Using national sewage sludge data for chemical ranking and prioritization

Using national sewage sludge data for chemical ranking and prioritization

Journal Pre-proof Using national sewage sludge data for chemical ranking and prioritization Arjun K. Venkatesan, Rolf U. Halden PII: S2468-5844(19)30...

1MB Sizes 0 Downloads 37 Views

Journal Pre-proof Using national sewage sludge data for chemical ranking and prioritization Arjun K. Venkatesan, Rolf U. Halden PII:

S2468-5844(19)30060-1

DOI:

https://doi.org/10.1016/j.coesh.2019.10.006

Reference:

COESH 146

To appear in:

Current Opinion in Environmental Science & Health

Received Date: 20 August 2019 Revised Date:

18 October 2019

Accepted Date: 25 October 2019

Please cite this article as: Venkatesan AK, Halden RU, Using national sewage sludge data for chemical ranking and prioritization, Current Opinion in Environmental Science & Health, https://doi.org/10.1016/ j.coesh.2019.10.006. 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 Elsevier B.V. All rights reserved.

1

Using national sewage sludge data for chemical ranking and prioritization

2

Arjun K. Venkatesan a,*, Rolf U. Halden b

3

a

4

Engineering, Stony Brook University, Stony Brook, New York, 11794

5

b

6

University, 1001 S McAllister Avenue, Tempe, AZ 85287-8101

7

*

Center for Clean Water Technology, Department of Civil Engineering, 250C Heavy

Biodesign Center for Environmental Health Engineering, The Biodesign Institute, Arizona State

Corresponding Author email: [email protected]; phone: +1 (631) 632-1998

8 9

Abstract

10

Treated sewage sludges (SS) or biosolids are rich in organic carbon, nutrients and, unfortunately,

11

chemical contaminants. Accumulation of chemicals in SS is influenced by the mass of chemical

12

produced and released into wastewater, resistance to (bio)degradation during treatment and the

13

chemicals’ propensity to sorb to particulates. Hence, accumulation of chemicals in SS is

14

indicative of their persistent and bioaccumulative behavior: the two characteristics that are

15

predominantly used for chemical prioritization. Thus, it is possible for risk assessors to use

16

existing SS survey data to identify, rank and prioritize persistent and bioaccumulative chemicals

17

present in the human society. In this review, we highlight unique papers that utilized this concept

18

to help prioritizing chemical contaminants in SS and the environment. We additionally showcase

19

a simple decision flowchart and scoring algorithm for prioritizing chemicals whose presence in

20

SS warrants further investigation.

21 22

Keywords: Biosolids; Sewage sludge; PBT chemicals; Chemical prioritization; Chemical

23

ranking; Chemical risk

1

24 25

1. Introduction

26

Municipal sewage sludge (SS) is an abundant byproduct of wastewater treatment. The SS matrix

27

is rich in organic carbon and nutrients, and hence >50% of the dry mass of municipal SS

28

produced in the United States currently is applied on land for inexpensive disposal and as soil

29

amendment (fertilizer) [1-3]. Research over several decades has shown that SS, unfortunately,

30

also is rich in pollutants such as toxic metals, pathogens, and organic contaminants [2,4-7].

31

Hence, land application of SS has been, and is, considered a controversial practice in the U.S.

32

and worldwide [8-12]. Looking at the presence of chemical contaminants in SS from a different

33

perspective, one could also say that SS is efficiently capturing and removing toxic, persistent and

34

highly bioaccumualtive chemicals present in reclaimed water during wastewater treatment,

35

which otherwise would be discharged into the environment along with treated effluent. The

36

presence of elevated levels of captured organic contaminants in SS, in essence, is evidence for

37

the effectiveness of wastewater treatment to remove pollutants from sewage and to prevent the

38

release of sewage-borne contaminants into the aquatic environment.

