r/EPA
United States
Environmental Protection
Agency
Office of Environmental
Information
Washington, DC 20460
EPA/240/B-06/004
February 2006
Systematic Planning:
A Case Study for Hazardous
Waste Site Investigations
EPA QA/CS-1
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FOREWORD
This document, Systematic Planning Using the Data Quality Objectives Process, shows
the use of the Data Quality Objectives (DQO) Process in the form of a case study. The
Environmental Protection Agency (EPA) has developed the DQO Process for project managers
and planners to help them collect the appropriate type, quantity, and quality of data needed to
support Agency actions. This guidance is the culmination of experiences in the design and
collection environmental data in different Program Offices at the EPA.
Systematic Planning Using the Data Quality Objectives Process is one of a series of
quality management documents that the EPA Quality Staff has prepared to assist users in
implementing the Agency-wide Quality System. Other related documents include:
EPA QA/G-4 Systematic Planning using the DQO Process
EPA QA/G-5S Guidance on Choosing a Sampling Design for Environmental Data
Collection
EPA QA/G-9R Data Quality Assessment: A Reviewer's Guide
EPA QA/G-9S Data Quality Assessment: Statistical Methods for Practitioners
This document provides guidance to EPA program managers and planning teams as well
as to the general public as appropriate. It does not impose legally binding requirements and may
not apply to a particular situation based on the circumstances. EPA retains the discretion to
adopt approaches on a case-by-case basis that differ from this guidance where appropriate.
This case study is one of the U.S. Environmental Protection Agency Quality System
Series documents. These documents describe the EPA policies and procedures for planning,
implementing, and assessing the effectiveness of the Quality System. Mention of any
copyrighted method does not constitute endorsement. These documents are updated
periodically to incorporate new topics and revisions or refinements to existing procedures.
Comments received on this version will be considered for inclusion in subsequent versions.
Please send your comments to:
Quality Staff (2811R)
Office of Environmental Information
U.S. Environmental Protection Agency
1200 Pennsylvania Avenue N.W.
Washington, DC 20460
Phone: (202)564-6830
Fax: (202)565-2441
E-mail: quality@epa.gov
Copies of the EPA's Quality System documents may be downloaded at: www.epa.gov/quality.
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PREFACE
Systematic Planning Using the Data Quality Objectives Process: A Case Study of a
Hazardous Waste Investigation describes the Data Quality Objectives (DQO) Process in a
decision-making situation. The case study shows how application of the DQO Process leads to
sound data collection techniques, sampling methods, and analysis of the results for decision
making. Elementary Data Quality Assessment is used to draw conclusions from the results.
The case study is presented in two parts - a Preliminary Investigation followed by a
Remedial Investigation - which correspond to the general stages of data collection and analysis
in an environmental investigation. With each investigation, information is presented according to
the three stages of EPA's Quality System - planning, implementation, and assessment. The case
study demonstrates how the study team succeeded in establishing the nature and extent of site
contamination and contaminants of potential concern during the Preliminary Investigation, which
provided the data necessary to support a well focused, statistically-based, sampling campaign to
complete the subsequent Remedial Investigation.
While reviewing the DQO development phase of the Preliminary Investigation, one
should focus on the iterative manner used for the DQO steps (concept grounded in good sense).
In the implementation phase, attention should be given to how a flexible probabilistic sampling
scheme was developed. In the final phase, assessment, note how only rudimentary statistics
were generated in the Preliminary Investigation but were enough to lay the groundwork for the
Remedial Investigation.
In the Remedial Investigation, the DQO activity was quite abbreviated due to the
efficiency of the DQO Process in the Preliminary Investigation. DQO activity in the
implementation phase was equally short. The assessment phase used simple statistical
techniques to analyze the data to produce a clear picture of what was happening and what
subsequent activities should be.
The case study is intended for all EPA and extramural organizations that 1) have quality
systems based on EPA policies and specifications, 2) may periodically assess these quality
systems for compliance to the specifications, or 3) may be assessed by EPA. The use of the
DQO Process conforms to the requirements of EPA Order 5360.1 A2 (EPA 2000) to use
systematic planning in the collection of environmental data.
The techniques discussed in this case study are non-mandatory and the case study is
intended to help project managers and staff understand how the DQO Process should be applied
in practical situations. The data and techniques discussed in the case study are real; however, the
location and identifying characteristics of the actual site have been modified to protect its
identity.
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TABLE OF CONTENTS
1. INTRODUCTION 1
1.1 Purpose and Scope 1
1.2 Case Study Background 1
1.3 Site History and Description 2
2. PRELIMINARY INVESTIGATIONS 3
2.1 Planning the Preliminary Investigations 5
2.2 Implementation of the Preliminary Investigations 14
2.3 Assessment the Preliminary Assessment 15
2.3.1 Real-Time Data Assessment and Post Stratification 15
2.3.2 Sample Size Selection for Background Comparisons 16
2.3.3 Decision to use Fixed Laboratory Data with BAP Equivalents 18
2.4 Preliminary Investigation Conclusions 18
3. REMEDIAL INVESTIGATION 21
3.1 Planning the Remedial Investigation 21
3.2 Implementation of the Remedial Investigation 21
3.3 Assessment of the Remedial Investigation 24
3.3.1 The Remedial Investigation Data 24
3.3.2 Calculation of Upper Confidence Limits 25
4. CONCLUSIONS 29
5. SUMMARY OF THE DQA STUDY 29
6. REFERENCES 30
APPENDIX A. THE PAH IMMONASSAY METHOD A-l
APPENDIX B. VISUAL SAMPLE PLAN B-l
APPENDIX C. SUMMARY OF THE DOWS DEVELOPED FOR THE PRELIMINARY
INVESTIGATION C-l
APPENDIX D. FIELD IMPLEMENTATION DETAILS D-l
APPENDIX E. SAMPLE SIZE SELECTION FOR BACKGROUND COMPARISONS E-1
APPENDIX F. COMPARISONS OF IMMUNOSSAY AND FIXED LABORATORY
RESULTS F-l
APPENDIX G. SUMMARY OF THE PRELIMINARY INVESTIGATIONS STATISTICAL
ANALYSIS OF THE COPCS G-l
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LIST OF FIGURES
Figure 1-1 M&HLtd. Site Map 3
Figure 2-1. The Data Quality Objectives Process 4
Figure 2-2 Initial Conceptual Site Model 5
Figure 2-3 Decision Logic Diagram Part 1: Initial Steps 9
Figure 2-4 Decision Logic Diagram Part 2: Preliminary Investigation Implementation Logic ...11
Figure 2-5 Real-Time Data Assessment Process Flow Chart 12
Figure 2-6 Sample Locations for Preliminary Investigation 13
Figure 2-7 Post Strata Showing 0-3ft.Weighted Average total PAH Concentrations 17
Figure 2-8 Locations and Depths Selected for Fixed Lab Analyses 17
Figure 3-1 Combined Preliminary and RI Sampling Location Map 23
Figure 3-2 Box-and-Whisker Plots BaP Equivalent Concentration Weighted Averages 26
Figure 3-3 Box-and-Whisker Plots BaP Equivalent Concentrations in the Northern (left) and
Southern (right) Sample Locations 27
Figure B-l Wilicoxon Signed Rank (One Sample) Test B-2
Figure B-2 Hotspot Sampling of 112500 Feet B-5
Figure G-l BaP Equivalents Box Plots: Standard and Log Scales G-2
Figure G-2 Arsenic Standard and Log Scales G-6
Figure G-3 Benzo(a)anthracene Box Plots: Standard and Log Scales G-7
Figure G-4 Benzo(a)pyrene Box Plots: Standard and Log Scales G-7
Figure G-5 Benzo(b)flouranthene Box Plots: Standard and Log Scales G-8
Figure G-6 Benzo(g,h,i)perylene Box Plots: Standard and Log Scales G-8
Figure G-7 Benzo(k)fluoranthene Box Plots: Standard and Log Scales G-9
Figure G-8 Chrysene Box Plots: Standard and Log Scales G-9
Figure G-9 Fluoranthene Box Plots: Standard and Log Scales G-10
Figure G-10 Indeno(l,2,3cd)pyrene Box Plots: Standard and Log Scales G-10
Figure G-ll Phenanthene Box Plots: Standard and Log Scales G-ll
Figure G-12 Pyrrne Box Plots: Standard and Log Scales G-ll
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LIST OF TABLES
Table 2-1 Median and Maxima for the Three Areas 19
Table 2-2 Number of Detects and Standard Deviation of the Three Areas 19
Table 2-3 Risk Assessment Meeting Notes 20
Table 3-1 Risk Assessment Meeting Notes 21
Table 3-2 Data Quality Objectives Summary Table for the Remedial Investigations 22
Table 3-3 BaP Equivalent Concentrations (ppb) for the Post Stratified Operations Area 24
Table 3-4 Upper 95% Confidence Intervals Northern Location 28
Table 3-5 Upper 95% Confidence Intervals Southern Location 28
Table 3-6 Upper 95% Confidence Intervals All Locations 28
Table 3-7 Upper 95% Confidence Intervals Northern Locations Weighted Data 28
Table 3-8 Upper 95% Confidence Intervals Southern Locations Weighted Data 28
Table 3-9 Upper 95% Confidence Intervals All Locations Weighted Data 28
Table B-l Summary of Sampling Design B-4
Table B-2 Number of Samples B-6
Table B-3 Cost Information B-6
Table E-l Sample Size Required in Each Site and Background Location E-l
Table F-1 Correlation of Fixed Laboratory total PAH with Immunoassay total PAH F-1
Table F-2 Correlation of Fixed Laboratory BaP equivalents with Immunoassay total PAH F-l
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LIST OF ACRONYMS USED IN THIS CASE STUDY
BaP Benzo(a)pyrene
CERCLA Comprehensive Environmental Response, Compensation, and Liability Act
COPCs Contaminants of potential concern
CSM Conceptual site model
DQOs Data Quality Objectives
FS Feasibility Study
GW Ground water
HH Human Health
MGP Manufactured Gas Plant
PAHs Polycyclic Aromatic Hydrocarbons
PCB Polychlorinated Biphenyls
QAPP Quality Assurance Project Plan
PI Preliminary Investigation
RI Remedial Investigation
UCL Upper Confidence Limit
VOCs Volatile Organic Compounds
VSP Visual Sample Plan
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1. INTRODUCTION
1.1 Purpose and Scope
The primary objective of this case study is to demonstrate the application of EPA's
systematic planning guidance, associated statistical design, and assessment tools to derive
sampling design and quality planning documents at each stage of an environmental investigation.
This case study is presented to provide insights into the process to systematic planning applied to
hazardous waste sites.
The case study focuses on a manufacturing/shipping facility situated near the downtown
of Brufton, a small city located on the U.S. east coast. A recent dredging operation revealed the
presence of high levels of Poly cyclic Aromatic Hydrocarbons (PAHs) in offshore sediments,
calling into question whether the facility was the source of the observed contamination.
Research into previous uses of the property found that the site was the location of a former gas
manufacturing plant. Similar to many small towns in the U.S., a manufactured gas plant (MGP)
operated in the town between the late 1800s and mid-1900s. At these plants, coal or oil was
heated in the absence of oxygen to drive off the volatiles that comprised the manufactured gas.
The typical by-products of this process included tars, ash and other solid waste from boilers, and
wastes from purifiers.
These findings of offshore sediment contamination prompted an investigation of possible
on-shore contamination sources that may be continuing to release these contaminants to the Bay.
Additionally, the investigation revealed thatMcfe H Ltd. was previously the site of an MGP.
This case study will be presented in two parts, corresponding to the general stages of data
collection and analysis in an environmental investigation. These parts are Preliminary
Investigation (Chapter 2) followed by the Remedial Investigation (Chapter 3). In each chapter,
information will be presented according to the three stages of EPA's Quality System - planning,
implementation, and assessment.
The case study will show how the study team succeeded in quickly establishing the
nature and extent of site contamination and contaminants of potential concern (COPCs) during
the Preliminary Investigation (PI), which provided the data necessary to support a well focused,
statistically-based, sampling campaign to complete the subsequent Remedial Investigation (RI).
1.2 Case Study Background
In a recent dredging operation of the ship channel in Buccaneer Bay, near M & H Ltd. (a
shipping and light manufacturing company), PAHs were detected in sediment at levels exceeding
ecological benchmarks. Routine bioassays and bioaccumulation studies resulted in a decision to
dispose of the dredge spoils in an offshore contained area disposal facility, wherein the more
contaminated sediments were capped with relatively clean sediments from other portions of the
channel.
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Research of the available records revealed that from the mid-1870s until approximately
1930, an oil-gas MGP operated on a property on the shore of the Bay. For a period of
approximately 30 years after the MGP was shut down, the land was owned by the regional power
company. During this period, records indicate that visible waste materials were removed. In the
1960s, the remaining derelict plant buildings were demolished and the city assumed ownership
of the land. The property was used as a materials storage yard for the municipality until 1985,
whenM & H Ltd. purchased it from the city.
