INTRODUCTION
Petroleum-derived fuels represent an important source of energy in
contemporary society (Dudley, 2018). Accidental releases due to storage
tank leaks, pipeline ruptures or improper waste disposal represent
widespread groundwater contamination threats posed by petroleum
hydrocarbons (e.g., gasoline, jet fuel and diesel). Whenever fuel is
released in a large volume or the release persistently occurs over a
long period, many hydrocarbons can migrate and reach the uppermost
portion of a saturated zone; from there, these hydrocarbons accumulate
and form a Light Non-Aqueous Phase Liquid (LNAPL) (ITRC, 2009; Tomlinson
et al., 2017). Once present in a subsurface environment, the petroleum
is distributed in a non-aqueous phase in pores within a multiphasic
context and releases soluble and also volatile compounds into water by
interphase mass-transfer, especially BTEX (benzene, toluene,
ethylbenzene and xylenes). Since the BTEX compounds released to
groundwater are soluble, mobile, and pose carcinogenic or neurotoxic
risks to humans, providing accurate predictions of BTEX movement
patterns and final deposition locations within a saturated zone is
crucial to establish remediation goals and actions in
petroleum-contaminated site management (e.g., MacDonald and Kavanaugh,
1994; Chesnaux, 2008).
Since the soluble or volatilized compounds of LNAPL pose risks to human
health (e.g., Peters et al., 1999; Huntley and Beckett, 2002; Baciocchi
et al., 2010; Thornton et al., 2013), management efforts should reduce
contaminant masses within the sub-surface. Collective actions that
facilitate the extraction or destruction of a contaminant are known as
remediation. Active remediation, based on physical extraction,
represents the most common strategy to clean subsurface leaks. Among
active remediation techniques, the pump-and-treat (P&T) method
represents the simplest and traditional approach used to promote LNAPL
recovery. The P&T approach consists of a simple extraction of both
LNAPL and contaminated groundwater from wells, followed by a treatment
of contaminated water prior to disposal. P&T normally is highly
expensive and time-consuming. Despite elevated efforts and investments
devoted to site cleanup, physical remediation cannot fully extract
hydrocarbons in the subsurface, as previously demonstrated by several
works such as Mercer (1990), McCray et al. (2011), Lenhard et al.
(2018), and Lari et al. (2018). After a remediation based solely on the
P&T approach, a large proportion of LNAPL will remain in the pores and
the remediation goal will be not reached.
Geological heterogeneity has frequently acted as a main impediment to
oil recovery within remediation systems (Kaluarachchi, 1996; Waddill &
Parker, 1997; McCray et al., 2011; Saenton & Illangasekare, 2013). Low
permeability lithologies impede the movement of non-aqueous fluids.
According to Mercer (1990) and McCray et al. (2011), most contaminant
removals occur in hydraulically accessible zones, and complete removals
are limited by contaminant masses stored in inaccessible zones. However,
regardless of the importance of geological heterogeneity, the main cause
of complications to LNAPL remediations is the complexity of LNAPL
distributions in pore spaces; these complications are accentuated by
water table fluctuations.
The multiphase distributions of
hydrocarbons, water and air in pore spaces represent a complex issue and
affect the LNAPL remediation ability. Only a limited proportion of LNAPL
is mobile and can be recovered, while a large proportion will remain
immobile as a residual or entrapped phase. More complex scenarios have
been observed in the field in response to water table fluctuations
caused by alternating wet and dry seasons. When a water table falls to a
position not previously recorded after the spill, LNAPL migrates to
lower parts of the aquifer (Kemblowski & Chiang, 1990; Charbeneau,
2007, Jeong & Charbeneau, 2014). When the water level rises, LNAPL is
retained through capillary force in the saturated zone; this phenomenon
is known as entrapment (Kemblowski & Chiang, 1990, Marinelli &
Durnford, 1996; Steffy et al., 1998; Charbeneau et al., 2007; Teramoto
& Chang, 2017). When entrapment occurs, LNAPL becomes entrained in the
saturated zone by capillary forces, thereby losing its mobility.
Conversely, when the water level drops and water is drained from the
pores, the LNAPL is released and the previously isolated drops and
ganglia agglutinate and gain mobility. According to Parcher et al.