39 40

Chemicals accumulating in SS are the same chemicals used in every-day products for personal

41

care (shampoos, detergents, etc.), health care (prescription drugs), and other household purposes

42

(flame retardation, food preservation, etc.) [2, 13]. Although there are many variations of

43

wastewater treatment plants (WWTPs), a conventional treatment plant employs at a minimum

44

the following steps: pre-treatment (to remove large objects), primary treatment (sedimentation

45

tanks), secondary treatment (e. g., activated sludge system with secondary sedimentation step),

46

and handling of the solids generated (e. g., anaerobic digestion of SS). The secondary treatment

2

47

of municipal sewage consists of a biological treatment system that employs a highly complex

48

microbial community optimized to remove most of the organics present in the wastewater.

49

Chemicals that withstand the secondary biological treatment process have to be considered

50

notably resistant to biodegradation and thus have the potential to also persist in the environment

51

upon their release in reclaimed water or SS. Secondary treatment also may be viewed as a large-

52

scale biodegradability test for chemicals. Thus, if a chemical is not significantly attenuated

53

during treatment and still present in the two end products of wastewater treatment, namely

54

treated effluent (reclaimed water) and SS (biosolids), then it must be considered persistent and

55

potentially contaminating for the environment. This concept was introduced in the past, where

56

researchers recognized that WWTPs are observatories to study the environmental fate of

57

chemicals used in commerce [13]. The relative abundance of chemicals in these two end-

58

products of WWTP depends on the chemicals’ partitioning behavior; i.e., persistent hydrophilic

59

chemicals will be abundant in treated wastewater, whereas persistent hydrophobic chemicals will

60

accumulate in biosolids (Figure 1). Additionally, the levels at which they occur in these two

61

treatment process flows is related to the chemical’s production volume in commerce and to the

62

fraction that is disposed of into wastewater [13]. Wastewater-based epidemiology (WBE)

63

enables an estimation of the consumption volume of chemicals from their levels detected in raw

64

wastewater entering the treatment facility [14-18]. Thus, analogous to WBE, data on chemical

65

concentration in SS (e.g., national SS surveys) allow one to identify persistent and potentially

66

bioaccumulative compounds that may represent contaminants of emerging concern (CECs) in the

67

communities served by the respective WWTP.

3

Influent: Used for WBE approach to estimate chemical consumption irrespective of persistence

68

Wastewater Treatment Plant

Effluent: Captures persistent and hydrophilic chemicals used in commerce

Biosolids: Captures persistent and hydrophobic (bioaccumulative) chemicals used in commerce

69

Figure 1. Overview of how the major process streams of wastewater treatment may be used to

70

prioritize chemicals with respect to their occurrence and threats posed.

71 72

2. Chemical prioritization in SS

73

National SS surveys are a valuable data source for advancing the understanding of what is

74

present in the treated SS and for evaluating the risks posed by sludge-borne, toxic pollutants. In

75

the United States, the U.S. Environmental Protection Agency (U.S. EPA) thus far has conducted

76

four national SS surveys to identify inorganic and organic contaminants of potential regulatory

77

concern [19,20]. The samples from the 2001 and 2007 (the most recent) surveys, now acquired

78

and archived by the National Sewage Sludge Repository (NSSR) within the Human Health

79

Observatory (HHO) at Arizona State University, have been tested for hundreds of organic CECs

80

providing nationwide chemical inventories [2]. A study conducted in 2014 [13], used the U.S.

81

national SS monitoring data to conveniently identify and prioritize chemicals based on

82

abundance and bioaccumulation potential. Results from the paper highlighted that (i) the

83

chemicals detected in excess of 1 mg/kg in SS were all high production volume (HPV)

84

chemicals, i.e., produced and used in commerce in excess of one million pounds per year; (ii) of

85

the 55 chemicals identified as being potentially bioaccumulative [i.e., featuring an n-octanol

86

water partitioning coefficient (KOW) of greater than 105], 93% were halogenated; (iii) eight CECs

87

were identified as priority chemicals based on their abundance and bioaccumulation potential; 4

88

these included penta-brominated diphenylether (BDE-99), deca-brominated diphenylether (BDE-

89

209), 1,2-bis(2,4,6-tribromophenoxy)ethane (BTBPE), nonylphenol (NP), nonylphenol

90

ethoxylates (NPEs, specifically NP-monoethoxylate, NP-diethoxylate), triclosan (TCS), and

91

triclocarban (TCC); and (iv) chemicals detected in the national SS survey samples, when

92

compared with chemicals inventorized by biomonitoring as toxic pollutants in humans, revealed

93

an overlap of 70%, confirming the utility of using inexpensive and non-invasive monitoring of

94

SS to estimate the type and average body burden of toxic pollutants present in local or national

95

populations.