The former use of this property and the prior existence of waste materials at the site were
documented during initial site inspection activities by local and state environmental agencies.
Negotiations among representatives of the power company, the state environmental agency, and
EPA resulted in the signing of a Consent Order under which the power company and current
landowner will jointly fund investigatory activities at the site. If remediation is required,
mediation will be used to determine who is financially responsible for the cleanup. The
environmental investigation will be conducted in a manner consistent with CERCLA guidance,
and the efforts will be overseen primarily by the State Department of the Environment (with
Regional EPA and other stakeholder participation), but the site has not been included on the
National Priorities List.
The Consent Order separated the site into two Investigation Units: An onshore area, and
an offshore area. The spatial extent and potential impacts related to offshore contamination in the
Bay are being addressed by a separate group. The purpose of the environmental investigation for
onshore contamination described in the Consent Order is to determine:
1. The nature and extent of onshore contamination associated with the former MGP,
2. Whether onshore contamination is a continuing source of contaminants to the Bay
environment, and
3. Whether onshore contamination presents unacceptable human or ecological risks.
1.3 Site History and Description
An MGP uses coal or oil as the feedstock to generate gas in a pyrolytic process. The raw
gas typically contained impurities including tar particles, sulfur, and metals which were
undesirable for transmission and for the purposes of gas illumination or heating. To remove
impurities, the raw gas was subjected to cleaning using various combinations of water sprays or
baths and filtering on media such as lime, wood chips, or iron. These impurities are the source of
recent contamination. One characteristic waste product of some oil-gas MGPs was a powdered
carbon material called lampblack. This originally nontoxic material could easily adsorb aromatic
hydrocarbons if co-disposed with other waste materials.
The property owned byM& H Ltd. occupies an area of approximately 25 acres.
Historical photographs of the area were obtained from archives of the power company and these
revealed that the main structures of the MGP (generator house, boiler house, purifiers, and gas
holders) were located in an area on the southern portion ofM&HLtd.'s property and occupied
several acres of land which today is covered with graveled parking lots and offices. A rail line
and spur runs along the border of the facility opposite the Bay; oil tanks were located near the
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rail spur. Much of the remainder of the property is today comprised of a single large
manufacturing building, shipping/dock facilities along the waterfront, and unused areas. Figure 1
shows the locations of current features of theM& HLtd.'?, site.
Site Map
Open Bay Storage Facility
Former MGP Operations
Area
Buccaneer Bay
Figure 1.1. M&H Ltd. Site Map
2. PRELIMINARY INVESTIGATION
Planning for the Preliminary Investigation was conducted by representatives of the State
Department of the Environment, site owners and operators, and Topdoglnc., an environmental
consulting firm hired as a facilitator. The investigation was led by a planning team who quickly
agreed to use the EPA's recommended method for systematic planning: the seven step Data
Quality Objectives (DQO) Process. The DQO Process (Figure 2-1) was used to design the
Preliminary Investigation (PI), and then repeated in an abbreviated manner for the Remedial
Investigation that followed. An initial conceptual site model (CSM) was developed that describes
these potentially contaminated areas and the fate and transport mechanisms by which
contamination may migrate or change in characteristics over time (Figure 2-2). The CSM was
used to structure discussions among stakeholders regarding the overall technical approach for the
investigation. The team recognized that the boundaries of the site would likely need to be
refined based on empirical data at a later date.
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Step 1. State the Problem.
Define the problem that motivates the study;
identify the planning team, examine budget, schedule
i
Step 2. Identify the Decision.
State how environmental data will be used in solving the
problem; identify study questions, define alternatives
+
Step 3. Identify Inputs to the Decision.
Identify the data & information needed to answer the
study questions, Action Level, and analysis method
i
Step 4. Define the Boundaries of the Study
Specify the target population & characteristics of interest,
define spatial & temporal limits, scale of inference
Step 5. Develop a Decision Rule.
Define the parameter and type of inference, and
develop the logic for drawing conclusions from findings
i
Step 6. Specify Tolerable Limits on Decision Errors
Set acceptable limits based on the consequences of
making a potential decision error
i
Step 7. Develop the Plan for Obtaining Data
Select the resource-effective sampling and analysis plan
that meets the performance criteria
Figure 2-1. The Data Quality Objectives Process
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Sources
Release Mechanisms
Primary Transport
Mechanisms
Primary Impacted
Media
Fate and Transport
Mechanisms
Exposure Media
Operations
Area
Oil Tanks
Storage /
disposal of.
waste
products
Leaks
Spills
^ Pipeline
Losses
Infiltration
Groundwater
Groundwater
flow r
Subsurface
soil
Surface
water
runoff
Biotic uptake
Surface soil T w- Infiltration
Surface
water
runoff
Buccaneer
Bay water
and sediments
Plants and
animals
Groundwater
-1 *
Subsurface
soil
Surface soil
Figure 2-2. Initial Conceptual Site Model
2.1 Planning the Preliminary Investigation
Existing data for the site was limited to PAH measurements from three surface soil
samples collected by the State Department of the Environment subsequent to the discovery of
PAHs in Bay sediments. The team examined this in order to project expected data collection.
These samples showed concentrations of one or more PAHs exceeding residential screening
criteria for two of the three samples and one also exceeded industrial screening criteria.
The information from local records, the findings at other former MGP sites, and the
initial soil samples indicated that residual onshore contamination was likeliest in the following
sub areas of the site:
1) The Operations Area where the generator house, boiler house, purifiers, and gas holders
were located. The three initial soil samples collected by the Department of the
Environment were from this general area
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2) The area of the Oil Holding Tanks near the rail spur and along the route of associated
piping leading towards the Operations Area. Although no records exist that document
releases of oil from tanks or piping, leaks are known to be relatively common based on
investigations of similar MGPs.
A review of findings at similar MGP facilities indicates that the analytical suites for soil
and groundwater samples should include PAHs, VOCs, metals and cyanide.
Topdoglnc. facilitated three rounds of planning team meetings using the DQO Process.
The key points of each meeting are grouped below according to the seven steps of the DQO
Process.
Meeting 1: DQO Steps 1-3 Investigated
Step 1: State the Problem
Topdoglnc. identified the important goals of maintaining timeliness, assuring technical
defensibility, obtaining data adequate for risk-based decision-making, and controlling
project costs.
It was agreed that field-based analysis of chemical concentrations in soil could be used to
establish the approximate spatial boundaries of contamination.
The study should be completed and a report issued within six months, and should not
exceed $100K for analytical and data assessment, analysis and report generation.
There was an extended discussion of land use assumptions. Though residential and
ecological habitat uses were considered, it was agreed to focus on current and future
industrial use scenarios.
Ecological concerns are limited due to current conditions at the site (largely unvegetated
disturbed soil, with extensive packed dirt and gravel roads and parking lots and buildings)
and the agreed-upon future land use. Concern regarding potential migration of
contaminants to the Bay was considered valid, and would be addressed as part of the
planned study.
The CSM identified the major anticipated sources, transport mechanisms, and primary
exposure media. The major pathway of concern was exposure to contaminated soil with
exposure to groundwater being also of potential concern.
Step 2: Identify the Decision
The goals of the PI center on identification of the types of contaminants present at the site
and their spatial boundaries of contamination. The information generated during the PI
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will then be used to establish statistically rigorous data collection in the subsequent
Remedial Investigation.
These are the primary study questions the PI produced:
> What is the nature and extent of contamination in soil and groundwater?
> Is soil and groundwater contamination a significant source of ongoing contamination
to the Bay?
> Are concentrations of contaminants greater than background concentrations?
> Are concentrations of contaminants in addition to PAHs greater than risk-based
screening criteria?
> What is the depth, direction, and rate of groundwater flow?
> What is the potential for erosion of contaminated site soils?
Step 3: Identify Inputs to the Decision
Total PAHs and Benzo(a)pyrene-(BaP) equivalent values were considered to be a good
surrogate for the presence of soil contamination using immunoassay techniques for field
measurements (Appendix A).
In order to confirm that the immunoassay results would provide data of adequate quality
for delineating contaminated soils, a small pilot test using SOPs from a similar
investigation consisting of five surface soil samples was ordered with results to be
presented by the second meeting. Topdoglnc., when preparing for second meeting, made
the team aware that previous steps may have to be refined.
Meeting 2: DQO Steps 2 and 3 Refined; Steps 4-7 Investigated.
Step 2: Identify the Decision
Discussion of whether the proposed study questions are objectively testable led to the
following revised versions:
> What is the spatial distribution of contaminants in soil and are they greater than the
screening criteria?
> Has soil contamination reached the shallow aquifer?
> Is soil and groundwater contamination a significant source of ongoing contamination
to the Bay?
The secondary study vs. primary study questions were then revised accordingly as
follows:
> In what areas of the site do COPC concentrations in soil exceed background
concentrations or industrial risk screening levels?
> Are soil contaminants detected in groundwater at locations of relatively high soil
contamination?
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> What is the potential for erosion of contaminated site soils?
Step 3: Identify Inputs to the Decision
Analytical laboratory PAH results from the five pilot test samples were evaluated. For
these pilot samples, the degree of correlation between total PAH and BaP equivalent
values (a function of the individual PAHs) was reasonably high (r2=0.82) thus
confirming that the field immunoassay method was appropriate for establishing the
boundaries of soil contamination.
Based on information from similar former MGP sites, PAHs, VOCs, metals and cyanide
were identified as potential site contaminants.
It was decided that background data would be compared to the fixed lab confirmation
data collected using a range of statistical tests sensitive to overall shifts as well as shifts
in the upper tail of a distribution (such as would be related to a "hot spot").
In order to assure that background comparisons and estimates of mean and variance can
be performed for all potential site contaminants, it was decided that a minimum number
of fixed laboratory confirmation samples would be analyzed for each of the subareas.
Step 4: Define the Boundaries of the Study
It was decided to divide (stratify) the site after the PI into regions of relatively similar
contaminant concentrations. Estimates of the mean and variance of soil contaminant
concentrations in these subareas would then be used to guide subarea-specific sampling
in the RI with decisions made on a subarea basis.
Well logs from properties adjoiningM&HLtd. indicate that the depth to groundwater of
the first water-bearing zone in the area is between 15 and 25 ft. below ground surface.
There is also evidence of a clay layer in the borehole logs at a depth of approximately 10
ft. below ground surface. This clay layer is ubiquitous in the alluvial deposits near the
Bay and is believed to be continuous.
The boundaries of the onshore investigation were accepted with the provision that they
could be extended if soil or groundwater sampling indicated contamination outside these
boundaries.
Step 5: Develop a Decision Rule
The facilitator presented a draft decision flowchart addressing the primary study
questions that had been established at the previous meeting.
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Step 6: Specify Tolerable Limits on Decision Errors
For the Oil Storage Area and Operations Areas the team will evaluate the use of different
grid scales to intersect a potential hot spot. The selection of a grid size will be done by
examining different options together with the probability of failing to obtain a sample
from a hot spot smaller than a certain size and shape. Visual Sample Plan (VSP) * is a
software tool that may be helpful in this exercise.
Step 7: Develop the Plan for Obtaining Data
Several draft sampling designs were
generated for discussion using VSP. Denser
sampling was proposed for the Operations
and Oil Tanks Areas based on an increased
concern of missing contaminants, the higher
probability of contamination in these areas,
and the potential for smaller locally elevated
areas of contamination. Systematic
sampling grids were selected and as part of
the evaluation of grid spacing options, the
size and shape of a hot spot that the grid
would have a high probability of intersecting
were considered. A draft design was
produced with a sampling grid of
approximately 150 ft. in the Operations and
Oil Tanks Areas and approximately 300 ft.
in the rest of the site.
The initial sampling design resulted in 30
sampling locations within the Operations
Area, 10 locations within the Oil Tanks
Area, and 20 samples in the remaining site
area. Samples from multiple depths were
discussed. Initial cost estimates for
collecting 60 samples at 3-4 depth intervals,
and performing field tests on these samples
was roughly $36,000 (240 @ $150 per
sample). Fixed laboratory confirmation
samples would be roughly $1,000 per
sample.
Conceptual site model of
sources, potential
contaminants, transport,
and exposure media
Agree on dynamic approach for
preliminary investigation (PI) using
field-based methods
Identify subareas of interest based on
CSM and utilize VSP to develop PI
sampling grids
Develop DQOs for PI
Prepare dynamic Work Plan and
QAPP
Initiate implementation of PI
Go to Field
Sampling
flowchart
Figure 2-3. Decision Logic Diagram
Part 1: Initial Steps
* VSP produces all the plans necessary for sound statistically defensible data, and it provides for immediate
comparisons of selected sampling plans. It has the capability of allowing for different sampling and analysis costs to
be compared and contrasted. For details about VSP, see Appendix B.
