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Health risk assessment of organic micropollutants
in greywater for potable reuse
Ramiro Etchepare a,b,*, Jan Peter van der Hoek c,d
Laborat
orio de Tecnologia Mineral e Ambiental, Departamento de Engenharia de Minas, PPGE3M, Universidade
Federal do Rio Grande do Sul, Av. Bento Gonçalves 9500, 91501-970 Porto Alegre, RS, Brazil
b
CAPES Foundation, Ministry of Education of Brazil, Brası́lia DF 70.040-020, Brazil
c
Delft University of Technology, Department Water Management, Stevinweg 1, 2628 CN Delft, The Netherlands
d
Waternet, Strategic Centre, Korte Ouderkerkerdijk 7, 1096 AC Amsterdam, The Netherlands
a
article info
abstract
Article history:
In light of the increasing interest in development of sustainable potable reuse systems,
Received 31 May 2014
additional research is needed to elucidate the risks of producing drinking water from new
Received in revised form
raw water sources. This article investigates the presence and potential health risks of
11 August 2014
organic micropollutants in greywater, a potential new source for potable water production
Accepted 21 October 2014
introduced in this work. An extensive literature survey reveals that almost 280 organic
Available online 12 November 2014
micropollutants have been detected in greywater. A three-tiered approach is applied for
the preliminary health risk assessment of these chemicals. Benchmark values are derived
Keywords:
from established drinking water standards for compounds grouped in Tier 1, from litera-
Greywater
ture toxicological data for compounds in Tier 2, and from a Threshold of Toxicological
Organic micropollutants
Concern approach for compounds in Tier 3. A risk quotient is estimated by comparing the
Risk assessment
maximum concentration levels reported in greywater to the benchmark values. The results
Potable reuse
show that for the majority of compounds, risk quotient values were below 0.2, which
Toxicological data
suggests they would not pose appreciable concern to human health over a lifetime exposure to potable water. Fourteen compounds were identified with risk quotients above 0.2
which may warrant further investigation if greywater is used as a source for potable reuse.
The present findings are helpful in prioritizing upcoming greywater quality monitoring and
defining the goals of multiple barriers treatment in future water reclamation plants for
potable water production.
© 2014 Elsevier Ltd. All rights reserved.
1.
Introduction
Treatment of wastewater for potable reuse is an emerging
strategy being implemented worldwide to supplement water
resource portfolios, especially in arid and semi-arid regions,
coastal communities faced with saltwater intrusions and regions where the quantity and/or quality of the water supply
may be compromised. Many examples of potable reuse
treatment trains are reported throughout the world and
rio de Tecnologia Mineral e Ambiental, Departamento de Engenharia de Minas, PPGE3M, Universidade
* Corresponding author. Laborato
Federal do Rio Grande do Sul, Av. Bento Gonçalves 9500, 91501-970 Porto Alegre, RS, Brazil.
E-mail addresses: ramiro.etchepare@ufrgs.br (R. Etchepare), j.p.vanderhoek@tudelft.nl, jan.peter.van.der.hoek@waternet.nl (J.P. van
der Hoek).
http://dx.doi.org/10.1016/j.watres.2014.10.048
0043-1354/© 2014 Elsevier Ltd. All rights reserved.
w a t e r r e s e a r c h 7 2 ( 2 0 1 5 ) 1 8 6 e1 9 8
recent discussions among water reuse experts have addressed
the reliance on the existing systems to produce acceptable
and safe water to consume (Rodriguez et al., 2009;
Tchobanoglous et al., 2011; Pisani and Menge, 2013; Gerrity
et al., 2013).
Due to an expected higher level of initial contamination in
the source wastewater in comparison to conventional source
waters, potable reuse systems are being scrutinized more
carefully by water regulators. Accordingly, multi-barrier
treatment systems are being applied to attain high levels of
chemical and microbial contaminant removal and to satisfy
established drinking water regulations. The evaluation of
potable reuse schemes should be in line with the World Health
Organization guidelines for Water Safety Plans (WSP), which
are usually applied for conventional drinking water supplies
(WHO, 2011). WSP are based on the human health risk
assessment of the potable water supply chain and take into
consideration the hazards within the system, from the
catchment to the consumer, in relation to the risk of producing unsafe water. Although in most cases pathogen removal
requirements drive unit process selection and integration,
another important major public health concern is the potential health impacts from long-term, and in some cases, shortterm exposure to low concentration of chemicals and micropollutants present in the reclaimed water (WHO, 2011).
Therefore it is important to characterize contaminant loads
and associated risks for all potential drinking water sources,
to adequately determine total removal required, identify
appropriate treatment trains and ultimately satisfy public
health criteria.
Municipal wastewater treatment plant (WWTP) effluents
have been the main source of water for potable reuse schemes
in large-scale installations (Gerrity et al., 2013). However, a
general trend is visible towards more decentralized and closed
loop (onsite) systems as separating wastewater at the source
and treating separately the different flows will offer possibilities to recover clean water, nutrients and energy (Jefferson
et al., 2000; Cook et al., 2009; van der Hoek et al., 2014). An
example of this is in the urban (domestic) environment, where
“green buildings” are being commissioned in growing number
(Zuo and Zhao, 2014) and water efficiency is accomplished
through the collection, treatment and reuse of rainwater,
black water and greywater (Johnson, 2000). Additionally, individual or cluster of housing estates and isolated communities, where there is no connection to the public water supply
and sewerage, may be benefitted with more readily available
sources of water for potable uses (Mwenge Kahinda et al.,
2007; Cook et al., 2009).
In the present paper, greywater (GW), used here to refer to
domestic wastewater excluding any input from toilets
(Jefferson et al., 2000), is introduced as an alternative potential source of water for potable reuse. GW has been estimated to account for about 60e80% of domestic wastewater
ndez Leal, 2010), yet, its chem(Eriksson et al., 2002b; Herna
ical nature is quite different. For example, the COD:BOD ratio
can be as high as 4:1 (Boyjoo et al., 2013), indicating a high
chemical content. It must also be pointed out that GW can be
highly variable in composition, being highly dependent on
the activities in the household, as well as the inhabitants'
lifestyles and use of chemical products. Many previous
187
works have been published on the characteristics of GW in
relation to conventional physical (temperature, colour,
turbidity, electrical conductivity, suspended solids), chemical (BOD, COD, TOC, pH, nutrients, heavy metals) and
microbiological (bacteria, protozoa, viruses, helminths) parameters and were recently reviewed and compiled by
Boyjoo et al. (2013).
