In situ disinfection of sewage contaminated shallow groundwater: A feasibility study

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In situ disinfection of sewage contaminated shallow groundwater: A feasibility study Morgan M. Bailey a, William J. Cooper b, Stanley B. Grant a,b,* a

Department of Chemical Engineering and Material Sciences, University of California, Henry Samueli School of Engineering, University of California, Irvine, CA 92697, USA b Department of Civil and Environmental Engineering, and Urban Water Research Center, Henry Samueli School of Engineering, University of California, Irvine, CA 92697, USA

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abstract

Article history:

Sewage-contaminated shallow groundwater is a potential cause of beach closures and

Received 18 June 2011

water quality impairment in marine coastal communities. In this study we set out to

Received in revised form

evaluate the feasibility of several strategies for disinfecting sewage-contaminated shallow

9 August 2011

groundwater before it reaches the coastline. The disinfection rates of Escherichia coli (EC)

Accepted 14 August 2011

and enterococci bacteria (ENT) were measured in mixtures of raw sewage and brackish

Available online 22 August 2011

shallow groundwater collected from a coastal community in southern California. Different disinfection strategies were explored, ranging from benign (aeration alone, and aeration

Keywords:

with addition of brine) to aggressive (chemical disinfectants peracetic acid (PAA) or per-

Disinfection

oxymonosulfate (Oxone)). Aeration alone and aeration with brine did not significantly

Shallow groundwater

reduce the concentration of EC and ENT after 6 h of exposure, while 4e5 mg L
1 of PAA or

Sewage

Oxone achieved >3 log reduction after 15 min of exposure. Oxone disinfection was more

Remediation

rapid at higher salinities, most likely due to the formation of secondary oxidants (e.g.,

Water quality

bromine and chlorine) that make this disinfectant inappropriate for marine applications.

Peroxymonosulfate

Using a Lagrangian modeling framework, we identify several factors that could influence

Peracetic acid

the performance of in-situ disinfection with PAA, including the potential for bacterial

Oxone

regrowth, and the non-linear dependence of disinfection rate upon the residence time of

Brine

water in the shallow groundwater. The data and analysis presented in this paper provide a framework for evaluating the feasibility of in-situ disinfection of shallow groundwater, and elucidate several topics that warrant further investigation. ª 2011 Elsevier Ltd. All rights reserved.

1.

Introduction

Beach closures and advisories are generally caused by the coastal discharge of land-side sources of fecal pollution such as urban runoff or sewage effluent (Boehm et al., 2002; Grant and Sanders, 2010). However, contamination of shallow groundwater by aging sewage collection systems and failing onsite sewage treatment and disposal systems has also been

identified as a source of fecal pollution at some coastal beaches (Lipp et al., 2001). The latter typically involves a two-step process: (1) shallow groundwater is first contaminated by the surface or subsurface release of sewage, and (2) the shallow groundwater is then discharged to coastal waters under the influence of land hydraulic gradients, tidal pumping, and/or current induced pressure gradients (Burnett et al., 2003b). The coastal discharge of sewage-contaminated shallow

* Corresponding author. Tel.: þ1 949 824 8277; fax: þ1 949 824 2541. E-mail addresses: [email protected] (M.M. Bailey), [email protected] (S.B. Grant). 0043-1354/$ e see front matter ª 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.watres.2011.08.020

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groundwater can impact near-shore water quality by vectoring fecal-oral pathogens (or their indicators) directly from sources of human sewage to receiving waters (Boehm et al., 2003). The discharge may also deliver nutrients that promote the survival, and perhaps growth, of fecal bacteria in near-shore waters (Boehm et al., 2004). To date, most studies on shallow groundwater discharge focus on its quantification using isotopic (McIlvin and Altabet, 2005), geophysical (Manheim et al., 2004; Santos et al., 2008; Swarzenski et al., 2006), or hydrological methods (Burnett et al., 2003a; Michael et al., 2005; Taniguchi et al., 2002), but to our knowledge there are no published reports on the very practical and important question of how to remediate shallow groundwater once it becomes contaminated with sewage. Given the advancing age and poor condition of sewage collection systems and onsite sewage treatment and disposal systems in many coastal areas of the U.S. (Food and Water Watch, 2008), a cost-effective strategy for remediating sewage-derived fecal pollution in brackish shallow groundwater is urgently needed for the sustainable use of coastal beaches and bays. While the best remediation strategy should always be to identify and eliminate the source(s) of sewage responsible for groundwater contamination, logistical and economic constraints may make such action infeasible in the near term, in which case interim solutions are needed. Further, even if a source of sewage contamination is identified and repaired, it may take some time before pathogens and indicator bacteria decay to acceptable concentrations, particularly when the sediments in question are subsurface and thus not exposed to sunlight (Mika et al., 2009). Subsurface injection of disinfectant (or “in-situ disinfection”) is one obvious interim strategy for remediating sewage-contaminated shallow groundwater, but several issues need to be resolved before such an approach can be implemented in practice. (1) Disinfectants can react with organic matter and/or trace anions (e.g., bromide and chloride ions) in brackish coastal groundwater to produce toxic disinfection by-products, and their discharge to coastal zones could pose a health risk to bathers along the shoreline and negatively impact sensitive marine ecosystems (Monarca et al., 2000). (2) The shallow groundwater adjacent to marine coastal areas can be thought of as “subterranean estuaries”, in which fresh (meteoric) waters mix with seawater before discharging to the ocean (Moore, 1999). Consequently, the flow in shallow groundwater can vary substantially in space and time, potentially affecting the disinfection contact times water parcels experience before discharging to coastal waters. (3) Sewage constituents, such as pathogens and their indicators, may not mix fully over the vertical dimension of the shallow groundwater, and therefore disinfection strategies may need to be tailored to target sewage constituents where they are located, for example near the top of the water table. (4) Planning and implementation of in-situ disinfection would greatly benefit from quantitative “design criteria” that account for the rate at which the target organisms decay with time upon exposure to disinfectant, the decay in disinfectant with time, the time scale over which water parcels reside in the shallow groundwater before discharge, and ecological processes that promote the subsurface regrowth of fecal bacteria.

