Methodology for Estimating Times of 

Remediation Associated with Monitored 

Natural Attenuation

By Francis H. Chapelle, Mark A. Widdowson, J. Steven Brauner, 

Eduardo Mendez III, and Clifton C. Casey

U.S. Geological Survey

Water-Resources Investigations Report 03–4057

Prepared in cooperation with the

SOUTHERN DIVISION, NAVAL FACILITIES ENGINEERING COMMAND and the

NAVAL FACILITIES ENGINEERING SERVICE CENTER

Columbia, South Carolina

2003
U.S. DEPARTMENT OF THE INTERIOR

GALE A. NORTON, Secretary

U.S. GEOLOGICAL SURVEY

Charles G. Groat, Director

Use of trade, product, or firm names in this publication is for descriptive purposes only 

and does not imply endorsement by the U.S. Government.

For additional information 

write to: 

District Chief 

U.S. Geological Survey

720 Gracern Road, Suite 129

Columbia, SC 29210-7651

email: dc_sc@usgs.gov

Additional information about water resources in South Carolina is available on the 

internet at http://sc.water.usgs.gov

Copies of this report can be 

purchased from:

U.S. Geological Survey

Branch of Information Services

Box 25286, Denver Federal Center

Denver, CO 80225-0286

1-888-ASK-USGS (275-8747)
Contents III

CONTENTS

Abstract...................................................................................................................................................................................... 1

Introduction................................................................................................................................................................................ 2

Purpose and Scope ........................................................................................................................................................... 4

Natural Attenuation of Petroleum Hydrocarbons ...................................................................................................................... 4

Biodegradation Processes................................................................................................................................................. 4

Aerobic Oxidation.................................................................................................................................................. 4

Anaerobic Oxidation .............................................................................................................................................. 5

Biodegradation of Methyl Tertiary-Butyl Ether..................................................................................................... 6

Sorption Processes ........................................................................................................................................................... 6

Advection and Dispersion................................................................................................................................................ 6

Volatilization .................................................................................................................................................................... 7

Natural Attenuation of Chlorinated Ethenes.............................................................................................................................. 7

Biodegradation Processes................................................................................................................................................. 7

Reductive Dechlorination....................................................................................................................................... 8

Aerobic Oxidation.................................................................................................................................................. 9

Anaerobic Oxidation ............................................................................................................................................ 10

Aerobic Cometabolism......................................................................................................................................... 11

Redox Conditions and the Biodegradation of Chlorinated Ethenes in Ground-Water Systems .................................... 12

Delineating the Distribution of Redox Processes in Ground-Water Systems ...................................................... 13

Organic Carbon Substrates that Support Reductive Biodegradation ................................................................... 16

Daughter Products Indicating Biodegradation ..................................................................................................... 16

Sorption Processes ......................................................................................................................................................... 16

Measuring Biodegradation Rates ................................................................................................................................... 17

Sources of Uncertainty in Biodegradation Rate Estimates ............................................................................................ 18

Time of Remediation Associated with Natural Attenuation.................................................................................................... 19

Summing the Processes that Contribute to Natural Attenuation.................................................................................... 19

Natural Attenuation Capacity......................................................................................................................................... 19

Distance of Stabilization ................................................................................................................................................ 20

Time of Stabilization...................................................................................................................................................... 21

Time of Nonaqueous Phase Liquid Dissolution............................................................................................................. 21

Time of Remediation Software ................................................................................................................................................ 23

Overview of Natural Attenuation Software ................................................................................................................... 25

Data Requirements and Input Using Natural Attenuation Software.............................................................................. 26

Time of Remediation Examples............................................................................................................................................... 31

Gasoline Nonaqueous Phase Liquid Example: Laurel Bay, South Carolina ................................................................. 31

Chlorinated Ethene Example: Kings Bay, Georgia........................................................................................................ 37

Summary.................................................................................................................................................................................. 46

References................................................................................................................................................................................ 47
IV Contents

FIGURES

1. Diagrams showing conceptualization of the time of remediation problem ................................................................... 3

2. Schematic diagram showing how molecular hydrogen drives reductive dechlorination............................................. 13

3. Graph showing characteristic H2 concentrations associated with different terminal 

electron-accepting processes....................................................................................................................................... 13

4. Flowchart for deducing terminal electron-accepting processes in ground-water systems........................................... 15

5–7. Graphs showing: 

5. Effects of natural attenuation capacity on contaminant concentration declines along 

ground-water flowpaths...................................................................................................................................... 20

6. Effects of natural attenuation capacity, initial contaminant concentration, organic matter content of 

aquifer material, and contaminant composition on times of stabilization.......................................................... 22

7. Time of nonaqueous phase liquid (NAPL) dissolution versus NAPL mass, and NAPL mass 

in differing aquifer thickness.............................................................................................................................. 24

8. Flowchart showing how NAS can be applied to time of remediation problems.......................................................... 25

9. Initial computer screens showing NAS and the hydrogeology data entry of NAS...................................................... 27

10. NAS computer screens of distance and time of stabilization screens, and graphical representation of 

time-of-stabilization calculations ................................................................................................................................ 28

11. NAS computer screens of data input for nonaqueous phase liquid time-of-dissolution calculations, 

and example of time-of-dissolution results ................................................................................................................. 30

12. Site map, locations of observation wells, and potentiometric surface of the Laurel Bay site, South Carolina ........... 32

13. NAS computer screens of summary of contaminant data, redox data, and summary of biodegradation rate 

and natural attenuation capacity estimates made from these data for the Laurel Bay site.......................................... 33

14. NAS computer screens of summary of time-of-stabilization and distance of stabilization estimates, 

and graphical view of time-of-stabilization estimates for the Laurel Bay site............................................................ 34

15. Graphs showing predicted benzene concentrations using time of stabilization estimates at well MW-8 

plotted versus measured benzene concentrations over time at the Laurel Bay site .................................................... 36

16. Graphs showing estimated time of nonaqueous phase liquid dissolution for MTBE, benzene, 

and total BTEX using NAS, and observed source-area contaminant concentration decreases 

in source-area well EX-1 at the Laurel Bay site ......................................................................................................... 37

17. Map showing location of total chlorinated ethene plume prior to in situ oxidation and locations of 

monitoring wells.......................................................................................................................................................... 38

18–20. Computer screens showing: 

18. Summary of hydrologic, contaminant, and redox characteristics of the Kings Bay site .................................... 39

19. Graph depicting discontinuity in biodegradation rates between redox zones, and summary table 

of estimated biodegradation rates at the Kings Bay site..................................................................................... 40

20. Summary of time and distance of stabilization estimates for the Kings Bay site ............................................... 41

21. Graph showing estimated time of stabilization for plume following nonaqueous phase liquid (NAPL) 

removal and time of NAPL dissolution versus NAPL mass at the Kings Bay site..................................................... 42

22–25. Graphs showing observed concentration changes: 

22. At well USGS-3 in the zone of Fenton’s reagent injection, and well KBA-11-13A, which are 160 feet 

downgradient of the injection zone .................................................................................................................... 43

23. At wells USGS-9 and USGS-11, which are 380 feet downgradient of the injection zone ................................. 44

24. Compared to NAS-simulated changes at well KBA-11-13A.............................................................................. 45

25. Compared to NAS-simulated changes at wells USGS-9 and USGS-11 ............................................................. 46

TABLE

1. Ground-water chemistry constituents used to identify microbial redox processes in ground-water systems, 

and common methods of analysis ............................................................................................................................... 14
Contents V

CONVERSION FACTORS, TEMPERATURE, DATUMS, ABBREVIATIONS, AND ACRONYMS

Temperature in degrees Fahrenheit (° F) may be converted to degrees Celsius (°C) as follows:

°C = (° F - 32)/1.8

Vertical coordinate information is referenced to the North American Vertical Datum of 1988 (NAVD 88); 

horizontal coordinate information is referenced to the North American Datum of 1927 (NAD 27).

Multiply By To obtain

inch per year (in/yr) 25.4 millimeter per year (mm/yr)

foot (ft) 0.3048 meter (m)

foot per day (ft/d) 0.3048 meter per day (m/d)

foot per year (ft/yr) 0.3048 meter per year (m/yr)

pounds (lbs) 0.4536 kilogram (kg)

gallon (gal) 3.785 liter (L)

Abbreviations

< less than

> greater than

mg/L milligram per liter

Mn/L nanomoles per liter

μg/L micrograms per liter

Acronyms

BTEX benzene, toluene, ethylbenzene, and xylene

BTX benzene, toluene, and xylene

DCE dichloroethene

DO dissolved oxygen

DOC dissolved organic carbon

DOS distance of stabilization

MCL maximum concentration level

MNA monitored natural attenuation

MTBE methyl tertiary-butyl ether

NAC natural attenuation capacity

NAPL nonaqueous phase liquid

NAS Natural Attenuation Software

PCE perchloroethene 

POC particulate organic carbon

RCC regulatory compliance concentration

TCE trichloroethene

TEAP terminal electron-accepting processes

TEX toluene, ethylbenzene, and xylene

TOC total organic carbon

TOR time-of-remediation problem

TOS time of stabilization

USEPA U.S. Environmental Protection Agency

USGS U.S. Geological Survey

VC vinyl chloride
Abstract 1

Methodology for Estimating Times of Remediation 

Associated with Monitored Natural Attenuation

By Francis H. Chapelle1, Mark A. Widdowson2, J. Steven Brauner2, Eduardo Mendez III 2, 

and Clifton C. Casey3

ABSTRACT

Natural attenuation processes combine to 

disperse, immobilize, and biologically transform 

anthropogenic contaminants, such as petroleum 

hydrocarbons and chlorinated ethenes, in ground-water 

systems. The time required for these processes to lower 

contaminant concentrations to levels protective of 

human health and the environment, however, varies 

widely between different hydrologic systems, different 

chemical contaminants, and varying amounts of 

contaminants. This report outlines a method for 

estimating timeframes required for natural attenuation 

processes, such as dispersion, sorption, and 

biodegradation, to lower contaminant concentrations 

and mass to predetermined regulatory goals in groundwater systems.

The time-of-remediation (TOR) problem 

described in this report is formulated as three 

interactive components: (1) estimating the length of a 

contaminant plume once it has achieved a steady-state 

configuration from a source area of constant 

contaminant concentration, (2) estimating the time 

required for a plume to shrink to a smaller, regulatoryacceptable configuration when source-area 

contaminant concentrations are lowered by engineered 

methods, and (3) estimating the time needed for 

nonaqueous phase liquid (NAPL) contaminants to 

dissolve, disperse, and biodegrade below 

predetermined levels in contaminant source areas. This 

conceptualization was used to develop Natural 

Attenuation Software (NAS), an interactive computer 

program that estimates times of remediation associated 

with petroleum hydrocarbon and chlorinated ethenecontaminated aquifers. NAS was designed as a 

screening tool and requires the input of detailed site 

information about hydrogeology, redox conditions, and 

the distribution of contaminants. Because NAS is based 

on numerous simplifications of hydrologic, microbial, 

and geochemical processes, the program may introduce 

unacceptable errors for highly heterogeneous 

hydrologic systems. In such cases, application of the 

TOR framework outlined in this report may require 

more detailed, site-specific digital modeling. The NAS 

software may be downloaded from the Web site 

http://www.cee.vt.edu/NAS/.

Application of NAS illustrates several general 

characteristics shared by all TOR problems. First, the 

distance of stabilization of a contaminant plume is 

strongly dependent on the natural attenuation capacity 

of particular ground-water systems. The time that it 

takes a plume to reach a steady-state configuration, 

however, is independent of natural attenuation capacity. 

Rather, the time of stabilization is most strongly 

affected by the sorptive capacity of the aquifer, which 

is dependent on the organic matter content of the 

aquifer sediments, as well as the sorptive properties of 

individual contaminants. As a general rule, a high 

sorptive capacity retards a plume’s growth or 

shrinkage, and increases the time of stabilization. 

Finally, the time of NAPL dissolution depends largely 

on NAPL mass, composition, geometry, and 

hydrologic factors, such as ground-water flow rates.

1 U.S. Geological Survey, Columbia, South Carolina. 2 Virginia Polytechnic Institute and State University, Department of Civil Engineering, Blacksburg, Virginia. 3 Southern Division Naval Facilities Engineering Command, North Charleston, South Carolina.
2 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

An example TOR analysis for petroleum 

hydrocarbon NAPL was performed for the Laurel Bay 

site in South Carolina. About 500 to 1,000 pounds of 

gasoline leaked into the aquifer at this site in 1991, and 

the NAS simulations suggested that TOR would be on 

the order of 10 years for soluble and poorly sorbed 

compounds, such as benzene and methyl tertiary-butyl 

ether (MTBE). Conversely, TOR would be on the order 

of 40 years for less soluble, more strongly sorbed 

compounds, such as toluene, ethylbenzene, and 

xylenes (TEX). These TOR estimates are roughly 

consistent with contaminant concentrations observed 

over 10 years of monitoring at this site where benzene 

and MTBE concentrations were observed to decrease 

rapidly and are approaching regulatory maximum 

concentration limits, whereas toluene, ethylbenzene, 

and xylene concentrations decreased at a slower rate 

and have remained relatively high. 

An example TOR analysis for chlorinated ethene 

NAPL was performed at the Kings Bay, Ga., site. 

NAPL removal action by in situ oxidation was 

performed here, and the NAS simulations indicated 

that TOR was highly dependent upon location within 

the plume (upgradient areas remediate faster than 

downgradient areas), and the organic carbon content 

(sorptive capacity) of the aquifer. In general, the NASestimated decreases in chlorinated ethene 

concentrations at different locations within the Kings 

Bay plume are roughly consistent with observed 

decreases over 3 years of monitoring. This comparison, 

however, also shows that observed patterns of 

contaminant concentration changes are much more 

complex than indicated by NAS. This, in turn, 

illustrates the general principle that hydrologic 

complexities of ground-water systems are not fully 

accounted for in simulation tools like NAS, and that 

TOR estimates made with such tools are inherently 

uncertain. Thus, although TOR estimates can be useful 

for evaluating different remediation strategies and 

goals for particular sites, these estimates should always 

be verified with site monitoring.

INTRODUCTION

Monitored natural attenuation (MNA) is the 

deliberate use of naturally occurring biodegradation, 

sorption, and dispersion processes to remediate 

contaminated ground-water systems. MNA is 

appropriate to use as a remedial strategy when “...it will 

meet site remediation objectives within a timeframe 

that is reasonable compared to that offered by other 

methods” (U.S. Environmental Protection Agency, 

1999). Thus, estimating the amount of time required for 

natural attenuation processes to attain regulatory 

objectives is useful when evaluating MNA as a 

remedial technology. This report outlines a conceptual 

framework and a methodology for estimating the 

amount of time required for natural attenuation 

processes to lower contaminant levels to given 

regulatory goals.

In concept, estimating the length of time required 

for natural processes to remove a particular 

contaminant from a ground-water system is a simple 

mass-balance problem. If the initial mass of 

contaminant, Mo, (units of mass) present in a groundwater system is known, and if the rate that the 

contaminant is transformed or destroyed by natural 

attenuation processes, RNA, (units of mass removed per 

unit time) is known, a mass-balance equation can be 

written:

[Mo – (RNA • t)] = Mremaining ,

where t is time and Mremaining is the contaminant mass 

remaining at any time t. It follows that a TOR can be 

defined as the time required to lower contaminant mass 

below a given threshold (Mthreshold):

[Mo – (RNA • t)] = Mthreshold ,

or

t

remediation = [Mo – Mthreshold]/RNA = TOR , (1)

where the TOR is defined explicitly as given in 

equation 1, and refers to the length of time needed for 

a given mass of initial contaminant (Mo) to be lowered 

below a given regulatory threshold (Mthreshold) by the 

rate of natural attenuation processes (RNA) occurring in 

a ground-water system. 