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Meeting 3: DQO Steps 4-7 Refined
Step 4: Define the Boundaries of the Study
After extended discussion of soil sampling depths intervals; the top interval was defined
as 0 - 0.5 ft. (the traditional definition of "surface soil."), and a second interval of 0.5 -
3 ft. defined (the approximate depth commonly associated with trenches for utilities and
building foundations).
Appropriate depths for lower depth intervals (3- 6 ft; 6 -12 ft, 12 ft. to groundwater)
were not easily agreed upon. The use of four intervals proposed by the State Department
of the Environment was considered acceptable, with the addition of a decision rule to
forego the two deepest intervals if total PAH concentrations in higher intervals were
essentially consistent with background concentrations.
Step 5: Develop a Decision Rule
Reconsideration of the draft decision flow chart lead to a decision to divide it into three
separate charts, two that address the planning stages (see Figures 2-3 and 2-4) and one
that addresses data assessment (Figure 2-5). Figure 2-4 focuses on decisions that will be
made essentially in real time during the sampling campaign as part of a dynamic,
adaptive sampling plan.
Step 6: Specify Tolerable Limits on Decision Errors
The planning team elected to specify error tolerances based on the desire not to miss hot
spots of a specified size and shape, if they are present.
Given the site conceptual model, and experience at other MGP sites, small hotspots were
not expected. The shape of a hot spot was also unknown, however an elliptical shape
was agreed to be a reasonable assumption. Finding a hot spot during the preliminary
investigation will result in further study to evaluate the risk associated with the elevated
chemistry - however, failing to find a hot spot might result in no further action. Using
VSP to investigate alternatives, the sample sizes required to have a 95% probability of
detecting a hot spot of approximately 1/8 acre in the two primary areas of concern, and
one acre in the rest of the site were determined. A five percent chance of missing a hot
spot of this size was considered acceptable, recognizing the consequences of failing to
evaluate the need for action.
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Initiate PI sampling using the PAH
immunoassay and grid sampling plan.
Obtain Geoprobe cores in the sequence
specified in the field sampling plan
Conduct immunoassays on all 0 - 0.5 ft
and 0.5 to 3 ft increments collected
during the day
ny visual o
olfactory evidence
of contamination
low 3 ft?
PAHs detected* in
0.5-3 ft interval?
Conduct immunoassays on the 3 - 6 ft
interval
3o not analyze deeper core
intervals at this location
ny visual o
olfactory evidence
of contamination
low 6 ft?
PAHs detected
in 3 6 ft interval r<
Conduct immunoassays on the > 6 ft
interval
Do not analyze deeper core
intervals at this location
* "detected" could be changed to measured at cone > some screening value
if pilot test info provides approximate BaP equivalent for total PAHs
Add total PAH results to site maps depicting
each depth interval
Are PAH
concentrations
bounded in each
interval, or are
additional samples
needed?
Expand sampling grid in the appropriate
direction by sequentially moving away
from unbounded PAH locations
Identify judgmental GW sampling
locations beneath and down
gradient of elevated soil PAHs
Collect Hydropunch GW samples
i
r
Go to Data
Assessment
flowchart
Figure 2-4. Decision Logic Diagram Part 2: Preliminary Investigation Implementation Logic
EPAQA/CS-1
11
February 2006
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Complete PI
sampling field effort
1
r
Develop exploratory data plots of the
preliminary PAH data, including bubble
plots showing spatial distributions
i
'
Determine whether to further post
stratify the three initial areas, to define
sub areas of relatively homogenous
PAH concentrations
1
r
Select 8-10 locations representing each
sub area for fixed laboratory analysis
i
'
Perform broad-scan fixed laboratory
analysis on all core intervals where
PAHs were detected
i
'
Perform HH screening and statistical
evaluation of fixed-laboratory data from
each sub area:
HH Screening
Comparison to background
Calculation of EPCs
Does the sub area
have one or more
COPCs?
Do GW data
indicate any MGP
related
contaminants >
screening levels?
Do soil data
indicate transport
of contaminants to
the Bav?
Propose
no action for
sub area
Determine mean and variance for
primary risk drivers using
combined preliminary (adjusted)
and fixed lab data as appropriate
Develop DQOs and statistical
sampling plan for RI focusing on
COPCs identified from PI
Go to RI
flow chart
Figure 2-5. Real-Time Data Assessment Process Flow Chart
EPAQA/CS-l
12
February 2006
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Step 7: Develop the Plan for Obtaining Data
VSP software was used to generate sampling locations for total PAHs in soil using
systematic grid sampling with a random start. Within the areas where historical information
suggests contamination may be likely, a triangular sampling grid of approximately 75 ft. was
selected to maximize the probability of detecting any localized areas (approximately 5000 sq. ft.)
of elevated PAHs. This resulted in a planned 41 sampling locations in the Operations Area and
15 samples in the Oil Tanks area. The remainder of the site was given a 200-ft. sampling grid,
with a resulting 24 samples. This sampling density provided a 95% chance of hitting a hot spot
approximately 35,500 sq. ft. (less than an acre). With 320 potential samples at $150 per sample
(for sample collection and immunoassay analyses), the cost of this part of the plan would be
approximately $50,000 (approximately half the original budget). The sample locations are
shown in Figure 2-6 where "A" represents the Oil Storage Area, "B" represents the Operations
Area, and "C" represents the general environs of the site.
Sampling Design for Preliminary Investigation
p-33| p-34| p-35| p-36| B-3
Buccaneer
Bay
Figure 2-6. Sample Locations for Preliminary Investigation
EPAQA/CS-1
13
February 2006
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As the PI was an adaptive sampling campaign, the actual number and location of samples were
determined in the field in accordance with the following criteria:
Soil Sampling Criteria: Geoprobe© cores were obtained for all grid sampling points; sampling
was conducted in Areas A, B and C sequentially. The data assessment team determined whether
to extend the sampling grids beyond the northern, eastern, or southern boundaries of the site, and
whether to extend the finer Area A or B grids into Area C. The team used the following
considerations in making this decision:
Consistency of data with conceptual site model;
Evidence of decreasing total PAH concentrations at the edge of a grid;
Relation of total PAH site data to background concentrations; and,
Relation of total PAH site data to the risk-based screening criterion.
Soil Depth Interval Sampling Criteria: PAH immunoassay data were collected from the 0 - 0.5
ft. and 0.5-3 ft. intervals at all sampling locations. If total PAHs were not detected in the 0.5 -
3 ft. interval, and if there was no visual or olfactory evidence of hydrocarbon contamination in
the deeper core, no additional depth intervals would be sampled. If otherwise, then PAH
immunoassay data would be collected from the 3 - 6 ft. interval. These criteria were to be
repeated to determine whether to sample the last depth interval of 6 ft. - groundwater.
Soil Confirmation Sampling Criteria: PI soil sampling subareas would be initially defined using
the total PAH immunoassay data. Splits from a minimum of eight or a maximum of 10% of the
soil samples collected in a subarea, were submitted to an analytical laboratory. Previous
experience with this kind of soil contamination indicated the use of normality-based methods for
calculating power would be appropriate criteria. By collecting a minimum of eight samples per
subarea, and having eight or more from a reference area, comparisons to background
distributions could be made, and differences of approximately 50-75% detected with reasonable
power (greater than .70), and larger shifts such as 100% with greater power.
Groundwater Sampling Criteria: Shallow aquifer groundwater samples will be collected by
Hydropunch upgradient of the site boundary, and downgradient from each soil subarea in a
location of the highest total PAH measurement in the deepest soil interval. If the selected
location does not yield a sufficient water sample, another location in the subarea will be selected.
Three attempts per subarea will be made to obtain a groundwater sample.
The final DQOs for the PI are summarized in Appendix C.
2.2 Implementation of the Preliminary Investigation
Preliminary Investigation soil and groundwater sampling was conducted over a period of
10 days. Sampling was begun in the Operations area, moved to the Oil Storage area, and finally
was completed in the remaining area of the site. Approximately 10 cores per day were collected.
Batches of five cores were sent to a trailer on site for sample preparation, logging, and analysis.
Extractions for all core intervals in a batch were performed simultaneously, and immunoassays
EPAQA/CS-1 14 February 2006
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initiated as soon as possible. In this manner, the results from 10 locations and associated QA
samples were generated in a given day.
The field team kept a daily log of the field screening results and resulting statistical
adaptive decisions related to the study design. A brief summary follows with a more detailed
discussion in Appendix C.
For the Oil Storage Area, a total of 15 cores were collected resulting in 52 immunoassays
for total PAHs; seven of which were from the 3-6 ft. interval, but none of which was in the > 6 ft.
interval. No highly contaminated soil in this area was found; however, total PAH concentrations
on the southern side of the rail spur in the top three depth intervals were higher than north of the
rail spur. In general, the surface interval was cleaner than subsurface samples.
For the larger Operations Area, cores were collected at the planned 41 sampling
locations. Many of these samples were taken from beneath the gravel parking lot, south of the
buildings. In these cases, the gravel layer was scraped away, and cores were taken starting at the
soil interface. The original sampling grid in this area was extended by two rows on the southern
boundary of the Operations Area due to the detection of high concentrations of total PAHs in the
southern region of the area and a total of 201 immunoassays performed for total PAHs. Elevated
PAHs continued to be found in the first new row to the south, but dropped to approximately
ambient levels in the last new row. The highest concentrations were closely related to visual
observations of a powdery black substance, probably lampblack, in the core.
For the remainder of the site, Site Environs, cores from the initial 24 sampling locations
were collected and field-screened for total PAHs. A visual analysis of some core material from
sample C-8 revealed debris mixed in with native soil, ash, slag, and lampblack. In the deeper
intervals, the core contained thick, black, tarry wastes which were analyzed by immunoassay and
found to contain levels of PAHs higher than the calibration scale of the kit.
After discussion it appeared that this sampling location was in alignment with a ravine-
like feature extending from the parking area to a cove in Buccaneer Bay. Based on
concentration, the team decided to take samples up- and down-gradient from C-8, to further
evaluate what appeared to be materials dumped in a former ravine. In all, five additional cores
were obtained and analyzed: two in the direction of the cove, and three upgradient. Tarry
material was found in the samples surrounding C-8, especially below three ft. of cover. An
additional core near the cove revealed consistent soil-fill with no evidence of tarry material, and
was not analyzed.
2.3 Assessment of the Preliminary Investigation
The logic to data assessment for the PI is summarized by the following three subsections:
2.3.1 Real-Time Data Assessment and Post Stratification
On a daily basis, sample results were added to a spreadsheet and imported (as txt files)
into the base map in VSP to post the results for each sample depth interval on a map. As
EPAQA/CS-l 15 February 2006
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previously described in Section 2.2, the initial sampling plan was supplemented by extending the
sampling grid two additional rows to the south of the Operations Area, and along the ravine in
the Site Environs area. A split of each homogenized core interval was created, labeled, and
stored in a freezer, following standard tracking and chain of custody procedures.
After completion of all PAH immunoassays, the concentrations at each depth interval
were evaluated for post-stratifying the site. To assist in post stratification, weighted average 0-3
ft. concentrations were created and posting plots created. A decision was made to perform an
expedited removal action to excavate the heavy tarry material (that was very high in PAHs) and
related ash and other debris in the ravine. This decision was made due to the high
concentrations, well-defined boundaries, and potential for migration via the historical ravine to
offshore sediments under flood events. The boundaries of the Oil Storage area and Operations
Area boundaries were refined, with a portion of each of those areas being added to the general
Site Environs, leaving those stations where concentrations were more uniformly elevated. The
post stratified sub- areas identified through this process became the spatial boundaries for all
subsequent data assessment, including risk screening, COPC identification, background
comparisons, and calculation of the mean and variances to support the design of follow on
investigations. Figure 2-7 shows the 0-3 ft. weighted average total PAH, and boundaries of the
post stratified areas.
To ensure that each area was represented by fixed laboratory results, a systematic
subsample of each of the post-stratified sub areas was taken, and depth intervals randomly
selected from each chosen location. The final selection included seven (six systematic plus one
judgment) samples from the Oil Storage Area, 12 (nine systematic plus three judgment) from the
Operations Area, and 11 (all systematic) from the Site Environs (Figure 2-8). The judgmental
samples were added to assist in forming fixed lab to field method regressions. Since a decision
was made to perform an expedited action in the ravine, no samples from that area were selected
for fixed lab analysis.
2.3.2 Sample Size Selection for Background Comparisons
The Background samples were taken from a similar area to the east of the railway line of
the MGP site with approximately the same sample matrix as those samples taken from the MGP
site. There were 15 existing background samples with a mean total PAH concentration of 1110.9
ppb and a standard deviation of 942.4 ppb (see Appendix D).
