Sediment Issue 

Determination of Rates and Extent of 

Dechlorination in PCB-Contaminated 

Sediments During Monitored Natural 

Recovery
 

Purpose 

Introduction 

Methods 

Challenges 

Case Study

 Lake Hartwell 

Superfund Site 

Conclusions 

References 

Purpose

The National Risk Management Research Laboratory (NRMRL) of the U.S. Environmental 

Protection Agency (U.S. EPA) is developing 

effective, inexpensive remediation strategies 

for contaminated sediments. This program 

theme includes the study and development of 

field monitoring tools to evaluate Monitored 

Natural Recovery (MNR) processes in aquatic 

sediments (1). Previous researchers have demonstrated the potential for PCB dechlorination 

in sediments using other evaluation methods, 

such as chiral chemistry (2) and laboratory microcosms (3). In contrast, the approach taken 

Lake Hartwell 

by NRMRL involved characterization of dechlorination in sediments 

using PCB congener fingerprinting and polytopic vector analysis 

(PVA). 

NRMRL conducted studies to evaluate the long-term recovery of 

PCB-contaminated sediments via reductive dechlorination, including 

the magnitude, extent, and rates of ortho and meta plus para dechlorination reactions with sediment depth and time (4, 5). The information learned is summarized in this Sediment Issue, which is intended to 

be used as a reference for site managers and U.S. EPA decision makers 

who may be considering MNR as a contaminated sediments management strategy. The data summarized in this Sediment Issue were generated during field studies conducted by NRMRL in cooperation with 

U.S. EPA Region 4 at the Sangamo-Weston/Twelvemile Creek/Lake 

Hartwell Superfund Site in Pickens County, SC. 

Introduction

In aquatic environments affected by contaminated sediments, risk 

management strategies focus on either removing the contaminated 

material or interrupting exposure pathways by which contaminants 

might pose an ecological or human health risk over time. This is 

generally achieved by dredging, capping, or MNR. MNR relies on 

naturally occuring processes to reduce risk to humans and/or ecological receptors, including physical, biological, and chemical mechanisms 
that act together to contain, destroy, or otherwise 

decrease the bioavailability or toxicity of contaminants in 

sediment (1). 

In the case of PCB-contaminated sediments, where buried 

sediments are anaerobic and ample organic carbon is present, PCBs may undergo metabolic transformation through 

a process known as reductive dechlorination (6-8). This 

metabolic transformation is mediated by bacteria, resulting in a hydrogen substitution for a chlorine on the PCB 

molecule. Generally, higher-chlorinated PCBs are more 

susceptible to transformation via reductive dechlorination, 

resulting in the accumulation of lower-chlorinated PCBs (9). 

Reductive dechlorination preferentially removes chlorines 

from the meta and para positions of PCBs (6), shown in 

Figure 1, which has been shown to lead to the conservation 

of biphenyl rings and ortho chlorines. Dechlorination of 

meta and para chlorines can result in relative detoxification through elimination of coplanar-like congeners and 

aryl receptor-mediated toxicity (10, 11) and through the 

transformation of generally more toxic, higher-chlorinated 

congeners to generally less toxic, though more mobile, 

lower-chlorinated congeners (12). 

Dechlorination patterns can be evaluated by measuring 

historical dechlorination patterns in vertical sediment 

core profiles and by multivariate receptor modeling, such 

as PVA. PVA, a sophisticated statistical procedure, is a 

self-training receptor/mixing model that separates complex 

mixtures into several contributing patterns and determines 

their contributions to each sample (13). PVA has been 

used increasingly for the characterization of PCB sources 

and to determine the transformation of PCBs in complex 

environmental settings (7-9, 14-16). 

Methods 

Identification and Characterization of Weathered and 

Dechlorinated PCB Congener Patterns. Detailed PCB 

analysis of 107 congeners (PCB molecules) was used to 

measure historical dechlorination patterns in vertical sediment core profiles. Assuming the PCB source remains 

unchanged, congener shifts (patterns showing an accumuFigure 1. Meta (3,3',5,5') and Para (4,4') Positions of PCB Molecule. 

lation of lower-chlorinated congeners and a corresponding 

decrease in higher-chlorinated congeners) are characterized 

by comparing surface sediment congener distributions with 

the distributions in buried sediments. 

