Journal of Hydrology 555 (2017) 724–735

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Journal of Hydrology
journal homepage: www.elsevier.com/locate/jhydrol

Research papers

Transport and fate of viruses in sediment and stormwater from a
Managed Aquifer Recharge site
Salini Sasidharan a,b,c,d,e,⇑, Scott A. Bradford d, Jiří Šimůnek e, Saeed Torkzaban c, Joanne Vanderzalm aa

CSIRO Land and Water, Glen Osmond, SA 5064, Australia
National Centre for Groundwater Research and Training, SA 5001, AustraliacFlinders University, Adelaide, SA 5001, AustraliadUSDA, ARS, Salinity Laboratory, Riverside, CA 92507, United Statese
Department of Environmental Sciences, University of California, Riverside, CA 92507, United Statesba r t i c l e

i n f oArticle history:
Received 16 August 2017
Received in revised form 14 October 2017
Accepted 25 October 2017
Available online 27 October 2017
This manuscript was handled by Prof. P.
Kitanidis, Editor-in-Chief, with theassistance of Martin Thullner, Associate
Editor
Keywords:
Virus
Calcium
Transport
Solid phase inactivation
Stormwater
Managed Aquifer Rechargea b s t r a c t
Enteric viruses are one of the major concerns in water reclamation and reuse at Managed Aquifer
Recharge (MAR) sites. In this study, the transport and fate of bacteriophages MS2, PRD1, and UX174 werestudied in sediment and stormwater (SW) collected from a MAR site in Parafield, Australia. Column
experiments were conducted using SW, stormwater in equilibrium with the aquifer sediment (EQ-SW),
and two pore-water velocities (1 and 5 m day1) to encompass expected behavior at the MAR site. The
aquifer sediment removed >92.3% of these viruses under all of the considered MAR conditions.
However, much greater virus removal (4.6 logs) occurred at the lower pore-water velocity and in EQSW that had a higher ionic strength and Ca2+ concentration. Virus removal was greatest for MS2, followedby PRD1, and then UX174 for a given physicochemical condition. The vast majority of the attachedviruses were irreversibly attached or inactivated on the solid phase, and injection of Milli-Q water or beef
extract at pH = 10 only mobilized a small fraction of attached viruses (<0.64%). Virus breakthrough curves(BTCs) were successfully simulated using an advective–dispersive model that accounted for rates ofattachment (katt), detachment (kdet), irreversible attachment or solid phase inactivation (ls), and blocking.
Existing MAR guidelines only consider the removal of viruses via liquid phase inactivation (ll). However,
our results indicated that katt > ls > kdet > ll, and katt was several orders of magnitude greater than ll.
Therefore, current microbial risk assessment methods in the MAR guideline may be overly conservativein some instances. Interestingly, virus BTCs exhibited blocking behavior and the calculated solid surface
area that contributed to the attachment was very small. Additional research is therefore warranted to
study the potential influence of blocking on virus transport and potential implications for MAR
guidelines.
Ó 2017 Elsevier B.V. All rights reserved.

1. Introduction
The availability of high-quality drinking water has decreased
due to climate variability and population growth, while demandhas increased to meet agricultural, industrial, environmental, andmunicipal water needs (Levantesi et al., 2010; Shannon et al.,2008; Yates et al., 1987). The United Nations has estimated thatabout 1.8 billion people around the globe will face severe water
stress and scarcity by 2025 (UN, 2013). Consequently, there is anurgent need to find alternative sources of freshwater, such as bydeveloping economic and effective water reclamation, recycling,
and preservation techniques (Levantesi et al., 2010; Shannon⇑ Corresponding author at: USDA, ARS, Salinity Laboratory, Riverside, CA 92507,
United States.
E-mail address: salinis@ucr.edu (S. Sasidharan).
https://doi.org/10.1016/j.jhydrol.2017.10.062
0022-1694/Ó 2017 Elsevier B.V. All rights reserved.

et al., 2008; Yates et al., 1987). Water recycling can be achievedby various engineering techniques and natural or passive treatment. Major water recycling techniques employ multiple barrier
approaches, including secondary treatment, riverbank filtration,
reverse osmosis, UV disinfection, chlorination, and ultrafiltration(Page et al., 2010a). However, many countries across the world
do not have access to cheap and efficient wastewater treatment
plants (Vega et al., 2003). Managed Aquifer Recharge (MAR) is acollection of natural treatment techniques, including Aquifer Storage, Transfer, and Recovery (ASTR) or Aquifer Storage and Recovery(ASR), that has gained a lot of attention recently (Ayuso-Gabella
et al., 2011; Bekele et al., 2014, 2013, 2011; Stevens, 2014; Toze
and Bekele, 2009; Ward and Dillon, 2009). Water recycling is facilitated during MAR by purposefully recharging lower quality water
into aquifers for natural treatment prior to recovery (Dillon et al.,2009; Page et al., 2010a). Currently, MAR is considered as an effec-