(1995), the LNAPL residual phase resulting from the vertical movement of
the water level is small in the unsaturated zone, where the pores are
occupied by air, LNAPL and water; conversely, the phase is high in the
saturated zone, where water and LNAPL occupy completely the porous
medium. According to Mercer & Cohen (1990), the residual saturation of
LNAPL ranges from 10 to 20% in the unsaturated zone. As demonstrated by
Chaberneau & Jeong (2014), Lenhard et al. (2017) and Lenhard et al.
(2018), LNAPL in free, entrapped, and residual phases, as well as its
relative permeability, are time-variant and depend of the elevation of
the fluid phase level. The analytical model presented by Lenhard et al.
(2018) and the experimental results of Gatsios et al. (2018) reinforce
that entrapment induced by a water table fluctuation represents the most
prominent challenge to active remediation effectiveness. As previously
demonstrated by Wang et al. (2014), Jeong & Chaberneau (2014) and Kuo
et al. (2016), the recovery rate of LNAPL is intrinsically controlled by
water table fluctuations.
Our study site, contaminated by a large volume of jet fuel in Brazil,
has been characterized by several works, including Bordignon et al.
(2016), Teramoto and Chang (2017), Teramoto and Chang (2018), Isler et
al. (2018) and Teramoto and Chang (2019). As demonstrated by Teramoto &
Chang (2017) and Isler et al. (2018), most of the LNAPL is distributed
in the entrapped phase below the water table, thereby impacting the
effectiveness of pump-and-treat remediation. This study presents a
phenomenological process related to the seasonal effect impacting the
water table level that governs LNAPL recovery; this study’s findings can
provide support to new strategies of remediation, especially in tropical
climates.
WIDE-RANGING WATER TABLE FLUCTUATIONS IN BRAZIL
The southeast Brazil encompass a subtropical to tropical climates, has a
well-defined wet period during the summer (December–January–February)
and a well-defined dry period during the austral winter (June–August).
During autumn (March–May) and spring (September–November), the region
receives an intermediate precipitation volume that falls between the
typical values observed in summer and winter. The water table
fluctuation in shallow aquifers reflects hydrogeological and climatic
conditions. Tropical regions, such as most of Brazil, are typically
characterized by a high amount of precipitation, with alternating dry
and wet seasons. Because of the large volume of precipitation in the wet
season, the groundwater recharge is also higher at this time, leading to
a wide range water table fluctuation.
Figure 1 illustrates the alternating rainy (October to March) and dry
seasonal precipitation (April to September), previously presented by
Teramoto and Chang (2017). The seasonal variation in precipitation
generates a cyclic water-level fluctuation (Healy & Cook, 2002;
Maréchal et al., 2006; Delin et al., 2007; Neto et al., 2015) similar to
those observed in Figure 1. A time lag of nearly
three months occurs in the study area between the peak of the rainy
season and the peak of the groundwater-level rise. The groundwater-level
maximum is generally reached in May and falls steadily until December.
The amplitude of the water level is directly related to the amount of
annual accumulated rainfall (Teramoto and Chang, 2018).
Figure 2 illustrates six hydrograms in several
locations of south and southeast Brazil, showing that water table
fluctuations mostly displayed variation ranges above four meters over
time.
MATERIAL AND METHODS
Study site
The study area is located in the municipality of Paulínia, São Paulo,
Brazil. A large volume of jet fuel is present in the subsurface, with an
estimated volume of 520 m3 (Pede, 2009). To determine
the extents of LNAPL and the plumes from the dissolved phase of BTEX
compounds, 104 monitoring wells were installed in an area of 264,600
m2. Figure 3 shows a
potentiometric map with the inferred boundary of the source zone,
monitoring locations, and pumping wells in the study area. The source
zone occupied an area of approximately 80,000 m2.
The studied Cenozoic shallow aquifer is heterogeneously composed of
clayey sands interfingered with coarse sand lenses, sandy clays and
clayey silts. The geometries of the sandy and clayey facies indicate a
depositional environment dominated by a meandering river (Bordignon et
al., 2015; Teramoto et al., 2017b). The hydraulic conductivity (K)
displays a high variability because it is intrinsically related to
aquifer lithology. K values determined by slug tests performed on 64
monitoring wells range from 1.2 x 10-7 m/s to 2.4 x
10-4 m/s, with a geometric mean of 2.8 x
10-5 m/s. The average hydraulic gradient is 0.0036 in
the northeast region and increases toward the discharge zone in the
southwest, reaching values of 0.0176.
