1. TABLE OF CONTENTS
      2. SECTION III: TECHNICAL AND PROCEDURAL GUIDANCE
      3. A. Fate and Transport Analysis
      4. BACKGROUND STANDARD
      5. STATEWIDE HEALTH STANDARD
      6. SITE-SPECIFIC STANDARD
      7. 1. Fate and Transport Analysis in the Unsaturated Zone
      8. a) General
      9. b) Minimum Contaminant-Specific and Site-Specific Requirements
      10. i) Contaminant-Specific Requirements for All Analytical Tools
      11. ii) Site-Specific Requirements for All Analytical Tools
      12. iii) Additional Requirements
      13. c) Conditions for Use of Analytical Tools and Parameter Input Values
      14. d) Conclusion
      15. 2. Fate and Transport Analysis in the Saturated Zone
      16. GROUNDWATER FLOW
      17. CHEMICAL FATE AND TRANSPORT MECHANISIMS
      18. a) Groundwater Solute Fate and Transport Modeling (General)
      19. b) Define Study Objectives
      20. c) Data Collection
      21. d) Conceptual Model
      22. i) Geologic Data
      23. ii) Hydrologic Data
      24. iii) Hydraulic Data
      25. iv) Chemical and Contaminant Data
      26. e) Model Selection
      27. QUICK_DOMENICO.XLS
      28. SWLOAD.XLS
      29. f) Calibration and Sensitivity
      30. g) Predictive Simulations
      31. h) Fate and Transport Model Report
      32. 3. Impacts to Surface Water from Diffuse Flow of Contaminated Groundwater
      33. a) Conceptual Framework
      34. b) Mathematical Framework
      35. c) Application
      36. d) Statewide Health Standard in Aquifers with 2,500 mg/L TDS or Less
      37. e) Examples
      38. i) Example 1: Groundwater Source Very Near or Adjacent to Surface
      39. Water Discharge
      40. Table III-1
      41. SUBSTANCE
      42. Number
      43. Table III-1
      44. SUBSTANCE
      45. Number
      46. Table III-1
      47. SUBSTANCE
      48. Number
      49. Table III-1
      50. SUBSTANCE
      51. Number
      52. Table III-1
      53. SUBSTANCE
      54. Number
      55. Table III-1
      56. SUBSTANCE
      57. Number
      58. Table III-1
      59. SUBSTANCE
      60. Number
      61. Table III-1
      62. SUBSTANCE
      63. Number
      64. Example 2: Groundwater Source at Distance from Surface Water
      65. Discharge – Steady-State Conditions
      66. Figure III-1
      67. Example 1 – PENTOXSD Model Inputs
      68. Figure III-2
      69. Example 1 –PENTOXSD Model Output
      70. Figure III-3
      71. Example 2 – Quick Domenico Model Output
      72. 2.701
      73. Figure III-4
      74. Example 2 – SWLOAD Model Output
      75. Figure III-5
      76. Example 2 – PENTOXSD Model Inputs
      77. Figure III-6
      78. Example 2 – PENTOXSD Model Output
      79. B. Guidance for Attainment Demonstration with Statistical Methods
      80. 1. Introduction
      81. 2. Data Review for Statistical Methods
      82. a) Summary Statistics
      83. b) Graphical Procedures
      84. 3. Statistical Inference and Hypothesis Statements
      85. 4. Selection of Statistical Methods
      86. a) Factors Affecting the Selection of Statistical Methods
      87. b) Recommended Statistical Procedures
      88. i) Soil Risk-Based Standards
      89. Figure III-7
      90. Flow Chart of Recommended Statistical Methods
      91. (a) 75%/10X Rule
      92. (b) The 95% Upper Confidence Limit (UCL) of Arithmetic Mean
      93. Figure III-8: Examples of Normal Distribution and Lognormal Distribution
      94. (c) No Exceedance Rule
      95. ii) Groundwater Risk-Based Standards
      96. iii) Soil Background Standards
      97. (a) Wilcoxon Rank Sum Test
      98. (b) Quantile Test
      99. iv) Groundwater Background Standards
      100. 5. Additional Information on Statistical Procedures
      101. a) Interval Tests
      102. b) Tests for Comparing Populations
      103. c) Trend Tests
      104. 6. Calculation of UCL of Mean When the Distribution of the Sampling Mean is
      105. Normal
      106. 7. Calculation of UCL of Mean of a Lognormal Distribution
      107. 8. Procedure and Example for Conducting the Wilcoxon Rank Sum Test
      108. Procedure
      109. Reference Area Cleanup Unit
      110. 9. Procedure and Example for Conducting the Quantile Test
      111. REFERENCES
      112. Table III-2: Random Number Table
      113. Table III-3: Student’s t-Distribution for Selected Alpha and Degrees of Freedom
      114. Table III-4: Table of z for Selected Alpha
      115. C. Storage Tank Program Guidance
      116. 1. Corrective Action Process
      117. 2. Corrective Action Process Checklist
      118. Figure III-9
      119. The Regulated Storage Tank Corrective Action Process Flowchart
      120. 4. Maximum Extent Practicable
      121. Figure III-10
      122. Corrective Action Process Report/Plan Cover Sheet
      123. Table III- 5
      124. Short List of Petroleum Products
      125. Table III-5 - Continued
      126. Short List of Petroleum Products
      127. D. Mass Calculations
      128. 1. Groundwater Mass Calculation
      129. 2. Soil Mass Calculation
      130. E. Long-Term Stewardship
      131. 1. Introduction
      132. 2. Uniform Environmental Covenants Act
      133. TABLE III-6
      134. Postremediation Care Decision Matrix
      135. Background
      136. Statewide Health
      137. Site-Specific
      138. 3. Institutional versus Engineering Controls
      139. 4. Postremediation Care Plan
      140. 5. Postremediation Monitoring
      141. a) Duration
      142. b) Frequency
      143. c) Cessation of Postremediation Monitoring
      144. 6. Postremediation Care Attainment
      145. F. One Cleanup Program
      146. 1. Purpose
      147. 2. Provisions and Applicability
      148. 3. Implementation
      149. 4. Benefits
      150. G. Data Quality and Practical Quantitation Limits
      151. 2. Preliminary Data Review
      152. 3. Practical Quantitation Limit (25 Pa. Code § 250.4)
      153. H. Site-Specific Human Health Risk Assessment Guidance
      154. 1. Introduction
      155. 2. When to Perform a Risk Assessment
      156. 3. Risk Assessment for Human Health [25 Pa. Code § 250.602(c)]
      157. a) Site Characterization [§ 250.602(c)(1)]
      158. i) Chemicals of Concern
      159. ii) Conceptual Site Model
      160. b) Exposure Assessment [§§ 250.603 and 250.604]
      161. i) Exposure Scenarios and Exposure Pathways
      162. ii) Exposure Characterization
      163. iii) Good Exposure Assessment Practices
      164. c) Toxicity Assessment [Section 250.605]
      165. d) Risk Characterization
      166. e) Uncertainty Analysis
      167. 4. References for Human Health Risk Assessment
      168. I. Site-Specific Ecological Risk Assessment Guidance
      169. 1. Introduction
      170. 2. Ecological Risk Assessment Process
      171. a) Step 1 - Fundamental Components
      172. b) Step 2 - Preliminary Exposure Estimate and Risk Assessment
      173. i) Decision Point
      174. c) Step 3 - Problem Formulation: Assessment Endpoint Selection and Testable
      175. Hypotheses
      176. d) Step 4 - Problem Formulation: Conceptual Site Model, Measurement
      177. Endpoint Selection, and Study Design
      178. e) Step 5 - Site Assessment for Sampling Feasibility
      179. f) Step 6 - Site Investigation
      180. g) Step 7 - Risk Characterization
      181. h) Step 8 - Risk Management
      182. 3. References
      183. Figure III-11

