Neonicotinoid insecticides in the drinking water system – Fate, transportation, and their contributions to the overall dietary risks

Journal Pre-proof Neonicotinoid insecticides in the drinking water system – Fate, transportation, and their contributions to the overall dietary risks Chensheng Lu, Zhengbiao Lu, Shu Lin, Wei Dai, Quan Zhang PII:

S0269-7491(19)35138-3

DOI:

https://doi.org/10.1016/j.envpol.2019.113722

Reference:

ENPO 113722

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Environmental Pollution

Received Date: 9 September 2019 Revised Date:

1 December 2019

Accepted Date: 3 December 2019

Please cite this article as: Lu, C., Lu, Z., Lin, S., Dai, W., Zhang, Q., Neonicotinoid insecticides in the drinking water system – Fate, transportation, and their contributions to the overall dietary risks, Environmental Pollution (2020), doi: https://doi.org/10.1016/j.envpol.2019.113722. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.

Table of Content

1

Neonicotinoid insecticides in the drinking water system – Fate, transportation, and their

2

contributions to the overall dietary risks

3

Chensheng Lu1, Zhengbiao Lu 2, Shu Lin2, Wei Dai2, Quan Zhang2*

4

1

College of Resources and Environment, Southwest University, 400715, Chongqing,

5 ，

People’s Republic of China 2

College of Environment, Zhejiang University of Technology, Hangzhou 310032, Zhejiang,

7

People’s Republic of China

8 9 10 11 12 13 14 15 1， 17 18 19

*To whom correspondence should be addressed: 8 Chaowang Road, Hangzhou, People’s

20

Republic of China, 310032

21

E-mail: [email protected] (Q Zhang).

Phone: +86 571 8887 1579; Fax: +86 571 8887 1579;

22 1

23

Abstract

24

Neonicotinoids (Neonics) have become the most widely used insecticides around the

25

world in recent years. Due to the hydrophilic character, neonics are emerging contaminants in

2，

drinking water. In this study, we aimed to characterize and quantify the fate and transport of

27

neonics in the drinking water treatment system and their contributions to the overall dietary

28

risks. Seven neonics in 97 surface and drinking water samples in the city of Hangzhou, China

29

were analyzed. The relative potency factor method was adopted in order to calculate the total

30

neonics concentrations. We then used the Monte Carlo simulation to calculate the chronic

31

daily intake (CDI) of total neonics from water consumption. All 16 surface water samples

32

collected from two rivers contained at least two neonics, and more than 93% of those

33

contained 3 or more neonics. Imidacloprid was detected in all 16 surface water samples,

34

followed by clothianidin and acetamiprid with average concentrations of 11.9, 7.6, 17.6 ng

35

L-1, respectively. The drinking water treatment plants removed approximately 50% of

3，

neonics from surface water. However, 68 out of 71 tap water samples that we collected from

37

the household faucets contained at least one neonic, with the highest average concentrations

38

of 5.8 ng L-1 for acetamiprid. The maximum of CDIs of total neonics from water

39

consumption for adult and children were 10.2 and 12.4 ng kg-1 d-1, respectively, which are

40

significantly lower than the acceptable daily intake (ADI). The results presented here shown

41

drinking water consumption only represented an insignificant portion of dietary risks of total

42

neonics, mainly due to the modern drinking water treatment technologies that are capable of

43

removing significant amount of neonics from drinking water. However, the ubiquity of

44

neonics in the drinking water sources to kitchen faucets, should be a concern for public

45

health.

4，

Keywords: Neonicotinoids; Fate; Drinking water; Dietary risks; Public health

47 2

48

1. Introduction

49

Neonicotinoids (Neonics) are the most extensively used insecticides around the world

50

due to their systemic characters, insect-targeting, and lower resistance (Douglas and Tooker,

51

2015). Neonics are registered in more than 120 countries and have been developed into a

52

market sale of €957 million in 2008 (Jeschke et al., 2011). The demand of neonics in the

53

United States was more than 4 million pounds per year, accounting for more than 20% of the

54

global pesticide market (Lu et al., 2018). There are more than 2,000 different agrochemical

55

products containing neonics registered in China, accounting for approximately 7% of total

5，

pesticide uses in China (Tian et al., 2016). Because of the systemic property, once applied

57

neonics are easily absorbed by the plants and distributed to all parts of crops that renders a

58

very high efficiency in controlling sucking insects, but potentially poses risks to non-target

59

organisms especially pollinators (Bass et al., 2015; Cimino et al., 2017; Jiang et al., 2018).

，0

Recent studies have demonstrated the causal effects of chronic sub-lethal exposure of neonics

，1

to the onset of honeybee colony collapse disorder (CCD) (Lu et al., 2012, 2014), as well as

，2

causing honeybee decrease in immune and reproductive developmental toxicity, affecting

，3

their navigation ability, and damaging the neurological system (Kwong et al., 2014; van der

，4

Sluijs et al., 2013).