Monitoring
Since 2002, the water level and free phase thickness of the study site
have been measured using an interface probe in the monitoring wells at a
biweekly frequency. This recorded time-series information has made it
possible to construct hydrographs and determine the floating phase
thickness variation for each monitoring well.
Remediation setup
At the study site, 20 pumping wells (Figure 3)
currently operate with a flow rate ranging from 0.087 to 15
m3/day. The extracted fluids are removed into a
separator box. When the contaminated water is directed to the treatment
station, the oil is stored in individual containers. The storage of
extracted LNAPL in individual tanks can be used to evaluate the
performance of each pumping well, thereby allowing an evaluation of the
spatial variability of aquifer parameters controlling the oil recovery.
Theorical basis of LNAPL recovery
A detailed description of an LNAPL distribution and its movement to a
well is described in Chaberneau (2007). In this section, we will
demonstrate the main formulations that moved the flowing LNAPL during
pumping-and-treat remediation, following the analytical model presented
by Chaberneau (2007).
The floating phase thickness (bn) recorded in monitoring
wells represents the most common criteria used to predict LNAPL
distributions based on the relationship of capillary
pressure/saturation, as demonstrated by Kemblowski and Chiang, 1990,
Marinelli and Durnford, 1996, Sleep et al. (2000) and Lenhard et al.
(2018). Assuming an equilibrium condition between fluids within the well
and the surrounding formation, the floating phase thickness can be used
to assess corresponding energy conditions within the pores of the
formation (Figure 4).
The residual saturation of the nonwetting phase shown in Figure 4 is a
measurement of the porous medium capacity used to retain nonwetting
fluid during re-filling with the water. The LNAPL head to water head
plus the equilibrium of LNAPL-layer thickness in a well is described by
Eq. 1.
\(h_{n}=z_{\text{an}}=h_{w}+(1-\rho_{r})b_{n}\) (1)
Where \(\rho_{r}\) represents the density ratio of the LNAPL over water
(pw).
The LNAPL saturation (\(S_{n}\)) in the given vertical interval of the
smear zone (i.e. \(z>z_{\text{an}}\)) may be defined by Eq. 2.
\(S_{n}\left(z\right)=S_{\text{nr}}+(1-S_{\text{wr}}-S_{\text{nr}})(S_{e\left[t\right]}-S_{e\left[w\right]})\)(2)
Where \(S_{\text{wr}}\), \(S_{\text{nr}}\),\(S_{e\left[w\right]}\),\(S_{e\left[t\right]}\), respectively represent the water
residual saturation, LNAPL residual saturation, and total liquid
effective saturation.
A significant portion of saturation was not mobile and was retained by
capillary forces in the pore space. Several laboratories have derived
experiments, such as Johnston and Adamski (2005), showing that the
residual LNAPL saturation values, Snr , linearly
increase with the initial LNAPL saturation values of (1 –Swi ) = Sni .
The LNAPL obstructs part of the pore space and reduces the permeability,
creating a profile of intrinsic permeability related to
Sn (Figure 4). The relative
permeability in a multiphase context may be calculated using the Mualem
equation (Eq. 3).
\(k_{\text{rn}}\left(S_{w},S_{n}\right)=\sqrt{S_{e\left[t\right]}-S_{e\left[w\right]}}\left(\frac{\int_{S_{e\left[w\right]}}^{S_{e\left[t\right]}}\frac{dS_{e}}{h_{c}}}{\int_{0}^{1}\frac{dS_{e}}{h_{c}}}\right)^{2}\)(3)
The extraction of contaminated groundwater through pumping wells creates
a gradient that causes LNAPL migration towards the well. Larger
groundwater pumping rates correspond to larger hydraulic gradients
toward the well and an increased LNAPL flow.
The water transmissivity in a screened interval lacking LNAPL is defined
by Eq. 4, while the LNAPL transmissivity is calculated by integrating
the relative permeability within the smear zone, as defined by Eq. 5.
