Note: Descriptions are shown in the official language in which they were submitted.
ESTABLISHMENT OF CONTAMINANT DEGRADATION RATES IN SOILS USING
TEMPERATURE GRADIENTS, ASSOCIATED METHODS, SYSTEMS AND DEVICES
CROSS-REFERENCE TO RELATED APPLICATION(S)
[001] This application claims priority to U.S. Provisional Application No.
62/151,564
filed April 23, 2015 and entitled "Establishment Of Biodegradation Rates In
Soils Using Vadose
Zone Thermal Gradients, Associated Methods, Systems And Devices," U.S.
Provisional
Application No. 62/158,823 filed May 8, 2015 and entitled "In Situ Measurement
Of Soil Fluxes
And Related Apparatus, Systems And Methods," and U.S. Provisional Application
No. 62/159,445
filed May 11, 2015 and entitled "Apparatus, System And Method For Measuring In
Situ
Microcosm Degradation Rates,".
TECHNICAL FIELD
[002] The disclosed embodiments relate to various methods, systems and
devices used to
estimate the rate of degradation of contaminants in the ground by measuring
temperature gradients
in the soil around a reactive zone where heat is produced by contaminant
degradation reactions. In
certain implementations, the temperature gradients are used to calculate the
reactive zone heat flux.
Exemplary embodiments quantify the long term, or time-integrated heat flux in
the reactive zone,
such as over a seasonal period to account for circumstances where the
groundwater and surface
temperatures vary in a cyclical manner. Exemplary embodiments can also correct
for the delay
introduced by the rate at which heat produced in the ground is propagated to
measurement points.
Various implementations are able to reduce or eliminate signal noise, such as
the noise caused by
changing ambient temperatures and other conditions. Further, a mathematical
model is provided
to test the validity of the system on two example sites.
BACKGROUND
[003] Contamination of subsurface environments by petroleum and other light
nonaqueous phase liquids ("LNAPL") is a widespread problem that raises
concerns about
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contaminant transport and groundwater pollution risks. LNAPL spills often
occur due to
pipeline breaks or leaking storage tanks near the ground surface.
Consequently, large volumes of
contaminants often accumulate in the vadose zone and on top of groundwater,
generating sources
that can pose potential groundwater and/or vadose zone pollution risks for
decades. In situ
biodegradation by native soil microorganisms (also known as natural source
zone depletion, or
"NSZD") can have strong effects on the fate of these petroleum hydrocarbon
releases under local
soil conditions.
[004] The strong dependence of microbial activity and contaminant
biodegradation on
temperature has been well documented under laboratory conditions. However, the
measurement
of local (discrete) biodegradation rates in soil has not been widely studied.
Accordingly, field
data relating degradation rates and soil temperatures is scarce. Recent work
has taken advantage
of this relationship to use increased groundwater temperatures as a line of
evidence for in situ
biodegradation. One such study was performed at a former refinery by McCoy, et
al, (2014).
Thermal anomalies in the vadose zone at contaminated soils have also been used
to estimate
aerobic biodegradation rates. However, the coupling of in situ biodegradation
rates and soil heat
transfer under variable geochemical zones of the vadose zone has not been
studied, despite the
widespread use of NSZD and enhanced biodegradation at sites across all
climates and over a
large soil and groundwater temperature ranges.
[005] There is a need in the art for improved systems, methods and devices
for
establishing biodegradation rates.
BRIEF SUMMARY
[006] Discussed herein are various methods, systems and devices relating to
the
establishment and use of contaminant degradation rates by way of soil thermal
gradients. In
certain embodiments, the measurement of a cycle comprises annual data, taken
over the course
of one or more years. In further embodiments, other durations can be used. In
certain
embodiments, the measurements are taken between two points in time having the
same or
substantially similar temperature profiles, such as between spring and fall,
or over the course of a
single month, depending on the climate and other conditions of the area. Soil
temperature
measurements are relatively inexpensive and easy to obtain year round, making
thermal
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gradients useful for monitoring NSZD. Methods presented herein are able to
estimate the NSZD
rate over a season cycle.
[007] The disclosed systems, methods and apparatus address cyclic ambient
temperature
changes in NSZD. In these circumstances, cyclic ambient temperature changes
result in short
term heat fluxes not correlated to the reaction heat and can be reversed or
otherwise vary
cyclically. In these circumstances, failing to account for cyclic variances
results in errors in the
prior art.
[008] Accordingly, by measuring cumulative heat fluxes across various
monitoring
locations - on the basis of continuous temperature measurements - the
presently disclosed
systems, methods and devices are able to counteract or otherwise prevent these
errors over time,
thereby making the measurement of heat fluxes a quantitative basis to more
accurately determine
reaction rates. Additionally, the disclosed systems, methods and devices
eliminate the need to
make measurements at a background location. The disclosed systems, methods and
devices
include various steps.
[009] In one Example, a system for establishing a rate of contaminant
biodegradation in
a reactive zone having a soil volume, including at least two temperature
sensors configured to
record soil data at a perimeter of the reactive zone, a database, the database
configured to store
the soil data; a central processor in communication with the database; and
reaction rate
estimation software configured to calculate the rate of contaminant
biodegradation from the soil
data by establishing temperature gradients at the perimeter of the reactive
zone; and time
integrated thermal heat flux at the perimeter of the reactive zone over a
temporal cycle. Other
embodiments of this aspect include corresponding computer systems, apparatus,
and computer
programs recorded on one or more computer storage devices, each configured to
perform the
actions of the methods.
[010] Implementations may include one or more of the following features.
The system
where the reaction rate estimation software is configured to model at least
one of the group of
including of contaminant degradation reactions methanogenic petroleum
degradation, methane
oxidation or aerobic petroleum biodegradation. The system where the reaction
rate estimation
software is configured to establish a biodegradation rate per unit of soil in
the soil reactive zone.
The system where the reaction rate estimation software is configured to report
groundwater heat
loss or gains from exothermic soil reactions. The system where the reaction
rate estimation
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software is configured to report the biodegradation rate without performing a
background
correction. The system where the reaction rate estimation software is
configured process at least
one of the group including of contaminant biodegradation rates, contaminant
distribution, soil
properties, ambient temperatures, groundwater temperatures, and combinations
thereof. The
system where the temporal cycle is selected from a group including about an
annual cycle and
about a seasonal cycle. The system where the reaction rate estimation software
is configured to
validate the perimeter of the reactive zone. The system where the reaction
rate estimation
software is configured to validate the rate of contaminant biodegradation
against a
biodegradation model. The method where processor is configured process at
least one of the
group including of contaminant biodegradation rates, contaminant distribution,
soil properties,
ambient temperatures, groundwater temperatures, and combinations thereof. The
method where
the exothermic reaction in the soil includes of at least one of the group
including of
methanogenic petroleum biodegradation, methane oxidation or aerobic petroleum
biodegradation. The method further including evaluating seasonal dependence of
the exothermic
reaction due to variable ambient temperatures. The method further including
establishing a
biodegradation rate per unit of soil in the reactive zone. The method further
including reporting
groundwater heat loss or gains from the exothermic reaction. The method
further including
providing a database, the database configured to store the soil data; a
central processor in
communication with the database; and reaction rate estimation software
configured to calculate
the rate of contaminant biodegradation from the soil data by establishing the
temperature
gradients at the perimeter of the reactive zone; and the time integrated
thermal heat flux at the
perimeter of the reactive zone over the course of a temporal cycle. The method
further including
providing a processor in communication with a database, where the processor is
configured to
establish the biodegradation rate of the petroleum from the recorded thermal
gradients. The
method where the rate of contaminant biodegradation in petroleum contaminated
soil includes of
at least one of the group including of methanogenic petroleum biodegradation,
methane
oxidation or aerobic petroleum biodegradation. The method further including
biodegradation rate
against a model. Implementations of the described techniques may include
hardware, a method
or process, or computer software on a computer-accessible medium.
[011] In one Example, a method of measuring a rate of an exothermic
reaction in soil
having at least one organic contaminant or contaminant reaction-intermediate,
the method
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including defining a reactive zone perimeter having an outside and an inside
including a soil
volume containing the at least one organic contaminant or contaminant reaction-
intermediate;
emplacing at least two temperature measurement devices at the reactive zone
perimeter;
recording soil data at each of the temperature measurement devices on a
database configured to
compile soil data; calculating at least one thermal gradient from the soil
data from each of the
temperature measurement devices on a processor; establishing time integrated
heat flux in the
reactive zone perimeter on the processor by calculating heat flux over time
from the soil data;
and determining an exothermic reaction rate of the contaminant or contaminant
reaction-
intermediate over a temporal cycle on the processor. Other embodiments of this
aspect include
corresponding computer systems, apparatus, and computer programs recorded on
one or more
computer storage devices, each configured to perform the actions of the
methods.
[012] Implementations may include one or more of the following features.
The method
where processor is configured process at least one of the group including of
contaminant
biodegradation rates, contaminant distribution, soil properties, ambient
temperatures,
groundwater temperatures, and combinations thereof. The method where the
exothermic reaction
in the soil includes at least one of the group including of methanogenic
petroleum
biodegradation, methane oxidation or aerobic petroleum biodegradation. The
method further
including evaluating seasonal dependence of the exothermic reaction due to
variable ambient
temperatures. The method further including establishing a biodegradation rate
per unit of soil in
the reactive zone. The method further including reporting groundwater heat
loss or gains from
the exothermic reaction. The method further including providing a database,
the database
configured to store the soil data; a central processor in communication with
the database; and
reaction rate estimation software configured to calculate the rate of
contaminant biodegradation
from the soil data by establishing the temperature gradients at the perimeter
of the reactive zone;
and the time integrated thermal heat flux at the perimeter of the reactive
zone over the course of
a temporal cycle. The method further including providing a processor in
communication with a
database. where the processor is configured to establish the biodegradation
rate of the petroleum
from the recorded thermal gradients. The method where the rate of contaminant
biodegradation
in petroleum contaminated soil includes at least one of the group including of
methanogenic
petroleum biodegradation, methane oxidation or aerobic petroleum
biodegradation. The method
further including biodegradation rate against a model. Implementations of the
described
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techniques may include hardware, a method or process, or computer software on
a computer-
accessible medium.