96 97

Methods for prioritizing organic contaminants typically use chemical properties to predict the

98

likely occurrence and persistence of chemicals in SS [21]. A Canadian study used four

99

physicochemical descriptors (volatility, organic carbon-partition coefficient, biodegradability,

100

and hydrolysis) to rank chemicals on an overall scale from 2 (low priority) to 9 (high priority)

101

[21]. The authors made use of the HPV chemical list to randomly select 34 chemicals that were

102

not previously analyzed in their study, and applied this predictive approach using structure

103

activity relationship models. One chemical, BDE-209, received the maximum rank score of 9,

104

and at that time (in year 1996) had not yet been analyzed in SS. However, later work showed that

105

BDE-209 indeed was abundant in SS [13], and emerged in the investigation as a confirmed high-

106

priority pollutant of SS. An important limitation of non-analytical approaches is that for many

107

chemicals, reliable values of physical-chemical parameters needed for predicting partitioning in

108

SS are not available.

109

5

110

In another recent study conducted in Finland, multi-criteria decision analysis (MCDA) was used

111

to build a decision support tool (DST) for selecting the optimal SS treatment [22]. In

112

constructing the DST, the authors used the occurrence of specific organic contaminants

113

considered to be risky as an important decision criterion. Similar to the Canadian study [21], the

114

authors scored the chemical based on toxicity, accumulation (in soil, plants and animals), and

115

risk to groundwater and surface water on a scale from 0 (low priority) to 11 (high priority).

116

Perfluorooctanoic acid (PFOS) was ranked the highest (value 9), followed by polychlorinated

117

dibenzodioxins and furans (PCDD/F) and polychlorinated biphenyls (PCBs). In contrast to the

118

U.S. [13] and Canadian [21] studies, the authors scored polybrominated diphenyl ethers (PBDEs)

119

and nonylphenols and their ethoxylates (NP & NPE) with lower scores of 7 and 3, respectively.

120

This was because the latter study used occurrence only, but not abundance (or concentration), for

121

assessing risks of SS-borne contaminants. Whereas PBDE and NP/NPEs feature toxicity values

122

that are lower when compared to dioxins and PCBs, they occur at quantities several orders of

123

magnitude higher than PCDD/F and PCB, thereby driving the risk from land application [2].

124

The importance of considering contaminant abundance was highlighted in a study where

125

researchers developed a quantitative risk ranking model to evaluate human exposure to CECs by

126

utilizing predicted environmental concentrations in soil, surface runoff, groundwater and from

127

the ingestion of contaminated drinking water [23]. The predicted concentrations used in the

128

model were calculated from average concentration of the chemicals in SS, thus incorporating the

129

abundance of the chemical as an important parameter for risk determination. Similar to the U.S.

130

study, the authors ranked NP as posing the largest threat among all contaminants to human

131

health. The model also highlighted TCS and TCC as CECs requiring further investigation,

132

cementing a conclusion previously drawn by others [6,24]. Noteworthy, both TCS and TCC later

6

133

were banned in consumer products in the U.S. [25] by the Food and Drug Administration,

134

thereby validating the utility of risk prioritization approaches using SS as a diagnostic matrix.

135 136

3. Decision flowchart for chemical ranking and prioritization using SS data

137

From the models discussed in the previous section, some common characteristics of chemicals

138

were used for ranking and prioritization: persistence (P), bioaccumulation (B), toxicity (T) and/or

139

long-range transportation potential (LRTP) [26]. These characteristics, especially P & B, are

140

commonly employed in risk assessment framework by the U.S. EPA [27], and by other countries

141

[28-30]. As shown in multiple studies [13,21,23], SS is a useful matrix for identifying chemicals

142

of the P and B category, and for estimating the mass of CECs released in reclaimed water and

143

land-applied SS [31-33]. Hence, one could use the SS monitoring data to prioritize P and B

144

contaminants, and also to identify contaminants likely to leach into groundwater or surface water

145

after land application. A decision flowchart was developed based on this concept (Figure 2) to

146

score and rank CECs based on concentration in SS, and the chemical’s octanol-water partitioning

147

coefficient (KOW).