Post-stratification is a re-examination of the boundaries of the original strata (Areas) to ascertain if the boundaries
were appropriate and, if not, redefine them. The technique improves the precision of the estimate made.
EPAQA/CS-1 16 February 2006
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Post Stratified Site Map
Buccaneer
Bay
t
N
Figure 2-7. Post Strata Showing 0-3 ft. Weighted Average total PAH
Concentrations
Fixed Laboratory Sample Depth Intervals \
Buccaneer
Bay
t
N
Figure 2.8 Locations and Depths Selected for Fixed Lab Analyses
EPAQA/CS-1
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February 2006
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2.3.3 Decision to Use Fixed Laboratory Data with BaP Equivalents
The Immunoassay results, Fixed Lab total PAH data, and BaP Equivalents data were
compared to assess their reliability. Although there was a moderately good correlation over the
entire range of concentrations it was significantly less for lower concentrations (see discussion in
Appendix E). This lack of a strong correlation led to the decision to use Fixed Lab data only and
not the Immunoassay data.
The results from fixed laboratory data were used to estimate potential carcinogenic risk
based on the toxicity of individual chemicals. Concentrations of individual PAHs were
converted into BaP equivalents in order to estimate the overall cancer risk from the combination
of potentially carcinogenic PAHs. The BaP equivalent is based on the EPA 1993 toxicity
equivalency factors and the concentrations of the seven individual carcinogenic PAHs . The BaP
equivalent calculation is based on a BaP toxicity equivalence factor multiplied by the
concentration of the PAH for each of the seven carcinogenic PAHs:
BaP equivalents = (0.1) benzo(a)anthracene + (l.O)BaP + (0.1)benzo(b)flouranthene +
(0.01) benzo(k)flouranthene + (O.OOl)chrysene + (0.1) ideno(l,2,3cd)pyrene.
The standard EPA industrial exposure scenario estimates the exposure of an outdoor
worker over 25 years and converts the BaP equivalents in soil concentration into a risk level.
From discussions with between risk assessors from the regulatory agencies and MGP personnel,
a risk of 1 x 10"5 was determined to be acceptable which converts to 2300 ppb BaP equivalents in
soil. Therefore, if the BaP equivalent for a sample is below the BaP equivalents corresponding to
10"5 risk (2300 ppb), there is no need to screen that sample for carcinogenic risk from individual
PAHs.
2.4 Preliminary Investigation Conclusions
Concentrations of metals in soils showed a slight elevation over Background, but all
(including Arsenic) were well below the applicable risk-based screening levels. Arsenic was
found above the industrial screening level at each of the areas but not thought to be a site
contaminant of concern. Based on the potential for risk relative to the MGP contaminants,
Arsenic should be included for the RI and other metals excluded from further investigation.
For the Post-Stratified Operations Area, the BaP equivalents for a number of samples
exceeded the BaP risk benchmark. These screening results indicate that, based on carcinogenic
risk from PAHs under an industrial scenario, the Post-Stratified Operations Area should be the
focus of any further soil investigation, while the other two areas could be proposed for no further
investigation based on the results of the preliminary investigation. The maximum concentration
of BaP equivalents found in one sample generates an estimate of the magnitude of the potential
carcinogenic risk from PAH to be 1.1 x 10"4; approximately 10 times the acceptable risk level
agreed to. Further investigation of carcinogenic PAHs in the RI should provide a more accurate
estimate of the potential risk to human health at this site.
EPAQA/CS-l 18 February 2006
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Tables 2-1, 2-2, and 2-3 show the statistical summaries for the three areas.
Table 2-1. Mean Concentrations for the Three Areas (
Parameter
BaP Equivalents
Fixed Lab.total PAH
Immuno. total PAH
Benzo(a)anthracine
Benzo(a)pyrene
Benzo(b)fluoranthene
Benzo(g,h,i)perylene
Benzo(k)fluorathene
Chrysene
Fluoranthene
Indeno( 1 ,2,3cd)pyrene
Phenanthene
Pyrene
Acenaphthylene
Anthracene
Dibenzo(a,h)anthracene
Naphthalene
Acenaphthene
Fluorine
Oil Storage Area (A)
330.2
2538.3
3749.0
99.5
189.8
187.7
277.2
80.7
140.8
537.0
291.8
173.5
407.7
0
71.2*
81.5*
0
0
0
Operations Area (B)
7465.3
57445.2
184752.6
2472.6
4260.3
2762.4
3823.1
1408.0
2863.1
14885.1
3901.0
5308.9
11380.9
425.0*
1372.4*
2274.4*
13.3*
2.4*
292.1*
F>pb)
Site Environs (C)
420.0
2747.8
3132.3
133.8
218.2
167.1
270.8
71.7
151.0
578.9
216.1
176.7
550.5
9.1*
54.5*
149.3*
0
0
0
Background BaP Equivalents Mean = 130.33
* assumes all nondetects = 0
Table 2-2. Median and Maxima for the Three Areas (ppb)
Oil Storage Area (A) Operations Area (B) Site Environs (C)
Parameter
BaP Equivalents
Fixed Lab.total PAH
Immuno. total PAH
Benzo(a)anthracine
Benzo(a)pyrene
Benzo(b)fluoranthene
Benzo(g,h,i)perylene
Benzo(k)fluorathene
Chrysene
Fluoranthene
Indeno( 1 ,2,3cd)pyrene
Phenanthene
Pyrene
Acenaphthylene
Anthracene
Dibenzo(a,h)anthracene
Naphthalene
Acenaphthene
Fluorine
Median
281.2
2550.0
4120.5
97.0
140.0
196.0
250.0
89.0
145.0
530.0
277.5
125.0
395.0
0
11.5*
14.5*
0
0
0
Maximum
754.6
5430.0
6697.0
200.0
450.0
340.0
590.0
140.0
260.0
1200.0
620.0
560.0
870.0
0
360.0
320.0
0
0
0
Median
4441.0
20284.0
60677.0
1307.0
1910.0
1206.0
2111.0
683.0
1106.0
3216.0
1608.0
1100.0
3417.0
0*
180.0*
240.0*
0*
0*
0*
Maximum
30167.0
197200.0
856420.0
9700.0
15000.0
9300.0
11000.0
5500.0
12000.0
55000.0
12000.0
21000.0
45000.0
1985.0
4900.0
12000.0
120.0
22.0
1389.0
Median
349.4
2493.0
3582.0
110.0
190.0
151.0
280.0
60.0
121.0
500.0
230.0
120.0
413.0
0*
25.0*
102.0*
0
0
0
Maximum
1065.2
6906.0
4070.0
335.0
559.0
335.0
407.0
213.0
427.0
1727.0
406.0
802.0
1117.0
66.0
259.0
400.0
0
0
0
* assumes all nondetects = 0
EPAQA/CS-1
19
February 2006
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Table 2-3. Number of Detects and Standard Deviation for the Three Areas (ppb)
Parameter
BaP Equivalents
Fixed Lab.total PAH
Immuno. total PAH
Benzo(a)anthracine
Benzo(a)pyrene
Benzo(b)fluoranthene
Benzo(g,h,i)perylene
Benzo(k)fluorathene
Chrysene
Fluoranthene
Indeno(l,2,3cd)pyrene
Phenanthene
Pyrene
Acenaphthylene
Anthracene
Dibenzo(a,h)anthracene
Naphthalene
Acenaphthene
Fluorine
Oil Storage Area (A)
# Detects
6
6
6
6
6
6
6
6
6
6
6
6
6
0
4
3
0
0
0
Std. Dev.
285.5
2073.4
2398.4
72.0
167.4
144.1
256.1
53.2
101.1
449.7
269.8
199.5
309.6
0
142.5*
128.8*
0
0
0
Operations Area (B)
# Detects
9
9
9
9
9
9
9
9
9
9
9
9
9
3
8
6
1
1
3
Std. Dev.
9495.9
67230.2
294886.6
3098.3
4798.6
3013.4
3760.4
1708.9
3854.5
19450.5
4107.2
7732.7
14539.9
808.1*
1958.5*
4089.5*
0
0
570.4*
Site Environs (C)
# Detects
11
11
11
11
11
11
11
11
11
11
11
11
11
2
10
8
0
0
0
Std. Dev.
280.1
1763.0
1052.9
90.8
134.3
94.6
123.8
52.5
107.6
509.4
97.5
226.3
360.1
21.6*
84.8*
154.9*
0
0
0
Background BaP Equivalents = 15, with Std. Dev. 155.6
The conclusions from inspection of Tables 2-1, 2-2, 2-3:
* assumes all nondetects = 0
Concentrations of BaP Equivalents and total PAH were highest in the Operations Area as
shown by comparisons of means and maxima (Tables 2-1 and 2-2).
There was almost no difference between Oil Storage Area and Site Environs averages,
but a large difference between both and the Operations Area (Table
2-1).
There was almost no difference between Oil Storage Area and Site Environs in terms of
variability, but the Operations Area very much more variable (Table
2-3).
Mean concentrations of BaP Equivalents and total PAH were significantly above
Background for the Operations Area and Site Environs, but less so for the Oil Storage
Area (see Appendix F for further discussion).
Mean concentration of BaP Equivalents exceeded the industrial worker risk-based
screening level of 2300ppb in only the Operations Area (Table 2-1).
Maximum concentration of BaP Equivalents did not exceed the industrial worker risk-
based screening level of 2300ppb in the Oil Storage Area and Site Environs (Table 2-2).
EPAQA/CS-1
20
February 2006
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Groundwater was minimally affected by MGP operations as contamination was minimal
in groundwater.
The overall conclusion to be drawn for the Remedial Investigation planning phase was
that only the Operations Area as defined by the post stratification needed to be the focus of
attention, and that the COPCs should be the BaP equivalents and Arsenic.
With the conclusion of the Preliminary Investigation, the data are now available for the
Remedial Investigation phase.
3. REMEDIAL INVESTIGATION
With the newly available preliminary data, the DQO Process was used again to develop
quantitative performance and acceptance criteria for the next phase, Remedial Investigation (RI).
The primary purpose of the RI was to produce data suitable for conducting a baseline human
health risk assessment.
3.1 Planning the Remedial Investigation
After completion of the preliminary investigation phase, the Planning Team held a
meeting to discuss issues related to development of risk estimates for exposure to COPCs in soil
at the Operations Area and the principal issues and agreements summarized in Table 3-1.
Table 3-1. Risk Assessment Meeting Notes
The risk assessor summarized the relevant risk parameters as:
1) 0.0 - 0.5 ft. interval (surface soil for an industrial outdoor worker
2) 0.5 - 1.5 ft. interval (possible exposures during construction and trenching)
3) 1.5-3.0 ft. (not based on a particular exposure scenario)
The post-stratification was based on a screening comparison to the maximum
concentration at each subarea followed by a screening comparison of each fixed lab
sample within each subarea.
The BaP screening level of 2300 ppb was revised after discussion to a 15 year
exposure with a soil ingestion rate of 25 mg/day (given the eight hour workday);
this led to a site specific Remedial Action Concentration of 12,000 ppb.
A not-to-exceed BaP concentration of 15,000 ppb will be used in the RI to evaluate
whether the Operations Area might contain small areas of unacceptably elevated
concentrations of BaP equivalents (hot spots).
After agreeing on the basic risk assessment parameters, the planning team discussed
DQOs for the additional data required to conduct the risk assessment. The hardest work had
EPAQA/CS-l 21 February 2006
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been completed by this point; the rest of the procedure would be relatively easy. Table 3-2
presents the DQOs resulted from the planning team discussions.
Table 3-2. Data Quality Objectives Summary Table for the Remedial Investigation
Step 1:
State the
Problem
The preliminary investigation indicated PAHs exceeding the soil screening threshold
were primarily located in the Operations Area (the focus of this DQO), and the ravine
area (to be investigated later).
Step 2:
Identify the
Decision
Does PAH contamination in Operations Area soils pose an unacceptable risk to users of
the site and need to be evaluated in a further study?
Step 3:
Identify
Inputs to
the
Decision
Site-specific risk-based Remedial Action Criteria for BaP-equivalents set at
12,000 ppb
Concentration of individual PAHs and BaP equivalents from soil samples to be
collected in Operations Area.
Step 4:
Define the
Boundaries
Of the
Study
The Operations Area has been redefined in the X, Y, and Z dimensions by means of
post-stratification of the screening and fixed laboratory data. A single decision will be
made for this area, by evaluating the PAH concentrations to several depths (0.0-0.5 ft.,
0.0-1.5 ft. and 0.0-3.0 ft.).
Step 5:
Develop a
Decision
Rule
If the 95% Upper Confidence Limit (UCL) values for BaP-equivalents in the top 0.5 ft,
or any weighted average down to 3 ft. exceed the applicable site-specific criteria, then
conclude that the Operations Area presents an unacceptable risk, and proceed with a
determination of the extent of remediation necessary to lower risk to an acceptable
level, and the evaluation of remedial alternatives in a future study.