[013] In one Example, a method of establishing the rate of contaminant
biodegradation
in petroleum contaminated soil of a defined volume including emplacing at
least two temperature
sensors within the petroleum contaminated soil; recording thermal gradients
from the at least two
temperature sensors over about one temporal cycle; and establishing a
biodegradation rate for a
reactive zone from the recorded thermal gradients. Other embodiments of this
aspect include
corresponding computer systems, apparatus, and computer programs recorded on
one or more
computer storage devices, each configured to perform the actions of the
methods.
[014] Implementations may include one or more of the following features.
The method
further including providing a processor in communication with a database,
where the processor is
configured to establish the biodegradation rate of the petroleum from the
recorded thermal
gradients. The method where the rate of contaminant biodegradation in
petroleum contaminated
soil includes at least one of the group including of methanogenic petroleum
biodegradation,
methane oxidation or aerobic petroleum biodegradation. The method further
including
biodegradation rate against a model. Implementations of the described
techniques may include
hardware, a method or process, or computer software on a computer-accessible
medium.
[015] One or more computers can be configured to perform particular
operations or
actions by virtue of having software, firmware, hardware, or a combination of
them installed on
the system that in operation causes or cause the system to perform the
actions. One or more
computer programs can be configured to perform particular operations or
actions by virtue of
including instructions that, when executed by data processing apparatus, cause
the apparatus to
perform the actions.
[016] Other embodiments include corresponding computer systems, apparatus,
and
computer programs recorded on one or more computer storage devices, each
configured to
perform the actions of the methods. In certain embodiments, a system may be
provided that
includes a processing device and a non-transitory computer-readable medium
accessible by the
processing device. The processing device may be configured to execute logic
embodied in the
non-transitory computer-readable medium. One or more computing devices may be
adapted to
provide desired functionality by accessing software instructions rendered in a
computer-readable
form.
6
[017] When software is used, any suitable programming, scripting, or other
type of
language or combinations of languages may be used to implement the teachings
contained
herein. However, software need not be used exclusively, or at all. For
example, some
embodiments of the methods and systems set forth herein may also be
implemented by hardwired
logic or other circuitry, including but not limited to application-specific
circuits. Combinations
of computer-executed software and hard-wired logic or other circuitry may be
suitable as well.
[018] While multiple embodiments are disclosed, still other embodiments of
the
disclosure will become apparent to those skilled in the art from the following
detailed description,
which shows and describes illustrative embodiments of the disclosed apparatus,
systems and
methods. As will be realized, the disclosed apparatus, systems and methods are
capable of
modifications in various obvious aspects, all without departing from the
spirit and scope of the
disclosure. Accordingly, the drawings and detailed description are to be
regarded as illustrative in
nature and not restrictive.
BRIEF DESCRIPTION OF THE DRAWINGS
[019] FIG. lA is a flow chart showing exemplary steps of certain
implementations of the
system.
[020] FIG. 1B is a three-dimensional (3-D) schematic of a reactive zone in
the soil where
reactions occur. Reactions generate a heat flux Gõõhon, out of the reactive
zone (reactive volume, Vol
reaction).
[020a] FIG. 1C shows the server and processors running the rate
estimation software in
communication with the soil database.
[021] FIG. 2A is one-dimensional (1-D) depiction of the reactive zone of
FIG. 1B, showing
heat conduction in soil around a soil representative volume element ("RVE")
including a reactive zone
where exothermic reaction(s) occur.
[022] FIG. 2B shows heat fluxes (G) and thermal gradients (dT/clz) are at
two upper and lower
boundaries of the reactive zone, using subscripts u and l respectively.
[023] FIG. 2C is a conceptual model of a LNAPL spill site with different
geochemical
zones. Arrows indicate soil gas transport of reaction products and reactants.
Red triangles represent
heat released by different biodegradation reactions. Zones identified include:
1) the aerobic
biodegradation zone; 2) the methane oxidation zone; and 3) the petroleum
anaerobic
(methanogenic) biodegradation zone.
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[024] FIG. 3A is a flow chart depicting an overview of the system,
according to an
exemplary embodiment.
[025] FIG. 3B is a flow chart depicting an overview of the validation
model, according
to an exemplary embodiment.
[026] FIG. 3C is a flow chart depicting an exemplary embodiment of the
model
solution.
[027] FIG. 4 shows LNAPL loss estimations for the former refinery site,
compared to
model-predicted and field measured LNAPL losses. Aerobic zone boundaries were
not
evaluated as there was no contaminant in this zone.
[028] FIG. 5 Shows LNAPL loss estimations for the former refinery site,
compared to
model-predicted and field measured LNAPL losses, using daily ambient
temperatures from a
nearby weather station. Results for thermal gradient based contaminant losses
on aerobic zone
were evaluated, but overlap those of the vadose zone.
[029] FIG. 6. Shows LNAPL loss estimations for the Bemidji site, compared
to model-
predicted and field measured LNAPL losses, using daily ambient temperatures
from a nearby
weather station.
[030] FIG. 7. Shows background corrected estimated and model-predicted
LNAPL loss
rates for Bemidj using daily ambient temperatures from a nearby weather
station.
[031] FIG. 8 Shows background corrected estimated and model-predicted LNAPL
loss
rates for Bemidji LNAPL loss estimations for the Bemidji site, compared to
model-predicted
and field measured LNAPL losses, using daily ambient temperatures from a
nearby weather
station. The background correction was done by assuming the background
location to have a
different thermal conductivity (k = 0.8 J/rn/K/s instead of k= 0.7 J/m/K/s for
the reactive zone).
DETAILED DESCRIPTION
[032] Although the present system has been described with reference to
preferred
embodiments, persons skilled in the art will recognize that changes may be
made in form and
detail without departing from the spirit and scope of the invention.
[033] As shown in the drawings and description, the various embodiments
disclosed or
contemplated herein relate to systems, devices and methods of establishing and
using
8
contaminant degradation rates by way of soil thermal gradients and associated
systems and
devices. For brevity, these embodiments may be described in relation to a
"temporal heat flux
system," 10 though that is not intended to limit the scope of the disclosure
in any way.
[034] It is understood that the various embodiments of the temporal heat
flux system,
methods and devices disclosed herein can be incorporated into or used with any
other known
contaminant degradation rate systems, methods and devices. For example, the
various
embodiments disclosed herein may be incorporated into or used with any of the
devices, systems
and methods disclosed in U.S. Provisional Application No. 62/158,823 filed May
8, 2015 and
entitled "In Situ Measurement Of Soil Fluxes And Related Apparatus, Systems
And Methods,"
and U.S. Provisional Application No. 62/159,445 filed May 11, 2015 and
entitled "Apparatus,
System And Method For Measuring In Situ Microcosm Degradation Rates,".
[035] As shown in FIGS. 1A-8, the disclosed methods, systems and associated
devices
demonstrate that the use of temperature measurements in the soil can be used
to evaluate the rate
of exothermic reactions, which generate thermal anomalies in the soil. Due to
the facility of
obtaining continuous temperature data throughout the soil column, tracking
soil temperatures
offers a promising technique for establishing contaminant degradation rates.
[036] In the disclosed examples, a simplified model of coupled soil heat
transport and
petroleum hydrocarbon biodegradation of in the vadose zone was developed to
evaluate the effects
of local temperatures on contaminant degradation rates. In the disclosed
examples, the model was
applied at two sites, the Bemidji Crude Oil Research Project ("Bemidji") and
at a former refinery
in Wyoming ("Wyoming"). The examples include a coupled heat transfer and heat
generation
model based that includes multiple soil zones that are differentiated by
different geochemical
conditions, which is discussed in relation to FIG. 2C. The described
geochemical conditions result
in several reaction mechanisms, each having its own associated reaction heat.
Previous studies in
this area have been limited to a single type of reaction, such as the aerobic
biodegradation of
petroleum. This use of a reaction prevalent found only in zones in close
proximity to the ground
surface and ambient, oxygen-rich air are necessarily more limited in
application.
As discussed in the present examples, the data used as model inputs¨
contaminant degradation
rates, contaminant distribution in soil, soil properties, and ambient and
groundwater
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temperatures¨were available from previous field studies at these sites and/or
published
laboratory studies. Implementations include integration of the current vadose
zone model with
coupled groundwater and heat transport, effectively making the current 1-D
model into a full 3-D
model. The advantage of this step-wise approach is that heat impacts from
methane production
from groundwater biodegradation - methanogenic reactions - and subsequent
methane off-
gassing and oxidation in the vadose zone can be readily accounted for by this
current model and
the associated examples to reduce the overall noise and/or errors and provide
more accurate
reaction rate readings.
I. THE TEMPORAL HEAT FLUX SYSTEM
[037] In exemplary implementations, the temporal heat flux system 10 uses
observed
temperatures to estimate in situ NSZD reaction rates in a reactive zone 2 of
interest. In various
implementations described herein, the system 10 can also include a coupled
heat generation, or
temperature-dependent Monod and heat transfer model, which can be used to
validate the results
of the estimated reaction rates. Further discussion of the system 10 and model
can be found in
relation to FIGS. 3A-3C, and the validation of the system 10 with the model
can be found in
relation to FIGS. 4-8 and in Tables 1 and 2.
[038] Turning to the figures in greater detail, as best shown in FIG. 1A,
in exemplary
embodiments of the temporal heat flux system 10, several steps are performed.
In one step, a
reactive zone is defined (box 20). In one step, heat measurement devices are
emplaced within a
soil region including the reactive zone (box 30). In another step, a processor
or module is used
to calculate the thermal gradient (box 40). In yet another step, a time-
integrated heat flux is
established over a temporal cycle (box 50). Further implementations can
comprise additional
steps.
[039] Returning to FIG. 1A, the presently disclosed heat flux system 10
relates to
measuring an exothermic reaction rate in soil of at least one organic
contaminant. In certain
embodiments, the reaction can be driven by microbes. In further embodiments,
the reaction can
be driven by chemical oxidants. In various implementations, several optional
steps are
contemplated by the disclosed systems, methods and devices.