In addition to providing a working definition of 

TOR, equation 1 also indicates the kinds of information 

necessary to make remediation time estimates. This 

information includes an estimate of the mass of 

contaminant present, and an estimate of the rate of 

ongoing natural attenuation processes acting on the 

contaminant. The principal technical problem, 

therefore, is to obtain reliable estimates of these 

parameters. Clearly, the reliability of any remediation 

time estimates will be directly linked to the reliability 

of the parameter estimates. In addition, equation 1 
Introduction 3

shows that determining remediation times requires the 

definition of an acceptable contaminant mass 

threshold. This threshold must be predetermined to 

make remediation time estimates.

In practice, however, the problem is much more 

complex then indicated by equation 1. The rate of RNA, 

particularly rates of biodegradation, may vary with time, 

so that the rate that contaminants are destroyed may not 

be constant (RNA • t) but rather a function of time

Furthermore, many instances of ground-water 

contamination by petroleum hydrocarbons and 

chlorinated solvents can be traced to the release of 

NAPLs at or near land surface. These NAPLs typically 

seep downward through the unsaturated zone, reach the 

underlying saturated ground-water system, and 

dissolve to form contaminant plumes. Initially, 

contaminant plumes tend to grow and expand over time 

as NAPLs dissolve. At a certain point, however, rates of 

NAPL dissolution tend to come into equilibrium with 

the rate of contaminant removal by natural attenuation 

processes, and the plume comes into a quasi steadystate configuration. If the NAPL source continues to 

dissolve over time until it is exhausted, the contaminant 

plume will also shrink. Alternatively, some of the 

NAPL source might be removed by engineering 

methods (excavation, in situ oxidation, etc.), in which 

case the contaminant plume would tend to shrink faster 

than if the NAPL were left in place. Because of these 

complexities, equation 1 is useful primarily as a 

definition of “time of 

remediation” and is not 

suited to solve actual 

TOR problems. 

To be practical, it is 

useful to divide the TOR 

problem into three 

distinct, but related, 

components (fig. 1). The 

first component is termed 

distance of stabilization

(DOS), and involves 

estimating the maximum 

distance a contaminant 

plume can migrate from a 

source area of given 

contaminant concentration. If the maximum 

distance that a plume migrates does not impact 

sensitive receptors so that no further remediation is 

deemed necessary, then the TOR is by default zero. 

Although cases of this kind may be the exception rather 

than the rule, it is important to be able to identify them 

when they do occur. In addition, DOS estimates can be 

useful in estimating contaminant concentrations in a 

source area that will preclude contaminant transport to 

nearby sensitive receptors. These estimates can be used 

to determine source-area remediation goals for 

engineered removal actions.

The second component is termed time of 

stabilization (TOS; fig. 1). This refers to the time it 

takes for a plume to shrink to a smaller configuration if 

a contaminant source is wholly or partially removed. In 

practice, this situation occurs when engineered 

methods are being considered to remediate 

contaminant source areas, and it is desirable to estimate 

the length of time it will take the contaminant plume to 

shrink to an acceptable configuration.

The third component is the time of NAPL 

dissolution (fig. 1). This refers to the time it will take 

for a NAPL body of given mass and composition to 

dissolve and disperse to the point where predetermined 

water-quality standards are met. This is usually the 

most important component associated with NAPLcontaminated ground-water systems.

In this report, each of these components are 

developed separately for practical and computational 

convenience. In practice, however, these issues are 

interrelated, and each is an important component of 

estimating times of remediation for contaminated sites.

RNAdt

0

t

∫

⎝ ⎠ ⎜ ⎟ ⎜ ⎟ ⎛ ⎞

.

Figure 1. Conceptualization of the time of remediation problem.
4 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

Purpose and Scope

MNA is the careful use of naturally occurring 

contaminant-degrading and dispersing processes, in 

combination with environmental monitoring, to 

remediate contaminated ground-water systems (U.S. 

Environmental Protection Agency, 1997). All 

anthropogenic chemicals, including petroleum 

hydrocarbons, chlorinated solvents, metals, and 

radionuclides, are subject to natural attenuation 

processes. The effectiveness, however, of these 

processes and, thus, the time required for natural 

attenuation to remove environmental contamination, 

varies widely for different contaminants and for 

different ground-water systems (Rifai and others, 

1995). This variability is not random and depends on 

the hydrologic, biologic, and geochemical attributes of 

particular ground-water systems. Because these 

attributes can be measured and interpreted in a 

logically consistent way, it is possible to estimate 

remediation times associated with natural attenuation 

processes. The purpose of this report is to describe a 

methodology for estimating TORs associated with 

MNA, and TORs associated with combining MNA 

with engineered contaminant-removal systems. The 

scope of this report includes MNA of petroleum 

hydrocarbons and chlorinated ethenes. The report 

begins with an in-depth description of the processes 

that contribute to natural attenuation, shows how these 

processes can be quantified into mass-balance 

equations, and uses these mass-balance equations to 

make TOR estimates. 

NATURAL ATTENUATION OF 

PETROLEUM HYDROCARBONS

Biodegradation Processes

Biodegradation processes are an important 

component of the natural attenuation of petroleum 

hydrocarbons. These processes can transform toxic 

petroleum hydrocarbons, such as benzene, to 

environmentally innocuous compounds, such as carbon 

dioxide and water. Because (1) most petroleum 

products are a complex mixture of many hydrocarbons, 

and (2) different hydrocarbons are subject to widely 

varying biodegradation rates, however, these processes 

must be carefully assessed prior to applying MNA. 

The effect of biodegradation processes on the 

mobility of petroleum hydrocarbons released to 

ground-water systems, and particularly the role of these 

processes in degrading and attenuating contamination, 

have not always been appreciated. As recently as 1981, 

papers using quantitative modeling techniques for 

evaluating hydrocarbon mobility did not consider the 

effects of microbial processes on hydrocarbon 

attenuation (Yazicigil and Sendlein, 1981). 

By 1985, microbiologists had gathered clear 

evidence that biodegradation of petroleum 

hydrocarbons occurred in both aerobic and anaerobic 

aquifer systems. The most telling evidence that such 

processes were important, however, came from 

numerous field studies showing that petroleum 

hydrocarbons were selectively removed under a variety 

of conditions. One study in California (Hadley and 

Armstrong, 1991) surveyed 7,167 water-supply wells 

for evidence of chemical contamination. These 

researchers anticipated that petroleum hydrocarbon 

contamination, particularly benzene contamination, 

would be prevalent because gasoline spills had 

occurred from thousands of leaking underground tanks 

during the previous 50 years. To their surprise, 

however, very little evidence of benzene contamination 

of ground water was found. After reviewing the 

possible processes that could remove benzene from 

ground water, including sorption and evaporation, they 

concluded that biodegradation processes were the most 

likely reason for the puzzling “absence” of benzene. 

The realization that microbial processes were 

important in the fate and transport of petroleum 

hydrocarbons in ground-water systems led to a number 

of investigations during the late 1980s. These studies 

form a basis for evaluating biodegradation as a natural 

attenuation process and as a possible strategy for 

remediating hydrocarbon contamination in groundwater systems.

Aerobic Oxidation 

The ability of microorganisms to degrade 

petroleum hydrocarbons has been widely studied, and 

many of the biochemical pathways involved in 

degradation have been worked out in some detail. 

However, predicting how complex natural systems, 

particularly inaccessible ground-water systems, will 

react to hydrocarbon contamination is difficult. The 

shrinking of plumes containing benzene, toluene, 

ethylbenzene, and xylene (BTEX) in shallow groundwater systems had been widely reported during the 
Natural Attenuation of Petroleum Hydrocarbons 5

1980s, usually with little documented evidence. Barker 

and others (1987), however, reported the results of an 

experiment in which about 1,800 liters of ground water 

containing 2.4 mg/L benzene, 1.8 mg/L toluene, 

1.1 mg/L each of p-xylene, m-xylene, and o-xylene, 

and 1,280 mg/L chloride were injected into a shallow 

aerobic aquifer. The chloride was added so that it 

would act as a conservative tracer. The resulting plume 

was then monitored by a dense network of multilevel 

piezometers. Samples from the monitoring wells were 

collected each day for 3 days after injection and usually 

each month thereafter. 

By day 53, the combined effects of advection and 

dispersion had moved the chloride tracer plume from 

between 3 and 16 ft along the natural gradient 

prevailing in the aquifer, spreading to about three times 

its initial size as it moved. The benzene component of 

the plume reacted similarly to chloride in the first 53 

days, spreading as it moved downgradient. The toluene 

component, however, was actually smaller at day 53 

than at the beginning of the experiment. By day 108, 

the toluene component of the plume had virtually 

disappeared; furthermore, the benzene component of 

the plume had shrunk noticeably relative to the chloride 

tracer. By vertically integrating concentrations of 

benzene, toluene, and xylene (BTX) in the plume, the 

mass of each compound present as a function of time 

could be calculated. The mass of chloride, as expected, 

changed very little. The masses of each BTX 

compound, however, decreased rapidly. By 108 days, 

the mass of toluene and the BTEX isomers had 

decreased to nearly zero. Although benzene was more 

resistant to degradation than the other compounds, the 

mass of remaining benzene was virtually zero 400 days 

after injection. 

This experiment differs from actual petroleum 

hydrocarbon spills in several ways. First, the large mass 

of aliphatic and alicyclic hydrocarbons present in all 

fuels were not included in the experiment. Thus, any 

effects of these compounds on BTX degradation were 

absent from the experiment. Because aliphatic 

compounds, however, are not soluble nor transported 

downgradient of petroleum spills in aqueous solution, 

this experiment accurately simulates conditions 

downgradient of petroleum spills. In part because of 

this lack of aliphatic hydrocarbons, aerobic conditions 

prevailed in the aquifer throughout the experiment. As 

aerobic bacteria may be more efficient hydrocarbon 

utilizers than anaerobic bacteria, this experiment 

probably records degradation rates as high as any that 

would be observed in ground-water systems. 

The significance of the experiment reported by 

Barker and others (1987) is that it verified the 

numerous observations that BTX compounds were 

actively biodegraded in ground-water systems. 

Because of the aerobic conditions and the lack of an 

immiscible hydrocarbon phase capable of leaching 

BTX compounds over time, the time required for 

complete degradation in this experiment, however, was 

probably less than that required in most petroleumproduct spills. 

Anaerobic Oxidation 

One of the first consequences of petroleum 

hydrocarbon contamination of shallow ground-water 

systems is the establishment of anaerobic conditions 

near the plume. One well-documented example of this 

was a crude oil spill that occurred near Bemidji, Minn., 

in August 1979. Prior to the spill, the aquifer was 

aerobic (dissolved oxygen (DO) was about 10 mg/L) 

and did not contain substantial concentrations of 

methane. Soon after the spill, however, increased levels 

of microbial respiration created anaerobic conditions 

near the oil lens, and methane concentrations began to 

increase. This, in turn, provided an opportunity for 

studying the anaerobic degradation of petroleum 

hydrocarbons in an anaerobic ground-water system 

under field conditions (Baedecker and others, 1988; 

1993). Concentrations of the BTEX compounds were 

observed to decrease substantially, as well as all 

alkylbenzene compounds. Because of the proximity to 

the oil lens, these concentration decreases could not be 

attributed to hydrodynamic processes and were 

interpreted as reflecting anaerobic microbial 

degradation (Cozzarelli and others, 1988). 

Further evidence that microbial processes are 

involved with degradation is provided by the observed 

distribution of organic acids in the anaerobic plume. 

High concentrations of organic acids, particularly 

acetic acid, were observed near the oil lens. These acids 

have been shown to be intermediate products of 

anaerobic benzene and toluene degradation in 

laboratory experiments, and their presence is evidence 

that anaerobic microbial processes were actively 

degrading the hydrocarbons in this system. 

Downgradient of the oil lens, concentrations of the 

organic acids decreased as Fe(III) reduction replaced 

FHC methanogenesis as the principal anaerobic 
6 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

metabolic process (Baedecker and others, 1988) and 

Fe(III) reduction (Lovley and others, 1989). 

Biodegradation of Methyl Tertiary-Butyl Ether

MTBE was introduced in the 1970s as an octane 

replacement for tetraethyl lead, and is currently added 

to 30 percent of the gasoline consumed in the United 

States (Squillace and others, 1997). MTBE is a fuel 

oxygenate that lowers carbon monoxide emissions in 

accordance with the Clean Air Acts Amendment of 

1990. MTBE is highly soluble in water, is readily 

transported in ground- and surface-water systems, has 

a low taste and odor threshold, and is tentatively 

classified by the U.S. Environmental Protection 

Agency (USEPA) as a possible human carcinogen. For 

these reasons, the potential contamination of drinking 

water supplies with MTBE has rapidly become a 

national concern. This concern has prompted the 

USEPA to establish a drinking water advisory of 20 to 

40 μg/L for MTBE.

Leakage of MTBE-containing gasoline from 

underground storage tanks, and the migration of this 

gasoline to the water table can produce very high 

concentrations of MTBE in ground water. At a gasoline 

spill site in Beaufort, S.C., for example, contaminated 

ground water containing more than 10,000 μg/L 

dissolved MTBE was reported (Landmeyer and others, 

1998). As this contaminated ground-water body passed 

through streambed sediments prior to discharging to a 

small stream, however, MTBE concentrations 

decreased dramatically due to microbial activity 

(Landmeyer and others, 2001). MTBE is commonly 

observed to biodegrade relatively slowly in groundwater systems, whereas biodegradation rates are much 

faster in surface-water sediments.

Sorption Processes

Sorption refers to the partitioning of a solute 

between the aqueous and solid phases present in 

aquifers. The solute may be adsorbed onto the surfaces 

of aquifer materials, or may be absorbed into the 

interior of the sorbent matrix. Thus, sorption can act 

either to remove solute from solution (adsorption), or to 

add solute to solution (desorption). These combined 

adsorption-desorption processes are called reversible 

sorption and can have important effects on the transport 

of solutes in ground-water systems. When a plume first 

develops from a new contaminant source, the sorptive 

capacity of the aquifer sediments is largely unfilled, 

and as solutes migrate away from the source, they tend 

to adhere to aquifer sediments, gradually saturating the 

sorptive capacity of the aquifer material. This causes 

the transport of contaminants to be initially retarded 

relative to the velocity of ground water and, as time 

passes, the sorptive capacity of the sediments becomes 

saturated and the effects of retardation become less 

effective. The principal effect of sorption on the 

development of plumes is to retard the spread of 

contaminants, however, contaminant spread in not 

deterred. The steady-state configuration of plumes 

(that is, their extent when contaminant delivery from 

the source is balanced by the sum of the natural 

attenuation mechanisms) is independent of the sorption 

capacity of the aquifer. Low sorptive capacity aquifers, 

however, will reach the steady-state configuration 

sooner than high sorptive capacity aquifers.

