Cotton, J.; Leroux, F.; Broudin, S.; Poirel, M.; Corman, B.; Junot, C.; Ducruix, C.

467

Development and Validation of a Multiresidue Method for the Analysis of More Than

468

500 Pesticides and Drugs in Water Based on On-line and Liquid Chromatography

469

Coupled to High Resolution Mass Spectrometry. Water Research, 2016, 104, 20-27.

470

(17) Zomer, P.; Mol, H. G. J. Simultaneous Quantitative Determination, Identification

471

and

472

LC-Q-Orbitrap™-MS. Food Additives & Contaminants: Part A. 2015, 32, 1628-1636.

Using

Qualitative

a

High-performance

Combination

Screening

of

Liquid

Page 20 of 37

of

Chromatography-tandem

Solid-phase

Pesticides

in

Fruits


Extraction

and

Mass

of

and

Vegetables

a

Liquid

Using

Page 21 of 37 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


473

(18) Akiyama, Y.; Matsuoka, T.; Mitsuhashi, T. Multi-residue Screening Method of

474

Acidic Pesticides in Agricultural Products by Liquid Chromatography/Time of Flight

475

Mass Spectrometry. J. Pestic. Sci. 2009, 34, 265-272.

476

(19) Renaud, J. B.; Sabourin, L.; Topp, E.; Sumarah, M. W. Spectral Counting

477

Approach to Measure Selectivity of High-Resolution LC−MS Methods for

478

Environmental Analysis. Anal. Chem. 2017, 89, 2747-2754.

479

(20) Wong, J. W.; Wang, J.; Chow, W.; Carlson, R.; Jia, Z.; Zhang, K.; Hayward, D. G.;

480

Chang, J. S. Perspectives on Liquid Chromatography−High-Resolution Mass

481

Spectrometry for Pesticide Screening in Foods. J. Agric. Food Chem. 2018, 66,

482

9573-9581.

483

(21) Collins, B. C.; Hunter, C. L.; Liu, Y.; Schilling, B.; Rosenberger, G. R; Bader, S.

484

L.; Chan, D. W.; Gibson, B. W.; Gingras, A.; Held, J. M.; Hirayama-Kurogi, M.; Hou,

485

G.; Krisp, C. K.; Larsen, B.; Lin, L.; Liu, S.; Molloy, M. P.; Moritz, R. L.; Ohtsuki, S.;

486

Schlapbach, R.; Selevsek, N.; Thomas, S. N.; Tzeng, S.; Zhang, H.; Aebersold, R.

487

Multi-laboratory Assessment of Reproducibility, Qualitative and Quantitative

488

Performance of SWATH-mass Spectrometry. Nature Communications, 2017, DOI:

489

10.1038/s41467-017-00249-5.

490

(22) Gillet, L. C.; Navarrot, P.; Tate, S.; Rost, H.; Selevsek, N.; Reiter, L.; Bonner, R.;

491

Aebersold, R. Targeted Data Extraction of the MS/MS Spectra Generated by

492

Data-independent Acquisition: A New Concept for Consistent and Accurate Proteome

493

Analysis. Mol. Cell. Proteomics. 2012, 11, 1-17. DOI 10.1074/mcp.O111.016717.

494

(23) Hopfgartner, G.; Tonoli, D.; Varesio, E. High-resolution Mass Spectrometry for

495

Integrated Qualitative and Quantitative Analysis of Pharmaceuticals in Biological



Page 22 of 37

496

Matrices. Anal. Bioanal. Chem. 2012, 402, 2587-2596.

497

(24) Roemmelt, A. T.; Steuer, A. E.; Poetzsch, M.; Kraemer, T. Liquid

498

Chromatography, in Combination with a Quadrupole Time-of-Flight Instrument (LC

499

QTOF), with Sequential Window Acquisition of All Theoretical Fragment-Ion Spectra

500

(SWATH) Acquisition: Systematic Studies on Its Use for Screenings in Clinical and

501

Forensic Toxicology and Comparison with Information-Dependent Acquisition (IDA).

502

Anal. Chem. 2014, 86, 11742-11749.