[040] According to one implementation, to evaluate reaction rates in the
reactive zone 2,
a first reactive zone perimeter 12 comprising a known volume is defined (shown
at box 20 in
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FIG. lA and in FIG. 1B). In various embodiments, a first dimension of the
reactive zone is
further defined by z, and a, where z, is the groundwater level and a is the
ground surface. An
example of one implementation of a reactive zone is shown in FIG. 1B. As used
herein, the term
"reactive zone" means the area in which exothermic reactions generate heat
flux Gre,,,,õ and can
include the vadose zone.
[041] According to one implementation of the system 10, at least two
temperature
measurement devices 14 emplaced around the first reactive zone perimeter 12
are selected for
study. In certain implementations, the temperature measurement devices are
thermocouples,
wherein each thermocouple has at least two conductors with electrical
junctions placed at testing
and reference locations with differing temperatures, respectively, to produce
a temperature-
dependent voltage thereby yielding the temperature. It is understood that each
thermocouple pair
described herein can be referred to as a single "heat measurement device." In
further
embodiments, heat flux sensors or transducers can be used though other known
temperature
measurement devices can be used in alternate embodiments.
[042] In certain implementations, each of the at least two temperature
measurement
devices is placed at a different altitude. In certain implementations, at
least four, at least six, at
least eight, at least 10, at least 12, at least 14 or at least 16 temperature
measurement devices can
be placed in the first reactive zone perimeter 12. In further examples, tens
or hundreds of
temperature measurement devices 12 can be placed.
[043] According to one embodiment, as shown in FIG. 1C, the system 10 also
has the
server or processor or processors 100 running reaction rate estimation
software 101. The
processor 100 comprises a central processor unit ("CPU") and main memory, an
input/output
interface for communicating with various databases, files, programs, and
networks (such as the
Internet), and one or more storage devices. The storage devices may be disk
drive devices or CD-
ROM devices. The processor 100 may also have a monitor or other screen device
and an input
device, such as a keyboard, a mouse, or a touch sensitive screen and may be
connected to a
network 105.
[044] According to one implementation, the processor 100 is in
communication with at
least one soil database 110. According to one embodiment, the soil database
110 contains
information regarding the time, temperature and depth at each temperature
measurement device
around the reactive zone, and the accumulation of any other kind of
information relating to each
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temperature measurement device 14A, 14B, 14C, 14D. A parameter database 115
may also be in
communication with the processor 100. The parameter database 115 contains
information
relating to any particular reactive zone, such as contaminant information,
reactive zone size
information, soil characteristics and the like.
[045] It is understood that the processor 100 can be any computer known to
those
skilled in the art. In one embodiment, the central processor 100 includes a
website hosted in at
least one or more computer servers. It is understood that any system disclosed
herein may have
one or more such server 105 and that each server may comprise a web server, a
database server
and/or application server, any of which may run on a variety of platforms.
[046] In one implementation, the central processor 100 includes software
programs or
instructions to process requests and responses. These software programs or
instructions perform
calculation, compilation, and storage functions, transmit instructions, and
generate reports. It is
understood that any embodiment of the systems 10 disclosed herein that provide
for data
collection, storage, tracking, and managing can be controlled using software
associated with the
system. It is further understood that the software utilized in the various
embodiments described
herein may be a software application or applications that are commercially
sold and normally
used by those skilled in the art or it may be a specific application or
applications coded in a
standard programming language.
[047] It is further understood that the software can be any known software
for use with
the systems described herein to track, calculate, and manage the various
parameters as described
herein. For example, as described in further detail herein, various
embodiments of the systems
described herein could have any one or more of software for tracking time,
temperature,
corrections, soil characteristics, contaminant information, or software
allowing for optimization
of any one of these parameters.
[048] The processor 100 allows access to various network resources. In one
embodiment, the central processor 100 also has access, via the network 120 or
some other
communication link, to external data sources that may be used to keep the
information in the
databases current. In one implementation, a number of site computers may be
connected to the
server at any given time, and therefore a number of facilities or locations
may utilize the system
simultaneously.
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[049] In the system 10, generally, reactive zone data (such as, for
example, time and
temperature data, etc.) entered into the system 10 via a client computer or
processor 100 is
received by the processor 100 or server 105 and stored in any of the
appropriate databases of the
system.
[050] The databases 110, 115 serve as the inputs to and information storage
for the
system 10, which processes the information as described below and generates
any one or more of
notifications, reports, work orders, suggested actions, and/or instructions to
a user or to a piece of
equipment or a third party system.
[051] Returning to FIGS. 1A-1B, in certain implementations, the system 10
performs an
optional measurement step (shown at box 30 in FIG. 1B) on the processor 100,
wherein the at
least two temperature measurement devices 14A, 14B measure a series of
temperature signals
where i is vertical location of the device with respect to the zone and t
indicates time. Further
discussion of these implementations is found herein in relation to Equations
12A-13.
[052] In various implementations, this measurement step comprises recording
and
storing the
readings, for example using computer-readable media, such as in data loggers
(for
example an Omega OM-EL-USB-1). In alternative embodiments, the Tv readings can
be
directly transmitted by wireless or wired communications to a recording module
located on a
server for subsequent.
[053] In certain implementations, a thermal gradient (dT/dz) in the sampled
soil is
calculated by the system 10 from the temperature signals Tia received from the
at least two
temperature measurement devices (shown at box 40 in FIG. 1B). In various
implementations, the
thermal gradient is calculated over the distance between the at least two
temperature
measurement devices 14 - here i and i+/ - given by dz. In these
implementations, the thermal
gradient at a given time t is given by:
aT Tit¨ Ti+, t Tit¨ Ti+Lt
1 ¨
= ¨
az t Az zi+i-zi [ ]
[054] It is understood that the system 10 establishes the time-integrated
heat flux in the
reactive zone 2, for example over a temporal cycle (shown in FIG. 1B at box
50). In various
embodiments, the system 10 utilizes an iterative algorithm so that the heat
flux (G) is repeatedly
calculated over time (to ¨> tf) Accordingly, in these implementations, the
heat flux (G) for each
13
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of the plurality of times (1) is calculated using the thermal conductivity (K)
of the media at the
specific time series t:
Gt = ¨KaTt Tz t [2]
[055] In certain implementations of the system 10, the exothermic reaction
rate or
biodegradation rate is calculated over about one temporal cycle (as shown at
box 50) by
integrating the heat flux calculated over the series of times of the about one
temporal cycle. In
these implementations, the thermal gradients (dT/dz) are measured as a
function of change in
heat flux (G) over change in time - the -time-integrated heat flux" - as
follows:
tf
It Gtdt
tf-t0
Reaction rate = _______________________________________________________ [3]
Hreact ion
where Hreact ion is the heat of reaction for contaminant degradation, as
described further in
relation to Equations 8-9. In certain implementations, this can be an aerobic
or anaerobic
reaction, as described further below in relation to FIG. 2C and Equations 20-
24.
[056] In certain implementations, by defining tf and t, to encompass time
points when
the soil temperature profiles are substantially similar - such as over one
temporal cycle of about
one seasonal cycle (such spring to fall) or one year - the resulting reaction
rate errors introduced
from discrete ambient temperature fluctuations are reduced. Further discussion
of these
implementations of the system 10 can be found in relation to Equations 6-16.
[057] In various implementations, if the soil temperature profiles differ
at times tf and to,
the estimate can be corrected based on the known or observed quantity of heat
stored in the
ground as follows:
tf
f to Gtdt -AQsoii
tf-to
Reaction rate = ______________________________________________________ [4]
H reaction
[058] In various implementations, daspii can be used to define the changes
in heat
stored in the soil within a time period defined by a final time tf and an
initial time to. For a
perimeter within a 1-D soil column, AQõ,i can be calculated using measured
depth-dependent
soil temperatures and heat capacities, as follows:
AQsou = jzz:(C p f Tf ¨ CpoTo)dz [5]
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[059] FIG. 2A shows a 1-D schematic diagram of heat conduction and heat
generation
in soil. In FIG. 2A, a representative soil volume element is shown, along with
the portion of the
soil where an exothermic reaction occurs. This 1-D simplification assumes that
changes in
temperature occur only in the vertical (z) direction. This assumption is
justified when the
contaminated site has a relatively large ground footprint as compared to the
thickness of the
contaminated soil.
[060] FIG. 2B shows the soil temperature at different elevations with
respect a reference
vertical location (datum). The temperature at the ground surface is given by
Tg, and the
temperature at the bottom of the volume element is given by Tdarum. In these
examples, Tg, can
be approximated by ambient temperatures. In circumstances where the datum is
at the
groundwater level, Tdarum corresponds to the groundwater temperature. Although
the datum
location can be anywhere within the reactive zone, the groundwater location is
a natural choice,
as groundwater temperature is often known. In various implementations, the
heat generated
within the reactive zone can be conducted - or "dissipated" - to zones above
and below the
reactive zone and/or datum. It is understood that in certain applications, the
reactive zone can
extend vertically beyond the vadose zone.
[061] FIGS. 2A-B therefore depict a single "snapshot" in time, in which
heat-generating
reactions occur at a rate sufficient to raise the soil temperatures higher
than in the surrounding
soil. In typical prior art approaches, these "snapshot" measurements have been
taken as
accurate. However, in various implementations, the exothermic reactions are
highly dynamic,
and can be caused by several temporal changes described herein.
[062] It is understood that in certain circumstances, ambient surface
temperatures (Tgs)
vary daily, weekly, monthly, seasonally, annually and the like. In certain
circumstances,
groundwater temperatures (T,4atum,1 also vary daily, weekly, monthly,
seasonally, annually and the
,
like. Other temperature variations are possible. For example, (as shown in
relation to FIGS. 4-
8), contaminant degradation rates in soil vary seasonally because of the
sensitivity of degradation
processes to local soil temperatures. In certain circumstances, reactions that
depend on microbes
- such as petroleum biodegradation - are particularly affected.
[063] Further, in certain circumstances, changes in soil properties can
occur over time,
as they depend on soil matrix composition. In these circumstances, events such
as precipitation
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and water infiltration will change the soil composition and its related
compositional properties,
such as heat capacity, thermal conductivity.
[064] Due to such temporal conditions, transient behaviors can include heat
flow
reversal near the ground surface, temporal heat accumulation within certain
regions of the soil, as
well as variable reaction and heat generation rates. In these circumstances,
using thermal
gradients and time-integrated heat fluxes to estimate degradation rates over
longer periods of
time, such as seasonally or annually. can address these temporal effects.