If any single value is found to exceed 15,000 ppb, then determine the extent of the hot
spot and evaluate remedial alternatives for hot spot removal.
Step 6:
Specify
Tolerable
Limits on
Decision
Errors
Null hypothesis (baseline assumption): Average site concentrations are > 3000 ppb.
A false rejection would be an indication that the average is less than 3000 ppb, when in
truth it is not. A false acceptance would be an indication that the average is greater than
3000 ppb, when in truth it is not.
The following error tolerance specifications were selected for this purpose:
false rejection rate: 10%
false acceptance rate: 5% (in keeping with the use of 95% UCL to represent
RME exposures in risk assessments)
width of gray region: 6000 ppb
estimated standard deviation based on fixed lab BaP equivalents: 8335
Step 7:
Develop the
Plan for
Obtaining
Data
21 sampling points were selected. Given the skewed distribution, the sample sizes were
based on use of the nonparametric Wilcoxon Rank Sum test. A systematic grid was
placed over the Operations Area, by selecting a random start that results in a grid
staggered from the original grid. Figure 3-1 shows the location of the new sampling
locations.
EPAQA/CS-1
22
February 2006
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Figure 3-1. Combined Preliminary and RI Sampling Location Map
3.2 Implementation of the Remedial Investigation
Collection of the 21 core samples occurred over a three-day period. Since a large number
of the samples were located under the large gravel parking lot, the following procedures were
used. Hand shovels were used to move the gravels aside, down to the surface of the soil. A
geoprobe sampler was then used to drive a two inch core down to the three ft. depth, and the core
samples taken to an on-site trailer for preparation for shipment to the fixed laboratory. Chain-of-
custody procedures as specified in the QA Project Plan were followed, and none of the samples
were lost during sample preparation or shipment, and none of the holding time requirements
were missed.
Fixed laboratory results were generated in one month, and electronic deliverables were
sent to an independent firm for validation, which took an additional week. After completing the
verification and validation process, data analysis and data quality assessment activities ensued.
EPAQA/CS-l
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February 2006
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3.3 Assessment of the Remedial Investigation
RI data were received from the fixed laboratory and an initial inspection of the data
showed that none of the individual non-carcinogenic PAH values exceeded the screening levels
used in the preliminary investigation. BaP equivalents were then calculated for the carcinogenic
PAH values for each depth, at each sampling location, following the same procedure that was
used for the fixed laboratory data in the Preliminary Investigation.
3.3.1 The Remedial Investigation Data
After verification and validation, the BaP equivalent values obtained from the Post
Stratified Area are presented in Table 3-3.
Table 3-3. BaP Equivalent Concentrations (ppb)
for the Post Stratified Operations Area
(values exceeding 15,000 ppb are indicated in boldface)
RIData
Label
RI-01
RI-02
RI-03
RI-04
RI-05
RI-06
RI-07
RI-08
RI-09
RI-10
RI-11
RI-12
RI-13
RI-14
RI-15
RI-16
RI-17
RI-18
RI-19
RI-20
RI-21
Easting
530.5
594.4
466.7
530.5
594.4
658.3
466.7
530.5
594.4
466.7
530.5
594.4
658.3
530.5
594.4
658.3
722.1
530.5
594.4
658.3
722.1
Northing
-776.2
-776.2
-840.1
-840.1
-840.1
-840.1
-904.0
-904.0
-904.0
-967.8
-967.8
-967.8
-967.8
-1031.7
-1031.7
-1031.7
-1031.7
-1095.6
-1095.6
-1095.6
-1095.6
Depth
0.0 - 0.5 ft
1959
4708
4057
4392
6674
3547
6470
8420
7963
7957
21929
23198
7188
18423
26755
16950
7482
7848
15179
13298
6665
0.5 - 1.5 ft
2785
3693
7377
8589
6434
5379
7818
14008
12428
9088
18707
16251
7597
19566
32720
16284
8492
8273
12976
14205
8332
1.5 - 3.0 ft
2740
2908
3063
3181
2472
2256
3039
2212
2752
5631
15103
11641
6530
14107
16419
14726
6864
5716
12232
10547
5967
Weighted Average
0.0 - 1.5
2510
4031
6270
7190
6514
4768
7369
12145
10940
8711
19781
18567
7461
19185
30732
16506
8155
8131
13710
13903
7776
0.0 - 3.0
2625
3470
4667
5186
4493
3512
5204
7179
6846
7171
17442
15104
6995
16646
23575
15616
7510
6924
12971
12225
6872
"Label" is the sample identification number and uses additional letters to denote the depth from
which the sample was taken (0.0 - 0.5 being "A"; 0.5 - 1.5 being "B," and 1.5 - 3.0 being "C").
Samples RI-01 to RI-09 are from the north end, samples RI-10 to RI-21 from the south end.
"Easting" and "Northing" give the co-ordinates of the sample location on a standard map; these
co-ordinates are then translated into actual Post Stratified Operations Area locations. "Depth"
gives depth from which the sample was taken such that a three-dimensional picture of the Area
may be constructed. "Weighted Average" combines the actual values proportionately, giving
more weight to the deeper values than those near the surface. The weighted average for the 0.0 -
EPAQA/CS-l
24
February 2006
-------
1.5 depth is given by 1/3("A" value) + 2/3 ("B" value); that for the 0.0 - 3.0 depth by 1/6 ("A"
value) + 2/6 ("B" value) + 3/6("C" value).
Inspection of Table 3-3 values shows some interesting results. All the values from the
northern end of the Post Stratified Operations Area are below 15,000 ppb, but approximately a
third of the southern end values exceed 15,000 ppb. A somewhat similar pattern can be seen in
the weighted average values. To visualize these patterns better a box-and-whisker plot (Figure
3-2) was developed.
From Figure 3-2 it can be seen that the overall median (horizontal line within the central
box) for each of the three depths is well below the Action Level of 12,000 ppb; however, a
substantial proportion of each depth's data values are above the Action Level (the upper
whiskers), thus confirming the conclusion derived from inspection of the raw data in Table 3-3.
Notice how the three plots are very similar in box sizes (showing the majority of the values) and
the whiskers or tails which show the extreme values. This indicates the distribution of data
values is consistent across the three depths with a slight diminution as the depth increases. The
difference in length between upper and lower whiskers shows the data to be skewed towards the
higher values but not too different from symmetry (recall, only 21 values were collected).
To further examine the difference between northern and southern locations, two
additional box plots were made (Figure 3-3), dividing the data into northern and southern
locations within the post stratified operations area. This plot clearly indicates that the values in
the northern part of this area are below the action level while those in the southern half contain
locations far in excess of the 12,000 ppb Action Level.
3.3.2 Calculation of Upper Confidence Limits
A UCL on the mean (arithmetic average) concentration is used to represent the
reasonable maximum concentration in evaluating risk due to site contamination. The manner by
which a confidence interval is calculated depends on several factors, the most important being
the assumption of normality in data distribution. This assumption is probably not warranted
given the appearance of the data in Table 3.2 but providing the normal -based UCL is carefully
interpreted, can yield information useful in characterizing the area from which the samples were
obtained. The UCL on the mean is given by:
where X represents the mean of the area under investigation, s the standard deviation,
n the number of samples, and tn_l l_a is taken from standard t-tables. Tables 3-4, 3-5, and 3-6
show the 95% confidence intervals for the Northern Locations, the Southern Locations, and for
All Locations, for all three depths.
EPAQA/CS-l 25 February 2006
-------
BaP Equivalent (weighted average) for All Sampling Locations
o
o
o
o
CO
o
o
o
IT)
CM
o
o
+- o
c o
J CM
flt
>
LU
Q.
CD
O-
O
O
O
O
O
O
O
action level
0.0-0.5 ft
0.0-1.5 ft
0.0-3.0 ft
Figure 3-2. Box and Whisker Plots BaP Equivalent Concentration Weighted Averages
EPAQA/CS-1
26
February 2006
-------
BaP Equivalent (weighted average) for Northern Sampling Locations
BaP Equivalent (weighted average) for Southern Sampling Locations
o
o
o -
o
o
o -
o
*- o
c o
_0) o
03 CO
cr
LLJ
Q. O
03 O
" S
o
o
o
o
o
o
04
o
o
o -
o
CO
o
o
o
If)
C-4
I §
03 O
.> o
3 eg
cr
LU
Q.
ro
QQ O
o
o
10
o
o
o -
o
action level
0.0-0.5 ft
0.0-1.5 ft
0.0-3.0 ft
0.0-0.5 ft
0.0-1.5 ft
0.0-3.0 ft
Figure 3-3. Box-and-Whisker Plots of BaP Equivalent Concentrations in the Northern (left) and Southern (right) Sample
Locations
EPAQA/CS-1
27
February 2006
-------
Table 3-4. Upper 95% Confidence Intervals Northern Locations
Depth
0.0 -0.5 ft.
0.5 -1.5 ft.
1.5 -3.0 ft.
n
9
9
9
Median
4708
7377
2752
Mean
5354
7612
2736
Std. Dev.
2151
2541
1784
UCL
6688
9187
3842
Table 3-5. Upper 95% Confidence Intervals Southern Locations
Depth
0.0 -0.5 ft.
0.5 -1.5 ft.
1.5 -3.0 ft.
n
12
12
12
Median
14239
13591
10844
Mean
14406
15861
10457
Std. Dev.
7106
7632
4129
UCL
18090
19818
12597
Table 3-6. Upper 95% Confidence Intervals All Locations
Depth
0.0 -0.5 ft.
0.5 -1.5 ft.
1.5 -3.0 ft.
n
21
21
21
Median
7848
8492
5716
Mean
10527
11476
7148
Std. Dev.
7120
6780
4975
UCL
14946
14028
9020
Table 3-7. Upper 95% Confidence Intervals Northern Locations Weighted Data
Depth
0.0 -0.5 ft.
0.5 -1.5 ft.
1.5 -3.0 ft.
n
9
9
9
Median
4708
6514
4667
Mean
5354
6860
4798
Std. Dev.
2151
3097
1518
UCL
6688
8779
5739
Table 3-8. Upper 95% Confidence Intervals Southern Locations Weighted Data
Depth
0.0 -0.5 ft.
0.5 -1.5 ft.
1.5 -3.0 ft.
n
12
12
12
Median
14239
13807
12598
Mean
14406
14385
12421
Std. Dev.
7106
7031
5455
UCL
18090
18030
15249
Table 3-9. Upper 95% Confidence Intervals All Locations Weighted Data*
Depth
0.0 -0.5 ft.
0.5 -1.5 ft.
1.5 -3.0 ft.
n
21
21
21
Median
7848
8155
6995
Mean
10527
11160
9154
Std. Dev.
7120
6752
5677
UCL
14946
15155
12231
* Assumes a Lognormal distribution
Case Study
28
February 2006
-------
Table 3-4 shows the UCLs to be well under the Action Level for all three depth levels,
but Table 3-5 show the UCLs to be well above the Action Level. For Table 3-6, Upper
Confidence Intervals all Locations, note how the UCL for both of the shallow depth ranges
exceed the Action Level (12,000 ppb), but that the deeper depth level appears to be well under
the Action Level. Taking Tables 3-4, 3-5, 3-6 together leads to the general conclusion that even
if the assumption of normality in data distribution was questionable, there seems to be a
difference in the interpretation of level of contamination (and hence risk between the Northern
and Southern Locations.
Tables 3-7 and 3-8 show the same patterns as do the raw data tables and show a
consistency in interpretation. Table 3-9, however has to be treated a little differently. The
reason lies in the assumption of normality made for the construction of the UCLs. When the
Northern and Southern Locations are considered individually, the assumption of normality
cannot be meaningfully challenged as the sample sizes are too small to show significant
deviations from normality. When the data sets are merged to become All Locations, there
become a sufficient number of samples to show any deviation. For the actual values (Table 3-3
"Depth," and Table 3-6) the assumption of normality is possible although there are many
significant deviations from normality. When the weighted values are considered (Table 3-3
"weighted average," and Table 3-9) the assumption of normality is definitely not true and an
alternative must be sought.
One alternative is to make the assumption that the distribution of the data is lognormal as
opposed to normality. Using this assumption and Land's Method (Gilbert, 1987) the UCL can
be calculated and Table 3-9, Upper Confidence Intervals All Locations Weighted Data, shows
the UCL to be well past the Action Level of 12,000 ppb.
4. CONCLUSIONS
The RI data indicate that concentrations of PAHs exceed the site-specific remedial action
concentrations in the operations area, and therefore potentially pose an unacceptable risk due to
exposure of industrial workers to residual contamination. The next phase after a Remedial
Investigation is a Feasibility Study (FS) designed to evaluate remedial alternatives in the top
three ft. of soil in the Operations Area. Based on the RI, it is evident that the FS should focus on
the southern part of Operations Area, where elevated PAH concentrations are highest.
