NEW APPROACHES AND METHODS FOR MANAGING

PETROLEUM HYDROCARBON SOURCE ZONES

Bettering Environmental Stewardship and Technology, Whistler, BC, May 25-27, 2016.

Ian Hers, Parisa JourabchiGolder Associates Ltd.

Sihota 2011

Golder 2015

Evaluate LNAPLMobility and Recovery

Mon

itorin

g

Stab

le, n

ot

reco

vera

ble

Mobile LNAPL Recovery (CUTEP)

Stable, Recoverable

Residual LNAPLRemediation

Exp

edite

d pr

oces

sC

onfir

med

M

igra

ting

Evaluate risks/concern

Establish objectives (risk-based, resource-based, timelines)

Develop LNAPLCSM

Golder Toolkits (2016) funded by CSAP & Shell

ITRC (2009) Guidance

NSZD = Natural source zone depletion; CUTEP = Clean-up to extent practicable; CSM – conceptual site model

Petroleum Hydrocarbon (LNAPL) Source Zone Remediation Framework

CUTEP based on key metrics tied to mobility (LNAPL transmissivity, LNAPL recovery, mobile LNAPL remaining)

Remedial strategy includes NSZD as appropriate

LA LNAPLWorkgroup (2015)

Multiple Lines of Evidence

GuidanceFactors

Two Big New IdeasPart I: LNAPL Mobility Lines of Evidence

Evaluation and TransmissivityPart II: Natural Source Zone Depletion

(NSZD) – Golder Toolkits for CSAP and Shell

Presentation Outline

GOLDER ASSOCIATES

Release Source

Vapor Phase

DissolvedPhase

LNAPL

Soil grains

Wetting fluid (e.g.,water) preferentially contacting the soil

Non-wetting fluid(e.g., air or LNAPL)

~1mm

From API Bulletin 18

LNAPL CSM

Lines of Evidence for Evaluation of LNAPL Mobility

Lines of evidence include evaluation of LNAPL:1. Presence/absence in wells2. Thickness (must be used carefully)3. Dissolved plume data4. Transmissivity5. Recovery data (asymptotic?)6. Seepage velocity7. Saturation (compare actual and residual saturation, i.e., lab tests)8. Entry pressure9. Weathering (Natural Source Zone Depletion or NSZD)

KEY POINT:

Multiple lines of evidence and commonality in results builds confidence in mobility conclusions

Should interpret in context of LCSM

and geology

COLLECT ADDITIONAL DATA• LNAPL transmissivity: baildown/skimmer• LNAPL recovery analysis• Hydraulic conductivity testing• Initial NSZD assessment?

TIER 2A

SPECIALIZED TESTING• Lab Tests (e.g., centrifuge/water drive)• Advanced Modeling• Advanced NSZD Assessment• Dye tracer

TIER 2B

SITE CHARACTERIZATION• Stratigraphy & hydrogeology• Hydrostratigraphs• Preferential pathways• LNAPL physical properties• Laser induced fluorescence (LIF)• Receptors

OBSERVATIONAL DATA• LNAPL thickness trends (seasonal data)• LNAPL presence/absence in wells• Dissolved plume trends

TIER 1

DEVELOP LCSM

Tiered LNAPL Mobility Framework

Under BC MoE Protocol 16 Tier 1 may be sufficient to indicate non-mobile, but should consider Tier 2A assessment (decision pts based

on indicators for potential mobile LNAPL & migrating LNAPL*)

* ITRC 2009 Definition

Confined LNAPL and Exaggerated Thickness

June 9, 2016 7

(ITRC, LNAPL Training Part 1 – Slide 53)

Initial Conditions -LNAPL/water table below bottom of confining clay unit

Rise in LNAPL/water table causes LNAPL to preferentially enter MW

KEY POINT:

LNAPL thickness represents confining pressures rather than recoverability or mobile LNAPL thickness

Tier 1: Observation Data: HydrostratigraphIIlustrating Confined Behavior

0

500

1,000

1,500

2,000

2,500

3,000

49

50

51

52

53

54

55

27-J

ul-0

5

24-N

ov-0

5

24-M

ar-0

6

22-J

ul-0

6

19-N

ov-0

6

19-M

ar-0

7

17-J

ul-0

7

14-N

ov-0

7

13-M

ar-0

8

11-J

ul-0

8

8-N

ov-0

8

8-M

ar-0

9

6-Ju

l-09

3-N

ov-0

9

3-M

ar-1

0

1-Ju

l-10

29-O

ct-1

0

26-F

eb-1

1

26-J

un-1

1

24-O

ct-1

1

21-F

eb-1

2

20-J

un-1

2

Appa

rent

NAP

L Th

ickn

ess

(mm

)LN

APL

Rec

over

ed (x

10-2

litre

s)