148 149

Since persistence has been shown to be inherent to chemicals detected in SS [13], only the

150

concentration in SS (indirectly representing chemical abundance in commerce and disposal into

151

wastewater), and bioaccumulation potential are scored on a scale from 1 to 3 (i.e., low to high

152

concern). These scores are then added up to provide a single score (2 to 6), which can be used to

153

compare chemicals and prioritize them for further investigation (toxicity and risk assessment).

154

As opposed to making use of only physical-chemical properties to prioritize CECs as performed

155

by non-analytical methods, the proposed tool additionally incorporates the true abundance of the

7

156

compound in the environment. In order to validate the applicability of the proposed ranking

157

technique, we compared the scores obtained from SS analysis with the traditional scoring

158

calculated using only P and B characteristics of chemicals (Table 1, Figure 3). National SS Analysis Abundance >1000 µg/kg dry wt.

Y

High (Score = 3)

N 1-1000 µg/kg dry wt.

Y

N

Low (Score = 1)

Y

KOW> 105

Highly Bioaccumulative (Score =3)

Non- to Moderately Bioaccumulative (Score = 1-2)

N

Persistent CEC likely to bioaccumulate Sum of scores = 2-6

Persistent CEC with moderate to high leachability from SS Sum of scores = 1-5

159

Medium (Score = 2)

Priority chemicals with score 5: Antimicrobials = TCS, TCC Antibiotics = Ciprofloxacin, Ofloxacin, Azithromycin

Priority chemicals with score 6: Surfactants = NP & NPEs Flame retardants = BDE-99, BDE-209; BTBPE

160

Figure 2. Decision flowchart for pre-screening priority contaminants of emerging concern

161

(CECs) using data from the national SS survey. 8

162 163

Table 1. Scoring criteria based on P and B characteristics of chemicals. Characteristics Persistence

Bioaccumulation

Criteriaa Half-life, days <60 60 to 180 >180 Bioconcentration factor <1000 1000 to 5000 >=5000

Interpretationb

Low (1) Medium (2) High (3) Low (1) Medium (2) High (3)

a

Source: [34] The U.S. EPA does not provide numerical scores as shown within parentheses; these were included in this study for comparison purposes only.

b

164 165

The comparison of P + B scores and the SS scores for 73 chemicals detected with varying

166

abundances in national SS data is shown in Figure 3 (see supplemental Table S1). These 73

167

chemicals were selected based on the availability of P and B data in the U.S. EPA’s PBT Profiler

168

and SciFinder® (Chemical Abstract Services) software packages. About 42% of the chemicals

169

had the same scores from both approaches and ~48% of the chemicals had a P + B score within a

170

range of ±1 of the SS scores (15% underestimated (P + B score -1) and 33% overestimated (P +

171

B score + 1) by the SS analysis approach.) These results suggest that the proposed SS scoring

172

technique is valuable and accurate in capturing P and B chemicals in the environment.

173

Interestingly, ~10% of the chemicals’ SS scores were greater than a value of 2 compared to the

174

calculated P + B score. These include three surfactants (NP and NPEs), one flame retardant

175

(BDE-209), and three pharmaceuticals and personal care products (TCS, TCC, and ibuprofen).

