WORKSHOP ON SOIL VACUUM EXTRACTION
APRIL 27 and 28,1989
ROBERT S. KERR ENVIRONMENTAL RESEARCH LABORATORY (RSKERL)
ADA, OKLAHOMA
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WORKSHOP ON SOIL VACUUM EXTRACTION
APRIL 27 and 28,1989
ROBERT S. KERR ENVIRONMENTAL RESEARCH LABORATORY (RSKERL)
ADA, OKLAHOMA
Technical Coordinator: Dominic DiGMio
WORKSHOP DESCRIPTION
The Superfund Amendments and Reauthorization Act (SARA) of 1986 requires EPA and responsible
parties to use permanent and cost-effective technologies to remediate hazardous waste sites while providing for
adequate protection of public health and the environment. Many sites on the National Priorities List (NPL)
contain soils with elevated levels of organic compounds which are presently contaminating or have the potential
to contaminate ground water. Soils remediation is frequently the most expensive aspect of site clean-up. Re-
cently, a relatively inexpensive technology utilizing an applied subsurface vacuum has been employed at several
NPL sites resulting in significant mass loss of volatile organic compounds (VOCs) from soils. The technology has
been called soil vacuum extraction (SVE) or soil venting and is presently receiving great interest in the hazardous
waste industry.
Soil vacuum extraction is a very exciting technology since it has the potential to remediate soils contain-
ing a variety of organic contaminants at relatively low cost. Potential applications of SVE include: removal of
volatile light non-aqueous phase liquids (e.g gasoline) from the capillary fringe; control of explosive vapors (e.g.
gasoline) or harmful gases (e.g. radon); and removal of organic compounds from soils. When used in conjunction
with dewatering techniques, vacuum extraction could also aid in aquifer remediation when most of the contami-
nant mass is near the water table surface.
At present, vacuum extraction has only been used to remediate soils containing volatile organic com-
pounds. Laboratory and field scale studies and numerous case histories have shown that SVE can remove an
impressive mass of VOCs from sandy soils in a short period of time. There is concern, however, on the ability of
SVE to remediate soils to low concentrations (parts per billion) typically required by federal and state regulatory
agencies within a reasonable period of time.
Although soil vacuum extraction has of yet only been used to remove volatile organic compounds from
soils, one of the most promising uses of this technology is in the enhancement of biodegradation of volatile and
nonvolatile organic contaminants. Oxygen is usually the limiting factor for aerobic biodegradation in the subsur-
face. Vacuum extraction offers an opportunity to circulate air in soil at depths greater than is possible by tilling
and at least conceptually should be more effective than injecting or flooding soils with hydrogen peroxide.
Vacuum extraction could also be used to enhance degradation of contaminants for which microbes require
methane as a carbon source. Another potential use of vacuum extraction is to circulate gases such as ozone which
may abiotically degrade organic contaminants. Using vacuum extraction to enhance abiotic or biotic degradation
may be more cost-effective than using the technology only to enhance volatilization since the need to treat
effluent vapors is minimized or eliminated.
When evaluating the potential effectiveness of soil vacuum extraction to enhance volatilization or
degradation, an understanding of complex physiochemical and biological processes occurring in the subsurface is
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necessary. For instance, many volatile organic compounds such as trichloroethene (TCE) are used as degreasers
and are thus present in soils as an oily mixture. The presence of an oil phase may suppress the volatility of VOCs
due to partitioning into the oil matrix and preferential air flow around oil saturated soils. In heterogeneous soils,
slow diffusion of organic compounds from fine grain soils into more permeable soils will cause physical sorption
nonequilibrium which may severally restrict the effectiveness of SVE
When designing soil vacuum extraction systems, one must realize that the effectiveness of this technol-
ogy is controlled by subsurface fluid flow and contaminant transport The analogy to aquifer restoration is
obvious where the effectiveness of remediation is controlled by similar processes. Thus, many of the field and
laboratory techniques used to determine hydraulic, physiochemical and, biological characteristics and variability
of aquifer sediment and water could be modified and used when designing SVE systems. Unfortunately in most
cases, the application of soil vacuum extraction has been limited to an "engineering judgment" approach. Infor-
mation is typically collected which is not applicable at other sites and can not be used to predict the ability of the
technology to meet stipulated soil cleanup levels nor improve the effectiveness of the process beyond engineering
modifications (e.g. impermeable cover).
The purpose of this workshop is to bring together researchers from various disciplines to discuss methods
of evaluating and enhancing the performance of S YE, The emphasis of the workshop will be on understanding
and evaluating subsurface vapor transport and fate processes. In addition to focusing future research, the work-
shop will better enable EPA research laboratories to provide technical assistance to the EPA regional offices. The
workshop is organized into five sessions: (1) Understanding Physiochemical Processes Influencing Enhanced
Volatilization; (2) Advances in Convective Vapor Transport Modeling; (3) Application of Laboratory and Field
Scale Studies in Enhancing and Evaluating SVE; (4) Enhancement of Abiotic and Biotic Degradation Using Soil
Vacuum Extraction, and (5) A Round Table Discussion. The round table discussion will be used to identify
research needs and discuss recommendations for conducting modeling, and laboratory and field scale tests to
enhance or evaluate site-specific use for SVE,
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Workshop on Soil Vacuum Extraction
April 27-28,1989
Robert S. Kerr Environmental Research Laboratory
Conference Room
Technical Coordinator: Dominic DiGiulio, RSKERL
Davl
8:30 a.m. Open ing Rem arks. Overview and Purpose of Workshop • Dick Scalf and Dom DiGiulio,
RSKERL
UNDERSTANDING PHYSIOCHEMICAL PROCESSES INFLUENCING
ENHANCED VOLATILIZATION
9:00 a.m. Dar ;ble, Louisiana State University. Physiochemical Processes Influencing Volatilization
9:40 a.m. Simon Davies, NSI (RSKERL), The Influence of Soil Characteristics on the Sorption Behavior
of Organic Vapors
10:20 a.m. Break (20 minutes)
10:40 a.m. Dermont B ouchard, RS KERL. The Role of Sorption in Contaminant Transport
ADVANCES IN CONVECTIYE VAPOR TRANSPORT MODELING
11:20 a.m. Jong Soo Cho, RSKERL, Soil Vacuum Extraction: Basic Principles in Gas Movement ofVOCs
12:00 a.m. Lunch
1:00 p.m. Jon Sykes, University of Waterloo, Modeling the Transport of Volatile Organics in Variability
Saturated Media
1:40 p.m. David Wilson, Vanderbili University, Modeling of Soil Vapor Stripping
2:20 p.m. Break (20 minutes)
2:40 p.m. Marion Kemblowski, Shell Development, Application of Soil Vacuum Extraction-Screening
Models and Field Considerations
APPLICATION OF LABORATORY AND FIELD SCALE STUDIES
IN ENHANCING AND EVALUATING SVE
3:20 p.m. Rick Johnson, Oregon Graduate Center, Soil Vacuum Extraction: Laboratory and Physical
Model Studies
4:00 p.m. Break (20 minutes)
4:20 p.m. David Krcamer, Arizona Stale University, Use of Trace Gases to Augment Field Investigation
for Vacuum Extraction
5:00 p.m. Adjourn
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Dav 2
8:30 ajn.
9:10 ajn.
APPLICATION OF LABORATORY AND FIELD SCALE STUDIES
IN ENHANCING AND EVALUATING SVE
(continued)
Robert Sterrett, Hydrologic Consultants, Inc., Analysis of In Situ Soil Air Stripping Data
Dorothy Keech, Chevron Oil Field Research, Subsurface Venting Research and Venting
by the American Petroleum Research Institute
9:50 am Break (20 minutes)
ROUNDTABLE DISCUSSION
(Restricted to Workshop Participants)
10:10 a.m. RoundTable Discussion
12:00 a.m. Lunch
1:00 p.m. RoundTable Discussion (continued)
1:40 p.m. Break (20 minutes)
ENHANCEMENT OF ABIOTIC AND BIOTIC DEGRADATION
USING SOIL VACUUM EXTRACTION
2:00 p.m. Susan Masten, NSI (RSKERL), Feasibility of Using Ozone in Place of Air in Vapor Stripping
Systems
2:40 p.m. Dave Ostendorf, University of Massachusetts (RSKERL), Biodegradation of Hydrocarbon
Vapors in the Unsaturated Zone
3:20 p.m. Break (20 minutes)
3:40 p.m. Ryan Duponl, Utah State University, Laboratory Scale Evaluation of'EnhancedBiodegradation
During Soil Vacuum Extraction
4:20 p.m. Rob Hinchee, Baiielle, Bioventing, Enhanced Biodegradation Through Soil Venting
5:00 p.m. Adjourn
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Workshop on Soil Vacuum Extraction
April 27-28,1989
Robert S. Kerr Environmental Research Laboratory
Bruce Bauman
American Petroleum Institute
1220 L. Street, NW
Washington, DC 20005
202/682-8345
Dermont Bouchard
U.S. EPA, RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
Jong Soo Cho
U.S. EPA, RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
Dom DiGiulio
U.S. EPA, RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
Ron Drake
Dynamac.RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
R. Ryan Dupont
Utah State University
Logan, UT 84321
801/750-3227
Evan Fan
U.S. EPA, UST Program
RREL. Mail Stop NS-104
GSA Rariton Depot
Woodbridge Age.
Edison, NJ 08837
FTS 340-6924
Paul van der Heijde
IGWMC
Holcomb Research Institute
Butler University
4600 Sunset Avenue
Indianapolis, IN 46208
317/283-9458
Robert E. Hinchee
BatteUe
Columbus Division
505 King Avenue
Columbus, OH 43201-2693
614/424-4698
Scott Huling
U.S. EPA, RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
Rick Johnson
Oregon Graduate Center
Dept. of Environ. Sci. & Engr.
Water Research Laboratory
19600 N.W. Von Neumann Dr.
Beaverton, OR 97006-1999
503/690-1121
Dorothy Keech
Chevron Oil Field Research
P.O. Box 446
LaHabre,CA 90631
213/694-7590
Marian Kemblowski
Shell Development Co.
P.O. Box 1380
Houston, TX 77001
713/493-8313
David Kreamer
Arizona State University
DepL of Civil Engr.
Tempe, AZ 85287
602/965-1734
Ralph Ludwig
Dynamac, RSKERL
P.O.Box 1198
Ada, OK 74820
405/332-8800
Susan Masten
NSI, RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
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p. 2
James McNabb "
U.S. EPA, RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
David Ostendorf
University of Massachusetts
Civil Engr. DepL
Amherst, MA 01003
Tom Pederson
COM
1 Center Plaza
Boston, MA 02108
617/742-5151
Dan Reible
Louisiana State University
Dept. of Chemical Engr.
Baton Rouge, LA 70803
504/388-3070
Randall Ross
U.S. EPA, RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
Dick Scalf
U.S.EPA, RSKERL
P.O. Box 1198
Ada. OK 74820
405/332-8800
Ron Sims
Utah State University
UMC-82
Logan. UT 84321
801/750-2926
Judy Sims
Utah State University
UMC-82
Logan, UT 84321
Don Stemitzke
Dynamac, RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
Robert Steirett
Hydrologic Consultants, Inc.
12596 W. Bayaud Avenue
Suite 290
Lake wood, CO 80228
303/969-8033
Jon Sykes
Dept. of Civil Engr.
University of Waterloo
Waterloo. Ontario
Canada N2L3G1
519/885-1211
Jim Weaver
U.S. EPA. RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
Ron Wilhelm
U.S.EPA
401 M Street, SW
Washington, DC 20460
202/382-4847
John Wilson
U.S. EPA, RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
David Wilson
Yanderbilt University
Dept of Chemistry
P.O. Box 1822-B
Nashville, TN 37235
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Workshop on Soil Vacuum Extraction
April 27-28,1989
Robert S. Kerr Environmental Research Laboratory
Bruce Bauman
American Petroleum Institute
1220 L. Street, NW
Washington, DC 20005
202/682-8345
Derrnont Bouchard
U.S. EPA, RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
Jong Soo Cho
U.S. EPA, RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
Dom DiGiulio
U.S. EPA, RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
Ron Drake
Dynamac, RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
R. Ryan Dupont
Utah State University
Logan, UT 84321
801/750-3227
Evan Fan
U.S. EP A, UST Program
RREL, Mail Stop NS-104
GSA Rariton Depot
Woodbridge Age.
Edison, NJ 08837
FTS 340-6924
Paul van der Heijde
IGWMC
Holcomb Research Institute
Butler University
4600 Sunset Avenue
Indianapolis, IN 46208
317/283-9458
Robert E Hinchee
BatteUe
Columbus Division
505 King Avenue
Columbus, OH 43201-2693
614/424-4698
Scott Huling
U.S. EPA, RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
Rick Johnson
Oregon Graduate Center
DepL of Environ. Sci. & Engr.
Water Research Laboratory
19600 N.W. Von Neumann Dr.
Beaverton.OR 97006-1999
503/690-1121
Dorothy Keech
Chevron Oil Field Research
P.O. Box 446
LaHabre,CA 90631 I
213/694-7590
Marian Kemblowski
Shell Development Co.
P.O. Box 1380
Houston, TX 77001
713/493-8313
David Kreamer
Arizona State University
Dept. of Civil Engr.
Tempe,AZ 85287
602/965-1734
Ralph Ludwig
Dynamac, RSKERL
P.O.Box 1198
Ada, OK 74820
405/332-8800
Susan Masten
NSI, RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
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p. 2
James McNabb
U.S. EPA, RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
David Ostendorf
University of Massachusetts
Civil Engr, DepL
Amhersl, MA 01003
Tom Pederson
CDM
1 Center Plaza
Boston, MA 02108
617/742-5151
Dan Reible
Louisiana State University
Dept. of Chemical Engr.
Baton Rouge, LA 70803
504/388-3070
Randall Ross
U.S. EPA, RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
Dick Scalf
US. EPA, RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
Ron Sims
Utah State University
UMC-82
Logan, UT 84321
801/750-2926
Judy Sims
Utah State University
UMC-82
Logan, UT 84321
Don Stemitzke
Dynamac, RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
Robert Sterrett
Hydrologic Consultants, Inc.
12596 W. Bayaud Avenue
Suite 290
Lakewood, CO 80228
303/969-8033
Jon Sykes
Dept. of Qvil Engr.
University of Waterloo
Waterloo, Ontario
Canada N2L3G1
519/885-1211
Jim Weaver
U.S. EPA, RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
Ron Wilhelm
U.S. EPA
401 M Street, SW
Washington. DC 20460
202/382-4847
John Wilson
U.S. EPA, RSKERL
P.O. Box 1198
Ada, OK 74820
405/332-8800
David Wilson
Vanderbilt University
Dept. of Chemistry
P.O. Box 1822-B
Nashville, TN 37235
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Introduction to PhyBiochemical Processes Influencing
Enhanced Volatization
Danny D. Reible
Department of Chemical Engineering
Louisiana State University
Baton Rouge, LA 70809
Presented at the Workshop on Soil Vacuum Extraction
RS Rerr Environmental Research Laboratory
Ada, OK
April 27, 1989
This presentation will review the basic equilibrium and rate processes
that influence the effectiveness of vacuum extraction of organic chemicals
from contaminated soils. The concept of partitioning between fluid phases
based on fugacities will be reviewed and applied. Common assumptions about
parameter values, techniques for estimation of parameters and sensitivity
of parameters to temperature will be emphasized. The BET isotherm for de-
scribing vapor sorption on soils will be discussed. The significant re-
duction in soil vapor sorption with soil water content will be summarized
with data. A conceptual model identifying key phase interfaces in the air,
water, soil and non-aqueous phase liquid system will be presented and its
implications for limiting mass transfer rates across these interfaces sum-
marized. Mass transfer resistances associated with the discontinuous res-
idual ganglia of non-aqueous phase liquid will also be identified.
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Introduction to Physiochemical Processes
Influencing Enhanced Volatization
by
Danny D. Reible
Department of Chemical Engineering
Louisiana Slate University
Baton Rouge, LA 70809
Presented at the Workshop on Soil Vacuum Extraction
RS Kerr Environmental Research Laboratory
Ada, OK
April 27, 1989
-1-
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Objectives and Focus
Introduce fundamental concepts
Provide a common basis for subsequent presentations
Focus:
Identification of key processes
Parameters that define those processes
Interrelationships between phases
(Air, Water, Soil and NAPL)
-2-
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Air- Water Interface
Air
C2i
Water
Equilibrium
fii = f2i (Fugacities - Corrected Pressure)
f j° = 1 atm
Y2 = — (Henry's Law)
X2S
°
-3-
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NAPL - Air Interface
Air
c..
4i
X..
4i
NAPL
Equilibrium
f h = f4i (Fugacities - Corrected Pressure)
Yl=
f ° =
Y4
y4
l
1 atm
= 1 (Raoult's Law)
* 1 (UNIFAC, Scatchard-Hildebrand Theory)
f° =
I4 -
X4i
= H X4i
•4-
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NAPL - Water Interface
Water
C4i
X.7*
4i
NAPL
Equilibrium
f2i = f4i (Fugacities - Corrected Pressure)
1
s
Y4
Y4
1 (Raoult's Law)
1 (UNIFAC, Scatchard-Hildebrand Theory)
X2i ~ X2S X4i
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NAPL - Fluid Interfacial Transport
Fluid
C4i
..
4i
NAPL
Transport
NA = kj (XH - Xj
= k4 (x4 - x4i) = Kj (x4 y4 Pv-
F"
K4
Two Film Theory Result- Partitioning dependent rates
H»l , NAPL phase controlling
H«l , Air phase controlling
Complications
Dynamic composition of NAPL
Bulk transport of mass/heat at high transport rates
"Skinning" effect
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NAPL - Fluid Interface
irameters
Activity Coefficient in NAPL - Y4
Scatchard-Hildebrand Theory
UNIFAC/UNIQUAC
Temperature dependence
_ h*
Aqueous Solubility (Inverse of y2)
Tabulated
KOW Correlations
Temperature Dependence
Follows temperature dependence of y2
Pure Component Vapor Pressure
Tabulated
Temperature Dependence
AH
-7-
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Air- Soil Interface
Damp
o
<2% 2-4% >5%
Equilibrium
Dry - Soil sorption controlled by air-soil partitioning
BET - multilayer adsorption - "S" shaped isotherm
Wet - Soil sorption controlled by water-soil paritioning
Vaporization controlled by water-vapor partitioning
Soil=> Water =* Air
Damp - Sorption from mixed phases
Soil
Water
Contaminant Vapor Pressures
Wet Soil» Damp Soil» Dry Soil
-8-
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• Benzene
• Ch lore benzene
A p-Dichlorobenzene
o m-Dichlorobenzene
A 1,2,4-Trichlorobenzerte
o Water (23.6
"0 0.2 0.4 O.e 0.8 1.0
Relative Vapor Concentration, f/f
Figure 1-9 Uptake of organic vapors and moisture by dry Woodbum
soil at 20 °C vs. relative vapor concentration.
40
S30|-
o
o
= 20
10
m-Diehloroben2«n*
020'C «30*C
1,2,4-Trtchloro benz ene
«30»C
0 0.2 0.4 0.6 0.8 1.0
Relative Vapor Concentration, f/f*
-ir: 1-10 Vapor uptake of m-dlchlorobenzene and 1.2.4-tricWewo-
benrene by dry Woodbum soil at 20 and 30 °C.
Chiou and Shoup, lilts'
1-37
-------
1.2
1.0
0.8
0.6
0.4
0.2
High Soil Looding
2 4 6 8 10 12 14
PERCENT SOIL WATER CONTENT
16
-------
1.00n
0.80-
n
c.
aO.60-
o
Q.
O
5 0.40-
O£
0.20-
r
O.OO-i^
Effect of Soil Water Content on
Dieldrin Vapor Pressure
'
/v
--*
^rr^f
D 2.12 Water
3. 94% Water
10% Water
-x- 172 Water
•a
i i
0 10 20
i i t i i i i i
JO 40 50 60 70 80 90 100
Dieldrin In Soil/ppm
Data from Spencer and Cliath, 1970
-------
0
Non Polor Organic
Vapor
Phase
Adsorbed
0
q
I ^ fm •%. ^ i^^ » M ^ -^ « 1
>olid Sunoce
o) DRY
0
QoO
0
oooo
OQQ
DAMP
n° °°
0 0°0
oon ooo
oooooo
c) WET
FIGURE I. ILLUSTRATION OF VOC ADSORPTION
WITH THREE MOISTURE REGIMES
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Air- Soil Interface
Damp Wet
o
Transport - Analogous to aqueous phase transport
Diffusion
0-r-A.lk -A,
Advection
a
a —> Capacity term (Assuming local equilibrium)
Varies with position if non-linear isotherm
ft 6 o K
0 + 2 + 3^3 32 (Vapor, Water & Soil)
1 H rl
-9-
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Air- Water- NAPL- Soil
Conceptual Model
Water
Water wetting soil surface (62 - 5-10%)
NAPL wetting water (04~ 5-10%)
NAPL form - discontinuous ganglia
NAPL wetting only fraction of residual water
Air filling remainder of pore spaces
Implications- Local equilibrium denied
Soil sorption from NAPL controlled by water
Equilibrium - x4 (x2S y4) p2 (^) 03 p3 K32
Rate - Dependent on partition coefficient, K32
K32 » 1, Slow sorption rate
NAPL vaporization from ganglion - 2 film resistances
NAPL side - diffusion out of ganglion
Air side - non-uniform air movement
-10-
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Residual NAPL Vaporization
NAPL
Transport out of NAPL
Ganglion Size
2a.
(Interfacial force balanced by gravity)
D - 1-8 times L
Sand (dp~0.3 mm), Lmax-o(5 cm), D~o(l cm)
Transport Rate
D2
Tc ~ ~ 69 hours
Transport into Vapor Space
Slowed by flow bypassing
Correlations exist in absence of bypassing
-11-
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Summary of Key Factors
Vapor Density
Pure component vapor pressure
Temperature
Concentration in soil, water and NAPL phases
Soil moisture content
Soil properties (sorption)
Vapor Transport Rate
Soil homogeneity
Soil fluid conductivity
Soil moisture content
-12-
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The Influence of Soil Characteristics on the
Sorption of Organic Vapors
_ Simon H. Davies
NSI Technology Services Corporation
R.S. Kerr Environmental Research Laboratory
Ada, OK 74820
The sorption of organic vapors by soils vill tend to reduce the ef-
ficiency of vacuum extraction processes. A basic understanding of the
mechanism of sorption is, thus, important to the design of vacuum extraction
systems. In this presentation I vill discuss the soil characteristics in-
fluencing the sorption behavior of organic vapors.
Studies on the sorption of hydrophobic (non-ionic) compounds from
water suggest that the mechanism of sorption can be explained in terms of the
partitioning of hydrophobic organic compounds into the soil organic matter.
In water the interaction between mineral surfaces and non-ionic compounds is
weak because of the preferential adsorption of water by the mineral surface.
Dehydrated soils are powerful adsorbents for organic vapors. For a
dehydrated soil the distribution coefficient, K,, for the partitioning of an
organic compound between the solid and vapor phases may be four orders of mag-
nitude greater than the K, for the partitioning of the same compound between
water and the soil. The strong sorption seer, in dehydrated soils is the
result of the interactions between the organic vapor and the mineral surface.
When water is present it displaces the organic compound from the surface, as
the polar water molecule is strongly sorbed by the polar mineral surface.
Studies with chlorobenzene, a weakly polar compound, indicate that, while it
may be strongly sorbed onto very dry soils, in wet or moist soils the sorption
behavior of chlorobenzene is virtually the same as that seen in soil slurries.
Except in extremely arid regions, the subsurface environment more than 10-20
cm below the surface is always moist or wet. Consequently, below the top 10-
20 cm of the soil, the interactions between a weakly polar compound, such as
chlorobenzene, and the mineral components of the soil are weak.
If dry air is used for vacuum extraction, there exists the possibility
that the soil may be dried out to such an extent that the interaction between
the mineral surface and the organic vapors is possible. This will decrease
the efficiency of the extraction process. The use of humidified air for the
extraction would resolve this problem. However, some drying of the soil is
beneficial, as It increases the permeabilty of the soil. Thus, it may be
necessary to adjust the humidity of the air used for the extraction to op-
timize the process.
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THE ROLE OF SORPTION IN CONTAMINANT TRANSPORT
Dermont C. Bouchard
Robert S. Kerr Environmental Research Laboratory
Ada, OK 74820, U.S.A.
One of the parameters distinquishing contaminant transport in the
subsurface from that in surface soil is the very low level of natural
•organic carbon associated vith the mineral phase of subsurface geologic
(material. The lov organic carbon content of subsurface materials
results In very lov sorption of many neutral organic compounds (NOC's)
(1-3). In addition to affecting the magnitude of sorption, the lov
organic carbon content of subsurface material also affects sorption
equilibrium (4) and exacerbates the effects of anthropogenic organic
carbon (5). ' "" ~
Sorption experiments utilizing both column and batch technics have
indicated that attainment of sorption equilibrium can occur very slovly
in some systems (4,14,15). The rate of sorption has often been observed
o vary inversely vith the magnitude of sorption. So solute-sorbent
combinations having a high degree of sorption, such as pyrene and a
surface soil vith l.OX organic carbon, vill take much longer to reach
sorption equilibrium than trichloroethene and a subsurface material vith
an organic carbon content of 0.05%. The rate of sorption is inversely
proportional to the magnitude of sorption, so that lov sorption also
results in more rapid sorption-desorption kinetics (4,14-15).
Most early models for describing contaminant transport in porous
media have assumed instantaneous and reversible sorption, linear and
single valued sorption isotherms, and diffusion equilibrium during
solute transport (6,7). In short, it vas assumed that all processes
affecting contaminant transport vere at equilibrium. However,
contaminant breakthrough curves (BTC's) from miscible displacement
studies vith soils and other geologic material have often differed from
the symmetric sigmoids predicted by the equilibrium contaminant
transport models (4,8,9). BTC asymmetry has usually been manifested as
fronting, or early contaminant breakthrough; or tailing, where system
•itput concentration (C) slovly approaches the input concentration (Co)
-or sorption, or C slowly approaches zero for desorption.
-------
BTC asymmetry has been attributed to physical characteristics of
the geologic material, such as pore geometry, that result in regions of
immobile, intra-aggregate pore water that are only accessible by
diffusion. Contaminant transport then is assumed to occur by convection
and dispersion in mobile vater regions, and soley by diffusion in the
immobile regions. Nonequilibrium conditions and asymmetric BTC's result
when there is slov contaminant diffusion into and out of the immobile
vater sinks. Since this process occurs entirely in the aqueous phase,
it affects both sorbed and nonsorbed contaminants. For sorbed
contaminants, sorption-desorption kinetics that are slow relative to
contaminant-geologic material exposure time will also result in
nonequilibrium conditions during solute transport. Combined equilibrium
and kinetic models vhere sorption was assumed to be at equilibrium on
some sorption sites and not at others have described some asymmetric
BTC's fairly well (10-11). However, slow aqueous phase diffusion and
slow sorption kinetics have very_similar,effects, on contaminant
transport; and are, therefore, easily confounded. In addition,
combined equilibrium and kinetic models have been shown to be
mathematically equivalent to the mobile-immobile water diffusion models
•12,13).
An important consequence of nonequilibrium sorption during solute
transport is the slow desorptive release of contaminants from geologic
material to the aqueous phase. This has important implications for the
remediation of sites contaminated with hazardous wastes. One of the
major groundwater remediation technologies in use today is "Pump and
Treat", where contaminated groundwater is withdrawn from wells, and then
pumped to the surface for treatment by adsorption on activated charcoal
or other technics. The slow desorptive release of contaminants from the
solid to solution phase may require that pumping times far in excess of
those predicted assuming sorption equilibrium be used for contaminant
removal.
Given the importance of organic carbon in NOC's sorption and
transport in the environment, it is clear that any perturbation in the
amount or type of organic carbon in a system will profoundly affect
NOC's transport. The effects of anthropogenic organic carbon are
magnified in the subsurface where the natural organic carbon content is
usually very low. When organic carbon is mobile, it may increase, or
jcilitate, NOC's transport through dissolution in (16), or sorption on
(17), the mobile organic carbon phase. However, when organic carbon is
-------
immobile, such as residual hydrocarbons from gasoline or other petroleum
products, NOC's sorption on the stationary organic carbon vill decrease
NOC's mobility in the environment (5) and may also affect sorption-
desorption kinetics.
-------
REFERENCES
1. Banerjee, P., H.D. Pivoni, and K. Ebeid. 1985. Sorption of organic
contaminants to a low carbon subsurface core. Chemosphere. 14:1057-
1067.
2. Bouchard, D.C., and A.L. Vood. 1988. Pesticide sorption on
geologic material of varying organic carbon content. Toxic. Indust.
Health. 4:341-349.
3. Schvarzenbach, R.P., and J. Vestall. 1981. Transport of nonpolar
organic compounds from surface water to groundvater. Laboratory
sorption studies':—Envlrbh~'Sci7~T'echnolT~15Tl360-:1367?"^ "
4. Bouchard, D.C., A.L. Wood, M.L. Campbell, P. Nkedi-Kizza, and P.S.C.
Rao. 1988. Sorption nonequilibrium during solute jranspor^t.j.jContam._
Hydrol. 2:209-223.
5. Bouchard, D.C., C.G. Enfield, and M.D. Pivoni. 1989. Transport
processes involving organic chemicals. In Reactions and movement of
organic chemicals in soils. Soil Sci. Soc. Am. Spec. Pub, Amer. Soc.
Agron., Madison, VI.
6. Lapidus, L., and N.R. Amundson. 1952. Mathematics of adsorption in
beds. VI. The effect of longitudinal diffusion in ion exchange and
chromatographic columns. J. Phys. Chem. 56:984-988.
7. Hashimoto, I., K.B. Deshpande, and B.C. Thomas. 1964. Peclet
numbers and retardation factors for ion exchange columns. Ind. Eng.
Chem. Fund. 3:213-218.
8. Kay, B.D., and D.E. Elrick. 1967. Adsorption and movement of
lindane in soils. Soil Sci. 104:314-322.
9. Nielsen, D.R., and J.V. Biggar. 1961. Hiscible displacement in
soils: Experimental information. Soil Sci. Soc. Am. Proc. 25:1-5.
-------
10. Selim, H.M., J.M. Davidson, and R.S. Hansell. 1976. Evaluation of
i two-site adsorption-desorption model for describing solute transport
in soil. Proc. Summer Computer Simulation Conf., 12-14 July 1976.
Washington, D.C., pp. 444-448.
11. Cameron, D.R., and A. Klute. 1977. Convective-dispersive solute
transport vith a combined equilibrium and kinetic adsorption model.
Vater Resour. Res. 13:183-188.
12. van Genuchten, H. Th. 1981. Non-equilibrium solute transport
parameters from miscible displacement experiments. Res. Rep. 119, U.S.
Salinity Labora.to.ry, andjp>ept, ,j)f ..5oll:^nd,. Environ. -Sciences., Univ. of
California, Riverside.
13. Nkedi-Kizza, P., J.V. Biggar, H.H. Selim, M. Th. van Genuchten,
P. J-.-Vi erenga;-37M .— BavlTlsT)n7-atrd-DrRT-T«^Tsoh- — 19841 — OrTWe
equivalence of two conceptual models for describing ion exchange during
transport through an aggregated Oxisol. Vater Resour. Res. 20:1123-
1130.
14. Karickhoff, S.W. , and R.R. Morris. 1985. Sorption dynamics of
hydrophobic pollutants in sediment suspensions. Environ. Tox. Chem.
4:469-479.
15. Vu, Shian-chee, and P.M. Gschvend. 1986. Sorption kinetics of
hydrophobic compounds to natural sediments and soils. Environ. Sci.
Technol., 20;717-725.
16. Rao, P.S.C., A.G. Hornsby, D.P. Kilcrease, and P. Nkedi-Kizza.
1985. Sorption and transport of hydrophobic organic chemicals in
(queous and mixed solvent systems: Model development and preliminary
valuation. J. Environ. Qual. 14:376-383.
17. Enfield, C.G., and G. Bengtsson. 1988. Macromolecular transport of
hydrophobic contaminants in aqueous environments. Ground Vater 26:64-
70.
-------
Figure 3. Cross-section of Subsurface Venting System, Granger, IN (Source;
American Petroleum Institute, 1985).
-------
Soil Vacuum Extraction: Basic Principles in
Gas Phase Movement of VOC
Jong Soo Cho
US EPA, RSKERL
-------
MECHANISMS FOR SOIL DECONTAMINATION
VENTILATED SOIL
TURBULENT AIR
FRESH FROM THE
ATMOSPHERE
ADSORBED
'HYDROCARBONS
HIGH EVAPORATION
RATE
AT ION ^Sti^ijigg- r-
IN VENTILATED SOIL "THE FRESH TURBULENT AIR MAXIMIZES THE EVAPORATION RATE.
THE SOIL VENT RAPIDLY REMOVES THE VOLATILIZED CONTAMINANT FROM THE SOIL.
UNVENTILATED SOIL
/HYDRO
ST^
ADSORBED
HYDROCARBONS
STAGNANT
SATUPATED AIR
EVAPORATION » CONDENSATION
RATE RATE.
IN UNVENTILATED SOIL THE AIR TRAPPED IN THE CONTAMINATED SOIL BECOMES SAT-
URATED WITH THE CONTAMINANTS. THE ONLY MECHANISM FOR DECONTAMINATION IS A
SLOW DIFFUSION FROM PORE TO PORE.
-------
1. Air movement
2. VOC movement in gas phase
-------
Assumptions
1. Constant Temperature: Uniform Isothermal Condition
2. Constant Properties of Air: Not Vary during Operation
3, Immobile Liquid Phase: Air flow doesn't Mobilize the Liquid.
4, No Transformation: Absence of Chemical and Biological Transformation
5. Ideal Gas Behavior of Air: Low pressure ( *1 atm )
6. Darcy's Law: Movement of Air
7. No Direct Contact between Air and Soil: Liquid is the Wetting Phase.
-------
Air Movement by Induced Pressure Gradient
I. Overall Mass Balance of Air
2. Darcy's Law for Air Movement
K
^a
3. Ideal Gas Law
RT
P=P
a M
a
-------
VOC Movement
1. Mass Balance of Component A in Air
2. Mass Balance of Component A in Immobile Phase (Liquid)
ac
-------
Soil-Air Permeability, K
a
K = K * K.
a ra i
Relative Air Permeability, K
ra
•1/2, , ,, 1/ni N2m
K =c 6 ( 1 -(1-6 )•)
ra a a
. Van Genuchien's Saturation and Capillary Head
Effective Diffusion Coefficient, D
D 2.34 , 2.0
DA 4> a
A- a a
-------
Inlerfacial Mass Transfer, S
K : Interfacial Mass Transfer Coefficient,! (Re, Sc, 0 )
G i a
* :
( P - P ): Potential of Interfacial Mass Transfer
-------
Simulation of 1-Dimensional, Homogeneous Soil Column
willi Single VOC Component
Pressure Distribution at Steady State
222
P= P- + ( P . - P-
Jin out i n
Air Flow Rate
( 2 2
K (p. - p
a in out
—
""M *-" r\ f\
, Pin + (Pout '
^ IL
i
9 y
Pin }L
-------
0.75-
Pout =0.6 Pin
Ou
0.50
Pout = 0.9 Pin
Pout = 0.8 Pin
0.0
Pout = 0.5 Pi'h
\
\
0.2
0.8
0.4 0.6
x/L
FIGURE 1. Pressure Distribution Inside. Soil Column
1.0
2.0-
i
i
1.8-7
1.6+
1.4+
1.2+
1.0-
0.0
0.2
Pout = 0.5 Pin
Pout = 0.6 Pin
Pout » 0.8 Pin Pout = 0.9 Pin
0.8
1.0
0.4 0.6
x/L
FIGURE 2. Linear Velocity Distribution inside Soil Column
-------
1000000
100000--
rg
<
E
o
\
O
c
>,
~ 10000+
4J
3
O
cu
1
c
-i-<
a.
1000-
100
Pin = 1.013 e6 {dyne/cmR2)
k = 4,34 e-7 cm
intrinsic permeability
total porosity = 0.455
velocity = 0.158 cm/min
5 10 15 20
Water Content (%)
FIGURE 3. Pressure Drop with Water Content
25
-------
Mass Balance of Component A in Gas Phase
inilial condition y . = y . att = t
A Ao o
boundary condition y A = y A. at x = 0
A Ai n
= 0 at x = L
Mass Balance of Component A in Liquid Phase
6 ,— T -- = - S A , initial condition, C A = C A at t= t
A A Ao o
-------
TADLE 1.
Characteristics of Soil Columns
Column Specification
* 9
Intrinsic Permeability (cm )
* "^
Soil Particle Density (g/cm )
Soil Bulk Density (g/cro3)
Initial Water Content U)
Initial VOC Content (|Jg/g SOIL)
Initial Amount of Soil (g)
Diameter of Soil Column (cm)
# 9 fi
Pressure at Exit (dyne/cm xlOD)
Mass Trans. Co. KQ (sec"1xlO~7)
Run 1
4.34xlO~7
2.68
1.46
4.1
8850
2600
6.35
1.0127
8.9
Run 2
4.34xlO~7
2.68
1.45
17.4
15
2650
6.35
1.005
8.75
Run 3
1.085xlO~7
2.66
1.4225
10.2
4010
2601
6.35
1.0076
1.265
Run 4
l.OSSxlO"7
2.66
1.4225
24.4
4.2
2468
6.35
0.629
1.75
*
estimated values
«
adjusted values to fit the experimental result
TABLE 2.
Chemical Properties[29] and Operating Conditions
Molecular Weight of TCE 131.4
3
TCE Liquid Density (g/cm ) 1.46
2 9
Diffusivity in Air(cm /sec) 8.0x10
Vapor Pressure (dyne/cm ) 7.73x10
Henry's Law Constant (dyne/cm )/(gmol/cm ) 7.143x10
Solubility in Water (g/cm3) l.lxlO"'3
Viscosity of Air at 20 C (cp) 0.01846
2 6
Initial Pressure inside column (dyne/cm ) 1.013x10
2 6
Entering Air Pressure (dyne/cm ) 1.013x10
Mole Fraction of TCE in Entering Air 0.0
Temperature (K) 293
-------
0.10
0.08-(]
(9
•o
" 0.06-
Q
4J
n>
7! °-04+
o
e
QJ
PS
0.02+
0.00
D
New Jersey Cohensey Sand
Pure TCE spiked
Computed
D Experimental
0 50 100 150 200 250 300 350 400 450
Days
FIGURE 4. Removal Rate of TCE from Soil Column
0.
0.004--
•O
3 0.003+
m
o
D
0.002--
0.001--
0.000-
New Jersey Cohensey Sand
TCE sat'd Water spiked
— Computed
S Experimental
D D
H ui n.
H 1-
+
0 5 10 15 20 25 30 35 40 45 50
Days
FIGURE 5. Removal Rate of TCE from Soil Column
-------
0.10
0.08
.r 0.06--
0)
ro
K
fl
o
6
o
0.04--
0.02--
0.00
D
D
-D-
Tennessee Loess Soil
Pure TCE spiked
- Computed
n Experimental
20 40 60 80 100 120 140 160
Days
FIGURE 6. Removal Rate of TCE from Soil Column
U . UD-
0.04-
-------
Conclusions
1. Water Content: Controls air movement and interfacial mass transfer.
2. Vapor Pressure: Total efficiency depends on.
3. Clean-up to desired level depends on the soil and VOC properties,
initial amount of VOC, and operating conditions.
4. First order kinetics model for interfacial mass transfer
-------
Future Researches (modelling and laboratory)
1. Multiphase movement, multidimensional configurations, and multicomponent
VOC's.
2. Nonhomogeneous soil media
3. Increased temperature operations
4. Chemical and biological transformation involvement
5, Combined operation with other processes
-------
ft ft ft/ft ft, ^ rp f{i ffi (ti
d)
-------
0.20
0.15
1
0.10
fl
>
O
E
tt)
tt
0.05-
0.00
T = 35
T » 20
- T « 5
C
c
C
0 50 100 150 200 250 300 350 400 450 500
FIGURE
Days
Comparison of Removal Rates at Different
Temperature Operations
-------
Multiple Well Operation
- Semianalytical Approximation for Air Flow by Potential Theory
1. Simulated Well by Line Sources/Sinks
2. Method of Images to Satisfy the Lower and Upper Boundaries
3. Doublet Panel for Stratified Soil
- Numerical Solution for Transport Equation
-------
Three Dimensional Gas Flow Equation
Al steady state
V kP Vp = 0
Kirchcoff Transformation
dP
= P Homogeneous Media
= kP Heterogeneous Media
Laplace Equation
V2 m = 0
-------
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MODELING OF SOIL VAPOR STRIPPING
Day id J. Ui1 son
Departments of Chemistry and of
Civil and Environmental Engineering
Vanderbilt University
Box 1822, Sta. B
Nashville, TN 37235
and
Robert D. Mutch, Jr., and Ann N. ClarKe
ECKENFELDER, Inc.
227 French Landing Road
Nashville, TN 37228
ABSTRACT
Mathematical models -for the modeling o-f soil vapor
extraction will be discussed and the results o-f calculations
with the models presented. The models assume that the soil
gas obeys the ideal gas law, that the gas velocity field is
independent o-f time, and that the volatile contaminant being
removed obeys an effective Henry's law. Both vapor stripping
in laboratory columns and by means of field vapor stripping
wells are considered. The lab column model can be used with
experimental data to obtain the effective Henry's constants
needed in the field model. The field model assumes that the
domain of interest is axially symmetric; this permits the
model to be run on readily-available microcomputers. The
effects of well depth, well spacing, the use of impermeable
caps, passive vent wells, soil pneumatic permeability, and
recon .. Tiinat i on from underlying NAPL are examined. Recent
modifi.at ions to the models permit the use of variable and
anisotropic pneumatic permeabilities and the description of
the vapor stripping of fractured porous bedrock.
INTRODUCTION
In this presentation I shall focus mainly on the
physico-chemical nature of the models for soil vapor
stripping and some of the results which have been obtained.
If any of you have need of the mathematical details, Mr.
DiGiulio has copies of the manuscripts describing in detail
essentially all of the work I'm going to talk about.
I became interested in the development of models for
soil vapor stripping in connection with AWARE's work on Cib<
Getgy's Tyson site near Philadelphia? this involved renego-
tiation of a record of decision to permit the use of soil
vapor extraction in the remediation of the site.
-1-
-------
In the construction of a. mathematical model one has two
major tasks. First is constructing the soil gas velocity
•field in the vicinity of a vapor stripping well. The second
is using this velocity field in a conservation equation to
model the movement through the soil of the volatile
contaminant.
The velocity field of an ideal gas in a laboratory
column or in the vicinity of a vapor extraction well is
assumed to obey Darcy's Law,
If uie combine this with the continuity equation for the gas
and assume that the velocity field is independent of time,
we find that the pressure Pf which is the velocity potential,
is a solution of the partial differential equation
= 0 <2>
Here Kp is the pneumatic permeability. This may vary from
place to place, and also may be anisotropic. In much of the
work which follows we assume a constant and isotropic
permeability. Along with Eq . <2> we require appropriate
boundary conditions. These are simply the inlet and outlet
pressures for laboratory columns, but are somewhat more com-
plex for vapor stripping wells. For these we assume axial
symmetry, and solve Eq . <2> either by the method of images
from electrostatics or by a numerical over-relaxation method.
