CSIRO LAND AND WATER FLAGSHIPNatural soil attenuation oforganic compounds
associated with coal seamgas extraction
Dirk Mallants, Andrew Taylor, Jirka Simunek, Rai Kookana andMike Williams
November 2015

CSIRO Land and Water Flagship

Citation
Mallants D, Taylor A, Simunek J, Kookana R and Williams M (2015) Natural soil attenuation of organic
compounds associated with coal seam gas extraction. CSIRO Land and Water, Canberra. 54 pp.

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iiContents
Acknowledgments

8

Executive summary

91

Introduction

102Modelling process

12

2.1

Conceptual model ............................................................................................................................... 12
2.1.1 Soil – shallow groundwater pathway........................................................................................ 122.1.2 Soil hydrological model ............................................................................................................. 14
2.1.3 Soil geochemical model ............................................................................................................ 15

2.2
Numerical model for multi‐component reactive transport modelling in saturated/unsaturated
media 172.2.1 HYDRUS‐1D.................................................................................................................................17
2.3

Model implementation ....................................................................................................................... 18
2.3.1 Soil hydrological characteristics ................................................................................................ 18
2.3.2 Soil geochemical Model ............................................................................................................ 20

3

Natural attenuation parameters for typical organic compounds

3.1

Organic compounds considered in this assessment ........................................................................... 24

3.2

Degradation in soil .............................................................................................................................. 26
3.2.1 Phenolic compounds................................................................................................................. 26
3.2.2 Polyaromatic hydrocarbons ...................................................................................................... 29
3.2.3 Hydraulic fracturing additives ................................................................................................... 30
3.2.4 Summary of chemical parameters of organic compounds ....................................................... 31

4

Detailed description of the simulation cases

4.1

Sensitivity analysis............................................................................................................................... 37

4.2

Phenolic compounds ........................................................................................................................... 39
4.2.1 Phenol .......................................................................................................................................39
4.2.2 2‐methylphenol.........................................................................................................................40

4.3

Polycyclic aromatic hydrocarbons....................................................................................................... 41
4.3.1 Naphthalene ............................................................................................................................. 41

4.4

Hydraulic fracturing additives ............................................................................................................. 42
4.4.1 2‐butoxyethanol........................................................................................................................42
4.4.2 Bronopol ...................................................................................................................................424.4.3 Limonene ..................................................................................................................................43
4.4.4 Dilution attenuation factors ..................................................................................................... 44

5Conclusions

24

37

45

3

References

46

Appendix 1 New HYDRUS‐1D module: Dependency of Kd and µ on soil organic carbon

54

4

Figures
Figure 1.1 Estimated volumes of produced water in Queensland (Source: DNRM, 2012) .............................. 10
Figure 2.1 Phases of development and operation of a coal seam gas project with typical activities.
Duration of each phase is indicative (length of arrows is not to scale). .......................................................... 12
Figure 2.2 Schematic description of the sources and pathways of contamination during the CSG
extraction depressurisation phase ................................................................................................................... 14
Figure 2.2 Finite element grid with soil layers (left) and location of four observation nodes (right) .............. 19
Figure 2.3 Calculated soil water content at five observation depths. Depths 2‐20 cm belong to soil layer
1, depth 50 cm belongs to soil layer 2 .............................................................................................................. 20
Figure 2.4 Soil organic carbon versus soil depth and modelled organic carbon depth‐dependency (datafrom Ringrose‐Voase et al., 2003) .................................................................................................................... 22
Figure 2.5 Principle of modelling the depth‐dependency of organic carbon in HYDRUS‐1D. Left: originalorganic carbon data; right: depth‐reduction factor. ........................................................................................ 22
Figure 2.6 Example demonstrating organic carbon profile (a), the derived depth‐reduction factor (b), thedepth‐reduction factor applied to the distribution coefficient for three chemicals involved in first‐ordertransformation reactions (c) and the first‐order degradation constant for the same three chemicals (d) .....23
Figure 3.1 Reported degradation pathway for phenol. Rectangle indicates compounds included in thecurrent assessments (Omokoko et al. 2008) .................................................................................................... 27
Figure 3.2 Summary of reported metabolic degradation pathway for o‐cresol (Ahamad et al., 2001).
Based on work by Dagley and Patel (1957); Nakagawa and Takeda (1962); Bayly et al. (1966); Ribbons(1966); Bayly and Wigmore (1973); Hughes et al. (1984). Rectangle indicates compounds included in thecurrent assessments ......................................................................................................................................... 28
Figure 3.3 Proposed pathway for 3‐methylcathechol degradation by the Rhodococcus bacteria (strain
ZWL3NT) (Tian et al., 2013). ............................................................................................................................. 29
Figure 3.4 Potential degradation pathway of toluene by the Burkholderia fungorum FLU100 strain(Dobslaw and Engesser, 2015) ......................................................................................................................... 29
Figure 3.5 Proposed catabolic pathway for naphthalene by soil bacteria (Denome et al., 1993; Kiyohara
et al., 1994; Goyal and Zylastra, 1997). Rectangle indicates compounds included in the current
assessments ...................................................................................................................................................... 30
Figure 4.1 Effect of distribution coefficient Kd on chemical breakthrough curves at the depths of 2 and 5
cm (left) and 10 and 20 cm (right). Biodegradation is not considered (decay constant = 0). Source
concentration = 1000 mg/L. ............................................................................................................................. 37
Figure 4.2 Effect of distribution coefficient Kd on chemical breakthrough curves at the depths of 2 and 5
cm (left) and 10 and 20 cm (right). Biodegradation is accounted for: decay constant µ = 0.001 day‐1 (left)
and 0.01 day‐1 (right). Source concentration = 1000 mg/L............................................................................... 38
Figure 4.3 Breakthrough curves of phenol (red), catechol (blue) and HMSA (green) in a shallow soil
profile accounting for sorption (Kd) and biodegradation (µ); (a) maximum Kd and µ, (b) mean Kd and µ, (c)minimum Kd and µ. A hypothetical source concentration C0 of 1 mg/L is used ............................................... 39
Figure 4.4 Breakthrough curves of 2‐methylphenol (o‐cresol) (red) and 3‐methylcatechol (blue) in ashallow soil profile accounting for sorption (Kd) and biodegradation (µ); (a) maximum Kd and µ, (b) mean
Kd and µ, (c) minimum Kd and µ. A hypothetical source concentration C0 of 1 mg/L is used. ......................... 40
Figure 4.5 Breakthrough curves of naphthalene (red) and DHDHN (cis‐1,2‐dihydroxy
1,2dihydronapthalene) (blue) in a shallow soil profile accounting for sorption (Kd) and biodegradation(µ); (a) maximum Kd and µ, (b) mean Kd and µ, (c) minimum Kd and µ. A hypothetical source
concentration C0 of 1 mg/L is used. .................................................................................................................. 41
5

Figure 4.6 Breakthrough curves of 2‐butoxyethanol in a shallow soil profile accounting for sorption (Kd)and biodegradation (µ); (a) maximum Kd and µ, (b) mean Kd and µ, (c) minimum Kd and µ. A hypotheticalsource concentration C0 of 1 mg/L is used ....................................................................................................... 42
Figure 4.7 Breakthrough curves of bronopol (red) and formaldehyde (blue) in a shallow soil profile
accounting for sorption (Kd) and biodegradation (µ); (a) maximum Kd and µ, (b) mean Kd and µ, (c)minimum Kd and µ. A hypothetical source concentration C0 of 1 mg/L is used ............................................... 43
Figure 4.8 Breakthrough curves of limone in a shallow soil profile accounting for sorption (Kd) andbiodegradation (µ); (a) maximum Kd and µ, (b) mean Kd and µ, (c) minimum Kd and µ. A hypotheticalsource concentration C0 of 1 mg/L is used ....................................................................................................... 43
Figure 4.9 Dilution attenuation factors as function of attenuation parameters {u, Kd}. A = phenol, B =catechol, C = HMSA; D = 2‐methylphenol, E = 3‐methylcatechol; F = naphthalene, G = DHDHN; H = 2‐
butoxyethanol; I = bronopol, J = formaldehyde; K = limonene ........................................................................ 44

6

Tables
Table 2.1 Defined variable boundary conditions ............................................................................................. 18
Table 2.2 Mean van Genuchten soil hydraulic properties for Vertosols (average across the Cox’s Creak
Catchment area, NSW) (source: Bennett, 2012) .............................................................................................. 19
Table 3.1 Chemical identification information on CSG‐related chemicals. ...................................................... 24
Table 3.2 Summary of the chemical parameters of organic compounds reviewed in this study. ................... 33
Table 3.3 Sorption (Kd), half‐life (t1/2) and degradation parameters (µ) used as input for HYDRUS‐1D
simulations ....................................................................................................................................................... 36
Table 3.4 Approximate retardation factors R calculated for a water content of 0.305 (cm3 cm‐3) and bulk
density of 1.32 g/cm3 (representative for the layer 1 during the leak period) ................................................ 36
Table 4.1 Dilution attenuation factors for mean, minimum and maximum attenuation (2 cm depth)........... 447

Acknowledgments

The authors would like to acknowledge Dr. Anthony Ringrose‐Voase (CSIRO Land and Water, Canberra) for
providing detailed soil data on the Liverpool Plains. We equally acknowledge the Land and Water Business
Unit for funding the strategic appropriation research project “Next generation methods and capability for
multi‐scale cumulative impact and management”. This report was peer‐reviewed by Dr. Graeme Batley and
Dr. Simon Apte (CSIRO Land and Water, Lucas Heights).

8

Executive summary

Coal Seam Gas production generates large volumes of produced water that may contain compounds originating fromthe use of hydraulic fracturing fluids. Produced water also contains elevated concentrations of naturally occurring
inorganic and organic compounds, and usually has a high salinity. Leaking of produced water from storage ponds may
occur as a result of flooding or containment failure. A review of Australian coal seam gas literature has identified
several contamination pathways from surface spills through soil and shallow groundwater to several potential
receptors such as rivers, water bores, wetlands, stygofauna, etc.
In this report, the fate of hydraulic fracturing chemicals and naturally occurring organic chemicals in soil as a result of
unintentional release from storage ponds has been evaluated, and exposure pathways and relevant hydro‐
biogeochemical processes along such pathways reviewed. A collation of physico‐chemical properties of organic
contaminants served as input to a set of generic simulations of transport and attenuation in variably saturated soil
profiles. Attenuation was simulated by means of a coupled equilibrium partitioning ‐ first‐order biodegradation model.
The coupled processes of unsaturated flow, transport and attenuation in soil of selected contaminants that areassociated with hydraulic fracturing fluids or that occur naturally in coal seams have then been modelled.
Naturally occurring organic compounds considered in this study include phenolic compounds and polycyclic aromaticcompounds. Chemical additives of hydraulic fracturing fluids studied include a biocide, a surfactant and a solvent.
Biodegradation pathways of these organics were reviewed and those relevant for soils were considered in theassessment. By considering a sequence of organics consecutively undergoing degradation and transformation,
coupled with sorption onto soil organic carbon, the natural attenuation of organic compounds in soil was calculated.
Organic carbon is one of the most important soil properties influencing sorption and transformation of organic
compounds. To account for this key soil property and its depth‐dependency in soil, a new module was developed for
HYDRUS‐1D which automatically distributes organic carbon with depth, given observed organic carbon in the top soil
and background organic carbon at the bottom of the soil profile. On the basis of detailed organic carbon data from theLiverpool Plains (NSW), this depth‐dependency of organic carbon was implemented in the model, and the sorption(KOC x fraction of organic carbon) and degradation parameters (first‐order degradation rate calculated from thechemical’s half‐life) were adjusted accordingly.
Results showed that for all chemicals considered in the assessment, the combined effect of strong sorption and fastbiodegradation resulted in complete degradation of all chemicals, including their transformation products, in the top 5
to 10 cm of the soil profile. These results are true for a broad range of sorption and degradation parameter values.
This indicates that the risk of bioaccumulation in soil and leaching to groundwater is very small for the scenarios
considered in this study. The methodology developed here can be easily extended to a more systematic analysis ofleaching risks of a broad range of organic compounds introduced in soil.

