Ground Water Monit R 2004 Suarez

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I by Monica P. Suarez and Hanadi 5. Rifai

Modeling Natural Attenuation of Total BTEXand Benzene Plumes with Different Kinetics

Abstract

Natural attenuation has em erged as a potential alternative for rem ediation of sites contamina ted with fuel hydrocarbons. Th is

paper com pares the results from modeling the natural attenua tion of BTE X (ben zene, toluene , ethylben zene, and xylene) at a

coastal site to the results from a benzene model at the sam e site. Field data for total BTEX and benzene were used to develop

model param eters for the Bioplum e 111 site model. A first-order kinetics express ion was used for benzene and an instantaneo us

expression for BTEX . M odeling results showed shorter cleanup timeframes for benzene than for BTEX. N atural attenuation

Cleanup times using BTE X and assimilative capacity are 47% to 90% higher than those for benzene alone. Cleanup times for ben-

zene of -100 years were estimated from model p redictions, whereas predicted cleanup times for BTEX varied between 150and

200 years.-

Introduction

Natural attenuation has been studied extensively. Most

case studies report on BTEX (benzene, toluene, ethylben-

zene, and xylene) as a whole (Borden et al. 1994; Breedveldet al. 1999; Brown et al. 1997; Cho et al. 1997; Davis et al.

1999; Doyle et al. 1994; Klens et al. 1999; Lahvis et al. 1999;

McLinn 1999; Wilson et al. 1986; Wilson et al. 1995; Wilsonet al. 1994b; Yang et al. 1997). In addition, mod els have been

developed (e.g., Bioplum e I11 [R ifai et al. 19971 and Bio-

Screen [New ell et al. 19963) which are used to sim ulate total

BTEX. This is mainly because electron acceptors are hard to

Proportion among BTEX components. However, these mod-

els may be used to simulate natural attenuation of a single

compound, e.g., b enzene, using first-order decay rates for the

component, which have been extracted from field data from

a site.Certainly, the fate and transport of fuel hydrocarbons in

ground water can be simulated using either a lumped com-

Pound or individual components. Nonetheless, both

approaches present drawbacks that should be recognized. For

example, modeling BTEX as a whole cannot account for

selective or competitive biodegradation of the hydrocarbons.

In addition, any model using instantaneous reaction is limited

to when the microbial biodegradation kinetics are fast rela-tive to the rate of ground water flow that mixes electron

acceptors with dissolved contaminants. Finally, the model

Copyright0 004 b y the Natio nal Ground Wate r Association.

using a lumped compound does not account for differences in

mobility and tendency to sorb of the various compounds, as

they are not modeled separately. On the other hand, when

modeling individual components using first-order kinetics,site-specific information may not be accounted for, such as

the availability of electron acceptors. In addition, first-order

decay rates, which are determined in the laboratory, do not

readily transfer to field situations. The model, furthermore,

does not assume any biodegradationof dissolved constituents

in the source zone.

This paper com pares the results from modeling the nat-

ural attenuation of BTEX at a coastal site to results from a

benzene mode l at the sam e site. Field data for total BTEX

and benzene were used to develop model parameters for the

Bioplume 111 model (Rifai et al. 1997). The calibrated mod-

els were used to estimate cleanup times for total BTEX andbenzene, and to determine the con fidence interval in model

results. A first-order kinetics expression was used for ben-

zene and an instantaneous expression for BTEX. Field data

were collected which, through modeling results, showed

shorter cleanup timeframes for benzene than for BTEX. For

these results, the benzen e cleanup goal was set to the m axi-

mum contaminant level (M CL) in drinking water (i.e., 0.005

m gL ). The BTEX cleanup goal, in turn, was set to 5 mg/L,asTEX compounds have much higher MCLs than benzene ( 1

mg/L, 0.7 mg/L, and 10mg/L, respectively).

An important consideration is that the site does not

exhibit contamination with MTBE (methyl tertiary butylether). An M TBE plum e would have required analysis as a

separate compound because its behavior is different from

BTEX and benzene in ground water.

Ground Water MonitoringL Remediation 24, no. 31 Summer 20041 pages 53-68 53



Site Description

The study site is an industrial facility in the U nited States

located in a coastal area. The site is bounded on the south by

the ocean, on the east by a river that discharges into a bay,

and on the no rth and west by refineries. The facility produced

ethylene, diethylene, and ethylene derivatives. Manufactur-

ing activities at the fac ility started in the 1950s and ended in

1985, and its operational units have been decomm issioned

and dismantled. During this time, crude and refined BTEXwere the only BTEX -containing materials handled at the site.

Surface topography at the site slopes to the south. The

conceptualized geology underlying this site can be divided

into two main units: (1) an upper zone with alluvial deposits

containing sand , silty sand, silty clay, and gravel; and (2) on

the bottom, a T ertiary Age limestone formation. The thick-

ness of the sand layers varies between 2.1 and 5.5 m. This is

underlain by a silty clay unit of unknown thickness that

appears to be limiting the extent of con tamination to the more

permeable upper layer.