，5

Neonics are being widely used in the seed-coating treatment in which a seed (such as

，，

corn) could contain 0.17-1 mg/seed of a neonic prior to sowing (Goulson et al. 2013,

，7

Sanchez-Bayo, 2014). It was estimated that 2-20% of neonic is actually absorbed thru the

，8

roots and with approximately 80-98% of neonic is directly released into the soil

，9

(Sanchez-Bayo, 2014). Because of neonics’ hydrophilic character (Hladik et al., 2018, 2014),

70

neonics in soil are known to leach and contaminate both surface water and groundwater

71

systems (Sanchez-Bayo and Hyne, 2014; Chen et al., 2019b; Yi et al., 2019). An Australia

72

study has shown that 93% of water samples collected from Rivers contained 2 or more 3

73

neonics with levels ranging 0.06-4.5 µg L-1 (Sánchez-Bayo and Hyn, 2014). Neonics, in

74

particular imidacloprid and clothianidin, have also been detected in surface water runoff

75

(streams or Rivers), groundwater, and drinking water in countries around the world, including

7，

Canada (Main et al., 2015; Schaafsma et al., 2015; Sultana et al., 2018), the United States

77

(Starner and Goh, 2012; Hladik and Kolpin, 2016; Sadaria et al., 2016), Japan (Yamamoto et

78

al., 2012), and Brazil (Miranda et al., 2011). In China, neonics have been frequently detected

79

in surface water in recent years. Chen et al. (2019a) reported that among all neonics,

80

dinotefuran, nitenpyram and imidacloprid were the most frequently detected neonics along

81

the Yangtze River in China, with the mean concentrations of 470, 430 and 23.6 ng L-1,

82

respectively. Zhang et al. (2019a) detected five neonics, including acetamiprid, clothianidin,

83

thiacloprid, imidacloprid, and thiamethoxam, in the Pearl Rivers, with the concentrations

84

ranging from ND to 162 ng L, levels that are lower than those measured in the Yangtze River

85

(Chen et al., -12019a). Wan et al. (2019) also reported levels of neonics in raw water samples

8，

collected from the Han and Yantz Rivers in which they found 100% detection of neonics but

87

with levels also lower than those reported by Chen et al. (2019a).

88

While most previous studies were focusing on neonics exposure and toxicological

89

effects in honeybees and other wildlife (Lu et al., 2014, 2016; Zeljezic et al., 2016; Bizerra et

90

al., 2018; Baldisser et al., 2018), very few studies were designed to quantify human exposure

91

to neonics until recently. Dietary intake was found as the primary exposure pathway for

92

human mainly due to the ubiquitous presence of neonics in fruits and vegetables that people

93

consumes daily (Zhang et al., 2018, 2019b; Chang et al., 2018; Lu et al., 2018). As water

94

consumption is an integral component of the overall dietary ingestion pathway, it was

95

suggested in a recent review article that neonics in drinking water could be an important

9，

pathway for human exposure to neonics (Zhang et al., 2018).

97

The objective of this study was to conduct exposure and risk assessments of total 4

98

neonics in drinking water in a cross-sectional study in which water samples were collected

99

from the city of Hangzhou, China. We aimed to quantify the occurrence and the fate of

100

neonics in the drinking water supply system, including source water, before-water treatment

101

plants, after-water treatment plants and tap water delivered to the households. We then

102

estimated the demographic-specific chronic daily intake (CDI) of total neonics and completed

103

the exposure and risk assessments for dietary ingestion of total neonics by incorporating the

104

component of water consumption.

105 10，

2. Materials and Methods

107

2.1. Reagents and Standards

108

We purchased analytical standards of acetamiprid (ACE, 98.1%), dinotefuran (DIN,

109

98.0%), clothianidin (CLO, 99.9%), thiacloprid (THIAC, 98.5%), imidacloprid (IMI, 99.0%),

110

thiamethoxam (THIAM, 99.0%) and nitenpyram (NIT, 98.6%) from Dr. Ehrenstorfer

111

(Augsburg, Germany). The physicochemical properties of those neonics are listed in the

112

supporting information (Table S1). The isotope-labeled clothianidin-d3 (CLO-d3),

113

imidacloprid-d4 (IMI-d4) and thiamethoxam-d3 (THIAM-d3) were purchased from C/D/N

114

Isotopes Inc (Quebec, Canada). Dichloromethane (99.9%, HPLC grade), acetonitrile (99.9%,

115

HPLC grade) and formic acid were obtained from Merck (Rahway, NJ, USA). Ultra-pure

11，

water was prepared using Milli-QA10 system (Merck Millipore, MA, USA).

117

2.2. Sample Collection

118

We collected 97 water samples, including 16 source water (SW), 10 treatment plant

119

water (TPW), and 71 tap water (TW) samples from 71 households living in 5 main districts

120

of Hangzhou, China. The SW samples were collected every 2 km along the Riverbank of

121

Qiantang River and East Shao Creek prior to the inlets of 5 drinking water treatment plants

122

(Figure 1). Five pairs of TPW samples, before entering (b-TPW) and after leaving (a-TPW) 5

123

the treatment plant, were collected from each of the 5 drinking water treatment plants. Four

124

pairs of TPW samples were taken from plants that receive water from the Qiantang River, and

125

one pair of TPW samples were collected from the plant receiving water from the East Shao

12，

Creek. The TW samples were obtained from 71 households living in five residential districts

127

served by the corresponding 5 drinking water treatment plants (Figure.1). All water samples

128

were collected between December 2017 and January 2018 and stored in the 1-L Nalgene

129

bottles at -20oC until analysis. All households have received the approved informed consent

130

prior to participating in this study.

