health risk assessment of organic micropollutants in greywater for potable reuse
TRANSCRIPT
Accepted Manuscript
Health risk assessment of organic micropollutants in greywater for potable reuse
Ramiro Etchepare , Jan Peter van der Hoek
PII: S0043-1354(14)00746-5
DOI: 10.1016/j.watres.2014.10.048
Reference: WR 10967
To appear in: Water Research
Received Date: 31 May 2014
Revised Date: 11 August 2014
Accepted Date: 21 October 2014
Please cite this article as: Etchepare, R., van der Hoek, J.P., Health risk assessment oforganic micropollutants in greywater for potable reuse, Water Research (2014), doi: 10.1016/j.watres.2014.10.048.
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No evaluation
Organic
micropollutants in
greywater
Log D ≥ 3
Established
drinking water
guideline available ?
Tier 1
Toxicity information
available ?
Calculation of a
benchmark value
Calculation of RQ value
Yes
No
Yes
No
No
Yes Tier 2
Tier 3
Selection of more
problematic compounds
Multiple barriers treatment
Potable water
Households
Greywater
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Health risk assessment of organic micropollutants in greywater for potable reuse 1
Ramiro Etcheparea,b, Jan Peter van der Hoekc,d 2
aLaboratório de Tecnologia Mineral e Ambiental, Departamento de Engenharia de Minas, PPGE3M, 3
Universidade Federal do Rio Grande do Sul, Av. Bento Gonçalves 9500, 91501-970, Porto Alegre-RS, 4
Brazil. Corresponding author: [email protected] 5
bCAPES Foundation, Ministry of Education of Brazil, Brasília – DF 70.040-020, Brazil. 6
cDelft University of Technology, Department Water Management, Stevinweg 1, 2628 CN Delft, The 7
Netherlands, [email protected] 8
dWaternet, Strategic Centre, Korte Ouderkerkerdijk 7, 1096 AC Amsterdam, The Netherlands, 9
Abstract 11
In light of the increasing interest in development of sustainable potable reuse systems, additional 12
research is needed to elucidate the risks of producing drinking water from new raw water sources. 13
This article investigates the presence and potential health risks of organic micropollutants in 14
greywater, a potential new source for potable water production introduced in this work. An 15
extensive literature survey reveals that almost 280 organic micropollutants have been detected in 16
greywater. A three-tiered approach is applied for the preliminary health risk assessment of these 17
chemicals. Benchmark values are derived from established drinking water standards for compounds 18
grouped in Tier 1, from literature toxicological data for compounds in Tier 2, and from a Threshold of 19
Toxicological Concern approach for compounds in Tier 3. A risk quotient is estimated by comparing 20
the maximum concentration levels reported in greywater to the benchmark values. The results show 21
that for the majority of compounds, risk quotient values were below 0.2, which suggests they would 22
not pose appreciable concern to human health over a lifetime exposure to potable water. Thirteen 23
compounds were identified with risk quotients above 0.2 which may warrant further investigation if 24
greywater is used as a source for potable reuse. The present findings are helpful in prioritizing 25
upcoming greywater quality monitoring and defining the goals of multiple barriers treatment in 26
future water reclamation plants for potable water production. 27
Key words: greywater, organic micropollutants, risk assessment, potable reuse, toxicological data 28
29
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1. Introduction 30
Treatment of wastewater for potable reuse is an emerging strategy being implemented worldwide to 31
supplement water resource portfolios, especially in arid and semi-arid regions, coastal communities 32
faced with saltwater intrusions and regions where the quantity and/or quality of the water supply 33
may be compromised. Many examples of potable reuse treatment trains are reported throughout 34
the world and recent discussions among water reuse experts have addressed the reliance on the 35
existing systems to produce acceptable and safe water to consume (Rodriguez et al., 2009; 36
Tchobanoglous et al., 2011; Pisani and Menge, 2013; Gerrity et al., 2013). 37
Due to an expected higher level of initial contamination in the source wastewater in comparison to 38
conventional source waters, potable reuse systems are being scrutinized more carefully by water 39
regulators. Accordingly, multi-barrier treatment systems are being applied to attain high levels of 40
chemical and microbial contaminant removal and to satisfy established drinking water regulations. 41
The evaluation of potable reuse schemes should be in line with the World Health Organization 42
guidelines for Water Safety Plans (WSP), which are usually applied for conventional drinking water 43
supplies (WHO, 2011). WSP are based on the human health risk assessment of the potable water 44
supply chain and take into consideration the hazards within the system, from the catchment to the 45
consumer, in relation to the risk of producing unsafe water. Although in most cases pathogen 46
removal requirements drive unit process selection and integration, another important major public 47
health concern is the potential health impacts from long-term, and in some cases, short-term 48
exposure to low concentration of chemicals and micropollutants present in the reclaimed water 49
(WHO, 2011). Therefore it is important to characterize contaminant loads and associated risks for all 50
potential drinking water sources, to adequately determine total removal required, identify 51
appropriate treatment trains and ultimately satisfy public health criteria. 52
Municipal wastewater treatment plant (WWTP) effluents have been the main source of water for 53
potable reuse schemes in large-scale installations (Gerrity et al., 2013). However, a general trend is 54
visible towards more decentralized and closed loop (onsite) systems as separating wastewater at the 55
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source and treating separately the different flows will offer possibilities to recover clean water, 56
nutrients and energy (Jefferson et al. 2000; Cook et al., 2009, van der Hoek et al., 2014). An example 57
of this is in the urban (domestic) environment, where “green buildings” are being commissioned in 58
growing number (Zuo et al., 2014) and water efficiency is accomplished through the collection, 59
treatment and reuse of rainwater, black water and greywater (Johnson, 2000). Additionally, 60
individual or cluster of housing estates and isolated communities, where there is no connection to 61
the public water supply and sewerage, may be benefitted with more readily available sources of 62
water for potable uses (Mwenge Kahinda et al., 2007; Cook et al., 2009). 63
In the present paper, greywater (GW), used here to refer to domestic wastewater excluding any 64
input from toilets (Jefferson et al., 2000), is introduced as an alternative potential source of water for 65
potable reuse. GW has been estimated to account for about 60-80% of domestic wastewater 66
(Eriksson et al., 2002b; Hernández Leal, 2010), yet, its chemical nature is quite different. For example, 67
the COD:BOD ratio can be as high as 4:1 (Boyjoo et al., 2013), indicating a high chemical content. It 68
must also be pointed out that GW can be highly variable in composition, being highly dependent on 69
the activities in the household, as well as the inhabitants’ lifestyles and use of chemical products. 70
Many previous works have been published on the characteristics of GW in relation to conventional 71
physical (temperature, colour, turbidity, electrical conductivity, suspended solids), chemical (BOD, 72
COD, TOC, pH, nutrients, heavy metals) and microbiological (bacteria, protozoa, viruses, helminths) 73
parameters and were recently reviewed and compiled by Boyjoo et al. (2013). 74
Despite its much lower pathogen content (absence of feces) and organic matter content, surprisingly, 75
GW has only been proposed for non-potable reuse applications, especially irrigation (Surendran and 76
Wheatley, 1998; Smith and Bani-Melhem, 2012; USEPA, 2012; Alfiya et al., 2013). Therefore the 77
associated risks are generally divided into two categories: environmental risks and human health 78
risks. Environmental risk assessments (ERA) related to detrimental effects of reclaimed water on soil 79
characteristics (Travis et al., 2010; Turner et al., 2013), plants growth (phytotoxicity – Garland et al., 80
2000; Pinto et al., 2010), surface/groundwater quality and aquatic/terrestrial organisms (van Wezel 81
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et al., 2002; Eriksson et al., 2006) are highly important to address environmental contamination 82
issues. Eriksson et al. (2002b) is one of the scarce studies addressing ERA of organic micropollutants 83
(OMPs) present in GW. Since using reclaimed GW for toilet flushing and car washing is also becoming 84
common, more information is available regarding (microbial) health risks for non-potable reuse 85
(Dixon et al., 1999; Maimon et al., 2010; O'Toole et al., 2012; Barker et al., 2013). Nevertheless, the 86
main challenge still waiting for advanced research development is to turn GW into potable water 87
quality (Oron et al., 2014) and very few studies have investigated the nature, loads and associated 88