[065] Previous studies have accounted for these temporal effects by
measuring the
temperature profile at both a contaminated location and a non-contaminated
location, frequently
referred to as a "background correction." However, such background correction
assumes that the
only difference between impacted and background locations is the contaminant
presence,
otherwise being identical. In practice, differences in groundwater elevation,
lithology and
ambient and/or groundwater temperatures between impacted and unimpacted
locations can be
significant, leading to the introduction of large errors by the correction.
For these reasons, the
method is not quantitative, and it has been referred to as able to estimate
"minimal" degradation
rates or relative between locations.
[066] FIG. 3A depicts a detailed view of various implementations of the
system 10, for
example running reaction rate estimation software (shown in FIG. 1C at 101).
It is understood
that in various implementations of the system 10, several inputs 130 can be
used, For example, in
various implementations, soil temperatures (box 132) from a model solution
(box 132A) and/or
field measurements (box 132B) can be inputs. Soil conductivity (box 134), for
example as given
by equations 6-7 can be used as input. The reaction mechanism (box 136), which
can be
determined from the local geochemistry (described in relation to FIG. 2C) can
be input, as can
the heat of reaction (box 138), which can be established by using the reaction
mechanism (box
136).
[067] It is further understood that the system 10 is able to use these
inputs (box 130) to
perform a calculation (box 140). In so doing, the system 10 performs a number
of steps in the
reactive zone perimeter 12 (discussed above in relation to FIGS. 1A-1C). It is
further understood
that some or all of these steps may be performed by way of the processor 100
and associated
components, as is discussed in relation to FIG. 1C.
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[068] In one step, the upper and lower bounding locations of the reactive
zone 2 are
established (box 142), as is discussed in relation to Eq. 11, below. In
another step, at each
location, two contiguous temperature measurements are selected (box 144). In a
further step, the
thermal gradient at each location is calculated (box 146), as is described
herein in relation to Eq.
1 and elsewhere. In a further step, the system 10 calculates the heat flux
(box 148), as is
described in relation to Eqs. 11-13 and elsewhere herein. In a subsequent
step, the system 10
calculates the cumulative heat flux over time (box 150), as is described in
relation to Eq. 14,
below. In a further step (as shown in box 152) the system 10 divides the
cumulative heat flux
over time (box 150) by the heat of reaction (box 138) to establish the
reaction rate, as is
described in relation to Eq. 15.
[069] In an optional further step, the system 10 can verify the accuracy of
the estimated
first reactive zone perimeter 12 (box 154) by querying whether a change in the
location of the
temperature measurement devices affects the estimate (156). If the change in
location
significantly affects the estimate, the system 10 can repeat the procedure
with a second reactive
zone perimeter (box 162), selecting new measurements and repeating the
procedure (return to
box 144), as is discussed in relation to section D.
[070] In a further step, if the location does not affect the estimate, the
time can be
increased by the duration of the short term variations (box 158). The system
10 can then query
whether a significant change in the estimate was caused by the increase in
time (box 160).
[071] If an increase is observed, the calculation period is increased (box
164), and the
procedure is repeated. If no, the system can provide a final estimate of the
reaction rate as an
output (box 180).
[072] It is understood that following the calculation steps (generally at
box 140), the
system 10 is able to generate outputs (box 180), including the time-integrated
thermal flux-based
reaction rate over the period of calculation (box 182). A detailed description
of the various
contemplated steps follows.
A. Heat Flux
[073] Certain embodiments of the system 10 provide for the measurement of
heat flux,
meaning the measurement of the transport of heat across a defined plane. In
various
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implementations, the heat flux measurement is defined in terms of energy, area
and time, and can
be given by G.
[074] As shown in FIG. 1B, a reactive zone 2 where contaminants are
degraded upon
exothermic reactions produces heat. The heat produced by these contaminant
degradation
reactions is transported through the soil in a diffusion-like process called
heat conduction. Heat
conduction follows Fourier's law and gives the equation for heat flux:
G = ¨KVT [6]
where G is the heat flux (in units of heat per unit area per time, such as
J/m2.$), K is the thermal
conductivity of the media - such as soil - in units of Watt/m oC, and VT is
the temperature
gradient in C/m. The soil thermal conductivity value is the volume weighed
average from all
different phases in the soil matrix, designated by s, w and a for solid,
aqueous and air fractions,
respectively:
Ksou = Ks + Kw +Pa [7]
[075] For a given reaction, the heat of reaction nti ¨reaction is known or
can be calculated
using standard thermodynamic techniques based on the reaction of interest. For
example,
consider a reaction where an organic molecule is degraded into inorganic CO2.
In various
examples, this organic molecule be a contaminant, such as petroleum, or a
contaminant
byproduct, such as methane -. This process is called mineralization, and is
given by:
Gni-1m + (m + 02 nC 02 + ¨
4 2H2 0
( kcal
AHreaction ¨e [8]
In such a mineralization, AHõõlioõ is stoichiometric, meaning that it directly
relates to the
reaction rate. Under optimum conditions, heat flux leaving the reactive zone -
such as the first
reactive zone perimeter 12 - can be described relative to the reaction rate by
the following
expression:
Greaction = AHreaction Ratereaction [9]
[076] In practice, the exact location of the reactive zone is often not
known, so a
monitoring zone including the reactive zone can be defined. In these
implementations, both
reactive and monitoring zones are surrounded by a zone in which ambient
temperatures occur
(Voiambient). The heat fluxes measured around the reactive, monitoring, and
ambient volumes are
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shown in FIG. 1B as Gõ,reaction, G monitoring, and Gm,ambient, respectively.
In these calculations, the
first subscript in, indicates that they are measured based on thermal
gradients and the second
subscript indicates the location at which the thermal gradient is measured. In
various
implementations, the reactive zone location and the ambient boundaries are
specific aspects of
the monitoring location.
[077] FIG. 1B shows a single "snapshot" in time for an idealized condition
in which
heat-generating reactions occur at a sufficient rate to raise the soil
temperatures higher than in
the surrounding soil. At steady state, the true heat flux from reaction
(Greaction) should be equal
to the heat flux at the monitoring location (G,,,monitoring) and also should
be equal to the heat
fluxes at the reactive zone and also at the interface with ambient
(G,,,reaction and Gni, ambient,
respectively).
[078] However, the interaction between generation of heat due to reactions
and heat
transfer in soil is actually highly dynamic due to several processes. Ambient
temperatures change
daily and seasonally. Heat propagation in soil requires time. in fact,
contaminant degradation
rates are known to vary seasonally. The interaction of ambient temperatures,
heat released from
reactions, and heat transfer processes determine local soil temperatures. The
sensitivity of
reactions to such local temperatures ultimately determines the overall rate of
contaminant
degradation in soils. However, current approaches to the measurement of
reaction rates do not
account for such fluctuations.
[079] As a result of these temporal conditions, transient behaviors result
in temporal -
such as daily and seasonal - heat flow reversal near ground surface, temporal
heat accumulation
in certain regions of the soil, and variable reaction and heat generation
rates. Thus, measured
heat fluxes based on temperature gradients at any chosen location (including
the monitoring
zone, but also at the ambient interface and the reactive zone boundaries) not
only includes the
heat from reactions, but also the noise generated by cyclic ambient
temperature fluctuations
around the reactive zone.
[080] Herein, a system 10 utilizing continuous monitoring of temperatures
at fixed
locations in the soil and calculation of the degradation rates configured to
correct for fluctuations
over a full seasonal cycle is described. The system enables distinguishing the
rate of heat
generated within the soil due to contaminant biodegradation reactions from
that transferred
to/from the surrounding ambient due to ambient temperature variations. The
various disclosed
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embodiments will be illustrated with two examples in which reactions occur in
the vadose zone
(the zone where soil pores are full of gas). For simplicity, the analysis on
these examples will be
conducted in one-dimension (1-D).
B. Thermal Gradients
[081] As used herein, the term "thermal gradient" can represent a spatial
change in
temperatures. In various implementations, thermal gradient is expressed with
the units of
temperature/length, and can be given by dT/dz.
[082] As discussed above, FIG. 1B depicts a conceptual model of heat
generation from
an LNAPL spill site in several different geochemical zones. In FIG. 1B. the
arrows indicate soil-
gas transport of reaction products and reactants and the red triangles
represent heat released by
different biodegradation reactions. The zones identified include the aerobic
biodegradation zone,
the methane oxidation zone, and the petroleum anaerobic biodegradation zone,
which is also
known as the methanoaenic zone, all of which are discussed in relation to FIG.
2C.
[083] As described in realtion to FIG. 3A, using this 1-D simplification,
the relationship
between heat fluxes and temperature gradients in Equation 1 (above) can be
given by:
dT
Gz = ¨K.3011dz [10]
again, where K is the thermal conductivity of the soil, and dT/dz is the
thermal gradient.
[084] The total heat flux out of the monitoring zone, defined by the upper
and lower
reactive zone boundaries (zõ and zi, where õ and / correspond to the values at
the upper and lower
boundaries defining the reactive zone, respectively) is as follows:
G monitor ing = G + G/ = K
¨ dT I I dT
u 1-1 + K1 I¨ [11
dz u
The sign difference in the formulas for G,, and Go accounts for the geometry
of the problem:
heat fluxes leaving the reactive zone have a different sign depending on
whether they are located
above or below such heat generating zone.
[085] In certain implementations of the system 10 (for example as discussed
above in
relation to box 142 of FIG. 3A), the region of interest or reaction zone must
be defined. In these
implementations, at least two monitoring locations outside of the reactive
zone 2 can be defined.
Using a 1-D model, these monitoring zones can be defined by z/ and zu. In some
cases, z/ can be
those at the groundwater level and zu being ground surface. In these
implementations, as the
temperature fluctuations at z/ and zu vary at different scales - for example
because ambient
temperatures can vary daily - the time interval to record temperatures at each
of the selected
locations can be adjusted so the temperature variations are captured by the
system 10.