5. SUMMARY
Two important parts of the Consent Order (the Preliminary Investigation followed by a
Remedial Investigation) were carried out in an efficient and timely manner because of the DQO
Process. It enabled a flexible, graded approach to the problem, resulting in a minimal necessity
to rework and repeat previous conclusions. The structure of the DQO Process culminated in two
fully documented data collection studies that allowed for the development of remedial action of a
potentially hazardous site.
EPAQA/CS-l 29
-------
6. REFERENCES
Gilbert, R.O., 1987. Statistical Methods for Environmental Pollution Monitoring, Wiley, N.Y.
US EPA 2000. Guidance for the Data Quality Objectives Process (EPA QA/G-4).
EPAQA/CS-l 30
-------
APPENDIX A
THE PAH IMMUNOASSAY METHOD
Environmental immunoassay techniques use the ratio of a light-absorbing chemical-
enzyme conjugate and the free chemical from the environmental sample to estimate the
concentration of a chemical in the environmental sample. The light absorption of various
samples is compared to the light absorption from a set of standards; the absorption decreases as
the concentration form the environmental sample increases. This technique is available for a
wide array of chemicals, as well as for classes of chemicals such as PCBs and PAHs. General
PAH kits are sensitive to 2,3 and 4 ring compounds. These kits use phenanthrene as the target
compound and are preferred for sites with fuel oil #2, diesel, and kerosene. Carcinogenic PAH
kits are for 3,4,5, and six ring PAHs and are preferred for JP-4, and mixtures of fuel oil coal tar,
and creosote.
PAH kits that are designed to detect a class of compounds cross-react more with
compounds that are not the PAHs of interest but have similar structures. These kits give results
that tend to be "biased high" compared to fixed lab results. In general, the detection limit for
total PAHs in a soil sample is 600-700 ppb. Detection limit for target compound (phenanthrene
or pyrene) in a soil sample is 300-400 ppb.
All immunoassay techniques run samples in batches. Reported times to run
immunoassay: (samples per batch/batch process time in minutes) 5/30, 10/70 and 20/120, not
including preptime. Anecdotal evidence shows that 35-200 samples per person per day can be
run depending on extent of preparation (soil samples would probably be on the low end of this
range).
At this site, a preliminary set of samples was taken to determine the expected range of
PAHs at site. This preliminary test was needed to determine the required dilutions and the site -
specific correlation between the immunoassay and fixed laboratory analysis. With multiple
standard calibration curves for each sub area of site (because of potential differences in
constituent PAHs or soil chemistry), the correlation coefficient for calibration should be 0.990-
0.995. Continuing calibration samples should be run every 4-6 samples and blank samples
should be run with each batch analyzed by immunoassay.
QC requirements are specific to the PAH kit, and obtained from the manufacturer. Field
duplicates should be run at a rate of one per 10 samples, or one per batch analyzed (some kits
run 20 samples per batch), whichever is the higher rate. Field duplicates should fall within 50%
of original for soils. Performance Evaluation samples (i.e., split samples) are needed throughout
the sampling to determine the comparability acceptance criteria. The comparability acceptance
criteria for soils is 50% relative percent difference for soil samples. Recommended frequency
for split samples is conventionally 10%, but may need to be adjusted for the project based on
meeting comparability acceptance criteria.
EPAQA/CS-l A-l February 2006
-------
EPAQA/CS-1 A-2 Febraary 2006
-------
APPENDIX B
VISUAL SAMPLE PLAN
Overview
Visual Sample Plan (VSP) is a software tool for selecting the right number and location
of environmental samples such that the results of statistical analyses of the resulting data have
the desired confidence for decision making. Sponsors of this public domain software include the
EPA, Department of Energy, Department of Defense, and Department of Homeland Security; it
was developed by Battelle Pacific Northwest National Laboratory. It provides simple, defensible
tools for defining an optimal sampling scheme for any two-dimensional contamination problem
including surface soil, building surfaces, water bodies, or similar applications.
Reports generated by VSP can be exported directly into a QA Project Plan or Sampling
and Analysis Plan. VSP uses the seven Data Quality Objectives steps and is especially useful in
resolving technical and statistical issues arising from steps 6 (Specify tolerable limits on decision
errors), and 7 (Develop a plan for obtaining data). In particular, VSP can be used to generate
different scenarios involving different decision error rates and statistical assumptions. VSP is
easy to use and contains many graphics, including help and tutorial guides.
VSP utilizes state-of-the-art statistical and mathematical algorithms applicable to
environmental statistics and presents the results in plain English. It provides the projected
number of samples needed to meet DQO specifications, total sampling costs, and actual locations
of the samples on an actual map of the site. VSP is designed for the non-statistician and is
upgraded at various intervals to include more functions and methodologies. It is available at no
cost from the website http://dqo.pnl.gov/vsp.
VSP and Comparing a Mean Against a Fixed Threshold
This is the basic option of VSP and follows the development of the DQO Process as
described in Guidance for the Data Quality Objectives Process (EPA QA/G-4) (US EPA 2000).
VSP takes the information developed in Step 6 (Specify Tolerable Limits on Decision Errors)
and calculates the number of samples needed assuming a normal distribution. The formula used
to calculate the number of samples is:
A2 2
where
n is the number of samples,
s is the estimated standard deviation of the measured values including analytical error,
A is the width of the gray region,
a is the acceptable probability of incorrectly concluding the site mean is less than the
threshold,
P is the acceptable probability of incorrectly concluding the site mean exceeds the
threshold,
EPAQA/CS-l B-l February 2006
-------
Zi_
i_p
is the value of the standard normal distribution such that the proportion of the distribution
less than Z\.a is 1-a,
is the value of the standard normal distribution such that the proportion of the distribution
less than Zi_^ is 1-p.
VSP then increases the number of samples to be taken by a further 16% to account for the
probable skewness of the actual distribution and to allow for nonparametric tests such as the
Wilcoxon Signed Rank Test. The resulting Performance Goal Diagram (figure B-l) shows the
performance curve based on the input information. The vertical line is shown at the threshold
(action limit) on the horizontal axis. The gray region is the shaded area; the upper horizontal
dashed line is positioned at 1- a on the vertical axis; the lower horizontal dashed line is
positioned at P on the vertical axis. A vertical line is positioned at one standard deviation below
the threshold.
Wilcoxon Signed Rank (One-Sample) Test
n=21, alpha=10%, beta=5%, std.dev.=8335 _
0.9
_ 0.8
0.7
E 0.6
k.
o
c
SS
E
0.2
a
3 0.1
o
1 I ' I ' I ' I ' I ' I ' I ' I ' I ' I ' I ' I ' I ' I TT' ' I ' | ' I ' 'T1T17"T~T~T~T~I7"T~T~IT"I~rITrTIT1 ' I ' | ' I ' I ' I ' I ' | ' I ' I ' I ' I ' | ' I ' I ' I
-12000 -10000 -8000 -6000 -4000 -2000 0 2000 4000 6000 8000 10000
True Mean or Median
Figure B-l: Performance Goal Diagram using the Wilcoxon Signed Rank Test
VSP also generates different scenarios for the specified variables and so can enable the project
team to conduct a sensitivity analysis of the problem and compare costs of different scenarios.
EPAQA/CS-l
B-2
February 2006
-------
VSP and Hot Spot Detection
For the location of a hot spot, four variables need to be considered: size of the potential
hot spot, the desired chance of hitting a hot spot (usually considered in terms of the risk of
missing a hot spot), the cost of sampling, and finally, the size of the grid spacing proposed. VSP
can be used to create statistically sound sampling designs that reflect combinations of each of
these variables by specifying three of the variables:
Using a predetermined grid spacing, VSP can calculate the chance of finding a hot spot of
a specified size.
For a specified probability with pre-determined grid spacing, VSP can calculate the
smallest size hot spot that can be detected.
For a specified probability and specified hot spot size, VSP can calculate the minimum
number samples to be taken in order to hit the hot spot.
For a predetermined cost (which dictates the grid size), VSP calculate the probability of
finding a hot spot of a given size.
VSP can be used to investigate the effects of changing the grid type (square, rectangular,
or triangular), grid spacing (distance between sampling nodes), and shape of hot spot (circular or
elliptical of some type).
VSP does, of course demand some reasonable assumptions: the hot spot is elliptical or
circular and not a strange shape with contours, the definition of what constitutes a hot spot is
known, and that the distance between grid points is much greater than the dimensions of the area
from which the physical sample will be taken.
It is useful to note that for hot spot detection, there is only one decision error to consider:
the false acceptance (false negative) error (saying a hot spot doesn't exist when in reality it
does). The other error (false rejection or false positive) does not apply as when we obtain a
"hot" sample we will automatically assume it really is a hot spot (i.e. we are saying with
certainty that it really is a hot spot).
It is common practice to make VSP generate a set of different scenarios for different
specified variables and so enable the project team to conduct a sensitivity analysis of the
problem, and finally select one arrangement that best satisfies the project needs.
For example, an abbreviated report from sampling the Operations Area would have the
following appearance:
Systematic sampling locations for detecting an area of elevated values (hot spot)
This report summarizes the sampling design used, associated statistical assumptions, as
well as general guidelines for conducting post-sampling data analysis. Sampling plan
EPAQA/CS-l B-3 February 2006
-------
components presented here include how many sampling locations to choose and where within
the sampling area to collect those samples. The type of medium to sample (i.e., soil,
groundwater, etc.) and how to analyze the samples (in-situ, fixed laboratory, etc.) are addressed
in other sections of the sampling plan.
The following table summarizes the sampling design developed.
Table B-l. Summary of Sampling Design
Primary Objective of Design
Type of Sampling Design
Sample Placement (Location)
in the Field
Formula for calculating
number of sampling locations
Calculated total number of samples
Number of samples on map a
Number of selected sample areas b
Specified sampling area c
Grid pattern
Size of grid / Area of grid cell d
Total cost of sampling e
Detect the presence of a hot spot
that has a specified size and shape
Hot spot (elliptical ratio 0.8)
Systematic (Hot Spot)
with a random start location
Singer and Wickman algorithm Probability of detection
(1-3) = 0.9566
15
14
1
112500ft2
Triangular
75 feet 7243 5. 625 ft2
$9000.00
a This number may differ from the calculated number because of 1) grid edge effects, 2) adding
judgment samples, or 3) selecting or unselecting sample areas.
b The number of selected sample areas is the number of colored areas on the map of the site.
These sample areas contain the locations where samples are collected.
c The sampling area is the total surface area of the selected colored sample areas on the map of
the site.
d Size of grid / Area of grid cell gives the linear and square dimensions of the grid used to
systematically place samples.
e Including measurement analyses and fixed overhead costs. See the Cost of Sampling section
for an explanation of the costs presented here.
The following graph shows the relationship between number of samples and the
probability of finding the hot spot. The dashed blue line shows the actual number of samples for
this design (which may differ from the optimum number of samples because of edge effects).
EPAQA/CS-l
B-4
February 2006
-------
100
95
90
85
80
75
70
55
>50
=45
20
15
10
5
Hotspot Sampling of 112500 Feet2
45 foot semi-major axis elliptical (0.80) hotspot
0 2 4 6 8 10 12 14 16 18 20 22 24
Number of samples using a triangular grid
Figure B-2: Hotspot Sampling of 112500 Feet
Statistical Assumptions
The assumptions associated with the sample spacing algorithm are that:
1. the target hot spot (its projection onto the coordinate plane) is circular or elliptical,
2. samples are taken on a square, rectangular, or triangular grid,
3. a very small proportion of the area being studied will be sampled (the sample is much
smaller than the hot spot of interest),
4. the level of contamination that classifies a hot spot is well defined, and
5. there are no misclassification errors (a hot spot is not mistakenly overlooked or an area is
not mistakenly identified as a hot spot).
These assumptions cannot be validated through data collection. The size and shape of a
hot spot of interest are well defined prior to determining the number of samples and the
measured value that defines a hot spot is well above the detection limit for the analytical methods
that will be used. Grid sampling will be carried out to the level achievable; topographic,
vegetative, and other features that prevent sampling at the specified coordinates will be noted
and their influence recognized.
EPAQA/CS-1
B-5
February 2006
-------
Sensitivity Analysis
The sensitivity of the calculation of number of samples was explored by varying Area
and Side and examining the resulting changes in the number of samples. The following table
shows the results of this analysis.
Table B-2. Number of Samples
Area= 56250
Area=l 12500
Area=168750
Side=37.5
31
60
91
Side=75
8
15
23
Side=112.
5
5
8
12
Area = Total Sampling Area
Side = Length of Grid Side
Cost of Sampling
The total cost of the completed sampling program depends on several cost inputs, some
of which are fixed, and others that are based on the number of samples collected and measured.