S. Sasidharan et al. / Journal of Hydrology 555 (2017) 724–735

tive and economical option to store water in the treatment train;e.g., a sequence of multiple stormwater treatments, which aredesigned to meet the needs of a particular environment, in orderto maximize results (MelbourneWater, 2017). MAR provides a natural buffer, increases public perception, provides a residence timethat can facilitate removal of biodegradable organic matter andpathogens, improves the quality of the treated wastewater orstormwater, and reduces the cost of seasonal peak demands(Dillon et al., 2009; Levantesi et al., 2010; Page et al., 2010a;
Page et al., 2010c). However, current MAR guidelines require
expensive and energy-intensive pre-treatment of injected waterand post-treatment of recovered water depending on the end
use, with drinking water supply requiring the highest level oftreatment (Dillon et al., 2009).
One of the major concerns with potable water reuse is the
microbiological quality of recovered water and the possibility oftransmitting infectious diseases from pathogenic microorganisms(virus, bacteria, and protozoa) that are not eliminated by conventional wastewater treatment (Costán-Longares et al., 2008;
Levantesi et al., 2010; Shannon et al., 2008). Enteric viruses posethe greatest public health concern because they can travel long distances (Schijven and Hassanizadeh, 2000) and are infectious atvery low doses (Ward et al., 1986). MAR systems can improvethe microbiological quality of water by natural attenuation processes during soil filtration and/or aquifer transport (Asano et al.,2007; Dillon et al., 2008; Levantesi et al., 2010; Mayotte et al.,2017). For example, inactivation occurs when viruses lose theirability to infect host cells and replicate because of the disruptionof proteins and the degradation of nucleic acid (Gerba, 1984;
Schijven et al., 2003). The most important factors affecting virus
inactivation rate include temperature, groundwater microbialactivity, pH, salt species and concentration, some forms of organic
matter, and virus type (McCarthy and McKay, 2004; Schijven and
Hassanizadeh, 2000). However, decay rates for human entericviruses, determined using diffusion chambers in monitoring wells
at MAR sites, have been found to be slow and nonlinear (Sidhu
et al., 2015; Sidhu and Toze, 2012). Quantitative microbial risk
assessment calculations for MAR systems have been developed
from a detailed hydrogeological assessment of the aquifer and insitu decay studies (Donald et al., 2011; Page et al., 2010b, 2015a;
Toze et al., 2010). These risk assessment studies considered thatliquid phase virus inactivation was the only reliable mechanism
for virus removal in the aquifer, and neglected the processes ofvirus attachment, detachment, and solid phase inactivation (AbuAshour et al. (1994); Dillon et al., 2008).
In addition to liquid phase inactivation, virus removal fromgroundwater may occur by attachment from the bulk solution to
the solid phase (Shen et al., 2012a,b), whereas detachment refers
to the reverse process of virus release from the solid phase to thebulk solution (Bergendahl and Grasso, 2000). Virus attachment toaquifer materials is a strong function of many physicochemicalvariables, including pore-water velocity (Hijnen et al., 2005); solution ionic strength (IS) (Da Silva et al., 2011; Knappett et al., 2008;
Xu et al., 2005); solution ionic composition (Bales et al., 1991;
Lipson and Stotzky, 1983; Sadeghi et al., 2013; Sasidharan et al.,2014; Walshe et al., 2010); and the presence of humic materials(Zhuang and Jin, 2003), and metal oxides (Foppen et al., 2006).
Consequently, an accurate assessment of virus attachment at
MAR sites must consider realistic solution chemistries and aquifer
mineralogy. In contrast, most virus transport studies have been
conducted under highly idealized conditions using clean sand or
glass beads, and simple electrolyte solutions.
Attachment during MAR can only serve as an effective,
long-term treatment when viruses are irreversibly retained orinactivated on the solid phase. It is difficult to separately quantify
the processes of irreversible attachment and solid phase inactiva-

725

tion because they both decrease the number of infective viruses
that can detach from the solid phase (Ryan et al., 2002). Consequently, much less is known about solid than liquid phase inactivation (Murray and Laband, 1979; Ryan et al., 2002). Solid phaseinactivation has been reported to increase with the strength of
the adhesive interaction and the temperature (Loveland et al.,
1996; Murray and Laband, 1979; Ryan et al., 2002). Yates et al.
(1985) found that the inactivation rate of MS2 in eleven groundwater samples increased with the Ca2+ concentration. However, lowlevels of virus detachment have been commonly observed understeady-state physicochemical conditions (Bales et al., 1993). Furthermore, changes in solution chemistry (e.g., a decrease in IS oran increase in pH) have been observed to produce large pulses of
released colloids (Bales et al., 1993). Consequently, there is a concern that attached viruses can be remobilized with a decrease in IS
or divalent cation concentrations during rainfall events (Gerba,
1983; Yates et al., 1988).
The main objective of this work was to systematically examine virus removal processes in urban stormwater from a wetland(Urrbrae, South Australia) when in contact with aquifer sedimentcollected from an ASTR site (Parafield Gardens, South Australia).
Three bacteriophages (PRD1, MS2, and UX174) were used as surrogate viruses for enteric human viruses. Laboratory scale virustransport experiments and inactivation studies were conducted.
Additional studies investigated the release of attached viruses
by sequentially injecting step pulses of solutions with alternating
solution chemistry. Virus breakthrough curves (BTCs) were simulated using the numerical solution of the advection–dispersion
equation with terms for attachment, detachment, Langmuirian
blocking, and a sink term that accounted for irreversible attachment and solid phase inactivation. Model parameters wereobtained by inverse fitting to the observed BTCs. Results fromthis study provide valuable insight on the relative importanceof natural attenuation processes for viruses at MAR sites andindicate that microbial risk assessments that only consider
liquid phase inactivation may be overly conservative in someinstances.
2. Materials and methods
2.1. Stormwater
Stormwater (SW) samples were collected from the Urrbrae
Wetland located in Mitcham, South Australia (Fig. S1). The wetlands were constructed to collect urban stormwater for flood protection in the nearby area and for potential future use in MAR
operations (Lin et al., 2006). The stormwater chemistry (major
and minor elements) was analyzed using an Inductively Coupled
Plasma Mass Spectrometry (ICP-MS) and the carbon content wasmeasured using Varo TOC Cube (Analytical Chemistry, CSIRO, Adelaide). The pH and electrical conductivity (EC) were measured
using a Eutech PC 700 (Eutech Instruments).
Dissolved calcium is a weathering product of almost all rocks
and is, consequently, abundant in most groundwater sources.
Water from limestone aquifers may contain 30–100 mg L1 of calcium, gypsiferous shale aquifers may contain several hundred milligrams per liter (Sadeghi et al., 2013), and dolomite produces
water with high levels of calcium and magnesium (Wade, 1992).
The calcium concentrations range from 0.03 to 36.5 mg L1 in Australian groundwaters (Radke et al., 1998). When water percolates
through soils, the concentration of divalent cations in soil solutions
often increases with depth along the vertical weathering-leaching
gradient (Sadeghi et al., 2013; Sverdrup and Warfvinge, 1993). It is,therefore, logical to anticipate that the solution IS and divalentcation concentration will increase with a travel distance and residence time during ASTR, due to mineral dissolution, along with