Elev

atio

n (m

asl)

Date

R4-MW27L

OWIAOICGWSScreen TopScreen BottomANTLNAPL Recovered

SA

ND

TILL

SA

ND

GROUND SURFACE

Tier 2A: LNAPL Transmissivity

LNAPL saturation correlated to LNAPL conductivity

Methods (ASTM E2856-13) Bail-down Skimmer Water-enhanced LNAPL recovery

LNAPL Transmissivity = Sum

nnn bKT ⋅=

Saturation shark fin

Residual LNAPL

Vertical equilibrium (VEQ) conditions in a sand tank

From ITRC (2009)KEY POINT:

Tn tells us more about potential recovery than LNAPL thickness (and possibly LNAPL mobility)

Residual LNAPL

Mobile LNAPL

Tier 2A: Transmissivity TestingASTM E2856-13

Maximum Drawdown

Skimming Test

* Sn here defined as drawdown following ASTM convention. Later defined as saturation.

Tier 2A Transmissivity Testing Results for Hydrostratigraph Example

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

50.2

50.4

50.6

50.8

51

51.2

51.4

51.6

51.8

-150 850 1850 2850 3850

LNAP

L Th

ickn

ess

(m)

Flui

d El

evat

ion

(m)

Time (min)

Elevation LNAPL/air interface (m)Elevation LNAPL/water interface (m)LNAPL thickness (m)

Test conducted over 3-day period using Spill-Buddy Pro

Initially 8 L removed (~ ½ from casing + filter pack); subsequently 0.55 L removed

Mobile LNAPL thickness estimated to = 0.3 m

KEY POINT:

Tn = 0.03 ft2/day – low Tn (less than ITRC range of hydraulic recoverable LNAPL of 0.1-0.8 ft2/day) despite LNAPL thickness of 2.8 m (points to thickness being an unreliable metric)

Tier 2A LNAPL Baildown Test Example

June 9, 2016 12

Confined response

0.96 m initial thickness

81% recovery in ~ 1 day

Tn = 1.3 ft2/day

KEY POINT:

All about drawdown-discharge relationship – art to

interpretation

Interpretation must consider behaviour. Baildown test result indicates mobile and potentially recoverable LNAPL

API LNAPL Transmissivity Workbook Used (unconfined, confined, perched)

Natural Source Zone Depletion

13

Definition:“NSZD is a combination of processes that reduce the mass of LNAPL in the subsurface”

Can occur through volatilization, biodegradation and dissolution

MNA and NSZD Toolkits Developed by Golder in BC

Tool kit #1 Case Study Toolkit

Tool kit #2 Monitoring and Prediction Toolkit

Tool kit #3 Remediation Technology Toolkit (in

progress)

Tool kit #4 Sustainability Toolkit (in progress

Key Questions:

How long take for sources to naturally deplete (e.g., to groundwater standards)?

How far will dissolved plume migrate?

How can we enhance attenuation?

Context: Draft BC MoE Technical Guidance 22 – 20 yr timeline for MNA

Toolkit #1 Outline

Conceptual Site Model

Multi-Site Database Studies

“(Big Data)”

BC Case Studies

Plume Lengths and Stability: US Multi-Site Study of Retail Sites with Gasoline Impacts*

Parameter Total Number of sites

Delineation criteria (µg/L)

Weighted mean on 90th and 50th

percentile of plume lengths (m)

Benzene 165 5 130 / 55

Parameter Total Number of sites

Decreasing plume lengths (%)

“Non-increasing” plume lengths

(%)Benzene 566 32 94

Summary of Plume Lengths

Summary of Stability Condition: Concentrations

Parameter Total Number of sites

Decreasing concentrations

(%)

“Non-increasing” concentrations

(%)Benzene 905 63 92

Summary of Stability Condition: Plume lengths

* From review of 13 multi-site or multi-plume studies (Connor et al., 2015)

California Multi-Site Study of Retail Gasoline Sites - Source Zone Attenuation (McHugh et al. 2014)

Data from 4,000 sites with monitoring from 2001-2011 with >= 4 years of data The estimated median attenuation rate for benzene = 0.18 per year (all sites,

most active remediation) When data analyzed separately for different technologies only slightly faster

attenuation rate, effect of remediation limited

Technology Constituent Increase in Source Attenuation Rate (%)