261-0300-101 / DRAFT December 16, 2017 / Page III-i
TABLE OF CONTENTS
SECTION III: TECHNICAL AND PROCEDURAL GUIDANCE...............................................III-1
A.
Fate and Transport Analysis ...................................................................................................... III-1
1.
Fate and Transport Analysis in the Unsaturated Zone................................................... III-3
a)
General............................................................................................................... III-3
b)
Minimum Contaminant-Specific and Site-Specific Requirements.................... III-3
i)
Contaminant-Specific Requirements for All Analytical
Tools ...................................................................................................... III-3
ii)
Site-Specific Requirements for All Analytical Tools ............................ III-4
iii)
Additional Requirements ....................................................................... III-5
c)
Conditions for Use of Analytical Tools and Parameter Input
Values ................................................................................................................ III-6
d)
Conclusion ......................................................................................................... III-7
2.
Fate and Transport Analysis in the Saturated Zone ....................................................... III-7
a)
Groundwater Solute Fate and Transport Modeling (General) ........................... III-9
b)
Define Study Objectives .................................................................................. III-11
c)
Data Collection ................................................................................................ III-11
d)
Conceptual Model............................................................................................ III-12
i)
Geologic Data ...................................................................................... III-12
ii)
Hydrologic Data................................................................................... III-12
iii)
Hydraulic Data ..................................................................................... III-13
iv)
Chemical and Contaminant Data ......................................................... III-13
e)
Model Selection ............................................................................................... III-14
f)
Calibration and Sensitivity............................................................................... III-15
g)
Predictive Simulations ..................................................................................... III-15
h)
Fate and Transport Model Report .................................................................... III-16
3.
Impacts to Surface Water from Diffuse Flow of Contaminated
Groundwater ................................................................................................................ III-18
a)
Conceptual Framework.................................................................................... III-18
b)
Mathematical Framework ................................................................................ III-20
c)
Application....................................................................................................... III-21
d)
Statewide Health Standard in Aquifers with 2,500 mg/L TDS or
Less .................................................................................................................. III-22
e)
Examples.......................................................................................................... III-23
i)
Example 1: Groundwater Source Very Near or Adjacent to
Surface Water Discharge ..................................................................... III-23
ii)
Example 2: Groundwater Source at Distance from Surface
Water Discharge – Steady-State Conditions........................................ III-32
B.
Guidance for Attainment Demonstration with Statistical Methods......................................... III-41
1.
Introduction.................................................................................................................. III-41
2.
Data Review for Statistical Methods ........................................................................... III-42
a)
Summary Statistics........................................................................................... III-42
b)
Graphical Procedures ....................................................................................... III-43
3.
Statistical Inference and Hypothesis Statements ......................................................... III-43
4.
Selection of Statistical Methods................................................................................... III-45
a)
Factors Affecting the Selection of Statistical Methods.................................... III-45
b)
Recommended Statistical Procedures .............................................................. III-47

261-0300-101 / DRAFT December 16, 2017 / Page III-ii
i)
Soil Risk-Based Standards................................................................... III-47
(a)
75%/10X Rule.......................................................................... III-49
(b)
The 95% Upper Confidence Limit (UCL) of
Arithmetic Mean ...................................................................... III-49
(c)
No Exceedance Rule ................................................................ III-52
ii)
Groundwater Risk-Based Standards .................................................... III-53
iii)
Soil Background Standards.................................................................. III-54
(a)
Wilcoxon Rank Sum Test ........................................................ III-54
(b)
Quantile Test............................................................................ III-55
iv)
Groundwater Background Standards ................................................... III-56
5.
Additional Information on Statistical Procedures........................................................ III-58
a)
Interval Tests.................................................................................................... III-58
b)
Tests for Comparing Populations..................................................................... III-58
c)
Trend Tests....................................................................................................... III-59
6.
Calculation of UCL of Mean When the Distribution of the Sampling Mean
is Normal...................................................................................................................... III-61
7.
Calculation of UCL of Mean of a Lognormal Distribution ......................................... III-62
8.
Procedure and Example for Conducting the Wilcoxon Rank Sum Test...................... III-65
9.
Procedure and Example for Conducting the Quantile Test ......................................... III-69
C.
Storage Tank Program Guidance ............................................................................................. III-78
1.
Corrective Action Process............................................................................................ III-78
2.
Corrective Action Process Checklist ........................................................................... III-78
3.
Use of the Short List of Regulated Substances for Releases of Petroleum
Products........................................................................................................................ III-85
4.
Maximum Extent Practicable....................................................................................... III-86
D.
Mass Calculations .................................................................................................................... III-91
1.
Groundwater Mass Calculation.................................................................................... III-91
2.
Soil Mass Calculation .................................................................................................. III-91
E.
Long-Term Stewardship .......................................................................................................... III-92
1.
Introduction.................................................................................................................. III-92
2.
Uniform Environmental Covenants Act ...................................................................... III-92
3.
Institutional versus Engineering Controls.................................................................... III-95
4.
Postremediation Care Plan........................................................................................... III-95
5.
Postremediation Monitoring ........................................................................................ III-96
a)
Duration ........................................................................................................... III-96
b)
Frequency......................................................................................................... III-96
c)
Cessation of Postremediation Monitoring ....................................................... III-97
6.
Postremediation Care Attainment ................................................................................ III-97
F.
One Cleanup Program.............................................................................................................. III-98
1.
Purpose......................................................................................................................... III-98
2.
Provisions and Applicability........................................................................................ III-98
3.
Implementation ............................................................................................................ III-99
4.
Benefits ........................................................................................................................ III-99
G.
Data Quality and Practical Quantitation Limits..................................................................... III-100
1.
Data Quality Objectives Process, Sampling, and Data Quality Assessment
Process ....................................................................................................................... III-100
2.
Preliminary Data Review........................................................................................... III-102
3.
Practical Quantitation Limit (§ 250.4)....................................................................... III-103
H.
Site-Specific Human Health Risk Assessment Guidance...................................................... III-104

261-0300-101 / DRAFT December 16, 2017 / Page III-iii
1.
Introduction................................................................................................................ III-104
2.
When to Perform a Risk Assessment......................................................................... III-104
3.
Risk Assessment for Human Health [§ 250.602(c)] .................................................. III-105
a)
Site Characterization [§ 250.602(c)(1)] ......................................................... III-105
i)
Chemicals of Concern........................................................................ III-105
ii)
Conceptual Site Model....................................................................... III-107
b)
Exposure Assessment [§§ 250.603 and 250.604] .......................................... III-107
i)
Exposure Scenarios and Exposure Pathways..................................... III-108
ii)
Exposure Characterization ................................................................. III-112
iii)
Good Exposure Assessment Practices ............................................... III-113
c)
Toxicity Assessment [Section 250.605] ........................................................ III-113
d)
Risk Characterization..................................................................................... III-115
e)
Uncertainty Analysis...................................................................................... III-116
4.
References for Human Health Risk Assessment ....................................................... III-118
I.
Site-Specific Ecological Risk Assessment Guidance ............................................................ III-122
1.
Introduction................................................................................................................ III-122
2.
Ecological Risk Assessment Process ......................................................................... III-122
a)
Step 1 - Fundamental Components ................................................................ III-122
b)
Step 2 - Preliminary Exposure Estimate and Risk Assessment ..................... III-123
i)
Decision Point.................................................................................... III-124
c)
Step 3 - Problem Formulation: Assessment Endpoint Selection
and Testable Hypotheses................................................................................ III-124
d)
Step 4 - Problem Formulation: Conceptual Site Model,
Measurement Endpoint Selection, and Study Design.................................... III-124
e)
Step 5 - Site Assessment for Sampling Feasibility ........................................ III-125
f)
Step 6 - Site Investigation .............................................................................. III-125
g)
Step 7 - Risk Characterization ....................................................................... III-126
h)
Step 8 - Risk Management............................................................................. III-126
3.
References.................................................................................................................. III-127