131

2.3. Pre-treatment of water samples

132

We added 2 g of sodium chloride and 25 µL of surrogate standards (IMI-d4, THI-d3) to

133

50 mL of each water sample and then shaken for 10 s. We then added 30mL of

134

dichloromethane, mixed, and shaken for 6 min. The organic phase was removed as much as

135

possible and then eluted by passing the sample through a chromatographic column, which

13，

contains 8 g of anhydrous sodium sulfate. The eluted aliquot was transferred into a round

137

bottom flask, dried by a rotary evaporator, reconstituted with 2mL of acetonitrile, and then

138

vortexed for 1 min. This led to the concentrating factor of 25 for the original levels in water

139

samples. Lastly, 40 µL of internal standard CLO-d3 was added to the flask, and the final

140

solution was stored at -20oC until quantification.

141

2.4. Instrumental conditions

142

Seven neonics were quantified by using an ultra-high performance liquid

143

chromatography with tandem mass spectrometry (UPLC-MS/MS, Waters Corporation,

144

Milford, MA) interfaced with a triple quadrupole mass spectrometer Xevo TQ-S (Waters

145

Corporation). Sample extract (2 µL) were injected into a high-performance liquid

14，

chromatography column, YMC ODS-AQ (100 mm × 2.1 mm, 3 µm, YMC, Allentown, PA,

147

USA). The mobile phase was composed of water acidified with 0.1% formic acid (A) and ，

148

100% acetonitrile (B) at a flow rate of 0.3 mL/min. The gradient was set as follows: 0-1 min

149

0% B and 100% A, 2 min 10% B and 90% A, 3 min 90% B and 10% A, 4 min 90% B and 10%

150

A, 5-6 min 0% B and 100% A. The MS/MS was conducted with electrospray ionization (ESI)

151

source in the positive ion mode with multiple reaction monitoring (MRM). For acetamiprid,

152

clothianidin, dinotefuran, thiacloprid, imidacloprid, nitenpyram and thiamethoxam, the MRM

153

parameters for quantification were 223.1/126.1, 250.0/168.8, 203.1/129.1, 253.0/126.1,

154

256.0/209.1, 271.1/225.1 and 292.0/211.0, respectively. The MRM parameters for

155

quantification of the internal standard (CLO-d3) and surrogate standards (IMI-d4, THIAM-d3)

15，

were 253.0/172.0, 260.0/213.2 and 295.0/214.0, respectively. The MS operating conditions

157

were as follows: the voltages of capillary and cone were set to 2600 V and 48 V, respectively,

158

and the source and probe temperature were set at 150oC and 350oC, respectively. In addition,

159

the gas flows of cone and desolvation, and nebulizer pressure were set at 150 L/h, 550L/h and

1，0

7.0 Bar, respectively. The calibration points for each neonic were 0.1, 0.5, 1, 2, 10, 20, 50 and

1，1

100 µg L-1.

1，2

2.5. Quality assurance (QA) and quality control (QC)

1，3

All water samples were fortified with recovery standards of THIAM-d3 and IMI-d4, and

1，4

internal standard of CLO-d3, to determine the performance of the UPLC-MS/MS method.

1，5

The recoveries for THIAM-d3 and IMI-d4 were 84.6 ± 3.8% and 76.9 ± 4.7%, respectively.

1，，

The average recoveries of IMI, ACE, DIN, CLO, THIAM, THIAC and NIT were 80.1 ± 5.6%,

1，7

72.6 ± 3.1%, 87.9 ± 3.4%, 87.6 ± 4.7%, 84.1 ± 5.2%, 79.4 ± 6.1% and 94.3 ± 4.0 %,

1，8

respectively. All measurements were corrected by the recovery efficiencies of QA/QC

1，9

samples and the concentrating factor of 25 in which 50 mL of water sample was reconstituted

170

by 2 mL of acetonitrile in the pre-treatment procedures. Each water sample was analyzed in

171

triplicate and the mean value was reported. A calibration standard was injected after every 7

172

samples as the check for drift in instrumental sensitivity. Procedural blanks were run with 7

173

each set of samples in order to ensure no cross-contamination of neonics during sampling,

174

transportation, or analysis. The limits of quantification (LOQ) of those neonics were reported

175

in Table 1.