SVE benzene 28MTBE 11

Air Sparging benzene 53MTBE 22

ChemicalOxidation benzene 20

Pump & Treat MTBE 17

California Geotracker Database

MNA-only technology:72 Sites

median benzene attenuation rate of

0.13/yearTimeline to attenuationto 5 µg/L from 10 mg/L:

58 years

BC Case Study Sites Gasoline Releases (6 sites)

1.E-04

1.E-03

1.E-02

1.E-01

1.E+00

1.E+01

31-Ja

n-93

28-O

ct-9

5

24-Ju

l-98

19-A

pr-0

1

14-Ja

n-04

10-O

ct-0

6

6-Ju

l-09

1-Ap

r-12

27-D

ec-1

4

Benz

ene

(mg/

L)

W3

DW

DL

KEY POINT:

Long-term data indicates benzene decreased to < DWstd. (5 ug/L) at 5 of 6 sites in 20 yr, ethylbenzene did not reach std (2.4 ug/L) at any of the sites!

1.E+00

1.E+01

1.E+02

1.E+03

1.E+04

1.E+05

1.E+06

11-Aug-87 28-Oct-95 14-Jan-04 01-Apr-12G

roun

dwat

er C

once

ntra

tions

(ug/

L)

MW-14 and MW07-6

Benzene Ethylbenzene Xylenes

Benzene

Site 1 – remedial excavations Site 2 – extensive SVE

Toolkit #2 Outline

Step 1: Evaluation of

Progress of MNAof Dissolved

Plumes

Step 2: Use of Screening Models

and Measurements for

Estimation of NSZD

Step 3: Use of Multi-Process

Models for Evaluation of

MNA and Plume Attenuation

MNA basics – lines of evidence Statistical methods to evaluate plume behaviour

Parametric regression analysis (Regression Tool Developed)

Non-parametric method (Mann-Kendall)

GWSDAT Software Ricker method New ideas for monitoring frequency

Step 1: Evaluation of Progress of MNA of Dissolved Plumes

1

10

100

1000

10000

100000

1989 1994 1999 2004 2009 2014 2019

Con

cent

ratio

n (µ

g/L)

Date Sampled

MW-12 Ethylbenzene - Upgradient Source SamplesRegression Linefirst confidence intervalClean Up Goal

Step 1: New Tools for Evaluation of Progress of MNA of Dissolved Plumes

GWSDAT (V2.1) API www.api.org/GWSDAT

Ricker, J. 2008. A Practical Method to Evaluate Groundwater Contaminant Plume Stability. GWMR. Fall.

Create grid file in SURFERCalculate average and center of mass simple calc’s – concentration x coordinate

Trend plot for non monotonic dataSpatiotemporal smootherIncludes Ricker method

New tools may be useful but basic posting of data on map as important

Step 1: MNA of Dissolved Plumes –Monitoring Frequency

Frequently Asked Questions about Monitored Natural Attenuation in Groundwater, ESTCP, 2014 http://www.gsi-net.com/en/software/free-software/monitoring-and-remediation-optimization-systems-maros-version-3-0.html

Step 2: Control Volume Method (Based on Measurement Data) (from ITRC, 2009)

𝑅𝑅𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 ≈ 𝑞𝑞𝑑𝑑𝐻𝐻𝐻𝐻 𝐶𝐶𝑑𝑑

𝑅𝑅𝐵𝐵𝐷𝐷𝐷𝐷𝐵𝐵𝐷𝐷𝐷𝐷𝐵𝐵𝐵𝐵 ≈ 𝐻𝐻𝑊𝑊 𝑆𝑆𝑂𝑂2𝐷𝐷𝑂𝑂2 𝐶𝐶𝑂𝑂2 𝑧𝑧

𝑅𝑅𝐵𝐵𝐷𝐷𝐷𝐷𝑆𝑆𝐵𝐵𝐵𝐵 ≈ 𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 𝑏𝑏𝑀𝑀𝑏𝑏𝑀𝑀𝑏𝑏𝑏𝑏𝑏𝑏 𝑓𝑓𝑓𝑓𝑓𝑓 𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑒𝑒𝑓𝑓𝑓𝑓𝑏𝑏𝑀𝑀𝑏𝑏𝑏𝑏𝑏𝑏𝑎𝑎𝑒𝑒𝑓𝑓𝑓𝑓𝑀𝑀 𝑀𝑀𝑏𝑏𝑎𝑎 𝑏𝑏𝑏𝑏𝑓𝑓𝑒𝑒𝑓𝑓𝑀𝑀𝑏𝑏𝑀𝑀𝑓𝑓𝑓𝑓𝑓𝑓𝑏𝑏𝑀𝑀𝑒𝑒𝑏𝑏𝑓𝑓𝑏𝑏 𝑎𝑎𝑓𝑓𝑓𝑓𝑎𝑎𝑝𝑝𝑏𝑏𝑒𝑒𝑀𝑀