Boundary conditions for vapor stripping wells include an
impermeable boundary at the water table at the base of the
domain .of interest, an impermeable boundary and/or a constant
pressure of one atmosphere at the top of the domain of
interest, a no-flow boundary condition or a constant pressure
of one atmosphere around the periphery of the domain of
interest, and a sink (to represent the well) on the axis of
the domain of interest. The condition around the periphery
of the domain is not needed if one is using the method of
images. The method of images allows one to calculate soil
gas velocity fields very rapidly, but constrains one to a
constant permeability and to rather simple boundary
condi t i ons.
Once one has obtained the soil gas velocity field, the
next step is the actual modeling of vapor extraction. For
our first model we assume a constant, isotropic permeability
and local equilibrium of the Henry's law type between the
stationary contaminant and the contaminant vapor. All of
these assumptions can be relaxed without difficulty if the
data are available to support a more accurate model. The
material balance equation for vapor stripping is
at
-2-
-------
where /77 - V C- «/
«
Use of Eqs. <4> and <5> permits us to write Eq. <3> in terms
of m and used the the mesh size together with
numerical dispersion to represent dispersion. This permits
one to use fewer mesh points than would otherwise be possible
and thereby results in substantial reductions in computer
time requirements. Uarying the dispersion does not seem to
result in significant variations in the overall rate of
removal of contaminant from the domain of interest, although
it does result in some variations in the details of the
distribution of contaminant in the domain of interest during
the course of the run.
One of the problems which arises in connection with
using these models is the assignment of the effective Henry's
constant. Our experience to date has been that, if one uses
a Henry's constant calculated from contaminant vapor pressure
and contaminant solubility in water, together with the soil
moisture content, one obtains removal rates which are far too
rapid. Effective Henry's constants appear to be one to two
orders of magnitude smaller. At the Tyson site this was
probably due to a large cosolute effect — the aqueous phase
was not essentially pure water by the wildest stretch of the
imagination. In addition, one has the adsorptive capacity of
the soil itself which must be taken into account. Prudence
would therefore dictate that effective Henry's constants be
determined on samples taken from the site, at least at
present. This can be done by use of the model for lab column
vapor stripping together with experimental data. One makes
runs for some fixed duration of time, after which one
analyzes the columns for the contaminants. One also maKes a
series of simulated runs of the same duration with varying
values of the Henry's constant, makes a plot o+ percent
removal versus effective Henry's constant, and then simply
-3-
-------
reads the effective Henry's constants which correspond to the
observed percent removals. Another approach is to note that,
for a given velocity field, removals of all contaminants
should plot similarly if the time variable
-T = t <6>
1 + w/V Kff
is used. A plot of percent removal versus Henry's constant
which we used on the Tyson data is given in Fig. 1
Permeability data are probably best calculated from
vacuum extraction test well flow rate data. For an isotropic
medium,
K= RTQ <7>
27TV r (1 -
Here R is the gas constant (cu m atm/mol K> ; T is the
temperature (K); Q, the flow rate (moles/sec); r, the
screened or packed radius of the well ; and Py:/ the well
head pressure (atm). The units of the permeability are sq .
m/atm sec. We see from Eq . (7) that the flow rate Q is pro-
portional to the product of the permeability and the screened
radius of the well. This suggests a method for extending the
vacuum extraction technique to soils of lower permeability;
simply increase the radius of the gravel packing of the well.
The overwhelming bulk of the flow resistance occurs in the
immediate vicinity of the well sink, which is the only region
in which pressure gradients and gas velocities are really
large.
In Fig. 2 we see the importance of drilling the wells.
down nearly to the water table. The shallower the well, the
longer the clean-up time. Also, one should screen vacuum
extraction wells only fairly near the bottom, to reduce
short-circuiting of gas along the short pathlengths near the
axis of the well; this, in turn results in decreased
efficiency of the well.
The results of Fig. 3 indicate that one pays a heavy
price for spacing vapor stripping wells too far apart; the
rate at which the lower peripheral region of the domain of
interest is cleaned up decreases rather drastically with
increasing domain radius for domains of radius much larger
than the depth of the well. We also conclude that "hot
spots" of contamination are most likely to be found midway
between wells and fairly near the water table, sine* this is
the region which is cleaned UP most slowly. This conclusion
is supported by the streamlines and gas transit times plotted
in Fig. 4.
The effect of placing an impermeable cap on top of the
domain o-f interest coaxial" with the vapor stripping well is
shown in Fig. 5. We see that impermeable caps result in
significant increases in removal rate, since they reduce the
-4-
-------
tendency of the soil gas to short-circuit along -flow paths
•fairly close to the well axis. Interestingly enough, the
effect of an impermeable gas on the gas flow rate through a
well is very slight; the gas flow rate with a 25 meter cap is
9B.B&'/. that of the gas flow rate when no cap is present. I
can't comment on the economics of using these caps, but note
that these results indicate the feasibility of vacuum
extraction under streets, parking lots, buildings, etc.
It has been suggested that passive vent wells around the
periphery of the domain of influence of a vacuum extraction
well may increase removal rates. In the absence of
impermeable caps, the results shown in Fig. & suggest that
this is usually not true. It appears that the passive wells
provide a short circuit across the bottom of the domain of
interest. Interestingly enough, in the presence of an
impermeable cap the passive wells result in significant
improvement in performance, as shown in Fig. 7.
In some work which Eckenfelder, Inc., is doing at Tom's
River, New Jersey, there is indication that the soil
permeability in the upper meter or so of soil is about
l/200th the permeability of the underlying soil. Since the
top meter is mostly clay and concrete, while the underlying
soil is mainly sand, this is hardly surprising. It results
in some rather drastic modifications of the Qas flow patterns
from what one would obtain if the permeability were constant
over the entire domain of interest; the influence of the
vacuum extraction test well, as measured by piezometer wells,
extends out radially much farther than one would expect.
Mutch, using my over-relaxation program for soil gas flow
fields,-was able to obtain a very good fit between the
experimental piezometer readings and the calculated soil gas
vacua by suitable adjustment of the permeabilities. His
experimental results are shown in Fig. 8. Well log data
plus readings from strategically placed piezometer wells
during the operation of a test vacuum well should permit one
to get a fairly good picture of the large-scale behavior of
the permeability, which can then be used in optimizing the
design of a vapor stripping well system.
So far, we have assumed that there is local equilibrium
between the vapor phase and the stationary phase with respect
to contaminant transport. This assumption may not be
warranted if one is vapor stripping a fractured porous medium
in which the soil gas moves principally along the fractures,
so that contaminant must move from the interior of the porous
blocks out to the fractures by diffusion. We have
constructed lumped parameter models to describe the vapor
stripping of a fractured porous medium in lab columns and by
a vacuum extraction well? the models can be run on
microcomputers. The time constant, obtained by solving a
simple diffusion problem, is estimated by
-5-
-------
(8)
The effect of the time constant on vapor stripping -from a lab
column is shown in Fig. ?j as expected, the larger the time
constant, the slower the rate of removal. The effect of the
time constant on the operation of a soil vapor stripping well
is shown in Fig. 10. One may be able to reduce costs in the
vapor stripping of fractured bedrock by operating the vacuum
extraction wells on an on-off duty cycle o-f length comparable
to the diffusion time constant 1/X •
I have some hope that soil vapor stripping may be able
to efficiently remove non-aqueous phase liquid which is
floating on top of the water table. Removal of floating NAPL
depends upon the movement of the contaminant by diffusion
from the surface, of the liquid pool up into the moving soil
gas, which then carries the contaminant along to the vapor
stripping well. We have constructed a model which allows us
to include a source term at the bottom of the domain of
interest to correspond to evaporating NAPL, and are currently
measuring diffusion constants of hexane, toluene, and some
other volatile organics, in sand. A plot of the total mass
of contaminant in the vadose zone versus time is shown in
Fig. 11. Here contaminant is diffusing into the bottom of
the domain of interest from an underlying pool of NAPL. If
it can be shown that vacuum extraction can be efficiently
applied to such situations this would markedly extend the
utility of the technique; we should have data on this by the
end of the summer.
In the course of vapor stripping one can expect to
evapora-te considerable water, which might result in
significant cooling of the soil. Reducing the soil
temperature should certainly reduce the effective Henry's
constants of volatile contaminants, which would reduce their
removal rates. UJe carried out a heat balance to explore this
point, and concluded that, under most circumstances,
evaporative cooling should not result in more than about a
degree and a half
-------
models. If the assumptions of axial symmetry and local
equi1ibriurn are poor, then the results of the calculations
will be poor. Also, if the accuracy to which the input
parameters required by the models are known is poor, then the
accuracy of the calculations will be poor. At this stage one
has no business to imply that we are dealing with high
precision tools here. I hope that the present models are
useful in providing upper bounds to times needed for cleanup,
that they permit better design of soil vacuum extraction
facilities, and that they provide a helpful basis for those
refinements which turn out to be necessary.
In closing, let me talk a little about unfinished
business. First and foremost, we need to do additional
validation of the models as additional data from field sites
become available. Models without validation are only
interesting exercises in differential equations. Only
validation can give them credibility.
Secondly, we could use better adsorption isotherms for
our contaminants than we have now. The assumption of an
effective Henry's constant is about as primitive as one can
get. The models can very easily be adapted to use better
isotherms when these become available.
Third, we need to complete the work on vapor stripping
underlying NAPL; for this we need contaminant diffusion
constants in porous media. This work is in progress.
Fourth, we need some lab work on the vapor stripping of
fractured porous media to test our lumped parameter model.
The possible cost advantages of on-off cycling of vapor
stripping wells in fractured bedrock should also be explored.
Fifth, we may well find that our assumption of axial
symmetry is too limiting—that we need to construct a full
three-dimensional mathematical model for vapor stripping!
This should include the possibility of impermeable barriers
on top of the domain of interest, a variable and anisotropic
permeability, and multiple wells. Such a model would have to
be run on a main frame computer, and would be substantially
more expensive to use than our present models.
BIBLIOGRAPHY
1. "Removing Volatile Contaminants from the Unsaturated Zone
by Inducing Advective Air-Phase Transport"f A. L. Baehr,
G. E. Hoag, and M. C. Marley, J. Contaminant Hydrolooy,
4, 1 <1989>.
2. "Soil Clean-up by In Situ Aeration. I. Mathematical Mod-
eling", D. J. Wilson, A. N. Clarke, and J. H. Clarke,
Separ. Sci. Technol., 23. 991 (1988).
-7-
-------
3. "Soil Clean-up by In Situ Aeration. II. Effects o-f Im-
permeable Caps, Soil Permeability, and Evaporative Cool-
ing", K. Gannon, D. J. Wilson, A. N. Clarke, R. D. Mutch,
Jr., and J. H. Clarke, Separ. Sci. Technol., in press.
4, "Soil Clean-up by In Situ Aeration. III. Passive Vent
Wells, Recontamination» and Removal o-f Underlying NAPL",
D. J. Wilson, A. N. Clarke* and R. D. Mutch, Jr., Separ.
Sci. Technol.| in press.
5. "Soil Clean-up by In Situ Aeration. IV. Anisotropic Per-
meabilities", R. D. Mutch, Jr.| and D. J. Wilson, Separ.
Sci. Technol., submitted.
6. "Soil Clean-up by In Situ Aeration. V. Vapor Stripping
•from Fractured Bedrock", M. M. Megehee and D. J. Wilson,
manuscript in preparation.
7. "Mathematical Modeling of In Situ Vapor Stripping o-f Con-
taminated Soils", D. J. Wilson, Proc., 1st Ann. Hazardous
Materials Management Con-f ./Central , p. 94, 1988.
8. "A Phased Approach to the Development o-f In Situ Vapor
Stripping Treatment", A. N. Clarke and D. J. Wilson,
Proc., 1st Ann. Hazardous Materials Management Con-f./
Central, p. 191, 1988.
9, "In Situ Vapor Stripping Research Project: A Progress
Report", R. D. Mutch, Jr.; ft. N. Clarke, and D. J. Wilson,
Proc., 2nd Ann. Hazardous Materials Management Con-f./
Central, p. 1, 1989.
10. "In Situ Treatment o-f Contaminated Soils Using Vacuum
Extraction", T. J. Dal-fonso and M. S. Navetta, DOE Model
Con-f. Abstr., p. 59, Oak Ridge, TN, Oct. 3-7, 1988.
11. "Forced Venting to Remove Gasoline Vapor from a Large-
Scale Aquifer", W. L. Wootan, Jr., and T. Voynick, sub-
mitted by Texas Research Institute to American Petroleum
Institute, Washington, D.C., Jan. 13, 1984. See also
"Examination of Venting for Removal of Gasoline Vapors
from Contaminated Soil", submitted to American Petroleum
Institute, API publ. no. 4429, 1980.
12. "Performance Evaluation Pilot Scale Installation and Op-
eration, Soil Gas Vapor Extraction System, Time Oil Com-
pany Site, Tacoma, Washington, South Tacoma Channel, Well
12A Project", Woodward-Clyde Consultants, work assignment
no. 74-ON14.1, Walnut Creek, CA, Dec. 13, 1935.
13. "In Situ Air Stripping of Soils Pilot Study", G. J. Anas-
tos, P. J. Parks, M. H. Corbin, and M. F. Co i a, submitted
by Roy F. Weston, Inc., to U.S. Army Toxic and Hazardous
Materials Agency, Aberdeen Proving Ground, MD., Report
-8-
-------
AMXTH-TE-TR-85026, Oct., 1985.
14. "Subsurface Venting of Hydrocarbon Vapors from an Under-
ground Aquifer", W. L. Crow, E. P. Anderson, and E. Min-
ugh, submitted by Riedel Environmental Services Co. and
Radian Corp. to American Petroleum Institute, Washington,
D.C. API publ. no. 4410, 1985.
15. "Zone I Soil Decontamination through In Situ Vapor Strip-
ping Processes", A. N. Clarke, AWARE, Inc., contract no.
68-02-4446, final report to EPA, April, 1987.
16. "In Situ Vapor Stripping of Contaminated Soils! A Pilot
Study", R. E. Bailey and D. Gervin, Proc., 1st Ann. Haz-
ardous Materials Management Conf./Central, p. 207, 1988.
17. "In Situ Hydrocarbon Extraction: A Case Study", E. U.
Fall, et al., Converse Environmental Consultants, CA,
Southwestern Ground Water Focus Conf., Albuquerque, NM,
1988. See also The Hazardous Waste Consultant, Jan/Feb,
1989, p. 1-1.
-9-
-------
FIG. 1.
100
Plot of Henry'a constant veraua percent removal after ;23
daya aeration. Lab column circulation. Column height »
32.1 cm; column radlua * 3.15 cm; airflow rate * 5.O |
mL/min; voids fraction «• .2; specific volume of water In
aoil » .2.
-------
^ 2 •
e
o
D»
O
9m
FIG, 2 Plots of log total solute DM a a versus tlma showing tha
effect of well depth. Depth of water tabla * 15 m; rad-
ius of zone of influence « 20 m; height of wall above
the water table * 3, 6, and 9 m. Other parameters as In
Fig. 6. No impermeable cap was used in theae runs.
-------
FIG. 3
30
m
t
Ixl0esec
Plot* of log total solute ma»a veraus time showing the
eiiecta of well spacing on th« rate of removal. No cap
was used in theae runa. Depth of water table = 2O m;
depth of well » 17 m; radiua of zone of Influence a
20, 25, and 30 n. Other parameters aa In Fig. 6.
-------
W
•
•a
Z t
FIGURE A SOIL AERATION BY A SINGLE VENT PIPE
-------
FIG. 5 n«*oTlojiolMi!»(o*in«»WM»tIin»it»w!nxihc«ff*r« cfcknilaf
lm|«mit»bb rip* on toil vifn urippint efficiency, C»p n&\ • 1.10; IS. 20.
ind 15n. R*diin of tone of influence - JO m; dejuh of ««ttr Ublt •Mm; hti|M
of *«ll ibov« »tttf ubk .9m; pt flow nit • 9.1 notice; Hmf) t romuni •
.01 well iti'mt m. Urn; votdt fr«e(ioo • 0.3; toil melilire faction • 0.); »tll
pmurc . .166 tlm; KD - 6 m'/iim tec; toll dcntlty - t 4 |tm'; Initilt tclwjW
totuie tcmnnviiloo • I00tn[t|. Thirt-poiin itfcod-oofer iljoriikim wvurmei)
to Tit It* bovndaQ tMtdiiiom.
-------
fO.IO)
.00,10)
3.0 r
0 0.5 x|O7 sec ' 1.0
- time
FIG. 6 Plot of log total solute raaaa versus time. Depth of water
table » 1O m; depth of well • 8 m; other parameters
given In Table 4.
-------
O
o>
O
0
Fi
-------
CRTRACTIOM
WCLU
*0
SS
50
40
LCOCHD:
ty
•l.o-
sott CAS moot
_MtAS"nEO IN SITU
VACUUM.
senti!H SCTTINQ TIG, 8
eowTouft or IH SITU
SOIL VACUUM. ,
CROS.S-SECTIONAL IN SITU SOIL VACUUM
CONTOUR MAP
(INCHES OF WATER)
-------
o
Oi
O
0
SxlCrsec
12
X = I0's sec'1
•^•^^••^^•^a
lO'4
18
t
FIG. 9 Plots of loglOCcon taminant mass) versus time, vapor
stripping in a laboratory column; effects of dlffu-
r' v -*• -j -^
sfon time constant A • A= "°, 10 , 10^ , 10 ,
and 10" sec""' . Other parameters as in Table t.
-------
-2
FIG. 12
- deg.
IO°C 20
Initial air. temperatur_e_
30
Change in soil temperature after 5O volumes of dry air
have been passed through 1 volume of wet soil as a func-
tion of initial air temperature. Soil volume • 1OOO mL;
aoil density = 1.6 gm/raL; aoil specific heat * 0.2 cal/
gm dag; initial soil temperature * 12.6° C; latent heat
of vaporization of water * 540 cal/gre.
-------
FIG. 11 Plots of log total solute maaa in the vadoaa zone versus
time. Henry'a constant » .01 (upper curve), .005 (lower
curve); other parameters given in Table 5.
-------
Modeling The Transport of Volatile
Organics in Variably Saturated Media
^_J. F. Sykes
Departments/ Civil Engineering,. University -of Waterloo,- Waterloo?
— -ABSTRACT-
The understanding of the processes of dissolution, volatilization, and gas-
liquld ^aTrtiliorung inr porous media is very limited. The lew mo dels which"
attempt lo characterize the transport of volatile organics in variably satu-
rated media all assume that mass transfer processes are at equilibrium. In
addition, gas phase advection IE usually neglected by assuming that gas phase
pressures are uniformly atmospheric and that density gradients are negligi-
ble. A model was developed to solve for water phase flow and transport and
density dependent gas phase flow and transport. Simple expressions for dis-
solution, volatilization, and gas-liquid partitioning, employing the concept of
an overall mass transfer coefficient, were incorporated into the model. The
transport of trichloroethylene in a variably saturated vertical cross section,
under a variety of conditions, is simulated; the results of the simulations
appear to be qualitatively correct. The importance of gas phase processes
in increasing subsurface contamination from volatile organics, and in dis-
sipating residual amounts of these substances is demonstrated. The lack of
similar analytical and/or numerical models, or suitable experimental studies,
excluded the possibility of validating, or verifying, the model. A parameter
sensitivity study is developed for a simplified gas flow model that assumes
an immobile water phase. The sensitivity studies are particularly useful for
the investigation of the importance of spatially distributed parameters such
as permeability.
-------
Volatile Organics
- petroleum products and halogenated
hydrocarbon solvents
•IUU_a__ I J .rnvmi JM • » t~ w nrl_.. L-. r i-n-L-T-imr-miril—f. ^^^____—^_^»^»jj.
—very-common-contaminants-of subsurface—•
, J . i . .iiiiir^1iiiiiiiiunjifiLj]i>M_.J_»iiLi_.i-ir-TT-a-rri-|—r-nr
'^ben^ene: J_^_..._!.
- "essentially" immiscible, but solubilities
...... " gi-eatiy
-^TCE- solability ; ^'
- in vadose zone VOC's also volatilize
. and moye in gas phase
- TCE saturated cone, in air at 10 C. = 250
ppm
-------
Volatile Organic Movement in Vadose Zone
- VOC's flow as immiscible phase if sufficient
quantities
. water- pHase — ..».•.,....*.-,.„.: — ^--»,
BlgnrrT*|TU """ nwri*
- density gradients in soil gas phase may
"transfer of solute between gas and water phases
due to gas-liquid partitioning
- three-phase coupled highly non-linear flow
with coupled non-linear transport
• i
- long-term threat to groundwater is residual
VOC
- assume all VOC is immobilized
-------
Mass Transfer Processes
- local equilibrium assumptions may not be
valid for dissolution, volatilization and
)f-^GompUcaWd-geemetTy-of-iflterface-
between phases
S*6
dissolution and volatilization:
- Cfm)
gas-liquid partitioning
u; - j
at at
-------
Water Flow Equation
- assume that:
gas pressures have no effect on water flow
^-density/is -constante^. ..JLL^-LU. 's.1.,1..1.^^.. ii'js
-------
Gas Flow Equation
- VOC vapours very dense relative to air
and density gradients significant
» W» * * ** 9 * * **• fc ~*» •* * ** *** «* » • * 1
irmvr
gas mcompressiDle
tt'lfcJtJiijm^^i.intjap^OaMi'it'iT nfHP*rt)H*i «*•••»
viscosity -constant
r —
Pa
-------
Transport Equations
- mass transfer processes appear
as sink/source terms
-^.for.-water-flow;
^&Qw^i****aix*aJ3£w^,i^-f.
Vy ^rrrJ — . tW :— — :..+_ (p.b
aXj y C7Xt-
dcw
-------
WATER - TYPE 2
X
3
LL,
0
i
in
LJ
w"
§
UJ
H
RESIDUAL — >-
T/^ir
LJL. _. 1 V-C.
>- E
1- 10 — *-
1
en
-------
AQUEOUS PHASE
GAS PHASE
Figure 2: Concentration i(g/l) at 340 days
High mass transfer rate 'constants
-------
AQUEOUS PHASE
ii
GAS PHASE
r
t
Figure 3: Concentralion (g/l) at 340 days
Low mass transfer rate constants !
-------
Figure 4: Dissolution rates
0.10 n
INITIAL RATE
= 0.345 Kg/day
0.08 -
High mass transfei
rate constants
Low mass transfer
rate constants
Ground surface ii
npermeablc to gas phase
I I I I I I I I I I I I I I I I I I I I I I l'| t I I I I I M I | I I I I I I I I I 1
i i i i i i i i i i
0.00
0
200 300 400
Time (days)
600
-------
0.10 -1
0.08 -
-O 0.06 -
Figure 5: Volatilization rates
INITIAL RATE
= 0.225 kg/day
High mass transfer rate constants
Low mass transfer' (ate constants
! t
Ground surface impermeable to gas phase
0.00
T I I I I I | I I I I I I I I I | > M I I I I I I 1 I I > I I I I
100 200 300
TT
400
500
600
Time (days)
! 1
-------
0.005
0.000
Figure 6: Rate of solute transfer from gas to water
phase
Low mass transfer rate constants
High mass transfer rate constants
-5 -0.005
-0.010
Ground surface impermeable to gas phase
-0.015
100
200 300 400
. Time (days) ;
500
600
-------
AQUEOUS PHASE
GAS PHASE
Figure 7: Concentration (g/l) at 340 days
No gas-liquid partitioning
-------
AQUEOUS PHASE
II
I!
GAS PHASE
Figure 8: Concentration (g/l) at 340 days
No gas phase adveclion •
-------
AQUEOUS PHASE
GAS PHASE
Figure 9: Concentration (g/l) at 340 days
Ground , ;ace impermeable to gas phase
flow an^l transport \
-------
- * t> >
i v i * i * *~r~fc rr i TT~W r~ ~
"" X
• i
1
*
1
\
*
*
t
i
%
V*^B
1 F>
\ X
\ ^
\ v*1
X ^
X "*
^i n- 4 *•* .*^r
h [
. i
'i J^ 4 ^^ >"W
Figure 10: Gas phase velocities'at 340 days
Ground surface permeable to gas phase I
Velocity scaling factor = 400 \
^^»teto^»^»»^^v . — ^_^
^X
*• f * 4 tl^lAI^IIIV
ivivvv^-^.
Figure 11: Gas phase velocities at 340 days
Ground surface impermeable to gas phase
Velocity scaling factor = 200
-------
Conclusions
- gas and water phase processes important in
modelling movement of VOC's
- gas phase advection may be significant
- determination of appropriate rate constants
for interphase mass transfer important
- effects of variable infiltration
and variable atmospheric pressure may
be significant
-------
WATER RESOURCES RESEARCH; VOL 25, NO. 1. PAGES 81-92, JANUARY 1989
Modeling the Transport of Volatile Organics
in Variably Saturated Media .
B. E. SLEEP AND J. F. SYKES
Department ef Civil Eagintering, Via otrstty cf Waterloo, Waterloo, Ontario, Canada
The understanding of the processes of dissolution, volatilization, and gay-liquid partitioning in porous
media is very limited. The few models which attempt to characterize [be transport of volatile organic* in
variably saturated media all assume that mass transfer processes are at equilibrium. In addition, gas
phase advection is neglected by assuming that gas phase pressures are uniformly atmospheric and that
density gradients are negligible. In this study a model was developed to solve for water phase flow and
transport and density dependent gas phase fiow and transport Simple expressions for dissolution.
volatilization, and gas-liquid partitioning, employing the concept of an overall mass transfer coefficient,
were incorporated into the model. The transport of triehloroethylene in a variably saturated vertical
cross section, under a variety of conditions, was simulated. Results of the simulations appeared qualita-
tively correct. The importance of gas phase processes in increasing subsurface contamination from
volatile organics, and in dissipating residual amounts of these substances, was demonstrated. The lack of
similar analytical and/or numerical models, or suitable experimental studies, excluded the possibility of
validating, or verifying, the model .
INTRODUCTION
Petroleum products and halogenated hydrocarbon solvents
are among the most ubiquitous contaminants of the subsur-
face environment. Although essentially immiscible with water,
these organics often have aqueous phase solubilities that
exceed drinking water standards by orders of magnitude. In
addition, many of these substances have significant vapor
pressures. Subsurface immiscible phase flow of these com-
pounds, resulting from spills, or leaks, leaves behind zones
containing immobilized organic at residual, or greater, satu-
ration levels. These remaining nonaqueous phase liquids
(NAPL's) may persist for long periods of time, slowly dissolv-
ing into the groundwater and'moving in the water phase
through advection and dispersion. In the unsaturated zone,
residual NAPL, as well as NAPL dissolved in the water phase,
may also volatilize into the soil gas phase. In the absence of
significant pressure and temperature gradients in the soil gas
phase, vapors less dense than air may rise to the ground sur-
face, while those more dense than air may sink to the capillary
fringe, leading to increased contamination of the saturated
zone.
As coefficients of gaseous molecular diffusion exceed those
of liquid diffusion by four to five orders of magnitude, molecu-
lar diffuson may be a significant transport mechanism for vol-
atile organics. Marrin and Thompson [1984] measured signifi-
cant concentrations of trichloroethylene vapors in soil gas
above contaminated aquifers. Weeks [1982] detected signifi-
cant downward diffusion of fluorocarbons into the vadosc
zone. Farmer et al. [1980] identified volatilization, and subse-
quent diffusion from the soil to the atmosphere, as a signifi-
cant process in the emission of hexachlorobcnzene from land-
fill sites. Thus volatilization and diffusion to the atmosphere
may be an important attenuating mechanism in groundwatcr
contamination by volatile organics. Alternately, if the mobility
of the gas phase exceeds that of the water phase, volatilization,
and subsequent gas phase transport and gas-waier partition-
ing, may result in increased water phase contamination in
both the unsaruraled and saturated zones.
Copyright !089 by the American Geophysical Union.
Pacer number 88WR03609.
0043-1397/89/89 W R-OJI«»SOS,00
Soil scientists, interested in predicting the fate of pesticides
in the vadose zone, developed the earliest models of volatile
organic transport. The pesticide behavior assessment model
described by Jury et al. [1985] is based on an analytical solu-
tion for one-dimensional, diffusive, vapor transport. Terms are
included to represent linear equilibrium adsorption and equi-
librium partitioning to a water phase characterized sim-
plistically by uniform water content and constant vertical flux.
Pressures in the gas phase were assumed to be uniformly at-
mospheric and density gradients were not considered, so that
gas phase advection was neglected.
This approach was extended to multicomponent hydro-
carbon mixtures in the the one-dimensional, finite difference
model of Baehr and Corapcioglu [1987] which included biode-
gradation and convectivc and dispersive transport in a water
phase characterized by constant vertical flux and uniform
water content. Transport to the saturated zone, not included
in the model, was by water phase advection only, Baehr
[1987] extended this model to a two-dimensional radially
symmetric system.
Gas phase flow and advection were included the two-
dimensional finite element model that Metcalfe and Farquhar
[I9S7] developed to predict subsurface migration of gases
from municipal landfills. As landfill gases typically have limit-
ed water solubility, however, interaction with the water phase
was limited to inclusion of a sink term in the gas transport
equation.
Abriola and Finder [1985] formulated a one-dimensional
finite difference model which included immiscible organic flow,
water flow, and equilibrium interphase transfer between the
immiscible organic phase, the water phase, and a static gas
phase. The results of one simulation were described to demon-
strate the numerical algorithms incorporated in the model.
Modeling multiphase flow involves many computational
difficulties, as outlined by Allen [1985]. In addition, the accu-
rate prediction of immiscible flow requires detailed knowledge
of the saturation-pressure head and saturation-relative per-
meability relationships and characterization of heterogeneities
of the flow system on a scale which is not feasible in most
situations. As the long-term pollution threat is the zone of
immobilized organic left in the wake of immiscible flow, the
characterization of the processes of miscible phase transport in
81
-------
SLEEP AND SVKES: TRANSPORT or VOLATILE OUGANICS
the water and gas phases, which is more tractable from a
computational standpoint, may be or more practical value
than trying to model full three-phase flow.
In modeling miscible transport of volatile organics in the
vadose zone the common assumptions of a static gas phase
and local equilibrium with respect to interphase mass transfer
require reexaminatton. Finder and Abriola [1986] questioned
the validity of neglecting gas phase advection in modeling the
transport of highly volatile organics in the vadose zone. Hell
[1987] investigating the transport of pcntanc in dry labora-
tory sand columns, noted significant advective transport.
. Vilker and Parnas [1986] discussed the need for unsteady
mass transfer expressions to characterize the movement of hy-
drocarbons across the soil water-air interface. Feenstra [1986]
and Sir or el al. [1987] stated that in many sites, where organic
contaminants were known to exist as an immiscible phase,
water phase concentrations of these contaminants correspond-
ing to equilibrium dissolution were not observed. Although
equilibrium may exist at the pore scale, the heterogeneous
distribution of the immobilized immiscible organics as ganglia
within the pores, and mixing and dilution at this microscale,
may result in infrequent observation of equilibrium con-
centrations since field scale measurements represent averages
of many pores. Thus in many field situations, equilibrium ex-
pressions for interphase mass transfer processes may not be
appropriate for numerical models discretized at the field scale.
In this paper a model is developed for predicting the fate of
immobilized volatile organic compounds in variably saturated
media. Variably saturated water flow, density dependent gas
flow, and water and gas phase transport are included. Water
and gas phase Mow are partially decoupled by assuming that
capillary effects between the water and gas phases arc negligi-
ble. The capability to account Tor nonequilibrium conditions
with respect to interphase mass transfer is also implemented.
The model is tested on a simple hypothetical field problem
involving transport of trichloroelhylene. Sensitivities to
various parameters arc evaluated to highlight some of the
important phenomena associated with the transport of volatile
organics in variably saturated media.
MASS TRANSFER PROCESSES
A variety of classical theories developed to predict mass
transfer rates across interphase boundaries are described by
Pfannkuch [1984]- The application Of these theories has been
limited to very simple systems where the area of contact of the
phases, the geometry of the phase interfaces, and the distri-
bution of the phases within the pores are known. Following
immiscible fluid flow in porous media the remaining, immobil-
ized, immiscible fluids may exist as a few large blobs ofliquid.
or a large number of smaller blobs with much greater surface
area to volume ratios, making determination of contact areas
infeasible. The geometry of the interfaces and the fluid distri-
bution depends on the nature of the capillary forces between
the fluids, the pore size and geometry, and the history of fluid
«* movement in the medium.
- In view of these difficulties in characterizing interphase mass
transfer processes in porous media in terms of fundamental
parameters, a simplified approach is needed. In chemical engi-
neering, mass transfer processes in separation equipment,
packed with materials to facilitate intcrplme contacting, arc
represented by first-order expressions in which the mass trans-
fer driving force is proportional to the difference between equi-
librium and actual concentrations [.Ilines and Muddax, 1985].
The proportionality constant is an overall mass transfer coef-
ficient reflecting the contribution of the geometry of the pack-
ing and the distribution of the phases within the packing. A
similar approach will be adopted in this paper to represent
dissolution, volatilization, and gas-water partitioning of
organic compounds in porous media.
If c represents the bulk concentration (mass/volume of
porous medium) of immobilized organic compound in the
porous medium, then the rate of dissolution of organic can be
described by
(1)
In (1). <(> is the overall porosity of the porous medium; S. is
the degree of water saturation of the void fraction; AD is the
dissolution rate constant (1/71; c. is the concentration (M/I?)
of organic in the water phase; and cn is the equilibrium
concentration of the organic in the water phase. The value
assigned iD in (1) will determine whether water velocities, or .
interphase resistance to mass transfer, determine the rate of
dissolution; /.D is thus an important parameter, which can be
used in calibrating models of volatile organic movement
against field results, if sufficient information is available to
provide a unique calibration.
An expression similar to that used for dissolution rates will
be used for volatilization of pure organic liquid into the air
phase. The rate of decay of the residual due to volatilization is
then
(2)
where St is the degree of gas saturation of the void fraction, iv
is the mass transfer coefficient for volatilization of organic
compounds in the vapor phase, e, is the concentration of
organic in the gas phase, and cf)0 is the equilibrium con-
centration in the vapor phase, determined by the vapor pres-
sure of the pure compound. Capillary effects on vapor pres-
sures of liquids confined in a porous medium will be assumed
to be negligible and standard literature values for vapor pres-
sures will be used.
In the three-phase water-air-immiscible organic liquid
system transfer of organic compounds between the water
phase and the air phase will also occur. Henry's law, which
predicts & linear relationship between equilibrium con-
centrations of volatile components in aqueous and gaseous
phases, is often used to characterize the gas-water partitioning
of sparingly soluble compounds. Dilling [1977] states Henry's
law for a system at equilibrium as
tf =
(3)
where H is the dimensionless Henry's law coefficient; P is the
pressure (millimeter Hg); M is the molecular weight of the
solute; 7* is the temperature (K); and fw_ is the equilibrium
solubility of the solute in the water phase (milligram per liter).
This equation was derived using the ideal gas law.
Applying this to th« rates of change of concentration of
organic in the liquid and gas phases due to gas liquid par-
titioning yields
-------
SLEEP AND SVKES: TRANSPORT OF VOLATILE ORGANIC:
83
where AH is the mass transfer coefficient Tor gas-liquid par-
titioning between the water and gas phases.
Studies have shown that the rates of diffusion in porous
media are affected by the overall porosity and the air and
water saturation levels. Various functional relationships have
been proposed to determine an "effective" diffusion coefficient
for porous media. Millington and Quark [1961] formulated the
following relationship for effective gaseous diffusion coef-
ficients in partially saturated porous media. The model is
10/3
(5)
where Dtt is the effective gaseous molecular diffusion coef-
ficient, ef is the gas-filled porosity, and £>f* is the coefficient in
air. Fanner et al [1980] determined that this relationship
could be used to calculate effective diffusion coefficients for
hexachlorobenzene in soils with gas-filled porosities greater
than 0.3. Sallam et al. [1984] found that this model slightly
underestimated diffusion coefficients for gas-filled porosities
between 0.05 and 0.15. A coefficient of 3.1, rather than 10/3,
provided better agreement with experimental data. In the
present study the original form of the Millington-Quirk model
will be used for calculating effective gaseous diffusion coef-
ficients. The same form will be used for the effective diffusion
coefficient in the water phase:
10/3
(6)
FLUID FLOW EQUATIONS
Equations of fluid flow in porous media are obtained by
combining Darcy's Law with the mass continuity equation.
The resulting equations for three phase flow systems of water,
a nonaqueous phase, and a gas phase can be represented by
Bear [1972]
The subscript / represents the phase (water (w), NAPL (n) or
gas (0)); pf is the fluid density (M/L3); fe(J° are the components
of the intrinsic permeability tensor (I?); ktf is the relative per-
meability with respect to the particular fluid phase; pj is the
fluid dynamic viscosity (MILT); pf is the fluid pressure
(Af/LT1); g is the gravitational constant (LIT1), i is the eleva-
tion measured from a reference datum; qj represents sources
or sinks of mass (M/I2T); is the porosity of the medium:
and Sf is the volumetric saturation of the phase. The equa-
tions for the three phases are linked by the capillary pressures
existing at interfaces between phases:
P. - P. - P« (8)
P. ~ P. - P«* f«
where pM is the capillary pressure between water and NAPL
phases and p,,( is the capillary pressure between waicr and gas
phases. The volumetric saturations are related by
5. = 1.0
(10)
When (he nonaqueous phase is immobilized, i( is not neces-
sary 10 wriie a flow equation for the NAPL phase. Changes in
the nonaqueous phase saturation level occur only as a result
of volatilization and dissolution, as defined by (I) and (2). If it
is assumed that water and gas phase pressures are indepen-
dent of pressures in the immobilized NAPL phase then (8) is
not required. S, in (10), which is nonzero only in the region
containing immobilized NAPL, can be specified as an initial
condition, which decreases with time as a result of dissolution
and volatilization. Alternately, in the case of a small degree of
NAPL saturation, it can be assumed that S. is effectively zero
for the purposes of calculating water and gas flow. In the
numerical model developed in this article, this assumption is
employed to simplify the flow computations.
Water Flow Equations
Although several authors have demonstrated the impor-
tance of the effects of a dynamic gas phase on water phase
flow in the case of infiltration fronts and surface ponding of
water in one-dimensional systems [Green et of, 1970; Morel-
Seyloux and Billica, 1985o, b; Toumo and Vaudin, 1986], the
traditional approach to solving the unsaturated water flow
equation (the Richards equation) is taken here. It is assumed
that the variations in gas phase pressure and viscous effects
due to gas flow have negligible effect on the flow of water, and
the water phase flow equation is solved independently of the
gas phase pressure.
In formulating the operational form of the water flow equa-
tion, pw is often replaced by the water pressure head t/f^, de-
fined by
(11)
[tensities of most nonaqueous organic liquids do not vary
from water densities by more than 30%. Changes in aqueous
phase density, due to dissolution of volatile organic com-
pounds, will be very small over the range of water phase solu-
bilities characteristic of most NAPL substances, By assuming
isothermal conditions, density may be considered constant in
(7). The hydraulic conductivity tensor for water flow in porous
media. KVIJ(L/T), is defined by
K „„ = ktJ°P^/fiw (12)
Combining (7). (11), and (12) and assuming constant water
phase density and porosity yields
C is the specific moisture capacity defined by
C = 4, 5SJd^m (14)
and „ (15)
,. Van Gtnuchien [1980] gives the following equation to de-
termine S_. from $„:
•J.--JI' o
___s,_
T-
(16)
where S, is the irreducible saturation level of water: S, is the
fully saturated volumetric saturation; Sf is the effective satu-
ration: and 1 and n are empirical parameters determined ex-
perimentally ; m is given by
m-l-(l/it) (17)
The relative permeability kr^ is estimated from S, by [Van
i. 1980]
-------
SLEEP AND SVKES: TRANSPORT OF Votxiui ORGANIC*
Initial conditions for (13) consist of specification or initial
values of pressure head, >$>„'.
. 0) - *„<*,) (19)
Boundary conditions may be Dirichlet (type 1)
#•0% 0= $*. on Fj (20)
or Ncuman (type 2)
on
(21)
where $Wt is the prescribed pressure head on the boundary FI ;
n, is the ith component of the unit vector normal to the
boundary F2, direction inward; and vui is the inward fluid flux
normal to Fr F, and F, comprise the entire boundary of the
domain.
Gas Flow Equations
If it is assumed that the pressures in the gas phase are
independent of variations in water phase pressures (equation
(9) is neglected) (hen the gas phase flow regime remains linked
to the water flow regime only through (10). St can be calcu-
lated from (10) after Sw has been computed by solving the
water flow equation.
In the case of gas phase flow involving substantial con-
centrations of volatile organic compounds, which may have
densities several times those of air, the constant density as-
sumption cannot be made. Frind [1982] rewrote the flow
equation for water flow in coastal aquifers, where density ef-
fects were significant due to the mixing of freshwater with
denser saltwater, in terms of an equivalent freshwater head. In
the case of air containing significant concentrations of NAPL
vapors, an equivalent head of pure air can be defined
''.* = Pjp£ + * (22)
where pf is the temporally and spatially varying gas phase
pressure and p, is the density of pure air at a specified set of
constant reference conditions.
The gas phase flow equation, derived from (7) and (22) is
where
P,
(24)
pt is the density of the air-organic mixture. The use of this
form of the equation increases the numerical efficiency, as
small variations in pf produce much larger fractional changes
in pr If nf is not significantly different than ^ over the range
Of concentrations or volatile organic compound, then the hy-
draulic conductivity with respect to air flow Km/, defined by
may be substituted in (23) to give
Assuming isothermal conditions and ideal gas behavior, and
using Amagat's law of partial volumes, the mass contained in
a unit volume of the gas mixture (Le., the gas mixture density,
P.) is the SUm or the masses of organic vapor and air:
Where p, is the pure organic vapor reference density and p0 is
the reference pressure (usually atmospheric pressure) for pt
and /v In the absence of air entrapment, or large, externally
imposed pressure gradients, deviations cX pt from atmospheric
pressure will be due only to gravity effects, Since the density of
the gas mixture is very small, these deviations wilt be very
email in comparison to atmospheric pressure. Thus the vari-
ation in gas phase density due to compressibility will be very
small relative to the variations due to organic vapor con-
centration (the second term on the right side or equation (27))
for dense organic vapors. Therefore pf can be written
P. = P. + ct
and p, can be computed from
<•-£)
(28)
(29)
Functional relationships between krf and 5, have been pro-
posed by Parker « ai [1987] and Brooks and Corey [1966].
The Brooks-Corey expression is
to,, = (1 — 5,JX1 ~ st(1*ivi) (30)
where S, is the effective water saturation, as defined before,
and /, is an empirical parameter. Brooks and Corey reported a
value of 3.7 for A for fine sand and a value of 1.82 for silty
loam.
Inputs of dense organic vapors, through volatilization (the
zone containing the immobilized organic is included in the
simulation domain) and gas-liquid partitioning, may represent
significant mass sources and sinks and should be included in
the source term in (26). Utilizing (2) and (4) (26) becomes
where qt' represents mass sources or sinks due to pumping, or
injection, of gas.
Initial conditions for (31) consist of specification of initial
values of the equivalent head of air, hf" -.
*,.*<*„ 0) = *...'(*,)
Boundary conditions may be Dirichlct (type 1)
fc.*(-V(, t) - fc^»(x,) on F,
or Neuman (type 2)
— I in, = ii.. on
(32)
(33)
(34)
where h,* is the prescribed value of n/ on T,; nt is the unit
vecior normal to the boundary Fj, direction inwards; and tt^
is the inward fluid flux normal to F,.