17，

2.6. The integrated exposure assessment approach

177

We adopted the relative potency factory (RPF) method in order to aggregate the total

178

neonics concentrations in water samples (Zhang et al., 2018, 2019b; Chang et al., 2018; Lu et

179

al., 2018). We selected imidacloprid as the reference neonic due to its frequent detection in

180

various sample media and more toxicological data available. We used the reference dose (Rfd)

181

for each neonic to calculate the RPF (Equation 1), which are listed in Table S1 along with the

182

acceptable daily intake (ADI) for each neonic published by the Ministry of Agriculture of

183

China (NY/T 2874-2015). The total neonics in each water sample, expressed as IMIRPF, was

184

then calculated using Equation 2,

185

RPFi = RfDimidacloprid/RfDi

18，

IMIRPF (ng L-1) = Σi(neonicsi×RPFi) = imidacloprid + thiamethoxam×9.5 +

187

acetamiprid×0.803

188

dinotefuran×2.85

189 190

+

…………..……………… (1)

clothianidin×5.816

+

thiacloprid×14.25

+

……………………………………...(2)

2.7. The exposure probability analysis We used Monte Carlo simulation (Crystal Ball software, Oracle Inc, California USA) to

191

calculate the chronic daily intake (CDI) of total neonics in drinking water using Equation 3:

192

CDIi (ng kg-1 d-1) = IMIRPF (ng L-1) ×IRw (L d-1) ×DFi × EF (days yr-1) ×ED (year) /

193

BW (kg) × AT (year)……………………… (3)

194

Where IRw is for water intake rate (1.43 and 0.78 L d-1 for adult and children, respectively);

195

DF is for detection frequency; EF is for exposure frequency (defaulted at 365 days yr-1); ED

19，

is for exposure duration (26 years for adult and 9 years for children); BW is for body weight 8

197

(62.4 and 30.6 kg for adult and children, respectively); and AT is for average time (365 ×ED).

198

We used the average values and standard deviations to generate 10,000 random data of

199

IMIRPF, IRw and BW, respectively. We then estimated the probability distribution of average

200

daily oral intake using the same Monte Carlo simulation, assuming IMIRPF and IRw are

201

log-normally distributed, but BW is normally distributed. The data for IRw and BW were

202

obtained from the Exposure Factors Handbook for Chinese population (Duan, 2013).

203

2.8.Data analysis

204

All statistical analyses were performed using Origin 8.0. The statistical methods that we

205

used in this study were two-sample t-test. The significant level of all the statistical tests was

20，

set at the level of 0.05.

207 208

3. Results

209

3.1.Neonicotinoids in source water (SW)

210

The descriptive statistics of seven neonics concentrations, as well as the total neonics

211

concentrations, in SW, b-TPW, a-TPW, and TW were shown in Table 1. Imidacloprid (IMI)

212

was detected in all 16 SW samples, followed by clothianidin (CLO) (15 out of 16 samples)

213

and acetamiprid (ACE) (14 out of 16 samples). Those three most frequently detected neonics,

214

ACE, IMI, and CLO, also have higher average concentrations of 17.6, 11.9, 7.6 ng L-1,

215

respectively, than the other three neonics. Only thiacloprid (THIAC) was not found in the SW

21，

samples. All those 16 SW samples were detected with at least two neonics, and more than 94%

217

of SW samples contained 3 or more neonics (Table 2). ACE, IMI, and CLO were all detected

218

in 8 SW samples collected from the Qiantang River, while 75%, 100%, and 88% of ACE, IMI,

219

and CLO, respectively, were found in 8 SW samples collected from the East Shao Creek.

220

Figure 2 shows the changes of the average total neonics concentrations, expressed as IMIRPF,

221

from drinking water sources in two different catchments to kitchen faucets. The average 9

222

concentrations of IMIRPF in the East Shao Creek (157.6 ng L-1) were higher than that in the

223

Qiantang River (52.2 ng L-1) in which the highest IMIRPF in the East Shao Creek is 539.6 ng

224

L-1, approximately 2.6-fold higher than that in the Qiantang River (205.6 ng L-1). The

225

IMIRPF was contributed mostly by ACE, IMI, and CLO, also the three most commonly

22，

detected neonics, with average concentrations of 22.6, 7.6, and 6.3 ng L-1 in Qiantang River,

227

and 12.5, 12.4, and 8.8 ng L-1 in the East Shao Creek, respectively.

228

3.2. Neonicotinoids in water before and after treatment plants (b-TPW and a-TPW)

229

The three most commonly detected neonics in SW samples were also most commonly

230

detected in those b-WTP samples (IMI 100%, ACE 80%, and CLO 80%), as well as in those

231

a-WTP samples, although the frequency of detection for CLO was decreased to 40% in the

232

a-WTP samples. THIAC and THIAM were not detected in either b-WTP or a-WTP samples.

233

The concentrations of total neonics in the b-WTP samples were significantly lower to those in

234

the SW samples, affected by the high levels of neonics measured in the East Shao Creek

235

(Figure 2). The concentrations of total neonics in the a-TPW samples were also significantly

23，

lower than those in the b-TPW samples (Figure 3), suggesting the efficiency of removing

237

neonics by the drinking water treatment plants. ACE was not the most frequently detected

238

neonic in either b-TPW or a-TPW samples, however, ACE had the highest average

239

concentrations of 11.2 and 5.9 ng L-1 in the b-TPW and a-TPW samples, respectively, a 48%

240

reduction. A similar significant reduction trend was also true for the total neonics

241

concentrations in which the average concentrations of IMIRPF in the b-TPW and a-TPW

242

samples were 47.9 and 23.3 ng L-1, a 51.4% reduction, with the concentrations ranging from

243

12.0 to 78.9 ng L-1 and 4.0 to 52.3 ng L-1, respectively.