health risks of OMPs in GW related to the use of GW as a new source for drinking water production. 89
The latter consists the focus of the present study. 90
At Delft University of Technology, in the Netherlands, a team of scientists, students and companies is 91
working on the Green Village, a temporary pilot site on the campus, which will be used to test new 92
technologies prior to their implementation in the development of the Green Campus, a more 93
ambitious project planned at the University (van der Hoek et al., 2014). The Green Village will not be 94
connected to water supply, the sewerage and cable systems. The aim is to develop it as an autarkic 95
and decentralized system, producing its own potable water (from GW) and electricity, and clean its 96
organic waste streams in a sustainable way. The present work is a first attempt, undertaken as part 97
of the Green Village project, at compiling a hazard assessment and risk characterization to identify 98
and understand the risks of potable water production from GW due to the presence of OMPs. 99
Although most studies investigating GW reuse and associated risks have focused on non-potable 100
applications and conventional water quality parameters, this work is intended to provide in-depth 101
and up-to-date compiled data on OMPs found in GW. This paper includes a preliminary health risk 102
assessment (screening level) by means of a theoretical and empirical framework (three-tiered 103
approach) of OMPs that may pose a risk to human health in reclaimed potable water and ends with a 104
discussion of the suitability of treatment barriers to mitigate problematic compounds. In part the 105
present study is aimed at helping prioritize further investigations in this subject. 106
2. Materials and methods 107
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If GW is to be treated and reused as potable water, a preliminary health risk assessment has to be 108
conducted to identify and determine which OMPs, at the concentrations present in GW, may pose a 109
potential health risk if not properly removed. The present work includes a risk characterization 110
conducted in four consecutive steps. First, an extensive literature review on the presence and 111
concentrations of OMPs in GW was conducted. Second, solute properties of the identified 112
compounds were obtained in order to prioritize the most relevant and problematic compounds and 113
exclude from the analysis those that are expected to be easily removed in conventional water and 114
wastewater treatment plants. Third, a three-tiered approach was applied to derive benchmark values 115
for the compounds with the aid of either statutory drinking water guidelines or toxicological 116
threshold values. Finally, measured maximum GW concentrations reported were compared to the 117
respective benchmark values and a risk quotient (RQ) was calculated. The detailed methodology used 118
for each of these steps is described in sections 2.1 through 2.4. and illustrated in Figure 1. Mixture 119
interactions were not quantified since the risk assessment methods for compounds with different 120
mode of action are a complex matter still under debate. 121
Figure 1. Flow chart indicating the risk assessment conducted in the present study. GW, greywater; 122
Log D, distribution coefficient; RQ, risk quotient. 123
2.1 Presence of organic micropollutants in greywater 124
A comprehensive literature review on the presence and concentrations of OMPs in GW was 125
performed. The survey did not include organic macro-pollutants, inorganic compounds such as 126
nutrients and metals since they have been extensively studied elsewhere, but was confined to 127
organic chemicals present in micro and nano-scale concentrations. The review covered the period 128
from 1991 to 2014, by consulting published (inter)national articles, conference proceedings, 129
academic theses and official reports. 130
2.2 Selection of compounds for assessment 131
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As it is not feasible to include every chemical in a toxicological assessment, the OMPs identified in 132
GW were prioritized based on their ability to easily pass conventional water treatment barriers, as 133
components not removed in conventional systems are likely to pose the most threat in potable reuse 134
of GW. 135
The n-octanol-water partition coefficient (log Kow) is a solute property related to hydrophobicity 136
which has been used as log cut-off to prioritize compounds in toxicological assessments (Schriks et 137
al., 2010). Compounds with a log Kow above 3 are less likely to pass water treatment plants that 138
include an activated-carbon adsorption stage than those with lower values (Westerhoff et al., 2005). 139
pH-corrected log Kow values are referred to as log D or distribution coefficient. The log D appears to 140
be a more accurate and conservative tool to predict the adsorption of ionic solutes than the log Kow 141
(Hu et al., 1997; Ridder et al., 2010). For neutral solutes, log Kow = log D, but for ionic solutes log D < 142
log Kow. In the present work, log D values were obtained with the aid of the estimation program 143
Marvin Sketch 6.2 and compounds with a log D ≥ 3 were excluded from further assessment. An 144
exception was made for 4 alkylphenol ethoxylates (octylphenol tetra-ethoxylate; octylphenol hexa-145
ethoxylate; octylphenol hepta-ethoxylate; and octylphenol octa-ethoxylate) which were not found on 146
the estimation software. For these compounds the log D values were obtained from literature (Ahel 147
and Giger, 1993). 148
2.3 Derivation of benchmark values with a three-tiered approach 149
Due to the potential toxicity of low doses of OMPs after mid- to long-term exposure and the 150
associated threat to public health, it was necessary to determine the concentrations of the selected 151
contaminants at which potential adverse health effects may occur. A three-tiered approach, as 152
similarly proposed by Rodriguez et al (2007), was applied in order to derive benchmark values. 153
Compounds with an established drinking water guideline or standard value, were allocated to “Tier 154
1”. Compounds without drinking water standards, but for which toxicity information is available were 155
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allocated to “Tier 2”. Those compounds for which toxicity information is not available were allocated 156
to “Tier 3”. 157
2.3.1 Tier 1: Regulated compounds 158
Conventionally, raw and treated potable water quality have been analysed by comparing the 159
measured concentration of a particular substance or parameter with the respective benchmark value 160
based on drinking water standards or guidelines. Because different states and nations regulate 161
different contaminants or may assign their own standard values for the same contaminant, it is 162
important to define the guidelines pertinent to a specific context. For the risk assessment of potable 163
reuse of GW in the Netherlands, the applicable maximum contaminant levels (benchmark values) 164
were extracted from the following drinking water guidelines, in order of priority: the Dutch Drinking 165
Water Decree (Staatsblad, 2011), the Guidelines for Drinking Water Quality (WHO, 2011), the 166
European Council Directive 98/83/EC (EC, 1998) and the 2011 Edition of the Drinking Water 167
Standards and Health Advisories (USEPA, 2011). However, since the established standards for the 168
parameters “pesticides” and “other anthropogenic compounds” in the Dutch Drinking Water Decree 169
were considered too generic to be used in the present risk assessment, their respective target values 170
were not used to derive benchmark values for pesticides and anthropogenic compounds. These 171
compounds were assessed individually. 172
2.3.2 Tier 2: Unregulated compounds with toxicity value 173
The first step of Tier 2 was to obtain toxicological threshold values for the assessed compounds 174
expressed as TDI (tolerable daily intake), ADI (acceptable daily intake) and/or RfD (reference dose) 175
from data sets and documents available from World Health Organization (WHO), U.S. EPA and other 176
reliable (inter)national sources which are presented in Table 1. If not available, a provisional TDI was 177
derived based on the lowest (sub) chronic no observed (adverse) effect levels (NO(A)ELs) obtained in 178
rodent studies divided by an assessment factor (AF) of either: 179
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• 100 – includes combined factor of 10 for interspecies extrapolation and factor of 10 for 180
inter-individual differences, 181
• 200 – includes an additional factor of 2 to extrapolate from subchronic to chronic exposure, 182
or 183
• 600 – includes an additional factor of 6 to extrapolate from subacute to chronic exposure, 184
depending on which was most applicable to the data available (Van Leeuwen and Vermeire, 2007). 185
Toxicological threshold values refer to the daily exposure likely to be without deleterious effects in 186
humans and therefore cannot be taken directly as drinking water standards but instead must be used 187
to derive benchmark values as described by the WHO (2011). In the present study the benchmark 188