Based on the numbers of samples determined above, the estimated total cost of sampling and
analysis at this site is $9000.00. The following table summarizes the inputs and resulting cost
estimates.
Table B-3. Cost Information
Cost Details
Field collection costs
Analytical costs
Sum of Field & Analytical costs
Fixed planning and validation costs
Total cost
Per Analysis
$150.00
Per Sample
$600.00
$600.00
15 Samples
$9000.00
$ 9000.00
$ 9000.00
EPAQA/CS-1
B-6
February 2006
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APPENDIX C
SUMMARY OF THE DQOS DEVELOPED FOR THE PRELIMINARY
INVESTIGATION
Step 1: State
the Problem
The Preliminary Investigation (PI) will focus on establishing the types of
contaminants present at the site and the approximate spatial distribution of
contaminant concentrations. The Remedial Investigation will use the information
generated in the PI to estimate the quantity of additional data needed to make
remedial decisions for the site with a specified level of confidence.
Step 2:
Identify the
Decision
Preliminary Investigation Questions
Primary Questions
> What is the spatial distribution of contaminants in soil and are they greater
than the screening criteria?
> Has soil contamination reached the shallow aquifer?
> Is soil and groundwater contamination a significant source of ongoing
contamination to the Bay?
Secondary Questions
> In what areas of the site do COPC concentrations in soil exceed background
concentrations or industrial risk screening levels?
> Are soil contaminants detected in groundwater at locations of relatively high
soil contamination?
> What is the potential for erosion of contaminated site soils?
Step 3:
Identify
Inputs to the
Decision
Field immunoassay method will be used for establishing the boundaries of soil
contamination.
Based on information from similar former MGP sites, PAHs, VOCs, metals and
cyanide are contaminants of potential concern (COPCs).
Background data will be compared to the fixed lab confirmation data.
A minimum number of fixed laboratory confirmation samples would be analyzed for
each of the post-stratified subareas.
Step 4:
Define the
Boundaries
of the Study
The top soil sampling depth interval will be 0 - 0.5 ft. (the traditional definition of
"surface soil."), and the second interval will be 0.5 - 3 ft..
Lower depth intervals (3- 6 ft.; 6 -12 ft., 12 ft. to groundwater) were defined with the
addition of a decision rule to forego the two deepest intervals if total PAH
concentrations in higher intervals were essentially consistent with background
concentrations.
Three initial subareas of interest were defined: 1) Operations Area,
2) Oil Storage Area, and 3) Surrounding Environs (the remaining
portion of the site).
Based on patterns of total PAH concentrations in each of the three initial subareas
and each of the four soil depth intervals, the boundaries of the subareas will be
refined for the RI.
EPAQA/CS-1
C-l
February 2006
-------
Step 5:
Develop a
Decision
Rule
Overall Decision Rule: If concentrations of MGP-related contaminants in surface
soil, subsurface soil, or groundwater in a subarea exceed PI risk-based screening
criteria, or if the pattern of COPC concentrations in surface soil indicate transport of
COPCs to the Bay, determine the additional data needs to complete a Remedial
Investigation for this subarea.
If concentrations of PAHs in a subarea or depth interval are found to be elevated
relative to background PAH concentrations, then MGP-related contaminants will be
presumed to be present and the area will be further evaluated to determine the need
for remedial action.
If a constituent is present in subarea soils at concentrations significantly higher than
background and if the maximum detected concentration is greater than its screening
criterion, then the constituent will be considered a COPC, and will be evaluated
further in the Remedial Investigation.
If the maximum detected concentration of a chemical in groundwater beneath a
subarea exceeds the groundwater screening criterion, then the chemical will be
identified as a COPC.
If surface soil data show decreasing concentrations of COPCs along an axis
perpendicular to the shoreline, and if surface soil concentrations at sampling
locations nearest the Bay are below screening criteria, then conclude that transport of
contaminants in site soils to the Bay is not a significant process.
Step 6:
Specify
Tolerable
Limits on
Decision
Errors
In both the Oil Storage and Operations Areas, a 75 ft. triangular grid will be used as
it provides a 95% change of hitting an elliptical hot spot with the length of the semi-
major axis of 45 ft. In the Site Environs, a 200 ft. grid will be used as it provides a
95% probability of hitting an elliptical hot spot with the length of the semi-major
axis of 119 ft. A systematic triangular grid will be utilized using a "find a hot spot"
sampling goal.
Step 7:
Develop the
Plan for
Obtaining
Data
Oil Storage Area (A) has 15 sample locations, Operations Area (B) has 41 locations
and Site Environs (C) 24 locations, for a total of 80 locations. If samples are
analyzed for all four depths at each location, 320 analyses will be conducted. Since
the sampling design is adaptive, a finer grid may be applied over a larger area and it
is assumed an additional 10% (32 analyses) may be required. The total projected
costs for the PAH immunoassay survey sampling and analysis is $52.8K.
Additional costs will be incurred for fixed laboratory analysis, estimated at
$lK/sample. Based on experience with other PAH-contaminated sites, it is assumed
that 30 fixed lab samples will be collected. In addition, a standard number of f QC
samples will be collected.
Groundwater sampling design will be biased toward the locations in each subarea
with the highest observed concentration of PAHs in the subsurface. Assuming the
three initial areas are retained, and two upgradient samples will be collected, the
team budgeted for five groundwater samples. These samples will be sent to the
laboratory to perform a PAH, SVOC and VOC analyses at a projected cost of
$700/sample, plus the cost of obtaining the hydropunch samples, estimated at
$300/sample.
The total projected costs for the PI is therefore $87K, to include soil and groundwater
sampling representative of the site. The remaining $13K is to be held as a contingency
fund to complete the field effort.
EPAQA/CS-1
C-2
February 2006
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APPENDIX D
FIELD IMPLEMENTATION DETAILS
Oil Storage Area - A total of 15 cores in the Oil Storage Area were collected resulting in
52 immunoassays for total PAHs; seven of which were from the 3-6 ft. interval, but none of
which was in the > 6 ft. interval. No highly contaminated soil in this area was found, however,
tPAH concentrations on the southern side of the rail spur in the top three depth intervals were
higher than north of the rail spur. In general the surface interval was cleaner than subsurface
samples. Due to slightly elevated concentrations at depth in station A-13, the team considered
expanding sampling at the 75 ft. spacing to the south. However, due to the fact that on both sides
of A-13 concentrations were much lower, and the moderate concentrations observed, the team
decided not to expand this grid. If sampling in the site environs (Area C) indicates elevated
PAHs at C-20 or C-21, additional samples in this area will be considered.
Coring logs and notes indicate that the clay layer noted in sampling of the Operations
Area was present in all samples. Slight discoloration, possibly due to oil contamination was
observed in the two samples with the highest PAH concentrations from just below the ground
surface to the clay layer, but not beneath the clay layer.
A groundwater sample was collected by Hydropunch at a location just to the west of
A-13: the location of the highest subsurface concentration in the 3-6 ft. interval (Figure 2-6) and
no free product was observed in the sample.
Operations Area - Cores were collected at the planned 41 sampling locations. The
original sampling grid in this area (Figure 2-7) was extended by two rows on the southern
boundary of the Operations Area (12 samples) due to the detection of high concentrations of total
PAHs in the southern region of the area. Following the adaptive analysis rules, a total of 201
immunoassays were performed for total PAHs. Elevated PAHs continued to be found in the first
new row to the south, but dropped to approximately ambient levels in the last new row. The
highest concentrations are correlated with visual observations of a powdery black substance,
probably lampblack, in the core.
Coring logs indicated a one to three ft. thick clay layer was present in all samples at a
depth of approximately 10 ft. below ground surface. Observations of the cores where high total
PAH concentrations were measured indicated that visible staining and petroleum odors were
occasionally noted immediately above the clay layer or at shallower depths but never below the
clay layer. This finding appears to confirm the team hydrogeologist's hypothesis that the clay
layer may have served as a barrier to vertical migration of hydrocarbons.
A groundwater sample was collected west of B-45, the location of the highest subsurface
PAH concentration (Figure 2-13). No free product was observed in any sample.
Site Environs - Cores from the initial 24 sampling locations were collected and field-
screened for total PAHs. During the first day, the field team met core refusal numerous times
when attempting to obtain a core from C-8. Gravel from the parking area was scraped away from
EPAQA/CS-l D-l February 2006
-------
a three ft. area, and eventually a reasonably intact core was collected. A visual analysis of failed
cores revealed debris mixed in with native soil, ash, slag, and lampblack. In the deeper intervals,
the core contained thick, black, tarry wastes. The tarry waste was analyzed by immunoassay and
found to contain levels of PAHs higher than the calibration scale of the kit. After discussing
these findings with the Power Company representative, and looking more closely at the
surrounding areas, it appeared that this sampling location was in alignment with a ravine-like
feature extending from the parking area to the cove. The team decided to take samples up- and
down- gradient from C-8, to further evaluate what appeared to be materials dumped in a former
ravine. In all, five additional cores were obtained and analyzed: two in the direction of the cove,
and three upgradient. Tarry material was found in the samples surrounding C-8, especially below
three ft. of cover. An additional core near the cove revealed consistent soil-fill with no evidence
of tarry material, and was not analyzed.
EPAQA/CS-1 D-2 February 2006
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APPENDIX E
SAMPLE SIZE SELECTION FOR BACKGROUND COMPARISONS
This appendix describes the determination of the necessary number of fixed lab samples
in the post-stratified areas to make comparisons to background levels. Under the null hypothesis
of equal site and reference means, it is assumed that the populations are identical and so the
reference mean and standard deviation will be used to determine sample size requirements.
Table D-l shows the necessary sample sizes for a two-sample, one-sided t-tesi for various
significance levels, power levels, and difference-to-be-detected as a percentage of the mean. The
sample sizes listed are for each population.
Table E-l. Sample Size Required in Each Site and Background Location
Power
0.80
0.85
0.90
0.95
Significance level = 0.05
Difference-to-be-detected
50%
37
43
50
63
75%
17
20
23
29
100%
10
12
14
17
125%
7
8
9
11
150%
5
6
7
8
Significance level = 0.10
Difference-to-be-detected
50%
27
32
39
50
75%
12
15
18
23
100%
7
9
10
13
125%
5
6
7
9
150%
4
4
5
6
It was decided to use a significance level of 0.05, a power level of 0.90, and a difference-
to-be-detected of 150%. These values reflect the planning team's assumption that if a
contaminant is related to the MGP, it is likely to be present at concentrations well in excess of
the Background site - that is at least 200% higher. By ensuring that a shift of 150% can be
detected with good power, it was thought that larger shifts would be detected with even better
power. The choice of a 10% chance of missing a shift of 150% (the power level of 0.90) was
based on experience with similar situations. In addition, since multiple statistical tests are to be
used, and not simply a two sample t-tesi, the probability of seeing other shifts, such as a shift in
the upper tail, would be greatly enhanced.
From Table D-l, with power of 0.90 and a difference to be detected at 150%, it can be
seen that at least seven samples would be required from both the sampled area and background
location. This minimal requirement was increased from seven (Oil Storage Area), to 11 (Site
Environs), to 12 (Operations Area) after discussion of the potential of each area to contain
contamination and the probable use of a non-parametric test (Wilcoxon Rank Sum) in the final
analysis (the use of a non-parametric test increases the sample size by about 15%). The
background requirement of seven samples was easily met by the existence of 15 samples being
available.
EPAQA/CS-l
E-l
February 2006
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EPAQA/CS-1 E-2 Febraary 2006
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APPENDIX F
COMPARISON OF IMMUNOASSAY AND FIXED LABORATORY RESULTS
Total PAH and BaP equivalents from Fixed Laboratory analyses were compared to the
immunoassay results to assess the reliability of the less expansive immunoassay readings.
It was thought that high immunoassay results would have a disproportionate influence on
correlation and so several correlation studies were made by eliminating some of the higher
values to ascertain their effect. Table E-l shows the correlation of Fixed Laboratory total PAH
with Immunoassay total PAH; Table E-2 shows the correlation of Fixed Laboratory BaP
equivalents with Immunoassay total PAH.
Table F-l. Correlation of Fixed Laboratory total PAH with Immunoassay total PAH
Data Used
All data
2 values > 200,000 ppb omitted
6 values > 50,000 ppb omitted
1 1 values > 1 0,000 ppb omitted
Correlation
0.9085
0.8135
0.8581
0.8486
Table F-2. Correlation of Fixed Laboratory BaP equivalents with Immunoassay total PAH
Data Used
All data
2 values > 200,000 ppb omitted
6 values > 50,000 ppb omitted
1 1 values > 1 0,000 ppb omitted
Correlation
0.6127
0.6216
0.6523
0.7827
Table E-l shows a relatively high degree of correlation between the immunoassay and
total PAH values (with r > 0.8) in all cases, whereas the correlation to BaP equivalents (Table E-
2) is not as good, and improves only once the higher screening values are removed. This
indicates that there is more variability in the concentration of those PAHs contributing to the BaP
equivalents and indicates that immunoassay is a better predictor of total PAH than it is of the
carcinogenic subset of PAHs. Based on this observation, it was decided that Fixed Laboratory
results will be necessary to complete the baseline risk evaluation in the Remedial Investigation.