176

9

8 (NP)

Proposed SS Score

(NPEs)

2

6

1

1

1

2

8

1

1

8

5

3

7

25

5

(TCS, TCC)

4

(Ibuprofen)

(BDE-209)

3

2 n = 73

0 0

2

4 P + B Score

6

8

177 178

Figure 3. Comparison of scores obtained for 73 chemicals from the proposed SS analysis

179

approach and P + B approach. P- persistence; B- bioaccumulation. P + B scores are based on

180

values in Table 1 and are scored out of a total score of 6 (1-3 for each P and B). SS scores were

181

obtained as shown in the decision flow chart in Figure 2. The center line represents equal scores

182

in both approaches, while the dotted line represents ±1 deviation from equal scores. The number

183

next to the point corresponds to the number of chemicals satisfying that score value. The

184

chemicals with significantly different scores (≥ 2) are named next to the point in parenthesis.

185 186

The difference in scores observed for these chemicals between the two approaches is due to the

187

incorporation of chemical abundance information in SS scoring approach. For example, NP has a

188

half-life of 140 days in the environment and a BCF of 120 leading to a P+B score of only 3. NP

189

is a HPV chemical and significant amounts of this chemical have been detected in environmental

190

matrices [35]. The U.S. national SS data from 2001 samples showed a mean concentration of

191

534.2 mg/kg for NP, resulting in a score of 3 for “abundance” and a score of 3 for its

192

bioaccumulative property (KOW>105) [13]. For this reason, the SS approach scores this chemical 10

193

as a high priority chemical with a maximum score of 6. The same reasoning holds true for the

194

other five chemicals that were underestimated by the P + B scoring technique. In addition to

195

identifying P & B chemicals, the proposed scoring tool can also identify chemicals that is likely

196

to leach from land-applied SS based on the lower KOW value (Figure 2). It must be noted that

197

many of the chemicals detected in SS are ionizable [36], and hence the mobility of the

198

compounds is determined by the pH of the SS and soil environment [37]. A better representation

199

of their leachability would be to use the pH-adjusted KOW values (DOW) as highlighted in past

200

studies [33,36].

201 202

4. Conclusions and future directions

203

It is estimated that about 2,500 new chemicals are introduced each year in the U.S., equivalent to

204

a rate of seven new chemicals per day [38]. Identifying problematic chemicals is a time-

205

consuming process and thus developing interventions through policies and laws may take several

206

decades to address risks to humans and the environment. The SS scoring approach proposed

207

here, that makes use of available national SS monitoring data, promises to provide an inventory

208

of priority CECs for future assessment. Along with other tools, it may serve as valuable tool

209

helpful in speeding up the data mining process for identifying priority chemicals of concern. This

210

list of chemicals can be further expanded by applying non-target screening in SS samples; this

211

was demonstrated in one study [39], where the researchers identified several siloxanes and

212

organophosphate flame retardants as emerging contaminants in the Artic region. These two

213

groups of chemicals represented 68% of the suspect chemicals detected in the SS samples

214

analyzed in the study [39], further supporting the notion of using SS as an indicator matrix to

215

identify P & B chemicals in the environment. However, this approach also has limitations in that

11

216

it does not inform on the toxicity of chemicals. It is possible that chemicals ranked lower via this

217

approach are highly toxic (e.g., PCBs, dioxins etc.), and hence a more comprehensive approach

218

would be to integrate a toxicity score with the SS score. Also, this tool is applicable only to

219

sludge-borne chemicals; but if one could analyze WWTP effluent, a much wider range of

220

chemicals also could be screened in a similar way, including hydrophilic CECs. A recent study

221

[40] utilized a similar approach to identify CECs relevant for reclaimed water reuse (managed

222

aquifer recharge) by considering usage volumes, ecological and health effects, and

223

concentrations of CECs in wastewater effluents. The researchers identified eight potential CECs

224

that required further treatment for potable water reuse applications, namely: PFOS,

225

perfluorooctanoate (PFOA), ibuprofen, carbamazepine, diclofenac, erythromycin,

226

sulfamethoxazole, and NP. All these chemicals were also detected in national SS samples at

227

varying abundance (Table S1), and additionally ibuprofen and NP were also ranked as high

228

priority chemicals in SS via the proposed ranking approach in this study. Hence, this ranking tool

229

using existing SS monitoring data can be useful for risk assessors as a pre-screening approach to

230

conveniently identify and prioritize chemicals for further investigations.