values for drinking water were calculated using Equation 1. This method allocates 20% of the 189
reference intake value (TDI/ADI/RfD) for drinking water, to allow for exposure from other sources, 190
then multiplies this allocation by the typical average body weight of an adult (60 kg) and divides it by 191
a daily drinking water consumption of 2 L. Equation 2 was used to calculate the benchmark value 192
corresponding to a conservative cancer risk of 10-5 for carcinogenic compounds which have not been 193
assigned a toxicological threshold value but have a reported oral slope factor (SF) value instead 194
(WHO, 2011). 195
Table 1. Sources to obtain toxicological threshold values 196
Equation 1: 197
����ℎ������ � =������
�
Where: 198
T = toxicological threshold value (TDI/ADI/RfD) 199
bw = body weight (60 kg) 200
P = fraction of the TDI allocated to drinking water (20%) 201
C = daily drinking water consumption (2 L) 202
Equation 2: 203
����ℎ������ � =�����������
����
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Where: 204
Risk level = 10-5 205
SF = Slope factor 206
2.3.3 Tier 3: Compounds without toxicity value 207
For compounds without toxicity information, target values were derived from a Threshold of 208
Toxicological Concern (TTC) approach. The TTC is a conservative level of human intake or exposure 209
that is considered to be of negligible risk to human health, despite the absence of chemical-specific 210
toxicity data. The widely accepted TTC values proposed by Munro et al. (1996) and Kroes et al. (2004) 211
are set as: 212
• 0.0025 μg/kg bw/day for substances that raise concern for potential genotoxicity; 213
• 0.3 μg/kg bw/day for organophosphates; 214
• 1.5, 9 and 30 μg/kg bw/day for Cramer class III, II and I substances, respectively. 215
Thus, these values were applied for the present Tier 3 compounds. The thresholds for non-genotoxic 216
compounds were elaborated using a dataset published by Munro et al. (1996), related to chemical 217
classes as defined by Cramer et al. (1978) and are based on the 5th percentiles of NOELs covering 218
chronic oral exposure. Possible genotoxic compounds and the Cramer class classification of 219
compounds were identified in the present work through structural alerts aided by the OECD QSAR 220
3.2 application toolbox (URL 1). The present approach also considered the exclusion of compounds 221
for which no TTC could be derived such as high potency carcinogens (i.e. aflatoxin-like, azoxy- or N-222
nitroso- compounds, benzidines, hydrazines), metal containing compounds, proteins, steroids, 223
polyhalogenated-dibenzodioxin, -dibenzofuran, and –bisphenyl (Kroes et al., 2004). 224
The TTC values were further translated to benchmark values by taking into account the body weight 225
and daily ingestion of drinking water (Equation 3). The same body weight (60 kg), allocation factor 226
(20%) and water consumption rate (2 L) of Tier 2 were applied in Equation 3. 227
Equation 3 228
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����ℎ������ � =������� �������
�
2.4 Calculation of a risk quotient 229
To evaluate the potential health risks and toxicological relevance of the assessed compounds, the 230
maximum concentration levels identified in GW were divided by the benchmark value and expressed 231
as a RQ. Compounds with a RQ ≥ 1 may be of potential human health concern if treated GW were to 232
be consumed over a lifetime period. These compounds would be of high-priority at the selection and 233
design of future GW treatment plants for potable water production. As similarly proposed by Schriks 234
et al. (2010), compounds in GW with a RQ value ≥ 0.2 and < 1, are considered to also warrant further 235
investigation. Compounds in GW with a RQ value < 0.2 are presumed to present less appreciable 236
concern to human health. 237
3. Results 238
3.1 Organic micropollutants in greywater 239
OMPs became a focus for GW research in the 1990’s after two articles (Burrows et al., 1991; Santala 240
et al., 1998) reported the presence of detergents and long-chain fatty acids detected through a GC-241
MS screening. A more comprehensive study in this field of research, which identified as many as 900 242
xenobiotic organic compounds (XOCs) as potentially present in GW, was performed by Eriksson et al. 243
(2002), using tables of contents of Danish household products (bathroom and laundry chemicals). 244
The XOCs are expected to be present in GW because they originate from the various chemicals and 245
personal care products used in households such as cleaning agents (detergents, soaps, shampoos), 246
fragrances, UV-filters, perfumes and preservatives. Subsequent screening of bathroom GW from an 247
apartment building in Denmark confirmed almost 200 different XOCs (Eriksson et al., 2003). 248
However, as the study also detected some unexpected chemicals not directly connected to 249
household chemicals (e.g. flame retardants and illicit drugs), it can be concluded that an inventory of 250
the use of household chemicals cannot compensate for a full characterization of the compounds 251
actually present in GW. In a later study investigating the concentrations of several selected organic 252
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hazardous substances in GW from housing areas in Sweden, Palmquist & Hanæus (2005, 2006) found 253
that 46 out of more than 80 organic substances were present in concentrations above the detection 254
limits. 255
Quite recently, Donner et al. (2010) reviewed the knowledge with respect to the presence of XOCs in 256
GW and investigated the sources, presence and potential fate of xenobiotic micropollutants in on-257
site GW treatment systems. However, Donner’s investigation focused on non-potable reuse of GW 258
and was limited to a few compounds selected from those listed either as Priority Substances or 259
Priority Hazardous Substances under the European Water Framework Directive (WFD) (EU, 2000). So 260
far the WFD has established environmental quality standards (EQS) for 41 dangerous chemical 261
substances (33 of them classified as priority substances). However, these are only a fraction of the 262
compounds that are potentially hazardous as this list does not include, for instance, any 263
pharmaceutical compounds or personal care products. 264
In spite of these findings, the number of publications on the monitoring and analysis of OMPs in GW 265
is still scarce. There are, to the best of our knowledge, 12 published studies on this topic, where GW 266
was produced, sampled and analysed from 7 different locations (5 housing estates, 1 camping site 267
and 1 sport club) spread in Sweden, Denmark and the Netherlands (Eriksson et al., 2003; Andersson 268
and Dalsgaard, 2004; Nielsen and Pettersen, 2005; Palmquist & Hanæus, 2005, 2006; Larsen, 2006; 269
Ledin et al., 2006; Andersen et al., 2007; Hernández Leal et al., 2010; Eriksson et al., 2009; Revitt et 270
al., 2011; Temmink et al., 2011). In total, 278 OMPs have been detected in GW considering all 271
available literature data. The full list of the OMPs identified and their concentrations is provided in 272
supplementary information, Table S1. Identified compounds were grouped into eleven substance 273
classes: 1) Plasticisers and softeners; 2) Preservatives; 3) UV filters; 4) Surfactants and emulsifiers; 5) 274
Flavours and fragrances; 6) Polycyclic aromatic hydrocarbons (PAHs); 7) Polychlorinated biphenyls 275
(PCBs); 8) Solvents; 9) Brominated flame retardants; 10) Organotin compounds; and 11) 276
Miscellaneous. 277
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3.2 Selection of compounds 278
The outcome of the prioritization of OMPs found in GW resulted in the identification of 89 279
compounds (log D < 3) out of the original list. These compounds were selected for further 280
assessment. Of these 89 chemicals surfactants contributed 5, fragrances and flavours 26, plasticisers 281
4, preservatives 17, solvents 10, organotin compounds 3, UV filter 1, PAH 1, and other miscellaneous 282
compounds 22. These OMPs and their respective CAS numbers and log D values are listed in Table S2 283
(supplementary data). 284
3.3 Preliminary health risk assessment of selected OMPs in GW 285
The final list of OMPs in GW with their respective benchmark values and RQ values is provided in 286
Table 2. For only 5 compounds (benzene, dichloromethane, ethylbenzene, pentachlorophenol and 287
trichloromethane) statutory drinking water guideline values were available and these compounds 288
were grouped into Tier 1. The benchmark values of Tier 1 ranged from 1 µg/L (benzene) to 300 µg.L-1 289
(ethylbenzene and trichloromethane, respectively) and originated from the Dutch Drinking Water 290
Decree, the WHO Guidelines for Drinking Water Quality and the USEPA, according to the order of 291
priority set in the present work. Toxicological data were found for 39 compounds (Tier 2). An 292
established TDI, ADI or RfD was available for 27 compounds and in 11 cases when there was no TDI, 293
ADI or RfD available, an established NO(A)EL was utilized to derive a TDI value with the aid of 294
assessment factors. Specifically for the carcinogenic 2,4,6-trichlorophenol there was a SF available 295
from EPA-IRIS. The remaining 45 compounds with no toxicological data were grouped into Tier 3. The 296