\(T_{w}\left(b_{w}\right)=\int_{z_{\text{an}}-b_{w}}^{z_{\text{aw}}}K_{\text{ws}}\left(z\right)\text{dz}\)(4)
\(T_{n}\left(b_{n}\right)=\frac{\rho_{r}}{\mu_{r}}\int_{z_{\text{nw}}}^{z_{\max}}K_{\text{ws}}\left(z\right)k_{\text{rn}}(S_{w},S_{n})dz\)(5)
The multiphase extraction by pumping recovered groundwater at rates of\(Q_{w}\), over a screened interval of \(b_{w}\). The flow of water to
the pumping wells also impacted the flow of LNAPL at rate \(Q_{n}\). The
flow rate of LNAPL recovered by the pumping well can be estimated via
the transmissivity of LNAPL (Eq. 4) and the water transmissivity (Eq.
5), according to Eq. 6.
\(Q_{n}=\frac{Q_{w}T_{n}(b_{n})}{T_{w}(b_{w})\rho_{r}}\) (6)
The LNAPL’s specific volume (\(D_{n}\)) serves as reference to quantify
the amount of LNAPL present as a function of the floating phase measured
in the monitoring wells. \(D_{n}\) corresponds to the area under the
LNAPL saturation curve (Figure 4), and it is calculated by an
integration of Sn within the smear zone, assuming a
porosity \(\varnothing\).
\(D_{n}\left(b_{n}\right)=\int_{z_{\text{nw}}}^{z_{\max}}{\varnothing S_{n}\left(z\right)\text{dz}}\)(7)
Only a fraction of \(D_{n}\) showed mobility and was subject to
recovery. The LNAPL recoverable volume, Rn , is determined by the
area between the LNAPL saturation curve and the residual saturation
curve.
\(R_{n}\left(b_{n}\right)=\int_{z_{\text{nw}}}^{z_{\max}}{\varnothing{(S}_{n}\left(z\right)-{(S}_{\text{nr}}(z))dz}\)(8)
All equations presented later in this study are based on the premise of
equilibrium and static conditions, in which the LNAPL is completely
released from the pore space and all revocable LNAPL can be recovered by
the pumping wells. However, in the field, due to the upward movement of
the water table, the pore space of the smear zone is imbibed with water
and the LNAPL is entrapped by capillary forces, resulting in a decrease
of the floating phase in monitoring wells. When the water table is below
the top of the smear zone (Figure 5a), the LNAPL
flows to the pumping well due to the hydraulic gradient created by water
extraction. When the water table rises above the top of the smear zone,
the LNAPL is fully entrapped and the floating phase disappears from the
monitoring wells; thus, no LNAPL can be recovered from the pumping wells
(Figure 5b). Moreover, most analytical models (e.g.,
Chaberneau and Jeong, 2014; Lenhard et al., 2017; Alfaro et al., 2019)
have not incorporated the hysteresis effect imposed by recurrent cycles
of drainage and imbibition of the pores with respect to the wetting
phase imposed by water table fluctuations.
To estimate the volume of recoverable LNAPL in favorable conditions,
when the water table fell and released the LNAPL from the pore space, we
performed simulations using the measured floating phase thickness,
physical aquifer parameters, and characteristics of LNAPL with an
assumption of vertical equilibrium. Using the analytical model of Jeong
and Chaberneau (2014), we simulated fifteen years of LNAPL recovery
assuming ideal conditions, in which the water table remains static and
the LNAPL can be recovered by the imposition of a hydraulic gradient
induced by pumping.
Physical parameters of aquifers
Because the physical properties of porous media play an important role
in mass transfers, an aquifer characterization was executed using
lithological data, hydraulic conductivity data, and retention curve
parameters extracted from previous studies (Bordignon et al., 2015;
Teramoto and Chang, 2018).
Due to the difficulty in accessing undisturbed aquifer samples in the
sub-surface, we collected similar samples in the outcrop close to the
study site. We performed measurements of the water matric potential in
the laboratory as a function of sample moisture to build a retention
curve using Richards’ plate apparatus and the filter paper test. The
generated points were fitted by the van Genuchten model (van Genutchen,
1981).