244

3.3. Neonicotinoids in household tap water

245

Following the same trend of SW and TPW samples, ACE (83%) and IMI (82%) were the

24，

most frequently detected neonics in the TW samples, but not CLO (15%). Further minor 10

247

reduction of individual neonics and the IMIRPF (Table 1), as well as the numbers of neonics

248

detected in each sample, were seen in the TW samples (Table 2). Even so, the majority of TW

249

samples (68 out of 71 TW samples, or 95.8%) were still detected for at least one neonic

250

(Table S2). The average concentrations of individual neonics in those TW samples were ACE

251

(5.8 ng/L), followed by IMI (4.0 ng L-1), NIT (2.5 ng L-1), DIN (1.8 ng L-1) and CLO (0.6

252

ng L-1). THIAM and THIAC were no longer detected in the TW samples. The average

253

concentration of IMIRPF in those TW samples was 17.2 ng L-1, ranging from non-detected to

254

105.4 ng L-1 (Table S2).

255

Figure 2 shows the fate of total neonics concentrations (IMIRPF) in a decreasing fashion

25，

from both rivers, through five drinking water treatment plants, and to the kitchen faucets in

257

the households. Such decreasing trend, as shown in Figure 3, was significantly different

258

between the b-TPW and a-TPW samples (t-test, p<0.05), indicating the capability of

259

removing significant portion of neonics by the drinking water treatment plants.

2，0

3.4. Risk assessment of total neonics intake through drinking water consumption

2，1

Figure 4 shows the cumulative distributions of the estimated chronic daily intakes (CDIs)

2，2

of total neonics (IMIRPF) from drinking water consumption for adult and children, which the

2，3

maximum CDIs were 10.2 and 12.4 ng kg-1 d-1, respectively. The CDIs of children was

2，4

significantly higher than those of adults. Overall speaking, the estimated maximum CDIs

2，5

were approximately 3 orders of magnitude lower than the acceptable daily intake (ADI) or

2，，

reference dose (RfD) for IMI, which is 0.057 mg kg-1 d-1. For the purpose of completing the

2，7

overall oral ingestion and risk assessments of total neonics, we estimated the probability

2，8

distribution of average daily oral intake by incorporating total neonics intakes from fruit and

2，9

vegetable consumption in the same Monte Carlo simulation with drinking water consumption

270

(Zhang et al., 2019b). We found fruit and vegetable consumption is the main pathway for the

271

overall oral ingestion of total neonics, and the intake of total neonics through drinking water 11

272

consumption only represents an insignificant portion, as shown in Figure 4.

273 274

4. Discussion

275

This paper was aimed to characterize the fate and transport of neonics from the sources

27，

for drinking water supplied to the municipality and then to the kitchen faucets in the

277

households. Qiantang River and East Shao Creek are two main drinking water sources for the

278

City of Hangzhou, China in which 80% of drinking water comes from Qiantang River. The

279

average annual runoffs for Qiantang River and East Shao Creek are 44 and 1.6 billion cubic

280

meters, respectively. The upper reaches for the East Shao Creek are predominated used by

281

agriculture, and this is likely the reason why the total neonics levels are higher than those in

282

the Qiantang River in which the upper reaches are mostly dedicated to industrial activities. A

283

similar paper to ours published recently shared the same objective of comparing total neonics

284

levels in source, treated, and tap water samples collected from the city of Wuhan, a

285

metropolitan city in the central part of China, where drinking water is supplied by the Han

28，

and Yangtz Rivers (Wan et al. 2019). Although data reported by Wan et al. were consistent to

287

ours in most aspects, the major difference between these two studies is the effectiveness of

288

removing neonics by the drinking water treatment plants. As discussed by Wan et al. (2019),

289

the lack of utilizing active carbon filtration in the drinking water treatments in the city of

290

Wuhan led to the almost identical median levels of neonics in the finished water samples as

291

in the raw water samples.

292

The data that we presented here are also consistent to those published recently. Hladik

293

and Kolpin (2016) reported at least one neonic was detected in 63% of surface water samples

294

collected from 48 streams in US in which IMI (37%) was the most frequently detected neonic.

295

In their later study, Hladik et al. (2018) showed that IMI (53%) continues to be the most

29，

frequently detected neonic in 10 major tributaries to the Great Lakes collected between 12

297

October 2015 and September 2016, followed by CLO (44%), THIAM (22%), and ACE (2%).