Desorption, the processes by which solutes are 

released from contaminated aquifer sediments, is an 

important factor in any remediation effort. When 

aquifer sediments contain large amounts of 

contaminant mass in the adsorbed phase, they can 

continue to be sources of contaminants for long periods 

of time. This contributes to the contaminant “rebound” 

effect commonly observed in pump-and-treat 

remediation systems once the pumps are turned off, and 

can greatly increase the time needed to effect site 

cleanup. As a general rule, plumes develop rapidly in 

low-sorption capacity aquifers, and can be remediated 

rapidly as well. Conversely, in high-sorption capacity 

aquifers, plumes develop more slowly, and take longer 

to remediate. For these reasons, remediation strategies 

should include a quantitative evaluation of aquifer 

sorption capacity. 

Advection and Dispersion

Advection refers to the migration of solutes 

resulting from the movement of the fluid phase in 

which the solutes are dissolved. In sandy aquifers 

with relatively high horizontal hydraulic conductivity 

(K >10 ft/d), advection is the dominant transport 

mechanism for relatively soluble contaminants such as 

chlorinated ethenes. If subsurface sediments were 

homogeneous, consideration of advective transport 

alone would account for much of the transport behavior 

of subsurface contaminants. However, the lithology 

and, thus, the hydraulic conductivity of ground-water 

systems, are highly heterogeneous. This heterogeneity 

causes variations in solute transport speed. If it were 
Natural Attenuation of Chlorinated Ethenes 7

possible to account for these variations, then advection 

could be used by itself to describe solute transport. 

Because these variations in advective transport are so 

complex, however, a meaningful account of them is not 

practical.

The traditional method for incorporating the 

unknowns associated with advective transport is by 

using what is termed hydrodynamic dispersion. 

Dispersion is a mechanical process that causes a solute 

to occupy a larger volume of porous media than would 

be expected by advection alone. In part, although 

dispersion accounts for the tendency of solutes to 

spread along concentration gradients, thus increasing 

the volume of the plume, dispersion is also a 

mathematical way of accounting for the uncertainty 

associated with hydraulic conductivity found in all 

ground-water systems. The most widely used form of 

the coefficient of hydrodynamic dispersion is:

D = Doτ + αν, (2)

where Do is the diffusion coefficient (L2T-1) for the 

solute in question, τ is a dimensionless tortuosity 

factor, α is the dispersivity of the porous media (L), and 

ν is pore-water velocity (LT-1). Under conditions where 

ground-water flow is substantial, the first term of 

equation 2 (diffusion) is negligible compared to the 

second term, and it reduces to:

D = αν. (3)

Thus, dispersion (advective “mixing”) of a solute is 

proportional to the speed of ground-water flow (ν) and 

the ability of the aquifer material to “mix” the water 

(α). In reality, dispersivity is a representation of 

uncertainty in the hydraulic conductivity of aquifers, 

and the uncertainty of ground-water velocity to 

transport solutes. Because this uncertainty increases 

exponentially with distance along a given flowpath, 

dispersivity also increases as the plume increases. This 

scale-dependent behavior is a characteristic feature of 

dispersivity (Gelhar and others, 1992).

Volatilization

When petroleum hydrocarbons are spilled onto 

soil, they tend to migrate downward under the pull of 

gravity until reaching the water table. Because gasoline 

and other fuels are lighter than water, they spread by 

forming a lens of free-phase hydrocarbon liquid 

floating on the water table. Above this lens, gases in the 

unsaturated zone tend to be at or near saturation with 

the more volatile components that are present in the 

hydrocarbon. This is sometimes referred to as the zone 

where the air is at “residual saturation” with respect to 

the hydrocarbon. The diffusive transport of volatile 

hydrocarbons upward from the zone of residual 

saturation is one component of natural attenuation.

In addition to volatilization, the unsaturated zone 

is conducive to microbial growth. The volatile 

components of petroleum hydrocarbons, such as shortchained alkanes, cyclic alkanes, and aromatic 

components, are readily oxidized by many kinds of soil 

bacteria. The presence of air allows oxygen to diffuse 

into the system with the consequent potential for 

aerobic metabolism. Thus, in addition to volatilization 

losses, there are substantial losses of hydrocarbons due 

to biodegradation in the unsaturated zone. 

NATURAL ATTENUATION OF 

CHLORINATED ETHENES

Biodegradation Processes

Biodegradation processes are an important 

component of the natural attenuation of chlorinated 

ethenes (Weidemeier and others, 1998), because 

biodegradation can transform chlorinated ethenes to 

environmentally innocuous compounds, such as carbon 

dioxide (CO2), ethene, and chloride. Because some 

transformation products, such as vinyl chloride (VC), 

can increase the toxicity of chlorinated solvents, these 

processes must be carefully assessed in applications of 

MNA. 

Chlorinated ethenes are subject to a variety of 

microbial degradation processes that include reductive 

dechlorination (Vogel and McCarty, 1985; Barrio-Lage 

and others, 1987, 1990; Bouwer, 1994; McCarty and 

Semprini, 1994; Vogel, 1994; Odum and others, 1995), 

aerobic oxidation (Hartmans and others, 1985; Davis 

and Carpenter, 1990; Phelps and others, 1991; Bradley 

and Chapelle, 1996, 1998a, 1998b; Bradley and others, 

1998b), anaerobic oxidation (Bradley and Chapelle, 

1996, 1998b; Bradley and others, 1998b), and aerobic 

cometabolism (Wilson and Wilson, 1985; Semprini 

and others, 1990, 1991; McCarty and Semprini, 1994; 

Semprini, 1995). Thus, assessing whether or not a 

particular degradation process is active in a hydrologic 

system is usually a complex task. Because the 

conditions under which these processes occur are 

known, identification of the presence or absence of 
8 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

particular degradation processes at a given site is 

possible.

Reductive Dechlorination

Chloroethenes are relatively oxidized 

compounds, due to the presence of electronegative 

chlorine atoms, and can act as electron acceptors in 

microbial metabolism (Vogel and others, 1987). In the 

presence of a suitable electron donor and catalyst, 

hydrogen can replace a chlorine on a chlorinated ethene 

molecule. This microbially catalyzed process is called 

reductive dechlorination. A number of reports have 

described the accumulation of perchloroethene (PCE) 

and trichloroethene (TCE) transformation products in 

anaerobic ground-water systems and have attributed 

this phenomenon to microbial reductive dechlorination 

(Barrio-Lage and others, 1987, 1990; Bouwer, 1994; 

McCarty and Semprini 1994; Vogel 1994; Odum and 

others, 1995; Vogel and McCarty, 1985). The 

consensus today is that microbial reductive 

dechlorination is ubiquitous in anaerobic, 

chloroethene-contaminated aquifers, but the extent of 

dechlorination is highly variable from site to site 

(Bouwer, 1994; McCarty and Semprini, 1994; Vogel, 

1994; Chapelle, 1996; Gossett and Zinder, 1996; 

McCarty, 1996).

The tendency of chlorinated ethenes to undergo 

reductive dechlorination decreases with decreasing 

number of chlorine substituents (Vogel and others, 

1987; Bouwer, 1994; McCarty and Semprini, 1994; 

Vogel, 1994). PCE, with its four chlorine atoms, is a 

stronger oxidant than all of the naturally occurring 

electron-accepting species found in ground-water 

systems, with the notable exception of oxygen gas (O2) 

(Vogel and others, 1987). Thus PCE readily undergoes 

reductive dechlorination to TCE except in aerobic 

aquifers. Reductive dechlorination of TCE to cisdichloroethene (cis-DCE) occurs under Fe(III)-

reducing conditions and in more strongly reducing 

environments. Reductive dechlorination of cis-DCE to 

yield VC apparently requires at least sulfate 

(SO4)-reducing conditions (Vogel and others, 1987; 

Chapelle 1996), but proceeds more readily in 

methanogenic environments. VC, on the other hand, is 

the least oxidized of the chloroethenes. Consequently, 

reductive dechlorination of VC to the nonchlorinated 

product, ethene, is characteristically slow and 

significant only under highly reducing, methanogenic 

conditions (Vogel and McCarty, 1985; Barrio-Lage and 

others, 1987, 1990; Freedman and Gossett, 1989; 

DiStefano and others, 1991; De Bruin and others, 1992; 

Bouwer, 1994; Ballapragada and others, 1995; Fennell 

and others, 1995; Maymo-Gatell and others, 1995; 

Odum and others, 1995; Wu and others, 1995). As a 

result of this decreasing reductive potential with 

decreasing number of chlorine substituents, reductive 

dechlorination of chloroethene contaminants is often 

incomplete in ground-water systems and frequently 

leads to the accumulation of cis-DCE and VC (Major 

and others, 1991; Kitanidis and others, 1993; McCarty 

and Reinhard, 1993; Haston and others, 1994; Weaver 

and others, 1995; Wilson and others, 1995). 

The growing recognition that microbial 

reductive dechlorination is common in anaerobic 

aquifers, but rarely results in complete reduction to 

nonchlorinated products, undermined early efforts to 

exploit intrinsic microbial activity for remediation of 

chloroethene-contaminated ground water. Because VC 

is a USEPA priority pollutant, its observed production 

and accumulation in anaerobic aquifers represents a 

potential increase in risk to human health and the 

environment. Consequently, in situ production of VC 

by indigenous microorganisms increased regulatory 

concern over chloroethene contamination and 

prompted widespread application of physical 

remediation methods, such as pump-and-treat systems, 

in an effort to remediate contaminated ground water. 

Unfortunately, because ground-water systems are 

commonly hydrogeologically complex, pump-andtreat systems are generally slow and inefficient 

(Bouwer, 1994). The lack of an effective alternative, 

combined with subsequent advances in the 

understanding of microbial mechanisms for degrading 

chloroethenes, has led to a reexamination of 

bioremediation in chloroethene-contaminated aquifers 

in recent years.

An appreciation for the potential contribution of 

intrinsic microbial reductive dechlorination to 

chloroethene remediation in ground-water systems was 

delayed by the widely held perception that this process 

is accidental and of no benefit to the microorganisms 

carrying out the processes. Furthermore, because the 

molar concentration of chloroethenes in ground-water 

systems is generally low in all but the most 

contaminated source areas, it is generally thought that 

these compounds are not sufficiently concentrated to 

serve as primary substrates in microbial metabolism. In 

addition, the first pure cultures determined to be 

capable of reductive dechlorination were methanogens, 

which did not grow on chloroethenes and apparently 
Natural Attenuation of Chlorinated Ethenes 9

did not gain energy from the reaction. These organisms 

mediated slow and partial reductive dechlorination of 

PCE and TCE to yield DCE. Based on these 

observations, reductive dechlorination has commonly 

been viewed as an anaerobic cometabolism brought 

about by the accidental interaction of chloroethenes 

with enzymes and cofactors produced by the 

microorganisms for other metabolic purposes 

(McCarty and Semprini, 1994). This type of 

cometabolic dechlorinating process was considered 

ubiquitous in anaerobic systems but generally 

incapable of mediating complete reduction to nontoxic 

products like ethene. 

This thinking began to change in 1993 when a 

number of investigations demonstrated that reductive 

dechlorination can be carried out by microorganisms 

that use chloroethene compounds as terminal electron 

acceptors for energy production. These 

microorganisms, collectively termed “halorespirers,” 

are able to grow by using chloroethenes as sole 

terminal electron acceptors, and are capable of much 

higher rates of reductive dechlorination. Although 

halorespirers capable of reducing PCE or TCE to DCE 

are relatively common (Holliger and others, 1993; 

Krumholz and others, 1996; Sharma and McCarty, 

1996; Maymo-Gatell and others, 1997), to date only 

one, Dehalococcus ethenogenes, has been shown to 

completely degrade PCE to ethene (Maymo-Gatell 

and others, 1997). If microorganisms, such as 

D. ethenogenes, are present in ground-water systems 

in substantial numbers, then complete reductive 

dechlorination to ethene may be a significant 

mechanism for chloroethene bioremediation in 

anaerobic aquifers.

At present, the general consensus is that, 

although complete microbial reductive dechlorination 

is possible in anaerobic aquifers, complete reductive 

dechlorination to ethene is rarely observed due to low 

electron donor availability, unfavorable 

reduction/oxidation (redox) conditions, or the potential 

absence of appropriate microorganisms. Thus, 

reductive dechlorination alone does not usually 

remediate chloroethene contamination in ground-water 

systems. In combination with aerobic and anaerobic 

mechanisms for microbial oxidation of DCE and VC, 

however, the process of reductive dechlorination can be 

an important component of the natural attenuation of 

chlorinated ethenes in ground-water systems.

Aerobic Oxidation

Although the tendency of chloroethenes to 

undergo reductive dechlorination decreases as the 

number of chlorine substituents decreases, the 

tendency to undergo oxidation increases with 

decreasing number of chlorine substituents (Vogel and 

others, 1987). As the least chlorinated of the 

chloroethenes, VC has the greatest tendency to undergo 

oxidation. Rapid microbial degradation of VC, 

including mineralization, has been observed in 

laboratory cultures and aquifer samples under aerobic 

conditions (Hartmans and others, 1985; Davis and 

Carpenter, 1990; Phelps and others, 1991; Bradley and 

Chapelle 1996, 1998a, 1998b; Bradley and others, 

1998b). Moreover, under aerobic conditions, VC can 

be used as a sole carbon source for growth and 

metabolism (Hartmans and others, 1985; Hartmans and 

deBont, 1992). These observations indicate that, in 

addition to incidental oxidation via cometabolic 

mechanisms, VC can be utilized as a primary substrate 

for microbial oxidation under aerobic conditions.

The cometabolic oxidation of DCE under 

aerobic conditions has been demonstrated for a variety 

of cosubstrates including methane, phenol, toluene, 

and propane (McCarty and Semprini, 1994). In 

addition, several recent studies indicate that microbial 

oxidation of DCE to CO2 can also occur aerobically in 

the absence of detectable cosubstrates (Bradley and 

Chapelle 1998b; Bradley and others, 1998b, 1998c). 

Mineralization of DCE without addition of a carbon 

cosubstrate has been documented in aquifer sediments 

(Bradley and Chapelle, 1998b; Bradley and others, 

1998b, 1998c). DCE mineralization activity was 

observed in liquid cultures (106 final dilution) 

containing DCE as the sole carbon source and oxygen 

as the terminal electron acceptor (Bradley and 

Chapelle, 2000), which indicates that DCE can be a 

primary substrate without the need for a carbon 

co-substrate. Microbial growth with oxygen as an 

electron acceptor and DCE as sole carbon source has 

only recently been reported (J.M. Gossett, Cornell 

University, written commun., 2001).

Unfortunately, microbial oxidation of DCE and 

VC under aerobic conditions is of limited relevance in 

most ground-water systems. In the rare event that VC is 

directly released to aerobic aquifers [a possibility at 

PVC manufacturing sites, Hartmans (1995)], rapid 

aerobic mineralization of VC by aquifer 

microorganisms can be expected. For the 

overwhelming majority of sites, however, the presence 
10 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

of DCE and VC in ground water is attributable to the 

existence of anaerobic conditions and the activity of 

reductive dechlorinating microorganisms. Addition of 

oxygen to ground water to stimulate aerobic 

contaminant biodegradation in an otherwise anaerobic 

aquifer system is expensive and in most cases 

impractical. Consequently, aerobic biodegradation of 

chloroethene contaminants in ground-water systems is 

probably limited to the edge of the contaminant plume 

where DO has not been depleted by microbial 

respiration (Bradley and others, 1998b). As discussed 

earlier, production and accumulation of VC requires 

the reducing conditions associated with SO4-reduction 

and methanogenesis. Thus, because the co-occurrence 

of VC and aerobic conditions is rare in ground-water 

systems, aerobic oxidation of DCE and VC as primary 

substrates for microbial metabolism is not considered 

to be an important mechanism for chloroethene 

biodegradation. As was the case for cometabolic 

oxidation, it is worth noting that microbial oxidation of 

DCE and VC under aerobic conditions can be 

significant at the interface of ground-water and surfacewater systems (Bradley and Chapelle 1998a, 1998b).