Congener-specific PCB data are evaluated using PVA. The 

use of a multivariate, variance-based technique, such as 

PVA, offers broad insight into mixing systems at a very 

high level of detail (sample-level resolution) using only data 

concerning the response variables of a system (13). PVA 

provides estimated compositions of contributing PCB fingerprints (end-members) directly from the analysis of the 

ambient data. The end-member (EM) refers to the original 

Aroclor formulation that the PVA analysis has determined 

and points to as being the original material that caused the 

contamination. In other words, PVA analysis is applied 

to a PCB data set that is comprised of an environmentally altered PCB congener composition (e.g., weathered, 

degraded), and the result of the analysis is an identification 

of the original Aroclor(s) that the contamination came 

from some time ago. PVA also provides estimates of the 

relative contribution of each EM in each sample. Only 

after the EM patterns are resolved are they compared to 

literature-reported source and alteration patterns (e.g., Aroclor compositions, PCB dechlorination patterns, and other 

weathering patterns). Using an exploratory approach with 

minimal a priori assumptions helps ensure that unknown 

or unforeseen PCB source or alteration mechanisms are 

not overlooked. Use of PVA, in conjunction with other 

forensic analysis approaches, can be important for understanding long-term fate and formulating efficient remediation strategies. 

Determination of Dechlorination Rates. Sediment age 

dating, using lead-210 (210Pb) and cesium-137 (137Cs), 

and linear relationships between meta plus para chlorine 

concentrations and sediment age are used to determine 

dechlorination rates (4). These rates are compared with 

literature-reported rates and to rates calculated using this 

equation by Zwiernik et al. (17): 

MDR = 1.16Ce + 6.37 (r2

 = 0.960) 

where MDR (nmol Cl-

/g sediment/week) is the maximum 

dechlorination rate and Ce (μg/L) is the aqueous phase 

PCB concentration. The aqueous-phase PCB concentrations were estimated based on equilibrium-partitioning coefficients, fraction of organic carbon, and total PCB 

(t-PCB) concentrations. The magnitude and extent of 

PCB dechlorination is measured by plotting ortho chlorines and meta plus para chlorines per biphenyl molecule 

(i.e., mole chlorine/mole PCB) with sediment depth. 

Linear regression analysis is used to determine the rate of 

meta plus para removals over time (as will be shown in 

later examples in this Sediment Issue). 

2 
 

 

T16

Challenges 

Challenges associated with using PCB dechlorination and 

the above methods to assess the extent of natural recovery 

include: 

• Direct Access to Reference Data Sets – Direct comparison of the congener patterns observed in sediments under 

study to known or historic dechlorination patterns can 

greatly facilitate interpretation; however, raw historic data 

often are unavailable. 

• Assuming Relativeness of Surface Sediment Distributions 

to the PCB Source – It is assumed that surface sediments 

are characteristic of the PCB source; however, if historical 

data from surface sediments are unavailable, this assumption may be impossible to prove. 

• Consistency of Dechlorination – Dechlorination may 

be very extensive in most of the cores, but it may not be 

consistent from core to core or at various depth intervals 

within a single core. 

• Dechlorination Rates – Rates of dechlorination are derived from the laboratory and may be higher than 

dechlorination rates measured directly in the field. 

• Analytical Limitations – Chemical analysis may result 

in the coelution of certain PCBs, making it impossible 

to calculate the numbers of meta and para chlorines per 

biphenyl molecule separately. In order to address 

coeluting congeners in this study, the meta and para 

chlorines were summed so that the magnitude and 

extent of PCB dechlorination were measured using 

ortho chlorines and meta plus para chlorines per 

biphenyl molecule (i.e., moles chlorine/mole 

PCB). However, as subsequently noted later 

in this Sediment Issue, three factors were 

considered before summing the meta and para 

chlorines to calculate dechlorination rates: 1) the 

uniformity of source material in the sediments, 

2) the conservation of ortho chlorines with sediment 

depth and time, and 3) the linear relationship between 

the meta and para chlorines and time. 

Case Study 

Lake Hartwell Superfund Site 

The methods described were conducted as part of an 

evaluation of the recovery of PCB-contaminated lake 

sediments at the Sangamo-Weston/Twelvemile Creek/ 

Lake Hartwell Superfund site (Pickens County, SC), 

shown in Figure 2. The Sangamo-Weston plant manufactured capacitors from 1955 to 1978 using dielectric 

fluids containing Aroclors 1016, 1242, and 1254. 