261-0300-101 / DRAFT December 16, 2017 / Page III-1
SECTION III: TECHNICAL AND PROCEDURAL GUIDANCE
A.
Fate and Transport Analysis
Fate and transport analyses required under Act 2 may involve a wide spectrum of predictive
assumptions, calculations and simulations, ranging from the simple to the complex, depending
on the hydrogeologic characteristics of a site, future use scenarios, and the selection/applicability
of a particular cleanup standard.
Fate and transport analysis or modeling is a necessary part of site characterization and
demonstrating attainment of an Act 2 standard.
However, the Chapter 250 regulations
governing Act 2 use the term “fate and transport analysis” as opposed to “fate and transport
model.” This particular distinction was made because it will not always be necessary to run an
analytical or numerical quantitative “fate and transport model” to achieve a standard.
Whether simple or complex, any fate and transport analysis must rely on having and/or obtaining
valid data. Reliable field data will be critical in supporting the professional conclusions
regarding any predictions of contaminant fate and transport and needs to be considered during
the site characterization.
Fate and transport analysis will be used in the Act 2 process to predict contaminant
concentrations migrating through the unsaturated zone and the saturated zone, including the
impact of soil contamination on groundwater. It will also include an analysis of diffuse
groundwater flow into surface water (e.g., a stream) for purposes of determining compliance
with surface water quality standards.
Generally, fate and transport analyses under Act 2 may be used for the following purposes:
To predict the concentrations of one or more contaminants at one or more locations in the
future, often at a specific time (e.g., 30 years).
To assess potential remediation alternatives.
To evaluate natural attenuation remedies and associated monitoring requirements.
To assure continued attainment of the relevant standard.
To estimate groundwater chemical flux used in mass balance calculations for attainment
of surface water standards.
To assess postremediation care requirements and termination.
Furthermore, fate and transport analysis is used in specific ways under the three remediation
standards.
BACKGROUND STANDARD
To justify reduced duration for monitoring of upgradient release.

261-0300-101 / DRAFT December 16, 2017 / Page III-2
To combine the background groundwater standard with non-background soil standards.
To assess the impact of transformations in the upgradient plume.
STATEWIDE HEALTH STANDARD
To justify reduced duration of attainment monitoring at the point of compliance.
To complete the equivalency demonstration for soil-to-groundwater attainment.
To predict the extent of contamination above the standard in off-property nonuse
aquifers.
To demonstrate attainment of the used aquifer standard at a point 1,000 feet
downgradient from the point of compliance (POC) for the nonuse aquifer standard.
To demonstrate compliance with surface water standards where there is diffuse
groundwater flow to surface water.
SITE-SPECIFIC STANDARD
To identify current completed pathways and related exposures.
To predict future completed pathways and related exposures.
To demonstrate pathway elimination.
To establish numerical site-specific risk-based standards.
To demonstrate compliance with surface water standards where there is diffuse
groundwater flow to surface water.
When applicable, the fate and transport analysis should also consider the degradation of a
particular chemical compound(s) into one or several “breakdown” compounds. This can occur in
the unsaturated or saturated zone at or below the point of release of a particular compound of
concern, or downgradient in the chemical plume. An example may include a scenario involving
a release of trichloroethylene from an upgradient source which has entered the saturated zone
and migrated downgradient under a site seeking a release under the background standard. The
site in question may exhibit dichloroethylene and vinyl chloride in wells on its property, but it
also may have never used chlorinated compounds. In this case, the remediator may be able to
demonstrate that there was no release of the regulated substance on the property and use fate and
transport analysis to demonstrate that the constituents result from breakdown of compounds from
the upgradient release.

261-0300-101 / DRAFT December 16, 2017 / Page III-3
1.
Fate and Transport Analysis in the Unsaturated Zone
a)
General
In lieu of using the soil-to-groundwater medium-specific concentrations (MSCs)
from Tables 3 and4 in Appendix A of Chapter 250 as the Statewide health
standards (SHS), a person may also perform a site-specific demonstration. The
site-specific demonstration can be used to show that contaminant levels in soil
exceeding the SHS for one or more contaminants at that site are protective of
groundwater. Such a demonstration requires the use of fate and transport models,
equations, algorithms, or methods (hereafter “analytical tools”) applied to
contaminants in the soil of the unsaturated zone and may also include the use of
groundwater fate and transport analytical tools (e.g., using the results of an
unsaturated zone transport demonstration as input into a groundwater fate and
transport analysis).
The unsaturated zone fate and transport analytical tools may be very simple
equations requiring minimal input or may be more complex models requiring
much more detailed input. The choice of the analytical tool or tools used in
making site-specific demonstrations for contaminants in unsaturated zone soil
should be appropriate to the circumstances of the site. At a minimum, the
analytical tools used in making demonstrations in the unsaturated zone should
include certain contaminant-specific and site-specific parameters. Other
parameters may also be necessary depending on the analytical tools being used
and the overall goal of the demonstration. In addition, the analytical tools and
parameter input values themselves are subject to certain conditions.
b)
Minimum Contaminant-Specific and Site-Specific Requirements
With very few exceptions, the analytical tools currently available for unsaturated
zone contaminant fate and transport demonstrations are based on equilibrium
partitioning equations. The equations that have been used in estimating the soil-
to-groundwater MSCs and the soil buffer distances in Tables 3 and 4 in
Appendix A of the regulations are equilibrium partitioning equations. These
equations can be used in a variety of different types of analytical tools.
Depending on the analytical tool being used, other parameter input values may be
necessary. At a minimum, input values are needed for each of the following
parameters for any unsaturated zone analytical tool:
i)
Contaminant-Specific Requirements for All Analytical Tools
K
oc
in L/kg or mL/g (for organic compounds only): this is the
organic carbon partition coefficient. Values for this parameter for
listed organic regulated substances can be found in Table 5A in
Appendix A of the regulations or in scientific literature. For
organic compounds not listed in Appendix A of the regulations,
values can be found in literature. K
oc
estimation methods (based
on other parameters such as aqueous solubility, octanol-water

261-0300-101 / DRAFT December 16, 2017 / Page III-4
partition coefficient, bioconcentration factor, and molecular
structure) are also available in literature.
K
d
in L/kg or mL/g (primarily for inorganic contaminants and, in
some instances, organic compounds): this is the soil-to-water
partition coefficient. Values for this parameter for listed inorganic
regulated substances can be found in Table 5B in Appendix A of
Chapter 250. Some K
d
values for inorganic contaminants can also
be found in scientific literature. In many instances, it may be
necessary to estimate K
d
values based on soil analytical data at a
particular site. This can be done by using total contaminant
concentrations in soil in conjunction with leachable concentrations.
Generally, the K
d
values for organic compounds are estimated
from K
oc
values and the fraction of organic carbon in soil (f
oc
-
which is discussed later) or by using total contaminant
concentrations in soil in conjunction with leachable concentrations.
If K
d
values are estimated in this manner, it is not necessary to
include or use a K
oc
value for the organic compound.
C
soil
in mg/kg: This is the dry weight concentration of a regulated
substance or contaminant in soil which is determined through use
of the site characterization data (if the demonstration is being done
to show that groundwater is protected under current site
conditions) or which is used as input (on a trial-and-error basis) to
estimate a concentration in soil that would be protective of
groundwater.
ii)
Site-Specific Requirements for All Analytical Tools
?
w
(dimensionless): This is the water-filled porosity of the
unsaturated zone soil. Appropriate values for this parameter
generally range from 0.05 to 0.15 for sandy soils to 0.26 to 0.45 for
clays. A default value of 0.2 has been used in the estimation of the
soil to groundwater MSCs in Tables 3 and 4 in Appendix A of the
Chapter 250 regulations.
b
in kg/L or g/mL: This is dry bulk density of unsaturated zone
soil. Appropriate values for this parameter generally range from
1.3 to 2.0 for silts and clays to 1.6 to 2.2 for sandy soils to 1.8 to
2.3 for gravelly soils. A default value of 1.8 has been used in the
estimation of the soil to groundwater MSCs in Tables 3 and 4 in
Appendix A of the regulations.
f
oc
(dimensionless): This is the fraction of organic carbon in
unsaturated zone soil. This parameter applies only to
demonstrations being done for organic compounds where the K
oc
values for the compounds are being used. For demonstrations for
organic compounds where K
d
is being estimated or determined by
a means other than use of K
oc
, this parameter is not needed.