In this paper we present laboratory data and modeling efforts intended to, at least preliminarily, address the issues raised above, using as a test case Avalon Bay, Catalina Island, California, where chronic fecal contamination of near-shore waters has been linked to sewage contamination of shallow groundwater by leaking sewage collection systems beneath the City (Boehm et al., 2003, 2009b). The goals of this study are to: (1) test three strategies for inactivating sewage-associated fecal bacteria from shallow groundwater, including aeration alone, aeration with addition of brine, and aeration with addition of either peracetic acid (PAA) or peroxymonosulfate (commercially known as Oxone); (2) characterize the salinity dependence and disinfection by-product formation potential of the latter two disinfectants; (3) evaluate several models for PAA disinfection; and (4) develop a Lagrangian modeling framework for evaluating, and potentially designing, in-situ disinfection of sewage-contaminated coastal shallow ground waters.

2.

Materials and methods

2.1.

Choice of disinfectant

Bench-scale experiments were carried out to measure the decay of sewage-associated fecal indicator bacteria in shallow groundwater upon exposure to: (1) aeration alone, (2) aeration with addition of brine, (3) aeration with addition of PAA (35% solution, CAS-79-21-0, Pfaltz & Bauer, CT), and (4) aeration with addition of Oxone (43% dry weight, CAS-37222-66-5, Alfa Aesar, Ward Hill, MA). The impact of aeration on bacterial dieoff was evaluated on the premise that, if efficacious, injection of ambient air into the subsurface would be a straightforward, economical, and environmentally benign approach for remediating sewage-contaminated shallow groundwater. The choice of brine as a candidate disinfectant was motivated by the fact that its injection into shallow groundwater is unlikely to cause environmental harm, and because the field site under consideration, Avalon Bay, has a desalination plant from which brine is produced as a waste product. PAA is a promising disinfectant for this application, because it produces little or no toxic disinfection by-products when mixed with seawater (it degrades into acetic acid, vinegar) (Kitis, 2004), is a strong biocide in marine waters as evidenced by its use as an antifouling agent in cooling water systems for coastal power plants, and is regarded as relatively safe for discharge to sensitive marine waters (Sanchez-Ruiz et al., 1995) including the highly regulated Italian Lagoon of Venice (Cristiani, 2005). To our knowledge, Oxone has not been tested as a biocide in coastal marine settings, but its application to this particular problem was motivated by the fact that, upon addition to water, it generates hydroxyl radicals and sulfate ions (Anipsitakis and Dionysiou, 2003); the former should accelerate the die-off of bacteria and viruses while the latter is already present at high concentrations in marine waters. Many commonly used disinfectants (e.g., ozone, chlorine gas, sodium hypochlorite) were excluded from consideration for logistical reasons and, although highly effective biocides, they would likely react with trace anions and organics in sewagecontaminated brackish groundwater to form toxic

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disinfection by-products (Abarnou and Miossec, 1992; Allonier et al., 1999).

2.2.

Experimental characterization of disinfection kinetics

Raw (untreated) sewage was diluted 1:100 using various mixtures (with various final salinities) of three source waters: (1) relatively fresh (salinity ca. 1) water from an inland groundwater well, (2) Avalon Bay water (salinity ca. 32), and (3) desalination plant brine (salinity ca. 45). All source waters were aseptically collected from the City of Avalon using sterile polypropylene bottles and mixed with raw sewage collected from influent to the City of Avalon wastewater treatment plant. Source waters were not sterilized prior to mixing with sewage, and therefore bacteria populations present in the final mixtures of sewage and source waters probably included (minor) contributions from the latter. Bench-scale disinfection experiments commenced within 6 h of sample collection and were carried out in 4 L Nalgene polypropylene reaction vessels maintained in the dark and partially submerged in a temperature controlled and recirculating water bath at 15  1  C. Contents of the reactor vessel were continuously aerated using a frit through which ambient air was driven by an aquarium pump. To capture a range of salinities and disinfectant concentrations, a matrix design was adopted in which over 45 separate disinfection experiments (including 10 no-disinfectant-added control experiments) were conducted at five different disinfectant concentrations (ranging from 0 to 7.3 mg L
1 for Oxone, and 0e8 mg L
1 for PAA) and four different salinities (0, 15, 32, 45). The concentration range adopted for PAA was based on previously published studies with this disinfectant (Kitis, 2004; Santoro et al., 2007). To our knowledge, this is the first study to evaluate Oxone disinfection in saline mixtures, and thus the concentration range adopted for this disinfectant was based on pilot studies (not reported) with this disinfectant. Each batch reactor was sampled seven times over a period of 1e6 h (depending on experiment). This sampling schedule was chosen to resolve disinfection over a single ebb tide, which represents a theoretical minimum time a fluid parcel would be in contact with disinfectant before discharging to Avalon Bay, assuming that the discharge of shallow groundwater was under tidal control. Samples were extracted from the reactor using either a sterile syringe or pipet, analyzed for pH and conductivity, quenched by addition of approximately 0.4 mL of 0.1 N sodium thiosulfate (CAS-7772-98-7, Mallinckrodt Chemicals), immediately diluted either 1:10 or 1:100 in sterile deionized water (Hardy Scientific, California), and enumerated for Escherichia coli (EC) and enterococci bacteria (ENT) using Colilert-18 and Enterolert defined substrate tests implemented in a 97-Well Quanti-Tray format (IDEXX Laboratories, Maine). The adoption of IDEXX Colilert-18 and Enterolert was motivated based on the fact that both tests are approved by the U.S. Environmental Protection Agency for enumerating EC and ENT bacteria in ambient waters (USEPA, 2003) and, more to the point, are used by the Los Angeles Department of Health Services in their routine monitoring of recreational beach water quality in Avalon Bay, and as a basis for management decisions regarding, for example, the posting of Avalon beaches as unfit for swimming. For a subset of the disinfection experiments, dissolved organic carbon (DOC) and total organic carbon (TOC) concentrations were measured: (1) on the source water (groundwater or

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bay water) prior to addition of sewage and disinfectant; (2) on the source water plus sewage prior to the addition of disinfectant; and (3) at the end of the disinfection experiment. Samples analyzed for DOC and TOC were collected in 500 mL amber glass bottles and acidified with 2 mL of hydrochloric acid, and then analyzed by TestAmerica using Standard Method 5310B.