The w ater table is present between 1.0 and 5.5 m below

ground surface and, in general, ground water flow is south-ward towards the sea. Ground water coming from the central

part of the north site boundary travels toward the bay with

slight deviations from a southerly direction. Ground water at

the northeastern part of the site moves in the southw est direc-

tion toward the inlet canal (Figure 1). Results from falling

head and constant head tests conducted in 1979 showed that

the hydraulic conductivities of the silty and clayey sands, and

sandy silts with fine gravels, ranged from 3.3x to 2.3 xm/sec. In add ition, available data sug gest that there are

not significant seasonal variations in ground water flow

direction for the northern part of the site. Data further show

that horizontal gradients vary betw een 0.0008and 0.002 m /mfor the dry and rainy season, respectively. Using a gradient of

0.002 m/m, an average hydraulic conductivity (geometric

mean) of 1.9 x d s e c , and an assumed effective porosity

of 0.2, the ave rage seepage velocity is -1.9 x 10-7 m/sec.

Contamination by petroleum hydrocarbons has been

detected in the north and northeastern parts of the site over an

area of -60 acres. Several on-site and o ff-site sources have

contributed to BTEX contamination of the underlying soil

and ground water. In 1977, a rupture in a pipe (Figure 1) that

transported BTX to the adjacent northern facility caused a

spill of -300,000 gallons of BTX, 70% of which was ben-

zene. Pump ing operations resulted in the recovery of 270,000gallons of the spilled hydrocarbons; however, a significant

num ber of wells still exhibit very high concentrations of ben-

zene. In addition, observations from site personnel indicate

that hydrocarbons were discharged into a creek that flows

into the ocean (Figure 1). Cloudy and w hite water running

into the creek and strong arom atic odors were reported sev-

eral times during the period 1965-1975. Lastly, several oil

spills into the creek were reported between 1989 and 1995.

In addition, some wells in the northeastern part of the

facility have shown the presence of light nonaqueous phase

liquids (LNAPLs). These LNAPLs were found floating

above the piezometric surface with thicknesses varying from0.02 to 0.7 rn.Compo sitional analysis of the observed NA PL

showed xylene as the main component with the exception of

wells near the pipe rupture. Finally, an extensive NAPL

Ii

Figure 1. Site map an d sampling locations.

plume present at the adjacent facility to the north (thickness

up to 1.5 m according to 1996 data) likely contributes to

hydrocarbon contamination in ground water.

Extent of Contamination

Dissolved Contamination

Dissolved organic contamination has been monitored at

the site since 1979. Historical data include BTEX concentra-

tions from the existing monitoring wells collected in 1979,

1982, and 1996. Data for this study were collected in Novem-

ber 1998, March 1999, November 1999, May 2000, and

Novem ber 2000, from -40 wells at the site (Figure 1). Data

in Figures 2 and 3 show the extent of the BTEX and benzeneplumes, respectively, for each of the sampling events.

In 1979, benzene concentrations within the studied area

varied from 1780 mg/L to < 1 mg/L across the site. Maxi-

mum concentrations of benzene were observed in wells D-1 1

and D-7 near the northern site boundary (Figure 2). Overall,

benzene concentrations have declined with time so that in

Novem ber 2000, the maximum measured concentration was

560 mg/L in well D-11. How ever, in November 1998 and

March 1999, an increase in the maximum b enzene concen-

tration was observed likely due to a decline in water table

levels. A similar general decline has been observed for the

BTEX plume, where the maximum concentration observedin 1979 was 1893 mg/L and 570 m g/L in November 2000.

Mapping of the BTEX and benzene plumes over time

(Figures 2 and 3) shows that despite the observed concentration

54 M.P.SuurczondHS.Rifuil Ground Water Monitoring 8. Remediation 24, no. 3: 53-68



N

-150 300 600m

Figure 2. BTEX contamination.

NO

/

Notes: the labels on he graphshd i i t e

m o n m w e n bcation usedtocontour

thedata.

concent ra l is in In@

increases mentioned previously, plume extent has rem ained

relatively constant since 1996. While plume lengths declined

from 550 to 305 m between 1979 and 1996, they have not

changed substantially since then. Additionally, the benzenea d BTEX plume extents are similar, which suggests parallel

behavior of benzene and "EX compounds.

Observed Patterns o f Intrinsic Bioremediation

In March 1999 and May 2000, a number of geochemical

parameters were m easured at selected wells including dis-

solved oxyg en, tempe rature, conductivity, redox potential,pH, alkalinity, ferrous iron, nitrate, sulfate, chloride, and

methane. Overall, the geochem ical parameters measured atthe site showed similar patterns of natural attenuation as

those observed at other sites (Barker and Mayfield 1988;

Metzinger and Capps 1997; Troy e t al. 1995; Wiedemeier et

55.P. SuarezandH.5 Rifai/ Ground Water Monitoring L Remediation 24, no. 3: 53-68



N

Firmre 3. Benzene contamination.

al. 1995; Wilson et al. 1994a; Wilson et al. 1995). That is,

highly contaminated areas had depleted electrcn acceptors

(dissolved oxygen and nitrate) and a high concentration of

byproducts (ferrous iron and methane). Sulfate concentra-tions, however, did not follow the expected trend observed at

many other sites. In general, these concentrations were very

high in the most contaminated area in the north part of the

site, the origin of which is unknown. Figure 4 includes the

results of the March 1999 geochemical analysis.