EPAQA/CS-l F-l February 2006
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EPAQA/CS-1 F-2 Febraary 2006
-------
APPENDIX G
SUMMARY OF THE PRELIMINARY INVESTIGATION
STATISTICAL ANALYSIS OF THE COPCS
Three analyses were conducted: BaP equivalents, Arsenic, and Individual PAHs.
The BaP Equivalents Analysis
Graphical comparisons and formal statistical tests were used to compare the three
investigation sites (Oil Storage Area, Operations Area, and Site Environs) and Background for
the principal COPC: BaP equivalents. These tests are described more fully in Data Quality
Assessment: Statistical Tools for Practitioners (EPA QA/G-9S).
Graphical Comparisons
Example of a Box-
and-Whiskers Plot
In addition to the straightforward interpretation of Tables 2A,
2B, and 2C, further investigation of the distribution of contamination
may be made through examination of Box-and-Whisker plots. These
are a simple way of condensing the data to a visual image and are
composed of a central box divided by a horizontal line representing
the median, and two lines extending out from the box called whiskers.
The length of the central box indicates the spread of the bulk of the
data (the central 50%) while the length of the whiskers show how
stretched the tails of the distribution are. The sample mean is
displayed using a "+" sign and any unusually small or large data
points are displayed by a "*" on the plot. If the distribution is
symmetrical, the box is divided in two equal halves by the median,
the whiskers will be the same length and the number of extreme data
points will be distributed equally on either end of the plot for
symmetric data. Values that are unusually large or small can be
easily identified, and a side-by-side comparison of box-plots for
different sets of data can be made to ascertain similarities in
distribution.
Figure F-l shows the BaP Equivalents for the three areas and Background on a standard
scale followed by the same comparison using the logarithmic scale. Note how only data from the
Operations Area exceed the screening level with the median level well above the screening level
of 2300 ppb; the Oil Storage Area, Site Environs, and Background being all well below 2300
ppb. For the Operations Area, the largest value (30167.0 ppb) has been noted (asterisk) as a
potential outlier as it is well larger than the majority of the data. The highly "squashed"
appearance of the Oil Storage Area, Site Environs, and Background data being due to the scale
being used to illustrate the data. Conversion of the data to a logarithmic scale allows the data to
be seen a little better with less influence from the variability of the data. Again, it is clear that
most of the contamination from the Operations Area exceeds the screening level. The long "tail"
EPAQA/CS-l
G-l
February 2006
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of the Background is indicative of there being mostly low levels of contamination present outside
the MGP operations area.
Box-plots of BaP Equivalent by Sampling Area
03
> O
'g- §
ill !£
CL
m o
Oil Storage Area Operations Area
Site Environs
Background
o
o
o -
o
LJJ
Q_
TO
CO
Box-plots of BaP Equivalent by Sampling Area
Oil Storage Area Operations Area Site Environs Background
Figure G-l. BaP Equivalents Box Plots: Standard and Log Scales
EPAQA/CS-l
G-2
February 2006
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Statistical Tests on the BaP Equivalents Data
Four statistical tests were made on the data from the three areas with respect to the
Background data: Two-Sample t-test, Wilcoxon Rank Sum test, Quantile test, and the Slippage
test. Each test considers a different aspect of the data.
The Two-Sample t-test
This test compares the mean of each area to the mean of the Background area. Due to the
large differences in standard deviations between the three areas and Background, Satterthwaite's
Two-Sample t-test is to be preferred over the more commonly encountered standard t-test (see
section 3.3.1.1.2 of Data Quality Assessment: Statistical Tools for Practitioners EPA QA/G-
9S). The assumption of approximate Normality in distribution of each data set used in the
comparisons is unlikely to be true (for the Operations area, note the large discrepancy between
mean [7465.3ppb] and median [4441.Oppb]; the mean and median should be quite close if the
data were normally distributed) and so the test may not be particularly informative.
Area
Oil Storage
Operations
Site Environs
Mean
330.2
7465.3
420.0
p-value
0.0745
0.0246
0.0033
Background Mean = 130.3
Operating on the base-line assumption (null hypothesis)that there is no difference
between the individual area means and Background, and using the p-value as a guide, it is clear
that there is a significant difference between the Operations Area and Background, also between
Site Environs and Background, but not between the Oil Storage Area and Background. It would
be expected that the difference between the Operations Area and Background should be far more
pronounced (compare the two p-values, Operations Area is not as strong as Site Environs) but
the effect is being greatly obscured by the lack of Normality, especially with the large data
values. The difference between Site Environs and Background suffers less because the lack of
Normality is in the low values. The test shows there is a difference but is not really too useful.
The Wilcoxon Rank Sum Test
This test may be regarded as the non-parametric analogue of the Two Sample t-test in
that the assumption of Normality is not required. The distributions of the two areas in the
comparison should be approximately the same and the test essentially looks to see if one
distribution differs from the other by a fixed (yet unknown) amount (see section 3.3.2.1.1 of
Data Quality Assessment: Statistical Tools for Practitioners EPA QA/G-9S).
Area
Oil Storage
Operations
Site Environs
p-value
0.1336
O.OOOO
0.0005
EPAQA/CS-1 G-3 February 2006
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Operating on the base-line assumption (null hypothesis) that there is no difference
between the individual areas and Background, and using the p-value as a guide, it is clear that
there is a significant difference between the Operations Area and Background, also between Site
Environs and Background, but not between the Oil Storage Area and Background. The
extremely small p-value for Operations Area indicates clearly that the difference clearly could
not be due to chance and this reinforces the conclusion drawn from inspecting the Box-and-
Whiskers plot. A similar conclusion can be reached for the difference between Site Environs and
Background (although not quite as strong). The failure to find a difference between the Oil
Storage Area and Background is a little surprising but all the tests may be affected by the lack of
similarity in distributional shape (the differences can be seen clearly in Figure F-l).
The Quantile Test
The Quantile test is useful in detecting instances where only parts of the data are different
as opposed to a complete shift in the data. It is often run together with the Wilcoxon test (see
section 3.3.2.1.2 of Data Quality Assessment: Statistical Tools for Practitioners (EPA QA/G-
9S).
Area
Oil Storage
Operations
Site Environs
p-value
0.1146
0.0006
0.0020
Using the base-line assumption (null hypothesis) that there is no difference between the
individual areas and Background, and using the p-value as a guide, it is clear that there is a
significant difference between the Operations Area and Background, also between Site Environs
and Background, but not between the Oil Storage Area and Background. The extremely small p-
value for Operations Area indicates clearly that the difference clearly could not be due to chance
and this reinforces the conclusion drawn from the Wilcoxon test. A similar conclusion can be
reached for the difference between Site Environs and Background (although not quite as strong).
As in the Wilcoxon test, there seems to be no difference between the oil Storage Are and
Background.
The Slippage Test
This test concentrates on the larger values of each data set and essentially compares the
largest values of an area against the maximum value of the Background data set (see section
3.3.2.1.3 of Data Quality Assessment: Statistical Tools for Practitioners EPA QA/G-9S).
Area
Oil Storage
Operations
Site Environs
p-value
0.0150
< 0.0000
0.0020
EPAQA/CS-1 G-4 February 2006
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With the null hypothesis that the larger values of an area are not significantly larger than
the maximum of the Background data set, inspection of the p-values indicates that there is indeed
a significant difference between the MGP areas and Background.
Arsenic
Graphical comparisons only are presented (Figue F-2) because all statistical tests on the
data (Two-Sample t-test, Wilcoxon Signed Rank, Quantile, and Slippage) failed to be significant
at even the 0.3 level. Inspection of the box-and-whisker plots shows only the Background area
to be even close to the screening level with the distribution of Arsenic approximately the same
across all four areas.
The Individual PAHs
Graphical comparisons only (Figures F-3 to F-12) were used to compare the three
investigation sites (Oil Storage Area, Operations Area, and Site Environs) and Background for
the individual PAHs as it had been decided to focus resources on the BaP Equivalents.
Inspection of the individual standard scale box-and-whisker plots indicates the large
predominance of PAHs in the Operations Area; large values in the Operating Area often being
orders of magnitude larger than the other areas. Inspection of the individual logarithmic scale
box-and-whisker plots show a marked similarity in the distribution of PAHs in the Operating
Area with the exception of fluoranthene and indeno(l,2,3cd)pyrene (which are very similar in
distribution themselves). The other areas (Oil Storage, Site Environs, and Background) show
marked similarity across all PAHs.
EPAQA/CS-1 G-5 February 2006
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o
O o
screening level
ARSENIC
Oil Storage Area Operations Area Site Environs Background
ARSENIC
J=
c
CD
O
O
screening level
Oil Storage Area Operations Area Site Environs Background
Figure G-2. Arsenic Standard and Log Scales
EPAQA/CS-l
G-6
February 2006
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Box-plots of BENZO.A.ANTHRACENE by Sampling Area
Box-plots of BENZO.A.PYRENE by Sampling Area
<
Q_
I
<
Q_
Oil Storage Area Operations Area Site Environs Background
Oil Storage Area Operations Area Site Environs Background
Box-plots of BENZO.A.ANTHRACENE by Sampling Area
Box-plots of BENZO.A.PYRENE by Sampling Area
Oil Storage Area Operations Area Site Environs Background
Oil Storage Area Operations Area Site Environs Background
Figure G-3. Benzo(a)anthracene Box Plots:
Standard and Log Scales
Figure G-4. Benzo(a)pyrene Plots
Standard and Log Scales
EPAQA/CS-l
G-7
February 2006
-------
Box-plots of BENZO.B.FLUORANTHENE by Sampling Area Box-plots of BENZO.G.H.I.PERYLENE by Sampling Area
Oil Storage Area Operations Area Site Environs Background
<
Q_
Oil Storage Area Operations Area Site Environs Background
Box-plots of BENZO.B.FLUORANTHENE by Sampling Area Box-plots of BENZO.G.H.I.PERYLENE by Sampling Area
Oil Storage Area Operations Area Site Environs Background
Figure G-5. Benzo(b)flouranthene Plots:
Standard and Log Scales
T O
< ^
Q_
Oil Storage Area Operations Area Site Environs Background
Figure G-6. Benzo(g,h,i)perylene Plots
Standard and Log Scales
EPAQA/CS-l
G-8
Febraary 2006
-------
Box-plots of BENZO.K.FLUORANTHENE by Sampling Area
Box-plots of CHRYSENE by Sampling Area
5 8
Q_ CN
1 1 1 1
Oil Storage Area Operations Area Site Environs Background
Oil Storage Area Operations Area Site Environs Background
Box-plots of BENZO.K.FLUORANTHENE by Sampling Area
Box-plots of CHRYSENE by Sampling Area
Oil Storage Area Operations Area Site Environs Background
T
<
Q_
Oil Storage Area Operations Area Site Environs Background
Figure G-7. Benzo(k)flouranthene Plots:
Standard and Log Scales
Figure G-8. Chrysene Box Plots:
Standard and Log Scales
EPAQA/CS-l
G-9
February 2006
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Box-plots of FLUORANTHENE by Sampling Area
Box-plots of INDEN0.1.2.3.CD.PYRENE by Sampling Area
o
o
o
1 1 1
Oil Storage Area Operations Area Site Environs
T °
I §
1 1 1 1
Oil Storage Area Operations Area Site Environs Background
Box-plots of FLUORANTHENE by Sampling Area
o
o
0 -
0
CM
O
o
0 ~
o
o
o
CM
X
Q_
0
O "
Lf>
_
0
o -
o
0
CM ~
,
I
;
|
i
'
o
o
0
J
+
. I
T
*
Box-plots of INDENO.1.2.3.CD.PYRENE by Sampling Area
I
-------
Box-plots of PHENANTHRENE by Sampling Area
Box-plots of PYRENE by Sampling Area
<
Q_
Oil Storage Area Operations Area Site Environs Background
Oil Storage Area Operations Area Site Environs Background
Box-plots of PHENANTHRENE by Sampling Area
Box-plots of PYRENE by Sampling Area
o
o -
in
I o
< o
Q. o -
Oil Storage Area Operations Area Site Environs Background
Figure F-ll. Phenanthrene Plots:
Standard and Log Scales
<
Q_
Oil Storage Area Operations Area Site Environs Background
Figure G-12. Pyrene Box Plots:
Standard and Log
Scales
EPAQA/CS-l
G-ll
February 2006
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