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mixing in aquifers containing groundwater of higher salinity. In alimestone aquifer, increases in calcium are prevalent due to thedissolution of calcium carbonate. This increase in solution IS andCa2+ concentration may increase virus attachment. Virus transportand survival experiments were therefore also conducted using
stormwater after it was equilibrated with the aquifer sediment(50 g of sediment with 200 mL of stormwater), denoted as EQSW. Table S1 provides a summary of selected chemical properties
for EQ-SW.
2.2. Porous media
Aquifer materials were collected from an ASTR site situated in
Parafield Gardens, Adelaide, Australia (Fig. S1) established forstormwater storage and treatment (Page et al., 2015b). The target
aquifer for ASTR is the lower Tertiary marine sediments of the Port
Willunga Formation (T2 aquifer), a well-cemented sandy limestone
aquifer which is intersected between 149 and 214 m Australian
Height Datum (AHD) (160–220 m below ground surface). At thislocation, the target aquifer is approximately 60 m thick and overlain
by 7 m thick clay aquitard of Munno Para Clay which prevents the
migration of injected stormwater to the overlying aquifers. A schematic cross-section of the aquifer is given in Fig. S2. Karstic features
were not identified during construction of the site (Vanderzalm
et al., 2010). The mineralogy in the storage zone is dominated bycalcite (65 ± 23%), quartz (30 ± 22%), and a trace amount of ankerite,
goethite, hematite, pyrite, albite, and microcline (Vanderzalm et al.,2010). Goethite and hematite largely account for the 2.1% Fe2O3
quantified by X-ray Fluorescence (XRF). The transmissivity of theaquifer ranges from 100 to >200 m2 d1, depending on the silt content and degree of weathering (Miotliński et al., 2014). Considerable
variability exists in hydraulic conductivity within the aquifer and,
therefore, the ASTR was constructed with partially penetratingwells to avoid the zone of high hydraulic conductivity in the lower
part of the aquifer and to exclude excessive mixing between native
groundwater and injection water (Miotliński et al., 2014). The aquifer is low in organic carbon (<0.5%) and has an average cationexchange capacity of 1.5 meq/100 g (Page et al., 2010b). The aquifer
has a temperature of 25 °C at ambient conditions. The design, operation, hydraulic, chemical, and physical properties of this aquifer
has been extensively studied and reported in the literature(Adkinson et al., 2008; Dillon et al., 2008; Kremer et al., 2008;
Page et al., 2010b; Pavelic et al., 2004; Rinck-Pfeiffer et al., 2005;
Vanderzalm et al., 2010). The aquifer material used in this study
was obtained from intact core samples taken at a depth of 171.30
m below the ground surface. The collected aquifer sediments weredirectly used in the experiments without any further treatment.
Selected physical and chemical properties of the sediment are provided in Table S2. The bulk mineralogy of the sediment sample wasdetermined by X-ray Diffraction (XRD). The major elemental composition was determined by XRF and Inductively Coupled Plasma
Optical Emission Spectrometry (ICP-OES) following reverse aquaregia acid digest. Sieve analysis was used to determine the particle
size distribution.
Additional transport experiments were conducted using ultrapure clean quartz sand (Charles B. Chrystal CO., Inc., NY, USA) withsize ranging from 125 to 300 lm. This sand was cleaned using anacid wash and boiling procedure described by Sasidharan et al.
(2014). Transport experiments with the ultra-pure quartz sandrepresent a worst-case scenario for virus transport because of minimal chemical heterogeneity.
2.3. Viruses
Bacteriophage MS2, PRD1, and UX174 were used as model
viruses in this study. These microbes were chosen because of theirstructural resemblance to many human enteric viruses and they
have been used in numerous investigations as surrogates forhuman enteric viruses (Chu et al., 2003; Schijven and
Hassanizadeh, 2000). It should be mentioned that recent studies
have demonstrated that the transport and fate of human entericviruses may not always be well correlated with that of bacteriophages (Bellou et al., 2015). Additional research is, therefore, warranted to identify the best surrogate for the transport and fate ofpathogenic viruses, but this issue is beyond the scope of the present study. The bacteriophages were analyzed using their respective Escherichia coli host. The production of bacteriophages andtheir analysis using double layer agar (DLA) methods were detailedin Sasidharan et al. (2016). Stock solutions of viruses were diluted
in stormwater to obtain an initial concentration (C0) of 5  106
plaque forming unit mL1. The survival of viruses over a 7 h interval was determined in both SW and EQ-SW solutions.
2.4. Zeta potential and size measurements
The electrophoretic mobility (EM) of viruses, crushed aquifer
sediment, and quartz (<2 lm) was measured in both SW and EQSW using a Zetasizer (Malvern, Zetasizer Nano Series, Nano-ZS).
The EM measurements were repeated five times with more thantwenty runs per measurement. The Smoluchowski equation(Elimelech et al., 1994) was used to convert the measured EM values to zeta potentials. The size distribution of viruses in both SW
and EQ-SW was measured using a dynamic light scattering (DLS)(Malvern Instruments Ltd, 2004; Sikora et al., 2016) process (Malvern, Zetasizer Nano Series, Nano-ZS).
2.5. Transport experiments
The column experiments were set up in a constant temperaturelaboratory (20 °C). Sterilized polycarbonate columns (1.9 cm inside
diameter and 11 cm height) were wet packed using aquifer material or ultra-pure quartz sand while the column was being vibrated.
After packing, the column was preconditioned with >10 pore volumes (PV) of stormwater water using a syringe pump (Model 22,
Harvard Apparatus) at a flow rate of 0.394 mL min1. A suspension
with known C0 of viruses (PRD1, MS2, and UX174) and solution
chemistry (SW or EQ-SW) was introduced into the column usinga syringe pump at a constant pore water velocity (1 or 5 m day1)
for 13 PV (Phase I), followed by injection of 7 PV of virus-freesolution at the same solution chemistry and velocity (Phase II).
To study the reversibility of attached viruses, the experiments
were continued by flushing the columns with 11 PV of Milli-Q
water (Phase III), followed by injection of 3% Beef Extract with
pH = 10 (Phase IV). Virus release is enhanced in Milli-Q water bya reduction in solution IS which expands the double layer thickness, and increases the magnitude of the sediment and virus zeta
potentials (Chen et al., 2014; Sasidharan et al., 2017b). Beef extract
is a mixture of peptides, amino acids, nucleotide fractions, organic
acids, minerals, and some vitamins, with a pH of 10 and its injection further enhances the virus release by masking positively
charged sites with organic matter, and reversing the charge ofsome pH dependent sites (Landry et al., 1978; McMinn, 2013).
Effluent samples were collected using a fraction collector (CF-2,
Spectrum, USA). The effluent concentrations (C) of viruses wereenumerated using the methods described above. Separate column
experiments were run for each porous medium (aquifer sedimentor ultra-pure quartz sand), solution chemistry (SW or EQ-SW),and pore-water velocity (1 or 5 m day1) combination.
Breakthrough curves (BTCs) were plotted as a dimensionlessconcentration (C/C0) of viruses as a function of PVs. A mass balance
was conducted for the viruses in the column experiments using
information on injected and recovered viruses during Phases I–

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IV. The percentage of virus mass retained on the solid phase (Ms)was determined as the difference in the mass of injected virus
and mass of virus recovered in the effluent BTC (MBTC = MI + MII)
during Phases I and II. The percentage of injected viruses thatwas recovered during Phases III and IV were denoted as MIII and
MIV, respectively. The percentage of injected viruses that were irreversibly retained (Mirr) was determined as 100-MBTC-MIII-MIV. The
log removal of the viruses in the column effluent experiments wasdetermined as log10(MBTC).