Volatilization /Unsaturated Zone Bio

Dissolution

Biodegradation

Step 2: Comparison of Methods for Estimation of Unsaturated Zone Biodegradation

Method Method Status Key Data Required Advantages Disadvantages

Gradient Well developed

[O2] gradient, porosity, moisture content, depth to source and water

table, native organic carbon

Simple method, uses

readily available data

Highly sensitive to soil moisture and water table

CO2 EffluxEmerging but rapidly developing

Surface CO2 efflux, 14C of CO2, δ13C of

CO2 (optional)

Direct measurement,

avoids estimation of

diffusion

Sensitive to natural soil respiration

Temperature NewTemperature profile,

soil thermal conductivity

Direct measurement,

potentially lower cost

Thermal conductivity difficult to estimate

Method calculates the biodegradation rate based on O2 flux estimated from O2 gradient and effective O2 diffusion coefficient

VZBL is a new model Microsoft® Excel Spreadsheet developed by Dr. John Wilson (Scissortail) and Golder Associates

Simple to use model with several features to improve estimation process Variable water table Multi-layered soil Optional baseline O2 respiration Mass balance for depletion

Step 2: Gradient Method – Vadose Zone Biodegradation Loss Model (VZBL)

Step 2: Gradient Method – Vadose Zone Biodegradation Loss Model (VZBL)

0.01

0.1

1

10

100

1000

0.01

0.1

1

10

100

1000

0 20 40 60 80 100TP

H C

onsu

med

(US

gal /

acr

e / y

r)

TPH

Con

sum

ed (g

/ m

2 /da

y)

Elapsed Time (years)

CO2 Efflux Expresssed as TPH Mass Consumed

g / m2 / yearUS gal / acre / year

1

10

100

1000

10000

100000

0 20 40 60 80 100

TPH

(mg

kg-1

)Elasped Time (years)

Maximum TPH at any Depth Interval

VZBL model provides information on time dependent changes in CO2 efflux

Step 2: CO2 Efflux Method CSM

Sihota et al. 2011

Method assumes that all hydrocarbons including methane are aerobically degraded by surface

Step 2: CO2 Efflux Method

Dynamic Chamber – Short-term Measurement (Infrared Gas Analyzer)(developed by UBC)

Static Trap – Longer-term Measurement (Soda-lime trap) (developed by Colorado State University)

Technology under rapid development

From E-Flux Website

0

500

1000

1500

2000

2500

Gal/a

cre/

yr

Dynamic Static Model

Database of Vadose Zone BiodegradationLoss Rates

CC C

W

W

WW

D

C = cold climate, W = warm climate, D = deep source (confined)

Two simple nomographs have been developed for estimation of mass loss by:1. Biodegradation/volatilization

from database of rates2. Dissolution

Based on estimate of LNAPL saturation or TPHconcentration, source dimensions and key parameters (groundwater flow rate, mass loss rate)

Requires soil core and TPH or saturation measurement

Step 2: Nomographs for Mass Depletion Time Screening

Simple fast preliminary screening method

Step 2: Nomograph for Mass Depletion Time – Biodegradation above water table

0.001

0.01

0.1

1

10

100

1000

10000

0.1 1 10 100

LNAP

L Sou

rce

Depl

etio

n Ti

me

(yr)

LNAPL Mass Loss Rate (g-TPH/m2-day)

LNAPL Source Depletion Time from LNAPL Saturation

T x Saturation = 2E-3 mT x Saturation = 4E-3 mT x Saturation = 8E-3 mT x Saturation = 2E-2 mT x Saturation = 4E-2 mT x Saturation = 8E-2 mT x Saturation = 2E-1 mT x Saturation = 4E-1 m

MHC = T x So x θ x ρ o x 103 Time = MHC / (ML x 365)

MHC = mass HC (g/m2) Time = Time for mass loss (yr)

T = Hydrocarbon thickness (m) ML = Mass loss rate (g/m2-day)

ρo = LNAPL (oil) density (kg/m3) θ = soil porosity (dimensionless)