298

The frequency of detection of IMI (89%) was much higher in the agricultural regions of

299

California in US (Starner and Goh, 2012). In Canada, THIAM and CLO were two most

300

frequently detected neonics in surface water samples collected from wetlands in

301

Saskatchewan, a mainly farming providence, during the summer of 2012 with detection

302

frequency of 74% (206 of 279 samples) and concentrations ranging from
303

L-1 and
304

CLO were 100% detected in surface water samples collected from the city of Guangzhou

305

areas with concentrations ranging from 32.9±11.6 to 249±19 ng L-1, 18.8±1.9 to 157±31 ng

30，

L-1 and 14.8±3.7 to 47.6±10.0 ng L-1, respectively (Xiong et al., 2019). THIAC was not

307

detected in any sample. Another recent study revealed the inputs of neonics from non-pointed

308

sources, the major contributors (91.3%) to the Yangtze River in China (Chen et al., 2019a).

309

Unlike data reported in the current literature, Chen et al. (2019b) showed two less frequently

310

detected neonics, nitenpyram (NIT) and dinotenfuran (DIN), which in combination

311

constitutes 88-94% of total neonics in samples collected along the Yangtze River basin

312

regardless the sampling locations or seasonality with the average concentrations of total

313

neonics of 990 ng L-1 during the dry season and 390 ng L-1 during the wet season. Chen et al.

314

(2019a) speculated that these results indicate some use pattern changes for neonics in recent

315

years in China.

31，

The maximum concentrations for any neonics reported by Starner and Goh (2012),

317

Hladik et al. (2016, 2018), Xiong et al. (2019) or Chen et al. (2019a) were all significantly

318

higher than those that we reported here (Table 1). The reason might be due to the fact that the

319

surface water samples that we collected were from areas without intensive agricultural

320

activities, and therefore not prone to be contaminated by agrochemicals. Considering the

321

water solubility of neonics, they can easily leach into waterways from nearby agricultural 13

322

land. Since both Qiantang River and East Shao creek are two important drinking water

323

sources for the city of Hangzhou, strict regulations have been implemented in order to protect

324

the water quality by limiting agricultural activities along both rivers. Although not all

325

rivers/streams are being used for drinking water sources, data reported here, as well as by

32，

other studies, should serve as an indication of the ubiquity of neonics in the surface water

327

bodies.

328

The neonic-related papers that we cited here as well as others published in the literature

329

essentially all reported individual neonics levels in various environmental media. Such data

330

reporting pattern could pose a limitation for assessing total neonic exposure under the

331

circumstances when more than one neonic is present in a sample concurrently. For instance,

332

among the 97 water samples that we collected and analyzed in this study, 82 of those

333

contained more than one neonic. Although simple arithmetic summation of individual neonics

334

is a convenient approach to reflect the total neonic exposure, it would underestimate the true

335

risk when more toxic neonics are present in the same sample with other less toxic neonics.

33，

Therefore, we adapted the RPF approach that was developed by the US Environmental

337

Protection Agency (USEPA) aiming for assessing health risks resulting from exposures to a

338

mixture of chemicals with similar molecular structures and the same mode of action, such as

339

organophosphorous pesticides (OPs) (Zhang et al., 2018). While the principle of applying

340

RPF to data management is relatively straight forward by using Equations 1 and 2, the

341

implication to assessing the aggregate exposures and cumulative risks for total neonics is

342

significant. The total neonics, or IMIRPF, represents the integration of all neonics in a sample

343

by normalizing the differences of toxicity for individual neonics, and is possible to allowing

344

for comparing results across different studies. Neonicotinoids are a group of pesticides that

345

are ideal of implementing RPF because of their similar structure and bearing the same mode

34，

of action. 14

347

The insignificant differences of total neonics (IMIRPF) in the SW and b-WTP samples, as

348

shown in Figure 3 should not be a surprise, after all those samples were considered raw

349

drinking water before the treatment. However, we found a significant reduction of total

350

neonics (Table 1 and Figure 3) in the a-TWP samples, suggesting the current drinking water

351

treatment technique is capable of removing more than 50% of neonics in the untreated

352

surface water. The common drinking water treatment technologies in China involve mixing

353

and sedimentation, ozone contact, activated carbon filtration, and chlorination before

354

discharging to the distribution system. A comparable study, both the levels and the frequency

355

of detection of neonics, was recently reported by Kathryn et al. (2017) in which they found

35，

significant reduction of concentrations for several neonics in tap water before and after the

357

drinking water treatment plant operated by the city of Iowa City, IA. However, such

358

significant reduction was not seen in tap water collected from the University of Iowa in

359

which has its own drinking water treatment plant. We found that such disparity is likely

3，0

caused by the use of activated carbon filtration, which has been demonstrated the great ability

3，1

to remove heterocylic aromatic nitrogen compounds, such as neonics, from water (Westerhoff

3，2

et al., 2005; Kathryn et al., 2017), as the finally step in the drinking water treatment plants

3，3

operated by the cities of Hangzhou and Iowa City, but not by the University of Iowa although

3，4

it is located within the city of Iowa City, IA.