Anaerobic Oxidation

By 1995, efforts to utilize in situ bioremediation 

in chloroethene-contaminated aquifers had reached an 

impasse. Microbial reductive dechlorination of PCE 

and TCE was considered pervasive in anaerobic 

aquifers, but, in most systems, reductive dechlorination 

appeared to stop with DCE and VC. Likewise, the 

characteristic association of DCE and VC 

accumulation with anaerobic conditions disqualified 

aerobic microbial metabolism as a significant 

mechanism for bioremediation of these compounds 

under in situ conditions. Without a demonstrable 

mechanism for in situ biodegradation of chloroethenes 

to nontoxic products, state and Federal regulators were 

understandably reluctant to accept in situ 

biodegradation as a legitimate mechanism for 

remediation of chloroethenes in ground water.

The discovery in 1996 that microorganisms can 

oxidize VC to CO2 under anaerobic conditions paved 

the way for regulatory acceptance of in situ 

bioremediation as a defensible mechanism for 

remediation of chloroethene-contaminated aquifers 

(Bradley and Chapelle 1996). Oxidation of VC can 

occur under anaerobic conditions if a sufficiently 

strong oxidant is available to drive microbial 

degradation. Fe(III) oxides are strong oxidants that are 

ubiquitous in ground-water systems. In an experiment 

conducted with sediment from a Fe(III)-reducing 

aquifer, addition of Fe(III) to anaerobic microcosms 

resulted in VC mineralization rates comparable to 

those observed under aerobic conditions. Low but 

significant VC mineralization was also observed in 

anaerobic microcosms under ambient Fe(III) 

conditions. These results indicated that VC could be 

mineralized under anaerobic, Fe(III)-reducing 

conditions, and that the bioavailability of Fe(III) was an 

important factor affecting the rates of mineralization. 

More importantly, microbial oxidation of VC under 

Fe(III)-reducing conditions provided a potential 

anaerobic alternative to the slow and inefficient 

reductive dechlorination of VC to ethene.

For ground-water contaminants that serve as 

electron donors during biodegradation, such as 

petroleum hydrocarbons, the availability of competing 

terminal electron acceptors affects the efficiency of 

contaminant biodegradation (Borden, 1994, Chapelle 

and others, 1996a). Oxygen reduction is the most 

thermodynamically favored and, typically, the most 

efficient metabolic mechanism for biodegradation 

of reduced ground-water contaminants. Among 

the remaining terminal electron acceptors that are 

commonly observed in ground-water systems, 

the oxidation potential decreases in the order of 

NO3 > Fe(III) > SO4 > CO2. Thus, in general, the 

potential for biodegradation of highly reduced groundwater contaminants is greatest under aerobic conditions 

and least under CO2-reducing (methanogenic) 

conditions. Because DCE and VC are relatively 

reduced compounds, a similar pattern of decreasing 

oxidation potential under increasingly reducing 

conditions would be expected (Vogel and others, 

1987). 

The effect of redox conditions on DCE and VC 

oxidation was recently investigated in aquifer and bedsediment microcosms (Bradley and Chapelle, 1998b). 

In that study, mineralization of DCE and VC to CO2

decreased under increasingly reducing conditions, but 

significant mineralization was observed for both 

sediments under anaerobic conditions. VC 

mineralization decreased in the order of aerobic 

>Fe(III)-reducing >SO4-reducing > methanogenic 

conditions. As one would expect given their difference 

in chlorine number, microbial oxidation of VC was 

greater than microbial oxidation of DCE for each 

electron-accepting condition. For both sediments, 
Natural Attenuation of Chlorinated Ethenes 11

microbial mineralization of DCE under aerobic 

conditions was at least twice that observed under 

anaerobic conditions. An interesting observation is that 

the rate and magnitude of DCE oxidation did not differ 

significantly among Fe(III)-reducing, SO4-reducing, 

and methanogenic conditions. Based on this and other 

observations, it was concluded that microbial oxidation 

of DCE under these redox conditions involved an initial 

rate-limiting reduction to VC, which was subsequently 

oxidized to CO2. This, in turn, suggested that direct 

oxidation of DCE requires a more powerful oxidant 

than Fe(III) oxides. A subsequent investigation 

demonstrated that aquifer microorganisms can 

anaerobically oxidize DCE to CO2 under Mn(IV)-

reducing conditions without an initial reduction to VC 

(Bradley and others, 1998c). Because Mn(IV) oxides 

are common in alluvial and glacial aquifer sediments, 

microbial oxidation of DCE may be significant in some 

anaerobic ground-water systems.

The ability of aquifer microorganisms to 

efficiently oxidize DCE and VC to nontoxic products 

under anaerobic conditions has important implications 

for the potential utilization of intrinsic biodegradation 

in ground-water systems. These results indicate that, in 

anaerobic aquifers, highly oxidized chlorinated 

chloroethenes, such as PCE and TCE, can be readily 

transformed to DCE and VC, which are susceptible to 

microbial oxidation under a number of anaerobic redox 

conditions. Thus, the combination of reductive 

dechlorination of PCE and TCE under anaerobic 

conditions, followed by anaerobic microbial oxidation 

of DCE and VC, provides a possible microbial pathway 

for complete degradation of chloroethene contaminants 

in ground-water systems.

Aerobic Cometabolism 

Another potential process for microbial 

degradation of chloroethenes in ground-water systems 

is cometabolic oxidation. Wilson and Wilson (1985) 

reported that methanotrophic bacteria were capable of 

oxidizing TCE to CO2 under aerobic conditions. Since 

then, a wide variety of aerobic microorganisms, which 

are able to oxidize TCE, DCE, and VC to CO2 without 

accumulation of toxic intermediates, have been 

identified. These include methane, propane, ethene, 

aromatic compound, ammonium, isoprene, and VC 

oxidizers (see McCarty and Semprini, 1994). 

Cometabolic oxidation of chloroethenes does not 

supply energy for microbial growth or metabolism. 

Rather, for each of these processes, the responsible 

microorganisms contain nonspecific oxygenase that 

fortuitously oxidize chloroethenes to CO2. 

Consequently, aerobic cometabolism of chloroethenes 

requires the presence of oxygen and a primary substrate 

to initiate the production of a suitable oxygenase. 

Cometabolic oxidation is not considered to be a 

significant mechanism for intrinsic biodegradation of 

chloroethene contaminants in ground water. 

Cometabolic oxidation of chloroethenes by subsurface 

microorganisms has been successfully exploited for 

engineered remediation of chloroethene-contaminants 

in ground water (Semprini and others, 1990, 1991; 

McCarty and Semprini, 1994; Semprini, 1995). TCE 

contamination in aerobic aquifers can be biodegraded 

by methanotrophic microorganisms when methane is 

supplied to the subsurface in sufficient quantities to 

stimulate and support methanotrophic activity. Because 

methane and oxygen do not typically co-occur in 

ground-water systems, however, methanotrophic 

oxidation of chloroethenes is unlikely under 

nonengineered circumstances. A number of ex situ 

investigations have demonstrated that toluene oxidizers 

can cometabolize chloroethenes under aerobic 

conditions (Fan and Scow, 1993; Fuller and others, 

1995; Hopkins and McCarty, 1995; Mars and others, 

1996). Moreover, many ground-water contaminant 

plumes are the result of mixed waste releases and, as a 

consequence, contain chloroethenes and aromatic 

compounds like toluene. Unfortunately, contaminant 

plumes, which contain aromatic compounds in 

sufficient concentration to support cometabolic 

oxidation of chloroethenes, are characteristically 

anaerobic as a result of oxygen depletion by aerobic 

respiration. Consequently, significant cometabolic 

oxidation of chloroethenes in such systems would be, 

at most, a transient phenomenon. Because 

circumstances suitable for cometabolic oxidation of 

chloroethenes are rarely observed in ground-water 

systems, this process is generally not considered to be 

an important pathway for microbial degradation of 

chloroethene contaminants.

The interface between ground water and surface 

water is a nonengineered system in which cometabolic 

oxidation could potentially be a significant mechanism 

for biodegradation of chloroethene contaminants. 

Because ground-water contamination occurs most 

commonly in local flow systems (that is, flow systems 

hydrologically connected to land surface), plumes of 

contaminated ground water frequently discharge to 

nearby surface-water bodies. The streambed sediments 
12 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

of these surface-water systems are commonly 

characterized by geochemical heterogeneity and 

remarkably active microbial communities. Because 

methanotrophic activity is commonplace in organicrich, streambed sediments, discharge of chloroethenecontaminated ground water can reasonably be expected 

to support significant cometabolic oxidation of 

chloroethenes. In fact, complete oxidation of DCE and 

VC has been reported in streambed sediments 

characterized by mixed aerobic/methanogenic 

conditions (Bradley and Chapelle, 1997). These results 

suggest that cometabolic oxidation of chloroethene 

contaminants may be significant in stream and lakebed 

sediments.

Redox Conditions and the Biodegradation 

of Chlorinated Ethenes in Ground-Water 

Systems

Although microbial degradation processes of 

chlorinated ethenes are complex, they are predictable. 

Under some redox conditions, all chlorinated ethenes 

can serve as electron acceptors in microbial 

metabolism. In this case, microorganisms are respiring 

the chlorinated ethenes by transferring electrons to 

them. This process is also called reductive 

dechlorination. Under other redox conditions, 

microorganism can use lightly chlorinated ethenes, 

such as DCE and VC, as electron donors. In this case, 

microorganisms oxidize the chlorinated ethenes and 

use them as a source of energy in the form of electrons. 

Under anoxic conditions, highly chlorinated 

ethenes, such as PCE and TCE, are subject to reductive 

dechlorination according to the sequence:

The efficiency of dechlorination, however, differs for 

different redox conditions. Dechlorination of PCE and 

TCE to DCE occurs under mildly reducing conditions, 

such as nitrate (NO3)- or Fe(III)-reduction, whereas the 

transformation of DCE to VC, or the transformation 

from VC to ethylene requires the more strongly 

reducing conditions of methanogenesis or SO4

reduction (Vogel and others, 1987). Reductive 

dechlorination has been shown to be driven by 

molecular hydrogen (H2) (DiStefano and others, 1991), 

and the efficiency of reductive dechlorination is 

directly related to the availability of H2. 

Concentrations of H2 in ground-water systems 

are controlled by ambient microbial terminal electronaccepting processes (TEAPs). Under anaerobic 

conditions, H2 is continuously produced by 

fermentative microorganisms metabolizing natural or 

anthropogenic organic matter. This H2 is then utilized 

by respirative microorganisms that most commonly use 

Fe(III), SO4, or CO2 as terminal electron acceptors. 

Significantly, each of these TEAPs has a different 

affinity for H2 uptake (Lovley and Goodwin, 1988). 

CO2 reduction (methanogenesis) has the lowest H2

affinity and steady-state H2 concentrations in 

methanogenic aquifers are, therefore, relatively high 

(about 10 nM/L). SO4 reduction has a slightly greater 

affinity for H2 than methanogenesis and is 

characterized by slightly lower H2 concentrations 

(1–4 nM/L). Fe(III) reduction (0.2–0.8 nM/L) and 

NO3 reduction (<0.10 nM/L) have even greater 

affinities for H2 and are characterized by progressively 

lower steady-state H2 concentrations (fig. 2). Thus, the 

observation that reductive dechlorination is more 

efficient under methanogenic or SO4-reducing 

conditions than under Fe(III)- or NO3-reducing 

conditions reflects the greater availability of H2 for 

reductive dechlorination, and not the activity of 

methanogenic or SO4-reducing microorganisms 

(Smatlack and others, 1996).

The lightly chlorinated ethenes DCE and VC can 

be oxidized to CO2 under oxic or Fe(III)-reducing 

conditions:

DCE Cl2C2H2 + 2O2 ⇒2CO2 + 2H+ + 2Cl– (4)

VC ClC2H3 + 5/2O2 ⇒2CO2 + H2O + H+ + Cl– (5)

Because DCE and VC are usually degradation products 

of reductive dechlorination, complete degradation of 

chlorinated ethenes is favored by sequential anoxicoxic conditions. First, under reducing conditions, PCE 

and TCE is transformed to DCE and VC. Then, as 

ground water migrates to more oxic conditions, DCE 

and VC can be oxidized to CO2:

PCE TCE+Cl DCE ⇒ 2Cl VC 3Cl

ethylene 4Cl +

⇒ + ⇒ + ⇒

anoxic (methanogenic, 

SO4-reducing, or 

Fe(III)-reducing 

conditions)

oxic, Fe(III)-reducing 

conditions

PCE, TCE ⇒DCE 

and VC

DCE, VC ⇒2CO2

and Cl–

⇒
Natural Attenuation of Chlorinated Ethenes 13

The efficiency with which chlorinated ethenes are 

completely degraded, therefore, is directly related to 

redox conditions present in an aquifer and to the 

succession of redox processes that chlorinated ethenes 

are exposed to along particular ground-water 

flowpaths. Thus, an important component to assessing 

the natural attenuation of chlorinated ethenes is to 

accurately delineate redox conditions in ground-water 

systems.

Delineating the Distribution of Redox 

Processes in Ground-Water Systems

The most common electron-accepting processes 

in ground-water systems are oxygen, NO3, Fe(III), 

SO4, and CO2 reduction (methanogenesis) (fig. 3). 

Microorganisms that naturally inhabit ground-water 

systems couple the oxidation of an electron donor 

(usually organic carbon) with the reduction of electron 

acceptors. In doing so, microorganisms use the most 

energetically efficient electron acceptor available. The 

stoichiometry and Gibbs free energy (∆Go in units of 

kilocalorie/equivalent at pH 7.0, Stumm and Morgan, 

1981, p. 453) of these processes can be represented by 

the generalized equations:

Figure 2. Schematic diagram showing how molecular hydrogen drives 

reductive dechlorination.

Figure 3. Characteristic H2 concentrations associated with 

different terminal electron-accepting processes.

O2 + CH2O ⇒ CO2 + H2O, ∆Go = -29.0, (6)

4NO3 + 4H+ + 5CH2O ⇒ 4NO2 ⇒ 2N2 + 5CO2 + 7H2O ∆Go = -19.6, (7)

4Fe(OH)3 + CH2O + 8H+ ⇒ 4Fe2+ + CO2 + 11H2O ∆Go = -10.0, (8)

2CH2O + SO4

2+ + H+ ⇒ 2CO2 + HS– + 2H2O ∆Go = -5.9, and (9)

2CH2O ⇒ CH4 + CO2 ∆Go = -5.6. (10)
14 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

Because oxygen is the most efficient oxidant (that is, 

∆Go is the most negative), microorganisms will use 

oxygen preferentially to NO3, Fe(III), SO4, or CO2. If 

oxygen is not available, however, microorganisms will 

preferentially use NO3 over Fe(III), SO4, or CO2. If 

oxygen or NO3 is not available, microorganisms will 

use Fe(III) over SO4 or CO2. Finally, if oxygen, NO3, 

and Fe(III) are not available, microorganisms will use 

SO4 preferentially to CO2. Because CO2 reducers are 

the least energetically favorable microorganisms, they 

can only become predominant in the absence of other 

more efficient electron acceptors. This observed 

behavior is commonly referred to as the ecological 

succession of terminal electron-accepting processes. 