-------
SLEEP AND SYKES: TRANSPORT OF VOLATILE OHCMNICS
85
TRANSPORT EQUATIONS
The equation for advective-dispersive transport of the vol-
aiile organic compounds in variably saturated media may be
written as [Huyakorn et ai, !985]
(35)
where c* is the concentration of solute, or vapor, in the
source/sink fluid.
D,j is the dispersion tensor, defined by {Bear, 1972]
(36)
where at and ar are the longitudinal and transverse dispersi-
vities (L), respectively; &tj is the Kroncckcr delta; |ti| is the
absolute value of the Darcy velocity; and T is the tortuosity.
The second term in (35) can be expanded to
density of 1.26 kg/mj. An air mixture, saturated with TCE
would have a density of 1.46 kg/m1, resulting in a coefficient
in front of the dispersion term of 1.160 in the case of fully
saturated trichloroethylene flow. Thus assuming that gas
phase densities were not significantly different than those of
pure air in solving the gas phase transport equation would be
equivalent to underestimating dispersion.
Saturated gas phase conditions will exist only in the im-
mediate vicinity of the sources of an organic compound. At
the tip of the contaminant plume concentrations will be much
lower and the effects of neglecting density variations would be
negligible. Therefore in the interest of computational ef-
ficiency, (44) will be simplified to
dc,
From the continuity equation for fluid flow
can be obtained
(37)
(38)
(39)
For the water phase, as previously, it can be assumed that p
is spatially and temporally constant. The transport equation
for the water phase thus becomes
Significant sources of organic compounds may result from
the dissolution and volatilization processes. Gas-liquid par-
titioning allows the gas and water phases to act as sink/source
pairs, transferring solute between them. For the water phase
the mass source term due to dissolution is defined by (1). The
sink/source term due to gas-liquid partitioning is defined by
(4). Dissolution and gas-liquid partitioning represent sinks, or
sources, of pure organic compounds, and cw* in (40) would be
equal to the mass density of the pure organic liquid. This
value of c_* would be much greater than the values of em
corresponding to the solubility limits of most volatile organic'
compounds. Dissolution and gas-liquid partitioning for the
water phase can be incorporated into the water phase version
of (40) by making the following substitution:
- c J +
(46)
From (28), for the gas phase
gt Wt Allowing ?„/ to represent fluid sources or sinks due to pump-
ing, or injection, only, the following equation for water phase
transport is obtained:
Substituting (41) into the gas phase form of (39) yields
t)t' is related to qtr' by
«.' -= (P. + i
(42)
(43)
Using (43) and (41) (35) can now be written for the gas phase
as
T? <47>
Volatilization also represents a source of pure organic
vapor and the corresponding c* in (45) would be the mass
density of the pure vapor, which would be much greater than
the maximum value of cf at saturated vapor concentrations.
Volatilization and gas-liquid partitioning for the gas phase
can be incorporated into (45) by making the following substi-
tution:
<48>
ci
The gas phase transport equation becomes
(44) _£_,
The nonlinearity of (44) dictates an iterative solution since
Pt is a Function of ct. However, if the density of the gas mix-
ture does not deviate significantly from thai of pure air the
nonlinearily can be avoided without significant loss of accu-
racy. Trichlorocthylcnc (TCE) has a saturated vapor phase
concentration of 0.26 kg/m3, an ideal gas phase vapor density
of 5.64 kg/m3 at I aim pressure and 10 CC, while air has a
(49)
where qlr' represents sources, or sinks, of fluid due to pumping
or injection processes.
The gas phase transport (49) and the water phase transport
(47) are linked by the gas-liquid partitioning term. Initial con-
-------
SLEET AND SYKES: TRANSPORT OF VOLATILE ORGANIC*
WATER-TYPE 2
R-NOFUUX
S
0
K —
tf£
5>-
£•-
i !
V «
CO
(9
1
f
1
* '
fiESIOUAL— ^i^lg ~
. TCC trrm ^ ^
' -JemU- f
s
APPROXIMATE WATER TABLE °
tn/>
X
U-
o
IE
f
s
E—
UIUJ
tf
IMPERMEABLE BOUNDARY
Fig. 1. Problem domain and flow boundary condition* used for simulations.
ditions for (47) and (49) consist of specification of initial con-
centrations in the water and gas phases:
c Jxp 0) .
(50)
boundary layer. This approximation is reasonable for dilute
concentrations.
Equation (58) may be used to specify a Cauchy (type 3)
boundary condition for gas phase transport at the ground
surface:
Boundary conditions for inflow boundaries are normally Di-
richlet (type 1)
(52)
. t) - cw, on P.,
onT
«i
or Cauchy (type 3)
(53)
(54)
(55)
where c^ and cfc are prescribed concentrations on the bound-
', aries FWJ and Ttl, respectively; n, is the unit vector normal to
' the boundaries, direction inwards; »„_ and P(I are the pre-
scribed fluid fluxes normal to the boundaries F_4 and T^; and
c^ and c^ are the prescribed concentrations associated with
the prescribed fluid fluxes.
At outflow boundaries the assumption is often made that
transport across the boundaries occurs by advection only
IFrind, 1982] and a Neuman (Type 2) boundary condition is
specified:
- 0
, = 0
onP.,
(56)
(57)
Large concentration gradients may exist across the ground
surface boundary due to the ability of the atmosphere to act
essentially as an infinite sink for organic vapors. As gaseous
molecular diffusion coefficients are large, significant gas phase
transport may occur across the ground surface boundary to
the atmosphere.
If a stagnant boundary layer exists at the ground surface,
due to vegetation and surface roughness, then flux to the at-
mosphere can be represented [Thibodeaux. 1981] as
n*
where N is the flux (M/l}T}; i is the thickness \L) of the
boundary layer; cfl is the concentration in the soil gas at the
ground surface: and c,,m is the concentration at the top of the
stagnant boundary layer. Equation (58) is a linear approxi-
mation of the equation for diffusion through a stagnant
(59)
where n, is the unit vector normal to the ground surface
boundary Ft>, direction inwards. It is assumed that cmm in (58)
is zero. When the ground surface is impermeable, as may be
the case in winter, vfi, and Dt*, at the ground surface may be
considered to be zero, and (59) reduces to a type 2 boundary
condition as specified by (57),
NUMERICAL SIMULATIONS
Numerical Model
The set of partial differential equations developed above are
solved for a two-dimensional, vertical, cross section using the
Galerkin method of weighted residuals. As the standard for-
mulations are used, the development of the discrete equations
will not be reproduced here. Two-dimensional linear iso-
parametric quadrilateral elements, as described by Huyakorn
and Finder [1983] are used.
In the computer code developed to solve the finite element
equations, the nonlinear water flow equations are solved itera-
tivcly, using a modified Newton- Raphson technique with an
Aitken accelerator (described by Irons and Tuek [1969]). After
the solution of the water phase equations and the determi-
nation of Darcy velocities and water and gas saturation levels
TABLE I. Medium Properties Used in Simulations
Hydraulic Conduct!vines, m'day
Water Phase
Air Phase
86.400
8.640
7.200
0.720
Wat*r Saturation—Pressure Head Parameters
(58) S,
5.
.0
0.01
1.0
2.0
Additional medium properties: porosity = 0.4; gas phase relative
permeability parameter (A) * 3.7; longitudinal di&pertivity e i.Om;
transverse dUpersivily = 0.01 m: and water infiltration rate - 0.003
m/day.
-------
SLEEP AND SYKES: TRANSPORT OF VOLATILE ORGANICS
87
TABLE 2. Physical Properties of Trichloroeihylene
[Verschueren, 1983]
Property
Value
"Aqueous solubility
Liquid diffusion coefficient
Vapor pressure at 10°C
Vapor density
Maximum gas phase concentration
Caseous diffusion coefficient
Henry's Law coefficient
1.1 kg/m'
1. x 1C'4 m3/day
35.7 rnmHg
3.64 kg/M'
0.26 kg/m'
0.6 m2/day
0.236
a Picard iterative scheme is used to solve consecutively the gas
flow, water transport, and gas transport equations. The same
time step sizes are used for all of the transient equations.
When the sum of the relative changes in gas phase heads and
water and gas phase concentrations between successive Picard
iterations are less than a specified criterion, the iteration
scheme is halted and the solution for the next time step start
ed.
In order to examine the interphase mass transfer processes,
a mass balance computational scheme is included in the
model. The methods detailed by Huyakorn et al. [1985] are
Used to determine flux rates and rates of dissolution, volatili-
zation, gas-liquid partitioning and accumulation of mass in
the aqueous and gas phases.
Conditions Used for Simulations
A finite clement grid of 640 elements (697 nodes) was used
to simulate a simple physical domain. The flow boundary con-
ditions assigned are shown in Figure 1. At the ground surface,
type 2 flow boundary conditions were prescribed for the water
phase in all cases. The lower boundary was impermeable. The
side boundaries were assigned no flux conditions for the top 6
m and (ype 1 boundary conditions for the lower 4 m. for the
water phase. The type 1 boundary conditions, specifications of
water pressures, were chosen to produce an unconfined aquifer
with a water table at approximately 6 m. The infiltration rate,
porosity, and unsaturatcd flow parameters are listed in Table
1.
The gas flow boundary conditions are also illustrated in
Figure 1. Hydrostatic conditions were assigned at the ends of
the domain. The lower boundary was the water table, assumed
to be impermeable with respect to gas flow. The upper bound-
ary, the ground surface, was modeled as a constant head
boundary for some cases (summer conditions) and as an im-
permeable boundary (winter conditions) for other cases. Con-
ditions were chosen so that in the absence of density gradients
and sources or sinks, there would be no flow in the gas phase.
TABLE 3. Summary of Conditions Used in Simulations
Case
1
2
3
4
5
6
Ground
Surface
Conditions
permeable
permeable
permeable
permeable
impermeable
impermeable
A0.
day-'
0.10
0.10
0.10
0.50
0.10
0.10
A,,,
day"'
0.10
0.10
0.10
O.JO
0.10
0.10
A*.
day"'
0.10
0.00
0.10
0.50
0.10
0.10
Additional
Conditions
no gas phase
adveclion
gas venting
GAS PHASE
Fig. 2. TCE concentrations (grams per liter) at 340 days for case 1;
i0 = ir = ia = 0.1 day"1, permeable ground surface.
With the exception of the ground surface, gas and water
phase contaminant transport boundary conditions were type
2, as shown in Figure 1. In all cases water phase solute trans-
port boundary conditions at the ground surface were type 3,
with no contaminant in the infiltration flux. As shown in
Table 3, the ground surface gas phase transport boundary
conditions were either no flux (impermeable boundary), of
type 3, with diffusion scross a stagnant boundary layer. When
the diffusion boundary condition was used the thickness of the
boundary layer was 0.1 m. As indicated in Table 1, longitudi-
nal and transverse dispersivities were 1.0 and 0.01 m, respec-
tively, for all simulations.
The physical properties of TCE, listed in Table 2. were used
in all the examples. TCE is a common contaminant of ground-
water systems. It is a dense nonaqueous phase liquid with a
significant vapor pressure at typical atmospheric temperatures
and a large pure vapor phase density due to its high molecular
weight.
In the simulations performed, immobilized TCE was located
1 m below ground surface in an area 1 m deep by 6 m wide.
The initial bulk concentration of TCE was chosen as 48 kg/m1
(representing a saturation level of TCE of 10%, with a total
porosity of 0.4 and a TCE liquid density of 1200 kg/m3), for a
AQUEOUS PHASE
GAS PHASE
Fig. 3. TCE concentrations (grams per liter) al 340 days Tor case 2
/,,) = /,, =0.) day~',xK = 0,0 day ~', permeable ground surface.
-------
88
SLEEP AND SYKES; TRANSPORT OF VOLATILE ORGANKS
0.10 n *_
INITIAL RATE
0.345 kg/day
0.00
100
ZOO 300 400
Time (days)
500
600
0.10
0.08
-60.06
.20.04
o
a:
0.02
0.00 1 1 1 1
-INITIAL RATE
•0.225 kg/day
CASE
1 1 1 1 1 1 1
100
1 1 1 1 ' 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
200 300 400 600
Time (days)
ig. 4. (Top) TCE dissolution rates. (Bottom) TCE volatilization rales.
600
total TCE mass of 288 kg/m. A variety of mass transfer coef-
ficients were used, as indicated in Table 3, to test the effects of
the coefficients on transport. In addition, the effects of gas
phase advcciion on mass transfer and contaminant movement
were investigated by performing a simulation in which the
only transport mechanism in the gas phase was molecular
diffusion. The effectiveness Of gas venting for plume contain-
ment and reduction of immobilized organic was also investi-
gated by simulating gas withdrawal at nodes below the immo-
bilized TCE.
The simulations were carried out over a period of 590 days
using single time steps of 0.1, 5, 10. and 25 days and 10 time
steps of 50 days. These lime steps resulted in reasonably stable
solutions and low mass balance errors.
Results of Simulations
Importance of gas phase processes. The importance of con-
sidering g2s phase processes in modeling volatile organic
transport arc demonstrated by comparing cases 1 and 2. In
case I the mass transfer coefficients were all set to 0.1 day"1.
In case 2 the water and gas phases were uncoupled by setting
the gas-water partitioning rate coefficient to zero. The con-
centration profiles are shown in Figures 2 and 3. The contour
levels, used for plotting purposes, for the water and gas phases
-------
25.00 -q
0.00
CASE 4
0.00 Ti .^ i(H ^ ^ ^Olllllll600
Time (doys)
500
600
100 200 300 400
Time (doys)
Fig. 5. (Top) TCE accumulation in water phase. (Bottom) TCE accumulation in gas ptuuc.
0.005
-0.020
200 300 400
Time (doys)
Fig. 6. Rate of transfer of TCE from water toga* phase.
£00
600
-------
90
SLEEP AND SVKES: TRANSPORT OF VOLATILE OftGAhUCS
were chosen to be in the ratio of the Henry's law coefficient for
TCE. The contour plots for water and gas phases for case 1
have roughly the same shape, showing that the gas and liquid
phases were roughly in equilibrium with respect to TCE con-
. centrations.
The inclusion of gas phase processes resulted in greater
horizontal spreading of the water phase plume. The plume
also traveled further to the left in the saturated zone, indicat-
ing that vapor phase transport resulted in earlier arrival of the
contaminants at the water table. The process of gas-liquid
partitioning also reduced the maximum water phase con-
centrations in the region of the immobilized TCE and reduced
the aqueous phase concentration gradients. Additionally, as
the water phase acted as a sink for the more horizontally
mobile TCE vapor (due to the difference between gas and
liquid diffusion coefficients, as well as horizontal advection in
the gas phase) the spread of TCE in the vapor phase was
retarded by gas-liquid partitioning.
The rates of dissolution and volatilization were determined
by integrating the expressions for dissolution and volatiliza-
tion (equations (1) and (2)) over the area containing the immo-
bilized TCE for each time step. These rates are plotted in
Figures 4(top) and 4(bottom). The dissolution rates in both
cases are slightly greater than the volatilization rates, demon-
strating that volatilization may be an important factor in the
overall rate of dissipation of volatile organics. As the water
saturation is decreased volatilization would become increas-
ingly more important.
The rate of dissolution was increased, and the rate of vola-
tilization decreased, by the inclusion of gas-liquid partitioning,
as shown in Figure 4. Gas-liquid partitioning reduced the
aqueous phase TCE concentration gradients and increased the
vapor phase concentration gradients in the contaminated
zone. Similarly, the accumulation of TCE in the water phase
was less in case 1 than in case 2, while the changes were
reversed for accumulation in the gas phase, as shown in Fig-
ures 5(top) and 5(bottom). The rate of transfer of TCE from
the water phase to the gas phase is plotted in Figure 6. Initial-
ly the rate was positive, since the contaminant was located
near the surface where gaseous diffusion to the atmosphere
resulted in net transfer from the water phase to the gas phase.
The movement of the more mobile vapor plume deeper into
the system, where the effects of diffusion lo the atmosphere
were reduced, resulted in reversal of the direction of net in-
terphase transfer.
The Darcy velocities in the gas phase are plotted in Figure
7. The concentration gradients in the contaminated region
caused significant downward velocities beneath this zone. The
velocity just beneath the zone of immobilized TCE was ap-
proximately 0.016 in/day. The presence of the impermeable
water table deflected this downward flow sideways. The lateral
movement of dense vapors in the lower portion of the unsaiu-
AQUEOUS PHASE
GAS PHASE
I
Fig. 8. TCE concentrations (grams per liter) at 340 days for case
3; AD « ir «• (ij, = 0.1 day"', permeable ground surface, no gas phase
advection.
Fig. 7. Gas phase Darcy velocity vectors at 340 days for case 1
(maximum velocity - 0.016 m.'day. velocity scaling factor - 400).
rated zone displaced gas upwards across the ground surface
boundary to the atmosphere.
In order to evaluate the contribution of gas phase advection
to transport, the simulation of case 1 was repeated without
density-dependent flow in the gas phase. The results for case 3,
plotted in Figure 8, clearly show the importance of advection
for volatile, dense organics. The rates of dissolution and vola-
tilization were also decreased by the exclusion of advection as
a transport mechanism.
Importance of moss transfer coefficients. The effects of
changing the three mass transfer coefficients from 0.1 to 0.5
day"' are illustrated by cases 1 and 4. The concentration
profiles in the two cases are illustrated in Figure 9. The greater
mass transfer coefficients resulted in greater concentrations in
the area of the immobilized TCE and greater spreading of the
plumes. The equilibrium concentration of TCE is 1.1 g/L in
water and 0.26 g/L in air. In case 1 the maximum steady state
concentrations were less than the equilibrium values, while in
case 4 the equilibrium concentrations were reached in the
region of immobile TCE. This is an indication that the rates of
transfer of TCE from the immiscible phase to the gas and
water phases were rate controlling in case !, while the rate of
removal of TCE from the interphase boundaries was the con-
trolling mass transfer mechanism in case 4. The equilibrium
mass transfer rale coefficients would therefore be between 0.1
and 0.5 for the system as specified. Variations in infiltration
rates due to the temporal variability of precipitation might be
expected to lead to a contaminanl plume with concentration
variations correlated 10 the patterns in infiltration rates. These
results illustrate that the effective mass transfer coefficients are
parameters which could be identified by an inverse modeling
approach, using concentration and flow data from laboratory
or field data.
The advancement of the aqueous phase plume toward the
left boundary was greater in case 4, indicating that the TCE
reached the water table sooner in ca&e 4. The gas velocities
below the contaminated area were greater in case 4 than in
case I (0.022 versus 0.016 m/day) due lo the greater TCE
concentration gradients in ihe vapor phase in case 4. As a
consequence, the gas and water phase plumes moved down-
ward more rapidly.
The rates of dissolution and volatilization for cases 1 and 4
are shown in Figures 4(top) and 4(boitom). The ratios of these
-------
SLEEP AND SYKES: TRANSPORT OF VOLATILE OUGANICS
91
' f i t \
"* i i %
Fig. 11. Gas phase Darcy velocity vectors at 340 dayt for ease 5
(maximum velocity = 0.048 m/day, velocity scaling factor - 200),
GAS PHASE
Fig. 9.
TCE concentrations (grams per liter) at 340 days for case 4;
iD = iv = Jia = OJ day"', permeable ground surface.
rates were initially equal to the ratios of the mass transfer
coefficienis. Al steady state the ratios of the rates declined to
about 2.0 for both the water and gas phases.
The total accumulation or TCE in the water and gas phases
was greater in case 4 than in case 1, as illustrated in Figures
S(lop) and 5(bottom). Similarly, the rate of transfer of TCE
from the gas phase to the water phase was increased, as evi-
denced by Figure 6.
Influence of the ground surface boundary condition. The pa-
rameters used in case 1 were also used in case 5, but the
ground surface boundary was treated as impermeable with
respect to gas flow and diffusion. To isolate the effects of gas
phase boundary conditions, it was assumed that the water
infiltration and water phase boundary conditions were the
same. The concentration contours for case 5 are plotted in
Figure 10. The concentrations at the ground surface were in-
creased and there was more lateral spreading of TCE along
the ground surface boundary with the higher mass transfer
coefficients. The maximum water phase concentration was
also slightly greater. The aqueous phase plume moved further
in the saturated zone in case 5, indicating that TCE reached
the water table more rapidly than in case 1.
The Darcy velocity vectors of gas flow Tor case 5 are plotted
in Figure 11. The concentration gradients in combination with
AQUEOUS PHASE
the impermeable surface established a convection cell around
the zone of immobilized TCE. The velocity just below the the
zone of immobilized TCE was 0.018 m/day. The velocities in
most of the contaminated zone were slightly greater in case 5
than in case 1, where the ground surface was permeable.
The rates of dissolution and volatilization were reduced in
case 5, since TCE vapors could not escape to the atmosphere
at the ground surface. The rates of TCE accumulation in both
phases were increased as losses to the atmosphere were elimi-
nated. The rate of transfer of TCE from the gaseous phase to
the aqueous phase was much greater in case 5 than in case 1
and continued to increase with time as the gas plume moved
outward more rapidly than the aqueous phase plume.
Effect of gas venting. The effects of in situ gas stripping, or
gas venting, were demonstrated by simulating gas withdrawal
below the zone of immobilized TCE. It was assumed that the
ground surface was impermeable, as in case 5. Sink terms were
added at three nodes just above the water table to give a total
gas volume withdrawal of 2.4 m'/day in the two-dimensional
vertical cross section. Maximum velocities of 0.3 m/day in the
horizontal direction were produced. The vacuum at the sink
nodes was about 50 Pa (0.5 cm water).
Steady state concentrations were reached after about 40
days. The total rate of removal of TCE due to gas venting was
about 0.066 kg/day, while rales of dissolution and volatiliza-
tion were about 0.036 and 0.032 kg/day, respectively, for the
1-m-thick, two-dimensional, cross section. The rate of transfer
of TCE from the water phase to the gas phase was equal to
the TCE dissolution rate. Gas venting increased the total rate
of dissipation of immobilized TCE by a factor of 1.65 over the
natural rate of 0.04 kg/day determined in case 5. The con-
centrations at 340 days, plotted in Figure 12, show that vcnt-
AOUEOUS CHASE
GAS PHASE
10. TCE concentrations (grams pet liier) al 340 days for case 5;
/.„ • /.,. = iu = o. I duy ~', impermeable ground surface.
GAS PHASE
GAS WITHDRAWAL POINT
Fij:. 12. TCE concentrations (grams per liier) al 340 days for caw
6; ;.p - ;.(. - ;.H _ O.I day"1, impermeable ground surface, gas vent-
ing.
-------
92
SUET AND SYKS: TRANSPORT OF VOLATILE ORGANICS
ing greatly reduced the spread of the plume in both the gas
and the water phases.
CONCLUSIONS
The current understanding of the processes of dissolution,
volatilization and gas-liquid partitioning in porous media is
very limited. Information concerning the rates of these pro-
cesses, which could be used in porous media transport models,
docs not exist.
A model was developed which simulated water phase flow
and transport, and density dependent gas phase flow and
transport, in variably saturated porous media. The effects of
capillarity on gas phase flow were not included. Gas phase
flow and water phase flow were linked by the water and gas
saturation levels which were determined by water flow con-
ditions. The model incorporated rate expressions for dissolu-
tion, volatilization, and gas-liquid partitioning. Rates at which
these processes occurred were controlled through the adjust-
ment of the appropriate mass transfer rate coefficient. • • '
From a qualitative point of view, the developed model suc-
cessfully simulated the transport of volatile organics in vari-
ably saturated media, including the dissolution, volatilization,
and gas-liquid partitioning processes, Laboratory and field
studies on dissolution, volatilization, and gas-liquid partition-
ing should be conducted to gain a better understanding of
these processes and to allow validation of the model.
The inclusion of volatilization, gas-liquid partitioning, and
advection in the gas phase is necessary for accurate determi-
nation of the fate of volatile organic compounds in variably
saturated media. Volatilization and gas-liquid partitioning, in
combination with diffusion of organic vapors from the soil gas
to the atmosphere may be more important than dissolution in
dissipating residual amounts of volatile organics immobilized
in the unsaturated zone.
REFERENCES
Abriola, L. M_ and G. F. Finder, A multiphase approach to the
modeling of porous media contamination by organic compounds,
2, Numerical simulation. Water Resour. fl«, 21(1119-28.1985.
Allen, M. B. Ill, Numerical modelling of multiphase flow in porous
media, Adi. Water Resour* S, 163-186,1985.
Bachr, A. L, Selective transport of hydrocarbons in the unsaturated
zone due to aqueous and vapor phase partitioning. Water Resour.
Rrs, 2J(IO), 1926-1936, 19S7.
Bachr, A. L., and M. Y. Corapcioglu, A compositional multiphase
model Tor ground water contamination by petroleum products, 2,
Numerical solution. Water Resour. R«, 2^(1), 201-513. 1987.
Bear, J, Dynamics of Fluids in Forma Mtdia, Elsevier, New York,
1971
Brooks, P. M,, and A. T. Corey. Hydraulic properties of porous
media, Hyarol Pep. 3, Univ. of Colo, Fort Collins, 1966.
Dilling. W. L, Inicrphase transfer processes II. J. Environm. Sci.
TtfhnoL 11(4). 40SJJ09,1077.
Farmer, W. J, M. S. Yang, J. Lclcy, and W. F, Spencer, Hexachloro-
benzenr: Its vapor pressure and vapor phase diffusion in soil. Soil
Sti. Soe. Am. J.. 44, (.76-680, 1980.
Fccnstra, S., Subsurface contamination form spills of den» noneque-
ous phase liquid (DNAPL) chemical}, paper presented ai The
Second Annual Technical Seminar on Chemical Spills, Environ-
ment Canada, Montreal, Quebec, Feb. 5-7. 1986.
Frind, E. O, Simulation or long-term transient density-dependent
transport in groundwater. Adv. Water Rtsour.. S. 73-86,1982.
Green, D. W., H. Dabiri, and C. F. Weinaug, Numerical modeling of
unuturalcd groundwater flow and comparison of the mode! to a
Held experiment. Water Resour. Res, 0(3), 862-674.1970.
Hints, A. I_, and R. N. Maddox. Mats Transfer, Fundamentals ma
Applications, Prentice-Hall, Englcwood Cliffs, N. J-, 1985.
Huyalcom. P. S, and G. F. Finder, Computational Methods in Subsur-
face F/OK-, Academic, San Diego. Calif, 1983.
Huyakorn, P. S, J. W. Mercer, and D. S. Ward, Finite element matrix
and mass balance computational schemes for transport in variably
saturated porous media. Water Retour. R«, 37(3), 346-3SB, 1985.
Irons, B. M, And R. C, Tuck, A version of the Aitken accelerator for
computer iteration. Int. J. N toner. Method Eng., /. 275-277.1969.
Jury. W. A, W. F. Spencer, and W. J. Farmer, Behavior assessment
model for trace organics in toil, I, Model description, J, Environ.
QuaL 12(4), 558-563,1985.
Kell, R. F, Studies on hazardous vapour transport in toil, M.S. ihesii,
156 pp, Dep. of Civ. Eng., Univ. of Waterloo, Waterloo, Ont, 1987,
Martin, D. L, and G. M. Thompson, Remote detection of volatile
organic contaminants in groundwater via shallow gat sampling, in
Petroleum Hydrocarbon and Organic Chemicals In GrounJwoter, pp.
473-503, National Water Well Association, Nov. 5-7, Houston,
Tei, 1984.
Metcalfe, D. J., and G. F. Farquhar. Modeling gas migration through
unsaturated soils from waste disposal sites, Water Air Soil Pottut^
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Millinglon, R. J, and J. M. Quirk, Permeability of porous solids,
Trans. Faraday Sof^ 57, 1200-1207,1961.
Morcl-Scvtoux, H. J., and J. A. Billica, A Two-phase numerical model
for prediction of infiltration: Applications to a semi-infinite soil
column. Water Resour. P«, 21(4), 607-615, tPSSo,
Morcl-Scytoux, H. J, and J. A. Billica, A two-phase numerical model
for prediction of infiltration: Case of an impervious bottom. Water
Resour. Re^llO), 1389-1396, 1985fc.
Parker, J, C, R. J. Lenhard, and T. Kuppusamy, A parametric model
for constitutive properties governing multiphase flow in porous
media. Water Resour. Res., 23(4), 618-624.1987.
Pfannkuch, H. O, Determination of contaminant source strength
from mass exchange processes at the pctroleum/groundwater inter-
face in shallow aquifer systems, in Petroleum Hydrocarbons and
Organic Chemicals in Groundwater, pp. 111-129, National Water
Well Association, Dublin, Ohio, 1984.
Pinder, G. F., and L. M. Abriola, On the simulation of nonaqueous
phase compounds in the subsurface. Water Rnour. Res^ 22(9),
109S-1195,1986.
Sallam, A., W. A. Jury, and J. Letey, Measurement of gas diffusion
coefficient under relatively low air-filled porosity. Soil Sci. Soc. Am.
J,«.3-«. 1984.
Sitar. N., J. R. Hunt, and K. S. Udell. Movement of nonaqueous
liquids in groundwater, paper presented at Proceedings of Geotech-
nical Practice for Waste Disposal 1987, GT Div, Am. Soc. Civ.
Eng, Ann Arbor, Mich, June 15-17.1987.
Thibodeaux, L. J-, Estimating the air emissions of chemicals from
hazardous waste landfills, J. Hazardous Mat trials, 4, 235-244,1931.
Touma, J, and M. Vauclin, Experimental and numerical analysis of
two-phase infiltration in a partially taturated toil. Transport
Porous Media, I, 27-35, 1986.
Van Genucttien, M, A closed-form equation for predicting the hy-
draulic conductivity of unsalurated coils. Soil Sti. Soc. Am. J, 44,
892-898, 1980.
Verschueren, K, Handbook of Environmental Data on Organic Chrmi-
eals. 2nd ed. Van Nostrand Rcinhold. New York. 1983.
Vilker. V. L, and R. 5. Parnas. Analysis of volatile hydrocarbon
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WeeLs, E. t>, D. E. Earp. and C. M. Thompson. Use of atmospheric
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(Received March 17. 19BS;
revised August 22,1988;
accepted August 26,1988.)
-------
PRESENTATION OUTLINE
- .: -s •
SOIL VACUUM EXTRACTION WORKSHOP
E.P.A.
ADA, OKLAHOMA
APRIL 27-28, 1989
APPLICATION OF SOIL VACUUM EXTRACTION -
SCREENING MODELS AND FIELD CONSIDERATIONS
M. W KEMBLOWSKI
SHELL DEVELOPMENT COMPANY
HOUSTON, TEXAS
1. VAPOR FLOW IN PARTIALLY-SATURATED POROUS MEDIA.
2. UNSTEADY FLOW TO A SINGLE WELL - CONSTANT PUMPING RATE.
3. UNSTEADY FLOW TO A SINGLE WELL - CONSTANT PRESSURE.
4. GROUNDWATER TABLE UPWELLING.
5. HYDROCARBON-VAPOR PARTITIONING.
6. ANALYSIS OF THE EQUILIBRIUM ASSUMPTION.
7. DIFFUSION-LIMITED VACUUM EXTRACTION.
8. LABORATORY AND FIELD EXPERIMENTS.
-------
PRACTICAL SCREENING MODELS FOR SOIL VENTING APPLICATIONS
Paul C. Johnson, Marian W. Kemblowski, and James D. Colihan
Shell Development
Westhollow Research Center
Houston, TX 77251-1380
The efficiency of any soil venting operation will depend significantly on three factors:
vapor flowrate, vapor flow path relative to the contaminant distribution, and composition of the
contaminant. Simple mathematical models were developed to be used as screening tools to help
determine if soil venting will be a viable remediation option at any given spill site. The models
relate the applied vacuum, soil permeability, and spill composition to the vapor fiowrates,
velocities, mass removal rates, and residual composition changes with time. In this report the
screening models and some sample calculations are presented. The results illustrate the advantages
-and limitations of venting as a remediation tool, under both ideal and non-ideal conditions.
-1 -
-------
INTRODUCTION
Soil venting is rapidly becoming a popular option for vadose zone soil remediation.
Unlike traditional mitigation options, such as he "pump and treat" schemes, soil venting systems
are designed to remediate the residual contamination in unsaturated soils, and can be combined
with groundwater pumping wells to remediate soil previously beneath the water table. Venting is
ideally suited for the removal of volatile compounds from highly permeable soils, and in such
situations is expected to be more efficient and cost effective than flushing, excavation, or
incineration. With possibly thousands of gasoline service station sites scheduled to be mitigated, it
seems quite probable that this technique will be used frequently in the near future. It is important,
therefore, that we understand the nature and limitations of soil venting.
The underlying physical processes that occur during soil venting are easily
understood. As illustrated in Figure 1. a vacuum well induces vapor flow through the subsurface,
and the natural rate of volatilization is enhanced. Higher vapor pressure components are removed
first, and with time the residual in the soil gradually becomes richer in the Isss volatile compounds.
Due to the change in composition, the vapor concentrations of contaminants and r s removal
rates decrease with time.
The available published information on soil venting is limited to a few controlled
experimental studies1-2 and some sketchy reports from field venting operations'-4^ With the
large number of potential sites for venting applications, we need to evaluate each site and
determine if soil venting will be appropriate at that location. It is desirable to be able to estimate
vapor flowrates, mass removal rates, and the time required to achieve a given degree of
remediation.
The main products of this investigation are simple predictive "screening models"
which can be used to estimate the performance of a soil venting operation. Basically, the vapor
flowratc, the composition of the residual contamination, and the location of contamination relative
to the vapor flow path determine the effectiveness of any soil venting mitigation. Sections of this
report address each of these factors, and equations are presented that can be used as predictive
tools to estimate the behavior of various aspects of a venting operation, such as vapor flowrates as
a function of well vacuum, or the change in residual composition with time. Examples of model
predictions are also presented for conditions that may be typical of many venting operations.
DISCUSSION
-2-
-------
VAPOR FLOW AND VACUUM-INDUCED BEHAVIOR
Estimation of the Time Required to Achieve Steady-State Vapor Flow
In following sections we present equations that predict the steady-state vapor flow to
a venting well. In this section we seek to validate the steady-state assumption by calculating the
time required to achieve steady-state vapor flow under typical venting conditions.
Consider the vapor flow through a confined porous stratum of thickness m. . The
governing equations are:
(1)
(2)
where:
p = vapor density [gm/cm3]
e » void fraction of soil
H s= darcian vapor velocity [cm/s]
k = soil permeability [cm2] or[darcy]
p. = vapor viscosity [gra/cm-s] or [centipoise]
P = vapor phase pressure [gm/cm-s2] or[atm]
y =. gradient operator [I/cm]
Equation (H is the continuity equation and Equation (2^ is Darcy's Law. We will be studying
problems for which the vapor flows primarily orthogonal to gravity, so the second term on the
right-hand-side of Equation (2^ will be neglected. In the case of vapor flow, a pressure-density
relationship is also needed before the equations can be solved. A reasonable assumption is that the
.vapor behaves as an ideal gas, so that:
p -
-3-
-------
where pAun is the vapor density at the reference pressure PAUH- Now substituting Equations
and (3") into Equation (H produces:
The pressure, P, can be expressed in terms of the ambient pressure, PAIRI. and a deviation, P1,
from this pressure. P' is equivalent to the vacuum that would be measured in the soil. If this is
done in Equation (41 . and if we neglect the product P'2 relative to the product PAtmP'. then the
resulting equation, for radial flow, is:
The solution to Equation (5). for the following boundary conditions:
F = 0; r»>»
»->o r 2Jtm(k/|i)
is given in Bear6:
4jtm(k/(i) 2
f =""
j -*• • 0)
where Q is volumetric flowrate to the vapor well. Solutions to the integral in Equation f71 are also
given in Bear6. The behavior of the integral is such that for (r2£H/4JcPAunO<0.001, its value is
very close to the asymptotic limit.
-4-
-------
It is of interest to see how soon steady-state is reached in a typical sand formation. In
other words, what time is required for (r2e^/4kPAtmt) to become smaller than 0.001. The
following set of parameters is typical for a sand formation:
E = 0.30
H =1.8xlO-4gm/cm-s
k = 10*7 cm2 = 10 darcys
PAtm = 1.0 atm = 1.013 x 106 gtn/cm-s2
The results are presented in Figure 2. where the time to reach steady-state is plotted for each
distance away from the well, r. Predictions are presented for several permeability(k) values. For
a typical sandy soil (10
-------
p
*
u(r) " -( >
w
Here H is the length of the vacuum well that is screened through the vadose zone.
For layered soil systems, Q is equal to the sum of the vapor flowrates for all soil layers:
where Uj and Hj arc the darcian vapor velocity and thickness of each soil layer i through which the
vacuum well is screened.
To convert actual vapor flowrates to equivalent standard vapor flowrates, Q* (P = 1
'aim) the following correction factor is used:
(13)
where Pw is the absolute pressure at the vacuum well expressed in aim.
Note that Equation (91 appears to predict that the pressure distribution is independent
of soil properties. This is slightly misleading because the radius of influence RI varies with soil
type and stratigraphy. Rj, 10 some extent, is a measure of how valid the radial vapor flow
assumption is. Smaller values of RI may indicate increasing vertical vapor flow, which might
occur when a vapor well-head is not properly sealed, or when the screened interval is at a shallow
depth below an unpaved surface. However, the radial pressure distribution is fairly insensitive to
significant changes in Rj. This is illustrated in Figure^ where radial pressure distributions are
plotted for RI values equal to 50 ft and 200 ft. ''i:ure3 indicates that for all practical purposes the
pressure distribution may be independent of s>oil type. Vapor flowrates are only slightly more
sensitive to changes in Rj. For a 4-in diameter vacuum well, the vapor flowrate prediction
• 6-
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decreases by 20% when Rj increases from 50 ft to 200 ft. For most venting applications, typical
R! values will range from 50 ft to 200 ft.
Equations (9) through H31 can be used to predict the vapor flowrate achieved for a
given applied vacuum, the vapor velocity as a function of position, and the time it takes vapor to
travel from a distance r to the well, after steady state has been achieved. Figures 4 through 8
present model predictions for what are expected to be representative conditions for field venting
operations. Figure 4 presents the dependence of vapor flowrate per unit screened well depth,
Q /H, expressed in units of standard cfra/ft (scfm/ft), on the applied vacuum. These calculations
are for a homogeneous soil system with the following properties:
R! =75ft = 2286cm
Rw =2 in = 5.08 cm
k = 1 darcy = 1.0 x 10'8 cm2 (a sandy soil)
li = 1.8 x 10-4 gm/cm-s = 0.018 cp
Figure 5 depicts the dependence of the vapor flowrate per unit screened well depth,
on soil type, for a fixed vacuum well pressure of 0.8 atm. Again, the radius of influence and well
diameter are equal to the values given above.
The predicted vapor velocity distribution results in Figure 6 illustrate that the linear
radial vapor velodty(=u(r)/£; £=0.3) is greatest near the vacuum well and decreases rapidly in
moving away from the vacuum well. These results correspond to a 0.8 atm pressure at the
vacuum well, and the Rj and Rw values given above.
Figure? presents the travel times required for vapor to reach the vacuum well from
different radial positions r. The travel time i is equal to the integral:
(14)
»(r)
It is predicted that, under these conditions, the vapor from a cylindrical volume extending from
r=Rw to r=Ri is removed about r. * every five days.
-7-
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Water Table Upwelling
During a venting operation the vacuum, or reduced pressure in the soil, will cause a
rise, or "upwelling", in the water table. The change in the water table height can be easily
determined from the predicted radial pressure distribution, because the rise at any point, Hrise
(measured in feet of H2O), will be equivalent to the change in pressure at that point, expressed as
equivalent feet of H20:
H.. 33.9(1 - P(r)) [ft] (15)
me
where P(r) must be expressed in atm, and H^sc is given in ft (33.9ft H2O = latm). Figure 8
illustrates that the upwelling can be significant under typical conditions. If the predicted water
table rise occurs and the contaminated zone lies just above the water table (as is often the case),
then the groundwater will become contaminated, the contaminated zone may become water
saturated, and the mass removal rate will be reduced. These results suggest that most soil venting
operations should also include a groundwater pumping well to keep the groundwater level below
the region of contamination.
The Effect of Temperature on Vapor F!QW
For gases, both the viscosity and the density are temperature dependent. It is
worthwhile, therefore, to examine how sensitive the predictions presented in Figures 1 through 8
might be to changes in temperature. The viscosity of a gas, at low pressures, varies with
temperature (expressed in °F) according to;
Therefore, according to Equation 1 j_. the vapor flowrates to two vacuum wells operating in
similar soils and at identical pressures, but different temperatures, will be related by:
Q(J)
-8-
-------
Here the units of temperature must be °F. For two venting operations operating at 20°F and 80°F,
Equation H71) predicts that the two vapor flow rates will only differ by 5%. Typical temperature
variations, therefore, should have little effect on the flow of vapor through soils.
Estimation of Air Conductivity of Soil Vsjn_g_Puinp_Test Data
.Proper design of subsurface venting systems requires knowledge of the soil permeability to vapor
flow, k. Theoretically, this parameter may be estimated using the hydraulic conductivity value
measured from groundwater well pump tests. However, properties of the water-saturated zone are
often different from those of the vadose zone. A better estimation of k can be obtained by
performing air pump tests for the vadose zone. By rearranging EauationflH to the form:
On tn(R/R.)
k »(-!=-) ^-^ 08)
the permeability to air can then be calculated from values of Q, Pw, Rw, RI, and H. Rw and H are
characteristics of the vapor well, and Q and Pw can be measured when a vacuum pump is
connected to the well. The value for RI must be estimated, however, one can substitute fc; atm
and RI an air pressure value P measured at a known distance R from the well, and obtain a more
accurate air permeability value.
As an example, consider the air pump test data reported by Crow et al.5. which is
presented in Figure 9. The screened interval for the 2-in diameter vapor well was between 14 ft
and 20 ft below ground surface. The soil was sandy and the ground surface was paved over. The
steady-state pressure distribution data presented in Figure 9 corresponds to Q=39.8 cfm. Using
Equation fl8^ and the values:
\i = 0.018 cp
Q/H = 6.63 ft2/min = 103 cm2/s
Rw = 0.0833 ft
Pw = 0.968 atm
then the permeability of the soil to vapor flow is calculated to be in the range 50 - 60 darcy.
Typical values of k for a ;dy soil lie in the range 1 -100 darcy.
-9-
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Figure? also presents the radial pressure distribution calculated from Equation (9} for
a 60 ft radius of influence.
VENTING REMOVAL RATES. VAPOR CONCENTRATIONS. AND RESIDUAL
COMPOSITION CHANGES
In the following section a simplistic equilibrium-based model is presented that can be
used to assess how effective soil venting may be for remediating a subsurface spill of a given
composition.
Local Equilibrium Assumption
In the model development presented below it is assumed that local equilibrium exists
between vapor, free-liquid, sorbed, and dissolved phases. The validity of this assumption can be
assessed by calculating the distance over which air becomes saturated with contaminant vapors
upon entering a contaminated region. Consider the following problem; clean air enters the region
between two plates. The inside walls of the plates, which are separated by a distance 2L, are
covered by a contaminant. Assuming negligible dispersion in the direction of flow (the z-
direction), then the equation governing the vapor phase concentration, C, is:
(— ) = D(^-|) (19)
where u is the vapor velocity in the z-direction, D is the vapor phase molecular diffusivity, and x is
the coordinate perpendicular to the plates. The appropriate boundary conditions are:
(20)
c=o
c = c°
ac/ax=o
z = 0
x = L
x = 0
Here C° is the equilibrium vapor phase concentration. The solution to this problem is:
-10-
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rv ^ ^M r 2, 1.2,20-- .7TX(2n+l)
C(x,z) = C {1 - 2* exp[ - it (n+y) {—-)] cos(—~—'- ) (21)
2 uL2 2L
Equation (21) predicts that the vapor phase concentration reaches 99% of its
equilibrium value C°, at the ccntcrline x=0, after the vapor has travelled a distance:
z = 2uL2/D (22)
For a typical venting operation the greatest pore vapor velocities are likely to be u=l
cm/s. Molecular diffusion coefficients for gases are generally D=0.10 cm2/s, and a typical pore
throat diameter would not likely be much greater than 0.10 cm. For these conditions the distance
to reach equilibrium, as calculated from Equation (221. is 0.2 cm. Vapors passing through a zone
of contaminated soil become saturated within a distance that is very small in comparison with
typical contaminated zone sizes.