Despite its much lower pathogen content (absence of feces)
and organic matter content, surprisingly, GW has only been
proposed for non-potable reuse applications, especially irrigation (Surendran and Wheatley, 1998; Smith and BaniMelhem, 2012; USEPA, 2012; Alfiya et al., 2013). Therefore the
associated risks are generally divided into two categories:
environmental risks and human health risks. Environmental
risk assessments (ERA) related to detrimental effects of
reclaimed water on soil characteristics (Travis et al., 2010;
Turner et al., 2013), plants growth (phytotoxicity e Garland
et al., 2000; Pinto et al., 2010), surface/groundwater quality
and aquatic/terrestrial organisms (van Wezel and Jager, 2002;
Eriksson et al., 2006) are highly important to address environmental contamination issues. Eriksson et al. (2002b) is one
of the scarce studies addressing ERA of organic micropollutants (OMPs) present in GW. Since using reclaimed GW
for toilet flushing and car washing is also becoming common,
more information is available regarding (microbial) health
risks for non-potable reuse (Dixon et al., 1999; Maimon et al.,
2010; O'Toole et al., 2012; Barker et al., 2013). Nevertheless,
the main challenge still waiting for advanced research
development is to turn GW into potable water quality (Oron
et al., 2014) and very few studies have investigated the nature, loads and associated health risks of OMPs in GW related
to the use of GW as a new source for drinking water production. The latter consists the focus of the present study.
At Delft University of Technology, in the Netherlands, a
team of scientists, students and companies is working on the
Green Village, a temporary pilot site on the campus, which
will be used to test new technologies prior to their implementation in the development of the Green Campus, a more
ambitious project planned at the University (van der Hoek
et al., 2014). The Green Village will not be connected to
water supply, the sewerage and cable systems. The aim is to
develop it as an autarkic and decentralized system, producing
its own potable water (from GW) and electricity, and clean its
organic waste streams in a sustainable way. The present work
is a first attempt, undertaken as part of the Green Village
project, at compiling a hazard assessment and risk characterization to identify and understand the risks of potable
water production from GW due to the presence of OMPs.
Although most studies investigating GW reuse and associated
risks have focused on non-potable applications and conventional water quality parameters, this work is intended to
provide in-depth and up-to-date compiled data on OMPs
found in GW. This paper includes a preliminary health risk
assessment (screening level) by means of a theoretical and
empirical framework (three-tiered approach) of OMPs that
may pose a risk to human health in reclaimed potable water
and ends with a discussion of the suitability of treatment
barriers to mitigate problematic compounds. In part the present study is aimed at helping prioritize further investigations
in this subject.
188
2.
w a t e r r e s e a r c h 7 2 ( 2 0 1 5 ) 1 8 6 e1 9 8
Materials and methods
If GW is to be treated and reused as potable water, a preliminary health risk assessment has to be conducted to
identify and determine which OMPs, at the concentrations
present in GW, may pose a potential health risk if not properly
removed. The present work includes a risk characterization
conducted in four consecutive steps. First, an extensive literature review on the presence and concentrations of OMPs in
GW was conducted. Second, solute properties of the identified
compounds were obtained in order to prioritize the most
relevant and problematic compounds and exclude from the
analysis those that are expected to be easily removed in
conventional water and wastewater treatment plants. Third, a
three-tiered approach was applied to derive benchmark
values for the compounds with the aid of either statutory
drinking water guidelines or toxicological threshold values.
Finally, measured maximum GW concentrations reported
were compared to the respective benchmark values and a risk
quotient (RQ) was calculated. The detailed methodology used
for each of these steps is described in Sections 2.1e2.4. and
illustrated in Fig. 1. Mixture interactions were not quantified
since the risk assessment methods for compounds with
different mode of action are a complex matter still under
debate.
2.1.
Presence of organic micropollutants in greywater
A comprehensive literature review on the presence and concentrations of OMPs in GW was performed. The survey did not
include organic macro-pollutants, inorganic compounds such
as nutrients and metals since they have been extensively
studied elsewhere, but was confined to organic chemicals
present in micro and nano-scale concentrations. The review
covered the period from 1991 to 2014, by consulting published
(inter)national articles, conference proceedings, academic
theses and official reports.
2.2.
Selection of compounds for assessment
As it is not feasible to include every chemical in a toxicological assessment, the OMPs identified in GW were prioritized
based on their ability to easily pass conventional water
treatment barriers, as components not removed in conventional systems are likely to pose the most threat in potable
reuse of GW.
The n-octanol-water partition coefficient (log Kow) is a solute property related to hydrophobicity which has been used
as log cut-off to prioritize compounds in toxicological assessments (Schriks et al., 2010). Compounds with a log Kow
above 3 are less likely to pass water treatment plants that
include an activated-carbon adsorption stage than those with
lower values (Westerhoff et al., 2005). pH-corrected log Kow
values are referred to as log D or distribution coefficient. The
log D appears to be a more accurate and conservative tool to
predict the adsorption of ionic solutes than the log Kow (Hu
et al., 1997; Ridder et al., 2010). For neutral solutes, log
Kow ¼ log D, but for ionic solutes log D < log Kow. In the present
work, log D values were obtained with the aid of the estimation program Marvin Sketch 6.2 and compounds with a log
D 3 were excluded from further assessment. An exception
was made for 4 alkylphenol ethoxylates (octylphenol tetraethoxylate; octylphenol hexa-ethoxylate; octylphenol heptaethoxylate; and octylphenol octa-ethoxylate) which were not
found on the estimation software. For these compounds the
log D values were obtained from literature (Ahel and Giger,
1993).
2.3.
Derivation of benchmark values with a three-tiered
approach
Due to the potential toxicity of low doses of OMPs after mid-to
long-term exposure and the associated threat to public health,
it was necessary to determine the concentrations of the
selected contaminants at which potential adverse health effects may occur. A three-tiered approach, as similarly
Fig. 1 e Flow chart indicating the risk assessment conducted in the present study. GW, greywater; Log D, distribution
coefficient; RQ, risk quotient.
189
w a t e r r e s e a r c h 7 2 ( 2 0 1 5 ) 1 8 6 e1 9 8
proposed by Rodriguez et al. (2007), was applied in order to
derive benchmark values. Compounds with an established
drinking water guideline or standard value, were allocated to
“Tier 1”. Compounds without drinking water standards, but
for which toxicity information is available were allocated to
“Tier 2”. Those compounds for which toxicity information is
not available were allocated to “Tier 3”.