Because of ecological succession, microbial 

processes tend to segregate into distinct zones 

dominated by oxygen, NO3, Fe(III), SO4, and CO2

reduction. Furthermore, given the different electron 

acceptors consumed (left side of eqs. 6–10) and final 

products produced (right side of eqs. 6–10), it is 

possible to logically deduce the zonation of microbial 

processes in ground-water systems. 

If DO is present in ground water at 

concentrations greater than 0.5 mg/L, then oxygen 

reduction (eq. 6) will be the predominant microbial 

process. If DO concentrations are less than 0.5 mg/L, 

but NO3 is present at concentrations greater than 

1 mg/L, then NO3 reduction (eq. 7) will be the 

predominant microbial process. Because nitrite (NO2) 

is an unstable intermediate product of NO3 reduction 

(eq. 7), the presence of measurable NO2 concentrations 

is indicative of NO3 reduction. If ground water lacks 

DO, NO3, or NO2, but concentrations of Fe2+ are 

greater than 0.5 mg/L, then Fe(III) reduction (eq. 8) 

will be the predominant process. If ground water lacks 

Fe2+ but contains concentrations of SO4 greater than 

1 mg/L and hydrogen sulfide (H2S) greater than 

0.05 mg/L, then SO4 reduction (eq. 9) will be the 

predominant process. Finally, if the water lacks DO, 

NO3, Fe2+, SO4, and H2S, but contains concentrations 

of methane greater than 0.2 mg/L, then methanogenesis 

(eq. 10) will be the predominant process. The logic of 

deducing predominant electron-accepting processes 

using observed changes of electron acceptor and final 

product concentrations in ground water is summarized 

in figure 4 (Chapelle and others, 1995).

In practice, this methodology commonly 

encounters uncertainties. Many products of microbial 

metabolism (such as Fe2+, H2S, and methane) can be 

transported by ground-water flow. In some cases where 

such transport is substantial, it is difficult to determine 

the exact redox zonation with this water-chemistry 

information. In these cases, direct measurement of 

dissolved H2 can be used to identify ambient redox 

processes (fig. 4).

Based on this methodology, the following data 

are required to identify microbial redox processes in 

ground-water systems (table 1):

Table 1. Ground-water chemistry constituents used to identify microbial redox 

processes in ground-water systems, and common methods of analysis 

Analytical constituents Method of analysis

Dissolved oxygen (DO) Field kit

Nitrate (NO3) Ion chromatography

Nitrite (NO2) Ion chromatography

Dissolved ferrous iron (Fe2+) Field kit 

Sulfate (SO4) Ion chromatography

Hydrogen sulfide (H2S) Field kit 

Dissolved methane (CH4) Gas chromatography 

pH (units) Meter

Dissolved hydrogen (H2) Gas chromatography
Natural Attenuation of Chlorinated Ethenes 15

Is

SO4

> 1 mg/L

?

Figure 4. Flowchart for deducing terminal electron-accepting processes in ground-water systems.
16 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

Of these constituents, the most important—and 

commonly the most difficult measurement to make 

accurately—is DO. This is a skill-intensive constituent 

to measure in the field, and extreme care must be taken 

to avoid oxygenation of the water sample prior to 

analysis. DO meters are convenient, but do not reliably 

measure low (<0.5 mg/L) concentrations of oxygen. 

DO kits, on the other hand, can accurately distinguish 

between truly anoxic ground water and low 

concentrations of DO (Chemetrics, Inc., 1984). 

Concentrations of NO3, NO2, and SO4 are most 

accurately measured in the laboratory using ion 

chromatography. H2S and Fe2+ are most efficiently 

measured in the field with appropriate field kits 

(table 1). Samples for methane analysis can be 

collected in the field and analyzed in the laboratory. H2

measurements are most reliable when made in the field 

(Chapelle and others, 1996b, 1997). 

Organic Carbon Substrates that Support 

Reductive Biodegradation

Reductive dechlorination, the process in which 

chlorinated ethenes serve as electron acceptors in 

microbial metabolism, requires an organic carbon 

substrate (a source of electrons) to proceed. These 

organic carbon substrates initially are degraded by 

fermentative bacteria that produce molecular H2 and 

other organic compounds. This H2 then reacts directly 

with the chlorinated solvent, resulting in reductive 

dechlorination (fig. 2). Many different kinds of organic 

carbon, including petroleum hydrocarbons, naturally 

occurring particulate organic carbon (POC) in aquifer 

sediments, and natural dissolved organic carbon (DOC) 

in ground water can be fermented to H2 to support 

reductive dechlorination. Organic carbon compounds 

differ substantially, however, in their ability to 

efficiently ferment and, therefore, the efficiency by 

which they can support reductive dechlorination. In 

particular, the ability to assess the efficiency by which 

natural DOC and POC are fermented is difficult. For 

these reasons, it is not currently technically feasible to 

quantitatively measure the mass of fermentable total 

organic carbon (TOC) available in ground-water 

systems. 

Although the ability to quantify the available 

mass of fermentable organic carbon available to 

support reductive dechlorination is difficult, the 

geochemical conditions resulting from organic carbon 

metabolism in an aquifer is relatively easy to assess. 

For these reasons, it is more appropriate for 

assessments of natural attenuation to focus on ambient 

geochemical conditions than on measuring available 

organic carbon.

Daughter Products Indicating Biodegradation

Concentrations of chlorinated ethenes and their 

degradation products give a direct indication of the 

presence or absence of microbial degradation (both 

reductive and oxidative) processes. In many cases, the 

production of cis-1,2-DCE, VC, and chloride ions 

along aquifer flowpaths is direct evidence of reductive 

dechlorination intrinsic bioremediation. VC and some 

DCE isomers could be primary contaminants in some 

ground-water systems. VC, however, is not normally 

present as a primary contaminant in solvent spills 

associated with military activities, because VC was not 

used as a solvent. Thus, the presence of VC in ground 

water associated with a chlorinated ethene spill is 

strong evidence of reductive dechlorination. Also, 

cis-1,2-DCE (rather than trans-1,2-DCE) is usually 

produced from the reductive dechlorination of TCE. As 

a rule of thumb, if cis-1,2-DCE comprises more than 

80 percent of the total DCE, then the DCE is likely of 

biogenic origin (Wiedemeier and others, 1998). Thus, 

VC and cis-1,2-DCE can be indicators of microbial 

reductive dechlorination.

Sorption Processes

Sorption refers to the distribution of a solute 

between the aqueous phase and the solid phase. The 

solute may be adsorbed onto the surfaces of the solid 

matrix, or may be absorbed into the interior of the 

sorbent matrix. Sorption can, therefore, act either to 

remove solute from solution (adsorption) or to add 

solute to solution (desorption). These combined 

adsorption-desorption processes are called reversible 

sorption and can have important effects on the transport 

of solutes in ground-water systems (Schwarzenbach 

and Westall, 1981). 

When a plume first develops from a newly inplaced contaminant source, the sorptive capacity of the 

aquifer sediments is largely unfilled; but as solutes 

migrate away from the source, they tend to adhere to 
Natural Attenuation of Chlorinated Ethenes 17

aquifer sediments and gradually fill the sorptive 

capacity of the aquifer material. This causes the 

transport of contaminants to be initially retarded 

relative to the velocity of ground water. As time passes, 

however, the sorptive capacity of the sediments is 

filled, and the effects of retardation become 

increasingly less evident. The principal effect of 

sorption on the development of plumes is to delay, or 

retard, the spread of contaminants; but, contaminant 

spread is not deterred. The steady-state configuration 

of plumes (that is, their extent when contaminant 

delivery from the source is balanced by the sum of the 

natural attenuation mechanisms) is independent of 

aquifer sorption. Low sorptive capacity aquifers, 

however, will reach the steady-state configuration 

sooner than high sorptive capacity aquifers.

Desorption, the processes by which solutes are 

released from contaminated aquifer sediments, is an 

important factor in any remediation effort. When 

aquifer sediments contain large amounts of 

contaminant mass in the adsorbed phase, they can 

continue to be sources of contaminants for long periods 

of time. This contributes to the contaminant “rebound” 

effect commonly observed in pump-and-treat 

remediation systems once the pumps are turned off, and 

can greatly increase the time needed to effect site 

cleanup. As a general rule, plumes develop rapidly in 

low-sorption capacity aquifers and can be remediated 

rapidly as well. Conversely, in high-sorption capacity 

aquifers, plumes develop more slowly and take longer 

to remediate. For these reasons, remediation strategies 

should include a quantitative evaluation of aquifer 

sorption capacity. 

Measuring Biodegradation Rates 

One approach to measuring biodegradation rates 

is to collect aquifer material, construct either static or 

flow-through microcosms in the laboratory, and 

measure the decrease in concentrations of particular 

compounds, or the production of 14CO2 from 

radiolabeled compounds (Chapelle and others, 1996a). 

These methods are advantageous in that they can be 

applied to a wide range of hydrologic systems, because 

results can be obtained in timeframes of weeks or 

months, and because abiotic controls can be used to 

separate biotic from abiotic effects. The laboratory 

approach, however, introduces uncertainties due to 

sediment disturbance and the difficulty of reproducing 

in situ conditions. 

Another approach to measuring biodegradation 

rates is to track the loss of contaminants along groundwater flowpaths. This approach also is subject to 

various uncertainties, particularly in separating the 

effects of microbial processes from abiotic processes, 

such as hydrodynamic dispersion, advection, and 

sorption. Uncertainty is associated with estimating 

contaminant mass from a limited number of data points 

in a heterogeneous medium.

Microbial utilization of substrates 

(contaminants) conforms to enzyme saturation 

(Monod) kinetics according to the Michaelis-Menton 

equation:

V = [vmax/Ks + S] (SB), (11)

where V is the rate of substrate uptake (moles per time), 

vmax is the maximum rate of substrate uptake (moles of 

substrate per time per gram of cells), Ks

 is the substrate 

concentration at which v = 1⁄2 vmax (moles of substrate 

per liter), S is substrate concentration (moles per liter), 

and B is the amount of cells (grams). At low substrate 

concentrations where S ~ K (that is, substrate uptake is 

not limited by enzyme availability), and when the 

microbial population is neither increasing or 

decreasing with time, the Michaelis-Menton equation 

is approximated by first-order kinetics:

V ~ kS, (12)

where k is a rate constant (units of 1/time). In many 

substrate-limited ground-water systems, first-order 

kinetics are an adequate approximation of contaminant 

degradation, and this approach has been widely used to 

simulate solute transport of organic contaminants. This 

simplification, however, is not recognized as an 

appropriate approach for sites with (1) high 

contaminant concentrations (>1 mg/L; Bekins and 

others, 1998) where the availability of degradation 

enzymes is substantially less than the availability of the 

contaminant; (2) contaminant concentrations that are 

toxic to microorganisms; (3) more than one substrate 

that limits microbial degradation rates; and/or 

(4) increasing or decreasing microbial populations.

One method for estimating biodegradation rates 

from field data is based on a dispersion model approach 

(Buscheck and Alcantar, 1995; Chapelle and others, 
18 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

1996a). This method was originally developed for 

dissolved BTEX compounds, but can be applied to 

dissolved chlorinated solvents as well.

The dispersion-model approach assumes that the 

plume is at steady-state conditions, (that is, the plume 

is not expanding or contracting with time), and that the 

equation

(13)

describes the exponential decrease in solute 

concentrations away from a constant source (Chapelle 

and others, 1996a). The decrease is proportional to 

ground-water velocity (<), the coefficient of 

hydrodynamic dispersion (D), and the biodegradation 

rate constant (k). This solution does not take into 

account transverse dispersion. The seepage velocity of 

ground water can be estimated by applying a 

modification of Darcy's equation, and the coefficient of 

hydrodynamic dispersion can be estimated from the 

scale of the plume. Given these estimates, k can be 

estimated by curve-fitting solutions of equation 13 to 

field data.

For chlorinated ethenes, this procedure is 

complicated because TCE, DCE, and VC are produced 

as daughter products from PCE as well as being 

degraded. TCE, DCE, and VC concentration changes 

along a flowpath segment reflect the difference 

between production and degradation. Thus, for TCE, 

cis-1,2-DCE, and VC, this procedure yields apparent 

degradation rate constants that underestimate actual 

degradation rate constants. In addition to 

underestimating degradation rate constants for 

daughter products, this method introduces several other 

sources of uncertainty, including those related to 

(1) source concentrations, (2) ground-water flow 

rates, (3) adequate sampling within the plume, and 

(4) deviations from steady-state conditions within the 

plume. Although these sources of uncertainty can be 

reduced by extensive data collection and the use of 

more sophisticated models, they cannot be entirely 

eliminated. Because of these uncertainties, it is clear 

that degradation rate constants obtained with these 

methods should be regarded as rough estimates.

Sources of Uncertainty in Biodegradation 

Rate Estimates

Estimating biodegradation rate constants using 

field data is subject to numerous sources of uncertainty 

that need to be explicitly considered in any application. 

These uncertainties include (1) variation of groundwater flow rates, (2) uncertainty in adequately 

sampling contaminant concentrations within the 

plume, and (3) deviations from steady-state conditions 

within the plume. Variation of ground-water flow rates 

in time and space due to heterogeneity of hydraulic 

conductivity and hydraulic gradient changes due to 

recharge events occurs in all shallow aquifers. This is 

an important source of uncertainty in estimating 

biodegradation rate constants because an n-fold error in 

ground-water flow velocity (v) results in an n-fold error 

in calculated biodegradation rate constant (k) (eq. 13). 

If variations in ground-water flow with time are large, 

then the steady-state assumption inherent in equation 

13 is not appropriate, and time-dependent solutions of 

equation 1 must be used (Rifai and others, 1995). 

Furthermore, if transverse dispersion is substantial in a 

system, then a two- or three-dimensional treatment of 

the problem is more appropriate (Weaver and others, 

1996). Adequate sampling of contaminant 

concentrations in a plume can also be a substantial 

source of uncertainty in evaluating the behavior of 

chlorinated ethene concentrations (Cherry, 1996). 

Contaminant concentrations are observed to vary 

substantially between the “core” and “fringes” of 

plumes. These variations can substantially affect 

biodegradation rate estimates. 

These procedures clearly show that there are 

numerous sources of uncertainty inherent in 

quantifying biodegradation rate constants using field 

data. Furthermore, many of these uncertainties are 

difficult or impossible to quantify. Although 

uncertainties can be reduced by extensive data 

collection, they cannot be eliminated entirely 

regardless of the effort expended. For these reasons, 

biodegradation rate constants and estimates of natural 

attenuation capacity obtained using these methods 

should be regarded as estimates. 

C x( ) Coexp – v v

2

+ + 4Dk

2D = – --------------------------------------- x
Time of Remediation Associated with Natural Attenuation 19

TIME OF REMEDIATION ASSOCIATED 

WITH NATURAL ATTENUATION

Summing the Processes that Contribute 

to Natural Attenuation

In this report, the TOR (tremediation) is defined in 

equation 1 as

t

remediation ≥ [Mo – Mthreshold]/RNA,

where Mo is the initial mass of contaminant present in 

the system, Mthreshold is the threshold for remaining 

contaminant mass, which is the remediation goal, and 

RNA is the rate that natural attenuation removes 

contaminants from the system. Many factors affect RNA

in ground-water systems, including hydrodynamic 

dispersion, advection, sorption, and biodegradation. 