Model Development
A total mole balance on component i during the venting operation shown
schematically in Figure 1 is:
dM.
B (23)
where Mi is the total number of moles of i in the soil. This includes free-liquid in the soil pores,
moles sorbed to the soil or dissolved in the soil moisture, and moles found in the pore vapor. Q is
the volumetric flowrate of air plus hydrocarbon vapors into the vacuum well, Cj is the molar
concentration of i in the vapor entering the vacuum well, and t denotes time. The rate of
degradation of i, whether due to biological or chemical processes, is lumped into the term B; in
Equation (23).
Equation (23) can be solved if the relationships between Mj, Cj, and B; are known.
A detailed solution can be calculated by solving an advection-diffusion differential equation, but
detailed knowledge of the subsurface structure and spatial distribution of contaminant are required.
For the purpose of this report we will examine predictions from a simpler, albeit less accurate
11
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approach. The problem is simplified by assuming that the contaminant is uniformly distributed
throughout a given amount of soil at all times. Furthermore, we will assume that the vapor, free-
liquid, sorbed, and dissolved phases are always in equilibrium. This assumption allows us to
write explicit expressions that relate Mj and C-v Soil column venting experiments by Marley and
Hoag1 indicate that an equilibrium distribution assumption may be valid for pore air velocities in
the range 0.03-0.21 ft/s (1-7 cm/s), confirming our analysis based upon Equation f23\
To obtain a relationship between Q and Mj at any time t, we write the following total
mole balance on component it
z.PeV Hc H,O M .,
(24)
where:
Xj = mole fraction of i in free liquid phase
Zj = mole fraction of i in the vapor phase
P = total pressure in the pore vapor
e = void fraction occupied by vapor
V = volume of contaminated soil
: R = gas constant (=10.73 psia-ft3/lb mol-R)
T = absolute temperature in soil
MHC = total moles in free liquid phase
= totai moles in soil moisture phase
= mole fraction of i dissolved in soil moisture
= sorption coefficient for species i
[(mass i/mass soil)/(mass i/mass H^O)]
= total mass of contaminated soil
= molecular weight of H2O (=1 8 Ib/lb-mol)
The first term on the right-hand side of Equation (24) represents the number of moles
• of i in the vapor phase, the second term is the number of moles of i in the free-liquid phase, the
third term is the number of moles dissolved in the soil moisture, and the last term is the number of
moles sorbed to the soil panicles. In writing this term it was assumed that the total number of
moles in the soil moisture is approximately equal to the number of moles of water because
hydrocarbon components are typically only slightly soluble in water.
-12
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In order to be able to calculate the equilibrium distribution between phases we will
assume that the vapor phase behaves as an ideal gas, the free-liquid hydrocarbon phase behaves as
an ideal mixture, and the soil moisture phase is non-ideal. Then Xj, y,, and Zj are related by:
(25)
where P|v is the pure component vapor pressure of component i, and ai is the activity coefficient
for i in water. Both Pjv and O-i are functions of temperature, which we assume to be a known,
constant parameter throughout the underground zone of interest. Equation (251 can be substituted
into Equation (241 to obtain an expression that relates Mj and either Xj, yj, Zj, or Cj. One form of
this equation is:
R.O H,0
^ ) = 0 if M^ =0 (26)
H,O
= 1 if M >0
Recall that X;, the mole fraction of i in the hydrocarbon free-liquid phase is equal to:
. = M?C/MHC. (27)
The equilibrium distribution between all phases can be determined or any set of M;
by iteratively solving Equations (26) and (21) subject to the constraint that £xpl. The solution is
simplified somewhat by assuming that MH20=ihe number of moles of water in the soil moisture.
When solving Equations (26) and (27) it is important to check that Mj is great enough
to have a free-liquid phase present. Otherwise, when all the Mj are small, the contaminant is
distributed between the soil moisture, sorbed, and vapor phases. When this is the case Equation
f2g) reduces to:
-13-
-------
M.
<**=- ^ 5^ (28>
Plev _ MP
[-i=r+-
If all the products Ojyi calculated from Equation (28) arc less than unity, for a given
set of Mit then the equilibrium distribution does not include a free-liquid phase.
Solution of the Equations
A Fortran program, VENTING FORTRAN, was written to solve the governing
equations. The algorithm solves Equation (23) explicitly for each time step St:
(29)
.,. then a new equilibrium distribution is calculated by solving Equations (261. (27). and (28) given
the new M^t+St). A subroutine solves for the equilibrium distribution by first determining the
number of phases that are present by using Equation (281 and the condition that all ctjYj
-------
temperature range between TB - 70°F, the Claussius-Clapeyron equation7 predicts the vapor
pressure dependence on temperature T:
m rrt
= P;CTR) exptc-^r) A - i> I<(TR>/PB>]
v ' 1
where TR is a reference temperature at which the vapor pressure is known (in this case
TR=68°F=528R), T is the absolute temperature at which the vapor pressure is to be calculated,
and PB is the pressure at which the boiling point (TB) is measured,
Vapor pressures may be affected by the capillary forces that hold residual
hydrocarbon in the soil matrix. The following equation7 predicts the change in vapor pressure
across a curved surface with radius of curvature r
2aV
(31)
where Piv(pore) is the modified vapor pressure, o is the surface tension, Vm is the molar volume
of species i, and R is the gas constant (8.314 x 107 gm cm2/gm-mole s2 °K). Consider the results
for benzene, which has the following properties:
o = 28.9 dyne/cm
Vm = 80cm3/mole
At 68°F the results of these calculations for pore radii of 0.01 cm and 1 x 10~5 cm arc:
Piv(porc)/Piv(T) = 0.99998; r = 0.01 cm
= 0.98151; r= 1x10-5cm
Since the radius of curvature of a liquid surface between soil panicles is not likely to
be as small as 1 x 10*5 cm, any influence of surface tension on vapor pressures is negligible.
However, if the contaminant is trapped in the micropores of individual soil panicles, then the
vapor pressure reduction will be more significant if the micropore diameter is smaller than 1
cm.
-15-
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Activity coefficients in water (oq) can be estimated from tabulated solubility values.
For a pure compound at its solubility limit in water 0^=1. Since hydrocarbons are generally
sparingly soluble in water we can write:
a. s -L = (55.55 moles/1) Mw 7S. (32)
1 ™J *
•for compounds that are liquids or solids at 1 atm and the desired temperature. For gases, the
corresponding relationship is:
1 latm M .(latm)
a. = (_L.) (L^L) = (55.55 moles/1) — ^ - (33)
where MWti is the molecular weight [gm/mole] and S, is the solubility [gm/liter] of compound i in
water.
*
Soil sorprion coefficients can be estimated with the Karickhoff8 equation:
«>
where kow j is the octanol-water partition coefficient [(p 7gm-octanol)/(gm-i/gm-H2O)], and f^
is the organic carbon fraction in the soil.
Model Predictions For a Hypothetical Venting Operation
In the following paragraphs model predictions are presented for the case of a
hypothetical gasoline spill, in order to illustrate the type of behavior that is expected to be observed
in a typical soil venting operation.
As an example, predictions were computed for the following situation: 400
gal{«1500l) of regular gasoline spilled into 1412 ft3 of soil with a moisture content of 10% by dry
soil weight This is equivalent to a residual composition of gasoline in the soil of 2% by dry soil
weight, or 20000 ppm total petroleum hydrocarbon content. The bulk density of the soil is 1.5
-16-
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gm/cm3, the total porosity is e=0.4Q, and the soil has an organic carbon fraction of ^=0.01. A
typical vacuum well vapor flowrate is 20 cfm, but we will assume that only 25% of the air actually
flows through the contaminated soil. The value of Q used in the predictions is then 5 cfm(=8500
1/hr). The relative humidity of the incoming air is 100%, and the underground soil temperature is
600R
Table 1 lists compounds found in a typical regular gasoline as well as their molecular
weights, mass fractions, and mole fractions. Table 2 list the relevant physical properties for each
compound. The vapor pressures, boiling temperatures, and solubilities for most compounds are
available in the literature. Few octanol-water coefficients were found, and hence most were
estimated by the fragment correlation method presented by Hansch and Leo.9
Figure 10 presents predictions for the total mass loss rate Qm(t) and cumulative
fraction of the initial spill mass recovered over a period of 400 days. In Figure.JQ the mass loss
rate is expressed in terms of gal/hr, where it has been assumed that 6.67 Ib of hydrocarbon vapors
are equivalent to one liquid gallon(=0.8 kg/1). The results show that the rate of gasoline removal
rapidly decreases over a period of a few days, then continues to decrease less rapidly over the next
few months. After a period of 400 d, about 90% of the initial hydrocarbon has been removed.
The change with time of total hydrocarbons (HC) and the the benzene, toluene, and
xylenes (BTX) concentrations remaining in the soil are presented in Figure 11. BTX and HC
concentrations are expressed in terms of dry soil mass, and represent the total mass of BTX and
HC in the free-liquid, soil moisture, sorbed, and vapor phases. Figure H illustrates that venting
removes the compounds in the order of their relative volatilities (benzene->toluene->xylenes).
Within 200d the BTX level is reduced to below 1 ppm, while the total hydrocarbon concentrations
are reduced from 20000 ppm to about 1000 ppm.
Figure Ij illustrates how the composition of the residual changes with time. As
expected, the residual gradually becomes richer in the less volatile compounds with time. These
concentrations are again based on dry soil mass and represent the total mass that is distributed
between free-liquid, sorbed, soil moisture, and vapor phases.
Often environmental regulations specify remediation goals in terms of groundwater
contamination levels. In addition to computing soil contamination levels, therefore, BTX
Ievels(based on mass of water) that would be found in water, if leaching occurred through the
contaminated soil after a period of venting, were calculated. The results appear in Figure Ig.
- 17-
-------
Initially, the soluble BTX levels increase with time as the most volatile compounds are removed
and the residual mole fractions of benzene, toluene, and the xylenes are increased. After about 10
days, however, the BTX groundwater levels decrease and eventually are reduced to below 1 ppb.
The model also predicts the removal of soil moisture by volatilization whenever the
relative humidity of the air entering the contaminated volume of soil is less than 100%. In this
example the relative humidity of the incoming air is 100%, so no soil moisture was removed by
venting. In an actual venting operation, however, the loss of moisture may be significant enough
to hinder microbiological processes in the vadose zone.
Of course, the removal rates and residual compositions at any time are dependent on
the vacuum well vapor flowrate, as well as the initial mass and composition of the spilled gasoline.
Increasing the air flowrate may accelerate the remediation process, but it will not change the order
in which compounds are stripped from the soil. When the time and other variables are scaled
properly, all venting results for a given initial composition and temperature are equivalent. In
other words, only one venting prediction needs to be computed for a given initial composition.
The results at any time for other flowrates or initial conn nation levels can be extracted from one
"master curve". For the case of soil venting, the appropriate reduced variables are:
time: t= tQm(t^D)/W(t=O)
mass loss rate: Qm(t)/Qm(t=0)
concentrations: C(t)/C(t=0) or m(t)/m(t=0)
where Qm is the total mass removal rate, m is the total mass concentration of contaminants, C
represents the total molar concentration of contaminants, and W(t=0) is the initial mass of gasoline
in the soil. Figure J4 presents the computed master curve formed by two sets of predictions. The
"field scale" results refer to predictions for the example described above. The "lab scale" results
are for the following case:
mass of spill = 123 gm soil moisture content = 0.0
mass of soil =6000gm vapor flow rate =85.5l/hr
tcmpcrature =60°F organic carbon fraction = 0.01
It appears that the predictions are not significantly affected by the presence or absence
of dissolved or sorbed phases, unless the residual concentrations are very low. The "lab scale"
-18
-------
results are for a soil system with no moisture or sorbed phase, but still they appear to match the
"field scale" results when scaled properly.
Often the results from studies of similar environmentally-related problems(such as
landfill leaching or soil column studies) are presented in terms of "pore-volume" units. It is
important to recognize that in the case of soil venting(and soil column flushing) the pore volume
unit is not an appropriate dimcnsionlcss variable. Results from experiments conducted with
different initial masses of gasoline, for example, will not appear identical when presented in terms
of pore volume units. An analysis of the governing equations shows that the proper scaled time
variable(or equivalentiy the scaled volume of air) is formed by a combination of time, a
characteristic mass removal rate, and the original mass of contaminant
Applicarionpfjhji Results to Field and Lab Data
The scaled "master curve" can be useful for extracting information from field data.
Often prior to venting the initial gasoline mass in the soil will not be known. Also, not all of the
induced air flow will pass through contaminated soil regions, so the effective air flow rate will be
less than the pumping rate in the vacuum well. Since the estimated length of a venting project
predicted by the model depends on both the air flow rate through the contaminated region and spill
. mass, it is desirable to have good estimates for these quantities.
The effective air flow rate can be easily estimated during a venting operation by
dividing the initial mass loss rate Qm(t=0) by the initial equilibrium vapor concentration
[mass/vol.] in the contaminated soil region, m(t=0). It can be measured by a soil gas survey or
predicted from a known residual composition. The initial spill mass can be estimated by
comparing measured Qm(t)/Qm(t=0) data points with the "master curve". For each
Qm(t)/Qm(t=0) value, the corresponding value of tQm(t=0)/W(t=0) can be read from the plot.
W(t=0) is then known because t and Qm(t^)) are already known.
Because nting results from different experiments can be related when the data is
scaled properly, the effectiveness of a proposed field operation can be estimated from the results of
a quick laboratory scale veniing test on a representative soil core sample. The lab study may not
yield information on the air flow patterns in the field, but it will provide an indication of the
maximum remediation level that can be obtained.
-19-
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figure 15 illustrates how the residual composition before venting influences the
results. Predictions are presented for both the fresh gasoline described in Table 1 and the
"weathered" gasoline defined in Table 3. The composition of the weathered gasoline is based on
the boiling point distribution curve for a sample of gasoline that was found floating on the water
table below a service station. The composition listed in Tabjgjj is not the actual chemical
composition, but is one that produces a calculated boiling point distribution curve that matches the
measured curve. The weathered gasoline contains less of the more volatile components found in
the fresh gasoline.
The predictions presented in Figure 15 are for the conditions:
mass of spill = 1.21 x 106 gm (400 gal)
soil moisture content = 10% by dry soil weight
total void fraction = 0.40
organic carbon fraction in soil =0.01
temperature — 60° F
vapor flowrate = 171001/hr = 10 ftVmin
Also presented in Figure 15 are measured values reported by Brown et al.2 for a service station
venting operation. It was estimated that betweer 00 and 500 gal of gasoline was in the soil
before venting. Three vacuum wells operating at a total vapor flowrate of 60 cfm were used, and
the results presented in Figure 15 represent the total recovery from all wells.
The differences between predicted recovery rates for the weathered and fresh
gasolines are greatest at the start of venting. Vapor concentrations arc initially greater for the fresh
gasoline because it contains significant levels of the more volatile components. The predictions
illustrate that recovery rates for a weathered gasoline will decrease less with time than for a fresh
gasoline. It appears that this is the case for the field data, which shows almost a constant recovery
rate for the first three weeks of operation. These results illustrate that the efficiency of any venting
operation is linked rightly to the initial residual composition.
Temperature Effects
Model predictions seem to indicate that the soil moisture content, or other soil
properties, do not significantly influence the venting removal rates. The only other parameter that
might affect the results, therefore, is the temperature. To illustrate how the results might change
-20-
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for a given change in temperature, one can calculate the change in vapor pressure for a given
compound. From 32°F to 80°F the vapor pressure of benzene increases from 0.037 atm to 0.137
atm, while for n-dodecane the vapor pressure increases from 2.8 x 10'5 atm to 2.3 x 1(H atm.
These results indicate that a venting operation during the winter in Michigan, for example, might
take about five times longer than a similar mitigation in California, for similar spills and vapor
flowraies.
VENTING OF HETEROGENEOUS SOILS AND FREE-PRODUCT LAYERS
In the preceding development of the equilibrium-based venting model, it was assumed
that the vapor flowed through regions of homogeneously con' inated soils. In such cases soil
venting will be an effective method to remove the volatile components, as illustrated by the model
predictions. Actual spill sites may not be so ideal, so it is important to investigate cases where
vapors do not flow preferentially through contaminated soils. Possible field scenarios include
=free-liquid gasoline floating on the water table, or hydrocarbons trapped within a clay lens that is
surrounded by a sandy soil. In both of these cases vapor flows around, but not through the zone
of contamination, and the venting mass loss rate is limited by diffusion from the contaminated
rone into the moving vapor stream.
Figure 16 illustrates the mass-transfer-limited behavior that is expected to occur in
these situations. Vapors passing by the contaminated zone are initially free of contamination. As
they flow past the zone of contamination, a concentration boundary layer develops due to vapor-
phase diffusion perpendicular to the direction of vapor flow. Depending on the values of the
vapor velocity, free-product thickness, and the vapor flow path length through the contamination
zone, the total mass removal rate may be limited by vapor-phase diffusion, liquid-phase diffusion
in the free-product layer, or a combination of the two. A complete solution of the governing
transport equations is beyond the scope of this report, but we will examine the case for which
vapor-phase diffusion is limiting. This would be the case for very thin free-product layers, and
slow vapor flows, or spills of a single chemical compound.
Vapor-Phase Diffusion-Limited Mode]
The following analysis is equally applicable to situations in which hydrocarbon is
trapped within a low permeability layer, or is present as a layer of free-product. In either case, we
will assume a horizontally layered system in which the vapors flow preferentially past, and not
through the zone c jntamination.
-21-
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If diffusion in the direction of vapor flow is negligible in comparison to convection,
then the governing equation for transport in the flowing vapor is:
05)
where: r = spatial coordinate in radial direction (direction of flow)
u = daician radial velocity
C = vapor phase concentration of contaminant
D = effective porous media vapor-phase diffusion coefficient
z~ spatial coordinate perpendicular to the direction of flow
It has been assumed that the steady-state concentration profile has developed, and u(r)
is given by Equation (101 for radial flow to a vacuum well. To simplify the problem somewhat,
the compressibility of the vapor will be ignored. The approximate darcian radial vapor velocity,
UA(T). which is the incompressible flow solution to Equations fl) and (21. is:
rln(Rj/Rw)
06)
where Patm, Pw, Rj, and Rw are again the ambient pressure, vacuum well pressure, radius of
influence, and well radius, respectively. This assumption may be justified by computing the ratio
uA(R)/u(R):
U4
A _ w / I -<- f I - I I I > Cl~J\
for the test case:
k = 1 darcy = 1.0 x 10'8 cm2
ji = 1.8 x 10'4 gm/cm-s = 0.018 cp
Pw = 0.8 atm = 0.813 x 106 gm/cm-s2
= 1-0 atm - 1-016 x 106 gm/cm-s2
-22-
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Rl =75ft = 2286cm
Rw = 2 in = 5.08 cm
The results are plotted in Figure 17. which illustrates that the agreement is good,
because the ratio UA/U is close to unity over most of the region Rw
C(r,z) = A + B( ) + C( ) z£5(r)
6(r) 5(r)
= 0 z>8(r) (39)
where 5(r) is the concentration boundary layer thickness at any position r. The constants A, B,
and C are determined by the conditions:
C =C° z = 0
C =0 z = 5 (40)
|£ =0 z=5
dz
The cc iitions in Equation (40") imply that the vapor concentration at the vapor/contaminant
interface is spatially uniform. The solution is:
23-
-------
C(rtz) = C°(l-z/5)2 z<6(r)
= 0 z>8(r) (41)
Equation (4T> for C(r,z) is now inserted into Equation (38"). which is then integrated
with respect to z over the interval 0
-------
H =
e = 0.30
D = 0.088 cmVs x £•& = 0.018 cm^/s
R2 =20 ft =610 cm
R! = 2 in B 5.08 cm
For these parameter values the results predicted by Equations (42^ and (44} are:
6(Rw) = 4.75ft
T| =8%
During an actual field venting operation the conditions may not be as ideal as the
model assumptions, but the results indicate that, even under the best conditions, the efficiency of
venting from heterogeneous systems will be lower than from homogeneous systems. For the case
t :
of free-product floating on the water table, it may be more efficient to recover the free-product by
pumping. Venting could then be used more effectively the remove the trapped residual
hydrocarbon remaining in the soil after pumping. If the product is trapped in a low permeability
soil, such as clay, it will be difficult to remove by any method. Venting may be just as effective as
any other mitigation scheme in such cases.
CONCLUSIONS
The simplistic mathematical models presented in this report can be used as screening
tools to help determine if in-situ soil venting will be a viable remediation option at any given spill
site. The sample calculations illustrate that three factors most significantly influence the
performance of a venting operation: vapor flowrate, contaminant composition, and vapor flowpath
relative to the contaminant location. Soil venting will be an effective mitigation scheme for spills
of volatile mixtures in relatively permeable formations, which may be the case at many service
station spills.
If conditions favor vapor flow through a contaminated region at reasonable flowrates,
then soil venting will efficiently remove the more volatile compounds from hydrocarbon mixtures,
such as benzene, toluene, and the xylcnes. Fortunately, these are the compounds that arc of
primary concern in the current environmental regulations. Gasoline, however, contains 10% to
20% of relatively non-volatile compounds (>Cio), which arc not removed rapidly by soil venting.
If the environmental regulations become based on total hydrocarbon concentrations, it is possible
-25-
-------
that soil venting alone may not achieve the mitigation goal in a reasonable time period. Even if soil
venting removes 90% of the original residual contamination, which might be 20,000 ppm (mass
hydrocarbon/mass soil), that would leave 2000 ppm soil contamination levels. However, those
materials are thought to be bio-degradable, and the oxygen provided by the venting may enhance
that process.
The next phase of this research will be a study of venting behavior in both laboratory-
and field-scale projects. The research will be focussed on obtaining data which can be compared
with model predictions. The results should help to better characterize the behavior of soil venting
under a wide variety of conditions. We aslo plan to measure and predict the total impact of venting
and biodegradation processes in the laboratory and field.
-26-
-------
REFERENCES
1. M. C. Marley and G. E. Hoag, Induced Soil Venting for the Recovery/Restoration Of
Gasoline Hydrocarbons in the Vadose Zone, NWWA/API Conference on Petroleum
Hydrocarbons and Organic Chemicals in Groundwater, Houston, 11/5-11/7/1984.
2. R. A. Brown, G. E. Hoag, and R. D. Norris, The Remediation Game: Pump, Dig, or
Treat, Water Pollution Control Federation Conference, 10/5 -10/8/1987.
3. J. S. Thornton and W. L. Wootan, Jr., Venting for the Removal of Hydrocarbon Vapors
from Gasoline Contaminated Soil, J. Environ. Sci. Health, A17(l), 31-44,1982.
4. G. V. Batchelder, W. A. Panzeri, and H. T. Phillips, Soil Ventilation for the \- moval of
Adsorbed Liquid Hydrocarbons in the Subsurface, NWWA/API Conference on Petroleum
Hydrocarbons and Organic Chemicals in Groundwater, Houston, 11/12 -11/14/1986.
5. W. L. Crow, E. P. Anderson, and E. M. Minugh, Subsurface Venting of Vapors
Emanating from Hydrocarbon Product on Groundwater, Groundwater Monit. Rev. 7(1),
51-57, 1986.
6. J. Bear, Dynamics of Fluids in Porous Media, American Elsevier, 1972.
7. G. M. Barrow, Physical Chemistry, McGraw-Hill, 1961.
8. S. W. Karickhoff, Semi-Empirical Estimation of Sorpnon of Hydrophobic Pollutants on
Natural Sediments and Soils, Chemospherc, 10(8), 833-846,1981.
9. C. Hansch and A. J. Leo, Substituent Constants for Correlation Analysis in Chemistry and
Biology, John Wiley, New York, 1979.
-27-
-------
Table 1. Composition of a Regular Gasoline.
# Compound
1 propane
2 isobutane
3 n-butane
4 trans-2-butene
5 cis-2-butene
6 3-methyl-l-butene
7 isopcntane
8 1-pentene
9 2-methyl-l-butene
10 2-methyl-l,3-butadiene
1 1 n-pcntane
12 trans-2-pcntene
13 2-methyl-2-butene
14 3-methyl-l,2-butadiene
15 3,3-dimethyl-l-butene
16 cyclopentane
17 3-methyl- 1-pentene
18 2,3-dimethyIburane
19 2-methylpentane
20 3-roethylpentane
21 n-hexane
22 methylcyclopcntane
23 2,2-dimcihylpentanc
24 benzene
25 cyclohexane
26 2,3-dimethylpentane
27 3-meihylhcxane
28 3-ethylpentane
29 2,2,4-trimethyIpentane
30 n-heptane
31 meihylcyclohexane
32 2,2-dimethylhexane
33 toluene
34 2,3,4-trimethylpentane
35 2-methylheptane
36 3-mcthylheptane
37 n-octane
38 2,4,4-trimethylhexane
39 2,2-dimethylheptane
40 p-xylene
41 m-xylenc
42 3,3,4-trimcthylhcxane
43 o-xylene
44 2,2,4-trimethylheptane
45 3,3,5-trimethylheptane
46 n-propylbenzene
47 2,3,4-trimethylhepunc
Chemical
Formula
C3H8
C4H10
C4H10
C4H8
C4H8
C5H10
C5H12
C5H10
C5H10
C5H8
C5H12
C5H10
C5H10
C5H8
C6H12
C5H10
C6H12
C6H14
C6H14
C6H14
C6HI4
C6H12
C7H16
C6H6
C6H12
C7H16
C7H16
C7H16
C8H18
C7H16
C7H14
C8H18
C7H8
C8H18
C8H18
C8H18
C8H18
C9H20
C9H20
C8H10
C8H10
C9H20
C8H10
C10H22
C10H22
C9H12
C10H22
Mw,i
fgm)
44.1
58.1
58.1
56.1
56.1
70.1
72.2
70.1
70.1
68.1
72.2
70.1
70.1
68.1
84.2
70.1
84.2
86.2
86.2
86.2
86.2
84.2
100.2
78.1
84.2
100.2
100.2
100.2
114.2
100.2
98.2
114,2
92.1
114.2
114.2
114.2
114.2
128.3
128.3
106.2
106.2
128.3
106.2
142.3
142.3
120.2
142.3
Initial
mass
fraction
0.0001 .
0.0122
0.0629
0.0007
0.0000
0.0006
0.1049
0.0000
0.0000
0.0000
0.0586
0.0000
0.0044
0.0000
0.0049
0.0000
0.0000
0.0730
0.0273
0.0000
0.0283
O.:000
0.0076
0.0076
0.0000
0.0390
0.0000
0.0000
0.0121
0.0063
0.0000
0.0055
0.0550
0.0121
0.0155
0.0000
0.0013
0.0087
0.0000
0.0957
0.0000
0.0281
0.0000
0.0105
0.0000
0.0841
0.0000
mole
fraction
0.0002
0.1999
0.1031
0.0012
0.0000
0.0008
0.1384
0.0000
0.0000
0.0000
0.0773
0.0000
0.0060
0.0000
0.0055
0.0000
0.0000
0.0807
0.0302
0.0000
0.0313
0.0000
0.0093
0.0093
0.0000
0.0371
0.0000
0.0000
0.0101
0.0060
0.0000
0.0046
0.0568
0.0101
0.0129
0.0000
0.0011
0.0065
0.0000
0.0858
0.0000
0.0209
0.0000
0.0070
0.0000
0.0666
0.0000
-28-
-------
481,3,5-trimethylbenzene C9H12 120.2 0.0411 0.0325
491,2,4-trimethylbenzene C9H12 120.2 0.0213 0.0169
SOmethylpropylbenzene C10H14 134.2 0.0351 0.0249
51 dimethylethylbenzene C10H14 134.2 0.0307 0.0218
521,2,4,5-tetramethylbenzene C10H14 134.2 0.0133 0.0094
531,2,3,4-tetramethylbenzene C10H14 134.2 0.0129 0.0091
54 U,4-trimethyl-5-ethylbenzene C11H16 148.2 0.0405 0.0260
55n-dodecane C12H26 170.3 0.0230 0.0129
56napthalene C10H8 128.2 0.0045 0.0033
57 n-hexylbenzene C12H20 162.3 0.0000 0.0000
58methylnapthalene C11H10 142.2 0.0023 0.0015
Total 0.9969 1.0000
-29-
-------
Table 2. Physical Properties of Regular Gasoline Constituents.
# Compound
1 propane
2 isobutane
3 n-butane
4 trans-2-butene
5 cis-2-butene
6 3-methyl-l-butene
7 isopentane
8 1-pentene
9 2-methyl-l-butene
10 2-methyl-l,3-butadiene
11 n-pentane
12 trans-2-pentene
13 2-meihyl-2-butene
14 3-raethyl-l,2-butadiene
15 3,3-dinoethyl-l-butene
16 cyclopentane
1 7 3-meihyl- 1 -pentene
18 2,3-dimethylbutane
19 2-methylpentane
20 3-methylpentane
21 n-hexane
22 methylcyclopentane
23 2,2-dimethylpentane
24 benzene
25 cyclohexane
26 2,3-dimethylpentane
27 3-methylhexane
28 3-ethylpentane
29 2,2,4-trirnethyIpentane
30 n-hepiane
31 methylcyclohexane
32 2,2-dimethylhexane
33 toluene
34 2,3,4-trimethylpentane
35 2-methylheptane
36 3-methylheptane
37 n-ociane
38 2,4,4-trimethylhexane
39 2,2-dimethyIheptane
40 p-xylene
41 m-xylene
42 3,3,4-trimethylhexane
43 o-xylene
44 2,2,4-trimethyIheptane
45 3,5-triineihylheptane
46 n-propylbenzene
47 2,3,4-trimcthyIhepiane
Piv
(20c)
fatml
8.50
2.93
2.11
1.97
1.79
0.96
0.78
0.70
0.67
0.65
0.57
0.53
0.51
0.46
0.47
0.35
0.29
0.26
0.21
0.20
0.16
0.15
0.11
0.10
0.10
0.072
0.064
0.060
0.051
0.046
0.048
0.035
0.029
0.028
0.021
0.020
0.014
0.013
0.011
0.0086
0.0080
0.0073
0.0066
0.0053
0.0037
0.0033
0.0031
R
E
F
1
1
1
4
4
2
2
1
4
1
1
2
4
4
4
1
4
1
1
2
1
2
2
1
1
2
2
4
2
1
2
4
1
2
4
2
1
4
4
1
1
1
1
*
*
1
*
TB
(latm)
(c\
-42
-12
-1
1
4
21
28
30
31
34
36
36
38
41
41
50
54
57
60
64
69
72
79
80
81
90
92
94
99
98
101
107
111
114
116
115
126
131
133
138
139
140
144
149
156
159
160
R
E
F
1
1
1
1
1
1
1
1
1
1
1
1
1
4
3
1
4
1
1
1
1
1
2
1
1
1
1
4
1
1
1
4
1
2
1
2
1
4
4
1
1
3
1
5
5
1
*
Si
(20c)
(mpA)
62
49
61
430
430
130
48
148
155
642
40
203
155
1230
23
158
56
20
14
13
13
42
4.4
1780
55
5.3
4
3.2
2.2
3
14
1.5
515
1.8
0.9
0.8
0.7
1.4
0.3
198
162
1.4
175
0.8
0.8
60
0.8
R
E
F
2
1
1
5
5
1
1
2
5
5
2
1
5
*
*
2
5
2
2
2
1
2
2
1
1
2
2
5
2
1
1
5
1
2
5
2
1
5
5
1
2
5
1
5
5
1
5
kow R
E
F
736
5376
9466
2046
2046
7086
18626
7106
5256
3236
25116
7086
5256
1486
13506
8716
18206
47866
64576
64576
87106
22396
166006
1356
32366
166006
224006
224006
426606
300006
112206
575446
4901
42658 6
77625 6
77625 6
1047006
147911 6
199526 6
14131
15851
1479116
5891
3890006
3890006
47861
3890006
-30-
-------
48 1,3,5-trimeihylbenzene
49 1,2,4-trimethylbenzene
50 methylpropylbenzene
51 dimetnylethylbenzenc
52 1,2,4,5-tetramcthylbcnzcnc
53 1,2,3,4-tctramethylbenzene
54 I,2,4-trimethyl-5-ethylbenzene
55 n-dodccanc
56 napthalene
57 n-hexylbenzene
58 methvlnapthalene
0.0024
0.0019
0.0010
0.0007
0.00046
0.00033
0.00029
0.0004
0.00014
0.00010
0.000054
2
2
4
4
2
4
4
1
1
4
2
165
169
182
190
196
205
210
216
218
226
24J
1
1
4
4
1
4
4
1
1
4
1
73
57
6.8
21
3.5
21
7
2
1
5
*
2
*
*
0.0041
33
1.3
27
1
*
1
12883 6
128836
33884 6
446686
12883 6
12883 6
2040006
1.5c7 6
17386
3090006
79436
(1) K. Verschueren, Handbook of Environmental Data on Organic Chemicals, Van Nostrand
Reinhold Co., New York, 1983.
(2) D. Mackay and W. Y. Shiu, A Critics! Review of Henry's Law Constants for chemicals of
environmental interest, J. Phys. Che . Ref. Data, 10(4), 1175-1199, 1981.
(3) R. C. Weast, M. J. Astle, and W. H. Beyer, CRC Handbook of Chemistry and Physics
65th ed, CRC Press Inc., 1985.
(4) Engineering Services Data Int. Lmtd., May 1985.
(5) G. T. Brookman, M. Flanagan, and J. O. Kebe, Literature Survey: Hydrocarbon
Solubilities and Attenuation Mechanisms, API Publication No. 4414, August 1985.
(6) C. Hansch and A. J. Leo, Substituent Constants for Correlation Analysis in Chemistry and
Biology, John Wiley, New York, 1979.
* estimated values
-31-
-------
Table 3. Composition of a Weathered Gasoline.
# Compound
1 propane
2 isobutane
3 n-butane
4 trans-2-butene
5 cis-2-butene
,6 3-methyl-l-butene
*7 isopentane
8 1-pentene
9 2-methyl-l-butene
1 0 2-methy 1- 1 ,3-butadiene
11 n-pentane
12 trans-2-pentene
132-methyl-2-butene
14 3-methyl-l ^-butadiene
15 3,3-dimethyl-l-bmene
16cyclopcntane
17 3-methyl-l-pentene
18 2,3-dimethylbutane
192-methylpentane
20 3-mcthylpcntane
21 n-hexane
22 meihylcyclopentane
23 2,2-dimeihylpentane
24 benzene
25 cyclohexane
26 2,3-dimethylpentane
27 3-meihylhexane
28 3-ethyIpemane
29 2,2,4-trimethylpenianc
30 n-hepianc
31 methylcyclohexane
32 2,2-dimethylhexane
33 toluene
34 2,3,4-trimethylpentane
35 2-methylheptane
36 3-methylheptane
37 n-octane
38 2,4,4-trimethylhexane
39 2,2-dimethyIheptane
40 p-xylene
41 m-xylene
42 3,3,4-trimethylhexane
43 o-xylene
44 2,2,4-trimethylhcptane
45 3,3,5-trimethylheptane
46 n-propylbenzene
47 2,3,4-trimethylheptane
Chemical
Formula
C3H8
C4H10
C4H10
C4H8
C4H8
C5H10
C5H12
C5H10
C5H10
C5H8
C5H12
C5H10
C5H10
C5H8
C6H12
C5H10
C6H12
C6H14
C6H14
C6H14
C6H14
C6H12
C7H16
C6H6
C6H12
C7H16
C7H16
C7H16
C8H18
C7H16
C7H14
C8H18
C7H8
C8H18
C8H18
C8H18
C8HI8
C9H20
C9H20
C8H10
C8H10
C9H20
C8H10
C10H22
C10H22
C9H12
C10H22
Mw,i
(pn1
44.1
58.1
58.1
56.1
56.1
70.1
72.2
70.1
70.1
68.1
72.2
70.1
70.1
68.1
84.2
70.1
84.2
86.2
86.2
86,2
86.2
84.2
100.2
78.1
84.2
100.2
100.2
100.2
114.2
100.2
98.2
114.2
92.1
114.2
114.2
114.2
114.2
128.3
128.3
106.2
106.2
128.3
106.2
142.3
142.3
120.2
142.3
Initial
mass
fraction
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0200
0.0000
0.0000
0.0000
0.0114
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0600
0.0000
0.0000
0.0370
0.0000
0.0000
0.0100
0.0000
0.1020
0.0000
0.0000
0.0000
0.0800
0.0000
0.0000
0.1048
0.0000
0.0500
0.0000
0.0500
0.0000
0.0000
0.1239
0.0000
0.0250
0.0000
0.0000
0.0250
0.0829
0.0000
mole
frnction
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0296
0.0000
0.0000
0.0000
0.0169
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0744
0.0000
0.0000
0.0459
0.0000
0.0000
0.0137
0.0000
0.1088
0.0000
0.0000
0.0000
0.0853
0,0000
0.0000
0.1216
0.0000
0.0468
0.0000
0.0468
0.0000
0.0000
0.1247
0.0000
0.0208
0.0000
0.0000
0.0188
0.0737
0.0000
-32-
-------
481,3,5-triinethylbenzene C9H12 120.2 0.0250 0.0222
491,2,4-trimethylbenzene C9H12 120.2 0.0250 0.0222
50methylpropylbenzene C10H14 134.2 0.0373 0.0297
51 dimcihylethylbenzene C10H14 134.2 0.0400 0.0319
52 U,4,5-tetramethylbenzene C10H14 134.2 0.0400 0.0319
53 U,3,4-tetramethylbenzene C10H14 134.2 0.0000 0.0000
541,2,4-trimethyI-5-ethylbenzene C11H16 148.2 0.0000 0.0000
55 n-dodecane C12H26 170.3 0.0288 0.0181
56napthalene C10H8 128.2 0.0100 0.0083
57 n-hexylbenzene C12H20 162.3 0.0119 0.0078
58 methylnapthalene C11H10 142.2 0.0000 O.OOOQ
Total 1.0000 1.0000
-33-
-------
-34-
-------
f
To Vapor Recovery System
Air Flow
Groundwater
Air Flow
Figure 1. Schematic of a Soil Venting Operation.
-------
= 50 ft
= 200 ft
0.7
0.6
0
P = 0.80 atm
=1.0 atm
100
Distance from well (ft)
200
Figure 2. Predicted Radial Pressure Distributions.
-------
Q*/H
(scfm/ft) ;
k = 0.10darcy
P =1.0atm
atm '
P (atm)
w v 7
Figure 3. Predicted Vapor Flowrates per Unit Well Depth.
-------
1000 ,
100.
10 .
,Q*/H
•(scfm/ft)
medium
sands
.01 .
.001 .
,01
1 10
k (darcy)
1000
Figure 4 Tfect of 'oil Type on Vapor Flowrate.
-------
10
1
u(r)/e :
(cm/s)'
.1:
.01
.001 -I—
0
k = 1 darcy (fine sand)
= 75 ft
=0.80atm
P = 1.0atm
atm
e = 0.30
20 40 60
Distance from well (ft)
Figure 5. Radial Linear Velocity Distribution,
-------
5 •
4
Travel
Time to
Well
(days)
3 •
0
k = 1 darcy (fine sand)
P =0.80atm
w
P =1.0atm
atm
R =2i
R =75 ft
£ = 0.30
0
20 40 60
Distance from veil (ft)
Figure 6. Predicted Time for Vapor to Reach Well.
-------
water table upwelling
P = 0.80 atm
Mr
Patm=LOatm
Rw=2in
0.40 atm
0.60 atm
0.80 atm
0
Distance from well (ft)
Figure 7. Water Table Upwelling During Venting.
-------
15 •
vacuum
(in H2O)
12
o
predicted vacuum
- measured vacuum
Q = 39.8 cfm
R =lin
w
Rw= 1 in
= 60 ft
?w = 0.968 atm
20 40 60
Distance from well (ft)
80 100 120
Fi re 8. Predicted ai Measured Radial Pressure
Distributions.
* - data from Crow, Anderson, & Minugh(1986)
-------
Qm(t=0) = 2.87 gal/hr = 8.69 kg/hr = 19.1 Ib/hr
Qm(t)
Qm(0)
T=16°c
spill volume = 400 gal
vapor flowrate = 5 cfm
contaminated soil volume = 52 yd
soil moisture =10%
.01
changed to 3-phase system
(sorbed, dissolved, vapor)
.001
100
80
60
40
r
e
c
o
v
e
r
e
d
20
0
0
100 200
Time (days)
300
400
Figure 9. Prer ed Mass Loss Rate During a
Hypothetical Venting Operation.
-------
10000 i
•Xylenes
•Total BTX
1000 :
ppm
100 -
10 •
Total Hydrocarbon
0
T=16°c
spill volume = 400 gal
vapor flowrate = 5 cfm
contaminated soil volume = 52 yd*
soil moisture =10%
100 200 300
Time (days)
400
Figure 10. Residual Soil Concentrations of Hydrocarbons
for a Hypothetical Venting Operation.
(concentrations represent mass of hydrocarbon/mass of dry soil)
-------
3000
ppm
2000
1000
0
800
600
ppm
400
200
0
0
Original Composition
tQm(t=0)/W(t=0) = 0
0 10 20 30 40
Component #
50
Composition at t = 211 d
tQm(t=0)/W(t=0) = 41
T=16 C
spill volume = 400 gal
vapor fiowrate = 5 cfm
contaminated soil volume = 52 yd
soil moisture = 10%
50
10 20 30 40
Component #
Figure 11. Residual Composition Changes During Venting.
(c. .icentrations represent mass of hydrocarbons per unit mass of dry soil)
-------
100
10 .
ppm
i .
.1 .
.01 .
.001
Total Soluble
Hydrocarbons
Soluble BTX
changed to 3-phase system
(sorbed, dissolved, vapor)
T=16 c
spill volume = 400 gal
vapor flowrate = 5 cfm
contaminated soil volume = 52 yd
soil moisture - \Q%
0
100 200
Time(days)
300
400
Figure 12. Soluble Levels of Residual Hydrocarbons
Remaining After Venting.
-------
Qm(t)
Qm(fc=0) .
.01
.001
0
100
80
% recovered
60
40
20
0
g
D
"b
0
- field scale
- lab scale
.0.
20 40 60
tQm(t=0)/W(t=0)
80
n on
n - field scale
• - lab scale
20 40 60
tQm(t=0)/W(t=0)
80
Figure 13. Scaled "Master Curve" for a Regular Gasoline.
-------
400
Recovered
(gal) 300
fresh gasoline
n- field data*
weathered gasoline
Q = 10 ft3/min
T _ 60°F
m(t=0) = 400 gal
1000
Mass Loss
Rate 100
(gal/d)
10
11
0
20 40 60 80 100
Time (days)
Q = 10 ft3/min
T = 60°F
m(t=0) = 400 gal
weathered gasoline
fresh gasoline
20 40
60 80 100
(days)
Figrre 14. redicted Results for Frer' and Weathered
G ;olines Compared With : Id Data*.