2.3.1.
Tier 1: regulated compounds
Conventionally, raw and treated potable water quality have
been analysed by comparing the measured concentration of a
particular substance or parameter with the respective
benchmark value based on drinking water standards or
guidelines. Because different states and nations regulate
different contaminants or may assign their own standard
values for the same contaminant, it is important to define the
guidelines pertinent to a specific context. For the risk assessment of potable reuse of GW in the Netherlands, the applicable maximum contaminant levels (benchmark values) were
extracted from the following drinking water guidelines, in
order of priority: the Dutch Drinking Water Decree
(Staatsblad, 2011), the Guidelines for Drinking Water Quality
(WHO, 2011), the European Council Directive 98/83/EC (EC,
1998) and the 2011 Edition of the Drinking Water Standards
and Health Advisories (USEPA, 2011). However, since the
established standards for the parameters “pesticides” and
“other anthropogenic compounds” in the Dutch Drinking
Water Decree were considered too generic to be used in the
present risk assessment, their respective target values were
not used to derive benchmark values for pesticides and
anthropogenic compounds. These compounds were assessed
individually.
available, a provisional TDI was derived based on the lowest
(sub) chronic no observed (adverse) effect levels (NO(A)ELs)
obtained in rodent studies divided by an assessment factor
(AF) of either:
100 e includes combined factor of 10 for interspecies
extrapolation and factor of 10 for inter-individual
differences,
200 e includes an additional factor of 2 to extrapolate from
subchronic to chronic exposure, or
600 e includes an additional factor of 6 to extrapolate from
subacute to chronic exposure, depending on which was
most applicable to the data available (Van Leeuwen and
Vermeire, 2007).
Toxicological threshold values refer to the daily exposure
likely to be without deleterious effects in humans and therefore cannot be taken directly as drinking water standards but
instead must be used to derive benchmark values as described
by the WHO (2011). In the present study the benchmark values
for drinking water were calculated using Equation (1). This
method allocates 20% of the reference intake value (TDI/ADI/
RfD) for drinking water, to allow for exposure from other
sources, then multiplies this allocation by the typical average
body weight of an adult (60 kg) and divides it by a daily
drinking water consumption of 2 L. Equation (2) was used to
calculate the benchmark value corresponding to a conservative cancer risk of 105 for carcinogenic compounds which
have not been assigned a toxicological threshold value but
have a reported oral slope factor (SF) value instead (WHO,
2011).
Benchmark value ¼
2.3.2.
Tier 2: unregulated compounds with toxicity value
The first step of Tier 2 was to obtain toxicological threshold
values for the assessed compounds expressed as TDI (tolerable daily intake), ADI (acceptable daily intake) and/or RfD
(reference dose) from data sets and documents available from
World Health Organization (WHO), U.S. EPA and other reliable
(inter)national sources which are presented in Table 1. If not
T x bw x P
C
(1)
Where:
T ¼ toxicological threshold value (TDI/ADI/RfD)
bw ¼ body weight (60 kg)
P ¼ fraction of the TDI allocated to drinking water (20%)
C ¼ daily drinking water consumption (2 L)
Table 1 e Sources to obtain toxicological threshold values.
Sources of toxicological assessment data
Environmental Health Criteria monographs (WHO)
European Comission e Health and Consumer Protection
(ECHCP)
European Comission e Scientific Committee on Health
and Environmental Risks (SCHER)
European Medicines Agency (EMA)
European Safe Food Authority (EFSA)
Joint FAO/WHO Expert Committee on Food Additives (JECFA)
Organization for Economic Cooperation and
Developmente Exisiting chemicals database (OECD)
The German Federal Institute for Risk Asessment (BFR)
The Scientific committee on occupational exposure
limits (SCOEL)
U.S. EPA Integrated Risk Information System (EPA-IRIS)
URL
http://inchem.org/pages/ehc.html
http://ec.europa.eu/dgs/health_consumer/dyna/press_room/index_
en.cfm
http://ec.europa.eu/health/scientific_committees/environmental_
risks/index_en.htm
http://www.ema.europa.eu/ema/
http://www.efsa.europa.eu/
http://inchem.org/pages/jecfa.html
http://webnet.oecd.org/hpv/ui/Search.aspx
http://www.bfr.bund.de/de/start.html
http://ec.europa.eu/social/main.jsp?
catId¼148&langId¼en&intPageId¼684
http://cfpub.epa.gov/ncea/iris/index.cfm?fuseaction¼iris.
showSubstanceList&list_type¼alpha&view¼A
190
w a t e r r e s e a r c h 7 2 ( 2 0 1 5 ) 1 8 6 e1 9 8
Benchmark value ¼
bw Risk level
C SF
(2)
presumed to present less appreciable concern to human
health.
Where:
Risk level ¼ 105
SF ¼ Slope factor
2.3.3.
Tier 3: compounds without toxicity value
For compounds without toxicity information, target values
were derived from a Threshold of Toxicological Concern (TTC)
approach. The TTC is a conservative level of human intake or
exposure that is considered to be of negligible risk to human
health, despite the absence of chemical-specific toxicity data.
The widely accepted TTC values proposed by Munro et al.
(1996) and Kroes et al. (2004) are set as:
0.0025 mg/kg bw/day for substances that raise concern for
potential genotoxicity;
0.3 mg/kg bw/day for organophosphates;
1.5, 9 and 30 mg/kg bw/day for Cramer class III, II and I
substances, respectively.
Thus, these values were applied for the present Tier 3
compounds. The thresholds for non-genotoxic compounds
were elaborated using a dataset published by Munro et al.
(1996), related to chemical classes as defined by Cramer
et al. (1978) and are based on the 5th percentiles of NOELs
covering chronic oral exposure. Possible genotoxic compounds and the Cramer class classification of compounds
were identified in the present work through structural alerts
aided by the OECD QSAR 3.2 application toolbox (URL 1). The
present approach also considered the exclusion of compounds for which no TTC could be derived such as high potency carcinogens (i.e. aflatoxin-like, azoxy- or N-nitrosocompounds, benzidines, hydrazines), metal containing compounds, proteins, steroids, polyhalogenated-dibenzodioxin,
-dibenzofuran, and ebisphenyl (Kroes et al., 2004).