503

(25) Roemmelt, A. T.; Steuer, A. E.; Poetzsch, M.; Kraemer, T. Liquid

504

Chromatography, In Combination with a Quadrupole Time-of-Flight Instrument, with

505

Sequential Window Acquisition of All Theoretical Fragment-Ion Spectra Acquisition:

506

Validated Quantification of 39 Antidepressants in Whole Blood As Part of a

507

Simultaneous Screening and Quantification Procedure. Anal. Chem. 2015, 87,

508

9294-9301.

509

(26) Elmiger, M. P.; Poetzsch, M.; Steuer, A. E.; Kraemer, T. Assessment of Simpler

510

Calibration Models in the Development and Validation of a Fast Postmortem

511

Multi-analyte LC-QTOF Quantitation Method in Whole Blood with Simultaneous

512

Screening Capabilities using SWATH Acquisition. Anal. Bioanal. Chem. 2017, 409,

513

6495-6508.

514

(27) Al-Qaim, F. F.; Abduiiah, M. P.; Othman, M. R; Latip, J.; Zakaria, Z.

515

Multi-residue

516

Chromatography-time-of-flight-mass Spectrometry for the Analysis of Pharmaceutical

517

Residues in Surface Water and Effluents from Sewage Treatment Plants and Hospitals.

518

J. Chromatogr. A. 2014, 1345, 139-153.

Analytical

Methodology-based


Liquid

Page 23 of 37 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


519

(28)

JIS

K0312:

520

octachlorodibenzo-p-dioxins, tetra-through octachlorodibenzofurans and dioxin-like

521

polychlorinatedbiphenyls in industrial water and wastewater, Japanese Industrial

522

Standards Committee: Tokyo, 2008.

523

(29) Rice, E. W.; Baird, R. B.; Eaton, A. D.; Clesceri, L. S., Ed.; In Standard methods

524

for the examination of water and wastewater 22ed; American public health association,

525

American water works association, Water environment federation: Baltimore, 2012; pp

526

1-20.

527

(30) JIS 7260-117: 2006. Partition coefficient (1-octanol-water) – High performance

528

liquid chromatography (HPLC) method, Japanese Industrial Standards Committee:

529

Tokyo, 2006.

530

(31) Stahnke, H.; Reemtsma, T.; Alder, L. Compensation of Matrix Effects by

531

Postcolumn Infusion of a Monitor Substance in Multiresidue Analysis with

532

LC−MS/MS. Anal. Chem. 2009, 81, 2185-2192.

533

(32) Nurmi, J.; Pellinen, J. Multiresidue Method for the Analysis of Emerging

534

Contaminants

535

Chromatography-time-of-flight Mass Spectrometry. J. Chromatogr. A. 2011, 1218,

536

6712-6719.

537

(33) Moschet, C.; Piazzoli, A.; Singer, H.; Hollender, J. Alleviating the Reference

538

Standard Dilemma Using a Systematic Exact Mass Suspect Screening Approach with

539

Liquid Chromatography-High Resolution Mass Spectrometry. Anal. Chem. 2013, 85,

540

10312-10320.

541

(34) Perez-Fernandez, V.; Rocca, L. M.; Tomai, P.; Fanali, S.; Gentili, A. Recent

in

2008.

Method

Wastewater

for

by

determination

Ultra


of

tetra-through

Performance

Liquid


542

Advancements and Future Trends in Environmental Analysis: Sample Preparation,

543

Liquid Chromatography and Mass Spectrometry. Analytica. Chemica. Acta. 2017, 983,

544

9-41.

545

Figure captions

546

Figure 1. Example of a target (Ketoprofen) correctly identified by using retention times,

547

accurate precursor and two product ions, their ion ratios, and product ions mass

548

spectrum.

549

(A) Extracted ion chromatograms of a precursor ion and two product ions

550

Ion 1 (blue): precursor ion (m/z = 255.102), Ion 2 (purple): product ion 1 (m/z =

551

105.033), Ion 3 (red): product ion 2 (m/z = 209.096)

552

(B) MS/MS spectrum

553

Blue: deconvoluted spectrum from a sample, Red: spectrum from a sample, Black:

554

library spectrum

555 556 557

Figure 2. Example of a precursor ion (m/z 350.117) of a target (Ampicillin) being

558

interfered with other substance(s).