Notes:he labels onhegraphs indicate

monitoringwell location used to contour the

data.Concentrations nm$

Conceptual Model and Model Setup

Input parameters used for the Bioplume 111site model are

based on available site data and a review of the per tinent lit-

erature. Where site-specific data were not available, reason-

able assumptions for the types of materials comprising the

aquifer were made according to widely accepted literature

values. The s ite was modeled using a grid s ize of 30 rows by

25 columns. Each grid cell was 76.2 m long by 76.2 m wide.

56 M.P. SuorezondHS.Rifoi/ Ground Water Monitoring 8, Remediation 24, no. 3: 53-68



Ben

i

Concentrations in

Figure 4. Site geochemistry in March 1999: (a) dissolved oxygen, (b) nitrate, (c) ferrous iron, and (d) methane.

The concep tual model and calibration parameters are detailed

here and presented in Table 1.

Geology

As mentioned prev iously, the geology underneath the s ite

is complex. For modeling purposes, the contaminated zone

Table 1Site Parameters for M odel Calibration

BTEX Plume Benzene Plume

Parameter (InstantaneousReaction) (First-OrderKinetics)

Porosity 0.2 0.2

Hydraulic condu ctivity

Longitudinal dispersivity 7.6 m 7.6 m

Ratio transverse/ longitudinal dispersivity 0.1a, 0.1 a,Retardation factor 1 1

Background dissolved oxygen concentration 8 mg/L -Dissolved oxygen utilization factor 3.13 -Background nitrate concentration 8.3 mg/L -Nitrate utilization factor 4.85 -Background ferric iron con centration 50 mg/L -Iron utilization factor 21.8 5 -Background sulfate concentration 100mg/L -Sulf ate utilization factor 4.7 -Background carbon d ioxide concentration 50 mg/L -Carbon diox ide utilization factor 2.15 -First-order decay rate - 0.OooudaySimulation period 18 years 18 years

3.38 X I@’ to 2.30 X 10” d s e c 3.38 x 10-7t02.30 x lc3 s e c

M.P.SuorezondM. Rifoi/ Ground Water Monitoring & Remediation 24, no. 3: 53-68 57



was con ceptualized and m odeled as a shallow, continuous,

unconfined aquifer comprised of silty clay and sandy silt

across the site. The modeled aquifer had a variable thickness

ranging from 2.1 to 5.5 m.

Ground Water Flow

The closest bodies of surface water that influence site

conditions to v arying degrees include the ocean (Figure l ) ,

two canals that transport sea water through the site, and a

creek binding the eastern side of the site. The canals had a

significant impact on ground water levels in the sou thern part

of the site since water was pumped from one of these, the

inlet canal. Additionally, seasonal fluctuations and tidal

influences further complicate the site hydrology. Because of

limited data and little historical information, the site hyd rol-

ogy w as conceptualized as follows.

0 Ground w ater discharges to the inlet and outlet channels

were simulated by introducing pumping wells at the

northernmost points of the modeled canals. Pumping

rates were varied until observed water levels were

matched in the vicinity of the conceptualized canals.0 Measured hydraulic conductivity values were used to

develop a hydraulic conductivity distribution across the

site. The values ranged between 3.35 x lW 7 and 2.32 x

lo-' d s e c . The distribution was generated by kriging.

0 Flow conditions at the site were calibrated to August

1996 data (Figure l ) , using ground w ater conditions gen-

erally typical of site flow cond itions. The m odel was run

under steady-state flow con ditions.

BTEX Plume Model

alized as follows.

For mod eling purposes, the BTE X plume was conceptu-

BTEX biodegradation was modeled using instantaneous

reaction kinetics.

The base year w as 1978 (after the BTEX p ipeline mp-

ture).

An initial dissolved plume was assumed in order to

account for contaminant conditions prior to 1978.

Sources of contamination (LNAPL dissolution and parti-

tioning from so il) were represen ted using injection wells.

These were placed at the points were LNA PL had been

detected or where known spills had been repo rted. There

were 1 1 cells within the grid identified as source s (Figure

5) .Source concentrations and rates were assumed variable in

time. The injection rates varied between 2.8 x 1W and

1. 1 x m3/sec, and concen trations varied between 100

and 1800mg/L. The modeled injection rates were suffi-

ciently low as not to impact the water balance in the

system.

Initial concentrations of electron acceptors were esti-

mated from field data collected in 1999 (Suarez and Rifai

2002).

Benzene Plume Model

The benzene model differed from BTEX in two keyways.

1. To model biodegrad ation, a first-order reaction was used.

A b iodegradation rate of 0.OOOUday (ha lf-life of 10

years) was used to model the benzene plume (Suarez and

Rifai 2002).

2. Seven wells were used to model sources (Figure 5).

These we lls correspond to the locations where hot ben-

zene spots had been observed.

Model Calibration

The Bioplume I11 model for the site was calibrated by

altering hydraulic parameters and sources (i.e., injection

wells) in a trial-and-error fashion. This was do ne until simu-

lated head s and plumes approximated observed field condi-

tions.

Ground Water Level Calibration

The water table w as calibrated by varying the pum ping

rates at the canals and varying hydraulic conductivity (within

the reported range) at locations where this parameter had not

been m easured. Observed and simulated water contours were

compared to determine the goodness of fit. In addition, water

levels for 27 wells w ere used to compare actual and modeled

heads, and to estimate the calibration error. The calculated

value of the root mean squared error (RMSE) is 0.19 m,

which corresponds to 8.6% of the head drop across the site.