The TTC values were further translated to benchmark
values by taking into account the body weight and daily
ingestion of drinking water (Equation (3)). The same body
weight (60 kg), allocation factor (20%) and water consumption
rate (2 L) of Tier 2 were applied in Equation (3).
Benchmark value ¼
2.4.
ðTTC valueÞ bw P
C
(3)
Calculation of a risk quotient
To evaluate the potential health risks and toxicological relevance of the assessed compounds, the maximum concentration levels identified in GW were divided by the benchmark
value and expressed as a RQ. Compounds with a RQ 1 may
be of potential human health concern if treated GW were to be
consumed over a lifetime period. These compounds would be
of high-priority at the selection and design of future GW
treatment plants for potable water production. As similarly
proposed by Schriks et al. (2010), compounds in GW with a RQ
value 0.2 and <1, are considered to also warrant further
investigation. Compounds in GW with a RQ value <0.2 are
3.
Results
3.1.
Organic micropollutants in greywater
OMPs became a focus for GW research in the 1990's after two
articles (Burrows et al., 1991; Santala et al., 1998) reported the
presence of detergents and long-chain fatty acids detected
through a GCeMS screening. A more comprehensive study in
this field of research, which identified as many as 900 xenobiotic organic compounds (XOCs) as potentially present in
GW, was performed by Eriksson et al. (2002a), using tables of
contents of Danish household products (bathroom and
laundry chemicals). The XOCs are expected to be present in
GW because they originate from the various chemicals and
personal care products used in households such as cleaning
agents (detergents, soaps, shampoos), fragrances, UV-filters,
perfumes and preservatives. Subsequent screening of bathroom GW from an apartment building in Denmark confirmed
almost 200 different XOCs (Eriksson et al., 2003). However, as
the study also detected some unexpected chemicals not
directly connected to household chemicals (e.g. flame retardants and illicit drugs), it can be concluded that an inventory of the use of household chemicals cannot
compensate for a full characterization of the compounds
actually present in GW. In a later study investigating the
concentrations of several selected organic hazardous substances in GW from housing areas in Sweden, Palmquist &
Hanæus (2005, 2006) found that 46 out of more than 80
organic substances were present in concentrations above the
detection limits.
Quite recently, Donner et al. (2010) reviewed the knowledge
with respect to the presence of XOCs in GW and investigated
the sources, presence and potential fate of xenobiotic micropollutants in on-site GW treatment systems. However, Donner's investigation focused on non-potable reuse of GW and
was limited to a few compounds selected from those listed
either as Priority Substances or Priority Hazardous Substances
under the European Water Framework Directive (WFD) (EU,
2000). So far the WFD has established environmental quality
standards (EQS) for 41 dangerous chemical substances (33 of
them classified as priority substances). However, these are
only a fraction of the compounds that are potentially hazardous as this list does not include, for instance, any pharmaceutical compounds or personal care products.
In spite of these findings, the number of publications on
the monitoring and analysis of OMPs in GW is still scarce.
There are, to the best of our knowledge, 12 published studies
on this topic, where GW was produced, sampled and analysed
from 7 different locations (5 housing estates, 1 camping site
and 1 sport club) spread in Sweden, Denmark and the
Netherlands (Eriksson et al., 2003; Andersson and Dalsgaard,
2004; Nielsen and Pettersen, 2005; Palmquist and Hanæus,
2005, 2006; Larsen, 2006; Ledin et al., 2006; Andersen et al.,
ndez Leal et al., 2010; Eriksson et al., 2009; Revitt
2007; Herna
et al., 2011; Temmink et al., 2011). In total, 278 OMPs have
been detected in GW considering all available literature data.
191
w a t e r r e s e a r c h 7 2 ( 2 0 1 5 ) 1 8 6 e1 9 8
Table 2 e Selected OMPs, maximum detected levels and calculated RQ values.
Compounds
Tier 1
Benzene
Dichloromethane
Ethylbenzene
Pentachlorophenol
Trichloromethane
Tier 2
1,3-Dioxolane
1-Dodecanamine, N,N-dimethyl2,4,6-Trichlorophenol
2,4-Dichlorophenol
2-Ethyl-1-hexanol
2-Hexanone
2-Methylphenol
2-Phenyl-5-benzimidazolesulfonic
acid
3,4-Dimethylphenol
3-Methylphenol
4-Methyl-phenol
Maximum
detected level,
mg L1
9.85
4.4
2.1
0.04
250
Drinking water
standard/toxicity
threshold value
Source
Benchmark
value, mg L1
1 mg L1
5 mg L1
300 mg L1
1 mg L1
300 mg L1
Staatsblad (2011)
USEPA (2011)
WHO (2011)
USEPA (2011)
WHO (2011)
1
5
300
1
300
9.85
0.88000
0.00700
0.04000
0.83333
75 mg/kg bw/day
50 mg/kg bw/day
0.011 per mg/kg bw/day
0.003 mg/kg bw/day
0.5 mg/kg bw/day
0.005 mg/kg
0.05 mg/kg bw/day
40 mg/kg bw/day
750
500
25
18
6
30
300
30,000
0.00227
0.01480
0.00400
0.00889
1.41667
0.02000
0.00080
0.00051
6
300
1500
0.00833
0.01967
0.11333
300
12,000
600
30,000
10,000
1000
0.00500
0.00004
0.03450