2.6. Simulation of virus BTCs
Experimental BTCs for viruses were simulated using the
HYDRUS-1D model (Šimůnek et al., 2016). The HYDRUS-1D program numerically solves the Richards’ equation for variably saturated water flow and Fickian-based advection–dispersion
equations for heat and solute transport. The governing
continuum-scale flow and transport equations are solved numerically using Galerkin-type linear finite element schemes (Šimůnek
et al., 2016). The following aqueous and solid phase mass balance
equations were considered in this model for each virus.

@C
@2C
@C
q
¼ kv 2  v
 katt wC  kdet b S  ll C
@t
@z
@z
h

qb @S
h @t

¼ katt wC  kdetqbhS  ls

qb
h

S

ð1Þ

ð2Þ

where t (T; T denotes unit of time) is time, z (L; L denotes units oflength) is the direction of mean water flow, C (NL3; N denotes
the virus number) is the aqueous phase virus concentration, k (L)is the dispersivity, v (LT1) is the average pore water velocity, qb(ML3; M denotes the unit of mass) is the bulk density, h is thewater content, S (NM1) is the solid phase concentrations of virus,
katt (T1) is the virus attachment rate coefficient, kdet (T1) is thevirus detachment rate coefficient, and ls (T1) is a sink term which
accounts for irreversible attachment and inactivation of viruses
attached on the solid phase, and ll (T1) is the inactivation rate
coefficient for viruses in the liquid phase. The parameter w is adimensionless Langmuirian blocking function that is given as(Adamczyk et al., 1994)



S
w¼ 1
Smax

ð3Þ

where Smax (NM1) is the maximum solid phase concentrations ofretained virus.
The fraction of the solid surface area that is available for retention (Sf) was calculated from Smax as (Kim et al., 2009; Sasidharan
et al., 2014):

Sf ¼

Ac qb Smax
ð1  cÞAs

ð4Þ

where Ac (L2N1) is the cross sectional area of a virus, As (L1) is thesolid surface geometric area per unit volume, and c is the porosityof a monolayer packing of viruses on the solid surface that was
taken from the literature to be 0.5 (Johnson and Elimelech, 1995).
The value of the sticking efficiency (a) was determined from thefitted katt value and the filtration theory as (Schijven and
Hassanizadeh, 2000; Yao et al., 1971):

a¼

2dc katt
3ð1  nÞv gcalculated using the correlation equation presented by (Messina
et al., 2015).
3. Results and discussion
3.1. Characterization of solution chemistry
SW had a pH of 7 and EC of 260 lS cm1 and after equilibration
with the aquifer sediment the pH and EC of the EQ-SW increased to
7.3 and 2230 mS cm1, respectively (Table S1). In addition, the concentration of all major ions also increased in EQ-SW, notably, with
7 times increase in Ca and K, and 11 times increase in Na concentration. Therefore, the ionic strength of the EQ-SW (0.014 mM)
increased 10 times compared to SW (0.002 mM). This increase in
pH and EC of EQ-SW compared to SW was attributed to the dissolution of limestone in the aquifer sediment (Table S2) that leaches
CaCO3 and increases the solution pH (Earle, 2013; Panthi, 2003).
The measured concentration value of Ca2+ in EQ-SW (151 mg L1,
Table S1) was very close to Ca2+ (135 ± 5 mg L1) in ambient
groundwater from the T2 aquifer (Page et al., 2010b) and, therefore, it confirms that the solution chemistry of the EQ-SW was representative of the target aquifer.
3.2. Characterization of aquifer sediment
The average particle size of the sediment was 110 lm, with
93.5% within the 20–200 lm size fraction (Table S2) and only
6.5% in smaller or larger size fractions. The quantitative bulk mineralogy of the sediment in Table S2 showed that the aquifer material was made of quartz (58.1%), calcite (35.0%), and goethite(2.2%). Major element analysis (Table S2) indicates the presenceof a large fraction of SiO2 (53.4%), Al2O3 (1.2%), Fe2O3 (3.5%), and
CaO (19.6%). Acid digest data (Table S2) revealed the presence ofother major ions such as K, Mg, and Na in the sediment. These
results demonstrated that the sediment was rich in major metaloxides such as CaO, MgO, Fe2O3, and Al2O3, as well as minerals suchas quartz and clays. The metal oxide surfaces are positively charged
and the mineral surfaces are negatively charged at the experimental pH (7.3) due to surface chemical reactions with H+/OH ions,
respectively (Tombácz, 2009). Consequently, the aquifer sedimentsurface is expected to be chemically heterogeneous and possess a
distribution of negative and positive surface charges. It has beenshown that minor degrees of positive charge heterogeneity on
the collector surface result in attachment rates that are an orderof magnitude larger than similar surfaces having no charge heterogeneity (Schijven and Hassanizadeh, 2000).
Table 1 shows that the crushed aquifer sediment and quartz
were negatively charged in the presence of SW and EQ-SW. We
assume that some of the positively charged surfaces were masked

Table 1
The measured zeta potential values of viruses and sediment and the measured valuesof the size of viruses in stormwater (SW) and stormwater equilibrated with aquifer
sediment (EQ-SW).
Virus

Solution

f+
[mV]

Size
[nm]

MS2

SW
EQ-SW
SW
EQ-SW
SW
EQ-SW
SW
EQ-SW
SW
EQ-SW

22.4 ± 1.2
12.6 ± 1.1
23.8 ± 1.2
13.7 ± 0.9
23.3 ± 1.4
14.8 ± 1.3
19.8 ± 0.8
16.2 ± 1.5
31.5 ± 2.8
27.2 ± 1.3

27.6 ± 3.4
28.3 ± 3.3
29.6 ± 2.6
30.0 ± 2.9
69.0 ± 0.82
68.3 ± 2.5
–
–
–
–

UX174
PRD1

ð5Þ

where n is the porosity (0.4) and dc (L) is the collector (mediangrain) diameter. The value of the single collector-efficiency, g, was