3，5

The incomplete removal of neonics by those treatment technologies has left some of the

3，，

neonics shown up in the tap water that individuals collected from their kitchen faucets in

3，7

Hangzhou China. The insignificant differences of IMIRPF between SW and b-TPW samples,

3，8

and between a-TPW and TW samples, elucidate two important facts that both have significant

3，9

public health implications. First, neonics are ubiquitous and quite stable in aqueous

370

environment where significant breaking down does not take place. Considering the popularity

371

of neonics in agricultural uses and its stability in the environment (Giorio et al. 2017), it 15

372

should be reasonable to assume neonics would be persistent and cumulative in the

373

environment. Secondly, the current drinking water treatment technology is adequate to

374

remove significant amount of neonics from water, but not necessarily all of the neonics

375

(Bonmatin et al. 2015). The leftover trace residues of neonics in drinking water that

37，

individuals would intake daily may pose a long-term health risk. While improving the current

377

drinking water treatment technologies in order to completely remove neonics from drinking

378

water may not be economically viable, reducing the use of neonics, in particular along the

379

drinking water sources, would be a reasonable choice.

380

In our previous study, we measured residues of 7 neonics in 123 fruit and vegetable

381

samples that children ages 8-12 living in Hangzhou China commonly consumed during the 5

382

consecutive weekends of study period (Zhang et al., 2019b). We then estimated the average

383

daily intake of total neonics as the result of fruit and vegetable consumption. In order to

384

complete the overall oral ingestion and risk assessments of neonics, data that we reported

385

here have allowed us to calculate the cumulative probabilistic risks of total neonics by

38，

incorporating individual risks of drinking water, fruits, and vegetable consumption. In the

387

current study, we found the maximum chronic daily intake (CDI) of total neonics (IMIRPF) as

388

a result of water consumption is 12.43 ng kg-1 d-1, significantly less than the CDIs resulting

389

from fruit and vegetable consumption (Figure 4), and contributes very little to the overall

390

risks, as compare to the RfD. In other word, fruits and vegetable consumption poses a higher

391

potential health risk of total neonics exposure than drinking water intake.

392

We acknowledged a limitation of this study, and that is the cross-sectional design of collecting

393

water samples once without repeated measurements. However, we believe that two findings

394

from the current study may suggest any temporal variations of neonics levels in drinking water

395

would not matter much to the overall dietary intake of neonics in individuals living in

39，

Hangzhou China. First of all, the capability of removing significant portion of neonics by the 1，

397

water treatment plants would minimize the impact of the temporal variations. Secondly, the

398

contributions of neonics intake from foods are much more significant than that from drinking

399

water consumption.

400 401

5. Conclusion

402

In conclusion, we found the modern drinking water treatment technologies operated by

403

the city of Hangzhou could remove significant amount of neonics from water, however,

404

approximately 96% of tap water samples that we collect from the household faucets

405

contained at least one neonic. From the perspective of assessing the risk of total neonics

40，

intake, drinking water consumption only represented an insignificant portion, comparing to

407

fresh fruit and vegetable consumption. Although the estimated daily intake of total neonics

408

(IMIRPF) resulting from drinking water consumption for people living in the five districts of

409

the city of Hangzhou China were significantly lower than the acceptable daily intake (ADI)

410

or reference dose (RfD) for imidacloprid, the ubiquity of neonics in drinking water, from

411

sources to household kitchen faucets, should raise the public health concern.

412 413

Acknowledgements

414

The National Natural Science Foundation of China (21777147, 21577129) supported this

415

study. Authors wish to thank the cooperation of technicians in those 4 drinking water

41，

treatment plants in Hangzhou China who are assisting in sample collection.

417

17

418

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22

551 552 553 554

Table 1. Summary statistics of individual concentrations (ng L-1), frequency of detection (%), and the total neonicotinoids (IMIRPF) concentrations (ng L-1) in source water (SW), before and after treatment plant water (b-TPW and a-TPW), and tap water (TW) samples collected from the city of Hangzhou, China. Sample

Summary

Type

Statistics

Neonicotinoids IMIRPF ACE

Limit

of

(N=5)

(N=5）

(N=71)

555 55， 557

DIN

NIT

7

30

40

88

44

100

94

0

25

25

n.a.

Mean

17.6

4.8

11.9

7.6

ND

2.4

1.6

127.88

(st. dev.)

(10.3)

(9.8)

(6.7)

(6.5)

(0)

(9.5)

(3.2)

(145.1)

Max.

34.4

29.6

31.7

29.5

ND

20.1

10.2

539.6

80

0

100

80

0

20

40

n.a.

Mean

11.2

ND

9.0

3.7

ND

3.0

3.8

47.99, 10

(st. dev.)

(6.6)

(0)

(3.6)

(2.3)

(0)

(6.7)

(7.3)

(24.3)

Max.

15.1

ND

13.1

5.8

ND

15.1

16.7

78.9

80

0

100

40

0

20

20

n.a.

Mean

5.9

ND

5.3

1.3

ND

2.1

2.1

23.39, 10

(st. dev.)

(5.3)

(0)

(3.5)

(1.7)

(0)

(4.7)

(4.7)

(20.9)

Max.