231 232

Acknowledgments

233

This study was supported in part by Award Number R01ES020889 from the National Institute of

234

Environmental Health Sciences (NIEHS) and by award LTR 05/01/12 of the Virginia G. Piper

235

Charitable Trust. The content is solely the responsibility of the authors and does not necessarily

236

represent the official views of the sponsors.

237 238

12

239

References

240

1. North East Biosolids & Residuals Association (NEBRA): A national biosolids regulation,

241

quality, end use & disposal survey. NEBRA, Tamworth, NH 2007.

242

2. Venkatesan AK, Done HY, Halden RU: United States National Sewage Sludge Repository

243

at Arizona State University—a new resource and research tool for environmental scientists,

244

engineers, and epidemiologists. Environ. Sci. Pollut. Res. 2015, 22:1577-1586.

245

3. Harrison EZ, Oakes SR, Hysell M, Hay A: Organic chemicals in sewage sludges. Sci. Total

246

Environ. 2006, 367:481-497.

247

4. McBride M: Toxic metals in sewage sludge-amended soils: has promotion of beneficial

248

use discounted the risks? A Adv. Environ. Res. 2003, 8:5-19.

249

5. Sidhu JP, Toze SG: Human pathogens and their indicators in biosolids: a literature

250

review. Environ. Int. 2009, 35:187-201.

251

6. Clarke BO, Smith SR: Review of ‘emerging’ organic contaminants in biosolids and

252

assessment of international research priorities for the agricultural use of biosolids. Environ.

253

Int. 2011, 37:226-247.

254

7. Westerhoff P, Lee S, Yang Y, Gordon GW, Hristovski K, Halden RU, Herckes P:

255

Characterization, recovery opportunities, and valuation of metals in municipal sludges

256

from US wastewater treatment plants nationwide. Environ. Sci. Technol. 2015, 49:9479-

257

9488.

258

8. Lu Q, He ZL, Stoffella PJ: Land application of biosolids in the USA: A review. Appl.

259

Environ. Soil Sci. 2012, 2012:1-11.

13

260

9. Oberg G, Mason-Renton SA: On the limitation of evidence-based policy: Regulatory

261

narratives and land application of biosolids/sewage sludge in BC, Canada and Sweden.

262

Environ. Sc. Policy. 2018, 84:88-96.*

263 264

In this study, the authors discuss about the differences in the regulatory frameworks pertaining to

265

land application of sewage sludge between Sweden, which is governed by the EU Directive

266

86/278/EEG, and the Canadian province of British Columbia, which is similar to the US EPA

267

503 Rule.

268 269

10. Al-Gheethi A, Noman EA, Mohamed R, Abdullah AH, Amir Hashim M: Microbial Risk

270

Associated with Application of Biosolids in Agriculture. Handbook. Environ. Mater. Manage.

271

2018:1-11.

272

11. Yoshida H, ten Hoeve M, Christensen TH, Bruun S, Jensen LS, Scheutz C: Life cycle

273

assessment of sewage sludge management options including long-term impacts after land

274

application. J. Clean. Prod. 2018, 174:538-547.

275

12. Pulkrabová J, Černý J, Száková J, Švarcová A, Gramblička T, Hajšlová J, Balík J, Tlustoš P:

276

Is the long-term application of sewage sludge turning soil into a sink for organic

277

pollutants?: evidence from field studies in the Czech Republic. J. Soils Sediment. 2019,

278

19:2445-2458.

279

13. Venkatesan AK, Halden RU: Wastewater treatment plants as chemical observatories to

280

forecast ecological and human health risks of manmade chemicals. Sci. Rep. 2014, 4:3731.

14

281

14. Gushgari AJ, Venkatesan AK, Chen J, Steele JC, Halden RU: Long-term tracking of opioid

282

consumption in two United States cities using wastewater-based epidemiology approach.

283

Water Res. 2019, 161:171-180.

284

15. Chen J, Venkatesan AK, Halden RU: Alcohol and nicotine consumption trends in three

285

US communities determined by wastewater-based epidemiology. Sci. Total Environ. 2019,

286

656:174-183.