261-0300-101 / DRAFT December 16, 2017 / Page III-5
Typical values for this parameter range from 0.001 to 0.006 for
subsurface soils to 0.01 to 0.03 for topsoil. A default value of
0.0025 has been used in the estimation of the soil to groundwater
MSCs in Table 3b in Appendix A of the regulations. A value of
0.005 has been used in estimation of the soil to groundwater buffer
distances in Table 3B in Appendix A of the regulations.
iii)
Additional Requirements
The simplest unsaturated zone analytical tools are those that estimate
contaminant concentrations in unsaturated zone soil pore water from
equilibrium partitioning equations and utilize these aqueous
concentrations as source input into a groundwater fate and transport
analysis. Actual transport through the unsaturated zone is not estimated
with this type of analytical tool. This type of unsaturated zone analytical
tool would require input data for only those parameters discussed above.
Another type of unsaturated zone analytical tool that is commonly used
and is more complex is one that estimates the migration of contaminants
through the unsaturated zone. These are generally either infinite source or
finite source analytical tools. Both are more complicated than the one
previously discussed and, as such, require additional parameter input
values. Both of these analytical tools require the vertical depth to
groundwater or bedrock from the contaminated soil as well as a water
recharge rate so that pore water velocity can be estimated. An unsaturated
zone finite source analytical tool is particularly useful in demonstrating
how long it will take a contaminant to migrate from unsaturated zone soils
to groundwater (if at all) and what the contaminant concentration
(including the maximum concentration) will be in soil or soil pore water at
various depths and at various times as migration occurs. Finite source
models generally require input values for additional parameters such as
values for C
soil
at different depths from the surface of the unsaturated zone.
This can ensure that mass balance constraints are met, i.e., the analytical
tool will not estimate migration of a greater mass of contaminant than the
amount that was originally in the source soil. The
BUFFER1.XLS
spreadsheet model is available on the DEP website to assist in performing
this modeling.
In addition, more complex unsaturated zone analytical tools can take into
account other mechanisms that would affect the vertical migration of
contaminants toward groundwater. These mechanisms are generally ones
that result in loss of the contaminant through time, meaning that additional
input values are required. Two loss mechanisms are biodegradation and
volatilization. Analytical tools that consider biodegradation require either
a degradation rate constant (in units of reciprocal time) or a half-life value
(in units of time). In rare circumstances, an analytical tool may consider
loss from volatilization. This would require a volatilization rate constant
which can be calculated from several other parameters (such as Henry’s

261-0300-101 / DRAFT December 16, 2017 / Page III-6
constant, vapor pressure, aqueous solubility, other partition coefficients as
well as soil property data) or can be estimated using onsite analytical data.
c)
Conditions for Use of Analytical Tools and Parameter Input Values
Dozens of unsaturated zone analytical tools exist in the public domain, most of
which are based on equilibrium partitioning between the solid soil matrix and the
soil pore water. As such, most of these analytical tools are very similar with
respect to the parameters that require input values. In order to ensure validity of
the results of all unsaturated zone demonstrations submitted to the Department,
the following conditions should be met:
Analytical tools used for unsaturated zone transport demonstrations should
be based on equilibrium partitioning concepts when possible. Although
analytical tools based on other concepts (such as metal speciation and
non-equilibrium desorption) exist and may be technically valid, their use
could cause significant delays in Department review time.
The source of all values for all required input parameters (K
oc
, K
d
, C
soil
,
?
w
,
b
, f
oc
) should be provided. All data used as input for C
soil
should be
representative of the area for which the demonstration is being made and
should meet all site characterization requirements.
If analytical tools require input values for water recharge rate and vertical
depth to groundwater, the sources of those values should be provided.
Any degradation rate constant or half-life used in any unsaturated zone
analytical tool should be based on site-specific data. Well-documented
degradation constants and half-life values may be used from the literature
or other studies only when it can be shown that the conditions at the site
are clearly similar to those from which the degradation rate constant or
half-life came. In addition, degradation products which may be toxic
(such as those from chlorinated alkenes) should be considered in the
demonstration. If these conditions are not met, the degradation rate
constant should be assumed to be zero.
Any unsaturated zone analytical tool that incorporates loss of contaminant
from volatilization processes should base the volatilization rate constant
on volatilization data for soils existing at the site. Otherwise, loss due to
volatilization should be assumed to be zero.
Any unsaturated zone analytical tool should be used only for soils in the
unsaturated zone and should not be used for saturated zone soils or
bedrock.
For any unsaturated zone analytical tool that links to groundwater by
means of dilution directly under the area of contaminated soil, the entire
aquifer depth directly under the soil should not be used in dilution
calculations, i.e., as a mixing zone. The mixing zone should be calculated

261-0300-101 / DRAFT December 16, 2017 / Page III-7
based on specific site parameters such as pore water velocity, groundwater
velocity and direction, depth of the entire aquifer under the site, and areal
extent of soil contamination.
d)
Conclusion
This guidance is being provided to aid any person who is submitting results of a
fate and transport analysis for the unsaturated zone to do so in a manner that will
ensure validity of the analysis as well as timely and efficient review by the
Department. There are many unsaturated zone analytical tools available in the
public and private domains. Some of these are extremely complex, difficult to
use, and not readily available to Department staff while others are fairly simple,
easy to use, and are readily available to the Department. For unsaturated zone
fate and transport analysis submissions that rely on concepts other than
equilibrium partitioning (such as metal speciation and non-equilibrium
desorption), adequate supporting documentation must be submitted to the
Department.
2.
Fate and Transport Analysis in the Saturated Zone
This section provides guidelines for the application of fate and transport analysis in the
saturated zone. As stated above, a “fate and transport analysis” is not necessarily a
highly complex computer simulation. It can be a range of analyses, based on physical,
structural, chemical and hydraulic factors. It is based on professional judgment and may
need to include the use of simulations.
Elements of fate and transport analysis include:
GROUNDWATER FLOW
Direction
Velocity
Boundaries
CHEMICAL FATE AND TRANSPORT MECHANISIMS
Leaching/dissolving
Adsorption/desorption
Matrix diffusion
Degradation/transformations/reactions
Volatilization
Precipitation