0.00002
0.00010
0.01700
12,000
6000
72,000
3000
600
6
4800
300
1500
10,000
15,000
450
3000
120
24,000
10,000
120
4.8
600
12,000
480
78
0.00095
0.00008
0.00021
0.00093
0.00167
0.50
0.00792
0.02967
0.00953
0.00410
0.00007
0.00133
0.00513
0.01583
0.00136
0.00370
0.00035
0.25000
0.03500
0.00175
0.00292
0.00513
9
9
9
180
180
180
180
180
180
180
180
180
0.13333
0.06667
0.01778
0.00056
0.00222
0.00167
0.01000
0.13778
0.00389
0.00167
0.00833
0.00778
0.05
5.9
170
0.001 mg/kg bw/day
0.05 mg/kg bw/day
50 mg/kg bw/day
Acetaminophen
Anise camphor
Benzalkonium chloride
Benzoic acid
Benzoic acid, 4-hydroxyButylparaben
1.5
0.5
20.7
0.5
1
17
0.05 mg/kg bw/day
2 mg/kg bw/day
0.1 mg/kg bw/day
5 mg/kg bw/day
1000 mg/kg bw/day
100 mg/kg bw/day
Camphor
Carvone
Citric acid
Citronellol
Coumarin
Dibutyl tin
Diethyl phthalate
Dihydromyrcenol
Dodecanamide, N,N-bis(2-hydroxyethyl)Ethylparaben
Eugenol
Isoeugenol
Linalool
Malathion
Menthol
Methylparaben
Naphthalene
Nicotine
Phenol
Propylparaben
Toluene
Tri(2-chloroethyl) phosphate
Tier 3
1,2-Ethanediamine, N-ethyl1,8-Nonanediol, 8-methyl2,5-Dichlorophenol
2,5-Dimethylphenol
2,6-Dimethylphenol
2-Hexanol
2-Methyl-butanoic acid, methyl ester
2-Phenoxy ethanol
3-Hexanol
3-Hexanone
3-Methyl-butanoic acid, methyl ester
4-Heptanone
11.4
0.5
15
2.8
1
3
38
8.9
14.3
41
1
0.6
15.4
1.9
32.6
37
0.042
1.2
21
21
1.4
0.4
2 mg/kg bw/day
1 mg/kg bw/day
1200 mg/kg bw/day
0.5 mg/kg bw/day
0.1 mg/kg bw/day
1 mg/kg bw/day
0.8 mg/kg bw/day
10 mg/kg bw/day
50 mg/kg bw/day
10 mg/kg bw/day1
2.5 mg/kg bw/day
0.075 mg/kg bw/day
0.5 mg/kg bw/day
0.02 mg/kg bw/day
4 mg/kg bw/day
10 mg/kg bw/day1
0.02 mg/kg bw/day
0.0008 mg/kg bw/day
0.1 mg/kg bw/day
2 mg/kg bw/day
0.08 mg/kg bw/day
13 mg/kg bw/day
EFSA (NOAEL); AF ¼ 600
OECD (NOEL); AF ¼ 600
EPA-IRIS (SF)
EPA-IRIS (RfD)
JECFA (ADI)
EPA-IRIS (RfD)
EPA-IRIS (RfD)
ECHCP (NOAEL);
AF ¼ 200
EPA-IRIS (RfD)
EPA-IRIS (RfD)
EPA report (NOAEL);
AF ¼ 200
EMA (ADI)
JECFA (ADI)
BFR (ADI)
JECFA (ADI)
OECD (NOAEL); AF ¼ 600
Daston et al. (2004) (NOEL);
AF ¼ 600
EFSA (TDI)
JECFA (ADI)
OECD (NOAEL); AF ¼ 100
JECFA (ADI)
EFSA (TDI)
WHOeIPCS (2006) (TDI)
EPA-IRIS (RfD)
JECFA (NOAEL); AF:200
EFSA (NOAEL); AF ¼ 200
EFSA (NOAEL); AF ¼ 600
JECFA (ADI)
EMA (ADI)
JECFA (ADI)
EPA-IRIS (RfD)
JECFA (ADI)
EFSA (NOAEL); AF ¼ 600
EPA-IRIS (RfD)
EFSA (ADI)
WHO (ADI)
JECFA (ADI)
EPA-IRIS (RfD)
SCHER (TDI)
1.2
0.6
0.16
0.1
0.4
0.3
1.8
24.8
0.7
0.3
1.5
1.4
1.5 mg/kg bw/day
1.5 mg/kg bw/day
1.5 mg/kg bw/day
30 mg/kg bw/day
30 mg/kg bw/day
30 mg/kg bw/day
30 mg/kg bw/day
30 mg/kg bw/day
30 mg/kg bw/day
30 mg/kg bw/day
30 mg/kg bw/day
30 mg/kg bw/day
TTC (Cramer
TTC (Cramer
TTC (Cramer
TTC (Cramer
TTC (Cramer
TTC (Cramer
TTC (Cramer
TTC (Cramer
TTC (Cramer
TTC (Cramer
TTC (Cramer
TTC (Cramer
1.7
7.4
0.10
0.16
8.5
0.6
0.24
15.3
RQ
class
class
class
class
class
class
class
class
class
class
class
class
III)
III)
III)
I)
I)
I)
I)
I)
I)
I)
I)
I)
(continued on next page)
192
w a t e r r e s e a r c h 7 2 ( 2 0 1 5 ) 1 8 6 e1 9 8
Table 2 e (continued )
Compounds
4-Methoxy-benzoic acid
4-Methyl-pentanoic acid, methyl ester
6-Methyl-5-hepten-2-one
Acetamide
Acetic acid, phenoxyBenzenesulfonic acid, methyl ester
Butanoic acid, butyl ester
Caffeine
Decanamide, N-(2-hydroxyethyl)Decanoic acid
Dimethyl phthalate
Dodecanoic acid
Eucalyptol
Geraniol
Hexanoic acid, methyl ester
Homomyrtenol
Hydroxycitronellol
Indole
Isobutylparaben
Methyl dihydrojasmonate
Mono 2-ethylhexyl phthalate
Monobutyl tin
Monooctyl tin
Octanoic acid
Pentanoic acid, methyl ester
Phenylethyl alcohol
Propanoic acid, 2-methyl-,
2,2-dimethyl-1-(2-hydroxy1-methylethyl)propyl ester
Propanoic acid, 2-methyl-,
3-hydroxy-2,2,4-trimethylpentyl ester
Salicylic acid
Sulphuric acid, dimethyl ester
Terpineol
Tetracanoic acid
a-Methyl-benzene methanol
Maximum
detected level,
mg L1
12.7
1.1
0.1
8.6
4
1.1
0.9
0.5
3.2
1.2
4.9
680
0.1
0.8
10.1
0.9
0.2
3.8
8
3.9
1.7
0.99
0.1
3
1.1
0.6
1.1
0.3
0.6
0.1
1.2
2808
0.1
Drinking water
standard/toxicity
threshold value
30 mg/kg bw/day
1.5 mg/kg bw/day
30 mg/kg bw/day
1.5 mg/kg bw/day
30 mg/kg bw/day
0.0025 mg/kg bw/day
30 mg/kg bw/day
1.5 mg/kg bw/day
1.5 mg/kg bw/day
30 mg/kg bw/day
30 mg/kg bw/day
30 mg/kg bw/day
1.5 mg/kg bw/day
30 mg/kg bw/day
30 mg/kg bw/day
30 mg/kg bw/day
30 mg/kg bw/day
1.5 mg/kg bw/day
30 mg/kg bw/day
1.5 mg/kg bw/day
30 mg/kg bw/day
1.5 mg/kg bw/day
1.5 mg/kg bw/day
30 mg/kg bw/day
30 mg/kg bw/day
30 mg/kg bw/day
1.5 mg/kg bw/day
TTC
TTC
TTC
TTC
TTC
TTC
TTC
TTC
TTC
TTC
TTC
TTC
TTC
TTC
TTC
TTC
TTC
TTC
TTC
TTC
TTC
TTC
TTC
TTC
TTC
TTC
TTC
1.5 mg/kg bw/day
30 mg/kg bw/day
0.0025 mg/kg bw/day
30 mg/kg bw/day
30 mg/kg bw/day
30 mg/kg bw/day
The full list of the OMPs identified and their concentrations is
provided in supplementary information, Table S1. Identified
compounds were grouped into eleven substance classes: 1)
Plasticisers and softeners; 2) Preservatives; 3) UV filters; 4)
Surfactants and emulsifiers; 5) Flavours and fragrances; 6)
Polycyclic aromatic hydrocarbons (PAHs); 7) Polychlorinated
biphenyls (PCBs); 8) Solvents; 9) Brominated flame retardants;
10) Organotin compounds; and 11) Miscellaneous.