latter comprised 29 compounds allocated to Cramer class I, 14 compounds allocated to Cramer Class 297
III and 2 compounds with genotoxic structural alerts. 298
Calculated benchmark values varied from 0.15 µg.L-1 (for the possible genotoxic benzenesulfonic 299
acid, methyl ester and sulfuric acid, dimethyl ester) to 72,000 µg.L-1 (for the preservative citric acid). 300
The highest observed benchmark values (eight of them >10,000 µg.L-1) referred to preservatives and 301
fragrances/flavours, which in general are also chemicals utilized as food additives. The lowest 302
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observed benchmark values related to compounds allocated to Tier 3 (from 0.15 to 180 µg.L-1), with 303
exception for benzene (1 µg.L-1), dichloromethane (5 µg.L-1) and pentachlorophenol (1 µg.L-1) in Tier 304
1; 2,4,6-trichlorophenol (25 µg.L-1), 2,4-dichlorophenol (18 µg.L-1), 2-ethyl-1-hexanol (6 µg.L-1), 2-305
hexanone, 3,4-dimethylphenol (6 µg.L-1), nicotine (4.8 µg.L-1), and tri(2-chloroethyl) phosphate (78 306
µg.L-1) in Tier 2. 307
For 5 compounds the RQ value was above 1, namely: benzene (Tier 1); 2-ethyl-1-hexanol (Tier 2); 308
benzenesulfonic acid methyl ester; dodecanoic acid; and tetracanoic acid (Tier 3). Accordingly, these 309
compounds may be of potential human health concern if not reduced in treatment barriers and are 310
considered to be of higher priority for further studies on the risk assessment and the selection of 311
technologies to be applied in future GW treatment plants for drinking water production. For 8 312
compounds (dichloromethane; trichloromethane; nicotine; acetamide; indole; decanamide, N-(2-313
hydroxyethyl)-; sulfuric acid, dimethyl ester; and methyl dihydrojasmonate), the RQ value was above 314
0.2 (and below 1). These compounds are also considered to warrant further investigation. 315
Table 2. Selected OMP, maximum detected levels and calculated RQ values 316
4. Discussion 317
Potable reuse of GW is a novel and potentially beneficial research topic given the increasingly urgent 318
need to identify and validate new raw water sources for safe drinking water production worldwide. 319
An important concern in the development of GW potable reuse schemes appears to be the lack of 320
knowledge about the presence and risks of OMPs. The occurrence of OMPs has been much better 321
characterized in WWTP influents and effluents and in surface waters than in GW (Pal et al., 2010; 322
Deblonde et al., 2011; Luo et al., 2014), and very little is known about OMPs in industrial 323
wastewaters. WWTPs that treat domestic (household) sewage, hospital effluents, industrial 324
wastewaters, as well as wastewaters from livestock and agriculture are considered to be the main 325
source of OMPs to aquatic systems (Kasprzyk-Hordern et al., 2009). Most of previous studies on GW 326
characterization and treatment have been limited to the assessment of conventional water quality 327
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parameters for non-potable reuse applications. Accordingly, the first challenge facing those who wish 328
to treat GW to potable water quality is to identify the chemicals which potentially represent a threat 329
to human health in future applications. The present study combined available data in literature with 330
risk characterization methods in order to improve our understanding regarding the presence of 331
OMPs in GW and the risks they may pose to human health. 332
The results presented in Table S1 (supplementary data) confirmed the presence of OMPs directly 333
associated with household chemicals, especially personal care products. Several miscellaneous 334
compounds, probably indirectly associated with household chemicals have also been identified (e.g. 335
brominated flame retardants, organotin compounds, and drugs). Nevertheless, pharmaceuticals 336
active compounds, which have been consistently detected in hospital effluents (Verlicchi et al., 2010) 337
and WWTPs (Deblonde et al., 2011; Luo et al., 2014) and raised environmental and human health 338
concern due to their persistency and potential in endocrine disruption (Daughton and Ternes, 1999), 339
were virtually not present. Two exceptions were the pharmaceuticals acetaminophen and salicylic 340
acid, but maximum detected levels in GW (1.5 µg.L-1 and 0.6 µg.L-1, respectively) are about 500 341
(acetaminophen) and 3,500 (salicylic acid) times lower than the corresponding maximum levels 342
reported in WWTP effluents (Pal et al., 2010 - Table 3). As administrated pharmaceutical compounds 343
are excreted from the human body via feces and urine, separate collection and treatment of GW in 344
households can contribute to keeping these substances away from reclaimed (potable) water. 345
Table 3 compares the concentrations of some of the OMPs compiled in the present study with 346
maximum concentrations reported for WWTP influents and effluents (based on recent review 347
papers/compiled literature data). Besides pharmaceuticals, in general, much higher loads of OMPs 348
associated to industrial chemicals and wastewaters are observed in WWTPs influents (among them: 349
bisphenol-A = 11.8 µg.L-1; 4-nonylphenol = 101.6 µg.L-1; 4-octylphenol = 8.7 µg.L-1; dibutylphtalate = 350
46.8 µg.L-1) when compared to GW (bisphenol-A = 1.2 µg.L-1; 4-nonylphenol = 38 µg.L-1; 4-351
octylphenol = 0.16 µg.L-1; dibutylphtalate = 3.1 µg.L-1), while concentrations of personal care 352
products are slightly higher in GW. Intermittent contributions from agricultural and/or livestock 353
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runoff and hospital discharges may also cause spikes in pharmaceuticals and steroid hormones in 354
WWTP influents and effluents (Verlicchi et al., 2010; Sim et al., 2011) and industrial discharges may 355
contain organic compounds and other materials that are typically absent in GW (e.g. 356
aminopolycarboxylate complexing agents - Reemtsma and Jekel, 2006). On the other hand, another 357
important factor is rainfall. Kasprzyk-Hordern et al. (2009) found that the concentrations of a 358
selection of 55 OMPs in the WWTP influent were doubled when the flow was halved during dry 359
weather conditions, suggesting that rainwater could dilute the concentrations of the compounds 360
within the sewage. Therefore, the common practice in potable reuse schemes of cotreatment of 361
hospital, industrial, agriculture, stormwater and domestic wastewaters at a municipal WWTP (Gerrity 362
et al., 2013) is not a sustainable approach for reducing the risks of OMPs because it is based on 363
dilution of different discharges and does not provide an adequate segregation of pollutants and, in 364
particular, of different classes of OMPs. 365
Table 3. Maximum concentrations of OMPs in GW (present study) in comparison with maximum 366
levels reported in WWTP influents and effluents. The literature data of WWTPs were compiled from 367
recent review papers (Pal et al., 2010; Deblonde et al., 2012; Luo et al., 2014) 368
A preliminary health-based risk assessment of 89 prioritized OMP (with log D < 3) in GW was 369
performed to determine benchmark values. The first step was a conventional evaluation of 370
contaminants and consisted of identifying compounds with an established drinking water guideline 371
or standard value (Tier 1). The need to develop additional tiers arose because no current guidelines 372
exist for a majority of the chemicals identified in this study. As the fulfillment of the criteria for 373
establishment of a guideline value may take place several years after a potential contaminant is 374
identified (WHO, 2011), an attempt was made to characterize the risks of selected compounds with 375
no established guidelines. There were 39 chemicals in this study for which relevant toxicity 376
information (ADI, TDI, RfD, NOA(E)L) exists (Tier 2), thus benchmark values were derived from this 377
available information. Health authorities recommend using maximum acceptable or tolerable levels 378
such as ADI, RfD and TDI as guidelines for contaminants that may accumulate in the body. Since its 379
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introduction in 1957 by the Council of Europe and later by the Joint Expert Committee on Food 380
Additives-JECFA (WHO, 2002), the ADI has been proven to be a valid and practical tool in the risk 381
assessment and are the basis for many regulatory standards (WHO, 2011). 382
The remaining compounds were those without established drinking water criteria or toxicity data 383
(Tier 3). The benchmark values developed in this study for compounds in Tier 3 ranged from 0.15 to 384
180 µg.L-1. The widely accepted TTC approach used to derive these benchmark values (Kroes et al., 385
2004; Munro et al., 1996) was considered appropriately conservative and protective to human 386
health, since it has been applied frequently by regulatory bodies for risk assessment of substances at 387
low dose oral exposure for which limited or no toxicity data are present (Leeman et al., 2014; EFSA, 388
2012; EU, 2012). However, it should be noted that more conservative TTC approaches than the one 389
applied in the present study have also been proposed. Mons et al. (2013), for example, set TTC 390
values for all chemicals other than genotoxic and steroid endocrine compounds at 1.5 µg/person per 391