Though the Sangamo-Weston plant no longer exists, waste 

disposal practices dating back to earlier operations led to 

PCB-contaminated sediments in Lake Hartwell, downstream of the Sangamo-Weston plant (18). 

A total of 280 samples from 18 sediment cores and surface 

sediment samples were collected during two annual events 

conducted in 2000 and 2001. Sediment sample locations 

are shown in Figure 2 as alpha-numeric transects. Sediment 

samples were analyzed for 107 PCB congeners, particle size 

distribution, total organic carbon (TOC), moisture content, and radioisotopes (210Pb and 137Cs). 

1. PCB Dechlorination: End-Member Characterization. 

PCB congener fingerprinting and PVA were used for identification and characterization of weathered and dechlorinated PCB congener patterns. 

Congener shifts were characterized by comparing surface 

sediment congener distributions with the distributions in 

Figure 2. Location Map of Lake Hartwell Transects. Lake Hartwell 

sediment cores were collected at 10 transect locations. Surface sediment 

samples were collected in Twelvemile Creek and in Town Creek above and 

below the former Sangamo-Weston plant. Reprinted with permission from 

(5) . Copyright 2005, American Chemical Society. 

3 
buried sediments and then matched with literature-reported dechlorination patterns from other sites. Examples of 

congener distributions (mole percent) are shown in Figure 

3 for surface and buried samples from the Transect L core 

collected in 2000. Congeners are plotted as they appear 

chromatographically, from left to right and generally from 

low to high molecular weight (from lower-chlorinated to 

higher-chlorinated congeners). Figure 3-c illustrates the 

net congener shifts from high to low chlorinated congeners due primarily to dechlorination, although other 

weathering mechanisms such as biotransformation, sorption, and benthic mixing also may have been involved. 

Negative concentrations in Figure 3-c represent a net 

concentration loss, while positive concentrations represent a net concentration gain. Comparison of the surface 

and buried congener distributions in the Transect L core 

reveals a congener shift from higher- to lower-chlorinated 

congeners with sediment depth and age. 

PVA results were used to determine PCB source and 

dechlorination EM patterns and their distributions in each 

of the cores. Analysis of PVA goodness-of-fit diagnostics 

indicated a four end-member model. 

Figure 4 shows the congener profile of the first end 

member (EM-1) as an example. The similarities between 

congener profiles were evaluated by calculating the cosine 

theta (cos θ) values (19). The cos θ value represents the cosine of the angle between two multivariate vectors, in this 

case the two matrices formed by the congeners used for 

each respective sample. A cos θ value of 0 would indicate 

two completely dissimilar, orthogonal vectors, and a cos 

θ value of 1.0 would indicate two identical vectors. The 

cos θ values were calculated for various Aroclor mixtures 

compared to EM-1, including mixtures of Aroclors 1016, 

1242, 1248, and 1254. Comparison of EM-1 with the 

50/50 Aroclor 1248/1254 mixture shown in Figure 4-b 

(c)

(b)

0-5 cm interval (a)

35-40 cm interval 

Difference of (0-5 cm interval) and (35-40 cm interval) 

Figure 3. Congener Distributions Showing Dechlorination Characteristics for Lake Hartwell Sediments. Panel (a) shows Transect L (year 

2000) surface sediment (0-5 cm) congener distribution; panel (b) shows the congener distribution in the 35-40 cm interval of the year 2000 

Transect L core; panel (c) shows the net dechlorination in the 35-40 cm interval by subtracting the congener distribution in panel b from 

panel a. Reprinted with permission from (4). Copyright 2005, American Chemical Society. 

4 
(b)

(c)

resulted in the highest cos θ value of 0.93. Comparison of 

EM-1 with the 50/50 Aroclor 1242/1254 mixture shown 

in Figure 4-c resulted in a cos θ value of 0.83. Both 

values are close to 1.0 and suggest strong similarities between these two Aroclor mixtures and EM-1. Congener 

profiles for EM-2 through EM-4 are provided by Magar et 

al. (5). 