LNAPL characterization
Characterization of LNAPL were performed in six floating phase samples
collected from the monitoring wells. The kinematic viscosity values were
obtained by methodology described in ASTM D445 standard, with the unit
of viscosity expressed in Stokes (St). To determine the surface and
interfacial tension of the fluids present in the porous medium, samples
of water and oil were collected along the free phase plume. Four water
samples and four oil samples were collected to measure the interfacial
and surface tension of both fluids.
The quantification of surface tension and interfacial tension between
the liquids was performed according to the ring method (Du Nouy), using
a Sigma 701 KSV tensiometer according to the procedures of ASTM D
971-99a. The test consists of determining the surface and interfacial
tension by measuring the force required to detach a platinum ring (of
known characteristics) by passing it through the air-water interface,
and then air-LNAPL and water-LNAPL, respectively. The tests were
performed at a constant temperature of 25±1 oC with
two conditions for descent speed and plate climbing (20 and 25
mm.min-1, respectively), to verify if the difference
in speeds significantly interfered with the measurement.
RESULTS
Water table fluctuation and floating phase thickness
The water table fluctuation of the fall and rise of the water table
observed in Figure 2, may be interpreted as recurrent cycles of drainage
and imbibition of smear zone pores. During the upward movement of the
water table during groundwater recharge, understood as an imbibition
cycle, the wetting phase enters the pores and entraps the non-aqueous
phase. Because the entrapment condition, the LNAPL lose its mobility,
leading to decrease or even disappearance of the floating phase into the
monitoring wells. In opposite condition, the downward movement of
groundwater during dry seasons may be interpreted as a drainage event,
since the water filling the pores is drained and the non-aqueous phase
is released, gaining mobility. The freed LNAPL can migrate to monitoring
wells and the thickness of floating phase into the monitoring wells
increases. The alternating cycles of entrapment and release of LNAPL is
easily identified in the combined time-series of water table height and
floating phase thickness. Figure 6 illustrates the water table
fluctuation and floating phase thickness variation during the period
spanning April 2006 and January 2015 in four monitoring wells.
Invariably, the recorded floating phase thickness is generally smaller
during periods of elevated water levels and progressively increases when
the water table falls.
The cycles of entrapment and release of LNAPL is best characterized by
maps of floating phase thickness (Figure 7).
Figure 7 presents the floating phase thickness
isovalues in different periods of monitoring study, showing large
variation over time. The maximum floating phase thickness was observed
in the interval of May to November 2008 (Figure 7a),
while the minimum floating phase thickness was recorded in May 2012.
Recorded LNAPL recovery
The study area has been investigated since 2002, with a pump-and-treat
remediation system in place since 2005. Initially, the remediation
system operated with four pumping wells (PB-01, PB-02, PB-03 and PB-04.
From 2006 to 2009, four additional wells were incorporated into the
system (PB-05, PB-06, PB-07, PB-08). From December 2010 to April 2011,
the remediation was paused and on April 2011, the operation resumed with
20 active pumping wells.
The LNAPL recovery rate of the remediation system broadly varied over
time. At beginning of remediation until November 2005, a neglectable
volume of oil was recovered. The period between October 2005 and March
2006 saw a recovery of 4.25 m3 of LNAPL. By March
2006, the LNAPL recovery rate strongly decreased. In November 2006,
there was an abrupt increase of LNAPL recovery in pumping wells PB-03,
PB-05, PB-06 and PB-07 (Figure 8), which correlated
with a strong decrease in the water table observed during this period.
Between October 2006 and March 2007, 84.67 m3 of LNAPL
was recovered, which accounted for 44% of all LNAPL recovered between
2005 and 2015. In March 2007, the LNAPL recovery rates both decreased
and increased in October 2007, then the recovery rate stayed high until
March 2008. During this period, the recovered LNAPL totaled 43.92
m3. After February 2008, oil recoveries of any
substantial volume completely ceased. A substantial rate of LNAPL
recovery was newly recorded only on September 2014 and ceased again in
March 2015. Between September 2014 and March 2015, 27.12
m3 of LNAPL was recovered.