day (target value in drinking water equal to 0.1 µg.L-1), to achieve drinking water of impeccable 392
quality in line with the so-called Q21 approach. On the other hand, the thresholds should be as 393
accurate as feasible and not over conservative to prevent unnecessary low thresholds. In this respect 394
it is noted that recently new thresholds have been proposed above the current (accepted) thresholds 395
used in this study (Munro et al., 2008; Tluczkiewicz et al., 2011; Leeman et al., 2014). These new 396
possibilities for the TTC approach must be further elucidated and validated by international 397
regulatory agencies before they can be put into practice. 398
Five pesticides were assessed in the present study (2,4,6-trichlorophenol, 2,4-dichlorophenol, 2,5-399
dichlorophenol, malathion and pentachlorophenol). The benchmark values derived for them in this 400
study ranged from 1 to 120 µg.L-1 and were far above the established standard (0.1 µg.L-1) for 401
pesticides set by the Dutch Drinking Water Decree and the European Council Directive 98/83/EC. 402
Although the present results suggest that these statutory standards might be overly pragmatic and 403
stringent, it is advisable that drinking water produced from GW complies with the pesticide 404
mandatory target value of 0.1 µg.L-1. 405
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The calculated RQ values for the majority of OMPs were below 1, indicating that these compounds 406
are presumed to present little appreciable danger to human health. However, a few compounds 407
(benzene; 2-ethyl-1-hexanol; benzenesulfonic acid, methyl ester; dodecanoic acid and tetracanoic 408
acid) had RQ values above 1, which suggests that these compounds may pose a more appreciable 409
concern. Further investigations should focus on reducing the concentrations of these more 410
problematic compounds from GW by the application of advanced treatment barriers in order to 411
reach the target safe levels. Different wastewater treatments may be appropriate only for some of 412
these OMPs due to the variability of their physico-chemical properties (e.g. hydrophobicity, 413
molecular weight, and chemical structure – Table S3) and therefore, a multiple barriers treatment is 414
advisable. In Windhoek, for instance, direct drinking water reclamation from wastewater has already 415
been applied successfully for more than 40 years based on the multiple barriers concept to reduce 416
associated risks and improve the water quality (du Pisani and Menge, 2013). The treatment train 417
consists of the following partial barriers for OMPs removal: pre-ozonation, enhanced coagulation + 418
dissolved air flotation + rapid sand filtration, and subsequent ozone, biological activated 419
carbon/granular activated carbon. 420
Based on these considerations, to remove OMPs from GW for potable reuse, a triple barrier 421
consisting of a membrane bioreactor (MBR, coupled with an ultrafiltration membrane), ozone-based 422
advanced oxidation process (AOP) and activated carbon adsorption (AC) appears to be promising 423
(van der Hoek et al., 2014). MBRs are able to effectively remove a wide spectrum of OMPs that are 424
resistant to conventional biological processes (Tadkaew et al., 2011; Trinh et al., 2012). Ozone-based 425
AOP and AC have demonstrated to be effective for removing the prioritized compounds found in the 426
present study (Rosal et al., 2010; Hernández Leal et al., 2011; Lee et al., 2012; Jurado-Sánchez et al., 427
2014). The application of AC is also supported by results obtained herein, which showed that 189 out 428
of the 278 compounds detected in GW have Log D values above 3 (high sorption), and thus are 429
expected to be removed by this treatment stage. In the Netherlands, this treatment train will be 430
tested and extensively studied in the aforementioned Green Village project at Delft University of 431
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Technology. The clean water supply of its test laboratory site will be provided using GW and 432
rainwater generated on site as raw water sources by reclaiming them in a pilot scale multiple barrier 433
treatment concept for drinking water production. 434
Looking towards the future, the results presented in this article can help researchers, water 435
engineers and stakeholders to prioritize further investigations about the use of GW as potable water 436
supply. 437
Conclusions 438
• An extensive literature review showed that, in total, 278 OMP have been detected in GW 439
from 7 different sites located in Denmark, Sweden and the Netherlands; 440
• The study shows a practical tool to assess the health risks of relevant OMPs by deriving 441
benchmark values for a group of (prioritized) compounds (log D < 3); 442
• The preliminary health risk assessment, performed with the aid of a three tiered approach, 443
showed that for only a minority of selected OMPs, established drinking water standards are 444
available. Benchmark values for non-regulated compounds were derived based on either 445
toxicological available data or TTC approach; 446
• The RQ values obtained (based on the maximum concentration levels detected in the limited 447
available GW sources and on calculated benchmark values) revealed that from the 448
toxicological point of view, the majority of assessed chemicals would not pose appreciable 449
human health concern in an exposure scenario to drinking water over a life-time period; 450
• A group of 5 compounds with RQ value > 1 as well as 8 compounds with the RQ value 451
between 0.2 and 1 suggest that advanced multiple treatment barriers would be required in 452
future potable water reclamation plants to reduce the concentration of these compounds to 453
safe levels. 454
Acknowledgements 455
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The authors wish to thank CAPES (Brazilian institution), that directly sponsored these doctoral studies 456
at Delft University of Technology (Scholarship n° 8106-13-4). Special thanks to students, professors 457
and researchers of TU Delft (Section Sanitary Engineering) and particularly, to Marisa Buyers-Basso 458
for her helpful comments on the manuscript and English revision. 459
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URL 1. OECD Organization of Economic Co-operation and Development. OECD Quantitative 653
Structure-Activity Relationships Project. http://www.oecd.org/chemicalsafety/risk-654
assessment/theoecdqsartoolbox.htm, accessed May 2014. 655
USEPA (United States Environmental Protection Agency), 2011. 2011-Edition of the Drinking Water 656
Standards and Health Advisories. EPA 820-R-11-002 Office of Water U.S. Environmental Protection 657
Agency Washington, DC. 658
USEPA (United States Environmental Protection Agency), 2012. Guidelines for water reuse. US 659
Environmental Protection Agency. Office of Wastewater Management, Washington, DC. 660
van der Hoek, J.P., Tenorio, J., Hellinga, C., Lier, J. van, Wijk, A. van, 2014. Green Village Delft - 661
Integration of an Autarkic Water Supply in a Local Sustainable Energy System. Journal of Water Reuse 662
and Desalination. In Press, doi:10.2166/wrd.2014.057. 663
Van Leeuwen, C.J., Vermeire, T., 2007. Risk Assessment of Chemicals, second ed., Springer, ISBN 978-664
4020-6101-1. 665
van Wezel, A.P., Jager, T., 2002. Comparison of two screening level risk assessment approaches for 666
six disinfectants and pharmaceuticals. Chemosphere 47, 1113–1128. 667
Verlicchi P., Galletti, A., Petrovic, M., Barceló, D., 2010. Hospital effluents as a source of emerging 668
pollutants: an overview of micropollutants and sustainable treatment options. Journal of Hydrology 669
389, 416–428. 670
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Wang, J., Junyang Cheng, Can Wang, Shaoxia Yang, Wanpeng Zhu, 2013. Catalytic ozonation of 671
dimethyl phthalate with RuO2/Al2O3 catalysts prepared by microwave irradiation. Catalysis 672
Communications 41, 1-5. 673
Westerhoff, P., Yoon, Y., Snyder, S., Wert, E., 2005. Fate of endocrine-disruptor, pharmaceutical, and 674
personal care product chemicals during simulated drinking water treatment processes. 675
Environmental Science and Technology 37 (17), 6649–6663. 676
WHO (World Health Organization), 2011. Guidelines for Drinking-water Quality. World Health 677
Organization. 678
WHO (World Health Organization), 2002. Evaluation of certain food additives and contaminants : 679
fifty-seventh report of the Joint FAO/WHO Expert Committee on Food Additives. Joint FAO/WHO 680
Expert Committee on Food Additives. 681
WHO-IPCS (World Health Organization - International Programme on Chemical Safety), 1994. 682
Environmental health criteria for phenol (161). First draft prepared by Ms G. K. Montizan: WHO, 683
Printed in Finland, 1994. 21p. 684
Zuo, J., Zhao, Z.Y., 2014. Green building research–current status and future agenda: A review. 685
Renewable and Sustainable Energy Reviews 30, 271–281. 686
687
688
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Table 1. Sources to obtain toxicological threshold values
Sources of toxicological assessment data URL
Environmental Health Criteria monographs (WHO) http://inchem.org/pages/ehc.html
European Comission – Health and Consumer
Protection (ECHCP)
http://ec.europa.eu/dgs/health_consumer/dyna/press_r