2.3.

Disinfection rate constants

Two different disinfection rate constants are reported in this study: (1) an effective first-order disinfection rate constant k0d , and (2) an intrinsic disinfection rate constant kd. Values of the effective first-order rate constant k0d were estimated by regressing log-transformed bacteria concentration against time based on Chick’s Law (Chick, 1908): NðtÞ ¼
k0d t ln N0

(1)

In Eq. (1), N(t) represents the concentration of bacteria in the reaction vessel at any time t and N0 represents the bacterial concentration present in the mixture at the start of the disinfection experiment. The regression excluded any bacterial measurements in the initial lag period and bacterial measurements that fell below the lower-limit of detection for the Colilert and Enterolert assays (in most cases, the lower limit of detection was 10 most probable number (MPN) per 100 mL of sample). In the case of PAA disinfection, an intrinsic disinfection rate constant was also calculated, which represents the susceptibility of bacteria to disinfectant independent of disinfectant concentration: kd ¼ k0d =C0

(2)

The variable C0 represents the initial (molar) concentration of peroxycompounds which, in the case of commercial preparations of PAA, includes both PAA and hydrogen peroxide (Wagner et al., 2002).

2.4.

Activation energy for PAA disinfection

Using the reactor set-up described above, four separate disinfection experiments were carried out at five temperatures (T ¼ 5, 10, 15, 20 and 30  C) and a fixed concentration of PAA (6 mg L
1) to determine the temperature sensitivity of EC and ENT disinfection by PAA. Intrinsic disinfection rate constants kd calculated from these experiments (see Section 2.3) were used to determine activation energies for the PAA disinfection of EC and ENT, based on an Arrhenius plot of ln(kd) against 1/T.

3.

Disinfection results and discussion

3.1.

Measurements of pH, TOC, and DOC

Over aeration of the reactor vessel caused the pH to increase slightly from 7.9  0.2 to 8.3  0.2. No other systematic pH trends were observed across the different experiments and different source waters tested. The average DOC concentration in groundwater ranged from 1.6  0.14 mg L
1 (N ¼ 7,

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foreshore well, salinity 20) to 2.9  0.2 mg L
1 (N ¼ 4, inland well, salinity 1). The TOC/DOC ratio was near unity in water collected from the inland well (1.1 0.1, N ¼ 4) implying that most of the organic carbon was dissolved. Raw sewage collected from the Avalon Sewage Treatment Plant had much higher levels of DOC (25 mg L
1, N ¼ 1). However, sewage contributed only background levels of DOC (<0.25 mg L
1) to the final 1:100 mixtures of sewage and source waters used in the disinfection experiments. For disinfection experiments carried out with PAA, the largest source of DOC was frequently the PAA solution itself, which contained upwards of 280 mg L
1 of carbon as acetic acid. The acetic acid was present as an equilibrium component of the commercial PAA preparation, and generated as a breakdown product of PAA.

3.2. Experimental characterization of disinfection kinetics First-order effective disinfection coefficients ðk0d Þ estimated from the 45 separate disinfection experiments are contoured using Delaunay triangulation (Igor Pro v 6.10, Lake Oswego, Oregon) against disinfectant concentration and salinity in Fig. 1. These results are described in the sections below. A more detailed analysis of k0d values, and an evaluation of different disinfection models, is presented later in the paper (Section 4).

3.2.1.

Aeration alone and aeration with addition of brine

We started by evaluating two environmental benign approaches for removing fecal indicator bacteria from sewagecontaminated shallow groundwater; namely, injection of ambient air and/or injection of brine produced from a local

desalination plant. Aeration alone and aeration with brine did not significantly reduce EC and ENT concentrations after 6 h of exposure; i.e., within the resolution of these experiments k0d ¼ 0. Thus these two strategies are unlikely to be effective against indicator bacteria in shallow groundwater over the time scale of a single ebb tide.

3.2.2.

Aeration with addition of PAA and oxone

EC and ENT concentrations were reduced by more than 1000 fold (3 log units) after 15 min of exposure to 4e5 mg L
1 of PAA. The effective disinfection rate constants calculated for these experiments (Fig. 1A and B): (1) increased monotonically with
1 PAA dose up to the maximum rate ðk0d ¼ 0:2 min Þ resolvable with our experimental set-up; (2) do not depend, at least not dramatically, on the salinity of the disinfection mixture; and (3) are larger for EC than ENT at a fixed PAA dose. The last observation is consistent with the results reported in Stampi et al. (2002). Averaged across all experiments (and excluding any experiments where the effective disinfection rate constant exceeded 0.2 min
1), the average intrinsic rate ¼ 2:3  0:57 and constants for PAA disinfection are kENT d
1
1 EC kEC d ¼ 3:7  0:2 mM min : The estimate for kd is similar to intrinsic rate constants estimated from previously published data for PAA disinfection of EC in secondary settled effluent (Dell’Erba et al., 2004) and PAA disinfection of fecal coliform (FC) in secondary-treated sewage effluent (Wagner et al., 2002) (Table 1). The fact that the intrinsic rate constants for PAA disinfection of EC and FC are similar across these three studies is notable, given that EC is a subset of FC, and the very different initial bacterial concentrations (and presumably sewage content) associated with the different source waters

Fig. 1 e Contour plots of the effective first-order rate constants k0d [minL1] for PAA disinfection of EC (panel A) or ENT (panel B), and Oxone disinfection of EC (panel C) or ENT (panel D).