91 Introduction

Extraction of coal seam gas requires de‐pressurisation of the coal seam layers by removing large amountsof groundwater through pumping. Reducing the hydrostatic pressure on the methane gas in the pores
allows gas to be released and flow towards the production wells. Coal layers generally have relatively low
permeability (i.e. ability to transmit fluids, including gas), particularly at greater depths. In the least
permeable coal measures, coal seam gas operations require the use of hydraulic fracturing as a means toincrease connectivity between naturally occurring fractures in coal beds, and thus enhance the flow ofhydrocarbons and other fluids towards the well. In Australia, coal measures in the Bowen Basin(Queensland) have much lower permeability than, for example, the Surat Basin (Queensland) and are
therefore likely to require higher levels of hydraulic fracturing.
The forecasts of coal seam gas water production will vary over time and geographically (DNRM, 2012). For
example, Figure 1.1 shows estimates of expected volumes of produced water per development area andthe whole‐of‐industry forecast in Queensland. Much of the variation is due to different assumptions about
the size and rate of coal seam gas industry development over the 50‐year time frame that is generally
assumed for forecasting water production (DNRM, 2012). By 2050, most coal seam gas areas will havereached the end of their production stage. During approximately 30 years, water production will be mostsignificant and presents a period during which risks of contamination of soil, groundwater and surface
water with produced water are the highest.

Figure 1.1 Estimated volumes of produced water in Queensland (Source: DNRM, 2012)

The produced water continuously emerges from the well and is usually stored temporarily in surface ponds;
for some of the coal seam gas wells, hydraulic fracturing will have been applied to enhance gas recovery(Vidic et al., 2013; Ward et al., 2015). Produced water has a high load of dissolved solutes (Batley et al.,10

2012; Ward et al., 2015), a high alkalinity (Ward et al., 2015) and contains organic and inorganic chemicals(Batley et al., 2012).
The aim of this study is to simulate the transport and transformation of organic compounds present in coalseam gas‐produced water infiltrating into soil. Such produced water may infiltrate into soil as a result of
spills following extreme rain events causing flooding of storage ponds containing produced water (DERM,
2011). Infiltration may also occur due to leaks from the same storage ponds in case the liner is breached(NSW Government, 2013). Finally, large‐scale diffusive leakage across the liners of storage ponds at very
low flow rates may also cause produced water to infiltrate soil (Rowe, 2012; Rowe and Hosney, 2010).
Our simulations involve coupled water flow and solute transport, sorption/desorption of organic
compounds on soil organic carbon, and degradation and transformation of such compounds whichthemselves are subject to transport and transformation. Both naturally occurring chemicals in coal‐seamwater (geogenics) and hydraulic‐fracturing organics are considered in the assessment.

11

2 Modelling process

2.1 Conceptual model
2.1.1 SOIL – SHALLOW GROUNDWATER PATHWAY
The lifetime of an individual coal seam gas well or an entire coal seam gas well field can be divided into
different phases (Figure 2.1). Each phase has a number of typical activities with a relatively well‐definedduration and set of risks. Importantly, these risks are not equally distributed across time and space.

Figure 2.1 Phases of development and operation of a coal seam gas project with typical activities. Duration of eachphase is indicative (length of arrows is not to scale).

The phases of development and operation of a coal seam gas well field are as follows:
1. Baseline or pre‐development phase: starts when the site is being established and includes activities

such as site identification, site access and preparation, baseline monitoring prior to production wellconstruction. This may take between two to five years.
2. Drilling and completion phase: includes activities such as well construction starting with a bare site,building a pad and pond, setting up the rig, drilling, installing casing and piping, and cementing. This isfollowed by pump installation, completion of the surface gathering system, and connecting the well to
the gathering system. The duration of the phase is normally from two to seven weeks per coal seam gas
well.
3. Pressurisation or hydraulic fracturing fluid injection phase: starts with the first injection of hydraulicfracturing fluid into the coal formation and terminates when the last fluid is injected. There may be anumber of injection events in the life‐time of the site. The duration of the injection phase is from hours
to days. It should be noted that the majority of production wells in Queensland and New South Wales
have not required hydraulic fracturing because the permeability is sufficiently high for gas to flow due
to natural fractures. Companies are preferentially targeting these areas initially. Coal seams in the
Bowen Basin (Queensland) have a much lower permeability than the Surat Basin (Queensland), and as aresult, hydraulic fracturing will likely have greater application in the Bowen Basin than in the Surat.
4. Depressurisation phase: starts soon after hydraulic fracturing phase ends, and covers both flowback

and production, including the extraction of gas and water from the coal seam until gas and water
extraction ends. In a coal seam gas well, water flow rates are initially high with low gas flow rates but as
the coal seam formation is progressively depressurised, gas flow rates continue to rise to a peak rate12(months or years after dewatering started) and water flow rates decline. There may be a number ofdepressurisation events intermittent with injection phases. The total duration of the depressurisation
phase may be up to 20 or 30 years.
5. Return to equilibrium or post‐operational phase: starts at the end of the depressurisation phase andfinishes when groundwater pressures have been restored to their pre‐operational levels. It includes
activities such as decommissioning, plugging, rehabilitation, and monitoring. This is done progressively
as wells are depleted, plugged, and abandoned. The cessation of water extraction via a coal seam gas
well does not necessarily result in an overall restoration of the original groundwater pressures. It will
depend, among other things, on how fast groundwater can flow towards the zones that experienced
depressurisation. In other words, although the depressurisation phase has ended because water
extraction has stopped, it may still take a very long time to restore all groundwater pressures to thepre‐operational conditions. Duration of the post‐operational phase can be easily in excess of 100 years,
and might in some circumstances take a thousand years or longer to reach a new equilibrium(CH2MHill, 2013).
There are several possibilities for the contamination of surface‐ and groundwater during the lifetime of ahydraulic fracturing operation site. This can happen by via an accidental spill of the fracturing fluid prior to
the injection, a failure in the well casing, a leakage in a transport line or a spill from a storage pond
(NYSDEC, 2011; Royal Society and Royal Academy of Engineering, 2012; DERM, 2013; NSW Government,2013). This study is based on the hypothetical scenario that a spill from a storage pond of produced water
occurs over several years during the CSG depressurisation phase. It implicates a surface source ofcontamination, which subsequently migrates through the upper soil. The extent of the contaminated area
will vary, depending on the chemical, volumetric and temporary characteristics of the spill, the soil
geochemical characteristics and the soil hydrological characteristics. The pathways can include a primarysurface runoff, infiltration through the upper soil layers with a possible reach of a shallow groundwatertable, lateral transport within the aquifer or an accelerated downward flux through natural cracks andfaults. Accordingly, possible receptors are groundwater, the surrounding ecosystem including wetlands,
springs, surface water and flora and fauna, and possibly existing water supply bores for domestic use(Figure 2.2).

13

Figure 2.2 Schematic description of the sources and pathways of contamination during the CSG extraction
depressurisation phase

In this study the focus is on the vertical reactive transport through the upper soil. For soils on a slope lateraltransport may be important, especially when a textural contrast exists between soil horizons. Analysis of
two‐dimensional flow is typically addressed by means of two‐dimensional saturated/ unsaturated
simulation codes such as HYDRUS (2D/3D) (Šimůnek et al., 2006, 2008).

2.1.2 SOIL HYDROLOGICAL MODEL
Simulation of variably saturated flow in soil requires a mathematical relationship between: (i) the soil watercontent (ϴ) and the soil pressure head (h), and, (ii) either the water content or the pressure and theunsaturated hydraulic conductivity K(ϴ) and K(h), respectively. The most commonly used mathematicalexpression for the soil water retention curve, ϴ(h), is the van Genuchten equation (van Genuchten, 1980)
since it permits a relatively flexible and accurate description of ϴ(h) for many soils using only a limited
number of parameters. The van Genuchten soil moisture retention characteristic is defined as:||

Equation 1

where ϴr is the residual water content (cm3/cm3), ϴs is the saturated water content (cm3/cm3), and α (1/m),n and m (= 1 – 1/n) are unitless curve shape parameters specifically for the van Genuchten equation.
The second important soil hydraulic property is the unsaturated hydraulic conductivity function, K(h). The
hydraulic conductivity characterises the ability of a soil to transmit water, and as such is inversely related to
the resistance to water flow. The hydraulic conductivity depends on many factors, including the pore‐size
distribution of the porous medium, and the tortuosity, shape, roughness, and degree ofinterconnectedness of pores. The hydraulic conductivity decreases considerably as the soil becomesunsaturated and less pore space is filled with water. The unsaturated hydraulic conductivity function gives
14

the dependency of the hydraulic conductivity on the water content, K(ϴ), or pressure head, K(h). The
conceptual model that views the soil as a bundle of capillaries of different radii may be used to evaluate thehydraulic conductivity function. By adding the conductivity of all capillaries that are filled with water at aparticular water content or pressure head, one obtains the hydraulic conductivity of the complete set ofcapillaries, and consequently of the soil itself.
Similarly, as for the soil water retention curve, analytical models are often used also for the unsaturated
hydraulic conductivity function, K(h). The van Genuchten (1980) retention function is coupled mostly withthe model of Mualem (1976) to give1/

1

Equation 2

where
1

1

,

1

Ks is saturated hydraulic conductivity, Se = (ϴ ‐ ϴr)/(ϴs ‐ ϴr) is the effective saturation, and m and n are as
defined previously. The pore‐connectivity parameter (l) was estimated by Mualem (1976) to be about 0.5
as an average for many soils.