287

16. Venkatesan AK, Chen J, Driver E, Gushgari A, Halden RU: Assessing the Potential To

288

Monitor Plant-Based Diet Trends in Communities Using a Wastewater-Based

289

Epidemiology Approach. In Wastewater-Based Epidemiology: Estimation of Community

290

Consumption of Drugs and Diets. Edited by: ACS Publications; 2019:187-198.

291

17. Gao J, O'Brien J, Lai FY, van Nuijs AL, He J, Mueller JF, Xu J, Thai PK: Could wastewater

292

analysis be a useful tool for China?—A review. J. Environ. Sci. 2015, 27:70-79.

293

18. Daughton CG: Monitoring wastewater for assessing community health: Sewage

294

Chemical-Information Mining (SCIM). Sci. Total Environ. 2018, 619:748-764.*

295 296

The author of this work was the first to identify the use of wastewater monitoring as a tool to

297

inform on population health. This paper provides an update on the sewage chemical-information

298

mining tool, from which the so-called wastewater-based epidemiology approach was developed

299

and applied by other researchers. In essence, the sewage sludge chemical prioritization tool

300

proposed in this paper is an extrapolation of this concept.

301

15

302

19. U.S. EPA: Targeted national sewage sludge survey statistical analysis report.

303

Washington, DC.: United States Environmental Protection Agency Office of Water. doi: EPA-

304

822-R-08-018 2009.

305

20. U.S. EPA: 2001 National Sewage Sludge Survey Report. 2007:

306

https://www.epa.gov/sites/production/files/2018-11/documents/2001-tnsss-report.pdf.

307

21. Webber M, Rogers H, Watts C, Boxall A, Davis R, Scoffin R: Monitoring and

308

prioritisation of organic contaminants in sewage sludges using specific chemical analysis

309

and predictive, non-analytical methods. Sci. Total Environ. 1996, 185:27-44.

310

22. Turunen V, Sorvari J, Mikola A: A decision support tool for selecting the optimal sewage

311

sludge treatment. Chemosphere 2018, 193:521-529.*

312 313

This is a recently published study, where the authors used multi-criteria decision analysis to

314

build a decision support tool (DST) for selecting the optimal sewage sludge treatment. Important

315

decision criteria included different treatment methods and the presence of organic contaminants

316

in the final treated sludge. The study provided a systematic and transparent process for making a

317

justified decision on a sewage sludge treatment.

318 319

23. Clarke R, Healy MG, Fenton O, Cummins E: A quantitative risk ranking model to

320

evaluate emerging organic contaminants in biosolid amended land and potential transport

321

to drinking water. Hum. Ecol. Risk Assess. 2016, 22:958-990.

322

24. Halden RU, Lindeman AE, Aiello AE, Andrews D, Arnold WA, Fair P, Fuoco RE, Geer LA,

323

Johnson PI, Lohmann R: The Florence statement on triclosan and triclocarban. Environ.

324

Health Perspect. 2017, 125:064501.

16

325

25. Food and Drug Administration: FDA issues final rule on safety and effectiveness of

326

antibacterial soaps. FDA Web site 2016: https://www.fda.gov/news-events/press-

327

announcements/fda-issues-final-rule-safety-and-effectiveness-antibacterial-soaps.

328

26. Muir D, Zhang X, de Wit CA, Vorkamp K, Wilson S: Identifying further chemicals of

329

emerging arctic concern based on ‘in silico’ screening of chemical inventories. Emerg.

330

Contam. 2019, 5:201-210.

331

27. U.S. EPA: A Working Approach for Identifying Potential Candidate Chemicals for

332

Prioritization. Edited by; 2018: https://www.epa.gov/sites/production/files/2018-

333

09/documents/preprioritization_white_paper_9272018.pdf.

334

28. Moermond CT, Janssen MP, de Knecht JA, Montforts MH, Peijnenburg WJ, Zweers PG,

335

Sijm DT: PBT assessment using the revised annex XIII of REACH: a comparison with

336

other regulatory frameworks. Integr. Environ. Assess. Manag. 2012, 8:359-371.