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Table 1 e Intrinsic disinfection rates and parameters from multiple studies. Value kd (mM
1 min
1)a

Source FC

EC

%H2 O2=%PAAb

Temp ( C)

N0 c

Solutiond

GW, BW, Br, TPI TPE TPE

ENT

This study

NA

3.7  0.2

2.3  0.57

0.183

15

104

Dell’Erba et al. Wagner et al.

NA 1.04  1.26

3.65  2.41 NA

NA NA

1.53 1.54

NR NR

102 105

NR-not reported. NA-not applicable. a Intrinsic disinfection rate. b Ratio of percent mass of PAA and hydrogen peroxide in PAA equilibrium solution. c Magnitude of initial bacteria concentration. d Sources waters for disinfection studies (GW-groundwater, BW-way water, Br-brine, TPI-treatment plant influent, TPE-treatment plant effluent).

used in these studies, ranging from 102 to 105 bacteria per 100 mL (Table 1). EC and ENT concentrations were reduced by more than 3 log units after 15 min of exposure to 4 mg L
1 Oxone. However, unlike PAA, the disinfection rate depends on both Oxone dose and solution salinity (Fig. 1C and D). At low Oxone dose (<2 mg L
1), the effective disinfection rate increases monotonically with Oxone dose, and exhibits no obvious salinity dependence (i.e., the contour lines are near vertical in this region of the plot). At higher Oxone dose, the effective disinfection rate increased monotonically with salinity, and exhibits no obvious dose dependence (i.e., the contour lines were near horizontal in this region of the plot). One possible explanation for this pattern is that Oxone may oxidize anions in the shallow groundwater and brine to yield, for example, the secondary oxidants chlorine and bromine. To explore this idea, a set of control experiments were carried out in which either PAA or Oxone was added to an aqueous solution consisting of 35 g L
1 NaCl to mimic the background salinity of seawater and varying concentrations

(0e70 mg L
1) of KBr to mimic the presence of trace anions. The formation of oxidized forms of chloride and bromide ions (e.g., chlorine and bromine) was monitored by measuring absorbance of the indicator dye N,N-diethyl-p-phenylenediamine (DPD) (Standard Methods, 4500-CL G). Fig. 2A shows DPD spectra measured after addition of 10 mg L
1 of either Oxone (solid lines) or PAA (dashed lines) to distilled water (Solution 1), an aqueous solution consisting of 35 g L
1 NaCl (Solution 2), or an aqueous solution consisting of 35 g L
1 NaCl and 70 mg L
1 KBr (Solution 3). In this set of experiments, the disinfectant was allowed to react in the solution for 5 min, whereupon DPD was added, and 1 min later the DPD absorbance spectrum was measured. Referring to Fig. 2A, the absorbance of DPD increased in the order Solution 1 < Solution 2 < Solution 3, consistent with the idea that Oxone oxidizes both chloride and bromide ions to form secondary oxidants. DPD absorbance did not increase when PAA was allowed to react for 5 min in Solution 2 and increased only slightly when PAA was allowed to react for 5 min in Solution 3. These latter results are consistent with the findings

Fig. 2 e Panel A: DPD absorbance spectra measured after 10 mg LL1 of either Oxone (solid lines) or PAA (dashed lines) is allowed to react for 5 min in: Solution 1 (DI water), Solution 2 (DI water and 35 g LL1 NaCl), or Solution 3 (DI water, 35 g LL1 NaCl, and 70 mg LL1 KBr). Panel B: DPD absorbance at 515 nm after 10 mg LL1 of either Oxone (solid lines) or PAA (dashed lines) are allowed to react for 5 min in Solution 2 with KBr concentrations shown. Panel C: the kinetics of oxidant formation by 10 mg LL1 of either Oxone (solid line) or PAA (dashed line) in Solution 3.

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of Booth and Lester (1995), who report that PAA could not oxidize chloride ion to hypochlorous acid, but could oxidize bromide ion to hypobromous acid. In the presence of Oxone, DPD absorbance increased with increasing KBr concentration in Solution 2 (Fig. 1B), and the oxidation kinetics in Solution 3 are relatively rapidly (<5 min of exposure time, Fig. 1C). In the presence of PAA, on the other hand, DPD absorbance increased only slightly with increasing KBr concentration in Solution 2 (Fig. 2B), and oxidization kinetics in Solution 3 are relatively slow (>150 min exposure time) (Fig. 2C). Collectively, the results presented above are consistent with the idea that Oxone quickly oxidized trace anions in brackish shallow groundwater to form secondary oxidants that act synergistically with Oxone to enhance disinfection rates. However, the reaction of Oxone with trace anions could also increase the toxicity of the shallow groundwater, by producing compounds that are carcinogenic (e.g., bromateion) and/or by producing secondary oxidants (e.g., bromine and chlorine) that subsequently react with organic compounds to form toxic disinfection by-products (e.g., trihalomethanes) (Guo and Lin, 2009). For these reasons, and despite its obvious utility as a disinfectant, Oxone should not be used for in-situ disinfection of sewage contaminated shallow groundwater in settings, like Avalon Bay, where the groundwater is under marine influence. PAA, on the other hand, does not appear to react strongly with chloride ion, or quickly with bromide ion, and thus is less likely to produce toxic disinfection by-products; a conclusion supported by several published studies (Liberti et al., 1999; Dell’Erba et al., 2007; Kitis, 2004). Although PAA does not appear to generate the quantity and spectrum of disinfection by-products associated with many disinfectants, some researchers have raised concern about the potential environmental impact of releasing disinfected effluents that contain a PAA residual (Antonelli et al., 2009; de Lafontaine et al., 2008), which can be toxic to crustaceans and microorganisms (Antonelli et al., 2009; de Lafontaine et al., 2008). However, Lafontaine et al. (2008) note that, because PAA breaks down rapidly in seawater, any potential impacts would be localized around the region where disinfection residual is discharged to the environment. Thus, if PAA is used for in-situ disinfection of sewage contaminated shallow groundwater, care should be taken to minimize the PAA residual discharged to coastal waters.