Sediment
Quartz728

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by negatively charged P, Dissolved Organic Carbon (DOC), and Dissolved Inorganic Carbon (DIC) present in the SW (Table S1), which
will lead to a reduction in the overall surface potential and a net
negative zeta potential value for the sediment (fsand )(Karageorgiou et al., 2007). Furthermore, the presence of SiO2
and clays will significantly decrease the value of fsand (Chen et al.,2014). Consequently, the zeta potential for quartz was lower than
the aquifer sediment (Table 1). Table 1 also indicates that the zeta
potential for the aquifer sediment and quartz was more negatively
charged in the presence of SW than EQ-SW. This could be
explained by an increase in EC, divalent cation (Ca2+ and Mg2+)
concentration, and IS by more than 8 times in EQ-SW comparedto SW, and the compression of the electrostatic double layer(Elimelech, 1994). Increased Ca2+ concentration can also lead tocharge reversal (Lipson and Stotzky, 1983; Moore et al., 1981;
Redman et al., 1999; Roy and Dzombak, 1996) and charge neutralization (Bales et al., 1991).
3.3. Characterization of viruses
The average size of MS2, UX174, and PRD1 was measured to be
27.6–28.3 nm, 29.6–30.0 nm, and 68.0–69.0 nm, respectively.
These values are within 3–5 nm of previously reported values(Chrysikopoulos and Aravantinou, 2012; Sasidharan et al., 2016;
Thomson, 2005), and this indicates that aggregation of theseviruses was negligible under our experimental solution chemistry
conditions. Table 1 shows the measured zeta potential values ofviruses in SW and EQ-SW. The absolute value of the zeta potential
for these viruses was always negative, but smaller in magnitude in
the presence of EQ-SW compared to SW. Similar to the sediment,
this can be explained by an increase in IS, compression of the double layer, and higher Ca2+ concentration for EQ-SW. In addition,
Ca2+ is expected to bind to the carboxyl functional groups on theviral protein capsid which reduces the negative surface charge
density (Harvey and Ryan, 2004).
3.4. Virus retention under various physicochemical conditions
Fig. 1 shows observed and fitted BTCs for the viruses under various solution chemistry (SW and EQ-SW) and pore-water velocity(1 and 5 m day1) conditions. The normalized effluent concentrations C/C0 (where C0 is the influent and C is the effluent virus concentration) were plotted as a function of pore volumes. Table 2
presents experimental mass balance (MBTC, Ms, MIII, MIV, and Mirr)
information. This data is summarized in Fig. 2 which presents
bar plots of the log removal (e.g., log10(MBTC)) of viruses under
different physicochemical conditions. The value of Ms = 26.2% isin the worst-case transport scenario using clean quartz sand and
SW at 5 m day1 (Fig. S3). In contrast, values of Ms in the aquifer
sediment were always much higher (>92.3%) than this control

Fig. 1. The observed breakthrough concentrations of viruses (A) UX174, (B) MS2, and (C) PRD1 at Phase I (injection of virus in SW or EQ-SW) and the observed effluent
concentration in Phase II (injection of virus-free SW or EQ-SW). The Phases I and II were conducted at pore water velocity of 1 or 5 m day1 using either stormwater (SW) or
stormwater equilibrated in the aquifer sediment (EQ-SW). Here, the markers are observed data and the solid black line is the fitted model.

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S. Sasidharan et al. / Journal of Hydrology 555 (2017) 724–735

Table 2
Experimental conditions and mass balance information from the column experiments. Here, MBTC, Ms = 100  MBTC, Mirr = (100  MBTC  MIII  MIV), MIII, and MIV denote thepercentage of the injection MS2, PRD1, and UX174 viruses that was recovered in the breakthrough curve, retained on the solid phase, irreversibly retained on the solid phasefollowing the completion of Phases I–IV, and recovered with the injection of Milli-Q water in Phase III and Beef extract with pH 10 in Phase IV, respectively.
Bacteriophage

UX174

Velocity[m d1]

1
5

MS2

1
5

PRD1

1
5

Solution Chemistry

Retention

Release

MBTC

Ms

Mirr

MIII

MIV

[%]

[%]

[%]

[%]

[%]

SW
SW EQ
SW
SW EQ

0.98
0.00
7.70
0.35

99.02
100.00
92.30
99.65

98.37
99.94
91.86
99.40

0.14
0.01
0.06
0.01

0.50
0.04
0.38
0.24

SW
SW EQ
SW
SW EQ

0.04
0.00
1.32
0.01

99.96
100.00
98.68
99.99

99.94
100.00
98.67
99.98

0.01
0.0001
0.002
0.002

0.01
0.001
0.006
0.009

SW
SW EQ
SW
SW EQ

0.09
0.00
2.51
0.01

99.91
100.00
97.49
99.99

99.87
100.00
97.46
99.97

0.02
0.0002
0.01
0.001

0.02
0.00040.02
0.01

experiment. The maximum retention for all three viruses wasobserved in the experiment conducted under EQ-SW at 1 m day1(>4.6 logs), whereas the least retention was observed under SW at
5 m day1 (Ms = 92.3%). A detailed discussion of the dependence ofvirus retention on water velocity, solution chemistry, and virus
type is given below.
Fig. 2 indicates that all three viruses always had a higher
removal in EQ-SW than SW at a given velocity. Table S1 indicatesthat the IS and concentration of Ca2+ were much higher for
EQ-SW than SW. This increase in IS and concentration of Ca2+ lowered the magnitude of the zeta potential of the sediment andviruses (Table 1) in EQ-SW and thereby increased the adhesiveinteraction between the sediment and viruses. Consequently, one
key consideration in the determination of virus removal is theeffect of ionic strength and the presence of multivalent cations(Harvey and Ryan, 2004). The effects of multivalent cations onvirus attachment can be attributed to a number of factors, including the larger ionic radius of Ca2+ (1.61 Å) compared to Na+ (1.02 Å)(Gutierrez et al., 2010), change in electrostatic interactions
between virus and mineral surfaces (Carlson et al. (1968)), cation
bridging (Bales et al., 1991; Chu et al., 2003; Pham et al., 2009),
charge neutralization (Bales et al., 1991; Lukasik et al., 2000),
screening of repulsive surface interaction energies between virus
and grain surfaces (McCarthy and McKay, 2004), reduction of the
net charge within the electrokinetic shear plane (Simoni et al.,2000), compression of the double-layer (Huysman and
Verstraete, 1993), inner sphere complexation of the cations atthe virus surfaces (Sadeghi et al., 2013), and the calcium binding
to the carboxyl functional groups on the viral protein capsid(Harvey and Ryan, 2004).
Greater removal of viruses occurred at a lower (1 m day1) thanhigher (5 m day1) pore-water velocity under given solution chemistry conditions (Fig. 2). Previous studies have similarly demonstrated that the retention of colloids such as viruses,
nanoparticles, and bacteria in porous media is velocity dependent(Hendry et al., 1999; Kim and Lee, 2014; Sasidharan et al., 2017a,
2014; Toloni et al., 2014; Torkzaban et al., 2007). Greater retentionof viruses at low flow velocity can be explained by: (i) an increasein the virus residence time (Meinders et al., 1994; Xu et al., 2005);(ii) an increase in the virus adhesive interaction (Xu and Logan,2006); and (iii) a decrease in the applied hydrodynamic torque thatacts on the virus (Bradford et al., 2011; Sasidharan et al., 2017a). It
should be mentioned that an increase in residence time increases