13.2

ND

9.2

3.3

ND

10.5

10.4

52.3

83

0

82

15

0

17

31

n.a.

Mean

5.8

ND

4.0

0.6

ND

1.8

2.5

17.210

(st. dev.)

(4.7)

(0)

(2.8)

(1.6)

(0)

(4.8)

(4.8)

(18.7)

15.5

ND

10.6

5.7

ND

25.0

22.6

105.4

Detection

Detection

Detection

Detection

Max. 1

THIAC

6

40

Freq. TW

5

70

Freq. a-TPW

CLO

4

40

Freq. b-TPW

IMI

3

60

Freq.

(N=16)

THIAM

2

30

Detection

SW

1

2

3

ACE: Acetamiprid. THIAM: Thiamethoxam. IMI: Imidacloprid. CLO: Clothiandin. 5THIAC: Thiacloprid. 6DIN: Dinotefuran. 7NIT: Nitenpyram., 8non-significantly different, 9significantly different (p<0.05), 10non-sginificant.

558

23

4

559 5，0 5，1 5，2

Table 2. Numbers of neonicotinoids detected and the frequency of detection (in parentheses) in source water, before and after treatment plant water, and tap water samples collected from five main residential districts in the city of Hangzhou, China. Sample type 0 Source water (N=16) Before-treatment plant water (N=5) After-treatment plant water (N=5) Tap water (N=71)

0 0 0 3 (4.2%)

Number of detected neonicotinoids 1 2 3 4 5 1 6 6 3 0 (6.3%) (37.5%) (37.5%) (18.8%) 1 2 1 1 0 (20%) (40%) (20%) (20%) 1 2 1 1 0 (20%) (40%) (20%) (20%) 11 28 25 4 0 (15.5%) (39.4%) (35.2%) (5.6%)

5，3 5，4

24

5，5

Figure Caption

5，，

Figure 1. Sampling locations for source water (SW) samples from Qiantang River and East

5，7

Shao Creek (pentagons), treatment plants water (TPW) samples from five drinking water

5，8

treatment plants (triangles), and tap water samples (blue, green, red, purple, and orange

5，9

circles) from seventy-one households living in five main districts of Hangzhou, China.

570 571

Figure 2. The changes of total neonicotinoids concentrations, expressed as the average of

572

IMIRPF (ng L-1), from sources thru five water treatment plants (a, b, c, d, and e) to kitchen

573

faucets in the households located in five main residential districts of Hangzhou China.

574 575

Figure 3. Distributions of total neonicotinoids, expressed as IMIRPF, (ng L-1) in sixteen

57，

source water (SW), five pairs of before and after treatment plant water (b-TPW and a-TPW),

577

and seventy-one tap water (TW), samples collected from seventy-one households living in

578

five main residential districts of the city of Hangzhou, China. a, IMIRPF concentrations were

579

significant different (two samples t-test, p<0.05); b, IMIRPF concentrations were not

580

significant different.

581 582

Figure 4 The cumulative distributions of the estimated chronic daily intake of total

583

neonicotinoids (IMIRPF) from drinking water consumption for adult (red line) and children

584

(orange line) and from fruits and vegetables consumption (green line, Zhang et al., 2019) for

585

children living in Hangzhou China.

58，

25

587 588 589 590 591

Fig. 1. Sampling locations for source water (SW) samples from Qiantang River and East Shao Creek (pentagons), treatment plants water (TPW) samples from five drinking water treatment plants (triangles), and tap water samples (blue, green, red, purple, and orange circles) from seventy-one households living in five main districts of Hangzhou, China.

592

2，

593 594 595 59， 597

Fig. 2. The changes of total neonicotinoids concentrations, expressed as the average of IMIRPF (ng L-1), from sources thru five water treatment plants (a, b, c, d, and e) to kitchen faucets in the households located in five main residential districts of Hangzhou China.

27

598 599 ，00 ，01 ，02 ，03 ，04 ，05

Fig. 3. Distributions of total neonicotinoids, expressed as IMIRPF, (ng L-1) in sixteen source water (SW), five pairs of before and after treatment plant water (b-TPW and a-TPW), and seventy-one tap water (TW), samples collected from seventy-one households living in five main residential districts of the city of Hangzhou, China. a, IMIRPF concentrations were significant different (two samples t-test, p<0.05); b, IMIRPF concentrations were not significant different.

28

，0， ，07 ，08 ，09 ，10

Fig. 4. The cumulative distributions of the estimated chronic daily intake of total neonicotinoids (IMIRPF) from drinking water consumption for adult (red line) and children (orange line) and from fruits and vegetables consumption (green line, Zhang et al., 2019b) for children living in Hangzhou China.

29

Highlights •

Fate and transport of neonicotinoids in the drinking water treatment system

•

The ubiquity of neonics in drinking water

•

The effectiveness of removing neonics from drinking water treatment plants

•

Neonics in drinking water do not contribute significantly to the overall dietary risks

Declaration of competing financial interests Authors declare no actual or potential competing financial interest.

1

All authors declare no competing financial interests associated with the works presented here.