559

(C) Extracted ion chromatograms of a precursor ion and two product ions

560

Ion 1 (purple): precursor ion (m/z = 350.117), Ion 2 (blue): product ion 1 (m/z =

561

160.043), Ion 3 (red): product ion 2 (m/z = 114.037)

562

(D) MS/MS spectrum

563

Blue: deconvoluted spectrum from a sample, Red: spectrum from a sample, Black:

564

library spectrum


Page 24 of 37

Page 25 of 37 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


565 566 567

Figure 3. Example of a product ion (m/z = 98.060) of a target (Cotinine) being

568

interfered with other substance(s).

569

(E) Extracted ion chromatograms of a precursor ion and two product ions

570

Ion 1 (purple): precursor ion (m/z = 177.102), Ion 2 (red): product ion 1 (m/z =

571

80.489), Ion 3 (blue): product ion 2 (m/z = 98.060)

572

(F) MS/MS spectrum from a sample

573



574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625

Page 26 of 37

B

A Ion 1

Ion 2 Ion 3

Figure 1.


Page 27 of 37 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

626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678


B

A Ion 1

Ion 2 2 Ion 3

Figure 2.



679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708

Page 28 of 37

B

A Ion 3 Ion 1

Ion 2

Figure 3.


Page 29 of 37 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


709

Table 1. Summary of target substances Class Number* Pesticide 296 Pharmaceutical 156 Personal care product 18 Indusrial chemical 10 Others 4 Total 484 Internal standard 6 Surrogate** 4 Matrix substance*** 5 * = including metabolites; ** = substances for evaluating analysis; *** = substances for evaluating matrix effects 710 711



Page 30 of 37

712

Table 2. LC/QTOF-MS conditions Sciex X500R QTOF Instrument 　　 system GL Science ODS-4 HP (150 mm, 2.1 mm, 3 Column µm) Column temp. 40 °C Flow rate 0.3 mL min-1 Mobile phase

A: 5 mM CH3COONH4 in H2O B: 5 mM CH3COONH4 in CH3OH

Gradient profile

Time,

Injection Volume Ion source Ionization Measurement mode TOF-MS (scan range) TOF MS/MS Collision energy ramp Mass resolution Total cycle time

B, % 5 95 2 L TurbolonSpray ESI-positive Swath 50 - 1000 Da, 0.1 s 50 - 1000 Da, 22 ranges, 0.07 s each 20 – 50 V 30000 1.768 s 　　

min

0

30 - 40

713 714


40.01 50 5

　

Page 31 of 37 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


715

Table 3. Method detection limit (MDL), ng L-1 MDL Number < 0.1 25 0.1 - 1 211 1 - 10 191 10 - 100 44 > 100 13 716 717



718

Table 4. Results of recovery test n=5 Number of substances (%) Recovery, % Concentration, 500 ng L-1 Concentration, 50 ng L-1 < 20 5 (1.2) 1 (0.3) 20 - 40 4 (1.0) 4 (1.0) 40 - 60 13 (3.2) 27 (7.0) 60 - 80 75 (18.6) 89 (23.0) 80 - 100 266 (65.8) 183 (47.3) 100 - 120 38 (9.4) 73 (18.9) 3 (0.7) 10 (2.6) ≥ 120 719 720 721


Page 32 of 37

Page 33 of 37 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


722

Table 5. Examination results of matrix effects by comparing influent and effluent spiked with 209 pesticides with pesticides standard solution. Ratio of sample to standard, % (sample/standard)

Number of substance* Effluent

Influent

< 40 2 0 40 - 60 14 17 60 - 80 43 42 80 - 100 76 88 100 - 120 58 47 120 - 140 12 12 3 2 ≥ 140 * = One pesticide was excluded for evaluation due to low sensitivity. 723 724 725



726

Table 6. Intermediate precision* Intermediate precision, %

Comprehensive Target Analysis for 484 Organic Micropollutants in

Recommend Documents