2.1.3 SOIL GEOCHEMICAL MODEL
Migration of chemicals in soil is primarily by advection1 and dispersion (ignoring gaseous transport). By
mathematically solving the solute transport or advection‐dispersion equation (ADE when advection is used,or CDE when convection is used), predictions of solute concentrations at different depths and times can beobtained (Mallants et al., 2011).
For transport of inert, non‐adsorbing contaminants during variably‐saturated water flow the ADE is asfollows (Toride et al., 1995):
Equation 3
where c is solute concentration in the water phase (mg/L), t is time (s), D is hydrodynamic dispersion (total
dispersion, which is the sum of molecular diffusion and mechanical dispersion) (m2/s), z is soil depth (m),and v is pore‐water velocity (m/s).
In the unsaturated zone, advective transport usually becomes an important component of the overall
transport, hence the two‐component dispersion coefficient (D) (m2/s) has to be used. Molecular diffusion(Dp) (m2/s) is one component of the hydrodynamic dispersion, but unless water flow is extremely slow,
molecular diffusion is of secondary importance2 in the migration of elements in soils and permeable aquifer
sediments. The second component of hydrodynamic dispersion is mechanical dispersion,  x v, as shown in
the following equation:
Equation 4
where D is hydrodynamic dispersion, or simply dispersion,  is dispersivity3 (m), and v is pore‐water velocity(m/s). Water content ϴ is needed to obtain pore‐water velocities (v) from water fluxes (q) following:

1

Sometimes referred to as convection
Mechanical dispersion in most subsurface transport problems dominates molecular diffusion in the liquid phase, except when thefluid velocity becomes relatively small or is negligible. Diffusion‐dominated transport occurs in low permeability media, such as
clays and rock matrices.
3
Longitudinal dispersivity (αL) is a term used to indicate dispersion along the main direction of flow
2

15

v

q/θ

Equation 5

Diffusion or molecular diffusion is transport of solutes from an area of higher concentration to an area oflower concentration. It occurs as long as such a concentration gradient exists, even if the water is not
flowing. Mechanical dispersion is a transport process due to heterogeneous distribution of water flow
velocities within and between different soil pores (Mallants et al., 2011). The result is that some solutes will
be ahead of the solute front, whereas others will lag behind, leading to solute mixing and generally a bell‐
shaped distribution of velocities and thus of arrival times, typical of a breakthrough curve. The processes ofmolecular diffusion and mechanical dispersion are incorporated into one parameter, the hydrodynamic
dispersion coefficient D. Phenomenologically, dispersion has two effects: it increases the passage time of acomplete solute pulse and it decreases the maximum concentration. In the case of a toxic contaminant for
example, it leads to a longer exposure time but also to a lower maximum concentration.
Dispersivity is a transport parameter that is often obtained experimentally by fitting measured
breakthrough curves with analytical solutions of the advection‐dispersion equation (Mallants, 2014;
Seuntjens et al., 2001). In this study a dispersivity = 0.1 m was taken, or one tenth of the total travel
distance (i.e. 1 m) from top to bottom of the soil profile.
When chemicals interact with the soil solid phases (organic carbon, clay, iron oxides), sorption has to beaccounted for in the solute transport equation. The sorption process is usually described by means of theretardation factor R, defined as:

R  1

bKd(1  n )  s K d
 1



Equation 6

where s is solid density (g/cm3 of solids), and Kd is the distribution coefficient for instantaneous, linear andreversible sorption (L/kg). The latter parameter depends on the type of porous medium and on theelement. It describes the capacity of a solid to remove a dissolved chemical from the liquid phase to thesolid phase. If sorption is fast compared to the flow velocity, the element will reach some equilibrium
condition between liquid and solid phase. This is called equilibrium sorption. The Freundlich equation is thesimplest approach to quantify the behaviour of retention of reactive solutes with the soil matrix. It has
been used widely to describe solute retention by soils and aquifer sediments (Helfferich, 1962; Sposito,
1984; among others). The Freundlich equation is expressed as:b

C ads = K d C liq

Equation 7

where Cads is the concentration of solute retained by the soil in mg/g of dry soil, Cliq is the soluteconcentration in solution in mg/ml, Kd is the soil‐water distribution coefficient, also referred to as
distribution coefficient, in ml/g, and the parameter b is dimensionless and typically has a value of b < 1. For
b = 1, the (nonlinear) Freundlich equation reduces to a linear sorption equation.
In case chemicals are consecutively undergoing biodegradation and transformation, the rate oftransformation is often described as a first‐order process. Especially biodegradation kinetics (the time‐dependent substrate removal and metabolism) in soil have conveniently been described by means ofrelatively simple mathematical models including first‐order kinetics (Scow and Johnson, 1997). In this case abiodegradation constant µ (days‐1) is calculated according to:µ

ln 2 0.693

t1 / 2
t1 / 2Equation 8

where t1/2 is the chemical half‐life (days). In case several chemicals are involved in a sequential first‐orderdecay or degradation chain (Ci, i = 1, n):

C1  C 2  ...  C n

Equation 9

a set of coupled differential equations governing advection‐dispersion, linear‐equilibrium transport of asequence of solutes consecutively undergoing biodegradation and transformation will be invoked. For two
16

elements, C1 and C2, the coupled advection‐dispersion equilibrium partitioning – first‐order biodegradation
equation becomes (van Genuchten, 1985):

R1C1  
C  qC1
 µ1 R1C1
 D 1  
t
x 
x 
x

Equation 10

 
C  qC 2
R2C 2
 µ2 R2 C 2  1 R1C1 D 2  
x 
x 
x
t

Equation 11

where R1 and R2 are retardation factors for chemical C1 and C2, respectively and µ1 and µ2 are first‐orderbiodegradation constants for chemical C1 and C2, respectively.

2.2 Numerical model for multi‐component reactive transport modellingin saturated/unsaturated media
2.2.1 HYDRUS‐1D
HYDRUS‐1D (Šimunek et al., 2008) is a public domain computer software package (www.hydrus2d.com)
that simulates the one‐dimensional movement of water, heat, and multiple solutes in variably saturated
media. The program uses finite elements to numerically solve the Richards equation for saturated‐unsaturated water flow and Fickian‐based advection‐dispersion equations for both heat and solutetransport. The flow equation includes a sink term to account for water uptake by plant roots as a functionof both water and salinity stress. The heat transport equation considers conduction as well as advection
with flowing water. The solute transport equations account for advective‐dispersive transport in the liquid
phase, and diffusion in the gaseous phase. The transport equations also include provisions for non‐linear
and/or non‐equilibrium reactions between the solid and liquid phases, linear equilibrium reactions
between the liquid and gaseous phases, zero‐order production, and two first‐order degradation reactions:
one which is independent of other solutes, and one which provides the coupling between solutes involvedin the sequential first‐order decay reactions.
The program may be used to analyse water and solute movement in unsaturated, partially saturated, or
fully saturated media. The flow region itself may consist of non‐uniform (layered) soils. The unsaturated soil
hydraulic properties (the constitutive relationships) are described using van Genuchten (1980) or Brooks
and Corey (1964) type analytical functions, or modified van Genuchten type functions that produce a better
description of the hydraulic properties near saturation. HYDRUS‐1D incorporates hysteresis by assumingthat drying scanning curves are scaled from the main drying curve, and wetting scanning curves from themain wetting curve. Root growth is simulated by means of a logistic growth function. Water and salinity
stress response functions can also be considered.
HYDRUS‐1D has capabilities to simulate the transport of viruses, colloids, and bacteria (Schijven andŠimunek, 2002; Bradford et al., 2003). HYDRUS‐1D uses a Microsoft Windows based Graphics User Interface(GUI) to manage the input data required to run the program, as well as for nodal discretisation and editing,parameter allocation, problem execution, and visualization of results. All spatially distributed parameters,such as those for various soil horizons, the root water uptake distribution, and the initial conditions forwater, heat and solute movement, are specified in a graphical environment. The program offers graphs ofthe distributions of the pressure head, water content, water and solute fluxes, root water uptake,temperature and solute concentrations in the soil profile at pre‐selected times. Also included is a small
catalogue of unsaturated soil hydraulic properties (Carsel and Parish, 1988), as well as pedotransfer
functions based on neural networks (Schaap et al., 2001).

17

2.3 Model implementation
2.3.1 SOIL HYDROLOGICAL CHARACTERISTICS
Simulation of coupled variably‐saturated water flow and solute transport requires flow boundary
conditions and soil hydraulic properties. Boundary conditions implemented in this study are summarised inTable 2.1. The top boundary is simplified by assuming net infiltration only, thereby simplifying processes of
evapotranspiration, runoff, and soil water redistribution into a single process of recharge (i.e. the next
result of all those processes). This means that the imposed water flux is continuous across the entire soil
profile, and the water flux at the bottom of the profile equals that at the top. The following features were
simulated with HYDRUS‐1D:Time series of soil water content, matric head, and solute concentrations (organic compounds)
Depth profiles of soil water content, matric head, and solute concentrations (organic compounds)
at prescribed time intervals
Time series of water fluxes at the bottom (drainage) of the soil profile, as well as solute fluxes(these will be shown to be effectively zero for all compounds considered).

Table 2.1 Defined variable boundary conditions

Time (years)

Recharge flux (mm/year)

Boundary solution

0‐20 warming up

40

Rainwater

20‐50 leakage period

35

Produced water

50‐60 post‐leakage

40

Rainwater

While generally low, leakage (the combination of advective and diffusive migration of fluids) from acomposite liner (geomembrane (GM) combined with either a compacted clay liner or a geosynthetic clay
liner) cannot be avoided and is mainly due to the fact that a GM installed as part of liner system generally
will likely have some holes (2.5 to 5 holes per hectare being most commonly assumed, Rowe et al. 2004;
Rowe and Hosney, 2010; Rowe, 2012). Holes may form as a result of (i) manufacturing defects, (ii) handlingof the GM rolls, (iii) on‐site placement and seaming, (iv) cleaning of residue from a water holding pond, and(v) stress cracking as the GM ages (Rowe, 2012). Leakage from a single GM with 2.5 holes per hectare(leakage head or water depth of 5 m typical of a water holding pond) was calculated to be 1,000 lphd4(1.2×10‐9 m/s) and 4,000 lphd (4.6×10‐9 m/s) for 0.5 and 1 mm radius holes, respectively (Rowe, 2012).
In Australia design requirements for storage basins are stipulated by the QLD Department of Environment
and Resource Management “Manual for Assessing Hazard Categories and Hydraulic Performance of Dams”(DERM, 2012) and the NSW Dam Safety Committee (DSC) requirements (NSW Government, 1978). Further
relevant guidance regarding liner design may be obtained from DITR (2007) for tailings management; acompacted clay liner would normally be expected to achieve a saturated hydraulic conductivity of less than
10‐8 m/s.
The 35 mm/y (~10‐9 m/s) leak rate chosen here is assumed to be typical for a design with a single
geomembrane liner, or a compacted clay liner if sufficiently thick. While lower leak rates may be obtainedwith geosynthetic clay liners and composite liners, the purpose of selecting 35 mm/y was to impose an
upper bound estimate for the water flux and assess the natural attenuation capacity of soil under suchcircumstances.

4lphd = liters per hectare per day

18

The soil profile is assumed 1‐m deep, with three soil layers: 0‐0.3 m, 0.3‐0.7 m, and from 0.7‐1.0 m. The van
Genuchten soil hydraulic properties were taken from Bennet (2012). These soil hydraulic properties were
calculated on the basis of the pedotransfer functions of Minasny and McBratney (2002) using soil data
points within the Cox’s Creek catchment, NSW. For three soil horizons particle size distribution and the bulk
density from the SALIS (New South Wales Soil And Land Information System) dataset were used as
predictor variables in the pedotransfer functions. From a total of six soil types identified from a soil survey(Tenosols, Dermosols, Vertosols, Chromosols, Sodosols, Kandosols), Vertosols were most prominent with
84 out of 143 soil profiles (59%). Mean Vertosol hydraulic properties were therefore selected here for thesimulations (Table 2.2).

Table 2.2 Mean van Genuchten soil hydraulic properties for Vertosols (average across the Cox’s Creak Catchment
area, NSW) (source: Bennett, 2012)

Soil layer3Θr(cm /cm3)3

Θs(cm /cm3)

α
(1/m)

n
(‐)

Ks
(m/day)l(‐)

1 (0‐0.3 m)

0.059

0.515

8.3

1.217

6.04

0.5

2 (0.3‐0.7 m)

0.066

0.538

7.4

1.190

4.51

0.5

3 (0.7‐1.0 m)

0.070

0.515

7.9

1.150

3.35

0.5

Bulk density for the three soil layers is 1.32, 1.42 and 1.45 g/cm3 for layers 1, 2 and 3, respectively. The 1‐mnumerical domain was discretised in 100 finite elements, each 0.01 m long. The numerical grid, the threesoil layers and four observations nodes for detailed output are shown in Figure 2.3. Note that this grid had
to be refined for the simulations with the chemical limonene to achieve an acceptable mass balance; asmaller discretisation at the soil surface was implemented based on a nodal density value of 0.1 applied tothe top model node.