2. PCB Dechlorination: Rates and Extent. An evaluation was conducted to determine the extent of reductive 

dechlorination by the preferential loss of meta and para 

chlorines, the conservation of ortho chlorines with sediment depth and age, and the historical transformation of 

higher-chlorinated PCB congeners (congeners with four or 

more chlorines) to mono-, di-, and trichlorobiphenyl congeners with sediment depth and time. The magnitude and 

extent of PCB dechlorination was measured by plotting 

ortho chlorines and meta plus para chlorines per biphenyl 

molecule (i.e., moles chlorine/mole PCB) with sediment 

depth, as shown in Figure 5. The loss of meta and para 

chlorines and the conservation of ortho chlorines with 

sediment depth suggests that the PCBs in the sediments 

underwent reductive dechlorination after burial. 

Dechlorination rates were determined on a sample-bysample basis for the Lake Hartwell site by plotting the 

numbers of meta plus para chlorines per biphenyl molecule 

(moles chlorine/mole PCB) with sediment age. Linear 

regression was used to determine the rate of meta plus para 

chlorine removals over time. Results of the linear regression analyses and corresponding meta plus para dechlorination rates measured for 2000 and 2001 cores are shown 

in Table 1. Three factors made it possible to calculate 

meta plus para dechlorination rates in this study: 1) the 

source material was relatively uniform throughout the Lake 

Hartwell surface sediments, 2) ortho chlorines were well 

conserved with sediment depth and time (the number of 

ortho chlorines did not change with depth since the input 

composition did not change with time), and 3) the linear 

Generated by 

the PVA model 

50/50 Arochlor 

1248/1254 mix 

50/50 Arochlor 

1242/1254 mix 

(a)

(b)

(c)

Figure 4. Congener Profile of EM-1. (a) Generated by the PVA model; (b) 50/50 Aroclor 1248/1254 mix; and (c) a 50/50 Aroclor 

1242/1254 mix for comparisons. Reprinted with permission from (5). Copyright 2005, American Chemical Society. 

5 
 

 

moles Chlorine/mole PCB moles Chlorine/mole PCB

 

 

 

T-OC (c) T-LC (d) 

Depth (cm) Depth (cm) 

T-OB (b) T-OA (a) 

Figure 5. Numbers of Ortho (n) and Meta Plus Para (s) Chlorines per Biphenyl Molecule (Moles Chlorine/Mole PCB) with Sediment Depth for Sediment Cores Collected in 

2001. Figures include (a) Cores T-OA, (b) T-OB, (c) T-OC, and (d) T-LC. Adapted from 

(4). Copyright 2005, American Chemical Society. 

Table 1. Measured Dechlorination Rates Using Moles of Meta Plus 


Para Chlorines Over Measured Time Intervals for Buried Sediments.
 

relationship observed between the number of meta plus para chlorines and time. 

For comparison to rates calculated using 

the equation by Zwiernik et al. (17), the 

average dechlorination rates for the 2000 

and 2001 transect cores (i.e., 0.0403 and 

0.0266 mole Cl-

/mole PCB/yr, respectively, from Table 1) correspond to 2.9 x 

10-6 mole Cl-

/g PCB/week and 2.2 x 10-6 

mole Cl-

/g PCB/week, assuming 261 g/ 

mole for Aroclor 1242 (the MDR equation was calculated using experiments 

with Aroclor 1242) and 52 weeks per 

year. Thus, average dechlorination rates 

assuming a sediment PCB concentration 

of 60 mg/kg (60,000 nanograms/gram) 

equates to 0.174 and 0.132 nmole Cl-

/g 

sediment/week for the 2000 and 2001 

rates, respectively. 

An inverse of the dechlorination rate 

indicates the time required for chlorine 

removal. Thus, for the average dechlorination rate for the 2001 transect cores, 

the amount of time for chlorine removal 

would be about 33 years. 

Conclusions 

At PCB-contaminated sediment sites, 

dechlorination may be an important 

component of the natural recovery of the 

sediments when anaerobic conditions 

Core Depth 

Range (cm) 

Date Rangea 

(year) 

No. of 

Samples 

2000 Transect Coresb 

Percent Decrease 

(mole Cl-/mole PCB/yr) 

(95% Confidence Limits) 

Correlation 

Coefficient 

T-O 

T-N 

T-L 

T-I 

T-T6 

Average 

0 – 40 

0 – 40 

0 – 35 

0 – 60 

0 – 20 

1981 – 1999 

1958 – 1997 

1979 – 1999 

1980 – 1999 

1960 – 1998 

8 

8 

7 

11 

4 

2001 Transect Coresc 

6.03 (6.01, 6.05)