3.3.

Activation energy for PAA disinfection

Based on measurement of intrinsic disinfection rates over a range of temperatures, from 5 to 30  C, the following activation energies were estimated for PAA disinfection of EC and ENT: 37.5  7.8 kJ mol
1 and 38.0  9.3 kJ mol
1, respectively. These activation energies are used later in the paper to estimate intrinsic disinfection rates for PAA over a range of temperatures relevant to the shallow groundwater in Avalon Bay (see Section 5.1).

4.

Modeling PAA disinfection kinetics

Of the strategies evaluated above, PAA disinfection appears the most viable, given that it is both a potent biocide and less likely to form toxic disinfection by-products. In this section we

evaluate several published models for PAA disinfection, all of which are special cases of Hom’s Law (Hom, 1972): dN ¼
kd Ntm Cn dt

(3)

where, N, C, kd, and t represent bacterial concentration, disinfectant concentration, intrinsic disinfection rate constant, and time, respectively. Chick’s Law (Eqs. (1) And (2) of this paper) corresponds to a choice of exponent values m ¼ 0, n ¼ 1, and a constant disinfectant concentration, C ¼ C0. Wagner et al. (2002) suggested that, during the disinfection process, the concentration of peroxycompounds in commercial PAA mixtures decays with time in accordance with the following second-order rate law: dC ¼
k C2 dt

(4)

The rate constant k* depends on the initial peroxycompound concentration C0 (Wagner et al., 2002): k ¼ aC
b 0

(5)

Where the pre-factor and power-law exponents are given by a ¼ 0.0093 mM(b
1) min
1 and b ¼ 1.420. In their analysis of PAA disinfection, Santoro et al. (2007) suggest that peroxycompounds exhibit zero-order decay; however, zero-order decay models predict negative concentration in finite time, and therefore will not be considered further here. Combining Eqs. (4) and (5), and solving the differential equation, yields the following prediction for disinfectant concentration as a function of time: CðtÞ ¼

1 1=C0 þ k t

(6)

Given this time-dependence for the disinfectant concentration, Hom’s Law becomes: dN
n ¼
kd Ntm ½1=C0 þ k t dt

(7)

Wagner et al. (2002) solved Eq. (7) for two different choices of the exponents n and m: (1) n ¼ 1 and m ¼ 0 (no-tailing model), and (2) n ¼ 1 and m ¼
1 (tailing model). The tailing model provided a better empirical fit to the PAA disinfection data, although their intrinsic disinfection rate constant kd varied with the initial disinfectant concentration, and a new fitting parameter (the time t at which N(t) ¼ N0) was introduced. Here we opt for the more parsimonious no-tailing model, for which an exact solution can be derived:
kd =k

N ¼ N0 ðk C0 t þ 1Þ

(8)

PAA disinfection data collected in this study were tested against Chick’s Model (Eq. (1)) and the no-tailing model (Eq. (8)) in Fig. 3. The data are plotted so that the intrinsic disinfection rate constant kd can be estimated directly from the slope b of the best-fit line: kd ¼ 2.303b (Chick’s Law) or kd ¼ b (no-tailing model). Also shown in Fig. 3 are two estimates of model performance, including the Pearson’s r2 correlation between logN/N0 and the x-axis (either C0t or log½k C0 t þ 1=k ), and the root mean square error (RMSE) between modeled and measured values of bacterial log reduction. In general, for a given choice of fecal bacteria group (either ENT or EC) the

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Fig. 3 e PAA disinfection data for EC (panel A and B) and ENT (panel C and D) fit to either Chick’s model (Eq. (1), panel A and C) or Wagner et al.’s no-tailing model (Eq. (8), panel B and D). Values for kd are mML1 minL1 and units for RMSE are logN/N0.

two disinfection models have similar r2 and RMSE values (compare panels A and C with panels B and D in Fig. 3). Both models are a better description of ENT disinfection (r2 ¼ 0.68 to 0.72, RMSE ¼ 0.32e0.37) than EC disinfection (r2 ¼ 0.52 to 0.55, RMSE ¼ 0.6e0.62). The fact that ENT exhibited less dispersion around the no-tailing model may reflect less variability (compared to EC) in the disinfection resistance of enterococci bacteria populations present in the sewage and source waters. Intrinsic rate constants estimated from the slope b are also similar for the two models. Chick’s Law yields intrinsic rate constants for EC and ENT of 3.0 and 1.9 mM
1 min
1, respectively (panels A and C). The no-tailing model yields intrinsic rate constants for EC and ENT of 3.3 and 3.5 mM
1 min
1, respectively (panels B and D). The intrinsic disinfection rate for EC is also similar to values estimated by averaging rate constants obtained from our individual experiments (see Section 3), and from data reported in other studies of PAA disinfection (Table 1). In summary, Chick’s Law and the notailing model were both reasonably good predictors of bacterial decay caused by PAA disinfection, and both yield values of

the intrinsic disinfection rate constant kd that were consistent across models, and across studies. Relative to the modeling effort described in the next section, the primary benefit of the no-tailing model is that it accounts for the decay in disinfectant concentration that will inevitably occur following injection of PAA into the subsurface.

5.