261-0300-101 / DRAFT December 16, 2017 / Page III-8
Phase behavior
Depending on the characteristics of the site and the type of standard/remediation selected,
the fate and transport analysis can range from the simple to the complex, which can span
from qualitative “empirical” or simple conceptual models, up to quantitative simulation
(analytical and numerical) models.
Simple descriptive or conceptual models may be either qualitative or quantitative. A
particular example under this scenario might be a facility seeking a release of liability
under the background standard. This facility (facility “A”) is downgradient from
facility “B,” which has caused a release of a contaminant to groundwater. The fate and
transport analysis required under § 250.204(f)(5) could conceivably be a simple
qualitative demonstration of a conceptual site model which employs the use of
monitoring well data/measurements to clearly establish that facility “A” is hydraulically
downgradient of facility “B.” Data requirements would include water level
measurements from a sufficient number of properly located monitoring wells and
establishing the hydraulic gradient. Note, however, that simple scenarios such as this can
easily become more complicated by other factors including water level fluctuations,
pumping influences of wells, etc., which could require a more detailed quantitative fate
and transport analysis.
Another scenario could involve the use of simple extrapolation in predicting groundwater
plume movement or its relative stability over time. If groundwater monitoring samples
have been collected over a sufficiently long period of time, and the information consists
of reliable data, then certain predictions can be made using professional judgment as to
aspects of plume behavior. For example, monitoring over a number of years may
indicate that the contaminant plume has exhibited no movement over that time. In this
case, the use of professional judgment involving simple extrapolation of the data may be
a sufficient fate and transport analysis. The conclusion could be made, based on the
above merits, that the plume has reached a steady-state condition and would not migrate
further downgradient. In this case it may also be possible to determine that downgradient
surface water quality criteria may be met even though the concentrations in the
groundwater plume exceed the MSCs.
Quantitative fate and transport analysis may be needed in more complex situations, where
a demonstration of attainment would require additional data and calculations.
One example might be a facility seeking to demonstrate that very low groundwater
velocities in bedrock would preclude contaminated groundwater from the facility from
reaching the property boundary/POC. Data requirements in this case would need to
include calculation of hydraulic gradient, determination of hydraulic conductivity,
estimation/measurement of effective porosity, and calculation of groundwater velocity.
Note that this somewhat simple example could evolve into a more detailed quantitative or
simulated model given a variety of complicating factors, such as saturated flow in soil,
preferential fracture flow, etc. Another example of this type may be a demonstration of
groundwater discharge into a natural flow boundary, as in the case of a facility located
adjacent to a large river sustained by regional groundwater discharge. While in some
cases this might be a qualitative analysis, in other cases there would be a need to

261-0300-101 / DRAFT December 16, 2017 / Page III-9
determine both vertical and horizontal gradients to demonstrate the stream is in fact a
discharge feature and not losing flow to the surrounding terrain.
Quantitative analysis may involve the use of more complicated fate and transport tools
involving various analytical equations up to the more complex numerical simulations of
groundwater flow, which collectively can help determine the spread of contamination in a
plume and predict its fate and concentration at specific future times and locations. The
simpler analytical equations are more appropriate where more uniform aquifer conditions
exist and there are no complex boundary conditions. An example might be a facility
seeking a release under Act 2 which is underlain by alluvium near a stream. Analytical
fate and transport equations can be used to help determine the concentration of a
groundwater contaminant at a downgradient location. In many cases the simple empirical
examples mentioned above may need to employ analytical equations, as conditions
warrant, to account for dilution, attenuation, degradation, and other physical and
chemical factors in contaminant fate and transport.
Numerical simulations are the most complex models used under the provisions of fate
and transport analysis under Act 2. They generally require use of a computer software
model due to the number of simultaneous equations to be solved. They are most
applicable where predictions of groundwater contamination need to be made at certain
locations in the future (e.g., property boundary, 1,000 feet downgradient from property
boundary, etc.), at sites which exhibit more heterogeneous geologic/hydrogeologic
characteristics and more complex boundary conditions (which are common in
Pennsylvania). As such, they will be useful tools for a variety of sites where such
predictions are required to demonstrate attainment of an Act 2 standard.
a)
Groundwater Solute Fate and Transport Modeling (General)
The Department recommends that those with appropriate academic training and
practical experience in the field conduct fate and transport analysis, especially if it
involves more complex numerical models.
Except in cases where it is unnecessary to project or predict contaminant
concentrations in groundwater at various locations into the future, some sort of
quantitative fate and transport analysis such as groundwater modeling will very
likely be needed.
Some considerations:
?
All models rely on input parameters that vary because of inherent
heterogeneity and anisotropy of the aquifer.
?
Some of the required input parameters such as dispersivity are not
measured and need to be determined by model calibration to accurate
isoconcentration contour maps.
?
Some important information such as the date of the release and mass
involved is often difficult to pin down.

261-0300-101 / DRAFT December 16, 2017 / Page III-10
All of the above creates uncertainty that needs to be considered in how the results
of any model are used and their reliability. The uncertainty associated with
models can and should be reduced by collecting site-specific data for certain input
parameters that are representative of subsurface conditions.
Accurate isoconcentration contour maps of each parameter of concern, which are
constructed from data collected during the site characterization phase of the
remedial action, are especially important. These maps are the calibration targets
of the model. Adequate data to determine if a plume exhibits a centerline, and, if
so, its location and associated concentrations is fundamental to a fate and
transport analysis. It is good practice to install several transects (lines of wells)
downgradient from the source and perpendicular to the direction of groundwater
flow to accurately find and define any plume centerline and the spread of
contamination away from the centerline.
The following data are the minimum input requirements of many models, both
analytical and numerical. The following data should be derived from
measurements made at the site:
Source Geometry and Concentration
Hydraulic conductivity
Hydraulic gradient
Natural fraction of organic carbon in the aquifer
Porosity
The following additional parameters are also often involved:
Time source active – this is a very important parameter in calibrating any
model if transient plume conditions are suspected or involved, and can be
one of the hardest to pin down unless good historical records are available.
K
oc
– this value can be obtained from Appendix A-Table 5A of
Chapter 250.
Lambda – this measure of biodegradation (as first order decay) varies
from site to site for each compound and is usually determined by model
calibration, or sometimes calculated from plume centerline data.
Published values such those in Appendix A, Table 5A of Chapter 250
should not be relied on as default values for site-specific modeling.
Soil Bulk Density – often estimated as (2.65 g/cm
3
)(1-porosity).
Dispersion – this parameter is used to simulate the spread of contaminants
in one, two or three dimensions. Values are often initially derived using

261-0300-101 / DRAFT December 16, 2017 / Page III-11
several published “rules of thumb” and then adjusted during model
calibration to fit plume isoconcentration contours.
After selection of the best values for input parameters, the model is run and
compared to the plume geometry portrayed by isoconcentration maps of each
parameter of concern. Adjustments may be needed for certain parameters such as
lambda, dispersion or others within reasonable ranges to obtain a better match to
site data. Measured site data should be utilized in conjunction with initial
modeling results to further calibrate the model using to ensure the most accurate
predictive results. Modeling efforts associated with a postremediation care plan
under an Act 2 standard should include a test of the predictive accuracy of the
model by comparing predictions to a future data set sometimes referred to as a
“post-audit,” followed by recalibration and retesting, if needed.
Readers are referred to ASTM Standard Guide D 5447-04 (2010) for an overview
of the basic elements involved in groundwater flow modeling effort. The same
general principles apply to fate and transport modeling. Since the ASTM
Standard Guide 5447-04 (2010) is intended as a general guide, covering both
analytical and numerical models, all elements discussed may not be applicable to
every modeling situation.
b)
Define Study Objectives
In all cases the site characterization should be conducted with the objective of
providing the data necessary to demonstrate attainment of an Act 2 standard.
Prior to any computer modeling, an initial conceptual model of local
hydrogeologic conditions should be developed. The results of the
characterization/initial conceptual site model will influence what kind of fate and
transport model, if any, should be used, as well as many of the values for the input
parameters to that model. Some models require certain kinds or quantities of data
which is good to know ahead of time. To some extent this will be an iterative
process. As data are collected and evaluated, the selected Act 2 remediation
standard may change, and areas where additional data are needed may be
identified.
The acceptable tolerances for model calibration should also be defined in the
study objectives.
c)
Data Collection
The data used for groundwater fate and transport modeling will come from the
site characterization, attainment monitoring, and in some cases, values published
in scientific literature or Table 5 in Appendix A to the regulations. Examples of
data that may need to be obtained from published values include first-order decay
coefficients and equilibrium partitioning coefficients. Once obtained, these
values may need to be adjusted within reasonable ranges to calibrate a model to
site conditions. Examples of data which should be obtained from the site
characterization, to name a few, include hydraulic conductivity, gradients,
porosity, organic carbon content and chemical concentrations. Some parameters