These processes can be summed mathematically to 

give overall concentration changes of a contaminant C 

with time (∂C/∂t). Thus, ∂C/∂t is equal to the sum of 

hydrodynamic dispersion

,

advection ,

sorption, ,

and biodegradation –Rbio, as well as accounting for 

sources of contaminants leaching from NAPLs, such 

as petroleum hydrocarbons or chlorinated solvents 

+ RNAPL. When these source and sink terms for a 

contaminant C are summed, they give a mass-balance 

equation:

(14)

where

C = aqueous concentration of contaminant (ML3),

t = time (T),

x = distance (L),

D = coefficient of hydrodynamic dispersion 

(L2T-1),

v = average linear pore velocity of ground water 

(LT-1),

ρb = bulk density of the porous medium 

(dimensionless),

Kd = an equilibrium sorption coefficient 

(dimensionless),

n = porosity (dimensionless),

Rbio = removal of contaminant due to biodegradation, 

and

RNAPL = addition of contaminant dissolving from 

NAPL,

which describe the transport of a contaminant. 

Equation 14 has been widely used to assess natural 

attenuation processes (Newell and others, 1996), and is 

useful for (1) assessing the natural capacity of an 

aquifer system to attenuate contaminants, 

(2) estimating the distance a contaminant plume will 

migrate from a source, (3) estimating the time a 

contaminant plume will take to develop from a source 

or the time it will take for a contaminant plume to 

collapse once a source is removed, and (4) estimating 

the time it will take for a NAPL source to dissolve and 

dissipate. Each of these applications have specific uses 

and will be discussed in detail. 

Natural Attenuation Capacity

The concept of “assimilative capacity” is well 

known in soil science (Charbeneau and Daniel, 1993, p. 

15.1) and surface-water hydrology (Chapra, 1996, 

p. 11) and refers to the capacity of a system to absorb 

and/or transform pollutants to innocuous byproducts. 

By analogy, a “natural attenuation capacity” can be 

defined for ground-water systems as being the ability to 

lower contaminant concentrations along aquifer 

flowpaths.

In surface-water systems, assimilative capacity 

depends upon hydrologic (streamflow, mixing, and 

hydrodynamic dispersion) and biological (biological 

oxygen demand) factors, and is assessed using 

analytical or digital water-quality models. Similarly, 

the natural attenuation capacity of ground-water 

systems depends upon hydrologic (dispersion and 

advection) and biological (biodegradation rates) factors 

that can also be assessed using quantitative models. As 

discussed previously, the sum of dispersive, advective, 

sorptive, and biodegradative processes acting on a 

solute in a one-dimensional flow system is given by 

equation 14.

Appropriate procedures for solving equation 14 

depend on the ground-water system in question and the 

specific problems being addressed. When a 

contaminant plume has reached approximate steadystate conditions (that is, the plume is not expanding or 

D∂

2

C

∂x

2 ---------

v

∂C

∂x – ------

ρbbKd

n ----------------∂C∂t – ------

∂C

∂t

------ D∂

2

C

∂x

2 --------- v

∂C

∂x

------ ρbKd

n ------------ ∂C∂t – – ------ Rbio RNAPL = – + ,
20 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

contracting with time and MC/Mt=0), the sorption 

term becomes small relative to the other three terms, 

and the solute-transport equation simplifies to the 

ordinary differential equation:

(15)

For boundary conditions of C = C0 at x = 0, and C = 0 

as x →∞, equation 15 has the particular solution:

(16)

Equation (16) indicates that the steady-state solute 

concentration decrease away from a constant source is 

dependent on hydrodynamic dispersion (D), the 

biodegradation rate constant (k), and ground-water 

pore velocity (<). With this usage, a positive value of k 

indicates contaminant loss. The slope of the steadystate solute concentration profile along a flowpath is 

proportional to the value of:

(17)

The term natural attenuation capacity (abbreviated 

NAC), as used in this report, refers to the quantity given 

in equation 17, which has units of inverse length (L-1). 

Conceptually, it may be thought of as the 

contaminant-lowering capacity of an aquifer 

per unit length (feet or meters) of flowpath.

The concept of natural attenuation 

capacity as defined in equation 17 is useful 

because it illustrates those characteristics of 

a hydrologic system that affect the 

efficiency of natural attenuation. For 

example, if the biodegradation rate constant 

is small (~0.001 d-1) relative to the groundwater velocity (about 1 ft/d) and aquifer 

dispersivity (10 ft), the NAC of the system 

also will be small (0.009902 ft-1). Because 

of this small NAC, contaminants will be 

transported relatively long distances 

downgradient of a source area (fig. 5). 

Conversely, if the biodegradation rate 

constant is high (0.01 d-1) relative to groundwater velocity (0.2 ft/d) and aquifer 

dispersivity (1 ft), the NAC will be proportionally 

higher (0.0477 ft-1) and the transport of contaminants 

will be restricted closer to the source area (fig. 5). More 

quantitatively, NAC can also be useful in providing 

estimates of the distance of plume stabilization, given 

different contaminant concentrations at the source area. 

This, in turn, can provide estimates as to what 

contaminant concentration at the source area is 

required to meet a regulatory goal at a given distance 

downgradient.

Distance of Stabilization

The distance that contaminants are transported in 

a ground-water system depends on the NAC and the 

contaminant concentrations at the source area. This 

distance, termed the distance of stabilization (DOS), 

can be estimated by solving equation 16 for distance 

(x), yielding

(ln Co /C)/NAC = x, (18)

where NAC is given by equation 17. Thus, given a 

target concentration C, an initial source-area 

concentration Co, and the NAC of an aquifer, the 

distance it will take for the aquifer to lower 

contaminant concentrations to the target C [usually 

maximum concentration levels (MCLs), which are 

established by regulatory agencies (U.S. 

Environmental Protection Agency, 1991)] can be 

calculated directly from equation 18.

Dd

2

C

dx2 --------- v

dC

dx – ------ – kC = 0

C x( ) Coexp – v v

2

+ + 4Dk

2D = – --------------------------------------- x

– v v

2

+ + 4Dk

2D – ---------------------------------------

Figure 5. Effects of natural attenuation capacity on contaminant 

concentration declines along ground-water flowpaths.
Time of Remediation Associated with Natural Attenuation 21

This reasoning identifies two ways in which the 

NAC of a ground-water system can be used to achieve 

site remediation. The first depends on whether the NAC 

is sufficient to achieve plume containment without 

additional remediation procedures. In this case, 

monitored natural attenuation may be an acceptable 

stand-alone remedial strategy. In many other cases, 

however, the NAC may not be sufficient as a standalone remediation strategy. In those cases, engineering 

methods (for example, excavation, in situ chemical 

oxidation, and in situ bioremediation) need to be used 

to lower source-area concentrations to levels where the 

NAC present in the aquifer can lower contaminant 

concentrations to MCLs at a given point of compliance. 

This methodology is consistent with recent USEPA 

guidance, which has stressed that natural attenuation is 

usually appropriate when used in conjunction with 

engineered reduction of contaminant sources:

“In the majority of cases where monitored 

natural attenuation is proposed as a remedy, its 

use may be appropriate as one component of 

the total remedy, that is, either in conjunction 

with active remediation or as a follow-up 

measure” (U.S. Environmental Protection 

Agency, 1999, p. 1).

The manner in which natural attenuation and active 

remediation measures (such as source removal, pumpand-treat, chemical oxidation, or enhanced 

bioremediation) are combined depends in part on the 

distance to stabilization given by equation 18.

Time of Stabilization

Distance of stabilization calculations are useful 

for estimating the maximum extent of a contaminant 

plume, and estimating maximum allowable source-area 

concentrations. These steady-state solutions, however, 

do not provide any indication of how long it takes for 

the plumes to reach steady state. The time of 

stabilization (TOS) is often an important regulatory 

consideration. This problem can be addressed using 

time-dependent solutions of equation 14. Analytical 

solutions to equation 14 have been found for a several 

sets of initial and boundary conditions. For the case of 

a semi-infinite aquifer with a constant source, a timedependent solution for equation 14 is given by 

Domenico (1987). This solution makes it possible to 

evaluate some of the factors affecting TOS. 

First, it may seem intuitively obvious that the 

higher the NAC, the faster a plume would come to 

stabilization. Application of the analytical solution for 

a hypothetical chlorinated ethene case (fig. 6A), 

however, shows that this is not the case. In fact, this plot 

shows that as NAC increases, TOS remains constant. 

Thus, although NAC greatly affects the distance that a 

plume will migrate, it does not affect the time it will 

take the plume to stabilize. Secondly, it seems 

intuitively reasonable that the closer the target 

contaminant concentration C is to the initial 

contaminant concentration Co, the shorter the TOS. 

Again, however, application of the analytical solution 

shows that this is not the case. Figure 6B shows that the 

predicted TOS does not vary with different ratios of 

C/Co, which reflects the exponential nature of the 

biodegradation kinetics used to simulate plume 

stabilization. 

Sorption processes, however, do have an 

important effect on the time to stabilization. Figure 6C 

shows a plot of TOS and percent organic matter in the 

aquifer (the greater the percentage of organic matter, 

the higher the sorption coefficient). As the organic 

matter content of the aquifer increases and, thus, the 

sorptive capacity of the aquifer increases, the predicted 

time to stabilization increases dramatically. This is a 

general result. The sorptive capacity does not affect the 

distance of stabilization, but it has a large effect on the 

time of stabilization. Time to stabilization is also 

affected by contaminant type. Figure 6D indicates a 

plot of TOS and organic matter content for MTBE, 

benzene, and TCE. The results indicate that the 

stabilization time of MTBE, the least strongly adsorbed 

compound, is the least affected by organic carbon 

content. Stabilization times of TCE and benzene, on the 

other hand, are progressively more affected by aquifer 

organic carbon content. Based on these results, TOS 

seems to be most affected by aquifer organic content 

(sorptive capacity) and by contaminant type (which 

also affects sorptive capacity). Some qualitative 

judgments about times of remediation are possible just 

by considering the observable properties of the aquifer 

and contaminants in question.

Time of Nonaqueous Phase Liquid 

Dissolution

The preceding analyses of aquifer properties that 

affect DOS and TOS are based on analytical solutions 

of equation 14 for generalized conditions that treat 

contaminants as a point source of constant 

concentration. In reality, aquifers are most commonly 
22 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

contaminated by petroleum hydrocarbons and/or 

chlorinated ethenes that seep into the aquifer as 

NAPLs. When a large amount of NAPL is present, the 

behavior of contaminant plumes that develop can be 

approximated by the constant source assumption. In 

reality, however, the ultimate TOR depends on how 

rapidly NAPL dissolved and how rapidly the dissolved 

constituents are attenuated. Thus, realistic estimates of 

TOR require a quantitative treatment of NAPL 

behavior. 

The dissolution and biodegradation of NAPL 

cannot be treated realistically by simple analytical 

solutions to equation 14. Rather, the more flexible 

boundary and initial conditions made possible by 

numerical solutions are required. In this report, the 

numerical model SEAM 3D (Waddill and Widdowson, 

1997) is used to estimate NAPL dissolution rates. The 

treatment of NAPL in SEAM 3D follows that of Imhoff 

and others (1993), and is based on the concept that the 

driving force for NAPL dissolution is the difference 

between the actual aqueous concentration of a solute 

(Sls) and the aqueous concentration of a solute in 

equilibrium with a given NAPL (S eq

ls ). The NAPL 

source term in equation 14 is given by: 

Figure 6. Effects of (A) natural attenuation capacity, (B) initial contaminant 

concentration, (C) organic matter content of aquifer material, and (D) contaminant 

composition on times of stabilization.
Time of Remediation Software 23

RNAPL

Source,ls = max[0,kNAPL (S eqls – Sls )], (19)

where RNAPL

Source,ls is the solute concentration at the 

source used in equation 14, kNAPL is the dissolution rate 

of the NAPL, and (Seq

ls – Sls ) is the difference 

between the equilibrium concentration of a solute in 

equilibrium with NAPL and the actual concentration at 

any given time. The equilibrium concentration of 

solute (S eq

ls ) can be calculated from Raoult’s law as:

(S eq

ls ) = ƒ ls (S solls ) ,

where ƒ ls = mole fraction of the solute, and

S sol

ls = solubility of the solute. With each timestep of 

the model, SNAPL

ls is updated as

 (20)

This treatment allows simulation of a given mass of 

NAPL in an aquifer, contained within a specified 

volume of aquifer, that is acted on by given hydrologic 

conditions. Furthermore, this treatment allows the 

calculation of contaminant concentration due to NAPL 

dissolution at any point in the model domain. For the 

purposes of this report, the term “time of NAPL 

dissolution” refers specifically to the time required to 

lower aqueous phase contaminants associated with a 

NAPL source below a given threshold directly 

downgradient of the NAPL. This definition is adopted 

because the ability to directly measure NAPL mass is 

technically difficult and subject to numerous 

uncertainties. On the other hand, measuring aqueous 

concentrations of contaminants directly downgradient 

of a NAPL source area is much easier to accomplish.

By using the mathematical treatment described 

above, some factors that affect the time of NAPL 

dissolution can be illustrated. Clearly the most 

important factor is the mass of NAPL present in the 

aquifer. For a given NAC (0.0093 ft-1), the TOR 

calculated with SEAM 3D varies almost linearly with 

respect to mass of contaminant (fig. 7A). This behavior 

reflects the progressive dissolution of NAPL (eq. 20), 

because dissolution occurs at the surface of the NAPL 

body. Also, the rate of NAPL dissolution varies in 

proportion to rates of ground-water flow. For example, 

for a NAPL mass of 200 lbs and a rate of ground-water 

flow of 100 ft/yr, time of NAPL dissolution is about 

33 years (fig. 7A). If the rate of ground-water flow is 

decreased by a factor of 2 to 50 ft/yr, then the time of 

NAPL dissolution increases by a factor of 2 to 62 years 

(fig. 7A). 

Time of NAPL dissolution is also affected by the 

dimensions of the NAPL body. For example, if a NAPL 

body 20 ft long and 10 ft wide has a thickness of 10 ft, 

a NAPL mass of 10 lbs would have a time of 

dissolution of about 37 years. Assuming, however, the 

thickness is decreased to 1 ft, the time of dissolution 

increases to 76 years (fig. 7B). Note also that as the 

NAPL thickness decreases, the more curvilinear the 

relation between NAPL mass and the time of 

dissolution becomes (fig. 7B). This reflects the surface 

area of NAPL subjected to dissolution (fig. 7B). This 

kind of analysis also indicates that time of dissolution 

is relatively unaffected by NAC, the organic matter 

content of the aquifer, and the kind and amount of 

electron acceptors available. These factors greatly 

affect the length of plume stabilization and the time of 

plume stabilization (fig. 6), but not the time of NAPL 

dissolution. This happens because natural attenuation 

mechanisms (principally biodegradation) operate more 

effectively on dissolved constituents than on NAPL. 

Thus, whereas the size of the plume emanating from a 

NAPL source, and the time to stabilization of that 

plume is highly dependent on NAC and aquifer organic 

matter content, respectively, the time of NAPL 

dissolution is more dependent on NAPL mass, NAPL 

geometry, and ground-water flow rates (fig. 7).