Lagrangian model of in situ disinfection

In this section we develop a quantitative model that accounts for the physical, chemical, and biological factors that might influence the in-situ disinfection of sewage contaminated shallow groundwater with PAA. The model is developed in two stages. First, a Lagrangian framework is used to predict the concentration of both sewage constituents (fecal indicator bacteria) and PAA residual in a parcel of shallow groundwater as it travels from the point of injection to the point where it is discharged to the coastal ocean. Second, an analytical model is derived for fluid parcel residence time in shallow

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groundwater, for the situation (relevant to Avalon Bay) where shallow groundwater discharge is dominated by tidal pumping and meteoric flow.

5.1. Lagrangian framework for modeling disinfection kinetics Fig. 4 illustrates the physical transport processes that might affect fecal bacteria concentration in a parcel of groundwater as it moves from the point where it first encounters subsurface injected disinfectant (point A) to the point where it exits the shallow groundwater and is discharged to the coastal ocean (point B). As the parcel moves from A to B, the concentration of bacteria in the fluid parcel changes with time due to disinfection, non-disinfection related die-off, regrowth, and attachment to the porous matrix (filtration). Mass balance over a fluid parcel as it travels from A to B yields the following rate expression for the concentration of bacteria (N, bacteria L
3), where s [min
1] represents the time a sewage contaminated water parcel has been in contact with disinfectant (referred to here as “residence time”), C is the disinfectant concentration [mM], and the rate constants for disinfection, inactivation, filtration, and growth are kd [mM
1 min
1], ki [min
1], kf [min
1], and mg [min
1]:  dN
1
¼
kd N½1=C0 þ k s
ki þ kf N þ mg N ds

(9)

In formulating Eq. (9), we adopted the no-tailing version of Hom’s Law described earlier (Eq. (7) with m ¼ 0 and n ¼ 1) and assume that inactivation, filtration, and regrowth of bacteria all follow first-order kinetics. While we did not

where, mg,max and Ks represent the maximum growth rate and saturation constant, respectively. Based on the measurements of DOC presented in Section 3.1, potential sources of DOC include ambient groundwater (DOCGW), sewage (DOCSewage), and acetic acid associated with the PAA mixture, including acetic acid present as an equilibrium component of commercial PAA preparations (DOCAA,0), and acetic acid formed by the decomposition of PAA during disinfection (DOCA(s)), where the latter can be estimated from the loss of peroxycompound concentration with time: DOCAA ðsÞ ¼ 0:82MðC0
CðsÞÞ

(11)

Eq. (11) assumes stoichiometric conversion of PAA to acetic acid, taking into account the molar fraction (0.82) of the peroxycompound concentration that is PAA and the weight of carbon associated with every mole of acetic acid, M ¼ 25 g of carbon per mole. Combining Eqs. (10) and (11), we have the following prediction for the total DOC available for growth of fecal indicator bacteria: DOCT ðsÞ ¼ DOCGW þ DOCSewage þ DOCAA;0 þ 0:82MðC0
CðsÞÞ:

(12)

Combining Eqs. (9)e(12) and solving the resulting differential equation, yields the following formula for the concentration of bacteria in a parcel of shallow groundwater as a function of residence time (s):

 
kf ðC0 M þ Ks Þ þ C0 Mki
C0 Mmg;max þ DOCT0 kf þ ki
mg;max þ ki Ks  N0 ðDOCT0 þ Ks Þ exp
s C0 M þ DOCT0 þ Ks a

NðsÞ ¼

(e.g., Lazarova et al., 1998; Lefevre et al., 1992). Here we use the Monod equation (Levenspiel, 1980) to model the dependence of growth rate mg on dissolved organic carbon (DOCT): mg;max DOCT ðsÞ (10) mg ðsÞ ¼ Ks þ DOCT ðsÞ



kd =k

ðC0 k s þ 1Þ

½C0 k sðMC0 þ DOCT0 þ Ks Þ þ DOCT0 þ Ks 

observe regrowth in the disinfection experiments presented earlier, it is a well-known that the acetic acid in commercial PAA mixtures can serve as a carbon source for the growth of heterotrophic bacteria, including fecal indicator bacteria

a¼

a

Ks mg M k ðC0 M þ DOCT0 þ Ks Þ2

(13a)

(13b)

Fig. 4 e A conceptual model for the in-situ disinfection of sewage-contaminated shallow groundwater in coastal marine environments.

w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 5 6 4 1 e5 6 5 3

Fig. 5A presents the bacterial log reduction predicted by Eq. (13) (solid curves) as a function of initial PAA concentration (vertical axis) and residence time (horizontal axis). This graph was generated using the parameter values listed in Table 2, which are based on the experimental measurements presented earlier and field conditions relevant to the Avalon Bay field site, including a shallow groundwater temperature of 15  C. For the range of peroxycompound concentrations considered in Fig. 5A, the dependence of bacteria concentration on residence time exhibits two patterns. At small residence times, very little of the PAA has been converted to acetic acid, disinfection dominates, and bacteria concentration declines rapidly with increasing residence time. At longer residence times, PAA has been mostly converted to acetic acid, regrowth of bacteria dominates, and bacterial concentration increases with increasing residence time. This decay/ regrowth pattern is illustrated for a single initial peroxycompound concentration (C0 ¼ 0.03 mM) and temperature (T ¼ 15  C) in Fig. 5B (dotted line). For this particular choice of parameter values, the model predicts that bacterial concentration falls approximately 2 log units within 12 h, and increases thereafter, eventually rising above the initial bacteria concentration at a residence time of around two days. As expected, bacteria removal increases monotonically with increasing initial peroxycompound concentration, as illustrated for a fixed residence time (s ¼ 5 days) and temperature (T ¼ 15  C) in Fig. 5C (dotted line). Using the activation energies for the intrinsic disinfection rate constant reported in Section 3.3, the model predicts similar trends over the range of temperatures (13e17  C) typically measured in Avalon shallow groundwater (compare the family of curves in Fig. 5B and C).