* - 'rown, Hoag, and Morris 1987
-------
Vapor Flow
u(r)
Concentration Boundary Layer
C(z,r)
Hydrocarbon Zone/Low Permeability Region
C = 0
C = C°
-R,
Figui 15. Concentra
-------
1.2
1.1
uA/u(r)
1.0 -
•((•(••••Klllltltf Hill •illtllllil
0.9
0.8 4
0
k = 1 darcy
P =0.8atm
Inr
Rj = 75 ft
Rw = 2in
20 40 60
D ance from well (ft)
Figure 16. Comparison of Compressible/Incompress* !e
Vapor Velocity Predictions.
-------
ABSTRACT
SOIL VACUUM EXTRACTION:
LABORATORY AND PHYSICAL MODEL STUDIES
Richard L. Johnson
Oregon Graduate Center
Beaverton. OR
To Improve our ability to utilize soil vacuum extraction for remediating
subsurface contamination we need to understand the physical, chemical, and
biological processes which control the transport and fate of volatile
contaminants. These processes include the multi-phase flow of air, water and
organic phasesT"the "distribution" of ""the~"ofganics" "as 'residual'"and"in pools,
diffusion, dissolution, and volatilization.
Because of the complex nature of the interactions between the processes,
we must approach an understanding of soil vacuum extraction by using a variety
of tools, including field studies, laboratory experiments, physical model studies
and numerical models. This presentation will focus on laboratory and physical
model studies, including the roles they can play and their strergths and
weaknesses.
In general, laboratory studies can provide quantitative information on
individual processes. This approach has proven effective, for example, in
looking at the diffusion and weathering of gasoline in the unsaturated zone.
Other aspects associated with soil vacuum extraction, for example the movement
of immiscible-phase gasoline in the subsurface or the effectiveness with which
pools of gasoline can be removed by venting, are difficult to evaluate at the
.laboratory scale. Large physical models, coupled with numerical modeling, are
proving useful for examining these more complicated processes under conditions
which can still provide quantitative data. Examples of the application of both
laboratory and physical-model experiments to the problems of subsurface gasoline
movement, volatilization, weathering of the gasoline and dissolution will be
discussed.
-------
VAPOR EXTRACTION
f>
-------
VAPOR
FREE-PRODUCT
RESIDUAL PRODUCT
DISSOLVED
-------
RESEARCH APPROACHES
FIELD INVESTIGATIONS
LABORATORY STUDIES
PHYSICAL MODELS
NUMERICAL MODELING
-------
PORTANT QUESTIONS
DISTRIBUTION OF PRODUCT
VOLATILIZATION OF RESIDUAL
VOLATILIZATION FROM POOLS
DISSOLU1 iQN OF THE GASOLINE
OPTIMIZATION OF ^MEDIATION
-------
DISTRIBUTION
FIELD: DIRECT OBSERVATION
LABORATORY: COLUMN EXPERIMENTS
PHYS. MODELS: LARGE-SCALE SPILLS
MODELING: k, JLTI-PhASE FLOW
-------
VOLATILIZATION
FIELD: SOIL-GAS MESUREMENTS
LAB: SPAhGING, PhiS. PROPERTIES
PHYS. MGuELS: 3-D EXPERIMENTS
MODELING: DIFFUSION, WEATHERING
-------
DISSOLUTION
FIELD- PLUME MEASUREMENTS
LABORATORY-COLUMN EXPERIMENTS
. MODELS- 3-D EXPERIMENTS
ELING- ...ULTI-PHASE FLOW
-------
INI1
-------
COMPOSmON OF GASOLINE
RLJ5-47
-------
ALIPHATIC
-------
O)
X
ULJ
EC
ID
CO
CO
ULJ
DC
DL
o:
o
Q.
-co
so
TO -
CO
50 -
40 -
30
20
-0 -
0
TCE VAPOR PRESSURE AS A
FUNCTION OF TEMPERATURE
8
2B
TEMPERATURE (C)
-------
0.6
0.5-
0.4-
0.3-
0.2 -\
O) 0.1 -
co
O
O
co
cc
2
LU
0
i r
8
12
16 20 24 28
32 36
TEMPERATURE (C)
-------
DC
O
o
s
z
o
Q
or
LL1
DC
12
11
10
9
8
7
6
0
0
TOTAL POROSITY = 0.35
BENZENE
PENTANE
0.04 0.08 0.12 0.16
WATER CONTENT
0.2
0.24
-------
o
UJ
O
LL
UJ
O
o
111
TOTAL HYDROCARBON
VAPORS
0.8 0.6 0.4
FRACTION GASOLINE REMAINING
..2
-------
o
UJ
O
LJJ
2
O
o
UJ
TOLUENE
^SxBENZENE
HEXANE\\
\\
PENTANE
TOTAL
HYDROCARBON
VAPORS
0.8 0.6 0.4 0.2
FRACTION GASOLINE REMAINING
0
-------
01
LU
o:
ID
CO
LL
CC
o
CL
i.
O
4-
AROMATICS
678
NUMBER OF CARBONS
-------
o
*
en
HI
O
o:
O
C8
C7
TOTAL
HYDROCARBON
VAPOR
20 40 60
PERCENT VOLATILIZED
80
100
-------
DISSOLVED FRESH GASOL.^E
[HYDROCARBONS] = 150 MG/L
ALKE.—o (13.2%
ALKANES (26.8%)
AROMATICS (60.0%)
-------
DISSOLVED WEATHERED GASOLINE
C4 - C5 HYDROCARBONS REMOVED
[HYDROCARBONS] = 100 MG/L
ALKENES (6.5%:
AL.KANES (5.5%)
AROMATICS (88.0%)
-------
DISSOLVED COMPOSITION AFTER VACUUM EXTRACTION
C4 - C7 REMOVED
[HYDROCARBONS] = 27 IUIG/L
ALKANES (5.5%) ALKENES (0.0%)
AROMATICS (94.5%)
-------
WATER RESOURCES RESEARCH. VOL 24. NO. 3, PAGES 331-W1. MARCH 1988
A Field Technique to Measure the Tortuosity and Sorption-Affected
Porosity for Gaseous Diffusion of Materials in the Unsaturated Zone
With Experimental Results From Near Barnwell, South Carolina
DAVID K. KREAMER'
Department of Hydrology aid Water Resources, University of Arizona, Tucson
EDWIN P. WEEKS
V. S. Geological Survey, Lakewood, Colorado
GLENN M. THOMPSON*
Department of Hydrology anA Wattr Resources, University of Arizona, Tucton
A tracer experiment was conducted at the commercial low-level nuclear waste disposal site near
Barnwell, South Carolina, to test a new method Tor determining the tortuosity and torpiion-aflected
porosity for gaseous diffusion transport of material* in the unsaturaied zone. Two tracers, CBrCIFj and
SFK. were released at constant rate* or 105 and 3.3 ng/s, respectively, from permeation devices, which
were placed in short screened icciiont in access holes. Soil gas was sampled from 15 piezometers located
at various distances from the sources by sequentially pumping 60-160 mL of gas from the piezometers
inio a dual-column gas chromatograph located ai the tot site. The CBrCIFj concentration data ob-
tained from several of the piezometers were analyzed by use Of type curves for a conttnuouc poinl source
in an areally extensive medium bounded above and below by planar r,< -flow boundaries. The tortuosity
of I he geologic unit tested, an eolian sand, wai determined to be abuut 0.4, and the SOrplion-affecied
porosity to be 0.22. The tortuosity value is plausible, but the sorption-aHeeled porosity value is substan-
tially Ins than that computed from the drained porosity, particularly if adjustments are made for
retardation due to solution of the tracer in the liquid phase and sorption on the solid phase, The SF4
data could not be reliably analyzed.
INTRODUCTION
iT Gaseous diffusion is one transport process by which volatile
hazardous substances can escape from waste burial facilities
or from contaminated water. In addition, toxic volatile com-
pounds from surface spills may diffuse downward to the water
•table in gaseous form. Other applications requiring a knowl-
edge of diffusive transport properties of the materials in the
unsaluraled zone include estimates of CO2 flux to the atmo-
sphere from strip mine coal spoils piles, the transport of
'*COj to a deepwater table by gaseous diffusion (thus affect-
ing the apparent groundwater age), and the extent of soil aer-
ation for plant growth.
The rate of gaseous diffusion of a given trace substance
through the unsalurated zone generally is considered to be
governed by the binary gaseous diffusion coefficient for the
trace gas in free air. DAe; the tortuosity T of the medium,
which represents a measure of the added resistance to diffu-
sion imposed by the structure of the medium; and the gas-
filled or drained porosity Op. or the porosity available for
diffusive transport in the gas phase. The actual rate of diffu-
sion of (he trace gas due to its concentration gradient is gov-
' Now ai Department of Civil Engineering. Arizona State Univer-
«i>. Ttmpe.
' Now at Tracer Research Corporation, Tucson, Arizona.
Copyright 1988 by the American Geophysical Union.
Paper number ?W4I77.
«M3-1397/M, 005 W-42 77S05.0Q
emed by the parameter iOJ3Ae or DAt', which commonly is
termed the effective diffusion coefficient.
This report describes a field experiment that was conducted
at the Chcm Nuclear, Inc., nuclear waste disposal facility at
Barnwell, South Carolina, to test a tracer technique for mea-
suring the parameters that govern gaseous diffusion through a
thick unsaturatcd zone. During the experiment, tracer gases
were released ai constant rates from subsurface sources, and
their concentrations were monitored at several sampling sta-
tions located radially and vertically from the source. The
transport properties were determined by matching the lime
history of the tracer gas concentrations to theoretical type
curves.
The technique promises advantages over previous methods
because the tracer is measured at points some distance from
the source, resulting in the sampling of a larger volume of
material. Moreover, measurement of the tracer breakthrough
at points some distance from the source should allow more
accurate determination of the ability of the medium to sorb
the tracer than does measurement at (he source itself.
PREVIOUS WORK
The effective diffusion coefficient for soils commonly has
been determined in the laboratory on cores or repacked sam-
ples [Buckingham, 1904: Penman, 1940; Taylor, 1950; Currie,
1961; Erans. 1965], Either coring or repacking can substan-
tially alter the structure of the porosity of the medium. Causing
the laboratory results lo be at variance from those in the field.
Consequently, several field techniques have been developed.
Rtsiwy [1950] developed a probe that was used at depths as
331
-------
332
K.REAMEA ET AL,: GASEOUS DIFFUSION IN THE UWATURATCD ZONE
0 10 20 3O 4O SOMiies
I 1 11 r1—i ' r 1
0 15 30 45 60 75 Kilometers
Fig. I. Location of the study area.
deep as 30 cm to measure the effective diffusion coefficient.
yThe probe was pursed of oxygen and then allowed to cquili-
.- brate by diffusion with the soil gas. The gas within the probe
was periodically sampled and analyzed .by use of an oxygen
analyzer to determine the rate at which Oxygen was entering.
The method does allow in situ sampling but is limited in its
potential depth of application and could be affected by hole
construction.
Lai tt al. [197C] determined diffusion properties by inject-
ing oxygen from a hypodermic syringe into the soil and then
analyzing very small samples taken from the same syringe.
The injected volume was assumed to form a spherical source
that then diffused into the surrounding medium. Although the
method allows for the determination or both the effective dif-
fusion coefficient and the effective porosity, the volume tested
is small, and depth of measurement is shallow.
Robertson [1969] analyzed diffusive gaseous flux through a
thick (%10 m) layer of playa sediments by injecting a large
volume (30,000 mj| of xenon-133 tagged air into the underly-
ing fractured basalt and determining the decrease in xenon
Concentration in the injected volume with time as the xenon
diffused and decayed. This experiment was massive in scale
.and would be inappropriate for most investigations.
Wetks tt al. [1982] analyzed the concentration profile with
depth of two environmental fluoroearhon gases to estimate
the effective diffusion coefficient and the tortuosity of the
medium, based on independent estimates of sorpiion. This
approach is appropriate only for very thick unsaiuraied zones
in arid regions Kecau-;* the concentration gradient for the am-
bient Ruorocarbons is small in the top 10 m or so. and the
transport of the gases would be predominantly by deep perco-
lation in subhurnid and humid environments.
FIELD EXPERIMENT IN UNSATURATED ZONE
Location and Site Description
The Chcrn Nuclear, Inc. low-level nuclear waste repository
is located near BarnwelL South Carolina (Figure 1). The cli-
mate is typical of humid coastal environments. Mean annual
temperature is about 18°C, and mean annual precipitation is
1211 mm. The altitude of the site is about 80 m above sea
level.
The base of the unsaturated zone at the site is about 12.5 m
below land surface. The Miocene Hawthorn Formation, con-
sisting of sandy clay to clayey sand, extends from a depth of
3.2 m to below the water table. A relatively clean eolian fine-
grained sand occurs at depths from about 0.9 to 3.2 m, and a
0.9-m layer of sandy clay fill covers the trench containing the
waste and the surrounding area for a distance of several
meters.
Tracers Used
The technique is made possible by the availability of per-
meation device sources of volatile liquid compounds detect-
able in the parts per trillion by volume range. Several com-
pounds are available, particularly among halogenated carbon
compounds, that meet these requirements. For this experi-
ment, two compounds, CBrOF2 (also known as BCF, Halon
1211, or F-12-B1) and SF6 were used, based upon their work-
ability in permeation tube dispensers and their absence from
the ambient soil gas. The name BCF is used for CBrClF2
throughout the remainder of this report. Some physical
properties of these two compounds are listed in Table 1.
Permeation devices, in general, are small Teflon containers
initially 70-90% filled with volatile liquid that provides vapor
that slowly diffuses through the Teflon walls. (Use of trade
names in this paper is for identification purposes only and
docs not constitute endorsement by the U. S. Geological
Survey or by the University of Arizona.) The release rate is
constant at any given temperature, thus providing a constant
flux source to introduce tracer into the unsaturated porous
medium. The BCF was released from a standard permeation
tube (Figure 2a). which contains the tracer in a length of
Tenon tubing seated at both ends. The tube was 100 mm long
with an OD of 5 mm and a wall thickness of t mm. The SF6
was released from a wafer device (Figure 2H. which consisted
TABLE 1. Physical Properties of Tracer* BCF and SF.
Physical
Properly
molecular weight
boiling point, 1 aim
density, gas
Unit*
K
BCF
165.36
269.18
SF.
146.05
209.4 (iuWinwlionl
critical pressure aim
critical tempera lure K
distribution (concentration
Coefficient in aqueous
40.4S J7-<2
437.1 Jl*7
O'V OUtlSl'
(ration in
fK pnsxl
All values e«ctpi "«
>"C from ( h.-m>fal
I'1""]
-------
KREAMER er AI_: GASEOUS DIFFUSION IN THE UNSATUKATED ZONE
333
A. STANDARD PERMEATION TUBE
souo CRIMP
PLUG BAND
TOTAL LENGTH-PTFE TEFUON
ftCTIVE LENGTH
'Til
OZD
CRIMP SOLID
BAND PLUG
B. WAFER DEVICE
PERMEATION
WINDOW —
PERMEABLE
PTFE TEFLON
'DSC
0)
=p d
MACHINED
STANLESS STEEL
RESERVOK CAP
MACHINED STAINLESS STEEL
BODY
. Fig. 2. Schematics of the permeation devices used for the test, (a)
Standard permeation lube used to dispense BCF. (fr) Wafer per-
meation device used to dispense SFt.
or a 57.2-mm long by 14.3-mm diameter stainless steel ampule
fitted with a Teflon window 4 mm2 in area by 1.3-mm thick. A
wafer device is used Tor compounds that create greater inter-
nal pressure than would easily be contained in a Teflon tube.
The diffusion rate generally is slower than that ol the per-
meation tubes due to the small permeable area of the wafer
device. Both permeation devices were constructed by Metro-
nics. Santa Clara, California.
The rate of tracer release at the ambient subsurface temper-
ature for each permeation device was determined in the lab-
oratory after the field test. For the determinations each device
was placed in an air-filled flask that was in turn suspended in
a constant temperature water -bath for about 45 days. The
devices were weighed, initially daily and later at approxi-
mately weekly intervals, and the release rate was computed as
the average rate of weight loss. These measurements indicate
that BCF was released at a rate of 105 ng/s at 23.0=C and SF6
a( a rate of 3.33 ng/s at I8.8CC. Based on the nine available
measurements, linear regression of mass loss of BCF versus
time showed a correlation coefficient of 0.9809 and a standard
error of 5.14 ng/s or 4.85%. The temperatures used to deter-
mine the release rates are the same as those measured in the
field using copper-constantan thermocouples placed beside
each permeation device and read by an automatic data logger
equipped with an electronic reference junction.
Piezometer Installation and
Tracer Emplacement
The test site was near waste trench 8. The trench had been
filled wiih boxes and drums containing nuclear waste, and
sand from the sand layer had been used to fill the Space
around the containers. Sandy clay fill had then been mounded
over the trench to a depth of 0.6-1.0 m. and the area has been
revegelated with grass.
The test installation included five piezometer nesis for sam-
pling and two access holes for tracer emplacement, all placed
on a line perpendicular to the Jong axis of the trench. Three
piezometer nesis conlaining a tolal of 15 screens (nests A, B,
and C in Figure 3) were installed in March 1981 by augering
tOO-mm diumeter holes almost to the water table and cm-
placing 300-mm long by 32-mm-lD polyethylene screens at
selected depths that were connected to land surface by nom-
inal )..« inch (actually 6 J-mm ID) steel pipe. Washed medium
to coarse sand was placed around each screen, and cement
was poured down the annulus to the next level at which a
screen was to be emplaccd (Figure 4). Sampling of the air in
these holes in May 1981 showed that six of the screens (not
shown in Figure 3) were plugged, although the top and
bottom screen at each location was open. The inoperative
screens were in sections of the hole that were suspected to
have been completely coated by cement. Piezometer nests D
and E (Figure 3) were installed the day before the test, and
cement grout was added through a tremi pipe to avoid sealing
the walls of the hole. All screens installed using the tremi pipe
remained open to the formation.
The 100-mm diameter holes for emplacement of the per-
meation devices also were auger drilled to depths of 2 and
12.35 m. These holes were completed with 150-mrn long, 38-
mm-ID polyvinal chloride (PVC) screen connected to land
surface through 38-mm-PVC pipe. The annulus around the
screen was packed with washed medium to coarse sand, and
the annulus around the pipe was backfilled with drill cuttings.
The tracer test was started at 1430 LT on June 4, 1981.
when the BFC source was placed at a depth of 1.83 m in the
shallow access hole and the SF6 source was placed at a depth
of 12.2 m in the deep access hole. Both sources were suspend-
ed at the tops of the access hole screens. Gas migration up the
PVC pipe was prevented by packers set immediately above
each screen. The packers consisted of a 460-mm-long section
of bicycle inner tube stretched and clamped on a 460-mm-long
by 25-mm-diameter PVC mandrel and were inflated downhole
to a pressure of about 20 kPa.
Sample Collection and Analysis
Sample collection began the morning of June 1,1981,3 days
before emplacement of the permeation devices, to obtain
background concentrations of the various ambient trace gases
and to ensure that the analytical system was functioning. After
emplacement of the diffusion sources, samples were collected
and analyzed onsite continuously for 7 days.
Gas analyses were made with a Varian 3700 Series gas
chromatograph, which was located near piezometer nest B to
minimize the length of tubing needed to connect the samplers
with the gas chromatograph. Samples were collected through
2-mm-ID nylon tubing that extended from the center of the
piezometer screen to the peristaltic pump and from the peri-
staltic pump to the gas inlet of the gas chromatograph. The
nylon tubing was sealed at the top of the piezometer pipe
(Figure 4) to prevent atmospheric air from entering the pipe.
Samples were collected by pumping a volume of gas equal to
twice the combined internal volume of the 2-mm connecting
tubing, plus about 10 mL assumed dead space. Thus each
piezometer was pumped by a different volume ranging from
60 mL for the closest, shallowest piezometer to 160 mL for the
farthest, deepest piezometer. That volume was selected as a
compromise between the need to obtain a representative
sample and the need to minimize conveetive flow in the un-
saturated zone. Samples were withdrawn at a rate of 120
mL/min.
The sample gas entered the chromatograph system through
the gas inlet, passed through the Nafion tubing to remove •
water vapor, and split into two flows that pass through each
of the two six-port gas-sampling valves. The valves were lo-
cated in the chromatograph oven to maintain u heated, con-
stant temperature environment where the injected volume is
constant and tracer sorpiion on the valves is minimized. A
-------
3J4
KREAUER er AI_: GASEOUS DirtvaoN IN THE UNUTURATED ZONE
I SCREEN NO.
2.01 DEPTH BELOW
LAND SURFACE,
2.0 r METERS
1.0
2
6.56
2
10,0 it.
I
J
1.0 2.0
SCALE, m
II 66m
12.14ml
SF6
12.20m®
LAND
SURFACE
HAWTHORN
SANDY
CLAYEY
FORMATION
CLAY TO
SAND
I
IZ.ZSo
12.20ml
WATER TABLE
Fig. 3. Vertical section ihowing the geology and the positions of piezometer* And tracer sources at the diffusion test
installation.
volume of 1 mL or sample gas was transported through each
column by the N2 carrier gas. A dual-column/detection system
was used to simultaneously measure BCF and SF6 under iso-
thermal conditions.
Analyses could have been made with a single column and
detector using standard oven temperature programming, but
this approach would have added to the total analysis time and
might have caused the baseline of the chromatograms to drift.
The chromatographtc columns used were (1) a I-m long.
1-mm-ID column filled with Carbopack B (Supelco Inc., Belle-
fonte, Pennsylvania) and (2) a 3-m long, 4-mm-ID column
filled with 10% SP2IOO on Suplecoporl 100-120 mesh (Su-
pclco. Inc.). The columns were operated at SO°C The BCF
was measurable on both columns, but SF6 was measurable
only on the Carbopack B column. Compounds other than
BCF and SF4 that appeared in the chromatograms are
ubiquitous in the environment and appeared to be somewhat
more concentrated in the gases from the unsaturated zone
than in the atmosphere.
Compounds such as CO., which eluie in about 7 min from
Ihc 5P2100 column, require about 30 min to move through
the CarbopacL & column. Thus after five or six 5Ft measure-
ments the ambieni halocarborts begin to interfere with the SF,,
peak. At thai time the columns were bated for aboul 20 min
at lOS'C to remove contaminants. This step could have been
avoided if a system to backflush the columns had been avail-
able.
Except for the first few hours of the test, sampling was
conducted in sequence from the piezometer most distant to
5.2mm ID TUBE
UNSATURATED
SOIL
PERISTALTIC
PUMP
-
GAS
OROMflTOGRflPH
.NOMINAL t/-6" PIPE <6.-»mm ID)
ti—NATIVE SOIL FILL MATERIAL
•-CEMENT SEAL
J—AIR PIEZOMETER SCREEN
-SAND
•-CEMENT SEAL
PIPE TO DEEPER PIEZOMETER
Fig. •> Schematic of an air piezometer with sampling tube con-
nection lo tKe gas chromatograph.
-------
K REAMER ET AL.: GASEOUS DIFFUSION IN THE UWATUftATED ZONE
335
-*B5
2000
4000 €000
TIME (minutes)
8000
Fig. 5. Concentrations of BCF measured at various times in samples obtained from piezometer! located near the BCF
source. Lines indicate approximate trends.
that nearest the BCF source. Once a sampling sequence was
completed, connecting tubing in the chromatograph and the
Nafion dryer were purged with N2 Tor about 40 rnin. After
purging the Oregon air standard (obtained from Biospherics
Research Laboratory, Hillsboro, Oregon) was analyzed.
Analysis of the Oregon air standard, which contained no BCF,
showed that measurable BCF contamination developed in the
analytical system during the test. The BCF contamination
typically was about 0.01 ng/mL, The Oregon air standard was
used throughout the lest as a check on instrument per-
formance.
Absolute calibration of the data was performed on June 6
and at the end of the test using two commercial standards
(Matheson Gas Products, Cucamonga, California), one con-
taining 1 ppmv (parts per million by volume) BCF and the
other J ppmv SF6.
Results
The concentration of BCF measured at various times at
screens AS, D3, D4. D5, El. and B5 {Figure 3) are shown in
Figure 5. These screens were closest to the BCF source, were
in the colian sand, and provided concentrations of sufficient
magnitude to be analyzed. BCF measurements for screens A4
and C5 are of about the same magnitude as the background
contamination and are not shown. Screen A4 is in the sandy
clay below the sand, and the absence of measurable BCF
supports the hypothesis, discussed below, that gaseous diffu-
sion is substantially restricted in the Hawthorn Formation.
The SF6 was measured in detectable quantities at screens
Bl, B2, B5. CS, Dl, and El. The tracer probably arrived at
screens Bl and Dl (Figure 3) by diffusive transport, but the
nrasured concentrations were so small and their variance so
brge that the data could not be reliably analyzed. The SFA
measured in the oihcr screens must have occurred by convcc-
tivc flow in fractures and cannot be reliably analyzed. Pretest
modeling of the tracer tests failed to indicate any problem
with the use of the SF6 wafer device in the sandy clay both
because its effective diffusivity was overestimated and the
practical detection limit Tor SF6 underestimated. In hindsight,
however, it is apparent that the release race for SF6 of 3.3 ng/s
was too slow to provide a reliable test. The experiment involv-
ing the release of SFt is considered a failure, and the results
are not discussed further here. All measurements of both BCF
and SF4 are given by Kreamer [1982].
RELATION OF EXPERIMENTAL RESULTS TO THEORY
Ordinary Gas Diffusion
Penman [1940] described ihe one-dimensional diffusive
transport of gases in the unsaturated zone due to con-
centration gradients by a modified form of Fick's second law:
dc
.
(1)
where
a tortuosity factor accounting for the added resistance
to diffusion imposed by the structure of the porous
medium, dirncnsionless;
drained or air-filled porosity, dimensionless;
the molecular diffusion coefficient of gas A into gas B
under free air conditions, l3T~';
concentration of diffusing gas, ML"1;
dimension in direction of diffusion, L;
time, 7".
This formulation has been nearly universally used by soil
physicists and hydrologisls to analyze gaseous diffusive trans-
port in ihe umalurated zone.
Weeks ei til. [1982] modified (I) to account for the solution
-------
336
KKUMEK FT M.. CAXOUS DIFFUSION IN THE UNMTVHATH> ZONE
of the gas into the liquid phase and sorpiion on the solid
phase, based on equilibrium distribution concepts:
6D + (Br - eD)pwk, -Ml -
«,
dx1 = dt
where
0T total porosity, dimensionless;
pw density of water, M/i-J;
Lw water-air distribution coefficient. that describes the
ratio of the concentration of the gas in solution to
its concentration in the overlying air under equilibrium
conditions, M/M of water/M/L3 of air. or I?/M;
p, ' grain density, M/i? ;
kp solid-water distribution coefficient describing the
mass of solute sorbed on a unit mass of the solid phase
divided by the solute concentration (M/M of solid/M/M
of water or L°).
The entire coefficient on the left side of (2) can be considered
a sorption -corrected effective diffusion coefficient D', resulting
in the abbreviated form
2
CX1 Cl
(3)
In the development of (3) it is assumed that convective
transport can be neglected, only solution and sorption reac-
tions of the solute are occurring, and that D', and by inference
its components, are scalar quantities that are constant in time
and space. It is also assumed that D' is independent of con-
centration. The liquid phase is assumed to be immobile and to
completely wet the solid phase, and the tracer gas con-
centration is assumed to equilibrate instantaneously among
the gas. liquid, and-solid phases. This implies that diffusion of
the gas through the liquid film prior to sorption on the solid
phase virtually is instantaneous with respect to the overall
diffusion process [Weeks et aL 1982].
Equation (3), subject to the appropriate initial and bound-
ary conditions, may be solved either analytically or numeri-
cally to describe the variation in concentration with time at
any specified sampling point. An analytical solution was used
to analyze the concentration data, although a numerical solu-
tion was implemented to test the validity of some of the as-
sumptions made for the analytical solution. Details of the nu-
merical simulation techniques are not included here.
In developing the analytical solution it was assumed that
the permeation tube could be idealized as a point source, with
the trace gas diffusing spherically from the source. For spheri-
cal symmetry, (3) can be rewritten as [Jost, 1960, p. 3]:
(4)
where r is the radial distance from the origin to the point of
interest.
Car slaw and Jaeger [1959, p. 261] present a solution to (4)
for the distribution of heal in a medium of infinite extent at
any time I after a continuous point heal source begins pro-
duction in a medium initially at zero temperature. This solu-
tion, substituting gaseous diffusion parameters, is .
where
4 the rate of gaseous diffusion from the source, M/T;
A 0D + (Or - 0D)p,kw + (1 - O^kjtp, dimensionless;
u r2/4D't, dimensionless;
I the elapsed time since the start of the continuous poini
source, 7*.
The BCF source was placed in the colian sand about 0.9 m
below a contact with clay fill and 1.4 m above the contact
with the clayey sand of the Hawthorn Formation (Figure 3).
Two limiting cases may be hypothesized concerning the effects
of this layering on the pattern of gas diffusion. At one limit the
clayey beds may be assumed to have the same diffusive
properties as the eolian sand. Under this assumption the
system would be bounded above by land surface, where the
tracer gas would be maintained at nearly zero concentration
by atmospheric circulation and below by the water table or
top of the capillary fringe, which would effectively be a barrier
to diffusion because of the ten-thousandfold contrast between
diffusion constants for gas and for liquid diffusion. Alter-
natively, the clayey beds may be treated as being impermeable
to diffusion. Both of these hypotheses were tested, as described
below.
In addition to the vertical discontinuities imposed by sedi-
ment stratification, land surface, and the water table, the
waste-material-filled trench forms a lateral discontinuity that
might have a greater or lesser diffusive transport capability
than the eolian sand. However, computations based on image
theory, described below, and the assumption that the trench is
either impermeable or infinitely permeable to gaseous diffu-
sion indicate that the presence of the trench should have had a
negligible effect on tracer concentrations in the samplers
during the 7-day test.
The effects of the various discontinuities can be simulated
analytically be invoking image theory [ferns ei aL 1962, p.
156]. For such an analysis a constant concentration boundary
is simulated by assuming an image tracer sink equidistant
from the boundary on a perpendicular through the real
source, and a no-diffusion boundary is simulated by a simi-
larly located image source. For parallel boundaries, images
are reflected to infinity.
For a system overlain by a constant concentration bound-
ary and underlain by a no-diffusion boundary the con-
centration at any point x. :. where .x is measured from the
source parallel to the boundary and : is measured from the
perpendicular through the source at the constant con-
centration boundary is given by the equation
+ L I —:
where
r' the radial distance from the observation point to firs!
image sink. L;
rm" rudiiil distance from observation point to each image
source, given by the equation
r = crfc vi u
4ifD'Ar ^
(5)
(7)
-------
KKEAMFR FT AL.: GASEOUS DIFFUSION IN THE UNSATURATED ZONE
3J7
where . .
n an integer varying from I to infinity;
h bed thickness. L;
a distance from source to constant concentration
boundary, L;
: distance from constant-concentration boundary (i = 0)
to observation point, L:
x distance from real source to observation point on
parallel to boundary;
T," radial distance from the observation point to each
image sink after the first.
For a system bounded by parallel impermeable boundaries
the equation becomes
I- I m.l
where
where
i an integer varying from 1 to 4 to allow for permutations
in sign:
i distance to nearer boundary, L;
: distance from observation point to nearer boundary, L.
Oiher Transport Processes
Caseous diffusion in porous media generally is a combi-
nation of molecular diffusion and Knudsen diffusion, which is
defined as diffusion resulting from interaction of (he diffusing
gas with the pore walls [Eians et al., 1961]. However, Knud-
sen diffusion generally has been ignored by soil physicists and
hydrologists, and no attempt was made to evaluate such diffu-
sion for the sediments at the test site. Its effect is lumped into
the tortuosity factor.
Cases also may be transported by thermal diffusion, but the
temperature gradients in the unsaturated zone are small. As
an example, for a typical soil thermal dilfusivity. diurnal tem-
perature variations at the base of the clay fill (90-cm depth)
would be negligible, and the maximum temperature gradient
at that depth arising from a 20"C variation in annual surface
temperature would be less than O.I'C/cm [Campbell, 1977, pp.
16-17]. Bird et al. [I960. pp. 567-568] present tabulated data
and an equation that can be used to show that thermal diffu-
sion would be negligible under these conditions.
Convective transport may result due to barometric fluctu-
ations, a rising or falling water table, an advancing wetting
front caused by deep percolation of infiltrated precipitation,
thermal convection, or withdrawal of gas for sampling. Bttck-
inplunn [1904] showed that the effects of barometric fluctu-
ations are small. The water table fluctuated little during the
lest, and no deep infiltration occurred. Kramer [1982] has
shown that thermal convection is negligible in this field lest
and that convection due to the pumping thai took place was
small even if a "worst case" approximation of piston flow in
porous media was considered.
Type Curre Analysis
A convenient method for analyzing the concentration data
is-to prepare a family of log-log type curves of erfc 4nD' Arcft
versus l/ii for each sampler location, as shown in Figure 6.
For this analysis a composite data plot should be prepared to
the same scale by plotting re versus f/rj for each measured
concentration at each sampler.
The composite data curve needs to be matched to the type
curve family, by keeping the axes parallel and attempting to
match the sets of data values for individual samplers to the
appropriate type curves in a single match. This added re-
striction, that data for individual samplers should fall on their
appropriate type curves, provides an important constraint that
makes possible the selection of a unique match between data
showing substantial experimental scatter and the appropriate
theoretical type curves. Once the data are matched the values
for any common point to the two plots are found, and the
values D'A and D' computed. If the type curve values of 1. 1
are chosen for the match, the equations for D'A and D' reduce
to
D'A = q/4nrc
£>' «= rj/4r
(10)
(ID
where re and r*/t are the data curve values coinciding with the
1,1 point on the type curve graph. The methods of type curve
analysis arc described in detail by Ferris et at. [1962].
A composite plot of the data from piezometers B5, El. D3,
D4, D5, and AS.was prepared for analysis (Figure 6). The
chosen match between the data plots and the type curves
developed assuming that the overlying and underlying sandy
clay beds arc impermeable to diffusion (equation (8V) also is
shown in Figure 6. The data for piezometers El, DJ, D5. and
A5 all match their respective curves reasonably well, although
the concentration data show substantial scatter about their
respective type curves. The selection of the match is strongly
dependent upon the assumption that the separate trends
shown by the above four samplers truly represent the effects of
layering of the porous media, rather than random deviations
due to sampling or analytical error.
Type curves were computed using (6), which is based on the
assumption that the sandy clay is equally as permeable to
diffusion as the sand. These type curves showed a reversal in
pattern from those based on (8) (and shown in Figure 6), with
the concentrations at the more distant sampler locations being
lower, on a t/r1 basis, than those at nearby sampling locations. '
Based on the observed trend toward an increase in con-
centration versus t/r* for the more distant samplers, it is logi-
cal to conclude that the clayey sand beds behuve as at least
partial barriers to diffusive transport.
The diffusive transport properties identified cither by type
curve analysis or by numerical modeling are subject to non-
uniqueness under the best of circumstances. This problem is
exacerbated when data exhibiting substantial variability due
to analytical error, such as those collected at Barnwctl. are
used in the analyses. Consequently, the diffusive transport
properties of the clayey sand cannot be determined from the
existing data. To fully confirm this, (racer breakthroughs were
simulated using the numerical code VS2D [Lupptila el al..
1987]. For the simulations the sand layer was assigned the
properties identified from I he type curve solution, and the
-------
338
KREAMER ET AL.: CASEOUS DIFFUSION IN THE UNSATITRATED ZONE
CO
LLt
O
to
LJ
"o
o
2000
1000
100
'1/rg DIMENSIONLESS
§
100
10
•0
m
CO
o
i
m
o
S
10
100
IOOO
t/rf SECONDS PER SQUARE CM
Fig. 6. Type curve family for a conlinuoui point source in a medium of infinite area] extent bounded above and below
by nondiffusive boundaries, wilh the composite concentration data from six piezometers superimposed.
underlying clayey sand layer and overlying sandy clay fill were
assigned various assumed values of ^ff>AS in separate runs.
These simulations indicate that curves of concentration versus
lime, simulated assuming thai the clayey sand layer and fill
layer were O.I times as tortuous as the eolian sand, fit the data
equally well as those generated, assuming that the clayey sand
is impermeable 10 diffusion. Thus it can only be concluded
lhat the clayey sand has a tortuosity that is al least a few
times smaller than lhat for the eolian sand.
The curve match shown in Figure 6 results in values of
vODDA, - 0.0084 cm!/s and A - 0.22. The accuracy of these
determinations is difficult to assess. The fil of the composite
data plot to the type curve family is fairly tightly constrained
by the requirement that the data plot for each sampler follow
its own type curve. Numerical simulations indicate lhat if the
clayey sand layers are assumed to have a tortuosity less than
about 0.2 that of the eolian sand, lhat requirement is well met.
and the above match values are little aflecicd. Thus the indi-
cated eolian sand tortuosity and acUorplion-afleeted porosity
are not sensitive to the confining bed properties.
The reliability of the above transport property estimates are
also dependent on the assumption that the data for samplers
El, D-4, D5. and A5 arc representative of the eolion sand as a
whole, and that those for B5 and D3 are anomalous, as de-
scribed below. Even based on this assumption the data show
enough scatter lhat the match point can be shifted signifi-
cantly without substantially violating the constraint that the
data for each sampler follow its own type curve. Match points
for the two plausible extremes (not shown) indicate that the
actual value of fO^jn ranges from 0.006 to 0.012, or about
±40",'., of the selected value. Moreover, the actual value of A
ranges from 0.19 10 0.25. Finally, the match of data from an
individual sampler to its type curve without respect to data for
the other samplers is much less constrained in some cases and
could result in identified diffusion property vulues ranging by
a factor of 3 or more. Thus it appears that multiple samplers
are required for a technique such as Ihis that generates noisy
Data frf>m sampler US show a radically different irend lhan
Ihnse from the other samplers on the composite plot. It was
first hypothcsircd that the delayed response, on a //r1 basis,
was due to a phenomenon analogous to well-bore storage
-------
KREAMER FT Al_: GASEOUS DlFFVSION IN T1IE UNiATURATED ZONE
339
[Papadopulos, 1967] because the tracer was released into a
short screen of finite diameter, rather than into the medium
itself. However, numerical model calculations were also made
using the actual dimensions of the permeation tube and well
screen; the volume within the well screen was assigned a diffu-
sion coefficient equal to that of BCF in air and a porosity of
unity, while the eolian sand was designated as having the
properties identified by the type curve solution. The simulated
concentrations versus time for all sampler locations are essen-
tially undistinguishable from those generated using the ana-
lytical solution, thus confirming the adequacy of the assump-
tion that the permeation tube and screen can be considered a
point source. The delayed response for this sampler instead
might result from effects of the cement coating that may have
built up along the borehole wall as underlying screens were
grouted in. This coaling may have lengthened the path re-
quired for the tracer to reach the sampler.
The early data from piezometer screen D3 also deviate sub-
stantially from their type curve, although the very latest data
to fit the curve. This response may arise because of a local
heterogeneity in the eolian sand, say a higher moisture content
near the lower contact with clayey sand. No attempt was
made to numerically simulate the data for this sampler.
SUBCOMPONENTS OF THE SORPTION-CORRECTED
EFFECTIVE DIFFUSION COEFFICIENT
The sorption-corrected effective diffusion coefficient is a
compound term that includes the free air binary gas diffusion
coefficient, total and drained or air-filled porosity of the
medium, the tortuosity of the medium to diffusion transport,
and the distribution coefficients for the tracer gas between air
and water and between water and the solid matrix, which in
turn provide a sorption-affected porosity. Each of these terms
was measured or estimated independently to evaluate the
plausibility of the test results.
Fret Air Diffusion Coefficient
The free air diffusion coefficient DAf is a measure of the rate
at which gas A diffuses into gas B (with equimolar counter
diffusion) in response to a concentration gradient under free
air conditions. Because a value is not available, to these au-
thors' knowledge, for the diffusion of BCF into air or its com-
ponents the values were estimated using an equation by Slai-
ifry and Bird [1958]. These computations, which generally
give resulis accurate within about 8% [Bird et al., 1960, p.
506], indicate that the free air diffusion coefficient of BCF, in
square centimeters per second, into nitrogen, oxygen, and air
at 23'C are as follows:
Air
BCF 0.092 0.090 0.092
Values for the diffusion of BCF into air was computed from
Blanc's law [Marrero and Mason, 1972. p. 7]:
1
(12)
where
x mole fraction of designated species;
A subscript denoting (race gas species.
The soil gas was assumed to be 80"-i N^ and 20%
Pttrosily. Mtriuurf Content,
and Grain Density
Porosities and moisture contents were determined on split
spoon samples of both the clayey sand and eotian sand using
standard techniques [Black, 1965]. Samples were weighed,
oven dried at 105'C, and re weighed. Porosities were calcu-
lated from the volume of the sample and the separately deter-
mined specific gravity of the solid material, and volumetric
moisture contents were calculated from the sample volume
and weight loss during drying.
Total porosity 0T, for the section of the Hawthorn forma*
tion extending from 3 to 13 M in depth ranged from 0.31 to
0.43, with an average for 16 samples of 0.38. The standard
deviation about the mean is 0.034.
Volumetric moisture contents were also determined on
these samples. The three deepest samples were collected from
within the capillary fringe, and the remaining 13 samples had
moisture contents ranging from 0.23 to 0.33, with a mean of
0.29 ± 0.03. However, those samples collected immediately
below the eolian sand-sandy clay contact had moisture con-
tents of about 0.30-0.33, possibly because the material in this
interval and a higher clay content than those deeper in the
formation. The drained porosity of the sandy clay unit above
the capillary fringe averages 0.09 ± 0.03, with the uppermost
section showing a drained porosity of about 0.06.
The eolian sand, extending from about 1 to 3 m in depth
was not well retained in the split spoon sampler, and only one
undisturbed sample was obtained for this study, and its poros-
ity was 0.38. Five additional drive core samples of eolian sand
were obtained by Dennehy and McMahon [1987], and the
porosity of these samples ranged from 0.36 to 0.40, except one
sample showing an anomalously low value of 0.28. The
median porosity value for all but the anomalous sample of
0.38 was assumed to be representative of the eolian sand.
The volumetric moisture content of the eolian sand was not
well determined. The one drive core sample obtained for this
study had a volumetric moisture content of 0.23. In addition,
two disturbed samples of the eolian sand were collected from
the auger bit during drilling, and gravimetric moisture con-
tents were measured on these samples. These gravimetric
moisture contents were converted to volumetric moisture con-
tents by assuming a porosity of 0.38 and a grain density of
2.69 g/cms. The two moisture contents thus determined were
0.03 and 0.05. The cause of the large difference in moisture
content between the drive core and the disturbed samples is
not known. Additional data on moisture content of the eolian
sand were obtained by Dennehy and McMahon [1987]. They
monitored soil moisture tension at two sites in the sand in
1983 and 1984 and developed moisture characteristic curves
for samples of sand from each tensiometer installation. The
saturation and volumetric moisture content can be inferred
from these measurements and indicate that volumetric mois-
ture contents were about 0.08 and 0.10 at the two sites in the
summers of 1983 and 1984. These values, averaged with the
three determined for this study, indicate that volumetric mois-
ture content may be about 0.10. resulting in an estimated
drained porosity of about 0.28.