The cyclical response of the LNAPL recovery strongly coincided with the
water table fluctuation, as seen in Figure 9. LNAPL
recoveries were only possible after a sufficient decrease in the water
table, with most incidences occurring between October and March.
Accordingly, LNAPL recovery rates strongly decreased or even ceased when
the water table increased. This observation is in accordance with the
seasonal cycles of LNAPL entrapment and releases in the pore space
caused by water table fluctuations.
Model prediction
Model parametrization
Based on the collected samples, we conducted laboratory tests to
characterize both oil and aquifer lithologies. Table
1 presents the physical parameters of the main lithologies obtained
from retention curve tests, while Table 2 presents
the results of LNAPL characterization in the analyzed samples. In our
simulations, we used the average values of measured parameters.
LNAPL recovery prediction
Based on the analytical model presented by Jeong and Chaberneau (2014),
we performed simulations employing the maximum recorded floating phase
recorded in the selected monitoring well to reproduce the theoretical
recoverable LNAPL without the effects of seasonal water table
fluctuations. A period of fifteen years of pumping was simulated under
ideal conditions, assuming that groundwater statistics and recoverable
LNAPL within the smear zone could be extracted. To predict the recovery
rate based on the water table and floating phase thickness recorded in
November 2008, we simulated the recovery of the two most productive
pumping wells, PB-06 and PB-07. The parameters employed in the performed
simulations are presented in Table 3.
The simulated scenarios of oil recovery in PB-06 and PB-07 are
illustrated in Figure 10, while
Table 4 summarizes the most important information
provided by the simulations.
DISCUSSION
The high precipitation in tropical and subtropical climates, which is
typically above 1,200 mm/year and is concentrated in wet seasons,
imposes large variations in the water tables of shallow aquifers
(Figures 1 and 2). This variation represents the
main mechanism that governs the LNAPL distribution in the subsurface and
its mobility. The water table fluctuation was previously recognized as a
factor that causes the entrapment of LNAPL, as described by the previous
works of Kemblowski and Chiang (1990), Marinelli and Durnford (1996),
Steffy et al. (1998), Charbeneau et al. (2007), Teramoto and Chang
(2017) and Isler et al. (2018). Furthermore, the water table fluctuation
also accounts for reductions in effectiveness of LNAPL recoveries via
physical extraction (Chaberneau et al., 2000; Kuo et al., 2016).
Most investigation procedures are based on simple and obsolete concepts
in which most LNAPL is distributed above the saturated zone, forming a
continuous phase in the pore system. Since the 1990s, this concept,
known as the “pancake model distribution”, has been deemed as
obsolete. However, in many regions around the world, the decisions and
actions of environmental agencies and consultancies are still guided by
the false concept that LNAPL is mostly distributed above the saturated
zone as a floating oil phase. For example, in traditional
investigations, the soil sampling for hydrocarbon analysis occurs only
in the unsaturated and capillary fringe zones. In most environmental
investigations, the main indicator of LNAPL is solely based on the
presence of floating oil in monitoring wells. Moreover, high
concentrations of BTEX (benzene, toluene, ethylbenzene and xylenes) in
an aqueous phase are misinterpreted as being transported in the
dissolved plume phase and are not seen as a result of a dissolution of
entrapped LNAPL. A simple reduction of the floating phase thickness
during a water table rise is equivocally associated with the
effectiveness of the operating remediation system, despite the low
overall recoverability of LNAPL volumes. These incorrect diagnostics and
elaborated conceptual models cause existing remediation systems to be
ineffective, expensive and environmentally unsustainable.
Regular monitoring provides essential elements to investigate the cycles
of entrapment and releases of LNAPL and their impact on the
effectiveness of remediation systems based on the pump-and-treat
methodology. Empirical observations in the studied site indicate that
recovering substantial amounts of LNAPL is possible only when the
floating phase thickness is above 30 cm in monitoring wells. Thus, the
floating phase thickness represents an important metric to determine the
favorable periods for LNAPL extraction.