TIME OF REMEDIATION SOFTWARE

The TOR problem, as developed in preceding 

sections, can be logically divided into (1) distance of 

plume stabilization, (2) time of plume stabilization, and 

(3) time of NAPL dissolution problems (fig. 1). Each of 

these issues can be addressed using particular solutions 

of the TOR equation (eq. 14), which can be developed 

according to specific needs. In this report, software was 

developed based on useful (but limited) solutions to 

equation 14 to address these three classes of TOR 

dSls

NAPL

dt ---------------------- n

ρb

-----Rsource ls , . NAPL =
24 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

problems. The software was designed to aid the user in 

assembling and organizing the data needed to make 

TOR estimates, to obtain appropriate and useful 

solutions of the TOR equation, and to illustrate the 

various uncertainties inherent in TOR estimates. The 

software, termed Natural Attenuation Software (NAS), 

is meant to be used as a tool to assist hydrologists in 

making TOR estimates. No attempt has been made to 

make NAS applicable to all, or even most, TOR 

problems. Rather, NAS is designed around numerous 

simplifications of hydrologic, microbial, and 

geochemical processes that, although convenient, will 

introduce unacceptable error to some problems. The 

NAS software can be downloaded from the Web site 

http://www.cee.vt.edu/NAS/ (accessed February 29, 

2003).

Figure 7. Time of nonaqueous phase liquid (NAPL) dissolution versus 

(A) NAPL mass, and (B) NAPL mass in differing aquifer thickness.
Time of Remediation Software 25

Overview of Natural Attenuation Software

The NAS tool is designed for application to 

ground-water systems consisting of porous, relatively 

homogeneous, saturated media, such as sands and 

gravels, and is designed specifically for petroleum 

hydrocarbon and chlorinated ethene contaminants. 

First, detailed site information about hydrogeology, 

redox conditions, and contaminant concentrations 

must be entered. NAS cannot be applied without 

extensive site characterization, and the software is 

intentionally designed to require these data before the 

analysis can proceed. If the data that NAS requires are 

not available, then TOR estimates cannot and should 

not be made.

A flowchart describing how the NAS software 

can be used to address TOR questions is shown in 

figure 8. After data entry, NAS estimates site-specific 

ground-water flow rates, biodegradation rates, and 

sorption properties. Based on these estimates, NAS 

then produces either analytical or numerical solutions 

of the TOR equation. The analytical solutions are 

specific to plume concentration questions, such as what 

is the DOS for given source-area contaminant 

concentrations, and what is the TOS if source-area 

concentrations are changed. For the DOS question, 

NAS calculates what the maximum source-area 

Figure 8. Flowchart showing how NAS can be applied to time of remediation problems.
26 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

concentration that can be allowed, based on a 

regulatory maximum concentration level at a given 

point downgradient of the source. Then, NAS estimates 

how long it will take for the plume to reach the lower 

steady-state configuration once source-area 

concentrations have been lowered by engineering 

methods. When the DOS and the TOS are acceptable, 

based on site-specific regulatory criteria, MNA can 

become an integral component of site remediation 

(fig. 8). 

In the case of NAPL contaminants, either 

chlorinated solvents or petroleum hydrocarbons, NAS 

uses the SEAM 3D code (Waddill and Widdowson, 

1997) to solve equation 14. The solution provided by 

NAS is tailored to estimate the length of time required 

by a given NAPL mass to dissolve and lower 

contaminant concentrations at the source area below a 

given user-supplied threshold. In principle, the 

numerical solution could then be used to estimate the 

distance of stabilization for the remaining residual 

concentration. Because this would substantially 

lengthen the amount of time required to make a 

simulation, however, this is not presently practical for 

distance and TOS problems. Rather, once the NAPL 

time to remediation calculation is completed, aqueous 

contaminant concentrations derived from the time of 

NAPL dissolution analysis can be used to make DOS 

and TOS estimates using the analytical solution (fig. 8).

Data Requirements and Input Using 

Natural Attenuation Software

When the NAS package is opened, the user can 

begin by clicking the button “Start a Project” (fig. 9A). 

This opens a dialog box in which the user can provide 

the facility and site names, and other appropriate 

information. The first task is to select the units to be 

used. Once the units are entered, a “next” button pops 

up that allows the user to move ahead. Throughout the 

program, the user is not allowed to move to the next 

step until the required information is entered. The next 

dialogue box queries the user as to the nature of the 

contaminants (petroleum hydrocarbons or chlorinated 

ethenes). If petroleum hydrocarbons are selected, the 

user has the option of considering MTBE and 

naphthalene in addition to BTEX compounds. If 

chlorinated ethenes are selected, the user must specify 

whether PCE or TCE is the source compound. NAS can 

be applied to mixes of petroleum hydrocarbons and 

chlorinated ethenes, but only by considering these 

classes of compounds in separate simulations.

After the contaminants have been properly 

identified, NAS returns to the main menu, illuminates 

the “Enter Site Data” button, which the user can click 

to open a dialogue box to enter site data. Hydraulic 

conductivity is entered as a range of values for 

maximum, average, and minimum (fig. 9B); the range 

of values at each site can be determined by hydraulic 

testing in the field (Bouwer, 1989). Similarly, values of 

hydraulic gradient are input as a range of values to 

accommodate variability of hydraulic gradient at a site 

and is a major source of uncertainty in estimating 

remediation times. Hydrogeologic data entry is 

completed by entering values for site porosity, aquifer 

thickness, and percent organic matter (fig. 9B). The 

percent organic matter (loss on ignition) is needed to 

estimate the sorptive capacity of aquifer material. 

The next site data required by NAS is 

contaminant-concentration data from along the axis of 

the plume. First, NAS queries the user about the 

sampling date and the number of wells available along 

the centerline of the plume. The user then creates a data 

table for each well, and inputs the well identifiers, the 

distance along the flowpath for each well, and 

contaminant concentrations. After these data are 

entered, NAS queries the user for redox chemistry data 

about the site. These data can be added for the same 

wells used for contaminant concentrations, or other 

wells can be used. The user then is queried about what 

redox measurements are available, and creates a table 

for data entry. NAS follows a flowchart similar to 

figure 4 to identify predominant redox processes. If the 

data indicate an ambiguous redox diagnosis (as 

commonly happens), then NAS will query the user to 

make the determination directly. A redox diagnosis 

must be made for NAS to continue. Because 

biodegradation rates are redox-dependent, NAS 

includes the capability for determining different 

biodegradation rates for different redox zones and is 

capable of considering up to four different redox zones 

that contain four different rates of biodegradation. NAS 

requires contaminant data from at least three wells in a 

given redox zone to assign zone-specific 

biodegradation rates.

Following redox data entry, NAS produces a 

summary of the data for the user to view. In addition, 

NAS uses the data to estimate biodegradation rates 

(based on contaminant concentration changes along the 

flowpath), redox zonation (based on redox chemistry 
Time of Remediation Software 27

data), and sorption parameters (based on contaminant 

type and organic matter content). When the user returns 

to the main menu, the buttons for “Source 

Concentration Reduction/Time of Stabilization” and 

“Contaminant Mass Removal/Time of Remediation” 

are illuminated. The “Time of Stabilization” button 

activates the analytical solutions. NAS then asks the 

user to input the distance between the contaminant 

source and the relevant point of contact (POC) at the 

site. When the POC is provided, NAS queries the user 

to input the width of the contaminant source. When the 

source width is provided, NAS queries the user to input 

the regulatory compliance concentration (RCC) at the 

POC. This is usually the MCL for contaminant of 

concern. When the user clicks the “calculate” button, 

NAS displays the maximum, best-estimate, and 

minimum TOS (fig. 10A). In addition, NAS displays 

the target source-area concentration (the maximum 

concentration allowable at the source for natural 

attenuation to lower contaminants below the RCC at 

the POC). By clicking the “graphical view” button, the 

solutions can be displayed visually (fig. 10B).

By returning to the main menu, the user can 

proceed to time of NAPL-based time of NAPL 

dissolution calculations. This part of NAS uses a 

numerical solution (SEAM 3D) of the TOR equation to 

make these estimates. When the “Contaminant Mass 

Removal/Time of Remediation” button is clicked, the 

user is queried about the length (length is perpendicular 

to the direction of flow) and width (width is parallel to 

the direction of flow) of the NAPL body. When these 

dimensions are entered, the user is then queried about 

Figure 9. Initial computer screens of (A) NAS and (B) the hydrogeology data entry of NAS.

(A)

(B)
28 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

the thickness of the NAPL body and the percentage of 

contaminants present in the NAPL. When this 

information is provided, NAS queries the user to enter 

the electron acceptors present at the site, including 

oxygen, NO3, bioavailable Mn (if data are available), 

bioavailable Fe(III) (if data are available), and SO4. 

Once the electron acceptor data are provided, the user 

may move to the next screen, which asks for the 

amount of NAPL present in the source area. The user 

can specify a single mass or a range of mass estimates. 

NAS then asks for the mass removal options being 

considered, which range from no removal to complete 

removal (although complete removal obviates any 

additional TOR calculation). The user can specify a 

simulation time of up to 100 years (any simulation time 

longer than 100 years is considered to have too many 

Figure 10. NAS computer screens of (A) distance and time of stabilization, 

and (B) graphical representation of time-of-stabilization calculations.

(A)

(B)
Time of Remediation Software 29

Figure 10. (Continued) NAS computer screens of (A) distance and time of 

stabilization, and (B) graphical representation of time-of-stabilization 

calculations.

(B)

(A)
30 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

potential sources of error to be meaningful in the 

context of the NAS tool), and run the simulation by 

clicking the “Execute TOR Calculation” button, which 

runs the SEAM 3D model with the NAPL package; the 

simulation can take several minutes. After the 

solution(s) have been calculated, the user is asked to 

specify an aqueous contaminant concentration level 

that represents site remediation. NAS then returns the 

length of time needed to reach that remedial goal 

(fig. 11).

Figure 11. NAS computer screens of (A) data input for nonaqueous phase liquid 

time-of-dissolution calculations, and (B) example of time-of-dissolution results.

(B)

(A)
Time of Remediation Examples 31

TIME OF REMEDIATION EXAMPLES

The TOR methodology was applied to two sites 

at Naval Facilities because of the substantial regulatory 

interest in evaluating times of plume stabilization/

NAPL remediation at each site. Furthermore, the U.S. 

Geological Survey conducted data-collection activities 

at each of these sites. TOR assessments were 

performed for petroleum hydrocarbon releases at the 

Laurel Bay site, Marine Corps Air Station, Beaufort, 

S.C., and chlorinated ethene releases at Naval 

Submarine Base, Kings Bay, Ga.

Gasoline Nonaqueous Phase Liquid 

Example: Laurel Bay, South Carolina

The Laurel Bay site in Beaufort, S.C., is a U.S. 

Geological Survey Toxic Substances Hydrology 

Program research site (Landmeyer and others, 1998) 

located in the lower Coastal Plain physiographic 

province, which is underlain by fine-grained, wellsorted sands of aeolian origin. The site is an active 

gasoline station at the Marine Corps Exchange. In 

1991, a leak was discovered in one of the underground 

gasoline storage tanks. The leaking tanks were 

removed along with substantial quantities of 

contaminated aquifer sediments in accordance with 

State guidelines (South Carolina Department of Health 

and Environmental Control, 1995). In 1993, the U.S. 

Geological Survey began to assess the migration of 

contaminants in the ground-water system. By 1996, a 

well-developed plume of BTEX- and MTBEcontaminated ground water had developed at the site.

The physical layout of the site, ground-water 

levels, and the locations of monitoring wells are shown 

in fig. 12. As is commonly the case at such sites, most 

of the monitoring wells were placed at locations that 

helped delineate the size and shape of the plume. As 

such, only a few wells are actually located in the 

centerline of the plume and, therefore, useful for 

estimating biodegradation rates. Contaminantconcentration data from wells outside the plume 

centerline can be a major source of error when 

estimating biodegradation rates, and such data should 

be avoided. As of 1996, five wells (1, RW, MSL-1, 8, 

19, and 21) were located in the central part of the plume 

oriented along the direction of ground-water flow 

(fig. 12). Of these five wells, two (1 and RW) are 

located in the NAPL source area. The potentiometric 

map shows a major discontinuity in ground-water 

levels near the downgradient ditch that is the discharge 

area for the local flow system. The rapid change of 

water elevation near the ditch causes the flow to 

accelerate as it approaches the ditch. As such, flow 

velocities in the upgradient part of the system are lower 

than in or near the ditch. As a result, and because NAS 

assumes a constant velocity, only wells upgradient of 

the potentiometric discontinuity were used to estimate 

biodegradation rates in NAS.

Contaminant and redox data collected at the 

Laurel Bay site were used as input into NAS and are 

summarized in figure 13. Also shown in figure 13 are 

the estimated biodegradation rates for benzene, 

toluene, ethylbenzene, xylene, MTBE and total BTEX, 

as well as the natural attenuation capacity of the aquifer 

for these compounds, as calculated by NAS. The 

calculated biodegradation rates, although similar to 

rates observed at other gasoline spill sites (Weidemeier 

and others, 1996), are relatively low. The estimated 

biodegradation rate for MTBE in particular is very low 

at the Laurel Bay site, and is consistent with laboratory 

studies of MTBE biodegradation in sediments 

conducted at this site (Landmeyer and others, 1998). 

Largely because of these low biodegradation rates, the 

natural attenuation capacity of the aquifer is similarly 

low—only 0.0061 ft-1 for total BTEX (fig. 13B). 

Maximum source-area concentration and TOS 

estimates given by NAS are shown in figure 14. Given 

the low NAC of the system, NAS estimated that the 

target source-area concentrations required to 

biodegrade contaminants below regulatory thresholds 

prior to discharge at the downgradient drainage ditch 

are fairly low; concentrations are 758 μg/L for total 

BTEX, 168 μg/L for benzene, and 2,362 μg/L for 

MTBE. NAS also estimated that it would take between 

4.1 and 6.2 years for the plume to stabilize to these 

lower source-area concentrations if a removal action 

were undertaken. 

These estimates cannot be directly verified at the 

Laurel Bay site because, although some sediment 

excavation occurred during tank removal, the 

excavation did not remove all of the gasolinecontaminated sediments. Predicted benzene 

concentrations based on time-of-stabilization estimates 

were compared to measured concentration declines of 

benzene in the plume. Figure 15 shows predicted 

concentration declines in well MW-8, assuming a 

complete source-removal action in 1994 compared to 

measured concentrations of benzene taken between 

1994 and 2000. Interestingly, measured concentration 
32 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

Figure 12. Site map, locations of observation wells, and potentiometric surface of the Laurel Bay site, South Carolina.
Time of Remediation Examples 33

Figure 13. NAS computer screens of (A) summary of contaminant data, (B) redox data, and 

(C) summary of biodegradation rate and natural attenuation capacity estimates made from these 

data for the Laurel Bay site.

(A)

(B)

(C)
34 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

Figure 14. NAS computer screens of (A) summary of time-of-stabilization and 

distance of stabilization estimates, and (B) graphical view of time-of-stabilization 

estimates for the Laurel Bay site.

(A)

(B)
Time of Remediation Examples 35

Figure 14. (Continued) NAS computer screens of (A) summary of time-ofstabilization and distance of stabilization estimates, and (B) graphical view of 

time-of-stabilization estimates for the Laurel Bay site.

(A)

(B)
36 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

declines of benzene follow a pattern consistent with a 

complete source-removal action, which seems 

counterintuitive; however, the observed NAPL 

dissolution behavior at this site suggests a possible 

explanation. 

The amount of NAPL that was released at Laurel 

Bay is not known precisely, but fuel inventory records 

suggest that between 100 and 500 gal of gasoline 

leaked into the aquifer. Given the density of gasoline 

(about 7 lbs/gal), it is estimated that between 500 and 

1,000 lbs of gasoline NAPL was delivered to the 

ground-water system. Gasoline NAPL, on average, 

contains 2 percent benzene, 10 percent toluene, 

1 percent ethylbenzene, 4 percent BTEX, and 

(in this case) 10 percent MTBE. Using these 

percentages for the NAPL at Laurel Bay, NAS can be 

used to estimate times of remediation for different 

masses of NAPL. 