the time for virus removal. It also increases the probability thatviruses can diffuse over shallow energy barriers on physicallyand chemically heterogeneous surfaces. Consequently, virus
removal at a MAR site will be influenced by the flow field, with lessremoval near the injection well. Careful consideration of the flow
field and separation distance between the injection and recovery
wells is therefore necessary to achieve the maximum virus
removal.
PRD1 is generally considered as the most conservative modelfor enteric viruses in subsurface viral transport studies (Harvey
and Ryan, 2004; Schijven and Hassanizadeh, 2000; Stevenson
et al., 2015). In contrast, Fig. 2 indicates that MS2 had the highest
removal followed by PRD1 and then by UX174 for a given physicochemical condition. Consequently, UX174 was the most conservative model virus (had the least removal) in our sediment andstormwater. It is commonly believed that the removal and interactions of viruses with a solid surface are the results of their electricalcharge and hydrophobicity (Shields and Farrah, 1987). Table 1
shows that the measured zeta potential values for all three virusesin each solution chemistry were in the same range, so differencesin the net zeta potential of the viruses cannot explain these variations in retention. Both PRD1 and MS2 are known to be partiallyhydrophobic and UX174 is hydrophilic in nature (Sasidharan
et al., 2016; Schijven and Hassanizadeh, 2000). The presence ofsome forms of hydrophobic organic matter in the solution(Table S1) and the sediment surface may enhance the hydrophobic
interaction between the partially hydrophobic viruses (PRD1 andMS2), which lead to their higher retention. In addition, nanoscalechemical and especially physical heterogeneity on the surfaces ofcolloids are known to strongly influence their adhesive interaction(Attinti et al., 2010; Bradford et al., 2017). The viral protein coat
may contain weakly acidic and basic amino acid groups which
act as localized positive and negative charges (Gerba, 1984) andit has a span of hydrophobic amino acids which will determine
the hydrophobicity of viruses (Bendersky and Davis, 2011;
Bradford and Torkzaban, 2012; Shen, et al., 2012d). The virus surface also contains nanoscale roughness features such as spikes(Huiskonen et al., 2007). Additional research is needed to fully
characterize nanoscale variations in chemical heterogeneity androughness features on the surfaces of our viruses and to assess
the influence of these factors on virus retention. Considerable
experimental and theoretical research would be needed to address
this issue, and it is beyond the scope of this applied study.

730

S. Sasidharan et al. / Journal of Hydrology 555 (2017) 724–735

Fig. 2. Bar plots of the log removal (e.g., log10(MBTC)) of viruses under the different physicochemical conditions shown Fig. 1.

3.5. Mathematical modeling of virus retention
Table 3 shows the liquid phase inactivation rate (ll) for virusesover the course of the transport and release experiments. The valueof ll was negligible (107 s1) in both SW or EQ-SW, and wasconsequently neglected in the mathematical model. A number ofdifferent model formulations were employed to describe the virus
BTCs. However, low values of the Pearson correlation coefficient(R2) and nonunique parameter estimates were obtained in many
instances. The best model description (R2 ranged from 67 to 98%)
was obtained when considering attachment, detachment, blocking,and a solid phase sink term that accounted for irreversible attachment and inactivation. Straining, clogging, and wedging were notconsidered as important mechanisms for virus retention in thisstudy, as the ratio of virus to a sediment grain diameter is far below
the suggested threshold of 0.003 (Bradford and Bettahar, 2006).
Table 4 presents fitted model (katt, kdet, Smax/C0, and ls) or calculated (a, g, and Sf) parameters, and the R2 for the goodness of model
fit.
Blocking decreases the attachment rate coefficient as available
retention sites become filled, and has typically been neglected inmost previous virus transport studies (Schijven and
Hassanizadeh, 2000). However, Fig. 1 (BTC is plotted in log scale)and Fig. S4 (BTC is plotted in normal scale) indicate that blocking
occurred for our viruses and sediment. In particular, BTCs were initially delayed (arriving after 1 PV), next they rapidly increased, andthen slowly approached the influent virus concentration. Consistent with our observations, Xu et al. (2017) observed blocking
Table 3The inactivation rate coefficients (ll) of MS2, PRD1, and UX174 in the stormwater(SW) and stormwater equilibrated with aquifer sediment (EQ-SW) for the experiment
duration (4500 min = 75 h) and the Pearson correlation coefficient (R2) value calculated using linear regression analysis.
Solution

ll

[s1]

R2
[%]

UX174

SW
EQ-SW

8.33  107
6.67  107

99.63
90.98

MS2

SW
EQ-SW

5.00  107
3.33  107

95.37
100

PRD1

SW
EQ-SW

1.17  107
1.00  107

99.78
100

behavior for UX174 on a goethite-coated sand. Many others havereported on similar blocking behavior for nanoparticles (Li et al.,2008; Sasidharan et al., 2014; Virkutyte et al., 2014).
Fitted values of Smax in the blocking model were subsequently
used to determine Sf (Table 4). Calculated values of Sf for theviruses were very small (1.30  108–1.45  104). Similarly, Xu
et al. (2017) reported small values of Sf (0.3  106–0.5  106)for UX174 on a goethite-coated sand. In contrast, values of Sf for
50 and 100 nm latex nanoparticles were much higher on clean
quartz sand (0.009–0.39) (Sasidharan et al., 2017b, 2014). Naturalsolid surfaces like sand grains always contain a wide distributionof physical (e.g., roughness) or chemical (e.g., metal oxides) heterogeneities (Bhattacharjee et al., 1998; Shen et al., 2012c). Previous
studies have demonstrated that roughness height and fraction,and positive zeta potential and fraction, at a specific location on
the collector (sand) surface can significantly reduce the magnitudeof the energy barrier to attachment and the depth of the primary
minimum for viruses (Bradford et al., 2017; Bradford and
Torkzaban, 2013, 2015; Sasidharan et al., 2017b; Torkzaban and
Bradford, 2016). In contrast to smooth latex nanoparticles, thevirus exhibits chemical (e.g., lipid membrane and protein coat)(Meder et al., 2013) and physical heterogeneity (e.g., spikes andtail) (Huiskonen et al., 2007; Kazumori, 1981) on their surface.
The combination of physical and chemical heterogeneities on bothvirus and collector surfaces apparently created a shallow primary
minimum with negligible energy barrier to attachment anddetachment for viruses, and thus, only a very small fraction of
the collector surface contributed to Sf.
Previous research has shown that the relative effluent concentration increased and the relative retention decreased withincreasing input concentration of colloids as a result of blocking(Leij et al., 2015; Wang et al., 2012). All three viruses were run in
the same experiment and had a total input concentration of
4.9  108 viruses in this study. Conversely, urban stormwater
has a much lower enterovirus concentration of 6–170 virus/10 L(Strassler et al., 1999). Consequently, blocking and the subsequent
exhaustion of retention sites may not be apparent in some natural
systems with low input concentrations. However, recharging
stormwater with a high concentration of some forms of organic
matter or negatively charged phosphate ions (Table S1) can mask
and reverse the charge of positive sites that are favorable for virus
retention (Schijven and Hassanizadeh, 2000). This competition for0.203
0.203
0.081
0.081
0.001
0.002
0.005
0.013
4.01  108
5.54  108
1.30  108
2.71  108
0.22
0.31
0.003
0.12
2.24
2.17
7.27  101
1.06
2.5  104
3.4  104
1.4  104
8.6  104
1.92  1054.85  105
1.86  104
3.11  104
2.2  104
8.9  105
2.3  103
1.7  102
2.4  103
6.1  103
5.8  103
1.9  101