261-0300-101 / DRAFT December 16, 2017 / Page III-12
such as dispersion coefficients, which are not available from the literature or site
characterization work, initially need to be estimated according to basic
assumptions and then adjusted during model calibration to match actual plume
shape and concentration data.
d)
Conceptual Model
As stated in ASTM D 5447, “the purpose of the conceptual model is to
consolidate site and regional hydrogeologic and hydrologic data into a set of
assumptions and concepts that can be evaluated quantitatively.” The conceptual
model of the site will emerge from the data collected during the site
characterization. The site characterization work should be designed to assure that
the quantity and kind of data collected will, in the end, be sufficient for justifying
and completing the fate and transport analysis. Elements important to developing
the conceptual model of the site for any fate and transport analysis include
geologic, hydrologic, hydraulic and contaminant data (note that these are common
elements of some of the non-numerical conceptual models discussed above).
Data collection should be concentrated on the site, but offsite features that
influence contaminant fate and transport on the site should not be overlooked.
i)
Geologic Data
Thickness, continuity, lithology and structural features of
consolidated geologic formations underlying the site.
Thickness, texture, density and organic carbon content of soil and
unconsolidated units.
Information from review of published reports on the geology and
soils of the site and nearby areas, or previous work at the site.
Information from any additional investigation needed to confirm or
refine existing data such as wells, borings and backhoe pits, and
possibly geophysical methods.
ii)
Hydrologic Data
Water levels, hydraulic gradients and groundwater flow directions,
including seasonal variations; determining seasonal variations in
hydrologic data are extremely important for conceptual site model
development. Seasonal variations in hydrologic data are site
dependent and may not exist at every Act 2 site. Conceptual site
model development as well as fate and transport analysis should
take into account any seasonal variations that may exist at an Act 2
site.
The presence and magnitude of vertical gradients at the site.

261-0300-101 / DRAFT December 16, 2017 / Page III-13
Recharge and discharge boundaries relevant to the site including
groundwater divides, streams, and drains.
Sources and sinks, e.g., characteristics of any pumping or injection
wells, artificial recharge, ponds, etc.
The presence of any confining units.
For bedrock aquifers, the degree to which the aquifer system
departs from assumptions regarding flow in porous media.
Data from review of available information as well as drilling of
wells, borings and piezometers, and water level measurements over
regular intervals.
iii)
Hydraulic Data
Hydraulic conductivity and transmissivity data for consolidated
and unconsolidated deposits.
Porosity, effective porosity estimates, and storativity.
The degree to which the aquifer(s) depart from assumptions of
isotropy or homogeneity.
The degree of interconnection between different aquifer units and
leakage characteristics between different water-bearing units.
Hydraulic data often is not available at the level of detail necessary
and may require pumping tests on wells to determine aquifer
anisotropy of bedrock systems and values for other hydraulic
parameters such as transmissivity. Slug tests may suffice in
bedrock wells where anisotropy is not a factor requiring
consideration.
iv)
Chemical and Contaminant Data
Location, age and current status of source areas to the extent
knowable.
Types of contaminants and their chemical properties such as
viscosity, solubility, biodegradability, density, toxicity, K
oc
value,
decay rate, etc.
The magnitude and vertical and horizontal extent of contamination
in soil and/or groundwater.

261-0300-101 / DRAFT December 16, 2017 / Page III-14
Dissolved oxygen content and other electron acceptors in
groundwater, if required by the model.
Historical plume configuration based on existing monitoring data.
Determination if the contaminant plume is at steady-state
conditions or is continuing to migrate. This is a critical piece of
information. Is the mass of contamination increasing, decreasing
or relatively constant? This should be determined by monitoring
the vertical and horizontal extent of groundwater contamination for
a period of time sufficient to reveal the trend. These data will be
useful in calibrating the model and making predictive simulations.
In some cases, the monitoring data alone may be all that is needed
to complete the fate and transport analysis, provided the
monitoring record is sufficiently long.
Review of chemicals used at the facility, which will help identify
the chemicals of concern. Sampling soil, soil vapors and
groundwater from appropriately constructed monitoring wells,
borings or excavations and checking for any free product will need
to be performed. Geophysical methods may be useful to delineate
areas needing further investigation or identifying sources.
e)
Model Selection
When the site characterization is completed and the conceptual model has been
developed, selection of an appropriate model can be made. At sites where there is
little variation in conditions over the model domain, with a simple plume
geometry or conceptual model, relatively simple analytical models should be
employed. At sites where the site characterization has determined significant
variation in important parameters, or where more complex questions are being
asked, a more sophisticated numerical solution may be needed.
The Department has prepared two spreadsheets that may be useful in completing a
fate and transport analysis. All spreadsheets are based on the following equation:
?
     
??
?
?
?
?
erf
??
y Y
     
x
?
erf
??
y Y
     
x
??
erf
??
z Z
   
x
?
erf
??
z Z
     
x
?
erfcx vt
v
vt
v
x
C
Cxyzt
y
y
z
z
x
x
x
x
o
?
?
?
?
??
??
?
?
/2/2
/2/2
/22
/2/2
14
/2
114
2
) exp
8
(,,,)
(
/
2
1
?
?
?
?
?
?
?
?
?
?
?
Reference: An Analytical Model for Multidimensional Transport of a Decaying
Contaminant Species, P.A. Domenico, 1987, Journal of Hydrology, 91, 49-58.

261-0300-101 / DRAFT December 16, 2017 / Page III-15
The two spreadsheets are:
QUICK_DOMENICO.XLS
The Quick Domenico (QD) application spreadsheet calculates the concentration
anywhere in a plume of contamination at any time after a continuous, finite source
becomes active. A “User’s Manual for the Quick Domenico Groundwater Fate-
and-Transport Model” accompanies the spreadsheet model on the PA DEP
website.
SWLOAD.XLS
This spreadsheet uses a rearrangement of the Domenico equation to calculate
concentrations at different points in the cross section of a plume at any distance
from a continuous finite source at any time. The concentrations are then added
and multiplied by the groundwater flux and can be used to estimate the mass
loading of a particular contaminant from diffuse groundwater flow to a stream or
surface water body.
As mentioned above, these spreadsheets and documentation can be downloaded
from the PA DEP web site under “Standards, Guidance and Procedures,”
“Guidance and Technical Tools,” “Fate and Transport Analysis Tools.” These
spreadsheets will not be applicable to every situation involving modeling. The
remediator should thoroughly review the help documents for the spreadsheet
programs to determine if the modeling spreadsheets are suitable for the situation.
f)
Calibration and Sensitivity
As stated in ASTM D 5447, calibration is the process of adjusting hydraulic
parameters, boundary conditions and initial conditions within reasonable ranges to
obtain a match between observed and simulated potentials, flow rates or other
calibration targets. In working with sites under Act 2, an obvious calibration
target is matching the model output to existing, and, if known, historical geometry
and concentration of plume contaminants. The Act 2 final report should include a
discussion of calibration targets, and an analysis and significance of residuals
(differences between modeled and actual contaminant concentrations).
Sensitivity analysis is an evaluation of which model parameters have the most
influence on model results. The parameters to which the model is most sensitive
should be identified. Those parameters which have the most influence on model
results are those which should be given the most attention in the data collection
phase.
g)
Predictive Simulations
Fate and transport models may be used in the Land Recycling Program (LRP) to
make predictions of future contaminant concentrations. Uses may include:

261-0300-101 / DRAFT December 16, 2017 / Page III-16
Predicting the maximum concentrations that will occur at downgradient
compliance points (usually property boundaries) for the SHS in the case of
both used and nonuse aquifers.
Predicting whether groundwater contamination above an MSC will extend
beyond 1,000 feet in the case of nonuse aquifers, and if it will be at or
below the MSC for groundwater in these areas within the next 30 years.
In cases where the fate and transport analysis indicates that a standard may
not be maintained at some time in the future, a postremediation care plan
will be needed.
If postremediation care is required, a “post-audit” of the fate and transport
model should be performed. In a post-audit, the fate and transport model’s
predictions are compared to continued monitoring data collected during
the postremediation care period to check the validity and accuracy of
previous model predictions. Monitoring wells for the post-audit must be
located at points where they would be sensitive to auditing the model.
This may not coincide with the property line compliance point if the
plume would not be expected to migrate to the compliance point by the
time of the post-audit.
Post-audits should be performed on the model during the attainment
monitoring phase (usually a minimum of two years) as a check on model
predictions.
h)
Fate and Transport Model Report
With the exception of those projects which do not require submission of a fate and
transport model, the following general report format should be used to the extent
applicable to adequately document the modeling effort:
1.0
Introduction
1.1
General Setting
1.2
Study Objectives - which Act 2 standard is being demonstrated and
what is the purpose of the modeling
2.0
Conceptual Model
2.1
Aquifer System Framework
2.2
Groundwater Flow Model
2.3
Hydrologic Boundaries
2.4
Hydraulic Boundaries

261-0300-101 / DRAFT December 16, 2017 / Page III-17
2.5
Sources and Sinks
3.0
Analytical Model
3.1
Model Selection - justification for use of analytical, numerical or
other analysis
3.2
Model Description - name and version of analysis, model
assumptions and limitations, name of organization or person which
has developed the analysis
4.0
Groundwater Flow Model Construction
4.1
Model Grid - state if fixed by model
4.2
Hydraulic Parameters - state source such as field determined or
literature. Cite relevant section of Site Characterization report or
literature reference.
4.3
Boundary Conditions - state if fixed by model
4.4
Selection of Calibration Targets
5.0
Calibration
5.1
Residual Analysis
5.2
Sensitivity Analysis
5.3
Model Verification, if applicable
6.0
Predictive Simulations - Indicate relation to applicable Act 2 standard
7.0
Summary and Conclusions
7.1
Model Assumptions/Limitations
7.2
Model Predictions
7.3
Recommendations - including planned post-audit activities during
postremediation care plan if required
8.0
Figures and Tables
8.1
Model grid or axes oriented on the site map
8.2
Input and output files

261-0300-101 / DRAFT December 16, 2017 / Page III-18
3.
Impacts to Surface Water from Diffuse Flow of Contaminated Groundwater
Sections 250.309 and 250.406 of the regulations provide for determining compliance
with surface water quality standards from a diffuse surface or groundwater discharge.
The following types of sites that are impacted by diffuse flow of a dissolved groundwater
plume into a stream need to be analyzed incorporating the methods and models of DEP’s
Bureau of Clean Water:
Some sites selecting the SHS for used aquifers with a total dissolved solids (TDS)
concentration of 2,500 mg/L or less;
All sites selecting the Statewide health nonuse aquifer groundwater standard;
All sites selecting the SHS for used aquifers with a TDS greater than 2,500 mg/L;
and
All sites selecting the site-specific standard for groundwater.
All discharges involved with a remediation should be in compliance with the provisions
of Chapter 93 to demonstrate attainment of the Statewide health and site-specific
standards. This includes all applicable antidegradation requirements as outlined by
Chapter 93.4(a) including the protection of exceptional value and high quality waters.
Any discharges to surface water should likewise be in compliance with the provisions
summarized in Chapter 93.6 (no presence of floating materials and sheens) in addition to
dissolved plumes.
a)
Conceptual Framework
In order to understand how to evaluate the impact of diffuse groundwater plumes
on surface water quality, several important concepts must be understood. These
concepts apply to evaluating impacts of groundwater plumes on surface water
regardless of the standard selected.
The first is the concept of “maximum average concentration.” Surface water
impacts must be evaluated for the time that the “maximum average concentration”
in the groundwater plume is discharging into the stream. As a plume in
groundwater begins to encroach onto a stream, the average concentration entering
the stream will rise, and remain steady, or then fall depending on the nature of the
source (continuous or pulse). For a constant source with a decaying contaminant,
the maximum average concentration to the stream occurs when the plume has
reached a steady-state condition. For a constant source and non-decaying
contaminant, the maximum average concentration to the stream occurs when the
mass discharging into the stream equals the mass emanating from the source. For
a pulse or slug source, the maximum average concentration will occur at the time
the peak concentrations in the pulse (or slug) pass into the stream. The
Department has prepared a spreadsheet, SWLOAD5 (SWL5), which will
calculate the “maximum average concentration” for decaying and non-decaying
plumes emanating from a constant source.

261-0300-101 / DRAFT December 16, 2017 / Page III-19
A second concept to understand concerns what is termed the plume “edge
criterion.” The “edge criterion” is the concentration equal or above which the
maximum average concentration and associated flow will be determined for the
plume in question. This is needed to assure that concentrations below the
criterion will not be used and serve to dilute the average concentration and/or
increase the flow in the plume to a point where any and all discharges to surface
water become acceptable. The “edge criterion” is contaminant specific. The
following rules should be used in establishing the “edge criterion.” These rules
apply to selection of the “edge criterion” regardless of the standard selected:
For those compounds on Table III-1 of the technical guidance manual
(TGM) which have established surface water criteria, further surface water
compliance evaluation is not necessary. Demonstrating that the MSC is
met at the POC or groundwater/surface water interface is sufficient to
address surface water concerns.
For all other compounds, further surface water compliance evaluation is
necessary.
Maximum average concentrations and flow for input into Pennsylvania’s
PENTOXSD surface water mixing model should only be calculated for portions
of a groundwater plume that exceed the “edge criterion” for the compound being
evaluated. The Department has prepared a spreadsheet, SWL5, which
incorporates the “edge criterion” for calculating inputs to PENTOXSD for
decaying and non-decaying plumes emanating from a constant source. If no
portion of a plume entering a stream at the time of maximum average
concentration exceeds the “edge criterion,” no further demonstration of surface
water attainment is needed.
A third concept to understand is that of “maximum modeled or measured
concentration.” It is important to understand that the maximum concentration
being referred to by this phrase is the maximum concentration in the plume at the
time and place that the maximum average concentration is discharging into the
stream. Therefore, a measured concentration is inappropriate, and a modeled
concentration should be used in cases where:
The plume has not yet reached the stream;
The plume is entering the stream, but has not yet reached its maximum
average concentration; or
The number and/or location of wells is insufficient to assure the
Department that the maximum concentration has been found.
A fourth concept to understand is where the concentrations should be measured
with respect to the Act 2 property line POC. If a plume discharges off the
property being remediated before discharging into a stream, then the criteria for
waiving a PENTOXSD analysis can be measured at the POC. If the plume
discharges into a stream before leaving the property, criteria must be

261-0300-101 / DRAFT December 16, 2017 / Page III-20
demonstrated along the groundwater/surface water interface where the plume is
discharging.
The spreadsheet SWL5 is constructed so that the “maximum modeled
concentration” is compared to the “edge criterion” for each compound and a
determination is automatically made if a PENTOXSD analysis is needed. By
convention, the “edge criterion” in SWL5 is defined as the threshold for waiving a
PENTOXSD analysis.
Two final comments need to be made regarding the demonstration of surface
water quality attainment. First, worst-case source concentration and flow
associated with the source can be input directly into PENTOXSD. Doing this will
avoid groundwater modeling or measuring concentrations at the POC or
groundwater/surface water interface in many situations.
Secondly, anytime it can be demonstrated conclusively that the maximum
concentration in a plume is less than the lowest surface water quality criteria,
attainment of surface water quality can be assumed. Surface water quality criteria
for specific compounds may be found in Tables 3 and 5 in 25 Pa. Code
Chapter 93, Surface Water Quality Standards.
b)
Mathematical Framework
The basic mass balance equation to determine the concentration of a contaminant
in surface water downstream of a diffuse groundwater contaminant discharge at
design flow conditions with background contaminant levels included is:
C
sw
= (Q
gw
* C
gw
) + (Q
sw
* Y
c
* C
bsw
)
(Q
sw
* Y
c
) + Q
gw
where:
C
sw
= the concentration in surface water of a contaminant of concern
downstream of the nonpoint source discharge into the surface water.
Q
sw
= the quantity of stream flow above the nonpoint source discharge
into surface water.
Q
gw
= the quantity of flow in the groundwater plume discharging into the
surface water.
C
gw
= the maximum average concentration of a contaminant in the
groundwater discharging into surface water.
Y
c
= the partial mix factor (decimal per cent), derived from using the
PENTOXSD model.