3.21 (3.20, 3.23)

5.76 (5.73, 5.79)

6.25 (6.22, 6.27)

2.81 (2.80, 2.82)

4.03 (4.02, 4.04) 

0.92 

0.85 

0.89 

0.88 

0.97 

0.79 

T-OC 

T-LA 

T-LB 

T-IA 

T-IB 

Average 

20 – 100 

15 – 35 

0 – 60 

0 – 20 

0 – 15 

1952 – 2000 

1962 – 1984 

1987 – 2001 

1993 – 2000 

1996 – 2000 

11 

4 

7 

4 

3 

1.52 (1.50, 1.53)

6.33 (6.29, 6.37)

8.33 (8.31, 8.35)

14.1 (14.1, 14.1)

16.4 (16.1, 16.6)

2.66 (2.65, 2.68) 

0.68 

0.94 

0.97 

0.99 

0.85 

0.52 

a

 Dates were determined using 210Pb and 137Cs age dating techniques. 

b

 The cores for the year 2000 were collected at the centerline of the 10 transects shown in Figure 2, i.e., one core to the depth indicated per 

transect. 

The cores for the year 2001 were collected laterally along (or across) three of the 10 transects shown in Figure 2. Three cores were collected to 

depth across Transect O (designated A, B, and C), three across Transect L (again designated A, B, and C), and two across Transect I (designated 

A and B). 

6 

c 
 

 

 

 

exist and the source(s) of PCBs in sediment remain 

unchanged. Under anaerobic conditions, the primary 

metabolic pathway for PCBs is reductive dechlorination in which chlorine removal and substitution with 

hydrogen by bacteria result in a reduced organic compound with fewer chlorine molecules (6-8). 

Reductive dechlorination of PCBs preferentially 

removes chlorines from the meta and para positions 

(6), which has been shown to lead to the conservation 

of biphenyl rings and ortho chlorines in laboratory 

dechlorinating enrichment cultures (14, 15). Generally, higher-chlorinated biphenyls are preferentially 

dechlorinated over lower-chlorinated congeners resulting in the accumulation of mono-, di-, and trichlorobiphenyls (9). As such, reductive dechlorination 

can be identified by the historical transformation of 

higher-chlorinated PCB congeners with sediment 

depth and time, and through the preferential loss of 

meta and para chlorines and the conservation of ortho 

chlorines. Determination of dechlorination rates is 

useful for predicting the number of years for chlorine 

loss to occur (i.e., for predicting when positive impacts 

of dechlorination could be observed). 

PCB congener fingerprinting and multivariate receptor 

modeling such as PVA can be used as exploratory data 

analysis tools to characterize PCB sources and alteration patterns. PCB sources and alteration patterns 

are determined by comparing PVA EM patterns with 

known source patterns (i.e., Aroclors or Aroclor mixtures) and literature-reported alteration patterns. PVA 

also is used to characterize the vertical and lateral distributions of PCB source and dechlorination patterns. 

Utilization of PCB dechlorination to assess the extent 

of natural recovery has proven to be a valuable tool; 

however, challenges associated with this tool may be 

encountered. Some of these challenges have been 

summarized herein to enable site managers to account 

for them in their research design and interpretation of 

results. 

References 

(1)	 United States Environmental Protection Agency. 2005. Contaminated Sediment Remediation Guidance for Hazardous Waste Sites, OSWER 

9355.0-85, EPA540/R05/012. December. http://www.epa.gov/ 

Superfund/resouces/sediment/pdfs/guidance/pdf. 

(2)	 Wong, C.S., A.W. Garrison, and W.T. Foreman. 2001. Enantiomeric 

Composition of Chiral Polychlorinated Biphenyl Atropisomers in 

Aquatic Bed Sediment. Environ. Sci. Technol., 35 (1): 33-39. 

(3)	 Pakdeesusuk, U., W.J. Jones, C.M. Lee, A.W. Garrison, W.L. O’Niell, 

D.L. Freedman, J.T. Coates, and C.S. Wong. 2003. Changes in 

Enantiomeric Fractions during Microbial Reductive Dechlorination of 

PCB132, PCB149, and Aroclor 1254 in Lake Hartwell Sediment Microcosms. Environ. Sci. Technol., 37 (6): 1100-1107. 

(4)	 Magar, V.S, R.C. Brenner, G.W. Johnson, and J.F. Quensen, III. 2005. 