7~iirfiHi.vi/r
The lorhmsiiy of the sand unit can be estimated from the
I)'.-I value from the type curve match (0.0084 cmj/s). Because
D'.-l •= t(',,£>. wiih a free air diffusion coefficient for BCF into
air of 0.1W2 cnr.s and the type curve determined gas-filled
porosity of 0.22. the tortuosity is 0.42. If the gas-hllcd porosiiy
-------
340
KRUMER ET AL: GASEOUS DIFFUSION (N THE UNUTURATED ZONE
TABLE 2. Tortuosity of Eolian Sand and Sandy Clay
Tortuosity
Author
Equation
Eolian Eolian Sandy
Sand. Sand. Clay,
B0 = 0.22 tia~ 0.28 «„ = 0.06
Marshall [1959] OB"* °-«7 &53 0-22
Milting,™ [1959] 0p'JtV OJO 0.36 0.006
Wesseling [1961] [(0.9flp-O.I)/OJ 0.45 0.54 Negative
Laiirt at. [1976] Vs 0-»3 «-I8 °-02
X//wrr»n [1979] 0.77(0B;flr| - 0.274 0.18 0.30 Negative
is instead 0.28. as estimated from sample and tensiometer
data, the tortuosity is 0.33. If the gas-filled porosity is one
standard deviation larger, or 0.35, the tortuosity is 0.26. Thus
the tortuosity of the eolian sand probably was about 0.3-0.4
at the water content prevailing at the lime of the test. For
comparison, several empirical and semiempirica! equations are
available for estimating tortuosity from air-filled and total po-
rosity [Weeks el a/., 1982]. The results of inserting gas-filled
porosity values of 0.22 and 0.28 and a total porosity of 0.38
into selected equations are tabulated in Table 2. Tortuosity
values for the sandy clay, computed using a drained porosity
of 0.06, as determined for the materials immediately below the
eolian sand contact, and a total porosity of 0.38, arc also
shown. Because the drained porosity of the eolian sand is only
imperfectly known, it is difficult to arrive at a conclusion re-
garding which of the equations best predicts the tortuosity of
the sand. However, all of the equations cited except that of
Marshall indicate that the tortuosity of the sandy clay unit is
quite small, in keeping with the results of the tracer test.
Other empirical equations relating tortuosity to drained
and total porosity, as discussed, say by Weeks el at. [1982],
would •provide an even larger range of values. These large
variations suggest that the empirical equations tend to be ap-
plicable only to the materials for which they were developed
and that they be used with care. In fact, their large variance
indicates the need to experimentally determine, e.g., by the
described technique, tortuosity in situations where the accu-
rate prediction of gaseous diffusion rates is important.
Distribution Coefficients •*
For this test the liquid phase (unsaturated zone water) was
considered to be immobile, and the diffusing tracer was as-
sumed to equilibrate with the water as it migrated outward
from the source. The assumption that the liquid phase is im-
mobile in such a humid environment is somewhat suspect.
However, studies by Drnnehy and McMahon [1987, pp. 37-
47]. involving the leaching of salt by deep percolation indicate
that such transport occurs only in the fall and early spring and
thai transport rotes are typically no more than millimeters per
day. Thus water movement during the 7-day lest was likely
quite 'small and can appropriately be ignored. The quantity of
tracer stored in the water can be estimated by multiplying the
water content by the wnter-air distribution coefficient. The
waier-iiir distribution coefficient for BCF at room temperature
(about 25 C| was determined by Tlumipson and Stilt's [19S1, p.
4] to he 0.22 mL p.
The BCT" in the wilier nlso w;is assumed to sorb to the solid
grain* of the medium, thus providing additional storage of the
diffusing compound. Kreamer [I9K2] attempted to determine
the solid-water distribution coefficient Kn for BCF on soil
samples from the site near Barnxvel! as a function of moisture
content. Mis results are erratic but indicate that the KD prob-
ably ranges between 0.0 and 0.1.
Tliumpion and Stiles [1981, pp. 33-36] determined a KD of
0.05 for BCF on sieved quartz sand cleaned of organic matter.
based on replicated column experiments. This value may be
reasonable for the eolian sand at the site near Barn well. No
measurements of organic content of the sand were made, but
visual examination suggested that their content is small.
Sorption-Affected Porosity
The water-air and solid-water distribution coefficients can
be used to compute a value of sorption-affecled porosity, A =
OB + kjiJOr - 0D) + kokj>Jil -Or), which in turn can be
compared to the value of A determined from the field experi-
ment. From the values for the various parameters listed pre-
viously. A = 0.32, which is substantially larger than the value
of 0.22 determined from the chosen best fit of the field data.
These results suggest that porosity of the eolian sand is over-
estimated, the prevailing moisture content was underesti-
mated, or that only part of the gas-filled porosity was effective
in trace gas transport. These uncertainties greatly outweigh
any probable effect of dissolution of the tracer in the liquid
phase or sorption on the solid phase. Thus the potential of
this type of tracer test to determine in situ sorpiion character-
istics of unsaturated materials remains undemonstrated.
POSSIBLE IMPROVEMENTS IN THE TECHNIQUE
To our knowledge, this experiment is the first of its kind.
Based on the results, several improvements might be made in
the experimental technique.
In deeper unsalurated zones, or in shallower systems with
fracture porosity, the volumes of gas that need to be pumped
to obtain samples may be large enough to produce significant
convective flow. This could be avoided by recirculating the
sample gas back down the piezometer, using either a parallel
or concentric small-diameter tube. Under these conditions the
gas chromatograph would need to be purged thoroughly be-
tween each sample run to avoid contamination by gas from a
previous run. Valves that allow each pneumatic line to be
isolated from the atmosphere and other lines also will aid in
reducing contamination. Ultrapure N, needs to be used as a
purge gas in the recirculating system, rather than He, because
He would tend to create a countcrdiffusive flux from the sam-
pler into the medium.
The internal volume of the screened section containing the
source needs to be kept to a minimum to avoid the well-bore
storage effect. Minimizing the volume of the pneumatic lines
will decrease the volume of withdrawal and convective flow in
a system in which the sampled pas is discharged to the atmo-
sphore or the amount of recirculation and potential contami-
nation in a rccirculaiion system.
The moisture content of the unsaturated zone needs to be
monitored periodically during the lest. These measurements
would provide a check on the validity of the assumptions that
there is no change in gas-rilled porosity, no pressure effect of a
continuous wetting front, no tracer transport due to down-
ward percolating water, and no fluctuation of the water table.
Also, one of the greatest weaknesses of this test was the failure
to adequately determine the drained porosity of the eolian
sand unit because of uncertainty in the measurements of volu-
metric moisture content. Estimates based on properly cali-
brated neutron logs probably would have been more accurate.
If the unsaturatcd materials at a site vary substantially in
their properties, the test probably will need analysis using a
numerical model. As an example, if moisture content varies
-------
KREAMER ET AL.: GASEOUS DIFFUSION IN THE UFOATVIKATED ZONE
34)
;:e:uiy spatially, it may be necessary to treat tortuosity as
-onii: selected function of moisture content or drained porosity
,«nJ 10 solve for the function parameters that provide the best
rr.atch to the measured data. A computer-aided automatic
>carch procedure would be useful in such cases.
SUMMARY AND CONCLUSIONS
Two simultaneous tracer tests were made at the nuclear
uaste disposal site near Barnwell, South Carolina. In one test,
BCF was released from a permeation tube at a rate of 105
ng s into an eolian sand extending from 0.9 to 3.2 m below
land surface. The sand was overlain by sandy clay fill and
underlain by sandy clay to clayey sand of the Hawthorn For-
mation. The tracer was monitored in eight piezometers com-
pleted in the sand and in seven piezometers completed in the
sandy day at various depths. A composite curve of con-
centration data from the six piezometers closest to the source
was analyzed by use of type curves for a continuous point
source to yield a value for tortuosity of about 0.4. The tortuos-
ity value of 0.4 is plausible, although the determination is
based on data showing substantial scatter due to analytical
errors. Consequently, that value may be in error by as much
as 40%. The type curve sorption-afTecled porosity value of
0.22 is not unreasonable. The value is substantially smaller
than the value of 0.32 computed from laboratory and other
field data, but these differences possibly can be accounted for
by errors in the type curve match, in determination of porosity
and/or moisture content, or by only part of the drained poros-
ity being involved in gaseous diffusion transport.
The second experiment was performed by releasing SF6
from a permeation device at & rate of 3.3 ng/s in a sandier
zone within the Hawthorn Formation between a depth of 11.3
m and the water table ai about 12.5 m. The results from this
test were not reliable. The tracer release rate probably was loo
slow to provide accurate concentration measurements, and
convective flow may have occurred in fractures due to pump-
ing for sampling, resulting in anomalously rapid movement of
the tracer from the source lo some of the piezometers.
Field tests using permeation tube devices as sources of trace
gases and a field-operated gas chromatograph are feasible and
can be used to obtain reliable estimates of tortuosity and
sorption-aHected porosity at a site. Such values should be par-
ticularly useful to compute the fluxes of radioactive or toxic
gases from a nuclear or toxic waste repository. The method
has the advantage that diffusion parameters are determined in
situ on a sample comprising several cubic meters of material
that should include the effects of soil structure and fractures.
The method is time consuming and expensive and requires
skilled practiiioncrs both to make the analyses and to inter-
pret the data. Hence application of the technique probably
will be limited to major waste disposal site investigations,
major volatile loxic spill sites, and sites underlain by ground-
water contaminated by volatile substances.
ArknowleiigmfMs. James Cahill. V. S, Geological Survey, made
arrangements with Chem Nuclear. Inc.. 10 conduct the test; he in-
stalled ihf piezometer nests, obtained cores, and made the laboratory
analyse! on cores. Marie Busscy of the University of Arizona assisted
in the field installation of the gas chromatograph and in making
".as-sample analyses.
RiiFERnscrs
Alhemon, M.. Carbon dioxide balance in the pus-filled part of the
unviiur.iled zone, dcmonsiraied at a nodsol (in liernwni, T. f/lan-
twrnachr BixJfnl... 141. .19-56, 1979.
Bird, R. U.. W. F.. Slewan, and E. N. Lighifooi, Trun.tp»rr
p. 567. John Wiley. New York. I960.
Black. C. A. nr»>. I..IU»,MHJ. ci) MI*.'*
VuL-u^t »-. ]«>v*.
u-ti«H),.iiiK-T Jt. CiO.
Niucmbcr .V I*»s7.|
-------
U/»I HYgJJOUJGl^^^
Robert J. Sterrett nWIcQNsuuANTsTTNc1
Analysis of in situ Soil Air stripping Data
Abstract
In situ soil air stripping was used to remediate
contamination from a spill of 1,3-dichloropropene (DCP) near
Benson, Arizona. The initial design of the system was based upon
the application of steady-state ground-water flow equations
modified for gaseous flow and steady-state diffusion equations.
The initial system included two blowers, ten extraction wells,
observation wells and recharge wells. Initial analysis of the
production data suggested that closer well spacings were needed,
also the extent of the spill was larger than first anticipated,
thus, necessitating additional wells. The final system included
three blowers and 79 extraction wells.
At the end of six months of operation, 90,000 pounds of DCP
were extracted. During the extraction process, a significant
amount of data were collected such as; exhaust gas flow rates,
gas concentrations, extraction gas and air temperatures, and
vacuum pressures in the system, bulk densities of the soil and
radii of influence of the extraction system, climatological data
were also digitally recorded. Such data included: air
temperature, relative humidity, barometric pressure, wind speed
and soil temperature. The influences of these various parameters
on the performance of the system were analyzed after the project
ended.
Based upon the analysis of the data, which included visual
observations of the data as well as multiple regression analysis,
the following conclusions were made.
• Concentrations of DCP in the blower exhausts fluctuated
directly with air moisture changes.
• Air temperature changes have a direct correlation with
DCP concentrations.
• Wind and barometric pressure changes did not influence
DCP production concentrations.
' • Bulk density of soil directly influences the anticipated
production rates.
• Diffusion from low permeability zones is an important
transport mechanism.
-------
HCI
jjYDflOLOGtC
Abstract
Page 2
As a result of this study, it was found that significant
reductions in operational costs can occur by pulsating the blower
operations, injecting humidified air into the contaminated soils
(for dry soils), operating during warm weather and reducing
extraction well spacing in areas where high bulk densities exist.
-------
ABSTRACT D. A. Keech Tel: (213) 694-7590
Chevron Oil Field Research Company
La Habra, California 90631
Subsurface Venting Research and Venting Manual
by the American Petroleum Research Institute
A brief summary of research, past and current, funded by the
American Petroleum Research Institute (API) will be
presented. As an outcome of the research, a venting manual
has been drafted which is due to be published this year.
The overview of the research will encompass the conclusions
from four past studies. Texas Research Inst. conducted
laboratory and pilot scale studies in the early eighties.
The pilot scale results were the basis for two field studies
conducted jointly by Riedel Environmental Services, Inc. and
Radian Corp. The first evaluated the effects of a single
venting well at various flow rates, with and without the
influence of air inlet wells (API Publ. No. 4410). The
second evaluated the combined effects of multiple venting
wells with no air inlet wells (report yet to be published).
The objectives of a field-project currently underway by
Harding Lawson Assoc. to document two full-scale case
studies will be outlined.
The venting manual was designed as a practical tool for two
user groups: (1) management personnel in the position of
making project decisions about the applicability of venting
and (2) engineers designing systems either at the conceptual
level or for construction; The fundamentals of the manual
content will be reviewed.
-------
API VENTING STUDIES
Item 1
Laboratory Scale Gasoline Spill and Venting, Interim Report
Texas Research Institute, October 1980 -Available?-
Item 2
Final Report: API Venting Study
Texas Research Institute, November 1980 -Available?-
Item 3
Forced Venting to Remove Gasoline Vapor from a Large-Scale Model
Aquifer, API Publ. No. 4431
Texas Research Institute, January 1984
{Thorton, J.S., R.E. Montgomery, T. Voynick, and W.L. Wootan.
1984. Removal of gasoline vapor from aquifers by forced venting.
p. 279-285. In Proc. 1984 Hazardous Material Spills Conference,
Nashville, TN. 9-12 Apr. 1984.) {Thorton, J.S. and W.L. Wootan.
1982. Venting for the removal of hydrocarbon vapors from gasoline
contaminated soil. J. Environ. Sci. Health A17:31-44.)
Item 4
Subsurface Venting of Hydrocarbon Vapors from an Underground Aquifer,
API Publ. No. 4410
Riedel Environmental Services Co. and Radian Corp., September 1985
Item 5
The Effects of Multiple Vapor Recovery Wells During Subsurface Venting
of Hydrocarbon Vapors, Draft Report
Riedel Environmental Services Co. and Radian Corp., June 1989 (2nd
Draft, March 1987; 1st Draft, March 1986)
Item 6
Design, Installation, Operation, and Evaluation Guidance for
Subsurface Venting, Draft Report
Radian Corp., May 1989 (1st Draft, July 1987) -
Field Evaluation of Soil Venting, In Progress
Harding Lawson Assoc. , Proposal, April 1988
Reports fron API Publications: (202) 682-8375
Items 1 & 2 mqy be available
Items 364 currently available
Items 5 & 6 to be published in 1989
-------
RESEARCH
Laboratory scale Gasoline Spill and Venting, interim Report
Texas Research Institute, October 1980
Final Report: API Venting Study
Texas Research Institute, November 1980
Prime Objective
Quantify mass balance hydrocarbon losses from known volume gasoline
spill in sand column, measure gasoline vapor diffusion coefficient for
upward migration of vapors in sand
Scope of Work and Results
Sand-packed aluminum column (4 in X 80 in) equipped with syringe vapor
sampling ports every 12 in, column core sampling ports every 4 in;
established static water table with known volume gasoline spill;
measured vapor flux at surface;and upward vapor diffusion coefficient
Results - Mass balance: liquid recovery + residual hydrocarbon in
column + volatile losses = 62%;of known volume spilled, remaining 38%
assigned to microbial biodegradation; estimated gasoline carbon
consumption and CO2 generated as a result of bioconversion
Diffusion coefficient: 0.08 cm2/s in 0.04 cm/s sand pack with a 0.28
porosity
Conclusions - venting should remove gasoline vapors effectively and
significantly enhance hydrocarbon microbial degradation by increasing
the oxygen supply needed for the conversion; vapor diffusion
characteristics were used to design meaningful venting experiments;
recommended additional column study to characterize vapor diffusion
parameters for ranges of permeabilities and temperatures to make
results more generally applicable
-------
RESEARCH
Forced Venting to Remove Gasoline Vapor from a Large-Scale Model
Aquifer, API Publ. No. 4431
Texas Research institute, January 1984
Prime objective
Quantify the efficiency of subsurface venting to control hydrocarbon
vapors in the vadose zone, pilot scale
Scope of Work and Results
Pour experiments conducted in sand-filled, insulated tanks (10 ft X 10
ft X 4 ft); flowing constant-head water table with gasoline spill:
controlled spatial layout of vacuum (vapor exhaust) wells, air inlet
wells, and soil gas monitoring probes at specific depths
Mass balance attempted: gasoline volume spilled versus hydrocarbon
removed in vapor phase by venting + in dissolved phase in water flow +
amount of gasoline biodegraded derived from C02 concentrations in
exhaust + residual hydrocarbon left in sands assessed from tank cores;
recovered amounts ranged from 50% - 84% in the four experiments
Experiments A & B: Two extraction well screen geometries contrasted,
long (sand surface to capillary zone) versus short (short screen near
capillary zone) X two flow rates
Results - Both configurations evacuated shallow soil, short screen
controlled vapors more effectively at low flow rate
Experiments C & D: Two textures of sand (2 permeabilities) X three
flow rates; extraction well screens in both sands were long geometry
but varied in length due to varying heights of capillary fringe in the
two sands
Results - More hydrocarbon removal by venting in higher permeability
sand but results confounded by varying well screen lengths (shorter
screen in .':. •' permeability sand pack), greater dissolved hydrocarbon
removal in liner textured sand pack
-------
RESEARCH
Subsurface Venting of Hydrocarbon Vapors from an Underground Aquifer,
API Publ. NO. 4410
Riedel Environmental Services Co. and Radian Corp., September 1985
Obi ecti
In field scale, quantify the effectiveness of subsurface venting to
control hydrocarbon vapors in the vadose zone and the potential of
venting as a means of removing spilled hydrocarbons from the
subsurface
Scope of Work and Results
Two field plots each with single venting well and two' air inlet wells
spaced 20 ft and 40 ft from venting well; wells had short, 4 ft
screens above water table (Experiment B configuration from pilot
studies); each plot had 16 soil vapor monitor probes for gas sampling
using syringes and vacuum monitoring using roagnehelic gauges; venting
well and vacuum system flow rates monitored with inline Pi tot tube,
with hot wire anemometer in air inlet wells; studied three flow rates
each of 15-day venting duration; formation texture of eand to fine
sand, approximately 1.5 g/cnr bulk density and 10"3 cm/s water
permeability; plots covered with plastic membrane
Results - Analyses of system effluent vapors: daily liquid recovery
rate by venting in high permeability plot, 4.2 gpd 6 22.6 scfm and 5.9
gpd e 39.8 scfm, and in the low permeability plot, 3.1 gpd @ 18.5 scfm
Soil monitor probe measurements: soil vapors concentrated near
capillary fringe and decline toward the surface; vapors rapidly
depleted by venting (1-2 days) versus slow reestablishment after
venting (weeks); venting influence and vapor reduction distinguishable
at vacuum as small as -0.1 in H20; air inlet wells induced linear flow
between inlet and venting wells, however, inlet well flow comprised
only 10% of total flow drawn by venting well; membrane appeared to
have no influence on soil vacuum distribution or vapor reduction;
vacuum distribution to distances ranging from 30 to 50 ft from venting
wells, no vacuum influence beyond air inlet wells; with air inlet
wells capped, vacuum distribution became concentric around venting
well to a distance of 110 ft
Conclusions - Venting is effective as a recovery technique; future
study should focus on venting well configuration and system operation
that maximizes collection of concentrated vapor from the capillary
fringe zone to optimize recovery
-------
RESEARCH
The Effects of Multiple Vapor Recovery Wells During Subsurface Venting
of Hydrocarbon Vapors, Draft Report
Riedel Environmental Services Co. and Radian Corp., June 1989 (2nd
Draft, March 1987; 1st.Draft, March 1986)
Prime Objective
ri*
Quantify the efficiency of subsurface venting to control vapors in the
vadose zone and recover hydrocarbon in a multiple venting well system;
quantify the interactions of multiple venting wells at different
spacings
Scope of Work and Results
Utilized same site as single well study; three venting wells connected
to common system manifold; 53 soil vapor probes at discrete depths for
gas sampling using syringes and vacuum monitoring using magnehelic
gauges; venting wells and system flow rates monitored with inline
Pitot tube; two tests run with.all 3 wells, first at 5 scfm/well then
at 10 scfm/well, to assess minimum pumping rate per well to recovery
maximum levels of hydrocarbon in system effluent; soil vapor
reduction trends and influence of multiple wells evaluated from soil <
gas analyses; three tests with only 2 wells at 100 ft spacing, at 5
scfm/well, then 10 scfm/well, then 20 scfm/well to map vacuum
distribution from soil probe vacuum measurements; test of one well at
10 scfm to map single well radius of vacuum influence at 10 scfm/well
Results - System effluent vapor analyses: liquid recoveries of 6.1 gpd
for 3 wells € 5 scfm/well (system % 14.2 scfm), 6.7 gpd for 3 wells @
10 scfm/well (system § 27.9 scfm), 2.0 gpd for 2 wells § 5 scfm/well
(system § 10.6 scfro), 3.2 gpd for 2 wells @ 10 scfra/well (system £
16.3 scfm), 7.2 gpd for 2 wells § 20 scfia/well (system @ 36.0 scfro),
and 1.9 gpd for 1 well @ 10 scfm/well (system @ 9.2 scfm); generally
greater recovery with multi-well system flow rate than by comparable
single well rate in previous study
Soil monitor probe measurements: 1 well 6 10 scfm induced soil vacuum
of 100 ft radius; 2 wells with both § either 10 scfm/well or 20
scfm/well induced soil vacuum to 200 ft from venting welle; areal
contours of multiple well soil: vacuum distribution formed by
overlapping radii of single well contributions; some soil vapor probe
concentrations near the capillary fringe remained high in areas of
venting overlap >
Conclusions - More efficient hydrocarbon recoveries achieved with
multiple wells at low flow rates per well than with a single well
operated at a high flow rate comparable to the multi-well system flow;
high concentrations near capillary fringe in overlap area evidence '
that venting well flow rates were small enough to match volatile
replenishment in the fringe zone for efficient, high concentration
steady state vapor recovery by 'the multiple well system
-------
RESEARCH
Field Evaluation of Soil anting, in Progress
Harding Lawson Assoc., Proposal, April 1988
Prime Objectives
Scientifically document two case studies that provide indisputable
evidence of petroleum hydrocarbon reduction in the vadose zone as
achieved by soil venting
INCLUDES a measure of residual hydrocarbon and water leachable
hydrocarbon from contaminated vadose zone soil before and after
venting
Identify the critical soil venting design parameters that affect
hydrocarbon removal and establish a basis for soil venting design
optimization that can be applied to future soil venting programs
INCLUDES identification and evaluation of technology to achieve
acceptable emissions from the venting system
Scope of Work
Two case study sites, one coarse-grained, one fine-grained, with free
product removal completed
Install vapor extraction wells, instrument for monitoring vapor flow
rates, hydrocarbon concentration, vacuum, vapor temperature?
similarly, monitor venting system effluent and treated off-gas
Install soil vapor monitor wells to assess vacuum propagation; water
leach boring cores in laboratory to measure extractable residual
hydrocarbon
Vent until effluent hydrocarbon reaches asymptotic level (2-3 mos);
collect additional core samples from same locations and repeat leach
studies
Attempt mass balance evaluation using collected data; discuss quality
assurance and control; provide method used to determine the number and
placement of extraction wells and discuss its adequacy
-------
MANUAL
Design, Installation, Operation, and Evaluation Guidance for
Subsurface Venting, Draft Report
Radian Corp., May 1989 (1st Draft, July 1987)
Prime Objective
Summarize subsurface venting principles and experience in a manual
form as a tool for decision making and system design
Manual Outline
Executive Summary
1. introduction
2. Basic Principles of Subsurface venting APPENDIX B
Subsurface Gas Movement Physics of
Natural Factors Subsurface Venting
Induced Flow
Important Soil Factors
Soil Porosity and Permeability
Water Content
3. Types of Venting Systems APPENDIX C
Vacuum Systems Venting
Pressure Systems System Types
Passive Systems
Systems with Air Inlet Wells
Advantages and Disadvantages of Systems
4. System Design, Installation, and Operations APPENDIX D
Site Assessment Venting System
Site Characterization Installations
Establishing Area of Contamination
Hazard Considerations
Regulation and Permitting
Preliminary Design Investigation
System Design and installation
Hell Placement
Pumps and Piping
System Emissions
Operations
Vacuum Systems
Pressure Systems
Passive Systems
Operating Mode Options
Venting Duration
5. Monitoring and Evaluation APPENDIX E
Subsurface site conditions Monitoring
Soil Vapor Distribution ( Methods
Static Pressure Distribution
System Monitoring APPENDIX P
Monitoring Parameters Case Studies
Recovery Estimate
Emission Monitoring APPENDIX A
6. Cited Literature Glossary
-------
Sandra L. Houston.' David K. Kreamer,l and Randolph Marwigl
A Batch-Type Testing Method for Determination of
Adsorption of Gaseous Compounds on Partially
Saturated Soils
Authorized Reprint 1989 from Journal of Testing and Evaluation, March 1389
Copyright American Society tor Testing and Materials, 1916 Race Street. Philadelphia, PA 19103
REFERENCE! Houston, S. L., Kreamer, D. K., and Marwig, R., -A
Batcb-Tvpt Teiting Method (or Determination of Adsorption of CM-
•ooi Compound* on Partial!; Satunled SoUf," Gtottctinicol Testing
Journal. GTJODJ, Vol. 12, No. 1, March 1989. pp. 3*10.
ABSTRACT! As part of this Etudy, a laboratory batch-type testing
method has been developed for determination of the adsorptrvc charac-
teristics and equilibrium adsorption coefficients for gaseous chemical
specie* on partially saturated soils. The testing procedure was originally
developed in support of in-situ tests at radioactive waste disposal cites in
which relatively inert tracer gases are injected into the soil« a means of
characterizing and monitoring the diffusive migration of gaseous spe-
cies from * disposal site. The adsorptive capacity of various toils for the
tracer gases has been determined at different water contents. Studies
show that the testing procedure is practical for the determination of ad-
torptive capacity of partially saturated soils for volatile organic pollu-
tants. Adsorption coefficients for trichtoroethylene (TCE) have also
been determined. A wide range of grain-size distribution was investi-
gated. The available adsorption data indicate that soil surface area
available for adsorption was of primary importance in the amount of
adsorption that occurred for the different soil types. The available sur-
face area for adsorption was decreased by increasing the water content
of the soil. The laboratory testing procedure provides a simple and
rapid method of assessing the adsorption coefficients, and the results
are very reproducible. The testing method can be used to determine the
relative adsorptive characterist ics of various toil types for essentially any
gaseous chemical species whose concentration can be accurately
measured.
KEYWORDS: adsorption, soil adsorption, partially saturated soil* ad-
sorption, gas adsorption, laboratory batch testing, hazardous waste
containment, volatile organic compounds
Nomenclature
CEC Cation exchange capacity
Kt. Adsorption coefficient =
/moles of pollutant adsorbed\
\ dry mass of soil /
/initial moles of pollutantN
total volume of gas /
KH Normalized adsorption coefficient = KJK.^.
volume of gas
*** dry mass of soil
NOTE: Discussion is encouraged and should be submitted by Sept. 1,
19S9.
'Assistant professors and research assistant, respectively, Department of
Civil Engineering, Arizona State University. Tempe, AZ652S7. R. Marwig
u currently at John Hallcnbccfc and Associates, Emeryville, CA.
© 1989 by the American Society tor Testing and Materials
/f»,,„ solution coefficient for water =
(moles disso!ved)/(mass water)
(initial moles)/(volume gas)
w Water content = weight of water 4- weight of solid
pd Dry density = dry mass •+• total volume
Introduction
Several options have been considered for the disposal and con-
tainment of hazardous wastes, including storage in geological for-
mations. Geological materials are typically used in conjunction
with man-made barriers to inhibit the release of contaminants into
the environment. Natural barriers, such as soils, have shown an
ability to aid in the attenuation of pollutants and to decrease the
potential environmental impact of some hazardous wastes. Often
the soil is required to art as a barrier for extremely long periods of
time, under altered chemical environments and at high tempera-
tures, such as with the disposal of radioactive wastes. Therefore, a
need exists for an extension of current knowledge of the engineer*
ing and physicochemtcal properties of soils subjected to hazardous
wastes, including their ability to retard waste movement.
An important aspect of the waste containment issue is an assess-
ment of waste migration through the geological material, via pro-
cesses such as diffusive and advective transport. In general, vapor
moves through soils by means of diffusion or advective flow, or
both. Diffusion is a change in response to a chemical concentration
gradient and advective flow is caused by a pressure gradient.
Continued spread of contamination problems has prompted a
demand for more sophisticated modeling of pollution migration.
To perform such modeling, a measure of the equilibrium adsorp-
tive capacity of the soil for the polluting compounds is required.
Historically, two types of test methods have been used to determine
the adsorptive capacity of a soil. One method employs the batch
test and the other the column test. The batch test is intended to
provide equilibrium adsorption coefficients under a controlled and
reproducible set of laboratory conditions. Batch tests are particu-
larly useful in assessing the relative adsorptive characteristics of
different soil types for a particular compound. A comparison of
batch and column testing has been made in which it was concluded
that batch tests typically result in lower inherent experimental vari-
ation, while column tests simulate field conditions much better [/],
There has not yet been a decisive conclusion reached as to which
test method produces better data.
While both batch and column methods have been the topic of
0149-6115/69'0003-0003$02.50
-------
4 GEOTECHNICAL TESTING JOURNAL
recent research, most studies have dealt with a batch test method
in which the aqueous phase of a soil-water mixture is sampled [2].
The column test has also betn used to study adsorption by satu-
rated soils [3]. Although a few studies have been reported [1,3],
there has been much less emphasis on partially saturated soils and
gaseous pollutants. To date, no standard procedure has been de-
veloped for batch tests on partially saturated soils.
This work is directed toward the development of a laboratory
testing procedure for determining the adsorptive capacity of a par-
tially saturated soil for a gaseous component. The development of
the test procedure included selection of a method of specimen
preparation. Five soils were tested, ranging from sand to clay,
using the batch-type laboratory procedure. Measurements of equi-
librium adsorption coefficients at various water contents were ob-
tained so that the effect of water content on the adsorption by the
soils could be investigated.
The gases used in this study were trichloroethylene (TCE), bro-
mochlorodifluoromethanc (BCF), and bromotrifluoromethane
(FI3B1 or Freon 13B1). Two of the three test gases selected for this
study, BCF and F13B1, were studied because of their use for m-
titu gaseous tracer diffusion tests to determine the diffusion-domi-
nated flow characteristics of volatile contaminants through par-
tially saturated toils [4\. Other gases could be tested, providing the
appropriate analytical chemistry technique is employed in mea-
surement of the compounds of interest.
The laboratory testing program has been designed as a method
of evaluating the adsorptive properties of soils in a controlled, re-
producible manner. The batch gaseous adsorption technique is rel-
atively simple and quick. The test data were used to determine the
amount of adsorption for a given chemical species on a given mass
of soil for a fixed time of exposure. Equilibration was reached in all
tests presented in this paper.
Tett Procedure
A schematic of the equipment used in the adsorption tests is
shown in Fig. 1. The test gas is injected into an evacuated soil con-
tainer, and samples of gas in the soil void space are withdrawn for
analysis. The experimental procedure for obtaining adsorption co-
efficients involves the testing of gaseous samples using a gas chro-
matograph. The gas samples in this study were directly injected
into a Perktn-Elmer Sigma 300 Gas Chromatograph, equipped
with a Ni-63 electron capture detector and having a 3 m length,
3.2-mm-dUmeter column of 10% SP-2100 on a 60-80 mesh Su-
pelcoport. Although direct injection was used for this study, the
procedure could be modified to allow syringe injection techniques
to be used. Likewise, other detectors, columns, or capillary
columns could be used for testing gaseous compounds.
The primary soil test container used in this study was fabricated
entirely of 304L stainless steel. The container had inside dimen-
sions of 71 mm height and 44 mm diameter. A schematic of a typi-
cal soil test container is shown in Fig. 2. The top cap and base
surfaces were machined so that they were very smooth and planar
where they mated together, and the seal was created by the com-
pression provided by the eight bolts through the flange. The only
welded joints were at the outside of the injection and withdrawal
ports. Another container used in this study was also fabricated en-
tirely of 304L stainless steel but had a copper gasket seal.
The container that performed best in regard to adsorption mea-
surements was that made entirety of the 304L stainless steel, with-
out the copper gasket, because it adsorbed the least when tested
empty with the gases used in this study. It is important to use stain-
less steel as the soil test container material because it is relatively
inert and does not readily provide cations for exchange with the
soil. However, the stainless to stainless seal between the top cap
and base surfaces is more difficult to obtain than the copper gasket
seal.
For the test results reported in this paper, only minor differences
in adsorption coefficients were obtained between tests performed
with the two different scaling surfaces. However, each set of soil/
gas mixtures should be evaluated separately if deviation from the
purely stainless steel container is made.
The adsorption of the containers, and other inline materials,
such as the filter, were measured separately, without the soil. This
adsorption was generally quite small (at least an order of magni-
tude less than the soil adsorption). Stainless steel tubing and valves
were used throughout the apparatus shown in Fig. 1. The reported
adsorption values for the soil were corrected for system adsorption.
In the cases where the copper gasket seal was used, a bench mark
test with the pure stainless container was performed as a check.
The air-dried soil samples were passed through a No. 40 (425-
pm) sieve, and then compacted into the soil testing containers
using the following procedure:
1. The dry density was selected and held constant at approxi-
mately 1.7 g/cnV for all tests.
2. A batch of air-dried soil was weighed and brought to the de-
sired water content by adding the required water and mixing the
ttlTHOOEN
TROOEh CTL*eeR
SEGUL4TOK
US O*OMATOffl»APM
SOIL TESTING SAMPLE LOOP
CONTA9O
TEST
-------
HOUSTON tT AL. ON A BATCH-TYPE TESTING METHOD 5
soil and water thoroughly. Approximately 0.2% water content was
allowed for evaporation.
3. The total moist mass required for the given dry density and
water content was calculated from the known dimensions of the
soil testing container used in the test.
A. The soil testing containers and a compaction collar were
weighed, and the weight was recorded.
5. The toil was compacted into the containers in four layers.
The moist mass for each layer was calculated by dividing the total
moist mass by four. A compaction collar was used to allow com-
paction of soil to a height slightly greater than the container
height.
6. The moist soil for each layer was spread evenly within the
container, and a 9.5-mm diameter rod was used to density the soil
by tamping.
7. The final tamping for the layer was accomplished using a
tamper whose diameter is approximately 90% that of the con-
tainer. Compaction continued until the height of the soil layer was
approximately one-fourth of the total height of the container.
8. The procedure was continued until all soil layers were com-
pacted; if any errors were suspected, the container and the soil al-
ready compacted could be weighed at any intermediate point to
insure the proper mass of soil had been used.
9. The total height of all four layers was approximately 4 mm
higher than the height of the soil testing container. This allowed
for trimming the soil flush with the top of the soil testing container.
These trimmings were then used to check the water content of the
specimen.
10. After the specimen was trimmed, filter paper was placed
over of the gas extraction port of the soil container so that the port
did not become clogged. The soil and container were then weighed
to insure the proper density had been achieved. The container was
then sealed and another filter attached to the outside of the con-
tainer to further insure no soil panicles were drawn into the sample
loop. The adsorption of the filter paper was measured separately
and found to be negligible.
In order to calibrate the detector, before the start of each experi-
ment the test gas was injected directly into the gas chromatograph,
bypassing the soil test container. The standards used in this study
were typically low concentration test gases (tracer or TCE) with the
balance of the gas mixture being nitrogen.
The procedure for injection of the test gas into the soil container
is outlined below. The experiments were performed at room tem-
perature in a temperature controlled laboratory.
1. The soil container was evacuated using a vacuum of 676 mm
of mercury, with Valves B and D open and Valves A and C closed
(Fig. 1).
2. Following the evacuation of the soil container. Valves B and
D were closed, and Valve A was opened. This allowed the soil con-
tainer to be filled with the test gas, which was at a known concen-
tration, temperature, and pressure (typically 103.5 kPa gage). The
line up to Valve A had been filled previously with the test gas dur-
ing the direct injection performed before each experiment.
3. After the pressure equilibrated in the test container, Valve A
was closed. For typical air permeabilities at saturation levels less
than about 70%, pressure equilibration would occur in a very short
period of time for a wide range of soil types, including clayey soils
15.6].
The total time between the closure of Valve B, after evacuation had
been completed, and the closure of Valve A, after the test gas filled
the soil testing container, was typically only a few seconds. Once
Valve A was closed, the pressure regulator on the test gas cylinder
was shut off for safety reasons.
4. Before analyzing the soil gas sample, the sample loop was
flushed with ultra high purity nitrogen.
5. To inject the soil gas sample into the gas chromatograph.
Valve B was opened, filling the gas chromatograph sample loop
with the nonadsorbcd gaseous phase from the soil specimen. This
gas sample, at known temperature, pressure, and volume, was.
then directly injected into the gas chromatograph for determina-
tion Of the concentration of the test gas in the voids of the soil
specimen.
6. After the analysis from the gas chromatograph output was
completed, Valve B was closed, and the sample loop is flushed with
ultra high purity nitrogen.
7. Steps 5 and 6 were often repeated at a later time to obtain
another sample to insure that the gas had reached an equilibrium
with the soil.
For some of the test results reported herein, the gas sample from
the soil testing container was injected into the gas chromatograph
at various times throughout the test in order to record the equili-
bration progress of gas adsorption onto the soil. Typical times of
injections of gas samples were 0.5, 10, 60, 300. and 720 min from
the start of the test. Other tests were conducted in which only two
samples were pulled, one after about 1 min. and another after the
predetermined equilibration time. The equilibration time allowed
was typically 720 min. However, for clayey'soils and silts at very
high water content, which exhibited slightly longer equilibration
times, 1440-min tests were performed. For these particular tests
the final (equilibrium) adsorption coefficients were not signifi-
cantly sensitive to the number of samples taken or to pressure
changes within the soil test container. The pressure drop observed
when a sample was pulled was about 3.5 kPa, and the number of
moles adsorbed for similar specimens at the predetermined equili-
bration time was the same (within 5%) whether one or four pre-
vious samples) had been taken. '
Description of SolU
Five soils were tested to determine their relative adsorptive char-
acteristics. The soils tested included a clean quartz sand, three
silts, and a clay. Water contents ranged from air-dried to about
20%. Atterberg limit data for each soil are given in Table 1. Gra-
dation analyses, including hydrometer data and Unified Soil Clas-
sification Symbol for each soil are summarized in Table 2. The first
three are sitty sands, and the fourth is a siti of high compressibility.
However, the original designations, based on visual classification,
were retained for consistency with previous reports on these soils.
TABLE 1—Summary of important peromtltrs for tttttd SOili.
Soil Identification
Soil Parameter
Silt 1 Silt 11 Sill III
Cay
Sand
Liquid limit, %
Plastic limit, %
Plasticity ind«, %
46
29
17
SJ
37
IS
62
38
24
92(89)
56(52)
36(37)
NOTE: Values in parenthesis arc results from Itsts conducted after oven
drying.
-------
6 GEOTECHNICALTESTING JOURNAL
TABLE 2—Grain lite analyiet.
Finer By Weigh)
Sieve Sizes
Silt] Sill II Sill 111 Clay Sand
No. 40 (425 tan)
No. 100 U 50pm)
No. 200 (75pm)
...(tOiiffl)
Unified foil
classification symbol
100
43
28
14
SM
100
61
36
19
SM
100
57
3d
17
SM
100
B6
70
52
MH
100
24
4
•m • i
SP
These five soils represent a wide range in soil gradation, allowing
for the study of the effect of particle surface area on the adsorptive
characteristics of the soils. The clay has a very low organic content,
as indicated by the similar liquid limits before and after oven
drying.
Normally, clayey soils have a higher organic content than silts or
sands, and this would be expected to increase the adsorption for
clayey soils. Given that the organic content for the test soils are
low, organic content is not likely to dominate the adsorptive mech-
anism. However, to whatever extent the low organic content affects
the adsorption of the clayey soils, it will be lumped together, with
other adsorption mechanisms such as the available surface area of
the clay. Thus, as in common engineering practice, the "effective"
adsorption of the soil will DC investigated, and the primary contrib-
utors to the adsorptive mechanism will be identified, as possible,
from this lumped parameter. It is, in fan, the "effective" behavior
that is most relevant to field performance.
The mineralogies! content of the soils was also obtained. The
X-ray diffraction data for the test soils have been summarized in
Table 3, along with the cation-exchange capacity for each soil type.
The range of "acceptable" values for the various index param-
eter reported in Tables I and 3 is quite large, because the range
reported even for pure clay minerals shows significant variation.
However, the Atterberg limit data and the cation-exchange capaci-
ties obtained for the test soils were not entirely consistent in that
•TABLE 3—X-ray diffraction and cation eschangt capacity data.
Soil
smi
smii
Silt III
Cla,
Minerals
Present
quarts
feldspar
illhe
kaolinhe
quartz
feldspar
kaolinhe
Ulite
quartz
feldspar
kaolioite
Ulite
quartz
feldspar
montmorillonite
CECon
No. 100 Material.
mco/lOOg
23
10
7
35
Sand
DO X-ray data available;
observation indicates
mostly quartz
Silt HI. with the highest PI for the "silts," exhibited a lower cation-
exchange capacity than Silt I. The Atterberg limit data are likely
the more reliable of the index parameters reported because these
numbers were double checked by the authors, and very little differ-
ence in the two tests were observed. The cation-exchange capacities
for the clay and Silt HI were obtained from tests conducted by the
authors, whereas that cation-exchange capacities for Silt I and Silt
II were provided by other investigators.
Percentages of the various clay minerals for the clay-sized frac-
tion of the soils were estimated from the Atterberg limit, X-ray dif-
fraction, grain-size, and cation-exchange data, and are given in
Table 4. These estimates are obtained using the following proce-
dure. First, each mineral type present is identified from the X-ray
diffraction analyses. The percent by weight of each mineral type is
estimated from the gradation analyses and available index tests.
Using typical values of Atterberg limits, CECs, and specific gravi-
ties for each mineral type, and taking a weighted average of the
properties (based on estimated percent by weight), these same
quantities are computed for the total soil specimen. The values
computed from the estimated percent by weight are then compared
to the measured values for the total soil. Iterations are performed
as necessary to obtain as close a match as possible between com>
puted and measured parameters.
Equilibration Tlmea
Several long-term tests were performed that indicated that the
tracer gases and TCE always came to equilibrium with the soils
within 1000 min from the start of the test.
A typical plot of molar concentration of F13B1 in the gaseous
phase versus time for two different water contents is shown in Figs.