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In an ideal scenario, by the time a fluid parcel of shallow groundwater is discharged to the ocean, both its bacterial concentration and PAA residual would be very small. The dependence of PAA residual on initial peroxycompound concentration and residence time can be estimated from Eq. (6), by setting the left hand side equal to a fixed residual concentration, Cres and solving for residence time s: sres ¼


b 1

1 C0 C
C
1 0 a res

(14)

Curves of constant peroxycompound residual are plotted in Fig. 5A (dashed curves). As expected, peroxycompound residual declines with increasing residence time for a fixed C0. Interestingly, the curve for Cres ¼ 1 mM roughly demarcates the transition from bacteria disinfection to regrowth (compare solid and dotted lines in Fig. 5A).

5.2.

Residence time of fluid parcels

The Lagrangian model presented above reveals that both the bacterial concentration and PAA residual were sensitive to the residence time of water parcels in shallow groundwater, and in this section we describe some of the physical processes that can affect this key parameter. Here, residence time has precisely the same meaning as in estuarine systems: “how long a parcel, starting from a specified location within a waterbody, will remain in the waterbody before exiting” (Monsen et al., 2002). Provided that material diffusion can be neglected (a key assumption in the Lagrangian approach adopted here) (Deleersnijder et al., 2001), the residence time

Fig. 5 e Model predictions for EC concentration and PAA residual for the in-situ disinfection of sewage contaminated shallow groundwater with PAA. Panel A: Curves of constant EC log reduction predicted by Eq. (13) (solid lines labeled with numbers ranging from L1 to L9), and curves of constant peroxycompound residual predicted by Eq. (14) (dashed curves, labeled with numbers ranging from 0.2 to 1 mM). Panel B: Change in EC concentration with residence time predicted by Eq. (13) for C0 [ 0.03 mM and the ambient groundwater temperatures shown. (C) Change in EC concentration with increasing initial PAA concentration predicted by Eq. (13) for a fixed residence time of s [ 5 days and the ambient groundwater temperatures shown. Parameter values used to generate these curves are listed in Table 2.

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Table 2 e Inputs parameters used to produce the disinfection contour plot (Fig. 5), residence time model (Fig. 6). Constant a b kd ki kf mg Ks DOCT0 M A Kp l

Name

Value (b
1)

k* fitting parameter k* fitting parameter EC disinfection rate (T ¼ 13,15,17  C) EC natural decay rate EC filtration rate Max growth rate Growth rate saturation constant Initial DOC Concentration Mass of carbon per mole PAA Wave amplitude Hydraulic conductivity Wave number

0.0093 mM min 1.42 3.3, 3.7, 4.1 mM
1 min
1 0.1 h
1 0 min
1 0.005 min
1 0.07 mg L
1 25 g 1m 5  10
4 m s
1 0.05 m
1

associated with the movement of a fluid parcel from point A to B in Fig. 4 can be written explicitly as follows: ZL sc ¼

dx v

(15)

0

where, v is the velocity experienced by the fluid particle as it moves toward the ocean. Here we have subscripted the residence time calculated from Eq. (15) (sc) to distinguish it from the actual residence time of a water parcel included in our disinfection model above (s). Fluid parcel velocity has contributions from tidal pumping (vt), wave set-up (vw), meteoric groundwater flow (vm), seasonal evapotranspiration (vs), and density driven flow (vd) (Burnett et al., 2003b; Michael et al., 2005): v ¼ vt þ vw þ vm þ vs þ vd

(16)

Given that tidal pumping appears to dominate the discharge of shallow groundwater to Avalon Bay (Boehm et al., 2009b), here we focus on the tidal pumping and meteoric terms in Eq. (16), vt and vm. Flow fields generated by tidal pumping can be approximated from the following expression (Nielsen, 1990):

vt ðx; tÞ ¼ Kp Ale
lx ðcos½ut
lx
sin½ut
lxÞ

Source
1

(17)

Nielsen derived Eq. (17) from the Boussenesq equation after invoking a number of simplifying assumptions, including a homogeneous unconfined aquifer of hydraulic conductivity KP, a vertical beach face, and a one-dimensional flow field (parallel to the x-axis, see Fig. 4) characterized by a wave number l, and forced by a single harmonic tide with amplitude A and angular frequency u. The wave number is defined as l ¼ 2p/x0, where x0 represents the inland distance over which tidal fluctuations in the shallow groundwater are significant. Because the flow field predicted by Eq. (17) is tidally periodic and spatially variable, the residence time of a fluid parcel will depend not only on where in the aquifer it is released (referred to here as the setback distance, x ¼ L, see Fig. 4) but also on when in the tidal cycle that release occurs; a very similar phenomenon has been described for the residence time distributions in coastal estuaries (Monsen et al., 2002; Oliveira and Baptista, 1997). Despite these complications, a characteristic residence time can be estimated from Eqs. (15)e(17) by releasing the fluid parcel at the precise moment when the recessional tide wave (associated

Wagner et al. Wagner et al. Measured Estimated Estimated Surbeck et al. Surbeck et al. Measured Calculated Estimated Calculated via KozenyeCarman Estimated

with the falling tide) passes point A in Fig. 4, which is mathematically equivalent to assigning the value p to the quantity (ut
lx) in Eq. (17). After invoking this simplification and allowing for the possibility of non-zero meteoric flow, Eqs. (15)e(17) can be combined to yield the following estimate for the characteristic residence time of a fluid parcel released at a setback distance x ¼ L from the beach: sc ¼

  log
AlKp
elL vm
log
AlKp
vm ; vm

sc ¼

1  lL e
1 ; Al2 Kp

vm ¼ 0

vm > 0

(18a)

(18b)

For the range of parameter values typical of the field site in Avalon Bay (see Table 2), the residence times predicted by Eq. (18) vary over one hundred thousand fold, from approximately 30 mine1000 days (Fig. 6). This variability in residence time derives, in part, from the non-linear dependence of residence time on both set-back distance and meteoric flow (Eq. (18a)). Furthermore, if studies of residence times in estuaries are any guide, the residence time sc of water parcels in shallow groundwater is best characterized by a probability distribution, not a single value. Studies in estuarine systems have noted that fluid parcel residence times tend to follow probability distributions characterized by long tails, implying that

Fig. 6 e Characteristic shallow groundwater residence times predicted by Eq. (18) for various set-back distances and meteoric flow velocities.