Long-Term Recovery of PCB-Contaminated Sediments at the Lake 

Hartwell Superfund Site: PCB Dechlorination. 2. Rates and Extent. Environ. Sci. Technol., 39 (10): 3548-3554. 

(5)	 Magar, V.S., G.W. Johnson, R.C. Brenner, J.F. Quensen, III, E.A. Foote, G. 

Durell, J.A. Ickes, and C. Peven-McCarthy. 2005. Long-Term Recovery of 

PCB-Contaminated Sediments at the Lake Hartwell Superfund Site: PCB 

Dechlorination. 1. End-Member Characterization. Environ. Sci. Technol., 

39 (10): 3538-3547. 

(6)	 Bedard, D.L. and J.F. Quensen, III. 1995. Microbial Reductive Dechlorination of Polychlorinated Biphenyls. In: Microbial Transformation and 

Degradation of Toxic Organic Chemicals, pp. 127-216, L.Y. Young and C. 

Cerniglia (Eds.). Wiley-Liss Division, John Wiley & Sons, Inc.; New York, 

NY. 

(7)	 Mohn, W.W., and J.M. Tiedje. 1992. Microbial Reductive Dechlorination. Microbiol. Rev., 6: 482-507. 

(8)	 Magar, V.S. 2003. PCB Treatment Alternatives and Research Directions. 

J. Environ. Eng., 129 (11): 961-965. 

(9)	 Quensen, J.F., III, and J.M. Tiedje. 1997. Evaluation of PCB Dechlorination in Sediments. In: Methods in Biotechnology; Bioremediation Protocols, 

pp. 257-273, D. Sheehan (Ed.). Humana Press, Inc.; Totowa, NJ. 

(10) McFarland, V. and J. Clarke. 1989. Environmental Occurrence, Abundance, and Potential Toxicity of Polychlorinated Biphenyl 

Congeners: Considerations for a Congener-Specific Analysis. Environ. 

Health Perspect., 81: 225-239. 

(11) Quensen, J.F., M.A. Mousa, S.A. Boyd, J.T. Sanderson, K.I. Froese, and 

J.P. Giesy. 1998. Reduction of Ah Receptor Mediated Activity of PCB 

Mixtures Due to Anaerobic Microbial Dechlorination. Environ. Toxicol. 

Chem., 17 (5): 806-813. 

(12) Agency for Toxic Substances and Disease Registry (ATSDR). 2000. Toxicological Profile for Polychlorinated Biphenyls (PCBs). Division of Toxicology, 

Toxicology Information Branch; Atlanta, GA. 

(13) Barabaás, N., P. Adriaens, and P. Goovaerts. 2004. Modified Polytopic 

Vector Analysis to Identify and Quantify a Dioxin Dechlorination Signature 

in Sediments. 1. Theory. Environ. Sci. Technol., 38 (6): 1813-1820. 

(14) Tiedje, J.M., J.F. Quensen, III, J. Chee-Sanford, J.P. Schimel, and S.A. 

Boyd. 1993. Microbial Reductive Dechlorination of PCBs. Biodegradation, 4: 231-240. 

(15) Quensen, J.F., III, J.M. Tiedje, and S.A. Boyd. 1990. Dechlorination of 

Four Commercial Polychlorinated Biphenyl Mixtures (Aroclors) by Microorganisms from Sediments. Appl. Environ. Microbiol., 56: 2360-2369. 

(16) van Dort, H.M. and D.L. Bedard. 1991. Reductive Ortho and Meta 

Dechlorination of a Polychlorinated Biphenyl Congener by Anaerobic 

Microorganisms. Appl. Environ. Microbiol., 57: 1576-1578. 

(17) Zwiernik, M.J., J.F. Quensen, III, and S.A. Boyd. 1999. Residual 

Petroleum in Sediments Reduces the Bioavailability and Rate of Reductive 

Dechlorination of Aroclor 1242. Environ. Sci. Technol., 33 (20): 3574-3578. 

(18) United States Environmental Protection Agency. 1994. Superfund Record 

of Decision: Sangamo-Weston/Twelvemile Creek/Lake Hartwell Site, Pickens, 

GA: Operable Unit 2. EPA/ROD/R04-94/178. 

(19) Davis, J.C. 1986. Statistics and Data Analysis in Geology. John Wiley & 

Sons, Inc.; New York, NY. 

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