The collective understanding of LNAPL behavior in a subsurface was
demonstrably improved in the last decade through the emergence of the
high-resolution technique Laser Induced Fluorescence (LIF). The
emergence of high-resolution techniques, and mainly laser induced
fluorescence such as UVOST® (St. Germain and Martin,
2008), has enhanced the current understanding of hydrocarbon behaviors
and distributions in a subsurface. Several works based on LIF
investigations have demonstrated that the current conceptual and
mathematical models cannot reproduce the oil distribution in a saturated
zone (Suthersan et al., 2015b; Isler et al., 2018; Gastsios et al.,
2018). Investigations with LIF carried out in September 2015 and
presented by Isler et al. (2018) show clearly that LNAPL are
overwhelmingly distributed in the entrapped phase below the water table.
The entrapment condition explains the absence of the floating phase in
our monitoring wells in 2015, 2016 and 2017.
One of most prominent features of
shallow aquifers situated in tropical climates is the wide range in
water table fluctuations, which is directly related to precipitation
amounts. In southeastern Brazil, the high rainy season encompasses the
period between October and February. Another factor that likely
contributes to water table increases is air entrapments, as described by
Gonçalves et al. (2019). In a similar behavior as LNAPL, the air filling
the pore system is displaced and becomes distributed as isolated bubbles
or ganglia in the center of the pores. Due to air clogging the pores,
there is a reduction in the specific yield of the formation, leading to
a water table increase. The wide range of water table fluctuations
promotes the entrapment of LNAPL below the water table (Marinelli and
Durnford, 1996; Steffy et al., 1998; Suthersan et al., 2015b; Teramoto
and Chang, 2017), thereby hindering the identification of the extent of
the source zone and impeding LNAPL recovery.
The transmissivity of LNAPL, estimated by bail-down tests used to
determine the hydraulic conductivity of an aquifer, represents the
criteria for conducting oil recoveries (Huntey, 2000; Beckett and
Huntley 2015; Palmier et al., 2016; Ahmed et al., 2019). However, the
LNAPL transmissivity broadly varies over time in response to water table
fluctuations and is not a representative metric for measuring
recoverable LNAPL (Gatsios et al., 2018). Determinations of oil
transmissivity during prolongated dry seasons, when the water table
decreases sufficiently and releases LNAPL from the pores, induces an
incorrect remediation design and incorrect oil recovery estimations.
Thus, we recommend the abolition of bail-down tests to estimate oil
recovery in cases where the water table strongly fluctuates.
The continuous lowering of the water table in our study started in April
2006 and allowed the removal large volumes of LNAPL in October of the
same year; 84.57 m3 of LNAPL was recovered in four
months and accounted for about 50% of the total jet fuel recovered
during the previous 40 months of pumping. The sudden increase in oil
recovery rates from the second half of October 2006 suggests the entry
of air into the porous medium that was previously filled by LNAPL and
water. The large volume of recovered jet fuel caused a rapid decrease in
the thicknesses of the monitoring wells. The most extreme case was
observed in a monitoring well located at approximately 160 m east and
upstream of PB-06, where a decrease of 65 cm in oil thickness in 72 days
was recorded. The decrease in oil recovery observed in January 2006 is
attributed to the influx of groundwater recharge, thereby leading to an
associated water table increase.
In our monitoring, we had a rare opportunity to observe the effect of
severe drought on the LNAPL remediation. Coelho et al. (2016) provided a
detailed description of the severe drought observed in 2014-2015 in
southeast Brazil. Because of the exceptionally reduced precipitation in
this period, the groundwater recharge was also anomalously low (50%
below the historical average record); this consequently led to strong
and anomalous decrease in the water table, as observed in
Figure 1 and 2. During the water table reduction,
LNAPL was completely released from the porous media, allowing for a high
rate of oil recovery by the remediation systems. Due to the strong
decrease in the water table recorded in November 2014, the LNAPL
migrated downward, increasing the entrapment likelihood, as observed by
the LIF tests carried out by Isler et al. (2018) at the study site.
Because of the strong entrapment, the opportunity for LNAPL recovery was
less frequent.
Assuming a hypothetical and idealized condition where the water table is
statistically controlled, a fifteen - year simulation of the pumping
wells of PB-06 and PB-07 (Figure 9) allowed estimated recoverable
volumes of 192.568 and 218.560 m3 of LNAPL,
respectively; this result represented the range of theoretical LNAPL
that could be recovered. However, due to the seasonal cycles of water
table fluctuation, LNAPL recoveries can occur only during four months of
dry years. The required time to reach this recovery volume likely would
have a timescale of decades or even hundreds of years.