So = Average LNAPL (oil) saturation (dimensionless)

Source Depletion Time ~ 40 yrs LNAPL thickness = 1 m

Residual LNAPL saturation = 0.1Bio rate = 1000 Gal/acre/yr(2 g-HC/m2-day)

Step 3: Use of Multi-Process Models for Evaluation of Natural Depletion and Plume Attenuation

Model

Processes in LNAPL Source Zone Vertical Diffusion from

LNAPL

Volatilization from LNAPL LNAPL

Dissolution LNAPL

Biodegradation Mass-Discharge

Factor

BIOSCREEN Yes Yes No No No

LNAST Yes No No Yes Yes

REMFUEL Yes Yes Yes No No

MIN3P-DUSTY Yes Yes No Yes Yes

RemFuel useful model for simulation of mass removal (remediation) but need to determine mass discharge (gamma) factor

LNAST useful model when volatilization could be important

Step 3: Use of Multi-Process Models for Evaluation of Natural Depletion and Plume Attenuation

Model

Processes in LNAPL Source Zone Vertical Diffusion from

LNAPL

Volatilization from LNAPL LNAPL

Dissolution LNAPL

Biodegradation Mass-Discharge

Factor

BIOSCREEN Yes Yes No No No

LNAST Yes No No Yes Yes

REMFUEL Yes Yes Yes No No

MIN3P-DUSTY Yes Yes No Yes Yes

RemFuel useful model for simulation of mass removal (remediation) but need to determine mass discharge (gamma) factor

LNAST useful model when volatilization could be important

Transmissivity is important new metric that should be considered in evaluating recoverability and mobility

NSZD is a significant process but predicted depletion timelines > 20 yrs (a few decades to ~ 100 years for large release)

Effect of remediation on degradation rates is variable, although BC data indicate benzene significantly attenuated

Range of tools may be used for prediction of NSZD: Regression analysis of time-series concentration data Biodegradation/volatilization mass loss tools (VZBL model, CO2 efflux) Nomographs and multi-process models for answering: How long will

source persist? How far will plume migrate? Toolkits #3 and #4 will evaluate performance and sustainability

of NSZD relative to active remediation technologies

Conclusions

Tool Name Description LinkBioCapacity.xlsx

Calculation of assimilative biodegradation

capacity in groundwater systemLink to be provided

BIOSCREENNatural Attenuation Decision Support

System

https://www.epa.gov/water-research/bioscreen-natural-

attenuation-decision-support-system

CV-NSZD Control Volume Based NSZD Tool Link to be provided

GWSDATVisualisation and interpretation of

groundwater monitoring data.

http://www.api.org/oil-and-natural-gas/environment/clean-

water/ground-water/gwsdat

LDRM LNAPL Distribution and Recovery Modelhttp://www.api.org/oil-and-natural-gas/environment/clean-

water/ground-water/lnapl/ldrm

LNAST API Interactive LNAPL Guidehttp://www.api.org/oil-and-natural-gas/environment/clean-

water/ground-water/lnapl/interactive-guide

MAROSMonitoring and Remediation Optimization

System

http://www.gsi-net.com/en/software/free-software/monitoring-

and-remediation-optimization-systems-maros-version-3-

0.html

Mass Flux Toolkit

Mass flux calculations from transect

groundwater data

http://www.gsi-net.com/en/software/free-software/mass-flux-

toolkit.html

NSZD Nomograph

Depletion time estimates from NSZD

processesLink to be provided

OWL Optimal Well Locator https://www.epa.gov/water-research/optimal-well-locator-owl

ProUCLStatistical Software for Environmental

Applicationshttps://www.epa.gov/land-research/proucl-software

RegressionMNA.xlsx

Regression Analysis Tool Link to be provided

REMFuelRemediation Evaluation Model for Fuel

hydrocarbons

https://www.epa.gov/water-research/remediation-evaluation-

model-fuel-hydrocarbons-remfuel

VZBL Vadose Zone Biodegradation Loss Model Link to be provided

Tools Reviewed or Developed

Questions

Release June 2016Please contact Parisa Jourabchi (pjourabchi@golder.comand Ian Hers ihers@golder.com if you would like copy

Step 2: Vadose Zone Biodegradation Rates Database from NSZD Studies (cont.)