BTEX Plume Calibration

Due to the presence of multiple sources at the site, 11

injection wells were used to simulate BTEX spills into the

ground water (Figure 5 ) . Rates and c oncentrations in these

wells were varied to simulate changes in source strength

observed from the field data. BTEX concentrations measured

Figure 5. Model grid and injection well locations.

58 M.P.Suorez ond H.S. Rifoi/ Ground Water Monitoring 8 Remediation 24, no. 3: 53-68



Figure 6.BTEX plume in 1996: (a) observed and (b) modeled.

in May 1979 were input as the initial condition. Injection

rates were set up at a maximum value of 1.1 x m3/sec o

minimize mounding effects. In particular, the concentration

of BTEX injected through wells 1 and 2 (close to monitoring

wells D-11 and D-7) was varied within the period

1978-1999 based on the observed Concentrations. Addition-

ally, injection rates were decreased with time to account for

changing dissolution rates as a result of LNAPL volume loss

(and subsequent surface area decrease), and for the effect of

Volatilization. Through a trial-and-error procedure, the con-

centrations in the injection wells were calibrated SO that the

total dissolved mass in 1996 (existing mass plus injected

mass minus mass lost via biodegradation) matched the total

dissolved BTEX mass observed in 1996.

The calibration error was determined in the same fashion

as that for simulated heads, an RMSE of 17 mg/L (3.0%)

being obtained for the predicted concentrations. Figure 6

shows a comparison of the observed and modeled BTEX

plumes in 1996, showing that the calibrated plume is in rea-

sonable agreement with the measured plume. The simulated

concentrations are slightly higher than those measured in

1996, but plume extent was in good agreement with that mea-

sured in the field.

The model was further run up to 1998 and the simulated

concentrationswere compared to those measured in Novem-

ber 1998. In order to match the observed concentrations,

source concentrations were changed to reflect observed pat-terns of source decay with time. First, the sources identified

with the numbers 9, 10, and 11 in Figure 5 were removed.

Second, sources 1.2, and 4 were moved -76 m down in the

direction of the ground water. Finally, new injection wells

were added on the north border near wells H-2 and D 4(sources 7 and 3, respectively). This was necessary to match

very high concentrations observed in 1998 in these wells.

The RMSE calculated using the predicted and observed con-

centrations for 1998wa s 15.4 mg/L (1.8%). Figure 7, which

compares the observed and modeled plumes in 1998, shows

that the simulated conditions relate well to the contamination

found.

To verify the appropriateness of the selected parameters,

the model was later run up to 1999 and the simulated con-

centrations compared to those measured in April and Sep-

tember 1999. For the wells in which both sampling rounds

were performed, the observed value was assumed to be theaverage of the two measurements. Model validation using the

1999 data yielded an RMSE of 23 mgL (1.9%). which is

within an acceptable range for this type of simulation. In

addition, 1998 and 1999 concentrations along the centerline

of the plume were compared to observed values as illustrated

in Figure 8. These comparisons show that the calibrated

model adequately represents site conditions.

Benzene Plume Calibration

Seven injection wells were used to simulate benzene

sources into the ground water (Figure 5 ) . Benzene data from

May 1979 were input as the initial benzene plume. As withthe BTEX simulation, changes in injection rates within the

period 1978-1999 correspond to the changes observed from

M.P. SuarezandH.S.Rifod Ground Water Monitoring 8, Remediation 24, no. 3: 53-68 59



Figure 7. BTEX plume in 1998: (a) observed and (b) modeled.

IOOO,

+Simulated value

Measuredvalue

100

0

0 50 100 IS0 200 250 300 350 400

Dbtance from Well D-ll (m)

Measured value

0 100 200 300 406

Dis(8oc.efromWellDl (m)

Figure 8. BTEX concentrations along plume centerline: (a)1998 and (b)1999.

field data. The 1996 plume and dissolved mass were matched

in a trial-and-error fashion. A plot of the concentrations gen-

erated using the aforementioned sources of contamination vs.

the observed concentrations in 1996 shows that the simulated

concentrations match the 1996 field observed values rela-

tively well (Figure 9). A calibration error (measured as RM S)

equal to 20 mg/L (2.3%)was obtained for the predicted con-

centrations. Figure 9 shows that these concentrations are gen-

erally higher than those me asured in 1996, but the shap e of

the plume is similar to that observed. The area of the simu -

lated plume is, however, greater than the plume dimensions

measured in the field. This is due to difficulties in matching

small concentrations measured in the leading edge using a

small biodegrada tion rate (Le., half-life of 10years).

The model was further run up to 1998 and compared to

concentrations measured in Novem ber 1998. As a result of

this exercise, two new benzene sources were added to the

model in the northeastern area (BE6 and B E7). The RMSE

calculated using the predicted and observed concentrations

for 1998 was 19.6 mg/L (2.3%). A comparison of the

observed and modeled plumes in 1998 (Figure 1 0) shows that

the extent of the calibrated plume is in reasonab le agreement

with the dimensions of the m easured plume.