oom/index_en.cfm
European Comission - Scientific Committee on
Health and Environmental Risks (SCHER)
http://ec.europa.eu/health/scientific_committees/enviro
nmental_risks/index_en.htm
European Medicines Agency (EMA) http://www.ema.europa.eu/ema/
European Safe Food Authority (EFSA) http://www.efsa.europa.eu/
Joint FAO/WHO Expert Committee on Food
Additives (JECFA)
http://inchem.org/pages/jecfa.html
Organization for Economic Cooperation and
Development– Exisiting chemicals database
(OECD)
http://webnet.oecd.org/hpv/ui/Search.aspx
TheGerman Federal Institute for Risk Asessment
(BFR) –
http://www.bfr.bund.de/de/start.html
The Scientific committee on occupational
exposure limits (SCOEL)
http://ec.europa.eu/social/main.jsp?catId=148&langId=e
n&intPageId=684
U.S. EPA Integrated Risk Information System (EPA-
IRIS)
http://cfpub.epa.gov/ncea/iris/index.cfm?fuseaction=iris.
showSubstanceList&list_type=alpha&view=A
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Table 2. Selected OMP, maximum detected levels and calculated RQ values
Compounds Maximum
detected
level,
µg.L-1
Drinking water standard/
toxicity threshold value
Source Benchmark
value, µg.L-1
RQ
Tier 1
Benzene 9.85 1 µg.L-1
Staatsblad (2011) 1 9.85
Dichloromethane 4.4 5 µg.L-1
USEPA (2011) 5 0.88000
Ethylbenzene 2.1 300 µg.L-1
WHO (2011) 300 0.00700
Pentachlorophenol 0.04 1 µg.L-1
USEPA (2011) 1 0.04000
Trichloromethane 250 300 µg.L-1
WHO (2011) 300 0.83333
Tier 2
1,3-Dioxolane 1.7 75 mg/kg bw/day EFSA (NOAEL); AF = 600 750 0.00227
1-Dodecanamine, N,N-dimethyl- 7.4 50 mg/kg bw/day OECD (NOEL); AF = 600 500 0.01480
2,4,6-Trichlorophenol 0.10 0.011 per mg/kg bw/day EPA-IRIS (SF) 25 0.00400
2,4-Dichlorophenol 0.16 0.003 mg/kg bw/day EPA-IRIS (RfD) 18 0.00889
2-Ethyl-1-hexanol 8.5 0.5 mg/kg bw/day JECFA (ADI) 6 1.41667
2-Hexanone 0.6 0.005 mg/kg EPA-IRIS (RfD) 30 0.02000
2-Methylphenol 0.24 0.05 mg/kg bw/day EPA-IRIS (RfD) 300 0.00080
2-Phenyl-5-benzimidazolesulfonic acid 15.3 40 mg/kg bw/day ECHCP (NOAEL); AF = 200 30,000 0.00051
3,4-Dimethylphenol 0.05 0.001 mg/kg bw/day EPA-IRIS (RfD) 6 0.00833
3-Methylphenol 5.9 0.05 mg/kg bw/day EPA-IRIS (RfD) 300 0.01967
4-Methyl-phenol 170 50 mg/kg bw/day EPA report (NOAEL); AF = 200 1,500 0.11333
Acetaminophen 1.5 0.05 mg/kg bw/day EMA (ADI) 300 0.00500
Anise camphor 0.5 2 mg/kg bw/day JECFA (ADI) 12,000 0.00004
Benzalkonium chloride 20.7 0.1 mg/kg bw/day BFR (ADI) 600 0.03450
Benzoic acid 0.5 5 mg/kg bw/day JECFA (ADI) 30,000 0.00002
Benzoic acid, 4-hydroxy- 1 1,000 mg/kg bw/day OECD (NOAEL); AF = 600 10,000 0.00010
Butylparaben 17 100 mg/kg bw/day Daston (2004) (NOEL); AF = 600 1,000 0.01700
Camphor 11.4 2 mg/kg bw/day EFSA (TDI) 12,000 0.00095
Carvone 0.5 1 mg/kg bw/day JECFA (ADI) 6,000 0.00008
Citric acid 15 1,200 mg/kg bw/day OECD (NOAEL); AF = 100 72,000 0.00021
Citronellol 2.8 0.5 mg/kg bw/day JECFA (ADI) 3,000 0.00093
Coumarin 1 0.1 mg/kg bw/day EFSA (TDI) 600 0.00167
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Dibutyl tin 3 1 mg/kg bw/day WHO-IPCS (2006) (TDI) 6,000 0.00050
Diethyl phthalate 38 0.8 mg/kg bw/day EPA-IRIS (RfD) 4,800 0.00792
Dihydromyrcenol 8.9 10 mg/kg bw/day JECFA (NOAEL); AF:200 300 0.02967
Dodecanamide, N,N-bis(2-hydroxyethyl)- 14.3 50 mg/kg bw/day EFSA (NOAEL); AF = 200 1,500 0.00953
Ethylparaben 41 10 mg/kg bw/day1
EFSA (NOAEL); AF = 600 10,000 0.00410
Eugenol 1 2.5 mg/kg bw/day JECFA (ADI) 15,000 0.00007
Isoeugenol 0.6 0.075 mg/kg bw/day EMA (ADI) 450 0.00133
Linalool 15.4 0.5 mg/kg bw/day JECFA (ADI) 3,000 0.00513
Malathion 1.9 0.02 mg/kg bw/day EPA-IRIS (RfD) 120 0.01583
Menthol 32.6 4 mg/kg bw/day JECFA (ADI) 24,000 0.00136
Methylparaben 37 10 mg/kg bw/day1 EFSA (NOAEL); AF = 600 10,000 0.00370
Naphthalene 0.042 0.02 mg/kg bw/day EPA-IRIS (RfD) 120 0.00035
Nicotine 1.2 0.0008 mg/kg bw/day EFSA (ADI) 4.8 0.25000
Phenol 21 0.1 mg/kg bw/day WHO (ADI) 600 0.03500
Propylparaben 21 2 mg/kg bw/day JECFA (ADI) 12,000 0.00175
Toluene 1.4 0.08 mg/kg bw/day EPA-IRIS (RfD) 480 0.00292
Tri(2-chloroethyl) phosphate 0.4 13 µg/kg bw/day SCHER (TDI) 78 0.00513
Tier 3
1,2-Ethanediamine, N-ethyl- 1.2 1.5 µg/kg bw/day TTC (Cramer class III) 9 0.13333
1,8-Nonanediol, 8-methyl- 0.6 1.5 µg/kg bw/day TTC (Cramer class III) 9 0.06667
2,5-Dichlorophenol 0.16 1.5 µg/kg bw/day TTC (Cramer class III) 9 0.01778
2,5-Dimethylphenol 0.1 30 µg/kg bw/day TTC (Cramer class I) 180 0.00056
2,6-Dimethylphenol 0.4 30 µg/kg bw/day TTC (Cramer class I) 180 0.00222
2-Hexanol 0.3 30 µg/kg bw/day TTC (Cramer class I) 180 0.00167
2-Methyl-butanoic acid, methyl ester 1.8 30 µg/kg bw/day TTC (Cramer class I) 180 0.01000
2-Phenoxy ethanol 24.8 30 µg/kg bw/day TTC (Cramer class I) 180 0.13778
3-Hexanol 0.7 30 µg/kg bw/day TTC (Cramer class I) 180 0.00389
3-Hexanone 0.3 30 µg/kg bw/day TTC (Cramer class I) 180 0.00167
3-Methyl-butanoic acid, methyl ester 1.5 30 µg/kg bw/day TTC (Cramer class I) 180 0.00833
4-Heptanone 1.4 30 µg/kg bw/day TTC (Cramer class I) 180 0.00778
4-Methoxy-benzoic acid 12.7 30 µg/kg bw/day TTC (Cramer class I) 180 0.07056
4-Methyl-pentanoic acid, methyl ester 1.1 1.5 µg/kg bw/day TTC (Cramer class III) 9 0.12222
6-Methyl-5-hepten-2-one 0.1 30 µg/kg bw/day TTC (Cramer class I) 180 0.00056
Acetamide 8.6 1.5 µg/kg bw/day TTC (Cramer class III) 9 0.95556
Acetic acid, phenoxy- 4 30 µg/kg bw/day TTC (Cramer class I) 180 0.02222
Benzenesulfonic acid, methyl ester 1.1 0.0025 µg/kg bw/day TTC (potential genotoxic) 0.15 7.33333
Butanoic acid, butyl ester 0.9 30 µg/kg bw/day TTC (Cramer class I) 180 0.00500
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Caffeine 0.5 1.5 µg/kg bw/day TTC (Cramer class III) 9 0.05556
Decanamide, N-(2-hydroxyethyl)- 3.2 1.5 µg/kg bw/day TTC (Cramer class III) 9 0.35556
Decanoic acid 1.2 30 µg/kg bw/day TTC (Cramer class I) 180 0.00667
Dimethyl phthalate 4.9 30 µg/kg bw/day TTC (Cramer class I) 180 0.02722
Dodecanoic acid 680 30 µg/kg bw/day TTC (Cramer class I) 180 3.77778
Eucalyptol 0.1 1.5 µg/kg bw/day TTC (Cramer class III) 9 0.01111
Geraniol 0.8 30 µg/kg bw/day TTC (Cramer class I) 180 0.00444
Hexanoic acid, methyl ester 10.1 30 µg/kg bw/day TTC (Cramer class I) 180 0.05611
Homomyrtenol 0.9 30 µg/kg bw/day TTC (Cramer class I) 180 0.00500
Hydroxycitronellol 0.2 30 µg/kg bw/day TTC (Cramer class I) 180 0.00111
Indole 3.8 1.5 µg/kg bw/day TTC (Cramer class III) 9 0.42222
Isobutylparaben 8 30 µg/kg bw/day TTC (Cramer class I) 180 0.04444
Methyl dihydrojasmonate 3.9 1.5 µg/kg bw/day TTC (Cramer class III) 9 0.43333
Mono 2-ethylhexyl phthalate 1.7 30 µg/kg bw/day TTC (Cramer class I) 180 0.00944
Monobutyl tin 0.99 1.5 µg/kg bw/day TTC (Cramer class III) 9 0.11
Monooctyl tin 0.1 1.5 µg/kg bw/day TTC (Cramer class III) 9 0.01111
Octanoic acid 3 30 µg/kg bw/day TTC (Cramer class I) 180 0.01667
Pentanoic acid, methyl ester 1.1 30 µg/kg bw/day TTC (Cramer class I) 180 0.00611
Phenylethyl alcohol 0.6 30 µg/kg bw/day TTC (Cramer class I) 180 0.00333
Propanoic acid, 2-methyl-, 2,2-dimethyl-1-(2-hydroxy-1-
methylethyl)propyl ester
1.1 1.5 µg/kg bw/day TTC (Cramer class III) 9 0.12222
Propanoic acid, 2-methyl-, 3-hydroxy-2,2,4-trimethylpentyl ester 0.3 1.5 µg/kg bw/day TTC (Cramer class III) 9 0.03333
Salicylic acid 0.6 30 µg/kg bw/day TTC (Cramer class I) 180 0.00333
Sulfuric acid, dimethyl ester 0.1 0.0025 µg/kg bw/day TTC (potential genotoxic) 0.15 0.66667
Terpineol 1.2 30 µg/kg bw/day TTC (Cramer class I) 180 0.00667
Tetracanoic acid 2808 30 µg/kg bw/day TTC (Cramer class I) 180 15.6
α-Methyl-benzene methanol 0.1 30 µg/kg bw/day TTC (Cramer class I) 180 0.00056
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levels reported in WWTP influents and effluents. The literature data of WWTPs were compiled from
recent review papers (Pal et al., 2010; Deblonde et al., 2012; Luo et al., 2014)
Compound Class GW (present
study) (µg.L-1
)
WWTPs
Influent
(µg.L-1
)
Effluent
(µg.L-1
)
Acetaminhophen Pharmaceutical 1.5 56.9 777
Salicylic acid Pharmaceutical 0.6 63.7 2,098
Caffeine Food additive/stimulant 0.5 209 43.5
Benzophenone Personal care product 4.9 0.9 0.23
Galaxolide Personal care product 19.1 25 2.77
Tonalide Personal care product 5.8 1.93 0.32
Triclosan Personal care product 35.7 23.9 6.88
4-Nonylphenol Surfactants 38 101.6 7.8
4-Octylphenol Surfactants 0.16 8.7 1.3
Bisphenol-A Plasticizer 1.2 11.8 4.09
Butylbenzyl phtalate Plasticizer 9 37.87 3.13
Di-(2-ethylhexyl) phthalate Plasticizer 160 122 54
Dibutyl phthalate Plasticizer 3.1 46.8 4.13
Diethyl phtalate Plasticizer 38 50.7 2.58
Di-isobutyl phthalate Plasticizer 8 20.48 -
Dimethyl phtalate Plasticizer 4.9 3.32 0.115
Dimethyl phthalate Plasticizer 4.9 6.49 1.52
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List of OMPs found in GW
Log D ≥ 3 No evaluation
Established drinking water guideline
available ?
Tier 1
Toxicity information available ?
Selection/calculation of a benchmark value
Calculation of RQ value
Yes
No
Yes
No
No
Yes Tier 2
Tier 3
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Greywater is a potentially novel raw water source for potable reuse.
The presence and concentrations of organic micropollutants in greywater was compiled.
A risk assessment identified the more problematic compounds for potable reuse.
The majority of assessed compounds pose no appreciable danger to human health.
Useful for future monitoring of greywater and design of potable water reuse plants.