Site and Reference Method Contami-

nant Type Soil Type

Depth to Water Table

or Contaminati

on (m)

Biodegradation Mass Loss Rate

(g-HC/m2-d)

Biodegradation Mass Loss Rate

(US Gal/acre-year)

#1 Former Refinery,

Vancouver, BC (Golder, 2015)

CO2 – Dynamic Chamber

Weathered middle

distillate

Silty Sand &

Silt

0.6 to 2.2 (highly

variable)

0.4 to 8.9Average = 2.4 (37

locations)

200 to 4,000 Average = 1,100

#2 Former Refinery,

Vancouver, BC (Golder, 2015)

CO2 – Static Trap

Weathered middle

distillate

Silty Sand &

Silt

0.6 to 2.2 (highly

variable)

0.1 to 5.2Average = 1.9(7 locations)

54 to 2,300Average = 870

#3 Traverse City; this report

Gradient Method

Aviation Fuel Sandy 5 0.18 to 0.86

(2 locations) 100 to 470#4 Traverse

City: Ostendorfand Kampbell

(1991)

Numerical Model and Soil

Gas ProfileAviation

Fuel Sandy 5 0.6 to 1.0 (4 locations) 320 to 550

#5 Bemidji Site; Sihota et al.

(2011)CO2 – Dynamic

Chamber Oil Glacial outwash 6 to 7 3.3

(average) 1,600

#6 Bemidji Site; Sihota et al.

(2011)

Numerical Model and Soil

Gas ProfileOil Glacial

outwash 6 to 7 1.6 to 4.4 780 to 2,100

#7&8 Six Sites in Yukon and

Alberta; Porter (2014)

CO2 Efflux –Dynamic Chamber

Oil, natural gas liquids and diesel

N/A N/A0.24 to 4.31

0.29 to 2.52

(163 locations)

120 to 2,1001

140 to 1,2002

#9 Refinery US Site; McCoy et

al. (2014) CO2 Efflux –Static Trap Fuels Sandy

Alluvium N/A 2.7 to 26(20 locations) 1,300 to 13,000

Step 2: Vadose Zone Biodegradation Rates Database from NSZD Studies

Site and Reference Method

Contami-nantType

Soil Type

Depth to Water Table

or Contaminat

ion (m)

Biodegradation Mass Loss Rate

(g-HC/m2-d)

Biodegradation Mass Loss

Rate (US Gal/acre-

year)#10 Six US Sites;

McCoy et al.(2012)

CO2 Efflux –Static Trap Fuels N/A N/A

1.3 to 37(75

locations)660 to 18,000

#11 US Site Gaitoet al. (2015)

CO2 Efflux –Static Trap N/A N/A ~ 5 0.53 to 1.9

(2 locations) 260 to 910

#12 US Site Gaitoet al. (2015)

CO2 Efflux –Dynamic Chamber

N/A N/A ~ 5 0.31 to 1.(2 locations) 150 to 900

#13 & 14 Victoria, Australia

McDonald et al.(2015) – Site 1

CO2 Efflux –Static Trap Gasoline Clay with Sand

Lenses

Shallow (average of

2) Deep (~ 4)

Shallow = 1.8

Deep = 0.1Shallow = 830

Deep = 46

#15 Victoria, Australia Site McDonald et

al.(2015) – Site 2

CO2 Efflux –Static Trap Gasoline Bedrock 8 - 10 0.38 170

Sweeney et al.(2014) Temperature Gasoline N/A N/A ~ 0.5 N/A

#16 North Battleford,

Saskatchewan; Hers et al. (2014)

Numerical Model and Soil Gas Profiles

Gasoline Glacial Till 3.0 0.7 to 1.3 370 to 700

Step 2: Vadose Zone Biodegradation Rates Database from NSZD Studies (cont.)

Site and Reference Method Contaminant

TypeSoil Type

Depth to Water Table

or Contaminati

on (m)

Biodegradation Mass Loss Rate

(g-HC/m2-d)

Biodegradation Mass Loss Rate

(US Gal/acre-year)

#17 Beaufort, South

Carolina; Lahvis et al.

(1999)

Numerical Model and Soil Gas Profiles

GasolineSilts and

Fine Sands

3.3 0.66 to 2.36 350 to 1,200

#18 Shell Carson

Facility, CA: LA LNAPLWorkgroup

(2015)

CO2 Static Trap Gasoline

Clay with sandy layers

Not reported0.92 to 8.9

Average = 2.8(8 locations)

415 to 4,000

#19 Tesoro Hynes

Facility, CA: LA LNAPLWorkgroup

(2015)

CO2 Static Trap Gasoline

Sand to Silty Sand

Not reported0.27 to 5.9

Average = 2.4(7 locations)

120 to 2,660