337

29. Matthies M, Solomon K, Vighi M, Gilman A, Tarazona JV: The origin and evolution of

338

assessment criteria for persistent, bioaccumulative and toxic (PBT) chemicals and

339

persistent organic pollutants (POPs). Environ. Sci. Proc. Imp. 2016, 18:1114-1128.

340

30. Li Y, Zhang L, Liu X, Ding J: Ranking and prioritizing pharmaceuticals in the aquatic

341

environment of China. Science of The Total Environment 2019, 658:333-342.

342

31. Chari BP, Halden RU: Predicting the concentration range of unmonitored chemicals in

343

wastewater-dominated streams and in run-off from biosolids-amended soils. Sci. Total

344

Environ. 2012, 440:314-320.

345

32. Deo RP, Halden RU: In silico screening for unmonitored, potentially problematic high

346

production volume (HPV) chemicals prone to sequestration in biosolids. J. Environ. Monit.

347

2010, 12:1840-1845.

17

348

33. Deo RP, Halden RU: Empirical model for predicting concentrations of refractory

349

hydrophobic organic compounds in digested sludge from municipal wastewater treatment

350

plants. Environ. Chem. 2009, 6:544-550.

351

34. U.S. EPA: Sustainable Futures / P2 Framework Manual 2012 EPA-748-B12-001. Estimating

352

Workplace Exposure and Industrial Releases Using ChemSTEER. 2012:

353

https://www.epa.gov/sites/production/files/2015-05/documents/11.pdf

354

35. Soares A, Guieysse B, Jefferson B, Cartmell E, Lester J: Nonylphenol in the environment:

355

a critical review on occurrence, fate, toxicity and treatment in wastewaters. Environ. Int.

356

2008, 34:1033-1049.

357

36. Venkatesan AK, Halden RU: Modeling the pH-mediated extraction of ionizable organic

358

contaminants to improve the quality of municipal sewage sludge destined for land

359

application. Sci. Total Environ. 2016, 550:736-741.

360

37. Lachassagne D, Soubrand M, Casellas M, Gonzalez-Ospina A, Dagot C: Impact of sludge

361

stabilization processes and sludge origin (urban or hospital) on the mobility of

362

pharmaceutical compounds following sludge landspreading in laboratory soil-column

363

experiments. Environ. Sci. Pollut. Res. 2015, 22:17135-17150.

364

38. Department of Toxic Substances Control: Chemicals of Emerging Concern. 2019.

365

https://dtsc.ca.gov/environmental-chemistry-lab/chemicals-of-emerging-concern/

366

39. Lee S, Kim K, Jeon J, Moon H-B: Optimization of suspect and non-target analytical

367

methods using GC/TOF for prioritization of emerging contaminants in the Arctic

368

environment. Ecotox. Environ. Safe. 2019, 181:11-17.**

369

18

370

In this study, the researchers applied non-target screening in various environmental matrices to

371

identify contaminants of emerging concern for the Arctic environment. The analysis included

372

sewage sludge samples, which showed high detections of priority contaminants identified in the

373

study. This is the first study to employ suspect and non-target analysis using GC-TOF for

374

prioritizing contaminants in the Arctic region.

375 376

40. Yuan J, Van Dyke MI, Huck PM: Identification of critical contaminants in wastewater

377

effluent for managed aquifer recharge. Chemosphere 2017, 172:294-301.**

378 379

In this study the authors make use of a multi-criteria approach to identify priority contaminants

380

in wastewater effluent for managed aquifer recharge. The study showcased that a statistical

381

analysis of WWTP effluent monitoring data can facilitate the selection of critical and priority

382

contaminants. The approach is very similar to what is proposed in the present study for sewage

383

sludge and helps to identify persistent, hydrophilic contaminants not detected in sewage sludge

384

matrix.

385 386

19

Highlights • • • •

Sewage sludge (SS) is abundant with persistent (P) and bioaccumulative (B) chemicals National SS survey data has been used by researchers to prioritize P & B chemicals A decision flowchart and scoring algorithm was developed to rank contaminants SS can be used as diagnostic matrix by risk assessors for chemical prioritization

S1

Competing interests: The authors declare no competing interests.

S1