Figure 2.3 Finite element grid with soil layers (left) and location of four observation nodes (right)

19

Total simulation time ranged from 5 to 125 sec on Personal Computer with an Intel Core i5‐2540M CPU and
2.6 GHz. Simulated water content (Figure 2.4) time series show typical patterns linked to the warming‐up
period, the leakage period with a lower recharge rate, and again a higher recharge for the third period. At
the deeper depth of 50 cm, the water content is higher (0.35 cm3/cm3) due to the different hydraulicproperties in this soil layer (Table 2.2). At all other depths water content is about 0.305 cm3 /cm3 during theleakage period.

Figure 2.4 Calculated soil water content at five observation depths. Depths 2‐20 cm belong to soil layer 1, depth 50
cm belongs to soil layer 2

2.3.2 SOIL GEOCHEMICAL MODEL
The two most important parameters determining chemical attenuation in soil are the soil‐water partition
coefficient Kd and the first‐order degradation constant µ. For nonpolar organic chemicals, Kd is strongly
related to the organic carbon in soil (Scow and Johnson, 1997); the same is true for the degradation
constant µ. Generally, the higher the organic carbon content, the higher is Kd. Dry mineral surfaces are also
known to adsorb organic compounds. Upon wetting, however, water generally causes organic compounds
to desorb from mineral sorption sites; the small remaining fraction of mineral sorption is generally muchsmaller than the sorption by organic matter (Chiou, 1990).
Several studies have investigated the effect of sorption on biodegradation rates. When chemicals become
partitioned between adsorbed and dissolved phase, either the dissolved phase only or both the dissolved
and sorbed phase may be metabolized. In case rapid exchange occurs between dissolved and equilibrium
sorbed chemical, all material in the labile pool may be available to microbes (Hamaker and Goring, 1976). If
a constant equilibrium is maintained between a dissolved substrate available to microorganisms and its
sorbed, unavailable form, sorption should affect biodegradation kinetics only by lowering the amount of
substrate metabolised in each time step. This assumes biodegradation rates are independent fromchemical concentration. Scow and Johnson (1997) argue that when sorption/desorption kinetics are very
fast compared to microbial kinetics, kinetics resembling liquid culture biodegradation rates will likely occur.
Some studies showed that only the dissolved phase was metabolised and that both attached andsuspended organisms were responsible for degradation (Ogram et al., 1985). Different microbial strains
have been shown different abilities in metabolising sorbed and dissolved chemicals: some can utilise the20sorbed compound, whereas others can only metabolise the dissolved compound, as was the case fornaphthalene (Guerin and Boyd, 1992, 1993).
In HYDRUS‐1D, biodegradation can be applied to either the dissolved phase, the adsorbed phase, or bothphases. If applied to both phases, different degradation rates can be applied to dissolved and adsorbed
phases. Because degradation rates are generally only available for the dissolved phase, often derived fromsolution cultures or batch tests, identical values are commonly applied to both phases. We here assume
that both adsorbed and dissolved chemicals are metabolised, and their biodegradation rate is identical.
Microbial biomass (fungi and bacteria) is affected by soil moisture and carbon content (Cookson et al.,2008; Araújo et al., 2009). The variation of carbon content with soil depth is therefore a useful indicator of
microbial biomass variation, and thus of the biodegradation rate (Anderson, 1984). Combining this with theprevious model assumption that sorption does not affect the ability for biotransformation, delivers a model
where both sorption and biodegradation are linked to the organic carbon content (see further in Section
2.3.2.2).
In soil, organic carbon is generally highest in the top layers and decreases with depth. This implies that if Kd
and µ are determined by organic carbon content, these values will decrease with increasing soil depth. For
this study to have some local relevance for Australian soils, soil data from the Liverpool Plains (NSW) was
reviewed and soil organic carbon data extracted and summarised as function of soil depth.

2.3.2.1 Organic carbon versus depth
Detailed soil data from the Integrated Catchment Management Project (Ringrose‐Voase et al., 2003) were
evaluated and soil organic carbon data extracted for three soil types: Vertosols, Chromosols, and Sodosols.
The Vertosols comprise a combination of Grey, Black, Aquic, and Red Vertosols. Organic carbon data as afunction of soil depth are shown in Figure 2.5. As expected, the highest carbon content occurs in the top 10
cm with a geometric mean value of 2.17%, then decreases somewhat exponentially with depth until itreaches a minimum background value of approximately 0.14% at the depth of 150 cm. From then onwards,
it remains more or less constant with depth. While an exponential model best describes the depth‐
dependency of organic carbon (Kookana et al., 1995), a linear approximation was derived for use in
HYDRUS‐1D. The average value of 2.17 % or 0.0217 g/g will be used to derive Kd values from KOC values andfOC, where fOC = 0.0217 g/g (see section 3.2.4).

21

Figure 2.5 Soil organic carbon versus soil depth and modelled organic carbon depth‐dependency (data from
Ringrose‐Voase et al., 2003)

2.3.2.2 Depth reduction of the retardation and biodegradation constants.
A new module was developed in HYDRUS‐1D to automatically update Kd and degradation constant µ as theorganic carbon decreases with depth, following the scheme suggested by Kookana et al. (2005). The
retardation and degradation constants are reduced by a depth‐dependent function, which has a constantvalue (1) in the top of the soil profile (above aDepth), then decreasing linearly down to a depth of bDepth.
Below this depth the reduction function has the value of cValue (Figure 2.6). Cvalue is calculated as theratio of organic carbon at bdepth to organic carbon at aDepth (i.e. the mean value between soil surface andaDepth). In the example of Figure 2.5, the mean organic carbon % from surface to aDepth is 0.65, and thecarbon content at cValue is 0.12. As result, cValue = 0.12/0.65 = 0.185.
00.2

Depth‐reduction factor
0.4
0.6
0.8

1

1.2

0
20
40

Depth [cm]

60
80
100
120
140
160
180
200

Figure 2.6 Principle of modelling the depth‐dependency of organic carbon in HYDRUS‐1D. Left: original organiccarbon data; right: depth‐reduction factor.

The parameters of this function are read from the input file Depth_Red.in, which looks as follows:22and which needs to be placed into the project folder. When this file does not exist, or the logical variable
lDepthRed is equal to false, the depth reduction is not considered. Note that the z‐coordinate of the surface
is equal to zero, and the axis is positive upward (the depths are thus in negative values).
The new executable (h1d_calc.exe) has to be either placed into the HYDRUS‐1D installation folder and thenit can be run directly from GUI, or can be run outside of the GUI. Then one has to place next to the exe file a
new file Level_01.dir, which contains the path to where the project is located:

Figure 2.7 illustrates: (i) the initial organic carbon data versus depth and the derivation of the parameters
aDepth, bDepth, cValue, (ii) the depth‐reduction factor as calculated in HYDRUS‐1D, (iii) the depth‐
dependency of Kd, and (iv) the depth‐dependency of the degradation constant as implemented in HYDRUS‐
1D. Note the curved lines in Figure 2.7c and d are due to the logarithmic X‐axis.

Figure 2.7 Example demonstrating organic carbon profile (a), the derived depth‐reduction factor (b), the depth‐
reduction factor applied to the distribution coefficient for three chemicals involved in first‐order transformation
reactions (c) and the first‐order degradation constant for the same three chemicals (d)When the principle of depth‐reduction factor is applied to the organic carbon data from the Liverpool
Plains (see section 2.3.2.1), the following parameters are derived: aDepth = ‐0.1, bDepth = ‐150, cValue =0.136/2.17 = 0.063. These values have been included in the Depth_Red.in file when running HYDRUS‐1D.

23

3 Natural attenuation parameters for typicalorganic compounds

3.1 Organic compounds considered in this assessment
The assessment considers two broad categories of chemicals: (i) chemicals that naturally occur in coal seam
pore‐waters and that could end up in flowback and/or produced water, albeit at low concentrations, and(ii) chemicals associated with hydraulic fracturing additives such as surfactants, solvents and biocides. The
first category of chemicals tested here includes the phenolic compounds phenol and 2‐methylphenol, andthe polycylic aromatic hydrocarbon (PAH) naphthalene. The second category tested here includes thehydraulic fracturing additives 2‐butoxyethanol, limonene and bronopol (Table 3.1). Where data on
transformation products were readily available, these have been included in Table 3.1.
Table 3.1 Chemical identification information on CSG‐related chemicals.
Name

CAS No.

Chemical Structure

ChemicalIUPAC name

Parentcompound (P)/transformation
products (D)formulaPhenol108‐95‐2

C6H6O

PhenolP

1,2‐Catechol

120‐80‐9

C6H6O2

Benzene‐1,2‐diol

D13270‐98‐2

C6H6O4(3E,5E)‐6‐hydroxy‐2‐oxohexa‐3,5‐dienoic
acid

D2

95‐48‐7

C7H8O

Other name:

P

(1,2‐
dihydroxybenzene)