the same retention sites and Smax could potentially cause blocking
to be enhanced.
Colloid filtration theory (CFT) has been developed to predict thevalue of katt under different physicochemical conditions (Yao et al.,1971). CFT considers that katt is proportional to the product of aand g that account for adhesion and mass transfer, respectively.
Consistent with CFT predictions, the value of katt (Table 4)
increased with increasing fluid velocity at a given solution chemistry. Similar to Fig. 2, values of katt for MS2 and UX174 werealways higher for EQ-SW than SW at a given water velocity. However, values of katt for PRD1 were nearly the same for EQ-SW and
SW. The observed dependence of katt on the solution chemistry
and the virus type was likely complicated by blocking which
reduced the apparent value of katt. Both a and Sf are strong functions of the interaction energy between the virus and sediment(Shen et al., 2010; Tufenkji and Elimelech, 2004), so it may not
be possible to separately quantify these effects especially when Sf
is very low.
The virus BTCs shown in Fig. 1 exhibited low levels of concentration tailing when the columns were eluted with virus-free SW
or EQ-SW. The model did not provide an accurate description ofthis tailing region when kdet was considered and ls was neglected.
Conversely, a good fit was obtained to both the retention and thetailing portion of the BTCs when ls and kdet (Table 4) were includedin the model. Little is known about solid phase inactivation ofviruses other than the need for a strong binding force which may
disintegrate the protein structure and thereby inhibit the abilityof viruses to infect their host (Harvey and Ryan, 2004). Only a
few approaches have been developed to separately quantify therates of virus attachment and solid phase inactivation (Grant
et al., 1993; Harvey and Ryan, 2004) such as radiolabeling polio
virus capsid and RNA to track the fate of these components(Murray and Parks, 1980). These approaches are difficult, time consuming, and/or require specialized equipment. In this research,these technical challenges were partially overcome throughnumerical modeling that allows the determination of attachment(katt) and detachment (kdet) rates, and a sink term to account forthe combined rate of irreversible attachment and solid phase inactivation (ls).
Guidelines for MAR have only considered inactivation of virusesin the liquid phase, but have neglected irreversible attachment andsolid phase inactivation of viruses (Abu-Ashour et al. (1994); Dillon
et al., 2008). Tables 3 and 4 indicate that katt > ls > kdet > ll, and katt
is 3–4 orders of magnitude higher than ll. Consequently, guidelines for MAR that only consider liquid phase inactivation will beoverly conservative for the considered experimental conditions.
Recognizing the removal of viruses via irreversible attachment
and/or solid phase inactivation during aquifer storage would help
to eliminate some of the expensive post-treatment for recovered
MAR water. However, we acknowledge that the virus removal via
irreversible attachment and/or solid phase inactivation is highlysite specific. Therefore, conducting site specific microbial risk
assessment and subsequent development of appropriate MAR
design that considers adequate residence time and travel distancebased on the horizontal and vertical flow field, soil heterogeneity,and chemical characterization is necessary to achieve the maximum virus removal.

5

96.17
96.84
93.55
97.11

5

1

1.18  103
2.86  103
1.08  102
3.06  102

8.09  106
4.14  106
1.25  104
1.08  103

0.127
0.127
0.048
0.048
0.007
0.006
0.011
0.01
2.74  106
1.45  1042.58  106
9.62  105
0.13
0.75
0.007
0.21
7.77  101
2.31  101
7.32  101
1.53  101
8.9  104
1.9  104
1.7  103
8.9  1045.93  105
2.11  105
1.87  1044.89  105
3.2  103
6.2  105
8.4  105
3.2  104
5.8  102
2.4  103
6.3  102
1.2  102
79.63
93.53
98.60
96.51

5

1

4.86  1034.00  103
1.52  102
1.21  102

4.81  1053.93  106
3.95  106
2.43  105

0.211
0.211
0.085
0.085
0.162
0.213
0.145
0.356
1.72  1062.01  105
9.12  107
3.99  106
0.35
0.19
0.45
0.58
2.11
2.49  101
1.12
4.94
2.7  104
1.2  103
3.2  103
7.6  104
1.94  105
3.99  1052.32  104
7.14  105
7.8  105
7.6  104
1.5  105
1.6  104
9.6  103
1.4  103
6.1  102
1.7  102
94.28
67.37
96.81
97.21
1

3.25  103
4.26  1035.80  103
1.43  1022.83  106
1.08  1052.65  106
1.63  105ga
Sf
S.E.Coeff  Smax/C0
Smax/C0(cm3 gr1)
S.E.Coeff  ms
ms(s1)
S.E.Coeff  kdet
kdet
(s1)
S.E.Coeff  katt
katt
(s1)
R2
(%)
Velocity(m day1)

731

Solution

SW
EQ-SW
SW
EQ-SW

SW
EQ-SW
SW
EQ-SW

SW
EQ-SW
SW
EQ-SW

MS2

PRD1

UX174

3.6. Release of virus

Virus

Table 4
A summary of experimental conditions (solution chemistry and water velocity), model parameters that were fitted to the virus BTCs (the attachment coefficient, katt ; the detachment coefficient, kdet ; the maximum solid phase virus
concentration, SCmax; and a sink term that accounts for irreversible attachment and solid phase inactivation, ls ) and parameters Sf, a, and g which were calculated from SCmax, katt , and the correlation equation of Messina et al. (2015),
00respectively. The table also includes the Pearson correlation coefficient (R2) for the goodness of model fit, and the standard error values (S.E.Coeff) on fitted parameters.