3.2.
Source
Selection of compounds
The outcome of the prioritization of OMPs found in GW
resulted in the identification of 89 compounds (log D < 3) out of
the original list. These compounds were selected for further
assessment. Of these 89 chemicals surfactants contributed 5,
fragrances and flavours 26, plasticisers 4, preservatives 17,
solvents 10, organotin compounds 3, UV filter 1, PAH 1, and
other miscellaneous compounds 22. These OMPs and their
respective CAS numbers and log D values are listed in Table S2
(supplementary data).
(Cramer class I)
(Cramer class III)
(Cramer class I)
(Cramer class III)
(Cramer class I)
(potential genotoxic)
(Cramer class I)
(Cramer class III)
(Cramer class III)
(Cramer class I)
(Cramer class I)
(Cramer class I)
(Cramer class III)
(Cramer class I)
(Cramer class I)
(Cramer class I)
(Cramer class I)
(Cramer class III)
(Cramer class I)
(Cramer class III)
(Cramer class I)
(Cramer class III)
(Cramer class III)
(Cramer class I)
(Cramer class I)
(Cramer class I)
(Cramer class III)
Benchmark
value, mg L1
RQ
180
9
180
9
180
0.15
180
9
9
180
180
180
9
180
180
180
180
9
180
9
180
9
9
180
180
180
9
0.07056
0.12222
0.00056
0.95556
0.02222
7.33333
0.00500
0.05556
0.35556
0.00667
0.02722
3.77778
0.01111
0.00444
0.05611
0.00500
0.00111
0.42222
0.04444
0.43333
0.00944
0.11
0.01111
0.01667
0.00611
0.00333
0.12222
TTC (Cramer class III)
9
0.03333
TTC
TTC
TTC
TTC
TTC
180
0.15
180
180
180
(Cramer class I)
(potential genotoxic)
(Cramer class I)
(Cramer class I)
(Cramer class I)
0.00333
0.66667
0.00667
15.6
0.00056
3.3.
Preliminary health risk assessment of selected
OMPs in GW
The final list of OMPs in GW with their respective benchmark
values and RQ values is provided in Table 2. For only 5 compounds (benzene, dichloromethane, ethylbenzene, pentachlorophenol and trichloromethane) statutory drinking water
guideline values were available and these compounds were
grouped into Tier 1. The benchmark values of Tier 1 ranged
from 1 mg/L (benzene) to 300 mg L1 (ethylbenzene and trichloromethane, respectively) and originated from the Dutch
Drinking Water Decree, the WHO Guidelines for Drinking
Water Quality and the USEPA, according to the order of priority set in the present work. Toxicological data were found
for 39 compounds (Tier 2). An established TDI, ADI or RfD was
available for 27 compounds and in 11 cases when there was no
TDI, ADI or RfD available, an established NO(A)EL was utilized
to derive a TDI value with the aid of assessment factors.
Specifically for the carcinogenic 2,4,6-trichlorophenol there
was an SF available from EPA-IRIS. The remaining 45 compounds with no toxicological data were grouped into Tier 3.
w a t e r r e s e a r c h 7 2 ( 2 0 1 5 ) 1 8 6 e1 9 8
The latter comprised 29 compounds allocated to Cramer class
I, 14 compounds allocated to Cramer Class III and 2 compounds with genotoxic structural alerts.
Calculated benchmark values varied from 0.15 mg L1 (for
the possible genotoxic benzenesulfonic acid, methyl ester and
sulphuric acid, dimethyl ester) to 72,000 mg L1 (for the preservative citric acid). The highest observed benchmark values
(eight of them >10,000 mg L1) referred to preservatives and
fragrances/flavours, which in general are also chemicals utilized as food additives. The lowest observed benchmark
values related to compounds allocated to Tier 3 (from 0.15 to
180 mg L1), with exception for benzene (1 mg L1), dichloromethane (5 mg L1) and pentachlorophenol (1 mg L1) in Tier 1;
2,4,6-trichlorophenol (25 mg L1), 2,4-dichlorophenol
(18 mg L1), 2-ethyl-1-hexanol (6 mg L1), 2-hexanone, 3,4dimethylphenol (6 mg L1), dibutyl tin (6 mg L1), nicotine
(4.8 mg L1), and tri(2-chloroethyl) phosphate (78 mg L1) in Tier
2.
For 5 compounds the RQ value was above 1, namely: benzene (Tier 1); 2-ethyl-1-hexanol (Tier 2); benzenesulfonic acid
methyl ester; dodecanoic acid; and tetracanoic acid (Tier 3).
Accordingly, these compounds may be of potential human
health concern if not reduced in treatment barriers and are
considered to be of higher priority for further studies on the
risk assessment and the selection of technologies to be
applied in future GW treatment plants for drinking water
production. For 9 compounds (dibutyl tin; dichloromethane;
trichloromethane; nicotine; acetamide; indole; decanamide,
N-(2-hydroxyethyl)-; sulphuric acid, dimethyl ester; and
methyl dihydrojasmonate), the RQ value was above 0.2 (and
below 1). These compounds are also considered to warrant
further investigation.