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Table S1. OMPs found in GW (µg.L-1
or indicated if different)
Compound name
Source of GW / Location
BO90 tenant
owner's
society /
Copenhagen,
Denmark1
Vibyasen
housing area /
Sollentuna,
Sweden2
Gebers housing
estate /
Skarpnäck,
Sweden3
Nordhavnsgarden
apartment
building
/Copenhagen,
Denmark4
Housing estate
/ Sneek, The
Netherlands5
Vasbadet
swimming
club /
Brondby,
Denmark6
Gals Klint
Campingsite /
Copenhagen,
Denmark7
Plasticisers and softeners
2-Ethyl-1-hexanol 8.5
Butylbenzyl phthalate <1 <1.0-9.0 1.4-3.3 0.42 0.22
Decanedioic acid, bis(2-ethylhexyl) ester 1.0
Di-(2-ethylhexyl) phthalate 9.8-39 8.4-160 7.5-20 28 14
Dibutyl phthalate 3.1
Diethyl phthalate <1-13 4.2-38 7.2-9.4 27 29
Di-isobutyl phthalate <1-3 <1.0-8 3.4-6.0 4.9 1.8
Dimethyl phthalate 4.9 <1.0 <0.5 0.15 0.98
Di-n-butyl phthalate <1 1.8-9.4 4.4-6.2 2.7 1.8
Dipentyl-phtalate <1-1.4
Hexadecanoic acid, methyl ester 14.2
Hexanedioic acid, bis(2-ethylhexyl) ester 1.0
Mono 2-ethylhexyl phthalate 1.7
Preservatives
2,4,6-Trichlorophenol <0.02-0.10 0.066
2,4-Dichlorophenol 0.06-0.13 0.16
2,5-Dichlorophenol 0.06-0.13 0.16
2-Phenoxy ethanol 24.8
Acetic acid, phenoxy- 4
Benzoic acid 0.5
Benzoic acid, 4-hydroxy- 1
Butylated hydroxyanisole 0.5
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Butylated hydroxytoluene 4.5
Butylparaben <0.2-17 0.19-4.4
Citric acid 15
Dichlorophenol 0.06-0.13
Ethylparaben 0.6 <0.1-41
Isobutylparaben 0.1-8
Malathion 1.9
Methylparaben 2.6 0.1-37
Octanoic acid 3
Phenol, 2,6-bis(1,1-dimethylethyl)-4-(methoxymethyl)- 0.4
Propylparaben <0.1-21 nd-5.5
Triclosan 0.6 0.56-5.9 0,075-0.3 6.3-35.7
UV filters
2-Ethylhexyl salicylate nd-4.7
2-Phenyl-5-benzimidazolesulfonic acid 0.1-15.3
4-Methylbenzylidene-camphor nd-8.9
Avobenzone 0.3-17.4
Benzophenone-3 0.3-4.9
Octocrylene nd-146
Parasol MCX 0.5 3.9-67.7
Fragrances and flavours
1-Dodecene 4.2
1-Hexadecene 0.4
3-Hexanol 0.7
3-Hexanone 0.3
3-Methylphenol 0.1 5.9
4-Methoxy-benzoic acid 12.7
4-Methylphenol 3.1 21
6-Methyl-5-hepten-2-one 0.1
Anise camphor (trans-anethole) 0.5
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Butanoic acid, butyl ester 0.9
Caffeine 0.5
Camphor 9.1-11.4
Carvone 0.5
Citronellol 2.8
Coumarin 1.0
Decanoic acid 1.2
Dihydroabietate 1.1
Dihydromyrcenol 8.9
Dodecanal 0.9
Dodecanoic acid, methyl ester 2.2
Eucalyptol 0.1
Eugenol 1.0
Farnesol 1.0
Galaxolide 5.7-19.1
Geraniol 0.8
Geranyl acetone 0.6
Hexadecanoic acid 76.9
Hexyl cinnamic aldehyde 0.7
Hexyl cinnamic aldehyde 0.6-11.5
Homomyrtenol 0.9
Hydroxycitronellol 0.2
Indole 3.8
Isoeugenol 0.6
Linalool 15.4
Linalyl propanoate 1.3
Menthol 32.6
Menthone 0.9
Methyl abietate 1.4
Methyl dihydrojasmonate 3.9
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Phenylethyl alcohol 0.6
Squalene 133
Terpineol 1.2
Tetradecanoic acid, methyl ester 3.1
Thymol 2.5
Tonalide nd-5.8
α-Methyl-benzene methanol 0.1
Surfactants
15-Octadecanoic acid 1.6
1-Dodecanamine, N,N-dimethyl- 7.4
1-Dodecanol 11.3
1-Hexadecanol 63.7
1-Octadecanol 117
2-(Dodecyloxy)-ethanol 37.3
2-(Tetradecyloxy)-ethanol 18.7
4-nonylphenol (NP) 0.4 2.82-5.95 0.56-1.1 0.35-1.63 0.8-38 0.9
4-NP di-ethoxylate 4.02-15.9 <0.05-5
4-NP hepta-ethoxylate 9.14-24.1 <0.05-5.2
4-NP hexa-ethoxylate 18.9-40.9 <0.4-9
4-NP mono-ethoxylate 2.75-6.73 <0.05-3.7 0.76
4-NP octa-ethoxylate <0.1 <0.05-3.3
4-NP penta-ethoxylate 15.5-49.7 <0.04-6.5
4-NP tetra-ethoxylate 21.1-61.4 <0.025-2.3
4-NP tri-ethoxylate 11.8-36.2 <0.025-3.3
4-octylphenol (OP) 0.08-0.16 0.07-0.15
4-OP tri-ethoxylate 0.37-4.74 <0.005-0.07
4-OP di-ethoxylate 0.24-0.6 <0.005-0.11
4-OP hepta-ethoxylate 0.17-0.44 <0.05
4-OP hexa-ethoxylate 0.26-0.81 <0.05
4-OP mono-ethoxylate 0.08-0.21 0.13-0.38
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4-OP octa-ethoxylate <0.001-0.14 <0.05
4-OP penta-ethoxylate 0.41-2.6 <0.05
4-OP tetra-ethoxylate 0.4-3.1 <0.05
9-Methyltetradecanoic acid 2.7
9-Octadecenoic acid 144-15863
9-Octadecenoic acid 27.4
9-Octadecenoic acid, (Z)-, methyl ester 18.0
Benzalkonium chloride 2.1-20.7
Bisphenol-A 0.42-1.2
Cyclododecane 8.1
Decanoic acid 5.5-755
Dodecanamide, N-(2-hydroxyethyl)- 0.8
Dodecanamide, N,N-bis(2-hydroxyethyl)- 14.3
Dodecanoic acid 5.9-680
Elicosanoic acid 19.7-189
Hexacanoic acid 291-7020
Hexadecanoic acid, 1,2-ethanediyl ester 8.2
Hexadecanoic acid, hexadecyl ester 4.5
Hexanoic acid 291-7020
Isopropyl myristate 1.6
Octadecanoic acid 4.2-3569
Octadecanoic acid, 2-hydroxyethyl ester 0.9
Octadecanoic acid, 2-methylpropyl ester 0.3
Octadecanoic acid, butyl ester 0.2
Octadecanoic acid, methyl ester 4.6
Octanoic acid 8.1-283
p-Octylphenolmethyl 0.2
Tetracanoic acid 4.4-2808
Tetracosanoic acid, methyl ester 0.6
Tetradecanoic acid 12.6
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Tetradecanoic acid, 12-methyl- 1.8
Tetradecanoic acid, 12-methyl-, methyl ester 1.8
Tetradecanoic acid, dodecyl ester 1.2
PAHs
Acenaphthene 0.26 0.018-0.072
Acenaphthylene - 0.15
Anthracene - 0.023-0.041
Benzo(a)pyrene 0.02-0.04 <0.01
Benzo(ghi)perylene 0.04 <0.01
Chrysene 0.01-0.02 <0.01
Fluoranthene 0.03-0.03 0.033-0.035
Fluorene <0.01 0.048-0.065
Naphthalene <4.5 <0.1 0.029-0.042
Phenanthrene 0.04 0.1-0.12
Pyrene 0.04-0.05 <0.01
PCB
PCB#105 <0.02 0.022-0.029 ng/L
PCB#118 <0.02 0.073-0.12 ng/L
PCB#156 <0.02 0.019-0.032 ng/L
PCB#157 <0.02 0.022-0.026 ng/L
PCB#167 <0.02 0.011-0.015 ng/L
Solvents
1,13-Tetradecadiene 1.8
1,3-Dioxolane 1.7
1,8-Nonanediol, 8-methyl- 0.6
1-Decene 0.6
1-Docosene 1.6
1-Nonadecene 0.8
1-Tetradecene 0.5
2-Hexadecanol 6.1
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2-Hexanol 0.3
2-Hexanone 0.6
3-Dodecene 0.4
3-Eicosene 7.3
3-Octadecene 0.5
4-Dodecene 0.5
4-Heptanone 1.4
5-Eicosene 5.2
5-Octadecene 0.4
7-Tetradecene 0.2
Acetamide 8.6
Benzene <1.9 <1.4-9.85
Cyclohexadecane 21.1
Cyclotetradecane 4.8
Decane 4.2
Dodecane 1.2
Eicosane 4.1
Ethylbenzene 1.9-2.1
Nonane 0.2
Octadecane 1.1
Sulfuric acid, dimethyl ester 0.1
Toluene 1.4
Tridecane 2.0
Xylene, m- 3.5
Xylene, o- 0.6
Organotin compounds
Dibutyl tin 252-3000 ng/L 28.2 ng/L
Dioctyl tin 20-21 ng/L
Monobutyl tin 431-990 ng/L 89.8 ng/L
Monooctyl tin 29-100 ng/L
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Tributyl tin 209-287 ng/L 6.4 ng/L
Brominated Flame Retardants
PentaBDE 0.17-0.76 0.0048-0.018
PentaBDE 100 0.026-0.11 <0.001-0.0027
PentaBDE 99 0.12-0.64 0.0039-0.015
HexaBDE 0.002-0.007 <0.001-0.0016
TetraBDE 0.066-0.24 0.0048-0.014
TetraBDE 47 0.049-0.22 0.0048-0.014
Miscellaneous
1,1-Dodecanediol, diacetate 0.8
1,2-Ethanediamine, N-ethyl- 1.2
11-Hexadecenoic acid 0.5
11-Hexadecenoic acid, methyl ester 3.7
1-Octadecene 2.4
2,5-Dimethylphenol 0.1
2,6-Dimethylphenol 0.4
2-Methyl-butanoic acid, methyl ester 1.8
2-Methylphenol 0.24
3,4-Dimethylphenol 0.05 0.05
3-Methyl-butanoic acid, methyl ester 1.5
3-Methylphenol 5.9 5.9
4-Heptanone, 3-ethyl- 0.2
4-Methyl-pentanoic acid, methyl ester 1.1
4-Methylphenol 170
7-Hexadecenoic acid, methyl ester, (Z)- 4.2
8,11-Octadecadienoic acid, methyl ester 15.5
9,12-Octadecadienoic acid, methyl ester 7.5
9-Hexadecenoic acid 18.7
9-Hexadecenoic acid, eicosyl ester, (Z)- 5.1
9-Hexadecenoic acid, methyl ester, (Z)- 31.3
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9-Hexadecenoic acid, octadecyl ester, (Z)- 4.8
9-Hexadecenoic acid, tetradecyl ester 3.2
9-Octadecenamide, (Z)- 0.6
9-Octadecenoic acid, (E-), octadecyl ester 10.6
9-Octadecenoic acid, (Z)-, 9-hexadecenyl ester, (Z)- 2.9
9-Octadecenoic acid, (Z)-, 9-octadecenyl ester, (Z)- 2.0
9-Octadecenoic acid, (Z)-, octadecyl ester 7.8
9-Octadecenoic acid, methyl ester, (E)- 2.2
Acetaminophen 1.5
Acetic acid, octadecyl ester 2.5
Benzenesulfonic acid, methyl ester 1.1
Cholest-4-en-3-one 0.9
Cholest-5-en-3-one 2.4
Cholesta-3,5-diene 12.8
Cholesterol 28.6
Cholesterol acetate 4.9
Cis-1,2-dichloroethylene 0.5
Coprostanol 0.2
Decanamide, N-(2-hydroxyethyl)- 3.2
Dichloromethane 4.4
Docosanoic acid, methyl ester 0.9
Dodecanoic acid, dodecyl ester 2.1
Dodecanoic acid, hexadecyl ester 5.3
Dodecanoic acid, tetradecyl ester 3.0
Eicosanoic acid 1.3
Eicosanoic acid, methyl ester 0.6
Glycerol β-palmitate 3.8
Heptadecanoic acid, methyl ester 1.7
Hexadecanamide 0.7
Hexadecanoic acid, 14-methyl-, methyl ester 1.1
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Hexadecanoic acid, octadecyl ester 3.4
Hexadecanoic acid, tetradecyl ester 5.3
Hexadecenoic acid, methyl ester 3.9
Hexanoic acid, methyl ester 10.1
Lanosta-8,24-dien-3β-ol 0.6
Nicotine 1.2
Octadecanoic acid, 2-[(1-oxohexadecyl)oxy]ethyl ester 2.8
Octadecenoic acid, methyl ester 9.7
Pentadecanoic acid, methyl ester 1.8
Pentanoic acid, methyl ester 1.1
Phenol 2.2 21
Phenol, m-tert-butyl- 0.9
Propanoic acid, 2-methyl-, 1-(1,1-dimethylethyl)-2-methyl-1,3-propanediyl ester 0.5
Propanoic acid, 2-methyl-, 2,2-dimethyl-1-(2-hydroxy-1-methylethyl)propyl ester 1.1
Propanoic acid, 2-methyl-, 3-hydroxy-2,2,4-trimethylpentyl ester 0.3
Provitamin D3 3.1
Salicylic acid 0.6
Tetrachloromethane <0.1-1
Tetradecanoic acid, 9-methyl-, methyl ester 0.5
Tetradecanoic acid, hexadecyl ester 6.5
Tri(2-chloroethyl) phosphate 0.4
Trichloromethane <0.1-250 0.34
Tridecanoic acid, methyl ester 1.2
Triphenyl phosphate 0.5
β-Sitosterol 0.7
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2 Palmquist and Hanaeus (2005).