[086] In certain implementations of the system 10, a measurement step is
performed
(box 148 in FIG. 3A), wherein at least two temperatures T are measured at
neighboring locations
around the monitoring points z/ and zu to determine the thermal gradients
dT/dz at each of these
locations. In these implementations, by using the thermal gradient dT/dz, the
heat flux (G) at a
single time t at each of these locations z/ and zu can be calculated as
follows, using the thermal
conductivity (K) of the soil at time t:
irr
112A1
1,t
and
G1,1 = I
11213
' lot
for the upper and lower locations, respectively. At each time t, the total
heat flux through the
monitoring points around the reactive zone 2 is given by:
Cti,t Gtot 1131
In certain circumstances, theimar conutteu vt ty cuatige (weir time, as is
uiscusseu m leiemon
to Eq. 2.
[087] In certain implementations, a correction step can be performed. In
certain
circumstances, the heat flux estimate requires a thermal conductivity (K)
correction. In certain
implementations, the correction can be of actual soil moisture levels. In
certain implementations,
the correction can be based on in situ measurements of this soil property,
such as those described
in U.S. Provisional Application No. 62/158,823 filed May 8, 2015 and entitled
"In Situ
Measurement Of Soil Fluxes And Related Apparatus, Systems And Methods," and
U.S.
Provisional Application No. 62/159,445 filed May 11 , 2015 and entitled
"Apparatus, System And
Method For Measuring In Situ Microcosm Degradation Rates,".
[088] As shown in FIG. 3 A at box 150, in certain embodiments, the average
heat flux
over a range of time - the time-integrated heat flux (Gueaction) - can be
calculated as the cumulative
heat flux divided by the duration of the time interval:
.tt
eReactIon t,, 1141
ti-
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[089] As shown in FIG. 3A at box 152, in these embodiments, by measuring
average
heat flux over an extended interval around the reactive zone, it is possible
to reduce the effects of
short term noise from cyclic fluctuations in ambient or groundwater
temperatures. In these
embodiments, the long term average reaction rate is therefore given by:
GReaction
Ratereaction = [15]
AHReaction
[090] In circumstances where the soil temperature profiles and/or the soil
saturation -
water content" - differ at the initial and final times (to and tf,
respectively) the reaction rate
estimate can be corrected based on differences in heat stored in the
monitoring portion of the
ground as follows:
tf
r
ito Gmonitoring,tdt AQsoil
Ratereaction [16]
,AHReaction(t f¨to)
where AQõ,i is the change in heat stored in the soil within a time period
defined by a final time tf
and an initial time to. For a perimeter within a 1-D soil column, dasoil is
calculated using soil
saturation depth-dependent soil temperatures and heat capacities, thereby
yielding Equation 5,
discussed further above:
AQsoit = fzu(pf Cpf Tf ¨ po Cpo To )dz 151
zi
C. Cumulative Heat Flux Measurements
[091] In various embodiments of the system 10, heat flux data can be
compiled
cumulatively. In these implementations, the system 10 can tabulate cumulative
heat fluxes to
establish cumulative total flux Gtotai. In these implementations, when the
addition of a discrete
short term heat flux measurement G to the cumulative total Gtotai does not
result in a statistically
significant change (such as less than about 1%), the cumulative heat flux
Gtotai can be used as an
adequate estimate of the time-integrated heat flux.
D. Defining The Reactive Zone
[092] In various implementations of the system 10, the contours of the
reactive zone 2
can be further defined. "Missing" the reactive zone, such as by locating the
temperature
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measurement devices within the reactive zone, will introduce errors into the
observed reaction
rates. In these implementations, additional reactive zone perimeters can be
used to more
accurately define the reactive zone 2 and more accurately establish the
reaction rates.
[093] In certain applications, the temperature measurement devices 14 are
emplaced at
imprecise locations around the first reactive zone perimeter 12 (preferably at
the upper and lower
boundaries in a 1-D model). For example, in certain implementations, at least
four temperature
measurement devices 14 are disposed at various heights in a well.
[094] Flux measurements recorded from such imprecisely located temperature
measurement devices 14 can therefore be flawed. In certain implementations of
the system 10,
several temperature measurement devices 14 can be deployed around the reactive
zone 2 and can
be used to improve/validate the proper location for the estimated reaction
rate. In these
implementations, several steps may be performed.
[095] In one step, two temperature measurement devices 14 are disposed
around the
reactive zone 2 arc selected or emplaced and used to estimate the first
reactive zone perimeter 12
heat flux (here, G/), as described elsewhere herein.
[096] In another step, the temperature measurement devices 14 can be
relocated
outward from center of the reactive zone 2, or a new set of more distant
temperature
measurement devices 14 can be selected (in either case, defining the second
reactive zone
perimeter 22). Following this step, the second reactive zone perimeter 22 is
used to calculate a
second perimeter heat flux G2-
[097] In these implementations, if the estimate from the second reactive
zone perimeter
22 does not differ significantly from first reactive zone perimeter 12, then
the first reactive zone
perimeter 12 can be validated. If a significant difference is observed, the
above steps can be
repeated to establish a third reactive zone perimeter (not shown) and so on,
in an iterative
manner.
[098] Further, in certain implementations, the process of defining the
reactive zone can
be combined with a cumulative calculation of heat flux to establish when short
term noise is no
longer significantly impacting the cumulative calculation of heat flux G,õõd
described above.
[099] In various applications, precisely defining the reactive zone 2 is
useful to the heat
flux estimate, as would be appreciated by a skilled artisan, but can also be
useful by itself, as it
would provide insight into where the exothermic reactions are occurring.
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II. MODEL FOR COUPLED HEAT TRANSFER AND HEAT GENERATION FROM
PETROLEUM BIODEGRADATION IN SOIL
[0100] To validate and calibrate the accuracy of the presently described
system 10, a
model 200 from previous work was developed.
[0101] It is understood that in various implementations, the model 200
performs several
steps, as is shown generally in FIG. 3B. In one implementation, the system
compiles various
model inputs (box 201), performs a model solution (box 250) and generates a
model output (box
255). Further discussion of each of these steps follows.
[0102] As shown in FIG. 3C, in exemplary implementations, the model
comprises a
variety of steps. As shown in box 203, the soil thermal conductivity value,
diffusivity and/or
heat capacity of the soil matrix can be established using Eqs. 7, 25 and 26.
As shown in box 204,
the initial boundary conditions at an initial time (t,=to) can be selected,
representing the ambient
and groundwater temperatures. As shown in box 206, a discretization step can
be performed,
where the total elevation (Az) and time and (At) are distributed into multiple
intervals.
[0103] Continuing with FIG. 3C, in box 208 the initial (t, = t0) soil
temperatures are
estimated at other soil elevations T(z,to). In box 210, Eq. 20 can be used at
each time (t,) and
elevation (z) to determine heat generation rates using ql, q2, q3 from Eqns.
21B, 22B, 23B, and
the local contaminant concentrations C(z,t,) can be corrected based on given
reaction rates. In
box 212, the T profile can be solved at each time (i) over the entire soil
elevation T(z,t,) using
Eq. 24. In box 214, the time and concentration calculations for (t,) (T(z,t,)
and C(z,t,)) can be
stored in the database, as discussed above. In box 216, the time interval is
increased, t1= t, + Az,
and in box 218, new boundary conditions can be selected. In box 220, a
comparison is made
between the assessed time and final time (t, = tf); if equal, the process is
ended (box 230), if not,
the process resumes at box 210.
[0104] As discussed herein, the presently disclosed heat flux system 10 was
applied and
model-validated at two sites, the Bemidji oil spill site in Minnesota (the
Bemidji Crude Oil
Research Project, which is managed by the USGS) and at a former refinery in
Wyoming. The
data used as inputs - biodegradation rates, contaminant distribution, soil
properties, and ambient
and groundwater temperature - were available from previous field studies at
these sites and or
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published laboratory studies. Implementations include integration of the
mathematical model
coupled with a groundwater and heat transport model. The advantage of this
step-wise approach
is that heat impacts from methane production from methanogenic groundwater
biodegradation
reactions and subsequent methane off-gassing and oxidation in the vadose zone
can be readily
accounted for by this model.
A. Exothermic Reactions
[0105]
Contaminant biodegradation reactions are exothermic, meaning that they produce
energy. This energy is used by microbes to grow and to fuel their metabolism.
Once a microbial
population is established on a contaminated site undergoing natural source
depletion (NSZD) the
mass o biomass stabilizes. Although this condition will likely change over
large periods of time
(years or months, as source depletion might affect long term contaminant
composition. or as
local soil temperatures change seasonally), changes over the short term (i.e.,
days or weeks) can
be assumed negligible. This condition is known as a pseudo-steady state. Under
such pseudo-
steady state, microbial growth rates are relatively small, and most of the
energy results in heat
released to the soil. Such resulting heat is proportional to the NSZD rates,
as the heat of these
reactions is stoichiometrically related to the extent of reactions by well-
understood
thermodynamic relationships.
[0106] In
practice, the actual reactions that occur at different soil locations are
determined by the local geochemistry. A conceptual site model for petroleum
hydrocarbons and
local geochemical conditions has been described earlier (as shown on FIG. 2C).
These
geochemical gradients are defined by available electron acceptors. An aerobic
and an anaerobic
zone are clearly differentiable depending on the presence or absence of
oxygen. The interface
between these two zones is known as the aerobic/anaerobic ("A/A") interface.
[0107]
Assuming that the LNPAL contaminant is represented by an example generic
hydrocarbon (i.e.. octane, C8f118), the reactions relevant to this conceptual
model are:
kcal
C81-118 12. 502 8CO2 + 9H20 AH aerobic [
= 1' 244' 17] -mole
kcal
C8I 3.5H20 ¨> 6.25 CH4 + 1.75 CO2 AH A
methanogenesis = g¨Hc. [18]
kcal
6.25CH4 + 12.502 6.25CO2 + 12.5H20 AHCH4 ox = 1,200
¨ [19]
g HC
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[0108] The AH of Eqs.17-19 were calculated from standard heats of
formation, as is
known to the skilled artisan. In Eq. 19, the methane oxidation is based on an
assumed 6.25 moles
of methane, as that is the amount of methane produced per mole of the example
hydrocarbon
C81-118. Thus, the heat of reactions is shown on a comparable basis per one
mole of degraded
hydrocarbon. Although reactions using other terminal electron acceptors -
including TEAs, such
as sulfate, iron, nitrate and the like are possible these are in limited
supply at contaminant source
zones. After an initial spill, TEAs are typically depleted, thereby leaving
methanogenesis as the
dominant anaerobic process at source zones.