As with the BTEX plume, the model was validated bymatching simulated concentrations with those measured in

April and September 1999. For the wells in wh ich both sam-

pling rounds were performed, the observed value was

assum ed to be the average of those measu red. Model valida-

tion using the 1999 data yielded an RM SE of 13.2 mg/L

(1.7%), which is within an acceptable range for this simula-

tion. In addition, 1998 and 1999 concentrations along the

60 M.P. uorczondH.S.Rifoi/ Ground Water Monitorin g & Remediation 24, no. 3: 53-68



I

Figure 9. Benzene plume in 1996: (a) observed and (b) modeled.

LEGEND SCALE IN METERS

(04j BENZENE CONCENTWITION (&)9 NE OF ECUALETEXCONCENTRATION (mgk)

Figure 10. Benzene plume in 1998: (a) observed and (b) mod eled.-M.P.Suorez and H.S. Rifai/ Ground Water Monitoring 8 Remediation 24, no. 3: 53-68 61



centerline of the plume were comp ared to observed values as

illustrated in Figure 11. These comparisons showed that the

calibrated m odel adeq uately represents site conditions.

Sensitivity Analysis o f Calibrated Model

Much uncertainty is associated with ground w ater con-

tamination depiction as the majority of aq uifer characteristics

and contaminant concentrations are spatially variable. While

it is true that adequate site characterization is required for a

natural attenuation assessment (and its associated costs are

justified when com pared to the m ore traditional approach of

installing expensive cleanup systems when they are not nec-

essary), sufficient data needed to adequately characterize

uncertainties in these systems is very difficult and costly to

collect. In natural attenuation assessments, the impact of

these uncertainties on plume g eometry and concentrations is

important, particularly with regard to potential risks associ-

ated with the contamination. Various methods are used to

assess this uncertainty, e.g., s tochastic modeling. Sen sitivity

analysis is also commonly used. The latter determines the

effect of model input parameters on model output. For the

calibrated models, reasonable ranges of variation for each

parameter were determined using this approach. The m odel

was run assuming the limits of such ranges, varying each

parameter individually. Table 2 includes the parameters eval-

1000, 1

100

0

0 loo 20 0 300 400

Mitance from Well D-11 (m)

9001 1 I800

2 00a8 600

I 00

-P

POp 30 0

$ 200

100

0

(a)

0 50 100 I50 200 250 300 350 400

Distance from WeU D-11 (m)

Figure 11. Benzene concentrations along plume centerline: (a)1998 and (b ) 1999.

uated in the sensitivity analysis, as well as the ranges w ithin

which they were varied.

The va riations in model output due to variations in input

parameters were quantified using two different criteria.

These were plume length (assuming 5 pg/L as the minimum

concentration) and concentrations in two locations, i.e.,

source area (well D-1 1) and midplume point (150 m down-

gradient from source well). The values obtained for these two

criteria were com pared to the values for the base case (1 996

calibration plume) to determine percentage of variation

(Table 3).

With respect to plume length, data in Table 3 indicate that

this criterion was most sensitive to changes in the biodegra-

dation parameters. These were, respectively, assimilative

capacity and biodegradation rate for the instantaneous and

first-order models. The maximum simulated BTEX plume

length was 686 m for a run assuming no b iodegradation. In

contrast, the maximum benzene plume length was 1067 m for

the higher hyd raulic conductivity value.

Additionally, concentrations at two different locations

were evaluated for the aforemen tioned scenarios. The per-

centage of variation of the simulated concentra tions was then

plotted in Figure s 12 and 13. As can be seen in Figure 12, for

the location within the source area (well D-1 I) , the model

was most sensitive to source definition (concentration and

injection rates) and hydraulic conductivity if assuming

instantaneous kinetics. Conversely, the first-order model was

most sensitive to biodegradation rate and source definition.

For the BT EX plume specifically, the maximum concen-

tration in the source area (12 12 mg/L) was obtained when the

source concentrations were multiplied by a factor of two. On

the other hand, the minimum concentration (61 mg/L) was

reached when the hydraulic conductivities were assigned the

upper limit value. For the benzene plume, on the other hand,

the maximum concentration in the source area (1 194 mg/L)

was obtained for the higher injection rate and the m inimum

(4 mg/L) for the higher biodegradation rate.

Data in Figure 13 show the sensitivity analysis for con-

centrations in a midplum e location. In this case, the parame-

ter that caused the most impact on concentrations was

biodegradation for both the BTEX and ben zene models. The

data presented in Table 3 and Figures 12 and I3 also indicate

that longitudinal and transverse dispersivities do not have a

significant impact on model results.

Model Predictions

Using the calibrated and verified models, future site con-

ditions were predicted by running the B ioplume I11 model up

to the year 2206. Two different scenarios were considered.

1. The injection rates and concentrations were decreased

with time using a line of best fi t of source d ata between

1978 and 1999.

2. The m odel was run assuming 20% annual reduction in

LNAPL volume.

For each scenario, six criteria were evaluated: maximum

concentration, average concentration across the site, distanceto downgradient edge from well D-l 1, total dissolved m ass,

plume length, and time to reach the cleanup goal. This was

defined as the time required to achieve concentrations lower

62 M.P. uarezand H.S. Rifail Ground Water MonitoringL Remediation 24, no. 3: 53-68



Table 2Variat ion of Parameters fo r Sensitivity Analysis

Parameter Range Explanation

Hydraulic conductivity

Longitudinal dispersivity

Ratio transverse1

longitudinal dispersivity

Retardation factor

Biodegradation capacity

(BTEX simulation)

First order biodegradation

rate (Benzene simulation)

Sourc e injection rate

Source concentration

1 x lo-* to 2 x d s e c

0.003 to 30.48 m

0 to 0.33 ax

1 to 17

0 to 480 mg/L

0 to 0.0I2lday

0.1 to 5 (multiplier)

0.5 to 2 (multiplier)

Representative values fo r silts and sands (W iedemeier et al. 1999).