HMSA
2‐hydroxymuconic
acid‐6‐semialdehyde

2‐methylphenolo‐cresol

3‐methylcatechol

488‐17‐5

C7H8O2

3‐Methylbenzene‐
1,2‐diolD

Naphthalene

91‐20‐3

C10H8

Bicyclo[4.4.0]deca‐
1,3,5,7,9‐penteneP

cis‐1,2‐dihydroxy‐1,2‐dihydronaphthalene

51268‐88‐3

C10H10O2(1R,2S)‐1,2‐dihydronaphthalene‐
1,2‐diolD

2‐butoxyethanol

111‐76‐2

C6H14O2

2‐Butoxyethanol
Other name: ethylene/

glycol monobutyl
ether
24

Limonene

138‐86‐3

C10H16

1‐Methyl‐4‐(1‐methylethenyl)‐
cyclohexene/

Bronopol52‐51‐7

C3H6BrNO42‐bromo‐2‐
nitropropane‐1,3‐diolP

Formaldehyde

50‐00‐0

CH2O

MethanalD

Phenolic compounds such as phenol and 2‐methylphenol have been observed in both low‐rank andbituminous coals (Siskin and Aczel, 1983) and these are likely to be derived from cleavage of aromaticcompounds as well as transformation of plant cell walls under high pressure and temperature during coalformation. In the US phenolic compounds such as dimethylphenol have been detected in coal seam gas
produced water in concentrations up to 5.89 mg/L (Orem et al., 2007). Phenol was detected at a level of 0.3
μg/L in Australian coal seam gas water holding ponds of the Walloon production area (Stearman et al.,2014). Specific drinking water guidelines for phenols currently do not exist (Orem et al., 2007; NHMRC,
2011; WHO, 2011). Therefore, the effect of chronic, long‐term exposure to phenolic compounds is not wellestablished. For the protection of aquatic life in freshwater ecosystems a threshold of 4.0 µg/L wasrecommend by the Canadian Council of Ministers of the Environment (CCME, 1999). For aquatic ecosystem
protection (95% protection level) the Australia & New Zealand water quality guideline for phenol is 320µg/L (ANZECC & ARMCANZ, 2000).
PAHs such as naphthalene belong to the naturally occurring compounds also known as geogenic
compounds. Owing to their low water solubility (de Maagd et al., 1998), PAH contamination of water isgenerally considered to be of lesser concern. Nevertheless, they are of significance due to the known
hazards, such as carcinogenicity, that they can present for human and environmental health (EC, 2003). For
aquatic ecosystem protection (95% protection level) the Australia & New Zealand water quality guideline
for naphthalene is 16 µg/L (ANZECC & ARMCANZ, 2000). Analysis of coal seam gas produced waters fromthe Powder River Basin (WY, USA) indicated PAHs were the most commonly observed group of organic
compounds; total PAH concentrations ranged up to 23 μg/L (Orem et al., 2007). In a more recent study
total PAH concentrations in coal seam gas produced water from the US were shown to exceed 50 ‐100 μg/L
(Orem et al. 2014). Based on 47 sampled wells of the Walloon coal seam gas production area, Stearman etal. (2014) reported only seven wells with detectable levels of PAHs, including naphthalene andphenanthrene. The maximum naphthalene and phenanthrene concentrations from a single well were 0.046
μg/L and 0.02 μg/L, respectively. Of all detected PAHs, naphthalene was detected at the highest
concentration. Naphthalene was detected at a level of 0.06 μg/L in Australian coal seam gas water holding
ponds of the Walloon production area (Stearman et al., 2014).
2‐butoxyethanol or 2BE is a surfactant used as pre‐flush hydraulic fracturing additive and acid additive.
Large quantities have been used in the US and Canada (US Congress Report, 2011; Wylde and O’Neil, 2011).
It is also one of the hydraulic fracturing chemicals used in Australian coal seam gas operations (APPEA,
2014). The role of the pre‐flush additive is to preferentially wet the formation to allow for better
propagation of the fracture through the production zone and post‐fracture production of the load water,
and ultimately, hydrocarbons (Wylde and O’Neil, 2011). Despite being readily degradable, 2BE is also
known to bioaccumulate and is generally toxic (Harris et al., 1998). 2BE was declared a Priority Existing
Chemical under Australia’s National Industrial Chemicals Notification and Assessment Scheme. The
assessment of 2BE demonstrated it is highly mobile in soil and water and has been detected ingroundwaters underlying municipal landfills and hazardous waste sites in the US.
Bronopol is a biocide used in hydraulic fracturing wells in the US (US Congress Report, 2011; Kahrilas et al.,2014) and Australia (QGC, 2012). It is toxic to marine invertebrates such as oysters; the observed LC50 is 1.6
25

mg/L for Daphnia magna (Sigma‐Aldrich, 2014) and 0.77 mg/L for the Eastern Oyster (US EPA, 1995).
Substantial spills into surface waters or streams may therefore have noticeable ecotoxicological effects onaquatic species. Bronopol was shown to produce tris(2‐hydroxymethyl‐2‐nitropropane‐1,3‐diol) (US EPA,
1995). Bronopol has been reported to hydrolyze within 3 h at 60 °C and pH 8, producing formaldehyde,
nitrosamines, and other molecules (Swenberg et al., 1980; Dunnett and Telling, 1984; Challis and Yousaf,
1990; Loeppky, 1994; US EPA, 1995). Although, the parent compound (bronopol) is rather short‐lived in theenvironment, its degradation products are still toxic and more persistent (Douglass et al., 1978; Swenberg
et al., 1980).
Limonene is a chemical additive of water and guar based hydraulic fracturing fluid systems; its use has beenreported for the US (US Congress Report, 2011) and Australia (Santos, 2013). Limonene is a terpene
hydrocarbon and is increasingly being used as a solvent for cleaning purposes. Terpenes such as limonene
are replacements for xylene‐ and toluene‐based solvents. They are derived from plant products, includingorange peels and pine sap. Compared with aromatic solvents, terpenes have good solvency, and arebiodegradable, less toxic, and less flammable.

3.2 Degradation in soil
Biodegradation involves biochemical reactions within the soil sub‐surface through which a parent
compound is changed or transformed to organic or inorganic end products or via a series of intermediates.
It is an important mechanism for the removal of organic compounds in soil (Loehr, 1989). Aerobic biotic
degradation rates (half‐life) and pathways for organic compounds in soils are influenced by many factors
including; their initial concentration at the time of release to the environment, the toxicity of a given
compound and its daughter compounds, the physical and chemical properties of the compound in question
and the physical, chemical and biological properties of the soil (Scow and Johnson, 1997). In the sections
below, we briefly present and summarise the previously reported degradation pathways and aerobic biotic
degradation half‐lives where available, for some of the organic compounds reviewed in this assessment.
Aerobic rather than anaerobic degradation rates are considered appropriate in the current assessment
involving shallow and well‐aerated soil.
Biodegradation studies and the parameters derived for modelling (e.g., biodegradation rate) often involve
tests in solution culture and batch systems, with experimental conditions often different from those in soil.
Two important questions arise: (i) whether biodegradation rates measured in solution culture areappropriate to soil, and (ii) whether parameters measured in batch systems can be extrapolated to dynamic
flow systems such as real soil. The few comparative studies reported to date suggest differences in kinetic
parameters are mainly due to indirect effects (differences in solution chemistry between solution culturesand solutions with soil or sediments present) rather than direct effects of sorbing surfaces on
microorganisms (Scow and Johnson, 1997). When batch‐derived biodegradation parameters are applied tocoupled flow and transport systems, mass‐transfer limitations may occur which might require correction of
the batch‐derived parameters (Scow and Johnson, 1997). To address these uncertainties aroundbiodegradation parameters, introduced when solution cultures and batch systems are the primary sourceof degradation tests, we here define a range of parameter values rather than using single values andsubsequently run the simulations multiple times (i.e. for minimum, mean, and maximum parametervalues).

3.2.1 PHENOLIC COMPOUNDS
Phenol (parent compound)
The degradation pathway of phenol is illustrated in Figure 3.1. Once phenol is released to the soil
environment, it has been found to initially degrade to catechol and then 2‐hydroxymuconic acid‐6‐
semialdehyde (HMSA) (Omokoko et al., 2008). Subsequent further degradation by hydrolysis can result in
the formation of compounds such as pyruvate and acetaldehyde. Degradation studies of phenol in soil
conducted by Scott et al. (1983) and Shiu et al. (1994) have provided important insights into the range in26

half‐life for phenol (hours to days) and the importance of either the initial concentration in soil or the pH of
the soil. Further degradation products such as pyruvate are important chemical compounds inbiochemistry; pyruvate is the output of the metabolism of glucose. Because of their inherently low toxicity,
the transformation products pyruvate and acetaldehyde are not considered in the current assessments.
Only the first three compounds of the phenol degradation pathway (phenol, catechol and HMSA) areconsidered in the coupled transport‐sorption‐degradation calculations.

Figure 3.1 Reported degradation pathway for phenol. Rectangle indicates compounds included in the current
assessments (Omokoko et al. 2008)

Catechol (daughter compound)
Catechol is the first degradation product of phenol (Figure 3.1). Depending on the degradation pathway,
similar compounds are formed as is the case for phenol including, HMSA, pyruvate and acetaldehyde(Zeyuallah et al., 2009). Soil‐based studies on the aerobic biotic degradation half‐life of catechol by Martin
et al. (1979) and Scott et al. (1983) have highlighted that its half‐life is far greater (weeks to months) thanthat of phenol. The stability of catechol in soil is influenced by its rapid polymerisation into new phenolicpolymers, incorporation into existing phenolic polymers by enzymes in the soil or by phenolases or
autoxidation (Martin et al., 1979). Similarly for phenol, the study by Stott et al. (1983) highlighted theinfluence of the initial concentration of catechol in soil, the soil pH and the type of soil on the range indegradation rate found.

2‐Hydroxymuconic acid‐6‐semialdehyde (HMSA) (daughter compound)
The second transformation product of phenol, 2‐hydroxymuconic acid‐6‐semialdehyde (HMSA; C6H6O4), has
found to be readily degradable in soil, with 95% of the initial concentration of HMSA degraded within 6days in the Zahn‐Wellens test (Luck, 1993). A biodegradation study on a similar compound (sorbic acid,
C6H8O2) conducted by the Chemicals Inspection and Testing Institute (1992) also found 83% biodegradation
after 2 weeks using an activated sludge seed, and an initial chemical concentration of 100 mg/L. Primary
aerobic biotic degradation rates for HMSA were also estimated in this assessment to be in the order ofhours to days, using the US EPA (2015b) BIOWIN biodegradability of organic chemicals software. Primarybiodegradation is the transformation of a parent compound to an initial metabolite. HMSA is furthertransformed into simple molecules, including pyruvate, citrate and acetaldehyde, used in the tricarboxylacid cycle through which microbes derive energy.

2‐Methylphenol (o‐cresol) (parent compound)
Ahamad et al. (2001) summarised literature reported metabolic pathways for o‐cresol degradation by
Pseudomonas in soil (see Figure 3.2). O‐cresol initially degrades to 3‐methylcatechol and subsequently
degrades to form 2‐hydroxy‐6 keohepta‐2,4 dieonate, followed by 2‐ketopent‐4‐eonate and 4‐hydroxy‐2‐
ketopentanoate. Degradation studies of o‐cresol in agricultural soils Loehr (1989) determined half‐lives
27

ranging between 1.6 to 5.1 days. Similar to the other phenolic compounds discussed here, reported
degradation rates appear to have been influenced by their initial concentration in soil, the pH of the soil
and factors including cation exchange capacity (CEC) and organic carbon content of the test soils.

Figure 3.2 Summary of reported metabolic degradation pathway for o‐cresol (Ahamad et al., 2001). Based on workby Dagley and Patel (1957); Nakagawa and Takeda (1962); Bayly et al. (1966); Ribbons (1966); Bayly and Wigmore(1973); Hughes et al. (1984). Rectangle indicates compounds included in the current assessments

3‐Methylcatechol (daughter compound)
The first degradation product of o‐cresol, 3‐methylcatechol, degrades to form compounds such as 2‐hydroxy‐6 keohepta‐2,4 dieonate. A degradation study using a pure bacterial culture by Tian et al. (2013)highlights the ability of the Rhodococcus sp. bacteria strain ZWL3NT to degrade 3‐nitrotoluene (3NT) to 3‐
methylcatechol (Figure 3.3); further degradation produces compounds as found in the degradation
pathway for o‐cresol (Figure 3.2). Owing to the inherently low toxicity of 2‐hydroxy‐6 ketohepta‐2,428

dieonate and subsequent transformation products, only o‐cresol and 3‐methylcatechol are included in thecurrent calculations.

Figure 3.3 Proposed pathway for 3‐methylcathechol degradation by the Rhodococcus bacteria (strain ZWL3NT) (Tianet al., 2013).

Furthermore, a study by Dobslaw and Engesser (2015) using pure cultures demonstrated the ability of
Burkholderia fungorum, a species of proteobacteria, to degrade toluene. The potential degradation
pathway proposed by Dobslaw and Engesser (2015) in Figure 3.4 has similarities to the one proposed byTian et al. (2013) (Figure 3.3). Aerobic biodegradation rates for 3‐methylcatechol were estimated in thisassessment to be in the order of days, using the BIOWIN software (US EPA, 2015b).

Figure 3.4 Potential degradation pathway of toluene by the Burkholderia fungorum FLU100 strain (Dobslaw andEngesser, 2015)

3.2.2 POLYAROMATIC HYDROCARBONS
Naphthalene (parent compound)
Naphthalene has been the subject of numerous degradation studies where bacteria in soil have degradednaphthalene to compounds such as naphthalene diol, salicylic acid, and catechol. Some pure culture studies
have shown bacteria utilise naphthalene as a source of carbon (Treccani et al., 1954), whilst others haveemphasised the ability of fungi to oxidise naphthalene (Cerniglia, 1984). Oxidation pathways for culture
conditions published in Cerniglia (1984) include five metabolites of naphthalene along the degradation
pathway: cis‐1,2‐dihydroxy‐1,2‐dihydronaphthalene, 1,2‐dihydroxynaphthalene, cis‐o‐hydroxybenzalpyruvic acid, salicylic acid, and catechol (Figure 3.5). Biodegradation has been shown toremove naphthalene from soil, with an estimated half‐life of more than 80 days (Howard, 1989).
Naphthalene is very toxic to aquatic organisms, with PNEC values of 2.4 microgram/L (EC, 2003). As far as
29human health is concerned, combined exposure may result in haemolytic anaemia, inhalation toxicity andcarcinogenicity (EC, 2003).