Estimated times of NAPL dissolution and 

concentration decreases to the levels indicated by the 

distance-to-stabilization estimates (fig. 14) for total 

BTEX, benzene, and MTBE, and assuming that NAPL 

masses ranging from 10 to 1,000 lbs, are shown in 

figure 16A. The analysis suggests that for the highly 

volatile compounds, benzene and MTBE, the TOR is 

fairly brief and is about 10 years for NAPL masses 

ranging between 100 and 1,000 lbs. Because groundwater chemistry data are available 

from the source area for the 10 years 

following the spill (well 1SAT), the 

predictions made by NAS can be 

tested. Figure 16B shows MTBE, 

benzene, and total BTEX 

concentrations in the source area (well 

1SAT) as a function of time beginning 

in 1993. These data show that benzene 

and MTBE concentrations were 

initially high, but have decreased over 

time. In contrast, total BTEX 

concentrations have decreased, but not 

as rapidly as benzene and MTBE. By 

2001 (about 10 years after the spill), 

measured concentrations of both 

MTBE and benzene reached the 

remediation level as suggested by the 

NAPL dissolution estimates, whereas 

less soluble toluene, ethylbenzene, 

and xylene (TEX) compounds did 

not. This analysis indicates that the NAPL dissolution 

rates estimated by NAS are consistent with measured 

values.

The observed rapid NAPL dissolution at the 

Laurel Bay site (fig. 16B) provides a possible 

explanation for the observation that concentration 

declines in the plume mimic those that would be 

expected if a source-removal action had been 

undertaken. For a number of hydrologic reasons, but 

most obviously because ground-water flow rates at this 

site are relatively high (about 1 ft/d), NAPL dissolution 

of the most soluble components of gasoline (benzene 

and MTBE) is relatively efficient (fig. 16B). This 

efficient dissolution results in the MTBE and benzene 

plume acting almost like a source-removal action. The 

more insoluble TEX components, however, more 

closely resemble the long-term source area that exists 

at this site. These data show that the TOR for benzene 

and MTBE is shorter (about 10 years) than the TOR for 

total BTEX (about 40 years). The behavior observed at 

the Laurel Bay site is expected to be similar to the 

behavior observed at other gasoline spills throughout 

the United States. This reflects the lower solubility of 

the TEX compounds relative to benzene and MTBE, 

suggesting that in the absence of source-area removal, 

the overall remediation time will be longer for TEX 

compounds than for benzene and MTBE.

Figure 15. Predicted benzene concentrations using time of stabilization 

estimates at well MW-8 plotted versus measured benzene concentrations over 

time at the Laurel Bay site.
Time of Remediation Examples 37

The Laurel Bay example points out the following 

important aspects of making TOR estimates for 

gasoline NAPLs:

1. Even when substantial numbers of observation 

wells are available at a site, the number of wells 

that intersect the central part of the plume and, 

therefore, are useful for documenting biodegradation rates, are commonly limited. This limited data places considerable uncertainty on the 

derived biodegradation rates.

2. When the site exhibits relatively low natural 

attenuation capacity, the target concentrations in 

the source area will be relatively low as well.

3. When the sediment lacks organic matter, the TOS 

is relatively rapid.

4. For relatively soluble components of NAPL, such 

as benzene and MTBE, the TOR can be fairly 

brief (in this case, on the order of 10 years). For 

less soluble TEX components, the TOR can be 

much longer (in this case, as much as 50 years).

Chlorinated Ethene Example: Kings Bay, 

Georgia

The site used for this example is an abandoned 

landfill known as the Old Camden Road landfill located 

at the Naval Submarine Base, Kings Bay, Ga. A dense 

Figure 16. (A) Estimated time of nonaqueous phase liquid dissolution for MTBE, benzene, and 

total BTEX using NAS, and (B) observed source-area contaminant concentration decreases in 

source-area well EX-1 at the Laurel Bay site.
38 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

network of monitoring wells was used to delineate the 

contaminant plume, as it existed in 1998 (fig. 17), and 

to follow contaminant concentration changes over 

time. The site is underlain by sediments of back-barrier 

and barrier-island origin. The most permeable sands 

(hydraulic conductivity about 8.2 to 5.5 ft/d) 

underlying the site are present at depths between 30 

and 35 ft, and were deposited by a prograding barrier 

island (Leeth, 1999). This permeable zone is underlain 

and overlain by finer-grained sediment, which are 

characterized by low hydraulic conductivity. The 

hydraulic gradient ranges between 0.004 and 0.006 

ft/ft, resulting in an average ground-water flow velocity 

of about 50 ft/yr. The hydrologic, geochemical, and 

contaminant data for this site are summarized in 

figure 18. 

The redox data at this site indicate SO4-reducing 

conditions in and near the source area grading to 

Fe(III)-reducing conditions downgradient (fig. 18). In 

addition, the contaminant-concentration data indicate a 

distinct change in biodegradation rates for total 

chlorinated ethenes that coincide with the change in 

redox conditions. This discontinuity between 

redox-dependent biodegradation rates can be simulated 

by means of the multizone model capability of NAS. 

Biodegradation rates for individual chlorinated 

ethenes and total chlorinated ethenes are summarized 

in figure 19. In general, these biodegradation 

rates are consistent with rates observed at other 

anoxic, chlorinated ethene-contaminated sites 

(Wiedemeier and others, 1999), and with rates 

estimated previously at this site (Chapelle and 

Bradley, 1998).

The maximum source concentration and time-ofstabilization calculations performed by NAS are 

summarized in figure 20. This analysis suggests a 

maximum source-area concentration for total 

chlorinated ethenes of 130 μg/L, given a point of 

Figure 17. Location of total chlorinated ethene plume prior to in situ oxidation and 

locations of monitoring wells.
Time of Remediation Examples 39

Figure 18. Summary of hydrologic, contaminant, and redox characteristics of the 

Kings Bay site.
40 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

Figure 19. Discontinuity in biodegradation rates between redox zones, and summary table 

of estimated biodegradation rates at the Kings Bay site.
Time of Remediation Examples 41

Figure 20. Summary of time and distance of stabilization estimates for the Kings Bay site.
42 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

contact 220 ft downgradient (roughly corresponding to 

the Navy property line) and an MCL at the property 

line of 5 μg/L. This is much lower than the source area 

concentration as of 1998 (about 4,500 μg/L), 

suggesting that a reduction in source-area 

concentrations was needed at this site. A previous 

source-area concentration analysis (Chapelle and 

Bradley, 1998) produced similar results, and based on 

this analysis, a source-area remediation was 

undertaken at this site with a source-area target 

concentration of 100 μg/L. A series of in situ oxidation 

source-removal actions was initiated in late 1998, 

which resulted in source-area PCE concentrations 

being lowered to <100 μg/L from the 4,000 to 

5,000 μg/L range. 

This source-removal action raises the question of 

how long it will take the plume to shrink to equilibrium 

with the lower concentration source area. The TOS 

calculations performed by NAS are plotted with 

sediment organic matter concentration and shown on 

fig. 21A. Because the organic matter composition of 

these sediments ranges from 0.1 to 0.5 percent, the 

analysis suggests that the TOS for this system will 

range from about 7 to 15 years, with a best estimate of 

11 years. These estimates suggest that even though 

much of the contaminant mass was removed by in situ 

oxidation in 1999, the contaminant plume will persist 

for the foreseeable future. 

Also of interest at Kings Bay are TOR estimates 

for residual NAPL present in the landfill. Excavations 

Figure 21. Estimated (A) time of stabilization for plume following nonaqueous 

phase liquid (NAPL) removal and (B) time of NAPL dissolution versus NAPL 

mass at the Kings Bay site.
Time of Remediation Examples 43

Figure 22. Observed concentration changes at (A) well USGS-3 in the zone of Fenton’s 

reagent injection, and (B) well KBA-11-13A, which are 160 feet downgradient of the 

injection zone.

at the landfill have revealed the presence of plastic 

5-gal buckets partially filled with NAPL PCE. Thus, 

undiscovered sources of NAPL are probably present at 

this site. Because containers ranging from about 1 to 

25 gal were disposed of at this site, NAPL masses at 

particular points in the landfill could likely vary from 

about a pound (a few ounces of PCE) to as much as 

250 lbs (19 gal of PCE). 

Figure 21B shows a TOR 

analysis at this site for NAPL 

masses ranging from 10 to 

250 lbs. The results suggest 

that low masses of NAPL 

(about 10 lbs) will disperse 

fairly quickly (about 3 years), 

whereas larger masses 

(250 lbs) would require as 

much as 77 years. This is 

roughly consistent with the 

observed behavior of PCE at 

this site where a contaminant 

plume, emanating from a highconcentration source area 

associated with the disposal of 

a PCE mass (about 200 lbs), 

has been observed to persist 

for at least 30 years (fig. 17).

This time-of-NAPL 

dissolution analysis illustrates 

the utility of source-area 

removal technologies to lower 

the TOR associated with 

natural attenuation processes. 

For masses of PCE exceeding 

50 lbs (about 6 gal), times of 

remediation without source 

removal would likely exceed 

20 years (fig. 21B). On the 

other hand, if 90 percent of the 

NAPL mass is removed via in 

situ oxidation by Fenton’s 

reagent, the TOR could be 

lowered to less than 5 years 

(fig. 21B). Thus, combining 

engineered NAPL removal 

with natural attenuation of an 

existing plume can be a useful 

remedial strategy.

The TOS estimates 

made with NAS can be 

compared to monitoring data 

at the Kings Bay site. Monitoring data from 1998 to 

present (2001) for four wells located at different 

distances along the flowpath are shown in figures 22 

and 23. At the most upgradient well (USGS-3), located 

in the zone injected with Fenton’s reagent, concentrations of chlorinated ethenes immediately decreased 

below 100 μg/L (fig. 22A). At well KBA-11-13A, 

(A)

(B)
44 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

which is located in the central part of the plume about 

160 ft downgradient of the source area, chlorinated 

ethene concentrations were observed to “spike” 

following the Fenton’s reagent injection, possibly 

reflecting contaminants being pushed downgradient 

(fig. 22B). Since that time, however, concentrations of 

chlorinated ethenes have steadily decreased. Of the 

eight downgradient wells at the site, all but one showed 

a trend of decreasing contaminant concentrations as 

illustrated by well USGS-9 (fig. 23A). Conversely, 

well USGS-11 showed an increasing trend of 

chlorinated ethene concentrations over time. 

The concentration trends shown by the 

monitoring wells can be compared to TOR estimates 

provided by NAS. A comparison of the NAS-simulated 

concentration trends to monitoring data collected from 

well KBA-11-13A is shown in figure 24. The NAS 

simulation predicts that concentrations of chlorinated 

ethenes would remain constant for the first 2 years 

following in situ oxidation (before remediated water 

Figure 23. Observed concentration changes at wells (A) USGS-9 and (B) USGS-11, 

which are 380 feet downgradient of the injection zone.

(A)

(B)
Time of Remediation Examples 45

reaches KBA-11-13A), and then decrease gradually 

over the next 3 years. Actual monitoring data, however, 

show more complex behavior. Concentrations of 

chlorinated ethenes were observed to be relatively 

variable. Part of this observed variability can be 

attributed to hydrologic disturbance following in situ 

oxidation. Much of the variability, however, probably 

reflects the more complex flow and chlorinated ethene 

transport in the aquifer than can be simulated by the 

relatively simple analytical model imbedded in NAS.

Comparison of the NAS predictions with 

chlorinated ethene concentrations observed in the more 

downgradient wells also shows considerable 

variability. In well USGS-9, for example, 

concentrations of chlorinated ethenes have decreased 

much more rapidly than predicted by the NAS 

simulation (fig. 25A). The pattern shown by well 

USGS-9 is observed in all but one of the downgradient 

wells. The exception to this pattern is well USGS-11, 

which shows that concentrations of chlorinated ethenes 

have actually increased over time. This pattern of 

behavior is actually more consistent with the NAS 

predictions (fig. 25B) than that observed at well 

USGS-9 (fig. 25A). In all cases, the differences 

between the NAS estimates and the observed behaviors 

can be attributed to hydrologic complexities of the site 

that NAS cannot simulate. These include head changes 

caused by Fenton’s reagent injection, ground-water 

flow direction changes caused by precipitation events, 

and the cessation of the pump-and-treat system in 

1998. All of these processes affect directions and rates 

of ground-water flow as well as the transport of 

contaminants in the system. 

Figure 24. Observed concentration changes compared to NAS-simulated changes 

at well KBA-11-13A.
46 Methodology for Estimating Times of Remediation Associated with Monitored Natural Attenuation

SUMMARY

The time-of-remediation (TOR) problem can be 

divided into three interrelated components including 

(1) the distance of stabilization (DOS) of a plume from 

a constant contaminant source of known concentration, 

(2) the time of stabilization (TOS) for a plume to shrink 

following a source-removal action, and (3) the time it 

takes for a NAPL of given composition to dissolve and 

disperse. A combination of analytical solutions (DOS 

and TOS) and numerical solutions (NAPL dissolution) 

to the solute-transport equation can be used to evaluate 

TOR questions, and are imbedded in the Natural 

Attenuation Software (NAS) described in this report. 

Comparison of the NAS-generated TOR 

estimates with actual long-term monitoring data at the 

Laurel Bay, S.C., (petroleum hydrocarbons) and Kings 

Bay, Ga., (chlorinated ethene) sites illustrates the 

uncertainties involved in making TOR estimates and 

Figure 25. Observed concentration changes compared to NAS-simulated 

changes at wells (A) USGS-9 and (B) USGS-11.

(A)

(B)
References 47

suggests how such estimates can be used appropriately 

in practical applications. One observation is that over a 

timescale of 1 to 3 years, the NAS predictions often 

differ substantially from observed monitoring data. In 

the Laurel Bay and Kings Bay examples, observed 

contaminant concentrations tended to decrease much 

faster at most monitoring wells than was predicted by 

the TOR analysis. In other cases, such as at well 

USGS-11 at Kings Bay, contaminant concentrations 

were observed to increase over time when the TOR 

analysis indicated that contaminant concentrations 

would remain steady over time. These observations 

clearly show that the actual behavior of contaminated 

sites can differ from the predicted behavior. These 

differences can be traced to the simplifications needed 

to model aquifer systems in NAS, as well as show that 

this procedure introduces uncertainty into each 

analysis. Thus, using TOR estimates as precise 

predictions of system behavior is not appropriate. 

On the other hand, the comparison of simulated 

and observed behavior suggests that over longer 

periods of time, the precision of TOR estimates 

becomes somewhat better. Over a timescale of about 

10 years, for which monitoring data are available at the 

Laurel Bay site, predicted and observed contaminant 

concentrations were largely in accord. Part of this 

concordance can be attributed to the fact that, in 

general, contaminant concentrations in ground-water 

systems tend to decrease because of natural attenuation 

processes. Nevertheless, these observations suggest 

that TOR estimates derived from NAS are likely to be 

more in accordance with observed behavior over 

periods of 5 to 10 years than with shorter periods of 

time. 

These observations emphasize that TOR 

estimates should not be regarded as precise predictions 

of future contaminant behavior. Rather, it is more 

appropriate for TOR estimates to focus on the effects of 

NAPL removal on long-term remediation goals, or on 

how different hydrologic factors affect time and DOS 

estimates. 

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