S. Sasidharan et al. / Journal of Hydrology 555 (2017) 724–735

Fig. 3 shows plots of UX174, MS2, and PRD1concentrations in
the column effluent during Phases III and IV when Milli-Q waterand 3% beef extract with pH = 10 were injected into the column,
respectively. Small pulses of released viruses were observed during
both phases, with a small peak followed by long concentration tailing. Table 2 summarizes mass balance information from Phases III

732

S. Sasidharan et al. / Journal of Hydrology 555 (2017) 724–735

Fig. 3. Observed effluent concentrations of viruses (A) UX174, (B) MS2, and (C) PRD1 in Phase III (Milli-Q water) and IV (3% beef extract with pH 10) at a pore-water velocityof 1 and 5 m day1.

and IV. Only a very small percentage (<0.5%) of the initiallyattached viruses were released even under the worst-case scenario
of beef extract with pH = 10.
Table 2 shows the mass of viruses on the sediment surface
that was not recovered after the release Phases III and IV(Mirr = 100  MBTC  MIII  MIV). The negligible release of viruses
and the presence of large Mirr > 91% indicate that the viruses were
irreversibly attached or inactivated on the solid surface. Values ofMirr followed similar trends to Ms with physicochemical conditions.
In particular, Mirr was higher for EQ-SW than SW for a given velocity, Mirr was higher at lower (1 m day1) than higher (5 m day1)
pore-water velocity at a given chemistry, and Mirr was highest forMS2 followed by PRD1 and then UX174. The presence of a large
Ms and Mirr value for the EQ-SW experiment implies that viruses
will irreversibly attach and/or inactivate on the solid before thewater reaches the recovery well during an ASTR operation, provided that a sufficient residence time is achieved. An injection
event will only release a very tiny fraction of the viruses which
may mobilize and re-attach to the surface as the water equilibrates
with the sandy limestone aquifer sediment and the IS and the divalent cation concentration increases. Therefore, during ASR operations the chance of releasing the attached viruses during thereverse flow is negligible. However, we assume that the ASTR operation has added advantage of long residence time and travel distance compared to ASR and, therefore, ASTR would be the best
option when removal of viruses via attachment/solid phase inactivation is considered.

4. Conclusions and future directions
This research was conducted to better understand and quantify
the relative importance of various virus removal processes during
MAR in a sandy limestone aquifer. The aquifer sediment was found
to remove >92.3% of bacteriophage MS2, PRD1, and UX174 from
SW and EQ-SW when the pore-water velocity was 1 or 5 m day1.
However, much greater virus removal (4.6 logs) occurred at thelower pore-water velocity and in EQ-SW because of an increase
in residence time, IS, and Ca2+ concentration. Bacteriophage
UX174 showed less removal than either PRD1 or especially MS2,
and was, therefore, the most conservative model virus for this site.
Negligible virus detachment (<0.64%) occurred when columns
were flushed with Milli-Q water or beef extract at pH = 10, and thisindicates that viruses were irreversibly attached or quickly inactivated on sediment surfaces.
Virus BTCs were successfully simulated using the advection–
dispersion equation with terms for attachment, detachment, Langmuirian blocking, and solid phase removal by irreversible attachment
and/or surface inactivation. Values of katt > ls > kdet > ll, and kattwas 3–4 orders of magnitude greater than ll. The value of kdet
was always small under steady-state physicochemical conditions.
The remaining viruses on the solid phase were either irreversibly
retained or inactivated. This process was modeled using the ls
term. Blocking has commonly been neglected in previous virustransport studies. In contrast, our results clearly demonstrated
blocking behavior. The relative importance of blocking is expected

S. Sasidharan et al. / Journal of Hydrology 555 (2017) 724–735

to decrease in a natural setting with lower input concentrations
and/or higher Smax (Leij et al., 2015). Furthermore, the value of Sf
was found to be very small for viruses. This result was attributed
to the presence of a shallow primary minimum due to roughness
on both the virus and sediment surfaces. Additional research isneeded to further assess the potential influence of blocking on
virus transport at MAR sites.
MAR has only been considered as a storage option in a water
recycling train. Consequently, all previous field scale studies for
MAR risk assessments have only considered virus removal by liquid
phase inactivation. Current MAR guidelines do not acknowledge theremoval of viruses by attachment and solid phase inactivation. This
research clearly demonstrated that viruses were irreversiblyattached or inactivated on the sediment surface when given enoughresidence time and that katt  ll. Natural treatment of injectedwater during infiltration through the unsaturated zone is widely
recognized. However, the mechanisms for natural treatment ofvirus within the saturated zone is not well understood and theselection of a sub-section of aquifer material with lower carbonate
content/higher quartz content represents an environment that isless favorable for virus removal (worst-case scenario). Furthermore,
greater virus removal is expected as water moves away from aninjection well due to a decrease in water velocity and an increasein IS and Ca2+ ions. However, field-scale experiments under actual
artificial recharge conditions, using the same bacteriophages
employed in this study, showed that the safe setback distancedepended on site-specific physicochemical conditions. For example,
the setback distance was estimated to be just a few meters (10 m)
in a sandy aquifer in Los Angeles County (Anders andChrysikopoulos, 2005), whereas the reported setback distance was8000 ± 4800 m in a fractured aquifer in Southern Italy(Masciopinto et al., 2008). Future MAR guidelines and microbial risk
assessment may therefore need to consider site specific removal ofviruses by irreversible attachment and solid phase inactivation during the storage period. This could help to eliminate some of theexpensive post-treatment to achieve desired water quality.
Notes
The authors declare no competing financial interest.
Acknowledgements
Funding for this research was provided by the National Centre
for Groundwater Research and Training (Ph.D. Research Scholarship awarded to S. Sasidharan, 2012–2016), an Australian Government initiative, supported by the Australian Research Council(ARC) and the National Water Commission (NWC). The project
was completed in collaboration with CSIRO Land and Water program and the Flinders University of South Australia. The work
was conducted in the CSIRO Laboratories at the Waite Campus,
Adelaide, South Australia. We acknowledge Ms. Karen Barry(CSIRO, Adelaide) and Mr. John Gouzos (Analytical services unit,
CSIRO, Adelaide) for providing assistance in the sediment mineralogy and stormwater chemistry analysis.
Appendix A. Supplementary data
Supplementary data associated with this article can be found, inthe online version, at https://doi.org/10.1016/j.jhydrol.2017.10.
062.
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