4.
Discussion
Potable reuse of GW is a novel and potentially beneficial
research topic given the increasingly urgent need to identify
and validate new raw water sources for safe drinking water
production worldwide. An important concern in the development of GW potable reuse schemes appears to be the lack of
knowledge about the presence and risks of OMPs. The occurrence of OMPs has been much better characterized in WWTP
influents and effluents and in surface waters than in GW (Pal
et al., 2010; Deblonde et al., 2011; Luo et al., 2014), and very
little is known about OMPs in industrial wastewaters. WWTPs
that treat domestic (household) sewage, hospital effluents,
industrial wastewaters, as well as wastewaters from livestock
and agriculture are considered to be the main source of OMPs
to aquatic systems (Kasprzyk-Hordern et al., 2009). Most of
previous studies on GW characterization and treatment have
been limited to the assessment of conventional water quality
parameters for non-potable reuse applications. Accordingly,
the first challenge facing those who wish to treat GW to
potable water quality is to identify the chemicals which
potentially represent a threat to human health in future applications. The present study combined available data in
literature with risk characterization methods in order to
improve our understanding regarding the presence of OMPs in
GW and the risks they may pose to human health.
193
The results presented in Table S1 (supplementary data)
confirmed the presence of OMPs directly associated with
household chemicals, especially personal care products.
Several miscellaneous compounds, probably indirectly associated with household chemicals have also been identified
(e.g. brominated flame retardants, organotin compounds, and
drugs). Nevertheless, pharmaceuticals active compounds,
which have been consistently detected in hospital effluents
(Verlicchi et al., 2010) and WWTPs (Deblonde et al., 2011; Luo
et al., 2014) and raised environmental and human health
concern due to their persistency and potential in endocrine
disruption (Daughton and Ternes, 1999), were virtually not
present. Two exceptions were the pharmaceuticals acetaminophen and salicylic acid, but maximum detected levels
in GW (1.5 mg L1 and 0.6 mg L1, respectively) are about 500
(acetaminophen) and 3500 (salicylic acid) times lower than the
corresponding maximum levels reported in WWTP effluents
(Pal et al., 2010 e Table 3). As administrated pharmaceutical
compounds are excreted from the human body via feces and
urine, separate collection and treatment of GW in households
can contribute to keeping these substances away from
reclaimed (potable) water.
Table 3 compares the concentrations of some of the OMPs
compiled in the present study with maximum concentrations
reported for WWTP influents and effluents (based on recent
review papers/compiled literature data). Besides pharmaceuticals, in general, much higher loads of OMPs associated to
industrial chemicals and wastewaters are observed in WWTPs
influents (among them: bisphenol-A ¼ 11.8 mg L1; 4nonylphenol ¼ 101.6 mg L1; 4-octylphenol ¼ 8.7 mg L1;
dibutylphtalate ¼ 46.8 mg L1) when compared to GW
(bisphenol-A ¼ 1.2 mg L1; 4-nonylphenol ¼ 38 mg L1; 4octylphenol ¼ 0.16 mg L1; dibutylphtalate ¼ 3.1 mg L1),
while concentrations of personal care products are slightly
higher in GW. Intermittent contributions from agricultural
and/or livestock runoff and hospital discharges may also
cause spikes in pharmaceuticals and steroid hormones in
WWTP influents and effluents (Verlicchi et al., 2010; Sim et al.,
2011) and industrial discharges may contain organic compounds and other materials that are typically absent in GW
(e.g. aminopolycarboxylate complexing agents e Reemtsma
and Jekel, 2006). On the other hand, another important factor is rainfall. Kasprzyk-Hordern et al. (2009) found that the
concentrations of a selection of 55 OMPs in the WWTP influent
were doubled when the flow was halved during dry weather
conditions, suggesting that rainwater could dilute the concentrations of the compounds within the sewage. Therefore,
the common practice in potable reuse schemes of cotreatment of hospital, industrial, agriculture, stormwater and domestic wastewaters at a municipal WWTP (Gerrity et al., 2013)
is not a sustainable approach for reducing the risks of OMPs
because it is based on dilution of different discharges and does
not provide an adequate segregation of pollutants and, in
particular, of different classes of OMPs.
A preliminary health-based risk assessment of 89 prioritized OMP (with log D < 3) in GW was performed to determine
benchmark values. The first step was a conventional evaluation of contaminants and consisted of identifying compounds
with an established drinking water guideline or standard
value (Tier 1). The need to develop additional tiers arose
194
w a t e r r e s e a r c h 7 2 ( 2 0 1 5 ) 1 8 6 e1 9 8
Table 3 e Maximum concentrations of OMPs in GW (present study) in comparison with maximum 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., 2011; Luo et al., 2014).
Compound
Acetaminhophen
Salicylic acid
Caffeine
Benzophenone
Galaxolide
Tonalide
Triclosan
4-Nonylphenol
4-Octylphenol
Bisphenol-A
Butylbenzyl phtalate
Di-(2-ethylhexyl) phthalate
Dibutyl phthalate
Diethyl phtalate
Di-isobutyl phthalate
Dimethyl phtalate
Dimethyl phthalate
Class
GW (present study) (mg L1)
Pharmaceutical
Pharmaceutical
Food additive/stimulant
Personal care product
Personal care product
Personal care product
Personal care product
Surfactants
Surfactants
Plasticizer
Plasticizer
Plasticizer
Plasticizer
Plasticizer
Plasticizer
Plasticizer
Plasticizer
because no current guidelines exist for a majority of the
chemicals identified in this study. As the fulfilment of the
criteria for establishment of a guideline value may take place
several years after a potential contaminant is identified (WHO,
2011), an attempt was made to characterize the risks of
selected compounds with no established guidelines. There
were 39 chemicals in this study for which relevant toxicity
information (ADI, TDI, RfD, NOA(E)L) exists (Tier 2), thus
benchmark values were derived from this available information. Health authorities recommend using maximum acceptable or tolerable levels such as ADI, RfD and TDI as guidelines
for contaminants that may accumulate in the body. Since its
introduction in 1957 by the Council of Europe and later by the
Joint Expert Committee on Food Additives-JECFA (WHO, 2002),
the ADI has been proven to be a valid and practical tool in the
risk assessment and are the basis for many regulatory standards (WHO, 2011).