[0109] Accordingly, in this example, the methane resulting from Eq. 18
diffuses upwards
and reacts with ambient oxygen to generate CO2, per the reaction of Eq. 19. As
methane is
readily biodegraded by aerobic microbial soil populations in the presence of
oxygen, methane
oxidation often occurs rapidly in a narrow soil band.
[0110] In this example, the heat from Equation 19 is about 98% of the heat
from Eq. 17.
Conversely, the heat produced under anaerobic conditions (Eq. 18) is nearly
two orders of
magnitude smaller than that from aerobic biodegradation (Eq. 17). These very
different heat
values of these reactions highlights the need to understand the specific kinds
of reactions
occurring at different soil levels before estimating reaction rates.
[0111] The conceptual site model described above implies that some of these
reactions
might be mutually exclusive - such as aerobic vs. anaerobic - or can be co-
located - such as
methane oxidation and aerobic degradation. Heat generated from degradation of
natural soil
organic matter was not considered in this study since it is about one order of
magnitude smaller
than the heat from petroleum degradation.
B. Model Components
1. Exothermic Reaction Kinetic Component
[0112] Under the Monod equation, biodegradation reaction kinetics depend on
the
concentration of the microbial substrate or contaminant. When the microbial
biomass achieves
steady-state, the Monod kinetics expression for reaction rate is given by:
dC kmaxC koC
[20]
dt C+Cm C+Cm
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dC
where ¨ is the change in contaminant concentration over time (reaction rate),
Cm is the half-
saturation constant, and kmax is the maximum biodegradation rate, which is
equal to the zero-
order biodegradation rate (ko). The Monod constants (kinõ and Cm) are reaction
specific,
meaning they differ for aerobic or anaerobic conditions and/or based on
different substrates. The
present kinetic model predicts a constant biodegradation rate at high LNAPL
concentrations -
where C>> C, - and first-order rates at low LNAPL concentrations - where C <<
2. Biodegradation-Related Heat Generation
[0113] FIG.
2C is a conceptual model of a LNAPL spill site with different geochemical
zones: 1) the aerobic biodegradation zone; 2) the methane oxidation zone; and
3) the anaerobic
biodegradation zone. In a 1-D model, the depths of these zones are given by
the ground surface
and the aerobic/anaerobic interface (for the aerobic degradation zone), and by
the
aerobic/anaerobic interface and a shallow location where methane is no longer
available (for the
methane oxidation zone), and 3) the anaerobic/aerobic interface and a lower,
deeper datum. The
heat generation rates of each of the biodegradation reactions included in the
system 10 are
discussed below: methanogenic LNAPL degradation, methane oxidation, and
aerobic LNAPL
degradation.
[0114]
Methano genesis. Methanogenesis occurs in the lower anaerobic biodegradation
zone shown in FIG. 2C, and the reaction for a generic alkane (C11l-1211,2) is
given by:
C H +(_ 1) H20 -> (1 - -1) CH4 + - -1) CO2 [21A]
x y 4 8 2 8 2
[0115] In
various implementations, the system 10 accounts for the quantity of heat
generated by methanogenesis (qi) as follows:
dC
(11 ¨ allmethanogenesis * Tt [21B]
where dC/dt is the reaction rate for methanogenesis.
[0116]
Methane Oxidation. In FIG. 2C, methane oxidation occurs in the middle methane
oxidation zone, and is given by:
CH4 + 202 -) CO2 + 2H20 [22A]
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[0117] In
various implementations, the heat produced by methane oxidation (q2) in this
finite layer is calculated through the integrated LNAPL concentration loss in
the anaerobic zone
as follows:
'111CH4OX rZb dC
172 = * ¨ dz [22B]
ZGw dt
where .4116/4õ is the heat of reaction for methane, zb is the bottom of the
methane oxidation zone
(i.e. the depth at which the anaerobic zone begins), ZGw is depth to
groundwater, and w is the
width of the methane oxidation zone.
[0118]
Equations 22A and 22B are sequential, and imply that heat released from
methane
oxidation occurs at a different location than petroleum degradation.
Accordingly, methane is
produced in the anaerobic zone (given by Equation 21A) and it is assumed to
transport upward
relatively rapidly to the methane oxidation zone, where it degrades in a fast
reaction upon contact
with atmospheric oxygen diffusing into the vadose zone and is therefore not
rate limiting.
[0119] The
location of this zone was assumed constant, although field measurements
could be used to correct its seasonal dependence, as the location and
thickness of this zone might
depend on the magnitude of the counter-diffusive fluxes of methane and oxygen,
both of which
might vary seasonally.
[0120]
Aerobic Biodegradation. In certain circumstances, aerobic degradation of LNAPL
occurs in cases where LNAPL is present in the upper soil layers that are close
to the oxygen-rich
ambient air. Typically, however, upper soil layers typically do not contain
large quantities of
LNAPL, as has been demonstrated in the former refinery site discussed below.
However, other
sites do present aerobic zone LNAPL, such as in the Bemidji site discussed
below. Accordingly,
in certain implementations the system 10 accounts for the aerobic
biodegradation of LNAPL.
The basic chemical equation for aerobic petroleum hydrocarbon oxidation is:
CH + (x + 02 --> xCO2+ H20 [23A]
xy 4 2
[0121] As
with the methanogenic petroleum degradation, the Monod-based reaction rates
and the corresponding thermodynamic heat generation from aerobic oxidation
directly depend on
the location specific LNAPL concentrations. In various implementations,
aerobic oxidation is
accounted for from ground surface to the depth of the anaerobic zone (given by
zb). In these
implementations, the equation for aerobic biodegradation (q3) is given by:
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dC
q3= AH aerobic * ¨dt [23B]
where ATI aerobic is the heat of reaction for aerobic oxidation. Aerobic
oxidation and
methanogenesis were assumed to take place at the same rate, meaning having
equal values for
the Monod constants, which is consistent with previous results.
3. Coupled Heat Propagation And Reaction Component
[0122] In
various implementations, the second law of heat conduction can determine the
propagation of internally generated heat due to methanogenesis (qi) in the
soil:
OT a2T qi
= + [24]
at az2 pcp
2T where ¨is the second derivative of the change in temperature with respect
to depth, and qi
represents the heat generation rate per unit volume due to specific
biodegradation reactions and a
is the thermal diffusivity of the media.
[0123]
Accordingly, in some implementations the thermal diffusivity of soils is
calculated as follows:
a = ¨ [25]
p Cp
[0124] The
bulk properties of both thermal conductivity and heat capacity are
composition-weighed properties. In various implementations, the product of
density and heat
capacity is estimated as follows:
P Cp = Cp)sOs (P C)
p, w . w (I Cp)a0a [26]
[0125]
Equation 26 allows the estimation of the heat capacity of the soil matrix (Cr)
as a
composition-weighted average, where p is density, and 41) is volume fraction,
and the subscripts
s, w, and a represent the soil, water and air components, respectively.
[0126] In
exemplary embodiments of the system, a temporal heat flux system 10 is
provided. In various embodiments of a system, a model is used to estimate
reaction rates. The
model consists of several components described above, including those in
relation to Equations
20-24.
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4. Model Solution And Validation
[0127] Atmospheric and groundwater temperatures vary seasonally and
generate heat
fluxes into and out of the soil. These heat fluxes interact with heat
generated from contaminant
biodegradation. In one example, groundwater and ambient temperatures were used
as model
input boundary conditions from actual field measured data. Accordingly, these
conditions are
assumed to be imposed on the system 10, rather than being calculated by the
model. The
temperature dependence of biodegradation rates (Eq. 20) was based on results
from laboratory
microcosm studies. Model calibration was performed using available site
specific measured
field biodegradation rates from previous reports.
[0128] In this example, the model is a transient. one dimensional (1-D)
vertical, or depth
model. In this example, the use of rectangular coordinates is justified by the
much larger scale of
the horizontal LNAPL as opposed to the height of the vadose zone. In further
implementations,
other coordinate structures can be used, as would be apparent to the skilled
artisan.
[0129] The present model was solved using a numerical finite difference
approximation
of the partial derivatives (coded in Anaconda Python 2.7, Continuum
Analytics). Partial
derivatives of temperature with respect to time and space were solved
implicitly, or "backward"
in time. The discretization of the second partial derivative of temperature in
space was obtained
using the implicit and explicit (forward in time) first derivative
approximations. The Neumann
stability criterion, given by:
2
[(a) I 2a) [27
was used to determine grid-spacing (At) along the x-axis of the finite
difference approximation,
where At is the grid spacing along the time domain and Ax is the grid spacing
along the depth
domain.
[0130] Heat production for methanogenesis (qi) and aerobic oxidation (q3)
(Equations A
and C) depend on contaminant concentrations that vary with location in the
soil column, while
heat from methane oxidation (q2, Equation B), represents uniform heat
generation rate within the
methane oxidation zone. The code to solve Eqs. 20-24 was validated by setting
qi = q3 = 0,
extending the methane oxidation zone to encompass the entire vadose zone, and
adjusting
boundary conditions to a constant temperature (T).
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[0131] Under these settings, the problem becomes identical to a finite slab
with uniform
internal heat generation. The analytical solution to this problem was used to
validate the
temperature profiles predicted by the numerical model. Additionally, based on
Example 1
(discussed below) the pseudo-steady state heat flux calculated from thermal
gradients under
constant boundary conditions (surface and groundwater temperature) matched the
Monod
kinetics-based model predicted contaminant loss.)
Example 1: Former Refinery Site
[0132] The model was applied to a former refinery site to validate the
method
(invention). The site is located in a dry, high desert environment in the
western US, and has
distinct cold and warm weather seasons. The site was used for petroleum
refining and production
of asphalt and coke. Measured LNAPL concentrations vs. depth from soil cores
in transect C3
were used as model input. The zone for methane oxidation (1.1 m to 2.3 m below
ground
surface) was determined from field measured subsurface CH4 and 02 gas
concentrations, and is
consistent with identification of methane oxidizing microbes based on DNA
analysis. The soil at
this site is mostly fine to medium sand and was assumed to be at residual
water saturation (3%)
due to the arid climate of the region. Based on this moisture level, the
thermal conductivity for
this soil type (k) is known to be 0.8 J/m.K.s. the residual water content, and
estimated porosity of
44% results in a thermal diffusivity a -= 6.06*10-7 m2/s. The calculated a
value is consistent with
reported values for unsaturated sandy soil. Daily median temperatures for the
2011 calendar
year from NOAA station GHCND:USC00481569 - about 2 miles West from the site -
were used
as the surface temperature boundary condition. The groundwater temperature
boundary
condition for the same period was available from measured groundwater
temperatures in nearby
well A2).