3 Palmquist and Hanaeus (2006).
4 Andersen et al. (2007); Eriksson et al. (2009); Revitt et al. (2011).
5 Hernández Leal et al. (2010); Temmink et al. (2011).
6 Andersson and Dalsgaard (2004).
7 Nielsen and Pettersen (2005).
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Table S2: List of prioritized OMP in the present study
Compound CAS Log D Compound CAS Log D
1,2-Ethanediamine, N-ethyl- 110-72-5 -3.43 Dibutyl tin 1002-53-5 2.19
1,3-Dioxolane 646-06-0 0.02 Dichloromethane 75-09-2 1.29
1,8-Nonanediol, 8-methyl- 54725-73-4 1.84 Diethyl phthalate 84-66-2 2.69
1-Dodecanamine, N,N-dimethyl- 112-18-5 2.71 Dihydromyrcenol 18479-58-8 2.82
2,4,6-trichlorophenol 88-06-2 2.14 Dimethyl phthalate 131-11-3 1.98
2,4-dichlorophenol 120-83-2 2.6 Dodecanamide, N,N-bis(2-hydroxyethyl)- 120-40-1 2.74
2,5-dichlorophenol 583-78-8 2.49 Dodecanoic acid 143-07-7 2.06
2.5-dimethylphenol 95-87-4 2.7 Ethylbenzene 100-41-4 2.93
2.6-dimethylphenol 576-26-1 2.7 Ethylparaben 120-47-8 2
2-Ethyl-1-hexanol 104-76-7 2.5 Eucalyptol 470-82-6 2.35
2-Hexanol 626-93-7 1.67 Eugenol 97-53-0 2.61
2-Hexanone 591-78-6 1.7 Geraniol 106-24-1 2.5
2-Methyl-butanoic acid, methyl ester 868-57-5 1.61 Hexanoic acid, methyl ester 106-70-7 1.96
2-methylphenol 95-48-7 2.18 Homomyrtenol 128-50-7 1.81
2-Phenoxy ethanol 122-99-6 1.13 Hydroxycitronellol 107-74-4 1.69
2-phenyl-5-benzimidazolesulfonic acid 27503-81-7 0.09 Indole 120-72-9 2.07
3,4-dimethylphenol 95-65-8 2.7 isobutylparaben 4247-02-3 2.88
3-Hexanol 623-37-0 1.74 Isoeugenol 97-54-1 2.63
3-Hexanone 589-38-8 1.95 Linalool 78-70-6 2.65
3-Methyl-butanoic acid, methyl ester 556-24-1 1.35 Malathion 121-75-5 1.86
3-methylphenol 108-39-4 2.18 Menthol 89-78-1 2.66
4-Heptanone 123-19-3 2.4 Methyl dihydrojasmonate 24851-98-7 2.92
4-Methoxy-benzoic acid 100-09-4 -1.44 Methylparaben 99-76-3 1.64
4-Methyl-pentanoic acid, methyl ester 2412-80-8 1.8 Mono 2-ethylhexyl phthalate 4376-20-9 1.19
4-Methyl-phenol (p-cresol) 106-44-5 2.18 Monobutyl tin 78763-54-9 -0.14
6-Methyl-5-hepten-2-one 110-93-0 2.02 Monooctyl tin NA1 1.45
Acetamide 60-35-5 -1.03 Naphthalene 91-20-3 2.96
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Acetaminophen (paracetamol) 103-90-2 0.9 Nicotine 54-11-5 -0.31
Acetic acid, phenoxy- 122-59-8 -2.01 Octanoic acid 124-07-2 0.51
Anise camphor (trans-anethole) 4180-23-8 2.94 Pentachlorophenol 87-86-5 2.79
BaCl (Benzalkonium chloride) 8001-54-5 1.69 Pentanoic acid, methyl ester 624-24-8 1.51
Benzene 71-43-2 1.97 Phenol 108-95-2 1.67
Benzenesulfonic acid, methyl ester 80-18-2 1.53 Phenylethyl alcohol (b-Methylphenethyl alcohol) 60-12-8 1.49
Benzoic acid 65-85-0 -1.48
Propanoic acid, 2-methyl-, 2,2-dimethyl-1-(2-hydroxy-1-
methylethyl)propyl ester 74367-33-2 2.7
Benzoic acid, 4-hydroxy- 99-96-7 -1.58 Propanoic acid, 2-methyl-, 3-hydroxy-2,2,4-trimethylpentyl ester 77-68-9 2.81
Butanoic acid, butyl ester 109-21-7 2.39 Propylparaben 94-13-3 2.52
Butylparaben 94-26-8 2.96 Salicylic acid 69-72-7 -1.52
Caffeine 58-08-2 -0.55 Sulfuric acid, dimethyl ester 77-78-1 -0.09
Camphor 76-22-2 2.55 Terpineol 98-55-5 2.17
Carvone 99-49-0 2.55 tetracanoic acid 544-63-8 2.31
Citric acid 77-92-9 -9.47 Toluene 108-88-3 2.49
Citronellol 26489-01-0 2.75 Tri(2-chloroethyl) phosphate 115-96-8 2.11
Coumarin 91-64-5 1.78 Trichloromethane 67-66-3 1.83
Decanamide, N-(2-hydroxyethyl)- 2128117 2.32 α-Methyl-benzenemethanol 98-85-1 1.62
Decanoic acid 334-48-5 1.17
1NA, not available
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Table S3. Physico-chemical characteristics of more problematic (RQ > 0.2) OMPs identified in GW
Compound Log
Kowa
Molecular
weightb
(g.mol-1
)
Formulab Surface tension
b
(mN.m-1
)
Vapour pressureb
(mmHg)
Water solubilityb
(mg.L-1
)
2-Ethyl-1-hexanol 2.5 130.23 C6H18O 47 0.205 1,285.3
Acetamide -1.03 59.07 C2H5NO na 0.0369 2,000
Benzene 1.97 78.11 C6H6 28.2 90 1,339
Benzenesulfonic acid methyl ester 1.53 172.20 C7H8O3S na 0.00175 3,174.2
Decanamide, N-(2-hydroxyethyl)- 2.32 215.34 C12H25NO2 na 1.08E-008 2,427.7
Dichloromethane 1.29 84.93 CH2Cl2 na 433 11,665
Dodecanoic acid 4.48 200.32 C12H24O2 26.6 0.00111 10.972
Indole 2.07 117.15 C8H7N na 0.0124 561.53
Methyl dihydrojasmonate 2.92 226.32 C13H22O3 na 0.000857 154.88
Nicotine 1.16 162.24 C10H14N2 na 0.0329 4.2E+5
Sulfuric acid, dimethyl ester -0.09 126.13 C2H6O4S 40.1 0.68 43,569
Tetracanoic acid 5.37 228.38 C14H28O2 na 0.00016 1.0548
Trichloromethane 1.83 119.38 CHCl3 27.1 192 8,630.2
Data from estimation software: aMarvin Sketch 6.2 and
bEPI Suite
TM; na = not available.