The widely held concept that a remediation system should operate
uninterruptedly during the presence of a free phase is not valid in this
case. Due to unfeasibility of LNAPL recovery in most period, remediation
systems should only operate when the water table decreases sufficiently.
Accordingly, remediation systems should operate only in the months of
water table retreat (October to January in our study area), since the
recovery of LNAPL is not directly related to the pumping rates but is
instead related to the available LNAPL after the drainage of water from
the pores. At this time, the remediation operation should be extended
beyond the pumping wells.
Teramoto et al. (2019) demonstrated that LIF allow a quantitative
assessment of entrapped LNAPL volume via fluorescence intensity. Based
on estimations of entrapped oil, it is possible to quantify the
recoverable LNAPL volume when the water table falls and releases the
non-wetting phase from the pore space.
A serious disadvantage of the pump-and-treat methodology is the large
volume of contaminated groundwater that should be extracted and treated
over a long period of time, thereby increasing the operation costs.
Moreover, there are no benefits to expending resources to extract the
contaminant in the aqueous phase; this was demonstrated when the
biodegradation rate imposed a narrow limit of plume migration as
demonstrated by Teramoto and Chang (2019) in the study site. Thus, the
simple maintenance of a remediation system that mostly operates while
extracting only water does not represent a sustainable option and should
be critically reviewed.
We conclude that remediation should be employed as complementary method
to accelerate the restoration of contaminated sites in tropical
climates. Under this assumption, a useful strategy for remediation
optimization is to establish a tridimensional distribution of LNAPL
based on LIF. Continuous monitoring of the water table depth may be used
as criteria to define favorable periods in which LNAPL recovery is
feasible. The operation of a pump-and-treat system should be employed
only in episodic cases in which the water table is low and most LNAPL
has been released. The physical extraction of hydrocarbons should be
understood as a complementary action to accelerate site restoration
based on source removal.
Aggressive remediation alternatives, which mainly comprise thermal
methodologies, can destroy organic contaminant mass in the subsurface
(Beyke and Fleming, 2005; McGuire et al., 2006; Falciglia et al., 2011;
Zhao et al., 2014; Hagele and Mumford, 2014). In most cases, however,
the costs of thermal remediation are infeasible and unnecessary due to
the absence of human health risks. On the other hand, the Natural Source
Zone Depletion method has developed \soutas into an attractive
approach in recent years for LNAPL contaminations, as described by
Johnson et al. (2006), Kulkarni et al. (2015), McCoy et al. (2015),
Eichert et al. (2017), Garg et al. (2017), Tomlinson et al. (2017), Lari
et al. (2019), and several others. NSZD encompasses a set of natural
processes, including dissolution, volatilization, and biodegradation
that causes mass losses of light non-aqueous phase liquid (LNAPL)
petroleum hydrocarbon constituents from the subsurface. NSZD is becoming
a critical component of hydrocarbon-contaminated site management because
the source depletion rates, driven by natural processes, are higher than
previously predicted. Furthermore, the amount of mass removed by NSZD
processes occurring at most petroleum-contaminated sites is in several
cases greater than the LNAPL mass extracted by active remediation. Based
on the findings described in this study and those previously presented
by Teramoto and Chang (2017) and Teramoto and Chang (2019), NSZD
represents the appropriate remediation approach for the study site.
CONCLUSIONS
This study describes a phenomenological process that associates the
entrapment and release of LNAPL in a pore space with seasonal water
table fluctuations, with implications for the effectiveness of active
remediation systems. Our field data indicates that the performance of
physical extraction techniques, such as pump-and-treat remediation, is
strongly affected by water table fluctuations, which are intensified in
tropical climates. The wide range of water table fluctuations, which
commonly is higher than 4 meters in tropical climates, provides
favorable conditions for LNAPL entrapment. In the study site, the
employed active remediation system was effective for four months during
the dry years, when the water table was extensively drained from the
pores and the LNAPL gained mobility. The phenomenon presented does not
represent a site-specific case; instead, it represents the norm in the
tropical climates. The findings presented in this study may therefore
have important impacts on contaminated site management schemes.