[0133] The majority of the former refinery contaminants were observed to be
in the C6 to
C28 range. Octane (C81418) was considered a representative formula of the
contaminant. Three
measurements of petroleum biodegradation rates are available from literature
at the same
location at this site, conducted by measuring CO2 fluxes at ground level.
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I. Kinetic Data
[0134] Monod kinetic parameters were reported from previous work used to
predict
methane generation from oil sands at 22 C. Based on reported values for first-
order reaction
rates for n-octane at 22 C, ko and Cm were calculated to be 1.54 kg/m3yr and
0.476 kg/m3
respectively. The dependence of biodegradation rates on temperature was
obtained from previous
laboratory microcosm studies which quantified biogas production rates in a
temperature range of
4-40 C. Temperature dependent zero-order biodegradation rates were calculated
from biogas
production rates and used as model inputs. The data from this microcosm study
at 22 C was
within 1% of the previously observed ko value from Siddique et al., thereby
showing remarkable
consistency between laboratory and field data from both research groups. The
previously
reported biogas production by Zeman et al. was null at 9 C, although the same
report showed
measurable contaminant biodegradation at the same temperature. As previous
research
documented degradation in the range of 5-10 C temperature range, it was
determined that the 9
'V data point was inconsistent, and it was therefore was omitted, resulting in
interpolated
estimates between 4 'V and 22 'V from measurements at the end points of this
range.
II. Model Calibration
[0135] In order to calibrate the model for the former refinery zero-order
rates from soil
microcosm, the experiments were adjusted so that model outputs of LNAPL
concentration loss
matched field estimates of LNAPL loss from CO2 fluxes. The data from
encompassed three
sampling events at different times of the year, allowing a three-point
calibration for the former
refinery site. Expressed as a multiplier of the lab microcosm data, field zero-
order rates fitted in
this manner were 1.3 times higher that those for the former refinery. These
scaling factors imply
that the field rates are within one order of magnitude of those from microcosm
studies. Model
solutions developed in this manner offer a way of allocating the heat
production rate within the
soil due to biodegradation reactions observed at field sties consistently with
kinetic data
available from other laboratory studies.
[0136] Equation 6 provides the basis to estimate soil heat flux, G in
J/m2s, from
temperature gradients given by dT/dz. In various implementations of the system
10, G can be
converted to estimates of LNAPL loss (kg/m2yr) using the known heat of
biodegradation for the
specific compound being degraded (for example by using Eqs. 12-15, above).
Accordingly, the
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total heat flux (G) in a one-dimensional system (1-D) encompasses heat flow
across two
boundaries, such as the top and bottom of a soil slab, as shown in FIG. 1B. In
these
implementations, establishing the total heat flux necessitates the summation
of dT/dz at both
boundaries: top and bottom.
[0137] After the heat flux is calculated, the degradation rate can be
estimated from the
reaction thermodynamics to establish the thermal-gradient based LNAPL losses
(Loss). In
various circumstances, thermal fluxes can be located at any plane
perpendicular to the reactive
zone being analyzed. To provide sensitivity analysis to this location, three
vertical locations that
correspond to the geochemical zones considered above were chosen: the entire
vadose zone
(between ground level and the groundwater interface - LossTG,M; the methane
oxidation zone
(LossTGArox); and the aerobic zone (LossTG,AE,), defined between ground level
and the bottom of
the methane oxidation zone (as shown for example in FIG. 2C).
III. Results
[0138] FIG. 4 shows estimates of the biodegradation losses at the former
refinery site
based on the Monod biodegradation kinetics model and thermal gradients
assuming an idealized
ambient temperature profile corresponding to an annual sine wave. As shown in
FIG. 4, the
model predicted LNAPL loss rates from biodegradation kinetics (Eq. 20,
LNAPLb,o) were
compared against 3 measured field events (McCoy, 2014). FIG. 4 demonstrates
the relatively
large propensity for error in estimates based on short term thermal gradients
at two different
locations: the vadose boundary (blue) and the oxidation boundary (green)
compared to the
model-predicted LNAPL loss rates from biodegradation kinetics (LNAPLb,o)
(red). Accordingly,
comparison with the model (LNAPLb,o) indicates that using raw temperature
gradients to estimate
the rate of LNAPL biodegradation is subject to large error due to interference
from surface and
groundwater temperatures. Although the magnitude of the error seems to vary
seasonally, timing
such a period without the actual biodegradation rates would be difficult.
Finally, it was observed
that the error seems to be larger in the site with significant aerobic
biodegradation, where thermal
gradients are even more sensitive to the location.
[0139] FIG. 4 therefore shows that although thermal gradient-based reaction
rate
estimates have a large error rate, these estimates seem to oscillate around
the correct mean of the
model-based degradation rates. Because the heat propagation process requires
time and is prone
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to a time delay, and that the soil temperatures follow an annual cycle, the
long-term calculation
of the heat flux based on continuous data through the monitoring locations is
able to offer a
rigorous estimation of the heat gained and lost through those locations. As
the soil temperatures
are similar between the beginning and end of the cycles, the net heat gain or
loss during this
period is negligible.
[0140] In FIG. 5, the LNAPL loss estimates were calculated in a similar
fashion to those
in FIG. 4, however, these estimates assumed daily measured ambient
temperatures at a nearby
weather station. In FIG 5, LossTG,m0x, LossTG,AE, and LossTG,vz, are the
biodegradation rate
estimates from thermal gradients under the present system 10 using the methane
oxidation,
aerobic zone and vadose zone boundaries, respectively. As shown in FIG. 5,
under short term -
here daily - variability, FIG. 5 shows that the error of single time point
estimates of the thermal
gradient based degradation rates can also be very large.
[0141] However, to validate the temporal cycle system 10 heat flux
calculation on
continuous data, Table 1 shows the average annual calculation of degradation
rates. Again, the
three locations (LossTG,mox, LossTG,AE, and LossTG,vz) are the methane
oxidation zone, the aerobic
zone, and the entire vadose zone, however, these estimates were compiled over
the course of
annual data. The Lossmmox estimates based on the methane oxidation zone are
within 6% of the
Monod-based biodegradation kinetics target, while the vadose zone LossTGyz and
aerobic zone
LossmAE are within 2% or less. Thus, the system 10 is robust to the selection
of monitoring
locations when scaled annually, as described above.
Table 1: Annual Average LNAPL Losses (Former Refinery)
Average Annual LNAPL
Loss
Difference
Soil Zone Value from
(kg/m2yr)
LNAPLbio
Loss TG,
1.60 6.1%
mox
Loss 1G,
1.67 2.1%
AE
Loss 1G,
1.68 1.5%
vz,
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In Table 1, the model-predicted annual average biodegradation losses
(LNAPLbio) were 1.70
kg/m2yr. Loss TG,M0z, LOSSTG,AE, and Lossmyz, are the biodegradation rates
estimates of the
system 10 from thermal gradients using the methane oxidation (Loss TG, mox),
aerobic zone (Loss
TG, AE) and vadose zone (Loss TG, VZ,) boundaries, respectively.
Example 2: National Crude Oil Research Site, Bemidji MN
[0142] In
1979, a pipeline north of Bemidji, MN burst and spilled nearly 10,700 barrels
of crude oil that eventually reached the groundwater, where it has since been
a source of
contamination. Interference of the pipelines with the temperature profile was
considered
negligible due to their distance (-20 feet) away from the modeled location.
Oil saturations along
the source zone transect of the north pool oil body for well 9015 were
transformed to
hydrocarbon concentrations assuming a porosity of 38% and oil density of 777
kg/m3 (for
heptadecane). The methane oxidation zone (located 1-2 m below ground) was
determined from
both soil methane and oxygen concentration data and modeling results. The
glacial outwash
deposits on the Bemidji site have been classified as sandy gravel to gravelly
sand with an
average residual water saturation around 15%, resulting in a k = 0.7 J/m.k.s.
Equations 2 and 22
were used to calculate a = 3.58*10-7 m2/s. The daily boundary conditions from
surface and
groundwater temperatures used as model inputs were available from reported
data: a) median
surface temperatures were from NOAA station GHCND:US0000MBEM for 2012 (distant
about
mi E from Well 9015) b) 2012 calendar year groundwater temperature for well
9015 (USGS,
2014, online database).
[0143]
Heptadecane (C17H36) was chosen as the characteristic hydrocarbon for the
Bemidji site, consistent with site-specific analysis of the products
identified in the source zone.
The reactions and their respective heats are shown below. Similarly than for
octane, the heat of
reaction from methane oxidation heat also represents 98% of the heat of the
heat of combustion.
kcal
C17H36 + 8. 502 8. 5CO2 + 18H20 ,6,11aerobic
= 2,553. 1 [28] ¨mole
kcal
C171136 8H20 13CH4 13CH4
4CO2 AHmethanogenesis ¨ 52.4 ¨ [29]
g HC
13CH4 12.502 ¨> 6.25CO2 + 12.5H20 ,6a-ICH4 ox =
2,500.7 ¨kcal
[30]
g HC
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[0144] The same values for ko and Cm used for the former refinery site (for
octane,
C8F118) were used for heptadecane degradation on the Bemidji site due to lack
of specific Monod
kinetic parameters for heavy hydrocarbons.
I. Model Solution, Validation, and Calibration
[0145] In order to calibrate the model for the former refinery and Bemidji
sites, zero-
order rates from in situ soil microcosm experiments were adjusted so that
model outputs of
LNAPL concentration loss matched field estimates of LNAPL loss from CO2
fluxes. Six
estimates for NSZD rates on the Bemidji site were available for a location
near well 9015 over a
1 year calendar year period (based on CO2 flux corrected for natural soil
respiration measured at
a nearby background location). Expressed as a multiplier of the lab microcosm
data, field zero-
order rates fitted in this manner were 0.38 for the Bemidji site. The higher
biodegradability
observed for Example 1 (the former refinery, characterized by the lower
molecular weight
octane), with a multiplier of 1.3, is consistent, as smaller molecules are
known to be more
biodegradable.