3 and 4 for Silt I and clay. The equilibration time for air-dried Silt I
soil was approximately 60 min. There was a trend of increasing
time to equilibration with increasing water content. However, at
the highest water content considered in this study, 20%, the equili-
bration time was still only about 240 min for the silts. Similar
trends were noticed for all gases with the five test soils. The room-
temperature test on the clay at 20% water content, shown in Fig. 4,
required the longest time for equilibration, about 1000 min. There-
fore, the gaseous adsorption tests were typically run for about 720
min for the silt and sand specimens, so that steady state values of
the adsorption coefficient were determined, the clay specimens
were run for a 1440-min period.
Equilibration times, as expected, vary for different soil types,
coil gradation, and chemical species being adsorbed. Therefore, H
is recommended that equilibration times be determined for each
specific case. In some cases, equilibration times might be ex-
tremely large, so that it would not be practical to run the batch
tesU to the steady state condition.
TABLE 4—Probable % ftay minerals for the clay fraction of At tat toils.'
Test Soil
Clay Mineral
Silt I
Silt II
Silt III
CUj
Kaoliniie
lithe
Montmorillontte
31
69
...
95
5
S3
47
...
92
8
•Based on X-ray diffraction, CEC, and Attcrbcrg limit data.
-------
HOUSTON ET AL ON A BATCH-TYPE TESTING METHOD 7
FIBBI EQUILIBRATION TIME
« W-20V SILT 1
D AIR DRIED. SILT I
1O
ao
S >.o
IT
1"
0
10 100 1000
TIME, (min.)
FIG. 3—F13B1 equilibration lime for Sill I,
FI3B1 EQUILIBRATION TIME
* W-20%, CLAY
O AIR DRIED. CLAY
10000
I 10 100 1000 , IOOOO
TIME (min.)
PIG. 4—FI3B1 tquilibrolion timtfor clay.
Reiulti of Adsorption Tett on Solb
The adsorptive characteristics of a soil, for given gas, are repre-
sented by the adsorption coefficient K*. The parameter JfA is de-
fined as the moles of the gas of interest adsorbed on the solid mate-
rial per unit dry mass of solid, divided by the initial number of
motes of the tracer of interest in the gaseous phase per unit volume
of void gas. The soil's adsorption coefficient JfA is typically given in
units of centimetres cubed per gram (cmVg).
The computation of /f A proceeds as follows; (1) The initial num-
ber of moles of the test gas in the sample loop is determined from a
volume and temperature adjustment to the standard concentration
introduced before each test. This result is used to calculate the ini-
tial concentration of the gas supplied to the soil specimen.,(2) The
final concentration of the test gas in the gaseous phase of the soil
mass is likewise determined, assuming equilibration throughout
the container. The total volume of gas is calculated from the
known final soil water content, soil sample void volume, and con-
tainer and tubing volumes. The total volume of gas includes the
pore volume, as well as a small tubing/air space volume (approxi-
mately 0.18 cm1). Typical pore volumes ranged from about 8 to 20
cm3. The tubing/air space volume was kept as small as possible by
using 1.6-mm outside diameter (OD) Tubing, so that the total vol-
ume of gas matched as closely as possible the pore volume of the
soil. (3) From the final and initial concentration of test gas in the
void space of the soil specimen, the change in number of moles of
gas is computed, which is the number of moles adsorbed by the soil
(after minor corrections for container and tubing adsorption).
(4) KA is calculated by
/ # moles adsorbed \ / initial # moles of gas \
\ dry mass of soil / \ total volume of gas )
As shown by the definition of K*. above, the amount of adsorp-
tion is a function of the initial concentration of the gaseous pollu-
tant. It is likewise affected by changes in pressure in the pore
space. For these particular experiments, the leakage from the con-
tainers was sufficiently small (about 6.9 kPa compared to approxi-
mately 207.0 kPa total), and the samples taken for testing were of
sufficiently small volume, that sensitivity of adsorptive characteris-
tics to concentration changes that occurred during the test because
of withdrawal of samples were not significant. The number of
moles of a species available for adsorption was carefully tracked
and accounted for in the adsorptive coefficients reported herein.
Interpretation of the test data is facilitated by the introduction of
a normalized adsorption coefficient KH
where
If —
*ln»
'initial it moles of test gas\ ^ /initial # moles of test gas'
dry mass of soil / V total volume of gas
_ total volume of gas
dry mass of soil
The normalized adsorption coefficient KH is a measure of the per-
centage of the available compound that is actually adsorbed. For
example, when KH is unity, 100% of the moles of test gas provided
to the soil were adsorbed.
Values for the water solution coefficient K,tm were also deter-
mined as a part of this study. Measured sorption of the gases by
water was eitremely low in comparison to soil adsorption.
The K,m coefficients were obtained by injecting the test gas (at
103.5 kPa gage) into a evacuated stainless Stctl container, with
one-half of the container volume filled with water. The water /test
gas mixture was shaken for 15 to 30 min to obtain equilibrium val-
ues of A" .„„, Values of KmHtt were between 0.002 and 0.005 cmVg
for the BCF and F13B1 gases. The TOE value of ATw,ln was also
small. 0.014 cmVg.
It is reasonable to assume that gas is dissolved into the water,
and therefore the number of moles "tied-up" by the water is
strongly related to the mass (or volume) of water placed in contact
with the gas. The gas can diffuse into the inner portions of an ele-
ment of water with relative ease, often first being adsorbed on the
surface of the water.
By contrast, the adsorption of gas onto solid soil particles would
be expected to be related strongly to available surface area because
-------
8 GEOTECMNICAL TESTING JOURNAL
after the gas is adsorbed onto the surfaces it cannot readily diffuse
to the inner pontons of the coil particles.
Effect of Water Content
The values of the adsorption coefficient A"A and normalized ad-
torption coefficients K* for all tests are given in Table 5. All soils
were tested at water contents ranging from air-dried (1 to 2%) to
about 20%. The relationship between water content and /TA is
shown in Fig. 5 for the test gas TCE and Silt 111. Figure 6 is a
similar plot for BCF and the clay. The trend of decreasing KA with
increasing water content observed in Figs. 5 and 6 is typical for the
data presented in Table S.
The decrease in A\ with increasing water content is believed to
arise because the soil particle surface area available for adsorption
is significantly reduced at the higher water contents. Many of the
cites, which would otherwise be available for adsorption, are cov-
ered up by the pore water. The values of /(„,„ obtained as a part of
this study were very low, 0.002 to 0.014 cm]/g for the test gases.
The fact that water is essentially nonsorptive for the test gases used
in this study is consistent with the trend of decreased soil adsorp-
tion with increased water content.
For a given soil, the higher the water content, the less adsorptive
the soil will be, provided K.tnr is small relative to the soil/gas/
water adsorption value JfA. For a given initial concentration, the
magnitude of X* was observed to decrease by as much as a factor
of 25 from the air-dried condition to a water content of 20%, Of
course, the magnitude of the reduction in A"A is also a function of
the initial concentration of the test gas.
The trend of decreasing KA with increasing water content ob-
served from this set of data indicates that the adsorptive character-
istics of a toil are a strong function of the surface area available for
adsorption.
Effect of Surface Am
With the data provided in Table 5, it is possible to compute the
corresponding values of initial and final number of moles per unit
volume of void space, provided the specific gravity of the solids is
measured or estimated. For example, the final concentration of
F13B1 for air-dried conditions, after equilibrium, was 5.6 X I0~"
moles/L for the sand, 6.1 to 8.8 X 10~4 moles/cm* for Silts 1, II.
and HI, and 2.3 X 1Q-'1 moles/L for the clay. In each case, the
initial concentration was the same. The differences in the final con-
centration reflect the different adsorptive capacities of the materi-
als. As will be discussed in this section, these differences are re-
lated to the surface area available for adsorption.
As given in Table 3, the minerals that were encountered in the
five test soils were quartz, feldspar, kaolinite, illite, and mom-
morillonite. The specific surface areas, Atterberg limits, CECs,
and specific gravities for pure clay minerals are given in Table 6.
Although the differences in mineralogy alone might be expected
to account for differences in adsorptive characteristics of the test
soils, the clay minerals are essentially all aluminosilicates and do
not differ tremendously in composition. However, the specific sur-
face areas for these clay minerals may differ by more than a factor
of SO.
The five soils studied as a part of this research exhibited differ-
ent degrees of adsorpttvity. which may be explained by the fact that
each soil had different gradations, different amounts of a given
clay mineral, and therefore, different surface areas. The adsorp-
TABLE 5—Summary of adsorption coefficients.
Test G«-
F13B1
F13BI
F13B1
F13B1
F13B1
BCF
BCF
BCF
BCF
BCF
TCE
TCE
TCE
TCE
Soil* Tett *: %
Silt 1 1.7
5.0
10.0
1S.O
18.7
Silt II 1.4
4.9
9.9
15.0
16.7
Silt 111 2.0
S.O
10.0
15.0
19.9
d»y 2.2
4.7
9.0
18.0
sand 1.1
4.9
9,7
1S.O
19.5
clay 2.2
4.3
9.0
17.9
sand I.I
4.6
10.0
1S.1
20.1
Siltl 1.7
4.9
10.0
14.9
16.7
Silt 11 1.4
S.O
1 0.0
15.0
16.9
Silt III 2.0
S.O
10.0
15.0
20.0
clay 2.2
5.4
10.0
20.2
Siltl 1.7
5.0
9.6
11.4
14.7
18.0
Silt I) data
Silt 111 2.0
S.O
9.9
14.8
19.9
Average
K,. cm'/g-
0.100
0.057
0.043
0.017
0.004
0.101
0.069
0.040
0.017
0.007
0.153
0.116
0.070
0.035
0.010
0.184
0.137
0.091
0.012
0.026
0.021
0.014
0.006
0.001
0.192
0.149
0.106
0.018
0.026
0.049
0.017
0.008
0.013
0.082
0.060
0.031
0.013
0.006
0.084
0.065
0.037
0.016
0.007
0.111
0.081
0.045
0.031
0.005
0.297
0.269
- 0.177
0.138
0.275
0.164
0.159
0.167
0.146
0.133
not available
0.320
0.253
0.206
0.158
0.139
KH
0.52
0.51
0.45
0.38
0.33
0.48
0.50
0.42
0.33
0.29
0.68
0.67
0.56
0.47
0.36
0.98
0.95
0.90
0.89
0.07
0.08
0.03
0.06
0.01
0.99
1.00
0.99
0.99
0.1P
0.1'.
0.06
0.03
0.02
0.43
0.43
0.33
0.27
0.22
0.55
0.43
0.39
0.31
0.16
0.49
0.47
0.37
0.32
0.24
0.96
0.83
0.84
0.82
0,90
0.74
0.78
0.83
0.87
0.85
0.97
0.87
0.90
0.69
0.&'
"The initial concentration of the BCF and F13B1 was ) ppm, and the
initial concentration of ihe TCE was 100 ppb.
•All specimens were compacted to a dry density of 1.7 ±0.05 g/cmj.
'K,, values are reproducible within 7%. Data used in reporting average
values are all within this tolerance.
-------
HOUSTON ET AL ON A BATCH-TYPE TESTING METHOD 9
O4
03
02
01
00
0 5 10 IS 20
WATER CONTENT (%)
FIG. S—Adsorption coefficient versus water content Jor TCE and Sill
III.
04
0.3
§ 0.2
O.I
0.0
CLAY
BCF
0 5 10 15 20
WATER CONTENT (%)
FIG. 6—Adsorption coefficient versus water content for BCF and clay.
tion coefficients increased with increasing surface area, as can be
observed qualitatively from the data presented in Table 5. For ex-
ample, the sand adsorbed less than the clay, and the silts had ad-
sorption coefficients that were intermediate between the ctay and
sand values. Variation in surface area provides a plausible expla-
nation of the observed differences in adsorption shown in Table 5,
as discussed in the following paragraphs.
The approximate percentage of each clay mineral was deter-
mined for each test soil based on the X-ray diffraction data, CECs,
and Atterberg limits. The results were shown in Table 4. When
these data are used together with the gradation analyses and the
specific'surf ace areas given in Table 6, the possible range in sur-
face areas for the five test soils is very large. Assuming spherical
particles for the plus No. 200 (75-prn) material, the surface areas
for the five test soils vary by as much as a factor of 3000 from the
sand to the clay when specific surface areas are considered. Al-
though this is'qualitatively the right direction for explaining the
differences in observed adsorption, if specific surface area were the
explanation for the differences in adsorption, the adsorption coef-
ficients might be expected to differ by about the same factor,
3,000. However, the ratio of the Kf, values of sand and clay were
about 10 or 12. rather than 3000.
A plausible explanation is that it is not the fully expanded, de-
flocculated, surface area thai controls the adsorptive characteris-
tics of a soil, but rather the "available" surface area. Because the
toil particles comprising the compacted test specimens would exist
in clumps or stacks, especially the clay particles, the available sur-
face area for a soil would be expected to be much lower than that
which would be computed using the fully expanded surface areas
reported for the clay minerals. Thus, the range in available surface
area for the five test soils would be expected to be much smaller
than the range in the fully expanded surface area. It appears at
least reasonable that the clumping of clay particles and the reduc-
tion in available surface area associated with the aggregation of
particles could account for the differences in adsorption coeffi-
cients for the test soils.
The available surface area is extremely difficult to quantitatively
evaluate. The surface area available for adsorption depends
strongly on the degree to which aggregates or "packets" of pani-
cles have been broken apart before the adsorption process begins.
When a standard test procedure for measuring surface area, such
as BET, for example, is employed, it is unlikely that the degree of
dispersion and defiocculation of panicles that occurs during speci-
men preparation will result in the same available surface area that
would ensue for an in-situ element of naturally occurring soil.
Likewise, the available surface area of the compacted specimens
used in this study is unlikely to be matched by the preparation
method used for a standard surface area measurement procedure.
Although the trend of increased adsorption with increased sur-
face area is easily observed from the adsorption coefficients on air-
dried soils for the BCF and the F13B1, the trend is not so well es-
tablished with the TCE data. An examination of the normalized
adsorption coefficient KK for each of the soils and tests gases sheds
some light on these results.
The values of K* for each of the soils and each of the test gases
were given in .Table 5. The normalized adsorption coefficients for
the F13B1 and BCF are well below 1.0 for the sand and Silts I
through HI. However, the KH value is very close to 1.0 for these
gases on the clay. In addition, all of the normalized adsorption co-
efficients for the TCE tests are very close to unity, for all soil tests.
As discussed previously, when the normalized coefficient becomes
unity, then all of the test gas provided to the soil specimen has been
adsorbed. This is most likely to occur when the concentration levels
of the gas are low (a case that is frequent in field applications), or
when the available surface area for adsorption is very large, or
both. The concentration of the TCE used in this study was 100
ppb, as compared to 1 ppm for the BCF and F13B1. Also, the
available surface area for the clay would be expected to be larger
than for the other test soils, particularly since it contained some
montmorillontte.
When the normalized adsorption coefficient approaches unity,
the "potential" for adsorption for the soil cannot be fully mea-
sured. Therefore, any trends of increased adsorption with increas-
TABLE 6—Summary of pure clay mineral characteristics J7],
Clay
Mommorillomte
Illite
Ktolintte
Cation Exchange
Capacity,
meq/lOOg
80 to ISO
10lo40
3 to 15
Liquid
Limit
522
56
SO
PlMlic
Limit
48
24
33
Plasticity
Index
474
32
17
Activity
5
1
0.5
Specific
Surface. mVg
700 to 840
65 to 100
10 to 20
Specific
Gravity
2.8
2.76
2.64
-------
I
0 GEOTECHNICAL. TESTING JOURNAL
mg available surface area would be masked, as was the case for the
TCE test data. If the maximum potential for adsorption of a par-
Bicular gaseous compound on a sot) is to be determined, then the
Best gas concentration must be great enough so that all available
sites for adsorption become occupied, while some of the moles of
provided to the soil are not adsorbed. However, if the actual
eld performance of a particular gas/soil mixture is to be deter-
, then it is likely, for typical low concentrations of pollutants,
that KH will approach unity, as occurred for some of the tests
Reported.
Summary and Concliulou
A batch-type testing procedure for measurement of adsorption
coefficients for gaseous chemical species on partially saturated
toils has been developed and tested. Details of the test procedure
have been provided.
Adsorption coefficients for several gases, including a volatile or-
ganic pollutant, have been determined for five different soils.
Using the batch-type testing method, it was found that for a given
soil, the water content of the soil affects the adsorptive characteris-
tics. In general, for a given soil, as the water content goes up, the
amount of adsorption for a given mass of soil decreases, provided
the solubility of the test gas in water is low. This is believed to be
due largely to the decrease in the surface area of soil available for
adsorption that occurred with increasing water content.
The adsorption data indicate that available surface area for ad-
sorption is the primary contributor in determining a soil's potential
for adsorption. This was investigated through the study of adsorp-
tion coefficients obtained for five soils covering a wide range in
available surface area. As the clay content of the soils increases,
the available surface area increases, and the potential for adsorp-
tion increases. However, given that clay panicles tend to aggregate
into clumps more than granular particles, the increase in available
turface area from silt to clay is not as great as one might assume by
considering textbook values of fully expanded surface areas.
Of course the amount of adsorption that occurs is dependent on
factors other than surface area, such as the initial and final con-
centration of the gaseous pollutant, soil mineralogy, organic con-
tent, and degree of monolayer versus multilayer adsorption. How-
ever, the test results presented suggest that these other factors may
be overshadowed by the available surface area for gas adsorption.
The test procedure and apparatus described can be readily ex-
tended for use with polluting gases other than those used in this
study. However, each pollutant may react differently with the sys-
tem components, and therefore system adsorption must be evalu-
ated for each test series. Use of stainless steel, such as 304L. is
recommended wherever possible.
The trends of decreasing adsorption with increasing water con-
tent observed in this study were specific to the test gases used. Sim-
ilar trends would be expected for gaseous pollutants that are not
highly soluble in water, such as most volatile organics. If the test
gas happened to have a high affinity for water then a possibility for
an opposite or reduced effect exists. The same test procedure, how-
ever, could be used.
Acknowledgment
The authors would like to thank Reynolds Electrical and Engi-
neering Company of Las Vegas, NV, for their support of this
project.
Rcferencct
I/] Griffin. R. A,, et al. "Batch Type 24-Hour Distribution Ratio for Con-
taminant Adsorption by Soil Material," Hazardous and Industrial
Solid Waste Testing and Disposal, 6ih Volume. STP 933. American
Society for Testing and Materials. Philadelphia, 1986. pp. 390-408.
\2\ Friewl, P., et al. "Interactions of Hydrocarbons with Soils,*'Journalof
Analytical Chemistry. Vol. 319, 1984, pp. 160-164.
[3] Jackson, D., et al. "Comparison of Batch and Column Method* for
Assessing Leaehability of Hazardous Wastes," Environmental Science
and Technology. Vol. 18, No. 9, 1964, pp. 668-673.
(4\ Olson, M. C., "In Situ Gaseous Tracer Diffusion Experiments and
Predictive Modeling at the Greater Confinement Disposal Test,"
DOE/NV/1M27-13, July 1985.
151 Blip, C., "Row of Air through Soils," Journal of Soil Mechanics and
Foundation Division, ASCE. Vol. SM4. April 1971, pp. 607-624.
161 Langfelder, L., Chen, C. P., and Justice,),, "Air Permeability of Com-
pacted Cohesive Soils," Journal of Soil Mechanics and Foundations Di-
vision. ASCE. Vol. SM4, July 1968. pp. 981-1001.
(7) Mitchell, J. K., Fundamentals of Soil Behavior, John Wiley and Sons,
New York, J976.
-------
Introduction to Physiochemical Processes Influencing
Enhanced Volatization
Danny D. Reible
Department of Chemical Engineering
Louisiana State University
Baton Rouge, LA 70809
Presented at the Workshop on Soil Vacuum Extraction
RS Kerr Environmental Research Laboratory
Ada, OK
April 27, 1989
This presentation will review the basic equilibrium and rate processes
that influence the effectiveness of vacuum extraction of organic chemicals
front contaminated soils. The concept of partitioning between fluid phases
based on fugacities will be reviewed and applied. Common assumptions about
parameter values, techniques for estimation of parameters and sensitivity
of parameters to temperature will be emphasized. The BET isotherm for de-
scribing vapor sorption on soils will be discussed. The significant re-
duction in soil vapor sorption with soil water content will be summarized
with data. A conceptual model identifying key phase interfaces in the air,
water, soil and non-aqueous phase liquid system will be presented and its
implications for limiting mass transfer rates across these interfaces sum-
marized. Mass transfer resistances associated with the discontinuous res-
idual ganglia of non-aqueous phase liquid will also be identified.
-------
Introduction to Physiochemical Processes
Influencing Enhanced Volatization
by
Danny D. Reible
Department of Chemical Engineering
Louisiana State University
Baton Rouge, LA 70809
Presented at the Workshop on Soil Vacuum Extraction
RS Kerr Environmental Research Laboratory
Ada, OK
April 27,1989
-------
Objectives and Focus
Introduce fundamental concepts
Provide a common basis for subsequent presentations
Focus:
Identification of key processes
Parameters that define those processes
Interrelationships between phases
(Air, Water, Soil and NAPL)
-2-
-------
Air- Water Interface
Air
,=X *
li
C2i
Water
Equilibrium
fu = f2i (Fugacities - Corrected Pressure)
v f°=x v f°
i *1 Ll A2i h L2
f j0 = 1 atm
7
— (Henry's Law)
X2S
f° =
L4
X2i
X
T~
2S
-3-
-------
NAPL - Air Interface
Air
C.V x..
It X li
C4i
x..
4i
NAPL
Equilibrium
fu = f4i (Fugacities - Corrected Pressure)
Y=
l
f ° =
Y4
l
1 atm
= 1 (Raoult's Law)
* 1 (UNIFAC, Scatchard-Hildebrand Theory)
f°=P
r
=X4iY4PV=Hx4i
-A-
-------
NAPL - Water Interface
Water
C2iV2i
C4i
x..
4i
NAPL
Equilibrium
f2i = f4i (Fugacities - Corrected Pressure)
X2i ^2 *2 = X4i
f2°
Y4
Y4
=f°=p
f4°
= 1
(Raoult's Law)
(UNIFAC, Scatchard-Hildebrand Theory)
X2i = X2S X4i
-5-
-------
NAPL - Fluid Interfacial Transport
Fluid
C4i
x..
4t
NAPL
Transport
NA =
- Xj) = k4 (x4 - x4i) = Kj (x4 y4 Pv-
1 _ 1 H
T? -- t~ + F~
Kj kj k4
Two Film Theory Result- Partitioning dependent rates
H»l, NAPL phase controlling
H«l, Air phase controlling
Complications
Dynamic composition of NAPL
Bulk transport of mass/heat at high transport rates
"Skinning" effect
-6-
-------
NAPL - Fluid Interface
Parameters
Activity Coefficient in NAPL -
Scatchard-Hildebrand Theory
UNIFAC/UNIQUAC
Temperature dependence
3lny4_ h*
3T '
Aqueous Solubility (Inverse of y2)
Tabulated
KQW Correlations
Temperature Dependence
Follows temperature dependence of y2
Pure Component Vapor Pressure
Tabulated
Temperature Dependence
AH
+C
-7-
-------
Air- Soil Interface
Damp
Wet
o
<2% 2-4% >5%
Equilibrium
Dry - Soil sorption controlled by air-soil partitioning
BET - multilayer adsorption - "S" shaped isotherm
Wet - Soil sorption controlled by water-soil paritioning
Vaporization controlled by water-vapor partitioning
Soil => Water _» Air
Damp - Sorption from mixed phases
Soil
Water
Contaminant Vapor Pressures
Wet Soil» Damp Soil » Dry Soil
-8-
-------
* Benzene
• Chlorobenzene
A p-Dictilorobenzene
0 m-Dichlorobenzene
A 1.2,4-Trichtoroberuene
D Water (23.6 "O
"0 0.2 6.4 0.6 0.8 1.0
Relative Vapor Concentration, P/P*
Figure 1-9 Uptake of organic vapors and moisture by dry Woodbum
soil at 20 °C vs. relative vapor concentration.
40
S30
«
a
J
O
= 20
IA
I 1 I
m-Dichlorobenzene
e20«C «30»C
1.2,4-Trlchlorebenzene
020*C »30*C
0 0.2 0.4 0.6 0.8 1.0
Relative Vapor Concentration. P/P*
I
* 1-1Q Vapor uptake of m-dich!orobenzene and 1,2,4-trichloro-
benzene by dry Woodbum soil at 20 and 30 °C.
Chiou and Shoiro/
1-37
-------
1.2
1.0
0.8
0-6
0.4
O.2
High Soil Loading
2 4 6 8 10 12 14
PERCENT SOIL WATER CONTENT
16
-------
LOO-.
0.80-
m
C
Q 0.60-
L.
O
Q.
O
.1 0.40-
"o>
0.20-
0.00
Effect of Soil Water Content on
Dieldrin Vapor Pressure
/
-D 2.1 Z Water
-$•3.94% Water
1 0% Water
-X- 172 Water
D 10
20
30
40
50
60
70
80
i
90
•LJ
1
100
Dieldrin in Soil/ppm
Data from Spencer and Cliath, 1970
-------
Vapor
Phase
0
I 1 Non Polor Orgonic
OH2°
o
Adsorbed f^i I^S
""' U o U
0
nnnnrrn
0
0
Q0 0
~rrrT—nrTTrn—
UoUo a o. oL A Joy L
b) DAMP
°
0
o
0
u
o
ooo
Uoooo oooUoooooooo
e) WET
FIGURE I. ILLUSTRATION OF VOC ADSORPTION
WITH THREE MOISTURE REGIMES
-------
Air- Soil Interface
Dry Damp Wet
Transport - Analogous to aqueous phase transport
Diffusion
«, e'0/3
Advection
a
a —> Capacity term (Assuming local equilibrium)
Varies with position if non-linear isotherm
6 + 2 + 3 PS 32 (Vapor, Water & Soil)
-9-
-------
Air- Water- NAPL- Soil
Conceptual Model
Water
Water wetting soil surface (02 - 5-10%)
NAPL wetting water (64~ 5-10%)
NAPL form - discontinuous ganglia
NAPL wetting only fraction of residual water
Air filling remainder of pore spaces
Implications- Local equilibrium denied
Soil sorption from NAPL controlled by water
Equilibrium - x4 (x2S y4) p2 (^) 63 p3 K32
Rate - Dependent on partition coefficient, K^
K32 » 1, Slow sorption rate
NAPL vaporization from ganglion - 2 film resistances
NAPL side - diffusion out of ganglion
Air side - non-uniform air movement
•10-
-------
Residual NAPL Vaporization
NAPL
Transport out of NAPL
Ganglion Size
Lmax = —- (Interfacial force balanced by gravity)
D~ 1-8 times L
Sand (dp-0.3 mm), Lmax~o(5 cm), D~o(l cm)
Transport Rate
D2
Transport into Vapor Space
Slowed by flow bypassing
Correlations exist in absence of bypassing
-11-
-------
Summary of Key Factors
Vapor Density
Pure component vapor pressure
Temperature
Concentration in soil, water and NAPL phases
Soil moisture content
Soil properties (sorption)
Vapor Transport Rate
Soil homogeneity
Soil fluid conductivity
Soil moisture content
-12-
-------
The Influence of Soil Characteristics on the
Sorption of Organic Vapors
- . Simon H. Davies
NSI Technology Services Corporation
R.S. Kerr Environmental Research Laboratory
Ada, OK 74820
The sorption of organic vapors by soils vill tend to reduce the ef-
ficiency of vacuum extraction processes. A basic understanding of the
mechanism of sorption is, thus, important to the design of vacuum extraction
systems. In this presentation I will discuss the soil characteristics in-
fluencing the sorption behavior of organic vapors.
Studies on the sorption of hydrophobic (non-ionic) compounds from
vater suggest that the mechanism of sorption can be explained in terms of the
partitioning of hydrophobic organic compounds into the soil organic matter.
In vater the interaction between mineral surfaces and non-ionic compounds is
weak because of the preferential adsorption of vater by the rain- .-1 surface.
Dehydrated soils are powerful adsorbents for organic vapors. For a
dehydrated soil the distribution coefficient, K,, for the partitioning of an
organic compound between the solid and vapor phases may be four orders of mag-
nitude greater than the K, for the partitioning of the same compound between
vater and the soil. The strong sorption seen in dehydrated soils is the
result of the interactions between the organic vapor and the mineral surface.
When water is present it displaces the organic compound from the surface, as
the polar water molecule is strongly sorbed by the polar mineral surface.
Studies with chlorobenzene, a weakly polar compound, indicate that, vhile it
may be strongly sorbed onto very dry soils, in wet or moist soils the sorption
behavior of chlorobenzene is virtually the same as that seen in soil slurries.
Except in extremely arid regions, the subsurface environment more than 10-20
cm below the surface is always moist or wet. Consequently, below the top 10-
20 cm of the soil, the interactions between a weakly polar compound, such as
chlorobenzene, and the mineral components of the soil are veak.
If dry air is used for vacuum extraction, there exists the possibility
that the soil may be dried out to such an extent that the interaction between
the mineral surface and the organic vapors is possible. This vill decrease
the efficiency of the extraction process. The use of humidified air for the
extraction would resolve this problem. However, some drying of the soil is
beneficial, as it increases the permeabilty of the soil. Thus, it may be
necessary to adjust the humidity of the air used for the extraction to op-
timize the process. ;
-------
Feasibility of Using Ozone in Place of Air in
Vapor Stripping Systems
Susan J. Hasten
KSI Technology Services Corp.
RSK-ERL, Ada, Oklahoma
A modified vapor extraction system using ozone in place of air has been
proposed* Vapor extraction systems are, in some cases, Inefficient due to
the the sorption of volatile organics (VOCs) or due the low volatility of
some of the more polar, less volatile organics. It is thought that the use
of ozone would alleviate some of these mass transfer problems since the
oxidation of these organics would be achieved in-situ. Additionally, since
the VOCs would be oxidized in-situ, treatment of the effluent gases by
activated carbon or by some other means would not be required.
In order to determine the feasibility of such a treatment technique, the
oxidation of five VOCs was studied in solutions containing Aldrich humic acid
as a model of naturally occurring organic matter. Experiments were conducted
in this manner since it was believed that the natural organic matter in a
soil system would compete for most of the ozone added, thus preventing the
oxidation of the VOCs. The effects of ozone dosage and pB were also studied.
It vas found that vhile the addition of ozone did not result in
significant changes in the TOC of the humic acid, it did result in changes in
the spectral characteristics of the humic acid, especially in the 230 to 255
nm region. Although the ozone did react with the aromatic portion of the
humic acid, and the presence of humic acid promoted the rate of ozone
decomposition; significant oxidation of the VOCs occurred in solutions
containing up to 200 mg/L humic acid. The effect of pH on the extent to
which each VOC was oxidized was compound specific, with pB having a greater
effect on the oxidation of those compounds which can be easily oxidized by
ozone directly. Increasing the ozone dosage resulted in an increase in the
extent of VOC oxidation, though no simple stoichiometric relationship between
the increases in the ozone dosage and the amount of VOC which reacted could
be made.
The effect of Eustis and simulated soils on the decomposition of cis-DCE
and PCE was studied. (Simulated soils were prepared by coating alumina with
Aldrich humic acid.) In both "soils", almost (>99%) complete oxidation of
the cis-DCE occurred with up to 1.0 g of soil when the soils were treated
with 0.21 mg ozone. The application of 0.17 rag of ozone resulted in
approximately AOZ decomposition of PCE in the presence of 1.0 g of Eustis
soil. Increasing the pH resulted in an increase in the extent to which PCE
reactedf especially at the higher humic acid concentrations.
A competitive kinetic model was used to model the experimental results.
It was found that the five compounds studied reacted to a much greater extent
than one would predict based upon competitive kinetics involving only the
direct reaction. The results of the laboratory and modelling efforts support
the hypothesis that the indirect reaction involving some free radical, such
as *OH, plays a significant role in the oxidation of these compounds.
-------
Biodegradation of Hydrocarbon Vapors in the Unsaturated Zone
David W. Ostendorf
Civil Engineering Department, University of Massachusetts
Amherst, Massachusetts
Don H. Karapbell
Robert S. Kerr Environmental Research Laboratory
United States Environmental Protection Agency, Ada, Oklahoma
Short Title: Biodegradation of Hydrocarbon Vapors
-------
Biodegradation of Hydrocarbon Vapors in the Unsaturated Zone
Abstract
Ve measure and model the concentration of hydrocarbon and oxygen vapors
in the unsaturated zone above residually contaminated soil from an aviation
gasoline spill at the US Coast Guard Air Station in Traverse City, Michigan.
Our analysis proceeds in the assumed absence of advection and transience,
and accordingly is a simple balance of gaseous diffusion and biological
degradation coupled in the tvo reacting constituents. The oxygen and
hydrocarbon transport equations are combined under the assumption of con-
stant air filled porosity and diffusivity, resulting in a straight line
relation for the combined species variable regardless of the nature of the
reaction. A linear regression through the field data then yields the oxygen
and hydrocarbon concentrations at the ground surface and capillary fringe,
respectively. These boundary conditions are input to an analytical model of
i
the separate constituent profiles which incorporates nonlinear Honod
kinetics under hydrocarbon limiting conditions. We use the maximum specific
reaction rate to calibrate the resulting model vith reasonably accurate
results. Volatilization is shown to be a significant transport mechanism
for hydrocarbons at Traverse City, and biodegradation prevents the escape of
appreciable contamination to the atmosphere for most locations at this site.
Ve expect little oxygen to reach the water table due to the aerobic
biodegradation process in the unsaturated zone.
-------
Introduction
Ve measure and model the concentration of hydrocarbon and oxygen vapors
in the unsaturated zone above residually contaminated soil from an aviation
gasoline spill at the US Coast Guard Air Station in Traverse City, Michigan,
Our vork bears upon the larger problem of organic contamination of the sub-
surface environment, a phenomenon of emerging importance due to the
widespread use of organic fluids and solutions in Post Vorld War II America
[National Academy of Sciences, 1984; Vise and Farenthold, 1981].
Pesticides, herbicides, solvents, gasoline, heating oil, creosote, and
transmission fluid are typical examples, and their eventual distribution in
vaste lagoons, agricultural runoff, landfills, spills, and buried drum sites
commonly leads to subsurface pollution [Schwille, 1967; Kitunen et al.,
1987} Reinhard and Goodman, 1984; Jury et al., 1986].
Gaseous transport of the volatile components of this organic pollution
has been identified as a potentially important mechanism in mathematical,
laboratory, and field investigations of the unsaturated zone. Baehr [1987]
and Sleep and Sykes [1989] devise analytical and numerical models of
hydrocarbon and .chlorinated hydrocarbon transport in the vadose zone,
respectively. Baehr's [1987] vork is a useful balance of transience, sorp-
tion, and gaseous diffusion which highlights the influence of air/uater
partitioning on the release of vapors to the surface and subsurface environ-
ments. Sleep and Sykes [1989] include advection in their finite element
code, which features dissolution of trichloroethylene into an underlying
vater table, as veil as degassing to the ground surface. These simulations
provide sensitivity studies for various hydrocarbon transport mechanisms,
-------
but are not calibrated or tested with data. Farmer et al. [1980] and
Bruelle and Boag [1986] measure the diffusion of hexachlorobenzene and
gasoline vapors through laboratory columns, vhile Vallingford et al. [1988]
and Hlnchee and Reisinger [1985] document field contamination by hydrocarbon
fumes. Hlnchee and Reisinger [1985] analyze the head space in groundvater
monitoring veils screened above and belov the vater table, vhile Vallingford
et al. [1988] present vertical profiles of hydrocarbon vapor concentration
obtained by sampling tubes driven to various depths in the unsaturated zone.
These and other studies demonstrate the mobility, of volatile organic con-
stituents in the vadose zone, a characteristic that can be exploited by the
soil venting remediation alternative [Thornton and Vootan, 1982; Grow et
al., 1985J.
The degradation of subsurface organic contamination by microbiological
activity has also engendered & substantial and continuing literature in the
transport disciplines. Borden and Bedient [1986], Holz et al. [1986], and
Viddovson et al. [1988] all derive numerical models of dissolved organic
contaminant transport subject to biodegradation. Borden and Bedient [1986]
consider oxygen limited kinetics, vhile Holz et al. [1986] model the addi-
tional constraint of nutrient availability. Viddovson et al. [1988] include
nitrate respiration and substrate limitation in their simulation of the
process. Ve note the use of laboratory microcosms to independently verify
biological kinetic parameters in the study of a dissolved benzene plume by
I
Chiang et al. [1986]. Wilson et al. [1986] measure the biodegradation of
alkylbenzene solutions in soil from the Traverse City site under aerobic and
anaerobic conditions, vhile Kemblowski et al. [1987] observe the aerobic
-------
decay of dissolved benzene in a similar fashion. Nichols et al. [1987] and
Kampbell et al. [1987] present laboratory investigations featuring gaseous
substrate removal from unsaturated soil and Vilson and Ward [1987] assess
the feasibility of petroleum hydrocarbon spill remediation vith biological
agents. Many other studies could be cited in this emerging field of inter-
disciplinary effort; Lee et al. [1988] present a more thorough review
describing the biorestoration of organic contamination in the subsurface en-
vironment.
Ve extend this considerable theoretical and experimental literature by
deriving and field calibrating a simple model of coupled hydrocarbon and
oxygen transport in a microbiologically active vadose zone vith a shallow
vater table. Our analysis proceeds in the assumed absence of transience and
advection induced by temperature gradients, pressure gradients, or recharge.
The conservation of mass equation is rather taken as a simple balance of
gaseous diffusion and biological degradation coupled in the tvo reacting
constituents. This gaseous transport paper is part of a vider study of the
Traverse City plume, which includes mathematical models of the dissolved
[Rifai et al., 1988] and immiscible [Ostendorf et al., 1989] contamination,
along vith laboratory Investigations of sorptive characteristics [Bouchard
et al., 1989] and biodegradation potential of the dissolved plume IWilson et
al., 1986]. Field [Kampbell et al., 1989] and laboratory [Vandcgrift and
Kampbell, 1988] methods for sampling and analysis have emerged from the
Michigan project as well, and major in situ experiments are underway to
demonstrate oxygen and nitrate based degradation of the aromatic fractions
of the spill.
-------
Governing Equations and Constituent Profiles
In simplest terms, the gaseous transport of hydrocarbon vapor H and
oxygen 0 is a coupled balance of diffusion and biological degradation R
A
nD5-? «= nR . (la)
dz
vith air filled porosity n and gaseous diffusivity D taken as constant in
the unsaturated zone bound by the top of the capillary fringe at z=0 and the
ground surface at z=C as indicated by Figure 1. The reaction ratio y is
based on the stoichiometry of the following approximation of the aerobic
biodegradation process for veathered aviation gasoline
(2a)
mass oxygen
mass gasoline
Y - 3.51 (2c)
The hydrocarbon formula reflects gas chromatographic analysis of free float-
ing product in a monitoring veil (MSA) at the site area, as summarized In
Table 1. Since the microbes must occupy a water environment, we suggest
that the bacteria exist as clusters [Molz et al., 1986] enclosed within the
mass of residual moisture in the unsaturated zone. All the reaction
products are assumed to mineralize to carbon dioxide and water in equation
(2a), on the presumption of a steady state tnicrobial community vith negli-
gible sloughing of biomass.
-------
AA/7 XX
LGROUND SURFACE
VADOSE ZONE
7/7
'"CONTAMINATED
CAPILLARY FRINGE
WATER TABLE
ig. 1. Definition Sketch.
-------
Table 1. Weathered Aviation Gasoline Composition and Properties
Constituent
2,2,4 Trimethypentane
2,3,4 Trimethylpentane
2,3,3 Trimethylpentane
2,3 Dimethylpentane
2,2,5 Trimethylhexane
Toluene
2,4 Dimethylpentane
2,2,3,4 Tetramethylpentane
2,3 Dime thy Ihexane
2,3 Dimethylbutane
2,5 Dimethylhexane
2,3,5 Trimethylhexane
2,2,5,5 Tetrame thy Ihexane
Remainder (Assumed)
Totals
Mass
Fraction
0.204
0.141
0.134
0.123
0.087
0.047
0.039
0.034
0.030
0.027
0.023
0.010
0.006
0.095
1.000
Free product from monitoring well
12 deg C vapor concentration data
Molecular
Veight
kg/mole
0.114
0.114
0.114
0.100
0.128
0.092
0.100
0.128
0.114
0.086
0.114
0.128
0.142
0.114
0.111
H54.
from Reid et
Mole
Fraction
0.199
0.137
0.130
0.137
0.075
0.057
0.043
0.029
0.029
0.035
0.022
0.009
0.005
0.093
1.000
al. 11977].
HS
kg/m3
0.164
0.085
0.085
0.020
0.055
0.071
0.294
0.042
0.072
0.646
0.095
0.055
0.031
0.100
0.117
Product density is 707 kg/m .
-------
Ve seek vertical profiles of the coupled constituents in the un-
saturated zone, embodied by the following boundary conditions
H D H0 (z=0) (3a)
0 " ° (z=0) (3b)
H - ° (z=O (3c)
0 - °C (z=O (3d)
The hydrocarbon is at concentration HO and oxygen is taken as small («rH )
at the top of the capillary fringe, where a separate phase product
[Schwille, 19671 and an appreciable biomass is presumed to exist. Ve note
the oxygen concentration 0^. at the ground surface, where the strongly dif-
fusive character of the atmosphere maintains the hydrocarbon at a low
(«O-/Y) value.
Yates and Enfield [1988] suggest that a dependence between two inter-
acting species may be established regardless of the nature of the reactive
term by eliminating R from the coupled transport equations (1). Ve follow
this procedure by defining the combined constituent variable X
*-••? . <«>
Equation (lb) is subtracted from (la) and constrained by equation (3) with
the result
&-°
X " HQ (z=0> (5b)
-------
8
Equation (5) yields to a general solution for the combined concentration
°Z
Ve stress that equation (6) is valid regardless of the nature of the reac-
tive term; our x profile reflects reaction stolchiometry rather than
reaction kinetics. The model validity rests upon biodegradation as the sole
sink for both oxygen and hydrocarbons in the unsaturated zone.
Ve must specify the reaction R in equation (1) to proceed with the
description of individual hydrocarbon and oxygen concentration profiles.
The reaction is presumed to follov Monod kinetics [McCarty et al., 1984] in
the biocluster with hydrocarbon as the limiting constituent in the un-
saturated zone
vith maximum specific reaction rate r, biomass H, and half saturation con-
stant K for hydrocarbons. The latter coefficient must accomodate solubility
and local mass transfer effects, since ve base our model on vapor concentra-
tions, and not dissolved substrate levels within the bacterial cell vails.
Our model is predicated on the abundance of oxygen, requiring concentrations
veil in excess of 0.003 kg/ra . This limit is based on an aqueous oxygen
4 *%
half saturation constant of 10" kg/m (Bprden and Bedient, 1986] and an
air/vater oxygen partition coefficient of 26.
-------
Following Suidan and Wang [1985], ve attack equations (la) and (7) in-
directly by considering the hydrocarbon flux J as a function of the
dimensionless hydrocarbon concentration H , whence
J2 = 0 (H*=0) (8b)
vith the flux and dimensionless hydrocarbon concentration defined by
J - -nug (9a)
(9b)
Ve separate variables in equation (8a) and integrate with the result
f -tr * 1 /7
J « [2Dn rMK[H -ln(l+H )}} (10)
Equations (9a) and (10) are combined next and integrated from the capillary
fringe to any z,H further up in the vadose zone. An implicit hydrocarbon
equation follows
o
*
(lla)
*
H
KH) = J - - (lib)
0 = --+Y-- (HC)
-------
10
with the oxygen profile specified by equations (4) and (6). The integral
function I(H ) nay be evaluated numerically, as shown for various capillary
fringe concentrations in Figure 2.