All the hydraulic conductivity values were multiplied by a factor

such that the maximum and minimum values were never outside

the reported range. These multipliers were calculated to be 0.009

an d 6 ; hus the model was run first for the lower limit (all values

X 0.009) and later for the higher limit.

Lower limit assumes no dispersion. Higher limit set to 0.1 X the

plume length (Spitz and Moreno 1996).

Lower limit assumes no transverse dispersion. Transverse disper-

sivity can also be estimated as 0.3301~ASTM 1995;US. PA

1986); this estimate was used as the upper limit.

For representative values of fraction of organic carbon for sands

and silts within the range O.OOO5 to 0.007 (Wiedem eier et al.

1999). published values of Kw or the BTEX compounds, and an

assumed bulk density of 1.9 g/cm J (Freeze and Cherry 1979).

the coefficient of retardation for the BTEX compounds ranged

between 1.2 and 17.

The lower limit assumed no biodegradation (absence of electron

acceptors). The upper limit was determined assuming the maxi-

mum background concentrations reported in the reviewed litera-

ture as cited in (Suarez 2000). That is 10,40,500, IOOO, an d 500

mg/L for oxygen, nitrate, ferric iron, sulfate, and carbon dioxide,

respectively. The maximum reported biodegradation capacity via

iron reduction and methanogenesis was multiplied by a factor of

five since byproduct concentrations do not give a good estimate of

assimilative capacity.

The lower limit assumed no benzene biodegradation. The upper

limit was determined as the 90th percentile of biodegradation

rates obtained from 38 field sites and reported in Rifai et al.

(unpublished).

The injection rate was decreased by one orde r of magnitude for

the lower limit. The upper limit was determined finding the maxi-

mum rate that did not cause disturbance of the ground water

contours.

than 5 mg/L in 95% of the cells for the BTEX plume and

0.005 mg/L for the benzene plume. The results of the analy-

ses are subsequently discussed.

BTEX Plume Predictions

Alternative I - ecaying Sources Using Regression Values

Results from model simulations show that the plume willdecrease substantially as it moves southward toward the sea.

For instance , model results indicate that by the year 2106 the

Plume will be -381 m long and will have a maximum con-

centration of 336 m g/L. Results from the model predictions

show that for this scenario the remediation goal will not be

reached until the year 220 6 (Table 4). he average and max-

imum BTE X concentrations by the year 2 206 will be 5.2 and

244 m g/L, respectively.

Alternative 2-Decaying Sources

Assuming 20%Annual LNAPL Removal

Th e LNAPL removal was simulated by decreasing both

injection rate and concentration by 20% per year. Table 4

includes the results of model predictions. It can be seen that

by the year 2206 the average BTEX concentration across thesite will be 4.0 mg/L with a m aximum concentration of 214

mg/L. For this alternative, a 50%reduction in total dissolvedmass is expected to occur between the years 2006 and 2206.

Model predictions show that remediation goals for this sce-nario will be achieved by the year 2 156.

M.P. SuorezondH.5. Rifoi/ Ground Water Monitoring 8, Remediation 24 , no. 3: 53-68 63



Benzene Plume Predictions

Alte rnat ive 1-Decaying Sources Using Regression Values

Results from model simulations (Table 4) show that once

the sources are depleted (year 2096), the plume w ill shrink

rapidly. By the year 2106, the benzene plume will have

reduced its length by 60% and concen trations across the site

will be zero. Overall, model simulations using a first-order

biodegradation rate showed that the leading edge of the

plume will not travel farther from where it was in 1999.

Rem ediation goals for this alternative will be achieved by the

year 2 I06 and the benzene plume will be completely

depleted by the year 2 156.

Alte rnat ive 2-Decoying Sources

Assuming 20%Annual LNAPL Removal

It can be seen in Table 4 that by the year 2156 the average

benzene concentration across the site will be 0.01 mg/L with

a maximum concentration of 1O m a . For this alternative, a

99% reduction in total dissolved mass is expected to occur

between the years 2006 and 2106. As for the previous sce-

nario, cleanup goals for the benzene plume will be reached by

the year 2106 and the plume will be depleted by the year

2 156.

Uncertainty Analysis for Model Predictions

Alternative 1, which assumes decaying sources, was

selected to perform the uncertainty analysis for model pre-

dictions. Based on the sensitivity analysis results for the cali-

brated model, five parameters were evaluated for estimating

variations of the predictive model. These parameters

included injection rate, source concentration, hydraulic con-

ductivity, retardation factor, and biodegradation capacity.

To quantify model sim ulation uncertainty, a modification

of the two-point technique (Yen and Guym on 1990) was

used. For this kind of analysis, reasonab le ranges of variation

for the different parameters were determined (Table 2) . Each

variable was then assigned two values that corresponded to

the upper and lower limits of such ranges. The two-point

technique calls for the model to be run for all the possible

permutations of the uncertain variables. Consequently, a total

of 32 (F) imulations were run to establish a statistical pop-

ulation for the differen t output criteria.