II. Results
[0146] Assuming daily measured ambient temperatures at a nearby weather
station, FIG.
6 shows estimates of the biodegradation losses at the Bemidji site based on
the Monod
biodegradation kinetics model, and based on thermal gradients. The model-
predicted LNAPL
loss rates from biodegradation kinetics (LNAPLbio - red line) were calibrated
against six
measured events. FIG. 6 illustrates the large error on the estimates based on
thermal gradients at
three different locations (green, blue, and gray lines) compared to the Monod-
based target
estimates (red line).
[0147] An implementation of the system 10 to calculate the long term
reaction rates
based on continuous measurements is shown in Table 2. Applied to two of the
three locations
(vadose zone and aerobic zone), the system 10 results in an estimation of
biodegradation rates
within less than 1.5% of the target Monod-based biodegradation rates. The
third location (the
methane oxidation zone) results in larger error (18.9%) because these limits
do not encompass
the whole reactive zone (which in this case includes shallow locations where
the contaminant is
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subject to aerobic conditions and thus undergoes degradation). As in the
Example 1 (the former
refinery) the method proposed is robust to the selection of monitoring
locations, as long as they
include the zones where heat is released. Although in this case two different
reactions occur
within the reactive zone (aerobic petroleum degradation and methane
oxidation), the heat from
both reactions is similar. such as within about 2%. Thus, not knowing the
extent of each of these
two degradation pathways does not introduce significant error in the
calculation.
[0148] Previously, a method consisting of using a correction based on the
difference
between the contaminant-impacted location and an unimpacted (background)
location has been
proposed. This method has been called the background correction. It has been
applied to
discreet. single time soil temperature profiles. The results of such
background correction in
combination with the method proposed here are shown in Table 2. It can be seen
that application
of the background correction in addition to the method proposed here does not
improve the
biodegradation rate estimates, which would be nearly impossible to replicate
in ongoing field
studies.
Table 2: Annual Average LNAPL Losses at the Bemidji site.
Average Annual LNAPL Annual Average Background
Loss Corr. LNAPL Loss
Difference
Value Value Difference from
Soil Zone - from 2
LNAPLb,,
(kg/myr) (kg/myr) LNAPLbio
Loss TG, 1140x 0.79 18.9% 0.79 19.0%
Loss TG, AE 0.96 1.5% 0.96 1.5%
Loss TO, VZ 0.97 0.1% 0.97 0.1%
In Table 2, the model-predicted annual average biodegradation losses
(LNAPLbio) were 0.97
kg/m2y. Loss TO, mox, Loss TO, AE, and Loss TO Vz, are the biodegradation
rates estimates of the
system 10 from thermal gradients using the methane oxidation (Loss TO M0x),
aerobic zone (Loss
To, AE) and vadose zone (Loss To, vz,) boundaries, respectively.
CONCLUSIONS
[0149] Temporal soil temperatures trends at both relatively shallow, cold
weather sites
studied suggest that thermal regimes in the subsurface change on a seasonal
basis, and are
controlled to a large degree by surface and groundwater temperatures. Model
predicted
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temperatures within the soil confirm empirical field observations that
biodegradation rates at
contaminated sites might be seasonal, with maximum rates towards the late
summer/early fall
and minimal during the winter. Thus, field measurements of long term
biodegradation rates need
to account for such seasonal variability.
[0150] The model validates that the presently disclosed system represents
significant
improvements in the art. In a prior art study invoking discrete soil
temperature measurements in
Sweeney and Ririe (2014)("Sweeney") were taken by lowering a sensor into an
existing well.
Such data collection method introduces large errors, as the existing well acts
as a mixing cell,
resulting in the well void having different temperatures than the surrounding
soil. The procedure
used by Sweeney consists of taking a single reading of temperature profiles
within a well to
establish the T(z) data series as the basis for the thermal gradient and heat
flux. The background
correction was implemented by repeating the procedure at an unimpacted
location, with the
difference in temperatures at impacted and background correction used to
determine the
background corrected heat flux due to biodegradation reactions.
[0151] The present system differs in several important ways. First, the
Sweeney
procedure only uses one specific reaction: the aerobic degradation of
petroleum. It does not
apply to the anaerobic degradation of petroleum as in the invention, which
applies to multiple
mechanisms. Second, the Sweeney procedure to estimate aerobic biodegradation
is
acknowledged by Sweeney as semiquantitative by indicating it is a minimum rate
or a relative
rate. The Sweeney procedure is described as one to determine reaction rates at
discrete times.
The present system 10 on the contrary measures the long-term average (time
integrated)
degradation rate, as it is acknowledged that the discrete calculation has a
large error rate, even
with the background correction. Third, the Sweeney procedure requires a
background correction.
The present system does not require a background correction, as the error
introduced by short-
term measurements is dealt with by performing measurements over a large time
scale. Finally,
Sweeny teaches the use of a constant heat conductivity, while the present
system 10 does not.
[0152] The model was useful for distinguishing soil heat generated from
biodegradation
of petroleum hydrocarbons versus the noise due to variable groundwater and
ambient
temperatures. Thus, estimating the rate of contaminant biodegradation by
measuring thermal
gradient-based heat fluxes in the soil is promising. Soil temperature
measurements are relatively
inexpensive and easy to obtain year round, making thermal gradients useful for
monitoring
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NSZD. Methods presented in this paper have the potential to estimate NSZD
rates at sites where
other methods are difficult to implement.
[0153] The model enabled identification of the following lessons toward the
implementation of such methodology.
[0154] Thermal processes in the soil are complex, as boundary conditions
from
groundwater and ambient temperatures change, and there is a time delay for the
heat generated
by reactions within the soil to locations where the thermal gradients are
measured. Thus, the
model suggests that single time raw thermal gradients (without correction)
proved to be subject
to high error in making an adequate estimate of single time biodegradation
rates based on heat
fluxes.
[0155] Both of the two corrections to the raw thermal gradients tested in
this work,
background correction and long term time integration significantly improved
the estimate of
biodegradation losses based on thermal gradients. Both corrections can be used
in combination.
[0156] Averaging thermal fluxes over a full seasonal cycle showed to be the
most
effective single correction to estimate long-term annual biodegradation rates.
When compared to
the target values from model-predicted biodegradation rates based on Monod
biodegradation
kinetics, the annual average was within 3% of the target for the former
refinery site, and 2% of
the target for the Bemidji site when considering the aerobic and vadose zone
boundaries. When
thermal gradient locations were chosen at the methane oxidation zone (not
including the full
reactive zone at the Bemidji site, which has a distinct aerobic zone), the
error increased to 19%
difference from the target. This highlights the importance of choosing the
thermal gradient
locations outside of the biologically reactive zone.
[0157] The background correction alone was able to provide single time
estimates within
approximately 10% of the target values for the site without an aerobic zone
for the full year,
and within about 30% for the Bemidji site. As in the case of the long term
average thermal
fluxes, selection of the thermal gradient boundaries within the reactive zone
(the methane
oxidation zone in the Bemidji site) and far from the location of heat
generation (the vadose zone
on the Bemidji site) generated significant error in LNAPL loss estimation.
Choosing boundaries
that encompass the majority of the heat generated while being close to the
source (i.e. the aerobic
zone on Bemidji) produces the closest LNAPL loss estimation to the target.
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[0158] It is noted that for the background correction, both contaminated
and background
locations were identical (except for the presence of contaminant). A practical
limitation is that
such condition would be difficult to replicate in the field, as it is subject
to site heterogeneity or
local conditions, even if a contaminant-free background location were
available. For example,
previous work suggests that contaminated locations have higher groundwater
temperatures which
may be affected by cumulative upstream thermal effects due to contaminant
degradation.
Parametric sensitivity analysis indicated that a small difference in
properties such as about 3% in
soil moisture between background location and an impacted location (other than
the presence of
contaminant) can led to error rates in the order of 300%.
[0159] When used in combination, the background correction did not improve
estimates
based on annual long term thermal fluxes. These results imply that a
background correction is
not needed for estimation of a long term. cyclic or temporal average LNAPL
loss rate, although
it can be used in combination if single time estimates throughout the year are
desired. Not
having to use a background location decreases the chance for error from using
an imperfect
background location.
[0160] As used herein, the terms -optional" or "optionally" mean that the
subsequently
described event or circumstance can or cannot occur, and that the description
includes instances
where said event or circumstance occurs and instances where it does not.
[0161] As used herein, ranges can be expressed herein as from "about" one
particular
value, and/or to "about" another particular value. When such a range is
expressed, a further
aspect includes from the one particular value and/or to the other particular
value. Similarly, when
values are expressed as approximations, by use of the antecedent "about," it
will be understood
that the particular value forms a further aspect. It will be further
understood that the endpoints of
each of the ranges are significant both in relation to the other endpoint, and
independently of the
other endpoint. It is also understood that there are a number of values
disclosed herein, and that
each value is also herein disclosed as "about" that particular value in
addition to the value itself.
For example, if the value "10" is disclosed, then "about 10" is also
disclosed. It is also
understood that each unit between two particular units are also disclosed. For
example, if 10 and
15 are disclosed, then 11, 12, 13, and 14 are also disclosed.
[0162] The foregoing description and drawings comprise illustrative
embodiments of the
present inventions. The foregoing embodiments and the methods described herein
may vary
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WO 2016/172714 PCT/1JS2016/029225
based on the ability, experience, and preference of those skilled in the art.
Merely listing the
steps of the method in a certain order does not constitute any limitation on
the order of the steps
of the method. The foregoing description and drawings merely explain and
illustrate the
invention, and the invention is not limited thereto, except insofar as the
claims are so limited.
Those skilled in the art who have the disclosure before them will be able to
make modifications
and variations therein without departing from the scope of the invention.
[0163] Although the disclosure has been described with reference to
preferred
embodiments, persons skilled in the art will recognize that changes may be
made in form and
detail without departing from the spirit and scope of the disclosed apparatus,
systems and
methods.
41