Figure 3.5 Proposed catabolic pathway for naphthalene by soil bacteria (Denome et al., 1993; Kiyohara et al., 1994;
Goyal and Zylastra, 1997). Rectangle indicates compounds included in the current assessments

3.2.3 HYDRAULIC FRACTURING ADDITIVES
2‐Butoxyethanol (parent compound)
Degradation studies of 2‐butoxyethanol have received little attention in the literature and therefore apaucity of data exists. A review of the toxicological profile for 2‐butoxyethanol by ATSDR (1998) did not
identify any studies that report degradation products or known pathways. Hydrolysis of 2‐butoxyethanol isunlikely, as it contains both alcohol and ether functional groups, which are generally resistant to hydrolysis
30

(Harris, 1990). Aerobic biodegradation studies of 2‐butoxyethanol using sewage for inocula andmineralisation (of the compound to carbon dioxide and water) as a measure of biodegradation indicated,
5% mineralisation in 5 days (Dow, 1993), 57‐74% in 10 days (Dow, 1993; Price et al., 1974), and 72‐88% in
20 days (Dow, 1993; Price et al., 1974). Waggy et al. (1994) determined the biodegradation of 2‐
butoxyethanol to be 47% in 5 days, 70% in 15 days and 75% in 28 days, using a closed bottle test withsettled sewage as a microbial inoculum. The aerobic biodegradation half‐life of 2‐butoxyethanol in surface
water has been estimated by Howard et al. (1991) to range between 7‐28 days. An aerobic biodegradation
half‐life was also estimated as part of this assessment to be ~416 hours using BIOWIN (US EPA, 2015b).

Limonene (parent compound)
Similar to 2‐butoxyethanol, limonene does not have functional groups for hydrolysis, its cyclohexene ringand ethylene group are known to be resistant to hydrolysis and it therefore is an unlikely process interrestrial or aquatic environments (US EPA, 1994). Biotic degradation of limonene by some species of
microorganisms has been reported. For example, Penicillium digitatum, Corynespora cassiicola and Diplodia
gossypina (Abraham et al., 1985), and a soil strain of Pseudomonas sp. (PL strain) (Dhavalikar &Bhattacharayya, 1966; Shulka & Bhattacharayya, 1968). MITI (1992) demonstrated that limonene wasreadily biodegradable with 41–98% degradation by biochemical oxygen demand in 14 days; testing wasunder aerobic conditions in a standard test specified by the OECD (OECD, 1981).

Bronopol (parent compound)
Bronopol can be stable to hydrolysis under normal/ambient conditions, but susceptible to hydrolysis when
exposed to elevated temperatures and alkaline conditions (US EPA, 1995). Degradation pathways forbronopol vary depending on the environmental conditions and medium. Bronopol has been found todegrade to formaldehyde, 2‐hydroxymethyl‐2‐nitropropane‐1,3‐diol (tris) and 2‐bromo‐2‐nitroethanol in areview summarised by the United States Environmental Protection Agency (US EPA, 1995). Other
degradation products consist of bromo‐nitroethane, bromo‐ethanol, and bromo‐nitroethanol (Wang et al.,2002). In ambient laboratory conditions, the half‐life for bronopol due to hydrolysis was determined to beapproximately 18 years at pH 4, about 1.5 years at pH 6 and about 2 months at pH 8. At an elevatedtemperature of 60oC and a pH of 4 and 8, half‐lives were found to be much shorter, 4 days and 3 hours,
respectively (US EPA, 1995). For the purpose of this study, it was assumed that bronopol will degrade toformaldehyde.

Formaldehyde (daughter compound)
There are limited data available on the degradation pathway for formaldehyde in soil and sediment. A
number of studies however, have reported that formaldehyde is readily degraded by soil bacteria such that
accumulation in soil does not occur (US EPA, 1985; IPCS, 1989). Similarly, the reported degradation rates ina handful of studies have all cited Howard et al. (1991), who estimated a soil half‐life of 24–168 h, based on
estimated aqueous aerobic biodegradation half‐lives.

3.2.4 SUMMARY OF CHEMICAL PARAMETERS OF ORGANIC COMPOUNDSFor each of the organic compounds considered in the current assessment, several chemical parameters
relevant to the calculation of their transformation in soil were compiled from a literature review. Two setsof parameters were considered: (i) parameters required for simulation of attenuation and transport
processes in soil (degradation pathway; sorption‐related parameters such as KOW, KOC, Kd; and half‐lives),and (ii) additional parameters that provide auxiliary information not directly used in the simulations(solubility, Henry constant, toxicity).

31

Table 3.2 summarizes the two sets of parameters; the data is organised for four groups of chemicals(naturally occurring phenolic compounds and PAHs, and chemical additives in hydraulic fracturing fluids),
and, within each group, the parent compound is listed first followed by one or more transformation
compounds (daughter compounds).
In deriving sorption values Kd, the following procedure was used:
1. Preference was given to using soil‐based Kd values if available; this was found to be the exception.
2. Calculated Kd as Kd = fOC×KOC, where KOC is the soil organic carbon partition coefficient, fOC is thefraction of organic carbon in the top soil equal to 0.0217 g/g (see section 2.1.3); this is the mostfrequent method applied here.
3. If KOC is not available, then KOC is estimated from KOW using EPI (Estimation Program Interface)models (US EPA, 2011).
The data from Table 3.2 were used to derive parameter ranges for the purpose of simulations with
HYDRUS‐1D. Minimum, mean, and maximum values for Kd and half‐life (t1/2) were obtained (Table 3.3).
Because HYDRUS‐1D uses first‐order degradation constant values (µ) rather than half‐life, µ was calculated
for each t1/2 value using µ = ln2/t1/2 = 0.693/t1/2. Identical values for mean, minimum and maximum indicate
only a single value was available from the review.

32

Table 3.2 Summary of the chemical parameters of organic compounds reviewed in this study.
Compoundgroup

Parent Compound

Aqueous
Solubility
at 25 OC
(mg/L)

Octanol‐
Water
Partition
Coefficient(Log Kow)

Henry's law
constant (KH)
(atm.m3/mol)Primary degradation
pathway

Soil Organic
Carbon‐Water
Partitioning
Coefficient(Koc) (L/kg)

Partitioncoefficient(Kd) (L/kg)

Aerobic
bioticdegradation(half‐life)

Toxicity

Phenolic
compounds

Phenol82,800*1.46*, [1]3.31E‐7*

Hydrolytic route(aerobic):
catechol =>2‐hydroxymuconic
acid‐6‐semialdehyde=> 2‐oxopent‐4‐
dienoate =>pyruvate

16[20]

0.35‐1.9#(soil)

2.7 – 3.5[6] hMutagen class3

Catechol (1,2‐dihydroxybenzene)

Polycyclicaromatichydrocarbon

461,000*

0.88*–
0.9[1]

1.2E‐9*2‐Hydroxymuconic
acid‐6‐semialdehyde

3.3E5* –414,800‐0.44* –0.36[30]

2.62E‐10*

2‐Methylphenol(o‐cresol)

25,900*1.95 –
2.17[26]

1.2E‐6*

3‐Methylcatechol

16,480* –27,9101.58*, [30]6.4E‐11*

Naphthalene31*

3.29[1]

4.4E‐4*Microbial
degradation route:3‐methylcatechol =>2‐hydroxy‐6keohepta‐2,4
dieonate =>2‐ketopent‐4‐eonate=> 4‐hydroxy‐2‐
ketopentanoate
Microbial
degradation route:=> cis‐1,2‐dihydroxy‐
1,2‐

39 – 91(soil)[6]

98 – 552[21] h[7]2900‐3100(sediment)
118[22](soil)(soil)(soil)
2.6#,[22](soil)

183 – 365days [24 ]25[23](kaolinites)(soil)

0.207[33]0.0045#

Hours todays[30]

Low toxicity

21.9[21](soil)

0.47#,[21](soil)

1.6 – 5.1[25]days (soil)

Possible humancarcinogen47[8]1.0#,[8]7[36] days
(soil)

136[9]

2.9#, [9]Days toweeks[30]Harmful to fish;
toxic to green
algae*

870.9[28]200 – 1470[27]1500[8]87.37#, [28]80 days[16](soil)

Very toxic toaquaticorganisms;
Combined
exposure:

18.9#
4.3 –

42‐d NOEC for
Eisenia foetida= 500 mg/kg dw(growth) and2000 mg/kg dw(mortality)

33

Chemical
additives inhydraulicfracturingcis‐1,2‐Dihydroxy‐1,2‐dihydronaphthalene

8,121

1.07[30]

2.82E‐92‐Butoxyethanol

1E6*

0.83*, [1]Sweet orange oil

7.57

*

4.57

[35]

34

2E5[15] ;2.5E5*‐0.64[29]1288[10]

31.9#,[27]Human health:haemolytic
anaemia,
inhalation
toxicity andcarcinogenicity

32.6#, [8]27.9#, [10]4.5[9]

0.097#, [9]Days[30]

Not bio‐accumulative or
persistent

2.08E‐8*, [8],[16]8*, [1], [11]1.5#, [1], [11]5.44E‐6(calculated)[2]*, [2]#, [2]

416 hr [30](soil)

HHE: C, R, HD,
DD, CN, LD, KP,
RI, A, HI

0.032

$

(limonene)

Bronopol (2‐bromo‐2‐
nitropropane‐1,3‐diol)dihydronaphthalene=> 1,2‐dihydroxy‐naphthalene, cis‐o‐hydroxybenzal‐
pyruvic acid =>salicylic acid =>catechol

1.3E‐11[29]

6.9

1.3

7 – 28 days
[16]
(soil)
Products formed
from the hydroxyl
radical reaction withlimonene are 4‐
acetyl‐1‐
methylcyclohexene[32], [33], [34],ketoaldehyde[32], [34],formaldehyde, 3‐
oxobutanal, glyoxal,
and a C10
dicarbonyl[33]1324Formaldehyde,
nitrosamines; tris (2‐hydroxymethyl‐2‐
nitropropane‐1,3‐
diol)

[12]

28.7

#, [12]

1300[13]28.2#, [13]1259[8]27.3#, [8]0.93[29]0.02#, [29]

EE: AAT

2.3 – 18
days[17]

In the aquatic
environment,limonene
exhibits highacute toxicity
to fish andDaphnia(toxnet)60 days (pH8) – 2 years(pH 6)[29]LowmammaliantoxicityFormaldeyde(formalin; methanal;
Methylene oxide;
formol; Oxomethane)

4E5*, [5]0.35[3]

2.2E‐2 – 3.4E‐2[18]

[4]

[19]

0.65

2.2E‐2 – 3.4E‐2

Formic acid andcarbon monoxide. In
water or soil, formic
acid is expected to
rapidly biodegrade.