Model Calibration
Ve calibrate our simple model of coupled oxygen and hydrocarbon vapor
transport with data obtained at an aviation gasoline spill site in Traverse
3
City, Michigan [Ostendorf et al., 1989]. The 1969 release of about 90 m
(64,000 kg) of aviation fuel presently exists as a separate phase slick in
the capillary .fringe covering an area about 80 m vide and 250 m long
[Kampbell et al., 1989] vith an attendant dissolved plume persisting much
farther downgradient [Tventer et al., 1985; Rlfai et al., 1988] as suggested
by Figure 3. The unsaturated zone extends some 5 m below the ground surface
and consists of uniform fine sand of 3.8xlO~ m median diameter, vith total
and air porosities of 0.367 and 0.258 respectively. The latter values are
obtained by weighing known solid core sample volumes vith subsequent
gravimetric analysis of the moisture. The diffusivity may then be computed
from Millington and Quirk's (1961] useful estimate of the quantity
2.34 i
D B DA n_ (12a)
"T
DA = 7.38xlO~6 m2/s (12 deg C) (12b)
vith air diffusivity DA and total porosity n^,. . Bruell and Hoag 11986J
demonstrate the applicability of equation (10) to hydrocarbon diffusion; we
modify their (hexane) diffusivity value to accomodate the average Traverse
-------
12
10
8
I(H') 6
O
o —
0
0.2 O.4 0.6 O.8 1.0
Fig. 2. Integral Function I(H ) for Various Values of the Dimensionless
Hydrocarbon Concentration at the Capillary Fringe Boundary H« .
-------
PLUME
BOUNDARY
N
BLDG.
60
DC 109
/ v /
IDGZSO i
i * i
I ^ HANGAR
BUILDING
FLANGE
ORIGINAL SOURCE
SCALE
50m
Fig. 3. Site Plan at Traverse City, Michigan Showing Four Vadose Zone
Sampling Locations.
-------
Soil Vacuum Extraction Seminar
Presentation
4/28/89
Date
Page
Laboratory Scale Evaluation _
of
Enhanced Biodegradation
During Soil Vacuum Extraction
R. Ryan Dupont
Utah State University
Utah Water Research Laboratory
Logan, Utah
Outllne
Q Introduction
Q Ancssmcnt of VKUVUTI Extraction Potential
Q Aseumen< of Enhanced Biodegrmdation
Potential
<» Volatillution Corrected Degraditian
Rile Methodology
Q Applications
Q HAFB Site Example
.. fcrtr«tU. W.kthip
SUdd
Introduction
Q V«mum Extraction Highly Attractive but Science
in Infancy
Q N'«d for AsMsonent of Vacuum Extraction &
Enhanced Biodegradata'ort Pofcntial-Pltraesa
Design/ Operation
Problem of Scale in Translation from Laboratory
*/ or Pilot-Scale to Reid
AppHnBorttinTroerf-Of-GDncrpT Rather Than
Final Process Design
ParticulArly Relevant to Bio*ugnvent*tion
Evaluation
RSKERL - Ada Technical Assistance Program
Wood Preserving Site Remediation
R. R. Dupont, Utah State University
801/750-3227
-------
Soil Vacuum Extraction Seminar
Presentation
4/28/89
Date
Page
Soil Vacuum Extraction
O Applied for Volrtfc * Semi-VoUtik
Compound Recovery from Subsurface
Material*
Q "Easy" to Implement Effective
O Cod Effective
O Luge Amount of Product Recovery, Perhaps
Before Ground water Contamination
O Control of Fhlid and Contaminant Movement
O True hi Situ Proas* - No Excavation
MlVa
Soil Vacuum Extraction (cont.)
O Applicable to Compounds of High Vapor
Pressure
Q Applicable to PenwaWe Soils
Q CeneraflyOn* Component of Overall .
Remediation Strategy
Q Interaction with Enhanced Bioremediitttm
Activities
Q Lack of Proven field Experience, Evaluation,
Central Design Criteria
Assessment of Vacuum
Extraction Potential
Q Determination oT Rate ind Extent of
Volatile Constituent Recovery
Q Determination of Residual 5oa/ Soil Gaa
Constituent Concentration & Composition
O Determination of Operation*! Effect*
(Operating T, Q, Pump Fr«]ueney,
Moisture Mgmt, etc.) on Vacuum
Extraction Potential
U) V.n.. trir.liU* W«LJ,.t>
RSKERL - Ada Technical Assistance Program
Wood Preserving Site Remediation
R. R. Dupont, Utah State University
801/750-3227
-------
Soil Vacuum Extraction Seminar
Presentation
4/28/89
Typical Laboratory Methodology
O Soil Microeocm t/ or Column
(.Undisturbed)
0 Wdl Defined Flow Low*
O SnuBSoleMntofO
O Pure Component! (•Mixture)
O Hig?i Flow Rite*
Date
Page
SpO V.m. I>l7.cU«i Wnkrinp
«""'
RSKERL - Ada Technical Assistance Program
Wood Preserving Site Remediation
R. R. Dupont, Utah Slate University
801/750-3Z27
-------
Soil Vacuum Extraction Seminar
Presentation
31 '=
Data Output
O Simulation of "Bc*t CMC" Opcnting
Condi ban*
a Minimum Sail Cacwentntien Level*
Over lime
O MnviTtnim Vtnl CM Coneentnrttmu
O Trarf-Of-Canoep<"V«itinePotentu]
4/28/89
Date
Page
What Studies Do Not Tell
D Effect of Soil Non-Homogeneity on
Vacuum Extraction Efficiency
O Effect of Row Held Non-Homogeneity
on Vacuum Extraction Efficiency
O Operational Vent Gas Concrntnuions
O &t* Operational limitations
1
Ml Vima
a- —
: ?i MV.«
Studies Can Be Extended
However, for
•* A»eumen(olMuugement
Techniques for Biologic*] Reaction
OpiimUalion
•* AiiKsmml of Biological Reaction
Rale* and PaOtwavs
Jt
»• btrirtin W«kA>» SUJ.11 T
KSKERL - Ada Technical Assistance Program
Wood Preserving Site Remediation
R. R. Dupont, Utah 9late University
801/750-3227
-------
Soil Vacuum Extraction Seminar
Presentation
4/28/89
Date
Page
Assessment of Enhanced
Biodegradation Potential
0 Retention of LTD Concept toXJnutonted
Zone Vapor Phase Remediation
O "Proof-of-Concept" far Enhanced
Biadegndatkm
O Evaluation of Wide Variety of
Management Techniques tot
Enhancement of In Situ Biodegndaticn
Economically
-ff
Sod V«» EitnrfliB WwVAip
fUd
!•» P
If
RSKERL - Ada Technical Assistance Program
Wood Preserving Site Remediation
R. R. Dupont, Utah State University
801/750-3227
-------
Soil Vacuum Extraction Seminar
Presentation
4/28/89
Date
Page
Volatilization Corrected Degradation
Rate Methodology
O Methodology for Quantifying Unique
Contaminant LossFithwtyi
O Laboratory Flaik/ Miawosm Sol*
O Mass of Conttituent Quntitated
••Emitted to Air Phase Over Dine
•• Remaining In Sou Fhise Ova-Haw
O KoticVcnui Abiotic Ln*
•» SterfflMd Controls
MVnu blndkn W«Ui*r
SUd«ll
VCDR Data Handling
O Compound Mast Emission Rate
O £ Mass Compound Einirted
D Compound Soil Concentration if "No
Degradation"
D Actual Mass Degraded
•*• *3 - Actual Compound Soil Mass
O Biodegradltion Lou
•«•*<- Abiotic Reactor Compound Loss
D VCDR From-InCMiw Degraded) vs£t
SeOVjcna
Slidtlt
R5KERL - Ada Technical Assistance Program
Wood Preserving Site Remediation
K. R. Dupont, Utah State University
801/750-3227
-------
EXAMPLE DATA CALCULATIONS FOR NUNN SOIL
VOLATILIZATION CORRECTED
DEGRADATION RATE DETERMINATION
Time
(d)
0
0.042
3
5
10
20
Tune
,(d)
0
6.042
3
5
10
20
Benzene
Mass Added
(US)
662.43
662.43
662.43
662.43
662.43
662.43
Toluene
Mass Added
(US)
757.68
757.68
757.68
757.68
757.68
757.68
Naphthalene
Time
-------
yo-.178x-.331j R-squared: .835
Benzene First Order Apparent Degradation Rate Determination,
Nunn Soil-Abiotic Control
y= .033x + 5.791. R^uared: .963
Benzene Volatilization Corrected Degradation Rate Determination,
Nunn Soil
&;&4iV -:Mfe^^^:r
-------
11
City vadose zone temperature of about 12 deg C for our model. The resulting
site diffusivity value is computed to be 2.30xlO~6 ra2/s.
Vertical clusters of stainless steel sampling tubes set at selected
depths are used to obtain vapor samples for direct analysis by a portable
Bacharach TLV combustible hydrocarbon indicator. Oxygen is also sensed by a
similar portable device. Four profiles (Figure 3) are observed above loca-
tions of known separate phase gasoline occurrence at the water table, as
verified by solid core data. The shallow hydrocarbon data correspond
closely to an independent set of near surface transects used to successfully
map the distribution of the separate phase aviation gasoline. Kanipbell et
al. 11989] provide a more extensive account of the sampling techniques and
mapping protocol at Traverse City.
The coupled variable X may be simply computed using equation (4) for
fitting of the straight line equation (6). Figure 4 and Table 2 show the
results of a tvo parameter calibration specifying HQ and 0.. Ve use statis-
tics of the error 8 defined by
A
x = X(measured)-X(predicted)
X H^ (13)
to calibrate the coupled model. Our use of HQ to normalize the error
prevents small values of X from unduly skewing the calibration. The 0. in-
tercept minimises the mean error l^ of the profile, while the capillary
fringe hydrocarbon concentration minimizes the error standard deviation a
A
-------
DG 109
-JOT
— 4
z,m
— 2
-.02 0 .02
X,
x x
— 4
A X
z,m
—2
DG280
I I
-.04 -.02 0 .02
.3
X, kg/m'
-.06 -.04 -.02 0 .02 -.04 -.02 O .02
X, kg/m3 x, kg/m3
Fig. 4. Observed (Circles) and Predicted (Lines) Coupled Constituent Variable
Profiles at Traverse City, Michigan.
-------
12
through a nested Fibonacci search technique [Beveridge and Schechter, 1970].
The statistical definitions are [Benjamin and Cornell, 1970]
I = jl{5) (Ua)
a- [h(t?)-l2]l/2 (Ub)
The standard deviation a for the straight line model is less than 112
A.
for each of the four profiles* indicating a reasonably good fit of the
coupled constituent theory and data. The observed linearity of the profiles
offers field validation of the simplifying assumptions that underlie our
modeling approach; the reaction stbichiometry is reasonably approximated by
equation (2a), transience and advection are indeed negligible, and n and D
are roughly uniform on a- time averaged basis. The biodegradation process
also appears to be the sole sink for oxygen and hydrocarbons in the un-
saturated zone at Traverse City.
With the boundary conditions in hand, we then search in a similar
fashion for biological parameter values for the separate species profiles.
The half saturation constant K for hydrocarbon vapor is related to its more
commonly measured aqueous counterpart Ky by the air/water partition coeffi-
cient X for aviation gasoline
(15a)
HS
X " c~ <15b>
S
-------
Table 2. Coupled Constituent Profile Parameters
Station
PT4
H30
DG280
DG109
c
m
4.70
4.54
4.97
4.82
0
C
kg/m3
0.162
0.214
0.131
0.157
H-
0
kg/m3
0.0220
0.0275
0.0274
0.0196
•Jv,
X
X
11
8
7
4
-------
13
vith a saturated H_ hydrocarbon concentration of 0.117 kg/m also computed
from the observed composition of the weathered aviation gasoline. We es-
3
timate a saturated dissolved concentration C_ of 0.0039 kg/m , so that the
o
partition coefficient is computed to be 30 at Traverse City. Borden and
Bedient [1986] and Holz et al. [1986] cite an aqueous half saturation con-
-4 3
stant of about 10 kg/m for hydrocarbons, which corresponds to K=0.003
kg/m for the vapors. The maximum reaction rate (rM) is then used to mini-
mize the mean error "3Lrt engendered by equation (11) and the hydrocarbon and
nu
oxygen data, as defined by
. H(measured)-H(predicted) ,,,. .
* = rj lioaj
H Ho
- 0(measured)-0( predicted) /i/:u\
*o o^ . (16b)
*HO - 2jI( VV (16c>
As vith the combined variable error, intercept concentrations are used to
normalize the error to prevent small concentrations from skewing the
calibration results, which are summarized in Tables 3, A, and Figure 5. The
error standard deviations range from 3 to 1% in magnitude, indicating a good
fit of the separate nonlinear profile theory and the individual constituent
observations. The accuracy is particularly encouraging in light of the
simplicity of the present approach.
Discussion
-------
Table 3. Separate Constituent Profile Parameters
Station
PT4
M30
DG280
DG109
rH
3
kg/m -s
1.50xlO~8
5.90xlO~9
9.47xlO"9
8.32xlO~9
r
s'1
7.96xlO~7
3.13xlO~7
5.03xlO~7
4.42xltT7
CT»A »/»
HO 0
v i/2
% kg/in -s
5 8.47xlO"9
3 6.09xlO~9
7 7.70xlO~9
5 5.87xlO~9
-------
Table 4. Measured and Predicted Vapor Concentrations
z
D
- j.
0.43
1.65 __
2.87
0.63
1.63
2.63
3.63
H(meas.)
kg/in3
• • ' .
0.0147
0.00360
0.000272
- • : - ', *
0.0193
0.0139 -
0.00754
0.00298
H(pred.)
kg/in3
0.0164
0.00571
0.00121
0.0215
0.0138
0.00808
0.00410
*"
Station PT4
-8
-10
-4
Station H30
-8
0
-2
.4
0(meas. )
ke/m3
,
0.00410
0.00751
0-0738
0.0246
0.0510
0.110
0.164
0(pred.)
kg/m3
- -
0.00219
0.0268
0.0731
0.0220
0.0633
0.112
0.166
X
1
-12
0
1
-6
-1
-1
Station DG280
1.06
2.06
-3.06
4.06
0.0175
0.00852
0.00105
0.000625
0.0157
0.00812
0.00329
0.00122
*
7
1
-8
-2
0.0212
0.0239
0.0383
0.0977
0.00733
0.0265
0.0552
0.0937
11
-2
-13
3
Station DG109
0.82
1.82
2.82
3.82
0.0144
0.00563
0.00144
0.000281,
0.0125
0.00647
0.00270
10
-4
-6
0.000955 -3
0.0178
0.0383
0.0710
0.108
0.0135
0.0392
0.0728
0.114
3
-1
-1
-3
-------
z,m
°/oc
z,m
0.5 1.0
H/H,
z,m
O
O.5
H.
Fig; 5. Observed Oxygen (Circles) and Hydrocarbon (Triangles) Vapor Concentra-
tions at Traverse City, Michigan., Curves Are Predicted Profile Values. J ;
-------
14
The foregoing analysis proceeds in the assumed absence of transience
and advection vith negligible hydrocarbon and oxygen at the ground surface
and capillary fringe respectively. It is appropriate to discuss the ap-
plicability of these assumptions at the Traverse City site. Ve assess the
transient assumption by computing a diffusive residence time T for the
vadose zone
T . §- (17a)
T - 107 s (17b)
This 3 month period is too sluggish for the vapor profiles to respond to
diurnal or meteorological unsteadiness in air filled porosity, temperature,
or pressure conditions. There may be seasonal fluctuations induced by a
varying oxygen demand near the ground surface, but our data do not reflect
this trend. In any event, the bottom hydrocarbon boundary condition should
be quite steady at all time scales due to small groundvater temperature
fluctuations. The data of Table 4 do support boundary conditions (3) and
oxygen concentrations are in abundance (»0.003 kg/m ) for all cluster
depths vith the possible exception of the near bottom region of PT4. Oxygen
limiting conditions may be responsible for deviations from the predictions
on Figure 5 for this profile.
The neglect of advective transport is deemed appropriate due to the low
solubility of aviation gasoline, as reflected in the following ratio of ad-
vective to diffusive flux
-------
15
j-2 ~ 0.01 (18a)
J0
J0 = {2Dn2rMKlH0*-ln(l+H0*)]}1/2 (18b)
o
Ve adopt a net recharge value e of 10 m/s in equation (18a) vith the
hydrocarbon flux through the capillary fringe J_ specified by equation (10).
In the latter regard, the four diffusive flux estimates for Traverse City
appear in Table 4 and are suitable for fate and transport studies of the im-
miscible aviation gasoline. Roughly speaking, this flux has dissipated
about half of the spilled fuel over the 20 year life of the plume, under-
scoring the importance of volatilization as a transport mechanism for light
hydrocarbon pollution. Ve note that the lov hydrocarbon concentrations near
the ground surface support lov fluxes, so that (for the four profiles
sampled) only a small portion of the volatile pollution escapes to the at-
mosphere. The data also suggest that only a small amount of oxygen reaches
the capillary fringe, and this will in all likelihood be consumed before
reaching the water table by microbes in the vicinity of the immiscibly bound
aviation gasoline. Thus we expect anaerobic conditions to prevail in the
upper regions of the aquifer.
The coupled variable intercepts have implications for vapor transport
in the unsaturated zone. The 0. values are substantially less than the at-
mospheric content of 0.287 kg/m , implying consumption of oxygen by surface
vegetation prior to its entry into the unsaturated zone. The H intercepts
are likewise considerably less than the saturated value, suggesting either
-------
16
mass transfer limitations [Pfannkuch, 1984] or biological degradation vithin
the capillary fringe itself. Thus, a complete account of the volatilization
process should include two thin layers adjacent to the ground surface and
water table, matched vith continuous flux and concentrations to our vadose
zone analysis. Such an effort must vait upon the detailed analysis of in-
tact cores through the layers, either in field or laboratory settings. The
use of empirical intercepts finesses this more fundamental study of the
phenomenon.
Ve estimate the biomass in accordance vith the following equation
Np P V
: M = BnM " (19)
vith cell number N per kg of dry soil, densities of dry soil pD and bacteria
o
PM, and individual cell volume VM. The cell number is set equal to
-i
1.35x10 cells/kg dry soil, based on Acridine Orange Direct Counts of vapor
exposed vadose zone soil samples [Smith, 1989J. Fiorenza [1989] measures
9
1.80x10 colonies/kg dry soil in an independent plate count of contaminated
vadose zone soil, and the ratio of the tvo figures suggests that about 8
bacteria reside in a cluster. Fiorenza [1989] uses a spread plate tech-
nique, with the colonies grown on Noble agar amended vith a mineral salt
solution incubated under an aviation gasoline vapor atmosphere for four
weeks. The colonies are consequently assumed to degrade hydrocarbons. The
dry bulk density of the soil is 1670 kg/m3, while the cell density is taken
as 1100 kg/m . Finally the cell volume is calculated to be 1.96xlO~19 m3,
-------
17
corresponding to a cylindrical configuration of 0.5 micron diameter and 1
micron length (excluding extracellular polymers).
*J O
These figures lead to a biomass estimate of 1.88x10 kg/m void space
at Traverse City, and in turn support a calculation of the maximum specific
reaction rates at the site. The maximum reaction rates of Table 3 vary over
983
a modest range of 5.90x10 to 1.50x10 kg/m -s, so that the maximum
specific reaction rates range from 3.13x10 (37 days' ) to 7.96x10 s"1
(15 days" ). The rates are substantially less than values reported for
saturated flow by Holz et al. {1986], so that degradation appears to be
slower in the unsaturated zone.
Conclusions
Ve measure and model the concentration of hydrocarbon and oxygen vapors
In the unsaturated zone above residually contaminated soil from an aviation
gasoline spill at the US Coast Guard Air Station in Traverse City, Michigan.
Our analysis proceeds in the assumed absence of advection and transience,
and accordingly is a simple balance of gaseous diffusion and biological
degradation coupled in the tvo reacting constituents. The oxygen and
hydrocarbon transport equations are combined under the assumption of con-
stant air filled porosity and diffusivity, resulting in a straight line
relation for the combined species variable regardless of the nature of the
reaction. A linear regression through the field data then yields the oxygen
and hydrocarbon concentrations at the ground surface and capillary fringe,
respectively. These boundary conditions are input to an analytical model of
the separate constituent profiles which incorporates nonlinear Honod
-------
18
kinetics under hydrocarbon limiting conditions. Ve use the maximum specific
reaction rate to calibrate the resulting model with reasonably accurate
results. Volatilization is shown to be a significant long term transport
mechanism at Traverse City, and biodegradation prevents the escape of ap-
preciable contamination to the atmosphere for most locations at this site.
Ve expect minimal oxygen to reach the water table due to the aerobic
biodegradation process in the unsaturated zone.
Notation
3
Cg dissolved hydrocarbon concentration at saturation, kg/m .
2
D gaseous diffusivity, m /s.
DA gaseous diffusivity in air, m /s.
B hydrocarbon vapor concentration, kg/m .
7
HQ hydrocarbon concentration at the capillary fringe, kg/m .
3
HS saturated hydrocarbon concentration, kg/m .
H dimensionless hydrocarbon concentration.
HO dimensionless hydrocarbon concentration at the capillary fringe.
I integral function.
2
J hydrocarbon flux, kg/m -s.
JD hydrocarbon flux through the capillary fringe, kg/m2-s.
K hydrocarbon vapor half saturation constant, kg/m .
-------
19
KJJ aqueous hydrocarbon half saturation constant, kg/m .
M biomass, kg.
n air filled porosity.
IL. total porosity.
0 oxygen vapor concentration, kg/m .
3
0. oxygen concentration at the ground surface, kg/m .
R rate of biodegradation, kg/m -s.
r maximum specific reaction rate, s~ .
T response time of the vadose zone, s.
z distance above capillary fringe, m.
hydrocarbon error.
50 oxygen error.
5 combined variable error.
n.
1an mean profile error.
a\J
"5 mean combined variable error.
^^
2
c recharge rate, kg/m -s.
C ground surface elevation, m.
X aviation gasoline air/vater partition coefficient.
X combined constituent variable, kg/m .
0 profile error standard deviation.
HO
-------
20
a combined variable error standard deviation.
A
Acknowlegments
The National Center for Groundwater Research of Rice University
provided sabbatical support for Dr. Ostendorf, vho served as a Visiting
Associate Professor at the Robert S. Kerr Environmental Research Laboratory
from September 1988 to June 1989. The research vas performed with the sup-
port of the US Coast Guard as veil. Although the study vas conducted by
Kerr Laboratory personnel of the US Environmental Protection Agency, the
paper has not been subjected to USEPA review. The work therefore does not
necessarily reflect the vievs of the Agency and no official endorsement
should be inferred.
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21
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22
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transport of residual hydrocarbon in groundvater—a case study, Proceedings
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around wood preserving facilities by polychlorinated aromatic compounds,
Environ. Sci. Tech., 21, 96-101, 1987.
Lee, H.D., J.H. Thomas, R.C. Borden, P.B. Bedient, J.T. Vilson, and C.H.
Vard, Biorestoration of aquifers contaminated with organic compounds, CRC
Crit. Rev. Environ. Control, 18, 29-89, 1988.
McCarty, P.L., B.E. Rittman, and E.J. Bouwer, Microbial processes affecting
chemical transformations in groundvater, Groundvater Pollution Microbiology,
edited by G. Bitton and C.P. Gerba, pp. 89-115, Viley-Interscience, New
York, NY, 1984.
Hillington, R.J. and J.P. Quirk, Permeability of porous solids, Trans^
Faraday Soc.. 57, 1200-1207, 1961.
-------
23
Molz, F.J., M.A. Widdowson, and L.D. Benefield, Simulation of microbial
growth dynamics coupled to nutrient and oxygen transport in porous mediat
Water Resour. Res., 22, 1207-1216, 1986.
National Academy of Sciences, Groundvater Contamination, 179 pp., National
Academy Press, Washington, DC, 1984.
Nichols, P.D.t J.H. Benson, C.P. Antvorth, J. Parsons, J.T. Wilson, and D.C.
Vhite, Detection of a microbial consortium including type II methanotrophs,
by use of phospholipid fatty acids in an aerobic halogenated hydrocarbon
degrading soil column enriched vith natural gas, Environ. Tox. Chem., 6, 89-
97, 1987.
Ostendorf, D.W., D.H. Kampbell, J.T. Wilson, and J.H. Sammons, Groundvatcr
pollutant source characterization of an aviation fuel spill, submitted to J.
Water Poll. Control Fed., and currently under review.
Pfannkuch, H.O., Determination of the contaminant source strength from mass
exchange processes at the petroleum groundwater interface in shallow aquifer
sys t ems, Proceedings Petroleum Hydrocarbons and Organic Chemicals in
Groundvater, 111-129, NWWA/API, Houston, TX, 1984.
Reid* R*C.t J.H. Prausnitz, and T.K. Sherwood, The Properties of Gases and
Liquids. 688 pp., McGraw-Hill, New York, NY, 1977,
Reinhard, H. and N.L. Goodman, Occurrence and distribution of organic chemi-
cals in two landfill leachate plumes, Environ. Scl. Tecju, IB, 953-961,
1984.
Rifai, H.S., P.B. Bedient, J.T. Wilson, K.M. 'Miller, and J.H. Armstrong,
Biodegradation modeling at aviation fuel site, J. Environ. Eng.t 114, 1007-
1029, 1988.
-------
24
Schville, F., Petroleum contamination of the subsoil—a hydrological
problem, The Joint Problems of the Oil and Water Industries, edited by P.
Hebble, pp. 23-54, Institute of Petroleum, New York, NY, 1967.
Sleep, B.E. and J.F. Sykes, Modeling the transport of volatile organics in
variably saturated media, Water Resour. Res., 25, 81-92, 1989.
Smith, R.L., Procedures for determining Acridine Orange Direct Counts of
bacteria in subsurface soil samples, R.S. Kerr Laboratory SOP, USEPA, Ada,
OK, in press.
Suidan, M.T. and Y.T. Wang, Unified analysis of biofilm kinetics, J^
Environ. Eng., 111, 634-646, 1985.
Thornton, J.S. and V.L. Wootan, Venting for the removal of hydrocarbon
vapors from gasoline contaminated soil, J. Environ. Set. Health A, 17, 31-
44, 1982. •-•-•
Tventer, F.R., T.R. Cummings, and N.G. Granneman, Groundvater contamination
in East Bay Township, Michigan, VRIR 85-4064, 63 pp., USGS, Washington, DC,
1985.
Vandegrift, S.A. and D.H. Kampbell, Gas chromatographic determination of
aviation gasoline and JP-4 jet fuel in subsurface core samples, J. Chromat.
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Vallingford, E.D., F.A. DiGiano, and C.T. Miller, Evaluation of a carbon ad-
sorption method for sampling gasoline vapors in the subsurface, Groundvater
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Widdowson, M.A., F.J. Molz, and L.D. Benefield, A numerical transport model
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availability in porous media, Water Resour. Res., 24, 1553-1565, 1988.
-------
25
Wilson, B.H., B.E. Bledsoe, D.B. Kampbell, J.T. Wilson, J.M. Armstrong, and
J.H. Sammons, Biological fate of hydrocarbons at an aviation gasoline spill
site, Proceedings Petroleum Hydrocarbons and Organic Chemicals in
Groundvater, 78-90, NWWA/API, Houston, TX, 1986.
Wilson, J.T. and C.H. Ward, Opportunities for bioreclamation of aquifers
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-------
y a -.111x - .133. R-squared: .936
7.5 10 125 15 175 20
Time(d)
22.5
Toluene First Order Apparent Degradation Rate Determination,
Nunn Soil-Abiotic Control
y= .102x + 5.347, R-squared: .979
4 6
limefd)
Toluene Volatilization Corrected Degradation Rate Determination,
Nunn Soil
m
-------
y e ..08x- .096, R-squtnd: .977
7.5 10 12.5
Time(d)
Naphthalene First Order Apparent Degradation Rate Determination,
Nunn Soil
.067X + 5.182, R-squared: .91
0 2.5 5 7.5 10 12.5 15 17.5 20 22.5
Timefd)
Naphthalene Volatilization Corrected Degradation Rate Determination,
Nunn Soil .
ii*.?; ?'5F:' -•£•. • • wSSfe^Jtlffiii
-------
ye-.04tx- .682,R-squared: .973
7.5 10 12.5
Time (d)
Methyl Naphthalene First Order Apparent Degradation Rate
Determination, Nunn Soil
y t= _010x +5.006,
TiJ.% «* *
1-Methy[Naphthalene Volatilisation Connected Degradation Rate
Determination, Nunn Soil
-------
Soil Vacuum Extraction Seminar
Presentation
4/28/89 .
Date
Page
VCDR Method Output
O Biotit Degradation Rale* Corrected far
O Relative Significe of Vobtfflutkm
Versus Biotic Venus Abiotic Ucae*
O Mass Balance for Constituent* Under
Controlled Condition*
*^ Corrected Kate cxunpott
£
Applications
Site Conditions Signifiontly Affect Fhynol
Vacuum Extraction Pnxcu
•» Requires Field Scale Test • Voiting
•* Bio-Potential Assessment on Lab Scale
One WeU Vent Test
«• Initia] Venl Well Concentrations
•• Site Pnssure Field Definition
•* Site Heferogeneity
-* Modri Scaling/
=i
Hill Air Force Base Example
O Site Conditions
•*• ZxOOO gal IP-4 Jet Fuel SpQU/9/S
•* RneSand/CnveltoSOft
P Vintmg Sy»iesn Design
•» 52,000 cy Excavated Soil in File -Vented
» VerticI«Wells-ScrmiedlOtoSOft
«* UtenlWelli- Under Tanks
-• Impervious Cover - Portion of Sil*
. «» Optional Ce Injection -Heating
•» Catalytic Indnemor- Off CBS Tic*tmeM
RSKERL- Ada Technical Assistance Program
Wood Preserving Site Remediation
R. R. Dupont, Utah State University
801/750-3227
-------
LEL CONTOURS OF VERTICAL VENT SYSTEM - 2/2/89
120
7 13 20 27 33 40 47 53 60 67 73 80 87 9,3 100 107 113 120 127 133 140 147||153 160
-------
SOIL GAS SSLEL CONTOURS - 3/11/89
10 20 30 40 SO 60 70 8' 90 100 110 120 130 14)
-------
concentration study. Several vapor and pressure sensors are 1n place around
the extraction well in a semi-circle at different distances and depths. No
free product has been found and is thought to be Immobilized in the soil.
ANALYTICAL
.EMISSION
CONTROL
EXCAVATED
SOIL
LATERAL
PIPE ARRAY
Figure 1. Conceptual Diagram of Soil Vapor Extraction Demonstration Project
at Hill Air Force Base (Source: Oak Ridge National Lab, 1988).
O O
D
O
>_*
?c
^-'•|| j ,
-r. •*- *•
— i
1 1 L ,
6lo««r/Emi«JCi»
Control Systtn
— —
^^•^
^••^
J
1
4
c
L
i
i
=
•^
f— :
L
—
1
~ - -r
•^ •
/
^^^
i
~
J
n
r
r
f
.
Vrrtictl
Lottrtl Vrnt
100
Figure 2. Soil Vapor Extraction System Layout at Hill Air Force Base
(Source: Oak Ridge National Laboratory, 1988)
-------
HILL.SHT
Chronological Sequence flf Events:
01/09/85 — Spillage of -26,000 gallons of JP-4, 1000 gallons recovered.
12/85 -- Remedial Investigation by Rollins, Brown and Gunnel1. Concluded no
Imminent danger.
07/87 --Radian Corporation Investigated site further. Recommended
additional monitoring.
07/22/87 -- D. DePaoll and S. Herbes of ORNL and Capt. E. Keyse of AFESC,
Tyndall AFB visited and selected Hill AFB as study site.
08/18/87 -- DePaoll proposed design for horizontal extraction wells in pile
and under tank pad for Installation during tank excavation and pad
construction.
08/31/87 -- DePaoll and Herbes propose soil sampling scheme.
10/87 -- Tanks were excavated, horizontal pipes Installed, and soil borings
performed.
01/10-22/88 -- 0. DePaoll, H. Jennings, J. Wilson, 0. Glllespie, and Capt.
E. Heyse conducted one-well vent test.
01/14-17/88 — J. Gierke (MTU) visited site and aided In one-well test
preparation. _. ,
04/21/88 -- Test plan developed by ORNL reviewed by N.J. Hutzler and
others and tentatively approved by U.S.A.F. Tentative starting date is late
summer 1988.
06/17/88 — Specifications of vent wells, pressure monitoring wells, and
plastic cover prepared by ORNL.
-------
SOIL GAS 5BLEL CONTOURS"- 4/2/89
-------
Soil Vacuum Extraction Seminar
Presentation .•
Bi =
Typical Well Construction Detail
»•»€• . ,WHB
' ^Ir^^,
II MM.
Bate
Stainless Steel Canister
F
Typical
System
Norm
System Sole Field
• Extndion Wrib 19
tlnMWclb
Wdl Sp*dng
Air Jnpot
Wdl DUmcto
Wdl M»terl*l
9" U V«,a« Irtirtil
«
-30ft
Stirfi
9 In
PlIobTickl
1-B9
0-21
14-100 ft
n SvrfMC/ InJKtioo
1J5-4U
PVC PVC -CiL Sled
•iWoAAif S1W.M R
RSKERL - Ada Technical Assistance Program
Wood Preserving Site Remediation
FT. R..nup07rt-,Ulati
-------
Soil Vacuum Extraction Seminar
Presentation
4/28/89
Date
Page
Typical Site Characteristics
Norm
Rant*
Soil
Depth to CW
SottFonBity
SrfnntedK
Affected Are*
Said
US ft
OJ9
0.02 an*
35%
•.7 me
Sud-CUyejrSUt
•-«00ft
T-O31
aoooi- 0.1 cm/«
T-S*nntedLettel
OJB-SDK
Affected Volume -MXMXJOcj 3,000
• StO Vtmm BMndlM (MuMp
HUCB
Typical Operating Characteristics
Horn
Kmge
VtcuuDi Sluice Blowea
Air Flour Rate* -TOO rfw
Operating Vacuum 5 In Hg
Impermeable Cap SO/50
AltfWHer Separator SOISO
VK»ara Pump
10 • 21,800 dm
OJ-SOlnHj
Monitoring
WeHi/Eittmul Cm
VcporPfobc*
Knodc-Oot Dn
Condenser
SoU Boring!
a
Typical
Contamination Characteristics
Norm
Chemical* Chlorinated Solvcnb)
Spill Volnrae 40^00 gal
Volume Rrccvcmi 11,100 J«1
* R«o»*ry, Soil Uft
ChEmlodExtradloii 82 Ib/d
lUtc
KUIKC
Aronalla/FDd
IDJMO • 100,090 g«]
190- 21^X10 g«l
0.19-70%
U-mlb/d
sMtxr
i
J
RSKERL - Ada Technical Assistance Program
Wood Preserving Site Remediation
R. R. Dupont, Utah State University
801/7SO-3227
-------
Soil Vacuum Extraction Seminar
Presentation • '"
Vent System Ferfonnance
MVw
4/28/89
10
Date
Page
Component Distribution Over Time
Component Distribution Over Time
• > u
Wl VU
RSKERL - Ada Technical Assistance Program
Wood Preserving Site Remediation
K. R. Dupont, Utah State University
801/750-3227
-------
Soil Vacuum Extraction Seminar
Presentation
Comonent Distribution Over Time
a
tw.IJ
4/28/89
Date
Page
Minearlization
« H X K
Soil Vacuum Extraction
Q Recovery of Vol»tiJe«nd Seni-Volitile
Fraction of RslduilOU
Q EnhlTKC Subsurftct Chcygrn St»tui M
Contamiiuled Sites tor the Enhancement
RSKERL - Ada Technical Assistance Program
Wood P; .• -rving Sile Remediation
R. R. Dupont, Utah State University
801/750-3227
-------
ENHANCED BIODEGRADATION THROUGH SOIL VENTING
Robert E. Hinchee, Battelle Columbus, Ohio 43201 (614) 424-4698
Conventional in-situ biodegradation techniques utilize water as a
carrier for oxygen (or an alternative electro acceptor). The problem with
this approach is that generally in-situ biodegradation of non-chlorinated
hydrocarbons is typically oxygen limited, and oxygen solubility in water is
low. Hydrogen peroxide has the potential to somewhat increase available
oxygen, however at some site hydrogen peroxide stability may be a problem,
this coupled with the high cost of hydrogen peroxide make its potential
application limited. As a result to deliver sufficient oxygen to
bioremediate a contaminated site very large volumes of water must be
delivered.
Solubility limitations restrict oxygen delivery to 8 mg/1 (.0008%)
for dissolved air, and 40 mg/1 (.004%) for dissolved pure oxygen. Hydrogen
peroxide in concentrations up to 1000 mg/1 it is theoretically possible to
deliver 500 mg/1 (.05%) oxygen.. By comparison ambient air contains 20.9%
oxygen. To simulate biodegradation delivery of air to contamination in the
vadose zone substantially reduces the cost of oxygen delivery and increases
the available oxygen. Based upon preliminary field work it appears that by
utilizing soil venting to deliver oxygen to contaminated vadose zone soils
is feasible and the system becomes less oxygen limited. At a typical site
oxygen break through to the vent well occurs within hours of initiation of
venting. This contrasts with weeks to months, or longer typically required
at a water borne oxygen or hydrogen peroxide site.
Battelle is currently involved in 3 different research projects in
which we are investigating the use of soil venting to increase
biodegradation. Two of these studies are supported by the U.S. Air Force
Engineering and Services Laboratory, Eglin Air Force Base, Florida, and one
by the Naval Civil Engineering Laboratory, Port Hueneme, California.
At Hill Air Force Base, Utah we are monitoring a JP-4, jet fuel,
conventional soil venting operation to determine biodegradation rates.
Additionally, we have collected soils from the site to conduct bench scale
treatability tests to evaluate the effect of nutrient and moisture content.
Results to date indicate that the soil venting is stimulating
biodegradation, and biodegradation may be resulting in 25% or more of the
remedial action. Bench scale tests indicate that by increasing moisture and
nutrient levels we can increase biodegradation rates.
At Patuxent Naval Air Station in Maryland we have been conducting
bench scale tests to determine the potential effectiveness of using venting
to treat in-situ vadose zone soils contaminated with JP-5 fuel. Based upon
our bench scale work field tests have been designed and will be monitored.
At another Air Force site we will be initiating a field study in
which we are designing a venting system specifically to maximize
biodegradation rates and minimize volatilization, the objective is to
minimize volatile hydrocarbon emissions. This system has been designed to
dewater the site to expose contamination at and below the water table.
This work indicates even at sites designed solely for physical
venting that biodegradation can be a significant mechanism for in-situ
treatment. Further work has the potential to increase biodegradation rates,
and minimize volatilization rates.
-------
Enhancing Biodegradation
Through Soil Soil Vapor Extraction
Robert Hinchee
Baltelle
... Putting Technology To Work
-------
-------
Aerobic Biodegradation
Hydrocarbon
Oxygen
+ Nutrients ^ Biomass
CO,+ H2O (Respiration)
-------
Aerobic Biodegradation - Respiration
C6H6+ 71/2O2 —* 6 CO2+ 3 H2O
3.1 lbO,/lbCRH
6" "6
6CO2+7H2O
3.52lb 02/lb C6H14
-------
Oxygen Supply
Water Ib carrier/lb O2
Air Saturated 100,000
Pure O2 Saturated 25,000
500 mg/l H2O2 10,000
Air
-------
• >«V w^&?*9s^wr^*M:>*&**f**ff*&p •—,-^f • •=£ *«ft«5«•=wa=H!ii*ifi5?i:s«''f^fc • • *i*™*i"iiPe*' • iswjjiasssJ J.'E;s322S?
©onventiOiilEnhaneedlBiQreclarnatiQn
-------
-------
tos*
-------
-------
-------
llBattelle
... Putting Technology To Work
Current Programs
Monitoring Biodegradation at Hill AFB Soil Venting Site
Sponsor: U.S. Air Force Engineering and Services Center
Doug Downey, PE, Project Officer
Enhanced Biodegradation Through Soil Venting
Sponsor: U.S. Air Force Engineering and Services Center
Doug Downey, PE, Project Officer
Enhanced Biodegradation in the Vadose Zone
Sponsor: Naval Civil Engineering Laboratory
Ron Hoeppel, Project Officer
-------
Oxygen Concentration in Vadose Zone Before Venting
Distance (feet)
10
10
20
1 30
*»
o 40 -
50 -
60 -
70
10%
20
IY
W
30
IT
40
50
60
IK
Vent
Well #7
70
*
IR
80
•
90
IM
• Q
-------
Monitoring Point Construction
To Surface
Grout Seal
1/4"
Polyethylene
Tubing
1/4" Tubing
Fitting
Stainless
Steel Mesh
21/64" Holes
1-1/2"Sch. 40
PVC Cap
-------
Location Y
Background
X Total
O Hydrocarbon
Degraders
70
100 1,000 10,000 100,000 1,000,000 10
CFU/gm
100 1,000 10,000 100,000
CFU/gm
-------
Oxygen Concentration in Vadose Zone After Venting
Distance (feet)
0 10 20 30 40 50 60 7O 80 90
-------
Monitoring Point Y In-Situ Respiration Test
December 19, 1988
15-
X Oxygen, k =-.00059/min
O Carbon Dioxide
1000
2000 3000
Time (minutes)
4000 4500
-------
Vent 7 Offgas Composition
30
C 20
S 10
C
o
o
Background 02 (20.9%)
Background
CO2 (0.03%)
I
5
10
i i i i i
15 20 25 30 35
Day
-------
Inorganic CO2 Uptake/Release
co, +
Soil Pore Water
2H+ ^Z^ Ca
++
2 HO + CO
-------
Cumulative Hydrogen Removal
Hill AFB Soil Venting Site
^ 14
W.Q 12
1 <5
§0
<2 +
10 15 20
January
Date
February
-------
Bench Scale Studies
Soil columns 1.5" x 12"
Upflow 100 ml/hr scrubbed air
250 gm of HAFB composite soil
5000 mg/kg initial JP-4 hydrocarbon content
25, 50, 75% field capacity
2% Restore® Nutrient Supply
Dead control (50% field capacity with Restore®)
-------
Without Nutrients
25% Field Capacity
50% Field Capacity
75% Field Capacity
A Sterile Control
Standard Deviation
15 20
Time (Days)
-------
With Nutrients
110
100
90
io 80
o
0) 70 •
o> 60
CO
0)
>
8
• 25% Field Capacity
H 50% Field Capacity
$ 75% Field Capacity
A Sterile Control
| Standard Deviation
10
15 20
Time (Days)
25
30
35
-------
Vent Pipe to
Blower or Intake
Bentonlte
Seal
8' 6*
Perforated Pipe
In Gravel Layer
for Water/Nutrient
Introduction
Monitoring Wells
tt
o o o
QeotextBe
O O O
Monitoring
I-*— Probes -»|
-/--v
0 0
Vent Pipe to
Blower or Intake
Bentonlte
Seal
2-PVCPIpe
Perforated Pipe
Plywood
Wrapped In
Plastic
-^ Original
Water Table
Water Table
r After
x " Dewatering
Bentonlte
-------
Side View
-2'-
/
Monltorlng Wells
o
o
Vent
Pipe
Plan View
------- |