The remaining compounds were those without established
drinking water criteria or toxicity data (Tier 3). The benchmark
values developed in this study for compounds in Tier 3 ranged
from 0.15 to 180 mg L1. The widely accepted TTC approach
used to derive these benchmark values (Kroes et al., 2004;
Munro et al., 1996) was considered appropriately conservative and protective to human health, since it has been applied
frequently by regulatory bodies for risk assessment of substances at low dose oral exposure for which limited or no
toxicity data are present (Leeman et al., 2014; EFSA, 2012; EU,
2012). However, it should be noted that more conservative
TTC approaches than the one applied in the present study
have also been proposed. Mons et al. (2013), for example, set
TTC values for all chemicals other than genotoxic and steroid
endocrine compounds at 1.5 mg/person per day (target value in
drinking water equal to 0.1 mg L1), to achieve drinking water
of impeccable quality in line with the so-called Q21 approach.
On the other hand, the thresholds should be as accurate as
feasible and not over conservative to prevent unnecessary low
thresholds. In this respect it is noted that recently new
1.5
0.6
0.5
4.9
19.1
5.8
35.7
38
0.16
1.2
9
160
3.1
38
8
4.9
4.9
WWTPs
Influent (mg L1)
Effluent (mg L1)
56.9
63.7
209
0.9
25
1.93
23.9
101.6
8.7
11.8
37.87
122
46.8
50.7
20.48
3.32
6.49
777
2098
43.5
0.23
2.77
0.32
6.88
7.8
1.3
4.09
3.13
54
4.13
2.58
e
0.115
1.52
thresholds have been proposed above the current (accepted)
thresholds used in this study (Munro et al., 2008; Tluczkiewicz
et al., 2011; Leeman et al., 2014). These new possibilities for the
TTC approach must be further elucidated and validated by
international regulatory agencies before they can be put into
practice.
Five pesticides were assessed in the present study (2,4,6trichlorophenol,
2,4-dichlorophenol,
2,5-dichlorophenol,
malathion and pentachlorophenol). The benchmark values
derived for them in this study ranged from 1 to 120 mg L1 and
were far above the established standard (0.1 mg L1) for pesticides set by the Dutch Drinking Water Decree and the European Council Directive 98/83/EC. Although the present results
suggest that these statutory standards might be overly pragmatic and stringent, it is advisable that drinking water produced from GW complies with the pesticide mandatory target
value of 0.1 mg L1.
The calculated RQ values for the majority of OMPs were
below 1, indicating that these compounds are presumed to
present little appreciable danger to human health. However, a
few compounds (benzene; 2-ethyl-1-hexanol; benzenesulfonic acid, methyl ester; dodecanoic acid and tetracanoic
acid) had RQ values above 1, which suggests that these compounds may pose a more appreciable concern. Further investigations should focus on reducing the concentrations of
these more problematic compounds from GW by the application of advanced treatment barriers in order to reach the
target safe levels. Different wastewater treatments may be
appropriate only for some of these OMPs due to the variability
of their physico-chemical properties (e.g. hydrophobicity,
molecular weight, and chemical structure e Table S3) and
therefore, a multiple barriers treatment is advisable. In
Windhoek, for instance, direct drinking water reclamation
from wastewater has already been applied successfully for
more than 40 years based on the multiple barriers concept to
reduce associated risks and improve the water quality (du
Pisani and Menge, 2013). The treatment train consists of the
w a t e r r e s e a r c h 7 2 ( 2 0 1 5 ) 1 8 6 e1 9 8
following partial barriers for OMPs removal: pre-ozonation,
enhanced coagulation þ dissolved air flotation þ rapid sand
filtration, and subsequent ozone, biological activated carbon/
granular activated carbon.
Based on these considerations, to remove OMPs from GW
for potable reuse, a triple barrier consisting of a membrane
bioreactor (MBR, coupled with an ultrafiltration membrane),
ozone-based advanced oxidation process (AOP) and activated
carbon adsorption (AC) appears to be promising (van der Hoek
et al., 2014). MBRs are able to effectively remove a wide spectrum of OMPs that are resistant to conventional biological
processes (Tadkaew et al., 2011; Trinh et al., 2012). Ozonebased AOP and AC have demonstrated to be effective for
removing the prioritized compounds found in the present
ndez Leal et al., 2011; Lee et al.,
study (Rosal et al., 2010; Herna
nchez et al., 2014). The application of AC is also
2012; Jurado-Sa
supported by results obtained herein, which showed that 189
out of the 278 compounds detected in GW have Log D values
above 3 (high sorption), and thus are expected to be removed
by this treatment stage. In the Netherlands, this treatment
train will be tested and extensively studied in the aforementioned Green Village project at Delft University of Technology.
The clean water supply of its test laboratory site will be provided using GW and rainwater generated on site as raw water
sources by reclaiming them in a pilot scale multiple barrier
treatment concept for drinking water production.
Looking towards the future, the results presented in this
article can help researchers, water engineers and stakeholders to prioritize further investigations about the use of
GW as potable water supply.
5.
Conclusions
An extensive literature review showed that, in total, 278
OMPs have been detected in GW from 7 different sites
located in Denmark, Sweden and the Netherlands;
The study shows a practical tool to assess the health risks
of relevant OMPs by deriving benchmark values for a group
of (prioritized) compounds (log D < 3);
The preliminary health risk assessment, performed with
the aid of a three tiered approach, showed that for only a
minority of selected OMPs, established drinking water
standards are available. Benchmark values for nonregulated compounds were derived based on either toxicological available data or TTC approach;
The RQ values obtained (based on the maximum concentration levels detected in the limited available GW sources
and on calculated benchmark values) revealed that from
the toxicological point of view, the majority of assessed
chemicals would not pose appreciable human health
concern in an exposure scenario to drinking water over a
life-time period;
A group of 5 compounds with RQ value > 1 as well as 9
compounds with the RQ value between 0.2 and 1 suggest
that advanced multiple treatment barriers would be
required in future potable water reclamation plants to
reduce the concentration of these compounds to safe
levels.
195
Acknowledgements
The authors wish to thank CAPES (Brazilian institution), that
directly sponsored these doctoral studies at Delft University of
Technology (Scholarship n 8106-13-4). Special thanks to students, professors and researchers of TU Delft (Section Sanitary Engineering) and particularly, to Marisa Buyers-Basso for
her helpful comments on the manuscript and English
revision.
Appendix A. Supplementary data
Supplementary data related to this article can be found at
http://dx.doi.org/10.1016/j.watres.2014.10.048.
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