3.6[14]0.08#, [14]24 – 168
hours [16](soil)

Unlikely tocause adverse
effects onterrestrial or
aquaticorganisms;
probably
carcinogenic tohumans(inhalation)[31]*

Listed in EPI (Estimation Program Interface) SuiteTM models (US EPA 2011; EPI Suite. Ver. 4.1. Jan, 2011. Available from, as of Sept 23, 2011:
http://www.epa.gov/oppt/exposure/pubs/episuitedl.htm); Koc calculated from Kow; # calculated as Kd = foc x Koc with foc = 0.0217 g/g; $ toxnet http:://toxnet.nlm.nig.gov; HHE = human health effect;
EE: environmental effect; AAT = acute aquatic toxicity (Stoiber et al. 2015)

References: [1] Hansch et al., 1995; [2] ASTER, 1995; [3] Hansch and Leo, 1995; [4] ATSDR, 1999; [5] Pickrell et al., 1983; [6] Scott et al., 1983; [7] Isaacson and Frink, 1984; [8] HSDB, 1995; [9] US EPA,
2015a; [10] Sabljic et al., 1995; [11] Lyman et al., 1982; [12] Chemspider, 2015; [13] Meylan et al., 1992; [14] Lyman et al., 1990; [15] Yalkowsky and He, 2003; [16] Howard et al., 1991; [17] MITI,
1992; [18] WHO, 2002; [19] NICNAS, 2006; [20] Boyd et al., 1983; [21] Shiu et al., 1994; [22] Boyd, 1982; [23] Haderlein and Schwarzenbach, 1993; [24] Stott et al., 1983; [25] Loehr, 1989; [26] Gaffney
et al., 1987; [27] ATSDR, 2010; [28] Karickhoff, 1981; [29] Kahrilas et al., 2014; [30] US EPA, 2015b; [31] IARC, 1995; [32] Arey et al., 1990; [33] Grosjean et al., 1992; [34] Hakola et al., 1994; [35] Li and
Perdue, 1995; OECD, 1998 [36].

35Table 3.3 Sorption (Kd), half‐life (t1/2) and degradation parameters (µ) used as input for HYDRUS‐1D simulations
Chemical compound

Half‐life t1/2 (days)
mean
min
max
6.84
0.11
23

Decay constant µ (days‐1)
mean
min
max
0.101
0.03
6.161

Phenolmean
1.38

Kd (L/kg)
min
0.35

max
1.9

Catechol

13.8

2.6

25

274

183

365

0.00250.00190.0038MHSA

0.00450.00450.0045

2

2

2

0.347

0.347

0.347

2‐Methylphenol

0.74

0.47

1

4.57

1.6

7

0.152

0.099

0.433

3‐Methylcatechol

2.9

2.9

2.9

7

7

7

0.099

0.099

0.099

Naphthalene

33.83

4.3

87.37

80

80

80

0.00870.00870.0087cis‐1,2‐Dihydroxy 1,2
dihydronaphthalene

0.097

0.097

0.097

2

2

2

0.347

0.347

0.347

2‐Butoxyethanol

1.4

1.3

1.5

6.26

0.29

17.33

0.111

0.04

2.377

Limonene

42.05

22.35

103.7

10.4

2.8

18

0.067

0.039

0.248

Bronopol

0.02

0.02

0.02

60

60

60

0.012

0.012

0.012

Formaldehyde

0.08

0.08

0.08

4

1

7

0.173

0.099

0.693

Based on Equation 6, the retardation factor R was calculated for the top layer assuming a water content of
0.305 (cm3 cm‐3) and bulk density of 1.32 g/cm3. Mean retardation factors range from 1 to 1605, while
maximum R values are as high as 3957 (Table 3.4).
Table 3.4 Approximate retardation factors R calculated for a water content of 0.305 (cm3 cm‐3) and bulk density of
1.32 g/cm3 (representative for the layer 1 during the leak period)
Chemical compoundmean

R (L/kg)min

Phenol54

14

73

Catechol

527

100

955

MHSA

1

1

1

2‐Methylphenol

29

19

39

3‐Methylcatechol

112

112

112

Naphthalene

1292

165

3334

cis‐1,2‐Dihydroxy
1,2dihydronaphthalene

5

5

5

2‐Butoxyethanol

54

51

58

Limonene

1605

854

3957

Bronopol222Formaldehyde

4

4

4

36

max

4 Detailed description of the simulation cases

Sensitivity analyses are undertaken in Section 4.1 to illustrate the combined effect of sorption andbiodegradation on chemical concentration in soil following release from a surface source. These initial
calculations use hypothetical compounds with assumed parameter values.
Migration of specific compounds in soil is discussed in Sections 4.2, 4.3, and 4.4. Literature‐based values for
sorption and biodegradation are used, while a hypothetical unit source concentration of 1 mg/L is assumed.
Because of the latter assumption, results are generic and will be used to derive dilution attenuation factors.
Concentrations for other source concentrations can be readily obtained from those dilution attenuation
factors.

4.1 Sensitivity analysis

Concentration (mg/L)

Prior to the discussion of attenuation behaviour of particular CSG‐related chemicals, sensitivity analyses
were undertaken to illustrate the combined effect of sorption and biodegradation on chemical
concentration in soil following release from a surface source. The first set of calculations assumed
chemicals migrate through soil according to the advection‐dispersion process; sorption onto the organiccarbon in soil was accounted for, while biodegradation was not considered. Three values for the
distribution coefficient Kd were considered: 5, 10 and 20 L/kg. The hypothetical chemical source consistedof a release at the soil surface of 1000 mg/L during a period of 30 years. The water flux into the soil had
three characteristic periods: a warming up period of 20 years with a water flux of 40 mm/year, followed by
a 30‐year period during which the chemical source existed considering a water flux of 35 mm/year,
followed by a 110‐year period to allow for complete solute breakthrough with a water flux of 40 mm/year.
Chemical breakthrough curves were calculated at the depths of 2, 5, 10, and 20 cm depth.

Figure 4.1 Effect of distribution coefficient Kd on chemical breakthrough curves at the depths of 2 and 5 cm (left)
and 10 and 20 cm (right). Biodegradation is not considered (decay constant = 0). Source concentration = 1000 mg/L.

37

The calculated breakthrough curves show that with increasing Kd the maximum chemical concentrations
decrease; at the depths of 2 and 5 cm the time at which the maximum concentrations occur are more orless independent from Kd, while at the deeper depths of 10 and 20 cm the time of maximum concentrations
is retarded as Kd increases (Figure 4.1). At a depth of 2 cm, the maximum concentrations have a ratio of
1.7/1.4/1 for a ratio of Kds of 5/10/20. At a depth of 20 cm, the ratio of maximum concentrations is3.5/1.9/1. This increase in this ratio is the combined effect of sorption and dispersion.
The next set of calculations incorporated both the effect of sorption and biodegradation. Biodegradation
was simulated as a first‐order degradation process, which means the concentration decreases following an
exponential decay function C = C0 exp(‐µt), where C0 is the concentration at time (t) = 0 and µ is the decay
constant. The same Kd values as above were used, together with decay constants µ of 0.001 and 0.01 day‐1.
The first decay constant corresponds to a half‐life t1/2 = ln(2)/µ = 693 days while the second one to a half‐life of 69.3 days. The calculated breakthrough curves now show much lower concentrations owing to theloss of chemical from the soil due to degradation (Figure 4.2). The larger the decay constant (or the shorter
the chemical half‐life) the smaller the maximum concentrations become. For a decay constant of 0.01 day‐1
the maximum concentrations at the 5 cm depth are 2, 0.2 and 0.007 for a Kd of 5, 10 and 20 L/kg,
respectively. Compared to the source concentration C0 of 1000 mg/L, these maximum concentrations C
represent a dilution attenuation factor (C0/C) of 500, 5000 and 140,000, respectively.
Decay constant = 0.01 day-1

Decay constant = 0.001 day-1
200

100
Kd = 5 L/kg

2 cm depth
5 cm depth

2 cm depth
5 cm depth

160

10
Kd = 5 L/kg
Kd = 10 L/kg

120

1

80

Kd = 10 L/kg

0.1

Kd = 20 L/kg

Kd = 20 L/kg

40

0.01

0

0.001
0

20

40

Time (years)

60

80

0

20

40

60

80

Time (years)

Figure 4.2 Effect of distribution coefficient Kd on chemical breakthrough curves at the depths of 2 and 5 cm (left)
and 10 and 20 cm (right). Biodegradation is accounted for: decay constant µ = 0.001 day‐1 (left) and 0.01 day‐1(right). Source concentration = 1000 mg/L

38

4.2 Phenolic compounds
4.2.1 PHENOL
Calculated breakthrough curves using HYDRUS‐1D for phenol and its daughter compounds catechol and
HMSA are shown in Figure 4.3 using the minimum, mean, and maximum values for sorption (Kd) andbiodegradation (µ) from Table 3.3. Concentrations are shown only at depths of 2 and 5 cm; at deeper soil
depths concentrations become insignificant.
Using mean parameter values for Kd and µ shows that phenol concentrations are lower than those of its
two daughter compounds by more than an order of magnitude (at the 2 cm depth) (Figure 4.3b). Thisbehaviour is due to the much longer half‐life of catechol (274 days) compared to that of phenol (6.84 days),despite the higher Kd for catechol (13.8) compared to phenol (1.38). HMSA, on the other hand, has a much
shorter half‐life (2 days) compared to its parent catechol. It therefore follows closely the concentration of
its parent, but is still lower in concentration due to short half‐life. At 5 cm depth, phenol concentrations
have become less than 0.0001 mg/L (not visible on the graph) because of the combined effect of sorption
and degradation. Catechol and HMSA concentrations have also decreased, but especially the longer half‐lifeof catechol keeps concentrations of both compounds between 0.001 and 0.01 mg/L.
When minimum values for Kd and µ are used (i.e. resulting in the lowest degree of attenuation),concentrations of phenol and cathechol are higher than when mean parameters are used. The exception isfor HMSA with lower concentrations for minimum than for mean parameters. This is due to the muchhigher half‐life of its parent, catechol (365 days compared to 274), which will generate, per unit of time,
much less of the daughter compound HMSA.
For maximum values of Kd and µ (i.e. resulting in the highest degree of attenuation), phenol concentrations
have dropped below 0.0001 mg/L (very short half‐life of 0.11 days) whereas catechol concentrations are
only slightly smaller than for mean parameters given relatively similar half‐lives. HMSA is now larger thancatechol due the considerably larger sorption value for catechol.

Figure 4.3 Breakthrough curves of phenol (red), catechol (blue) and HMSA (green) in a shallow soil profile
accounting for sorption (Kd) and biodegradation (µ); (a) maximum Kd and µ, (b) mean Kd and µ, (c) minimum Kd andµ. A hypothetical source concentration C0 of 1 mg/L is used39

4.2.2 2‐METHYLPHENOL
Breakthrough curves for 2‐methylphenol and its daughter 3‐methylcatechol at two soil depths again
demonstrate the considerable reduction in chemical concentration due to the combined effect of sorption
and biodegradation (Figure 4.4). Using mean parameter values (i.e. resulting in a mean degree ofattenuation) produces concentrations for both 2‐methylphenol and 3‐methylcatechol between 0.01 and0.001 mg/L at 2 cm depth. The combination of very similar half‐fives (4.57 and 7) and a slightly higher Kd for
3‐methylcatechol (2.9 compared to for 0.74) produces nearly identical concentrations. Once the chemicals
have reached the depth of 5 cm, their concentrations have further decreased to less than 0.0001 mg/L.
Minimum parameter values for Kd and µ result in the overall highest concentrations (Figure 4.4c) for bothchemicals. 2‐methylphenol has a maximum concentration around 0.01 mg/L, whereas maximum
concentrations for its daughter compound are between 0.01 and 0.001 mg/L. At the depth of 5 cm,
concentrations are between 0.001 and 0.0001 mg/L.
A maximum degree of attenuation produces 2‐methylphenol concentrations less than 10‐5 mg/L (at 2 cm
depth), whereas 3‐methylcatechol has maximum concentrations around 0.001 mg/L (Figure 4.4a). The
higher concentrations for the daughter compound are the result of the longer half‐life (7 days) compared to
1.6 days for 2‐methylphenol. At 5 cm depth 2‐methylphenol has obtained negligible concentrations (< 10‐7mg/L).