The 1996 calibrated model was used as the starting point

for model pred ictions, and fou r criteria were evaluated in the

year 2 106. These criteria include average plume concentra-

tion, distance traveled by the plume, plume length, and dis-

solved mass.

The results of the uncertainty analysis associated with

model assumptions are presented in Figure 14. As can be

seen, the first-order model resulted in lower values of aver-

age concentration and dissolved mass than the instantaneous

model. Regarding plume length and traveled distance, both

models resulted in similar median and maximum values.

Output data were further analyzed to calculate confidence

intervals with a significance level of 95%. The results, as

summarized in Table 5 , indicate that the longest distances

from well D-I1 that the plumes would travel by the year

2106are 720 and 7 19rn for BTEX and benzene, respectively.

3

4 I

Figure 12. Maximum va riations in simulated concentrations atthe source area: (a) instantaneous model and (b) first-orderdecay model.

Add itionally, by the year 2106 the average BTEX concentra-

tion across the site would be at most 28.2 mgL, while the

average benzene concen tration would be 14.7 mg L. Finally,

plume length predictions have a confidence of f 132 and

175 m for BTEX and benzene, respectively.

Summary and Conclusions

The Bioplume 111 model was used to predict the fate and

transport of BTE X and benzene plumes at the study site using

two different kinetic expressions for biodegradation (instan-

taneous and first-ord er rate). It can be conclud ed that natural

attenuation models can be used to simulate BTEX plumes

using instantaneous biodegradation and one-component

plume s using first-order kinetics.The input parameters the Bioplume 111 model was

observed to be m ost sensitive to when using instantaneous

kinetics are source definition, hydraulic conductivity, and

assimilative capacity. For a first-order kinetics simulation, on

the other hand, the model is most sensitive to changes in

biodegradation rate and source definition.

In general, the sensitivity analysis show ed that simu lated

plumes using a first-ord er model for the site were longer than

those obtained using an instantaneous reaction model. The

sensitivity analysis for plume length showed that biodegrada-

tion is a key parame ter for both scen arios, whether for instan-

taneous o r first-order kinetics. Howev er, for the first-order

kinetics, the Bioplume 111 model was most sensitive to

hydrau lic conductivity when looking at plume leng th.

Model predictions showed that if no source is removed,cleanup goals will be achieved by the years 2206 and 2106for the BTEX and benzene plum es, respectively. Removing

64 M.P.SuorezondH.S.Rifoi/ Ground Water Monitoring 8, Remediation 24, no. 3: 53-68



Variable

Table 3Summary f Sensitivity

--1i

iB2_

9EE

0r:gII

10P

-*Maximum distance fmm well D-11 raveledby the leadingplume edge

Concentration (m&) variation A ConcentrationMax Plume Plume

Concentration Length Mid In Plume to Base ' ase

Value (m@) (mt o5pp b)' D-11 D-16 Plume Length D-11 D-16 Plume

BaseCase


Dispersivity

Ratio aT/at

Retardation factor

Biodegradationcapacity

Source injection rate


Average

6K

0.009K

100

0.0

0.33

0

1.2

17

0

480

0.1

5

2c

0.5C

588

28

846

53

640

593

603

600

358

619

450

250

1043

1212

313

595

547

457

229

305

533

305

305

305

229

686

152

305

533

305

305

36

588

61

732

516

638

593

603

600

312

619

420

67

041

1212

313

548

41

225

0

0

19

0

0

0

0

69

0

0

21

0

0

25

195

I72

108

267

98

266

280

267

16

165

0

245

160

31 1

263

188

0%

-50%

-33%

17%

-33%

-33%

-33%

-50%

-50%

-67%

-33%

17%

-33%

-33%

-30%

-90%

24%

-12%

9%

1%

3%

2%

-47%

5%

-29%

-89%

60%

106%

47%

-7%

449%

-100%

-100%

-54%

-100%

-100%

- 1 0 %

-100%

68%

-100%

-100%

49%

-100%

-1 0 %

-42%

-12%

4 5 %

37%

-50%

42%

44%

37%

-92%

-15%

-100%

26%

-18%

59%

35%

4%

Base Case


Dispersivity

Ratio *aL

Retardation factor

Biodegradation rate

Source injection rate


Average

6K

0.009K

100

0.01

0.33

0

I.2

I7

0

0.012

0.1

5

2c

O X

560

355

974

716

794

768

775

68

I74

1101

219

117

1444

1545

387

707

686

I067

686

762

6%

762

762

762

686

762

152

762

838

762

762

726

560 21 108

1% 105 171

462 15 46

476 24 116

598 20 105

555 21 107

563 21 109

526 20 87

174 15 36

960 73 364

4 0 0

77 20 81

1194 25 292

1116 21 123

282 21 101

516 28 123

56%

0%

11 %

0%

11 %

1 1 %

11%

0%

11%

-78%

1 1%

22%

11 %

11%

6%

-65%

-18%

-15%

7%

-1%

1%

-6%

-69%

71%

-99%

-86%

113%

99%

-50%

-8%

400%

-29%

14%

-5%

0%

0%

-5%

-29%

248%

-1m-5%

19%

0%

0%

36%

58%

-57%

7%

-3%

-1%

1%

-19%

-67%

237%

-100%

-25%

170%

14%

-6%

15%

I 4

Table 4Model Predictions

2006 2056 2106 2156 2206

Parameter Alt 1 Alt 2 Alt 1 Alt 2 Alt 1 Alt 2 Alt 1 Alt 2 Alt 1 Alt 2~

Maximum concentration (m@)