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w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 5 6 4 1 e5 6 5 3

Table 3 e Inputs Parameters used in the uncertainty analysis (Eq. (19)). Constant k* kd ki mg Ks DOCT0 C0 s

Name

Value

Estimated uncertainty

PAA decay rate EC disinfection rate (T ¼ 15  C) EC natural decay rate Max growth rate Growth rate saturation constant Initial DOC concentration Initial peroxycompounds Residence time

1.35 L$mmol
1$min
1 3.7 L$mmol
1$min
1 0.1 h
1 0.005 min
1 0.07 0.006 g/ L
1 0.03 mmol 2 day

0.2 0.2 0.2 0.2 0.2 0.2 0.2 1

a minority of fluid parcels spend a very long time in the estuary (Oliveira and Baptista, 1997).

6. Uncertainty analysis and practical implications One advantage of the analytical in-situ disinfection model derived earlier (Eq. (13)) is that the uncertainty associated with different independent variables can be assessed quantitatively using the Law of Uncertainty (Taylor and Kuyatt, 1993): u2 ðSÞ ¼

p X i¼1

 2 vS u2 ðXi Þ vXi

(19)

In this equation, u2(S ) and u2(Xi) represents the variance of the dependent and independent variables, respectively, the dependent variable is the log-transformed bacteria concentration (S ¼ log(N )), the independent variables Xi include all variables appearing on the right hand side of Eq. (13) (i.e., C0, Ks, mg, DOCT0, k*, kd, ki, or s), vS/vXi is the sensitivity of the dependent variable to change in a particular independent variable (computed analytically from Eq. (13)), and the summation is taken over all independent variables (P ¼ 8). The uncertainty (or variance) associated with each independent variable was estimated from the relative uncertainty UR(Xi) and magnitude jXi j values listed in Table 3: uðXi Þ ¼ UR ðXi ÞjXi j

(20)

The form of the Law of Uncertainty adopted here assumes that independent variables do not co-vary, which is reasonable for most combinations of independent variables included in this analysis. When applied to Eq. (13), the Law of Uncertainty reveals that 99% of the variance in the log-transformed bacteria concentration can be attributed to variance in just three independent variables: residence time (s) (90%), maximum growth rate (mg) (8%), and the inactivation rate (ki) (1%). These results imply that the prediction (and optimization) of in-situ disinfection will depend strongly on the residence time of shallow groundwater which, in turn, depends non-linearly on the injection well set-back distance (L) and physical characteristics of the shallow groundwater system that can vary in time and space (l, A, KP, vm) (see Eq. (18)). Given the very approximate nature of the analysis that led to Eq. (18), experimental characterization of shallow groundwater residence times would be a fruitful topic for further investigation.

The disinfection model’s sensitivity to residence time is, in part, a consequence of the fact that fecal bacteria can grow in the environment, and thus dramatically different disinfection outcomes (e.g., from a net reduction in bacteria concentrations to a net increase in bacteria) can be caused by slight changes in residence time of water parcels in the shallow groundwater. Given that most recreational waterborne illnesses are caused by human viruses that cannot grow outside their host (Schoen et al., 2011), it is possible that in-situ disinfection of sewage contaminated shallow groundwater would reduce shoreline concentrations of human pathogens (and hence lower recreational waterborne illness rates), even if it did not substantially reduce fecal indicator bacteria concentrations. Indeed, the environmental growth of EC and ENT can lead to a decoupling between fecal indicator bacteria and human pathogens in recreational waters (Litton et al., 2010), and potentially nullify epidemiological relationships upon which current fecal indicator bacteria criteria are based (Colford et al., 2007). In light of these and other concerns the U.S Environmental Protection Agency is evaluating and possibly revising the current water quality criteria for marine recreational beaches (Boehm et al., 2009a).

7.

Conclusions

 Aeration alone and aeration with brine did not significantly reduce EC and ENT concentrations in mixtures of raw sewage and shallow groundwater after 6 h of exposure, while 4e5 mg L
1 of PAA and 4 mg L
1 Oxone achieved >3 log reduction of EC and ENT after 15 min of exposure.  Oxone disinfection is enhanced at higher salinities, most likely due to the formation of secondary oxidants (e.g., chlorine and bromine) that make this disinfectant inappropriate for marine applications.  PAA disinfection of fecal bacteria in shallow groundwater in coastal settings depends non-linearly on residence time, and the “ideal” disinfection outcome (low bacterial concentration and low PAA residual) is achieved over a relatively narrow window of residence times and initial disinfection concentrations.  By analogy to surface estuaries, the residence time of water parcels in shallow groundwater under the influence of marine tides (i.e., subterranean estuaries) is likely to exhibit broad (e.g., logenormal) probability distributions with long

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w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 5 6 4 1 e5 6 5 3

tails, and depend sensitively on local precipitation, meteoric flow, and tidal variability.  Uncertainty calculations suggest 99% of the uncertainty associated with the log reduction of bacteria is caused by just three independent variables: residence time (s) (90%), maximum growth rate (mg) (8%), and the inactivation rate (ki) (1%).  Given these results, further research into the residence time of water in shallow groundwater is needed before an in-situ disinfection schemes can be successfully designed and implemented.

Acknowledgments The authors thank R. Litton, L. Ho, and J. Monroe for assistance with the experiments, and C. Wagner and P. Woolson, and the City of Avalon staff for the use of City Hall for the disinfection studies. Funding was provided by the City of Avalon and State Water Resources Control Board Clean Beaches Initiative, under Agreement 07-582-550.This is publication 66 of the Urban Water Research Center, University of California, Irvine.

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