Figure 4.4 Breakthrough curves of 2‐methylphenol (o‐cresol) (red) and 3‐methylcatechol (blue) in a shallow soil
profile accounting for sorption (Kd) and biodegradation (µ); (a) maximum Kd and µ, (b) mean Kd and µ, (c) minimum
Kd and µ. A hypothetical source concentration C0 of 1 mg/L is used.

40

4.3 Polycyclic aromatic hydrocarbons
4.3.1 NAPHTHALENE
Breakthrough curves at 2 cm depth for mean parameters show naphthalene concentrations between 0.001
and 0.0001 mg/L, while its daughter compound has nearly 100 times higher maximum concentration(Figure 4.5b). The much lower sorption for DHDHN (Kd = 0.097 L/kg) compared to naphthalene (Kd = 33.8L/kg) explains its higher concentration. At 5 cm depth naphthalene concentrations have decreased tonearly 10‐7 mg/L, while the daughter compound remains at 10‐4 mg/L.
Using minimum attenuation parameters (note that mean, minimum and maximum half‐lives for therespective compounds are identical) results in naphthalene concentrations between 0.1 and 0.01 mg/L, andslightly lower DHDHN concentrations (Figure 4.5c). Because sorption values for both compounds are moresimilar now (Kd = 0.097 for DHDHN and 4.3 for naphthalene) compared to the mean values, the larger half‐life for naphthalene (80 days) compared to DHDHN (2 days) results in higher concentrations for the former.
With maximum Kd values the naphthalene concentrations are around 10‐6 mg/L, the overall lowest results
across the three parameter values (Figure 4.5a). The much higher DHDHN concentrations are due to themuch lower Kd for DHDHN (Kd = 0.097) compared to naphthalene (Kd = 87.4). At 5 cm depth naphthalene
has degraded to values below 10‐8 mg/L.

Figure 4.5 Breakthrough curves of naphthalene (red) and DHDHN (cis‐1,2‐dihydroxy 1,2dihydronapthalene) (blue) ina shallow soil profile accounting for sorption (Kd) and biodegradation (µ); (a) maximum Kd and µ, (b) mean Kd and µ,(c) minimum Kd and µ. A hypothetical source concentration C0 of 1 mg/L is used.

41

4.4 Hydraulic fracturing additives
4.4.1 2‐BUTOXYETHANOL
Maximum concentrations for 2‐butoxyethanol at 2 cm depth were approximately 0.0002, 0.002, and 0.02
mg/L for maximum, mean, and minimum attenuation, respectively (Figure 4.6). These results are uniquely
due to differences in half‐lives, as the sorption parameters are virtually identical (Kd = 1.3, 1.4, and 1.5). At 5
cm depth maximum concentrations are less than 10‐6 mg/L for maximum attenuation, 10‐5 mg/L for mean
and 10‐3 mg/L for minimum attenuation.

Figure 4.6 Breakthrough curves of 2‐butoxyethanol in a shallow soil profile accounting for sorption (Kd) andbiodegradation (µ); (a) maximum Kd and µ, (b) mean Kd and µ, (c) minimum Kd and µ. A hypothetical source
concentration C0 of 1 mg/L is used

4.4.2 BRONOPOL
Bronopol sorption and degradation parameters are identical for mean, minimum and maximum
attenuation conditions. As a result, all predicted bronopol concentrations are identical for the three
conditions (Figure 4.7). The degradation product formaldehyde has concentrations that display the typicaleffect of increasing half‐lives when comparing Figure 4.7a, Figure 4.7b, and Figure 4.7c. Because of thesomewhat lesser degradation of bronopol (half‐life = 60 days) combined with a very low sorption (Kd = 0.02L/kg), concentrations are shown at 5, 10 and 20 cm depth. At the 5 cm depth, concentrations areapproximately 0.2 mg/L; at 20 cm depth maximum bronopol concentrations have dropped to 0.02 mg/L.
Formaldehyde concentrations at 5 cm depth range from 0.003 to 0.02 mg/L.

42

Figure 4.7 Breakthrough curves of bronopol (red) and formaldehyde (blue) in a shallow soil profile accounting forsorption (Kd) and biodegradation (µ); (a) maximum Kd and µ, (b) mean Kd and µ, (c) minimum Kd and µ. A
hypothetical source concentration C0 of 1 mg/L is used

4.4.3 LIMONENE
Limonene concentrations at 2 cm depth were very low for all parameter combinations considered, i.e. fromless than 10‐4 mg/L for the minimum attenuation parameters to less than 10‐11 mg/L for the maximum
attenuation parameters (Figure 4.8). Only for the minimum attenuation parameters was the concentration
larger than zero at the 5 cm depth, i.e. between 10‐9 and 10‐10 mg/L.
With mean parameter values Kd = 42 L/kg and half‐life = 10.4 days, limonene is very strongly sorbed onto
the soil organic carbon while biodegradation is very fast. For instance, after about 70 days, the equivalentof 7 half‐lives, the concentration at any depth will have decreased by a factor 100 due to biodegradation.
The risk for bioaccumulation of limonene in soil environments is therefore very small.

Figure 4.8 Breakthrough curves of limone in a shallow soil profile accounting for sorption (Kd) and biodegradation(µ); (a) maximum Kd and µ, (b) mean Kd and µ, (c) minimum Kd and µ. A hypothetical source concentration C0 of 1
mg/L is used43

4.4.4 DILUTION ATTENUATION FACTORS
Dilution attenuation factors are calculated for as C0/Cmax, where C0 is source concentration (1 mg/L) andCmax is the maximum calculated concentration. Based on maximum concentrations at the 2 cm depth,
dilution attenuation factors for mean, minimum and maximum concentrations range from 4 for bronopol to
5.5x107 for limonene (Table 4.1).
Table 4.1 Dilution attenuation factors for mean, minimum and maximum attenuation (2 cm depth).
Chemical compounds

Dilution attenuation factor
Mean

Minimum

Maximum

Phenol42

13

92

Catechol

24

6

64

MHSA

51

92

34

2‐Methylphenol

323

73

1.96x105

3‐Methylcatechol

385

258

1515

Naphthalene

384

33

1.0x106

cis‐1,2‐Dihydroxy 1,2
dihydronaphthalene

116

75

117

2‐butoxyethanol

562

60

6369

Limonene

5.5x10733333>5.5x107

Bronopol444Formaldehyde

65

39

253

The dilution attenuation factors are expressed as function of the combined attenuation factors Kd and µ,
calculated as (exp(‐µ)/Kd)‐1. This parameter is generally positively correlated with the dilution attenuation
factor (Figure 4.9). This means that for most compounds strong sorption (high Kd) is combined with a shorthalf‐life (small t1/2 or large µ), and low sorption with large half‐life.

Figure 4.9 Dilution attenuation factors as function of attenuation parameters {u, Kd}. A = phenol, B = catechol, C =HMSA; D = 2‐methylphenol, E = 3‐methylcatechol; F = naphthalene, G = DHDHN; H = 2‐butoxyethanol; I = bronopol,
J = formaldehyde; K = limonene44

5 Conclusions

Hydraulic fracturing chemicals and naturally occurring organic compounds may occur in soil as a result of
unintentional release of coal seam gas produced water from storage ponds owing to flooding and leaks. Naturally
occurring organic compounds considered in this study include phenolic compounds (phenol and 2‐methylphenol) andpolycyclic aromatic compounds (naphthalene). Chemical additives of hydraulic fracturing fluids included a biocide(bronopol), a surfactant (2‐butoxyethanol) and a solvent (limonene). A literature review resulted in a range ofdistribution coefficient (Kd) and biodegradation constant (µ) values, from which mean, minimum and maximum values
were determined for use in simulations of natural soil attenuation. For the majority of the organic compounds
involved in the review, direct measurements of soil Kd were not available. For those cases, Kd was derived from KOC,
when available, and the fraction of soil organic carbon. In only a few cases KOC had to be derived from KOW using KOC‐
KOW relationships from the literature.
Calculation of natural soil attenuation of the organic compounds involved implementation of biodegradation
pathways, i.e. a sequence of organics consecutively undergoing biodegradation and transformation, coupled withsorption onto soil organic carbon. These coupled processes were numerically simulated using the HYDRUS‐1D
simulator for a scenario where produced water leaks from a storage pond into soil during a 30‐year period,
corresponding to the assumed duration of gas and water production. Incorporating transformation products in thesimulations is important because some of the transformation products have a higher ecotoxicity than their parent
compounds; such is the case for catechol which is the transformation product of phenol.
Organic carbon is one of the most important soil properties influencing sorption and transformation of organic
compounds. To account for the measured soil organic carbon depth‐dependency in soil and its effect on sorption andbiodegradation, a new module was developed for HYDRUS‐1D which automatically distributes organic carbon withdepth. On the basis of detailed organic carbon data from the Liverpool Plains (NSW), this depth‐dependency oforganic carbon was implemented in the model, and the sorption and degradation parameters were updated
accordingly. Three representative soil types of the Liverpool Plains were considered for analysis of the organic carbon
data: Vertosols, Chromosols and Sodosols.
Results showed that for all chemicals considered in the assessment, the combined effect of strong sorption and fastbiodegradation resulted in nearly complete degradation of all chemicals in the top 5 to 10 cm of the soil profile. These
results are true for a broad range of sorption and degradation parameter values. This indicates that the risk of
bioaccumulation in soil and leaching to groundwater is very small for the conditions of this study, i.e. a small
infiltration flux approximately equal to the long‐term recharge rate of several tens of mm per year. The methodology
developed here can be easily extended to a more systematic analysis of leaching risks of a broad range of organic
compounds introduced in soil. Further work should include testing the attenuation behaviour under different flow
conditions, including higher infiltration rates typical of saturated or near‐saturated soils in case of flooding,preferential flow typical of cracking Vertosol soils, and the effect of the high‐pH produced water on sorption andtransformation of organics. To further reduce uncertainty around predicted attenuation of some of the more toxic
compounds, soil‐specific sorption and biodegradation laboratory experiments are recommended.

45

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Appendix 1 New HYDRUS‐1D module: Dependencyof Kd and µ on soil organic carbon*************************************************************************************************
subroutine ReadDR(cDataPath)character cFileName*260,cDataPath*260
logical lDepthRed,lOpen
common /depth_redution/ lDepthRed,aDepth,bDepth,cValue
iLengthPath = Len_Trim(cDataPath)cFileName = cDataPath(1:iLengthPath)//'\Depth_Red.in'

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open(37,file=cFileName, status='old',err=998)
inquire(unit=37,opened=lOpen)if(lOpen) thenread(37,*,err=998)
read(37,*,err=998) lDepthRed,aDepth,bDepth,cValue
write(*,321) lDepthRed,aDepth,bDepth,cValue
format('lDepthRed=',l3,/'aDepth=',f7.3,/'bDepth=',f7.3,/!
'cValue=',f7.3)
end ifreturncontinue
lDepthRed=.false.
returnend************************************************************************
function rX(z)998logical lDepthRedcommon /depth_redution/ lDepthRed,aDepth,bDepth,cValuerX=1.
if(.not.lDepthRed) returnif(z.gt.aDepth) thenrX=1.
else if(z.lt.bDepth) thenrX=cValueelse
rX=cValue+(1.-cValue)/(aDepth-bDepth)*(z-bDepth)
end ifreturnend*******************************************************************************

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