Average concentration ( m a )

Distance from D- I I to

downgradient edge (m)

Totaldissolved mass (kg)

Concentration > 95%

of cells (m@)

BTEX

Benzene

BTEX

Benzene

BTEX

Benzene

BTEX

Benzene

BTEX

Benzene

BTEX

Benzene

672.0

1079.0

11.9

10.1

38

838

28,910

24,090

451914

56.5

16

527.0

974.0

11.1

10.3

38

838

27,250

25.390

38

914

57.1

17

458.0

223.0

10.5

1.7

533

457

29.470

3540

38

533

55.6

3

367.0

11.0

8.6

0.4

457

38

24.580

700

305

38

52.

2

336.0

7.0

7.8

0.1

686

533

25,200

220

38

38

45.6

0

28 O

I .o

6.4

0.2

610

457

20.420

5

229

76

25.5

0

320.0

1 O

6.2

0

762

0

20980

10

3050

20.1

0

261.0

1 o

5.0

0.01

686

457

16.760

5

229

0

4.

0

244.0

5.2

838

17.580

305

-----2.9

0

2 4.0-4.0-762-13.790-229

0

0

0

c I

M.P. Suarez andH. I Rifai/ Ground Water Monitoring& Remediation 24, no. 3: 53-68 65



Table 5Uncertainty Estimation for Model Predictions

BTEX 17.4 1.005 x 103 31.7 17.4 f 10.8

9.0 2.873 X lo2 16.9 8.9 f .8Average concentration (mg/L) Benzene

CriterionI1 Distance traveled by plume' (m)

Standard Confidence Interval

Plume Mean Variance Deviation (or = 0.05)

Plume length (m)

Dissolved mass (kg)

BTEXBenzene

552 2.446 X 105 495526 3.299 X 105 574

BTEX 485 1.487 X 105 386

Benzene 466 2.623 X l(r 512

552f 168526f %

485 f 132

466f 175

BTEX 42,823 7.145 x 109 8.45 x 104 4.28 x 104i2.88 x 104

Benzene 19,890 1.193 X lo9 3.45 X 10" 1.99 x 1 @ * 1.18 x 1@~ ~ ~

'Maximum dismce from well D-11 raveled by the leading plume edge

LNAPL at an annual rate of 20% will shorten the remediation

time for the BTEX plume by 50 years, but it will not have an

impact on the benzene remediation time. While BTEX and

benzene plume dimensions are similar, cleanup times maydiffer because of maximum concentrations, cleanup goals,

and calculated decay rate on a component-by-component

basis. Natural attenuation cleanup times using BTEX and

assimilative capacity are 47% to 90% higher than those for

benzene alone. Finally, the uncertainty analysis for model

predictions showed similar plume lengths and distances trav-

eled by the leading edge for both the benzene and BTEXplumes.

Figure 13.Maximum variations in simulated concentrations ata midplume location: (a) instantaneous model and (b) first-

order decay model.

AcknowledgmentsThe authors would like to acknowledge the funding pro-

videdby

Union CarbideInc.

and the Gulf Coast Hazardous

Substances Research Center for the completion of this work.

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B ogra ph ca SketchesMonica P. Suarez is a researcher in civil and environmental

engineering at the University of Houston. She holds an M.S. in

environmental engineering ro m the University of Ho uston and has

s i x years of experience in waste water treatment and sustainable

development. Her c urrent research focuses on understanding nat-

ural attenuation processes at the field scale. She may be reached

at the University of Houston, 4800 Calhoun Rd., Room N107D,

Houston, Tx 77204 4003; (713) 743-0753; f a x (713) 743-4260;

monica.suarez @m ail. h. edu.

Hanadi S. Rifait corresponding author, is an associate profes-

sor in civil and environmental engineering at the U niversit y of

Houston. Her research efforts o cus on contaminant at e and trans-

port modeling, and remediation and natural attenuation. She ha s

coauthored two textbooks: Ground W ater Contamination: Trans-

port and Remediation, published by Prentice-Hall in 1994 and

1999, and Natural Attenuation o f Fuels and Chlorinated Solvents in

the Subsurface,published by McGraw Hill in 1999. She is the edi-

tor-in-chief of Bioremediation Journal and a member of the US.

Environmental Protection Agency Science Advisory Board Envi-

ronmental Engineering Committee (FYOO) Natural Attenuation

Subcommittee, 2000. Raip may be reached at the University of

Houston, 4800 Calhoun Rd., Room N107D, Houston, ITX

77204 4003 ; (713) 743 4271; ar (713) 743 4260; [email protected].

nternational Center for Ground Water & Public Policy“For public health and natural resources officials of the world”

A / info.ngwa.org/icgwpp

601 Dempsey Road, Westerville, Ohio 43081 U.S.A.614 898.7791 or fax to 614 898.7786

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