261-0300-101 / DRAFT December 16, 2017 / Page III-21
C
bsw
= the background concentration in surface water of a contaminant of
concern above the nonpoint source discharge.
The equation for determining the allowable groundwater concentration in a plume
discharging to surface water is:
Y
c
* Q
sw
* (C
x
-C
bsw
)
C
gw
= C
x
+
Q
gw
where:
C
x
= the water quality objective (criteria value most of the time, can be
site–specific).
Other variables are as listed above at design flow conditions (e.g. Q
7-10
or
Q
hm
).
For surface water bodies exhibiting tidal effects (e.g. Delaware River
estuary) 1% of the Q
7-10
and Q
h
flows are acceptably conservative for
calculations of Q
sw
in estuaries.
c)
Application
The general procedure for applying the mathematical framework above to
applicable compounds requires estimating the flow and maximum average
concentration of the contaminated groundwater plume for each parameter of
concern at the groundwater/surface water boundary. These values, in turn, are the
discharge flow and discharge concentration values to be evaluated using the
Bureau of Clean Water’s PENTOXSD model to determine if the groundwater
discharge to the stream meets the applicable surface water quality criteria. Users
are referred to Technical Guide 391-2000-011 and PENTOXSD for Windows
(Version 2.0D) Supplemental Information for information on using the
PENTOXSD model.
The analysis will involve incorporating background concentrations in surface
water for certain contaminants. Users are referred to TGM 391-2000-022
(Implementation Guidance for the Determination and Use of
Background/Ambient Water Quality in the Determination of Wasteload
Allocations and NPDES Effluent Limitations for Toxic Substances) for
information on how and when to apply background water quality data.
For steady-state plumes which have compliance points at or very near a stream,
the groundwater flow and concentrations (mass load) within the plume can and
should be determined from direct measurements. The mass loading of
groundwater plumes which have not yet reached the stream boundary, which are
not at steady state at the stream boundary, or for which data at the stream
boundary are not available, must be estimated in some way (e.g. using
groundwater solute transport models, or by assuming, conservatively, that the

261-0300-101 / DRAFT December 16, 2017 / Page III-22
highest concentrations measured in the plume are representative of those at the
stream boundary).
The general guidelines and example problems presented below in this guidance
apply to single source discharge analysis. If there is more than one source of a
pollutant in a stream reach, it may be necessary to evaluate the cumulative impact
of these sources. The stream reach is determined by the site-specific travel times,
stream flow, discharge flow dilution and potency of the pollutant as it moves
downstream. The term that describes this process is “multiple source discharge.”
The Bureau of Clean Water recommends that the Equal Marginal Percent
Reduction (EMPR) method of allocation be used for these situations.
EMPR is a two-step process:
Baseline Analysis: this step evaluates each contributor individually to
determine if it would exceed the water quality objective by itself. This
step evaluates the contributor’s currently modeled load and compares it to
the water quality objective. If the modeled load is greater than the water
quality objective, the modeled load is reduced to the water quality
objective. A baseline value is determined for every contributor. This
baseline value is either the currently modeled load or the water quality
objective. This step assures that no contributor would cause an
exceedance of the water quality objective by itself.
Multiple Analysis: this step evaluates the cumulative impact of multiple
sources on the stream. The analysis is carried out by systematically
moving downstream, adding the baseline pollutant loads, and determining
if the water quality objective is met at all locations. Through this process
the critical reach of the stream can be found and any further necessary
reductions from the baseline values can be made to meet the water quality
objective at all points in the stream. Any further reductions from the
baseline are made on an equal percentage basis.
Further information regarding the EMPR process can be found in the Technical
Reference Guide for the Wasteload Allocation Program for Dissolved Oxygen
and Ammonia-Nitrogen on the Bureau of Clean Water web page.
d)
Statewide Health Standard in Aquifers with 2,500 mg/L TDS or Less
For certain compounds that have SHSs established in Chapter 250, simply
demonstrating attainment of the residential or nonresidential SHS MSC for
groundwater in used aquifers with TDS less than or equal to 2,500 mg/L at the
point of compliance, or at the groundwater/surface water interface when the
plume discharges to surface water prior to or instead of passing through the
property line POC, will satisfy the surface water criteria attainment
demonstration. This is because either the MSC is equal to or below the lowest
surface water quality criterion (LSWC) or the compound in question does not
have any corresponding surface water criteria at this time. These compounds are
listed in Table III-1.

261-0300-101 / DRAFT December 16, 2017 / Page III-23
For all other compounds, surface water compliance analysis is required to the
compound’s edge criterion. These are compounds where the MSC exceeds the
LSWC. In some cases, the LSWC may be much lower than the laboratory PQL.
In this case, please contact the Act 2 site project officer for further guidance.
Regardless of the standard selected, whenever the maximum concentration of a
regulated substance in groundwater discharging to a stream at the time of
maximum mass loading to the stream is quantified at a level lower than the
LSWC, further demonstration of compliance with surface water criteria is not
required.
It is also important to note that if the fate and transport modeling or actual in-
stream sampling show that surface water quality criteria are exceeded, the
remediator may be able to demonstrate that the site-specific standard can be
attained by addressing the applicable exposure pathways. This would result in a
waiver of the provisions of Chapter 93 Water Quality Standards as described in
§ 250.406(c)(2) of the regulations.
e)
Examples
i)
Example 1: Groundwater Source Very Near or Adjacent to Surface
Water Discharge
A site with an accumulation of gasoline as a separate phase liquid lies
immediately adjacent to a small stream. Separate phase liquid is being
collected by an interceptor/skimmer system that prevents its discharge to
the stream. However, a dissolved phase hydrocarbon plume with
maximum concentrations of certain compounds near their effective
solubility is entering the stream. The remediator has selected the site-
specific standard for these contaminants and must determine if surface
water criteria are met without any treatment or removal of the dissolved
phase plume. Because the groundwater concentrations exceeding the
lowest surface water quality criteria are entering the stream, a
PENTOXSD analysis is required.
Because the site is located very near the surface water discharge point, no
opportunity for dispersion or decay of the groundwater plume prior to its
discharge is expected. Data from the site characterization and attainment
monitoring wells is assumed here to allow an accurate estimate of the
quantity and concentration of the groundwater plume entering the stream,
without any need for fate and transport modeling of groundwater. The
following characteristics of the groundwater plume have been determined:
Plume (source) width: 100 feet
Plume depth: 10 feet

261-0300-101 / DRAFT December 16, 2017 / Page III-24
Table III-1
Compounds Excluded from Further Surface Water
Evaluation on Attainment of NR SHS for GW ≤ 2,500 TDS
SUBSTANCE
CAS
Number
ACENAPHTHYLENE
208-96-8
ACEPHATE
30560-19-1
ACETALDEHYDE
75-07-0
ACETONITRILE
75-05-8
ACETOPHENONE
98-86-2
ACETYLAMINOFLUORENE, 2-(2AAF)
53-96-3
ACROLEIN
107-02-8
ACRYLIC ACID
79-10-7
ALACHLOR
15972-60-8
ALDICARB
116-06-3
ALDICARB SULFONE
1646-88-4
ALDICARB SULFOXIDE
1646-87-3
ALLYL ALCOHOL
107-18-6
ALUMINUM
7429-90-5
AMETRYN
834-12-8
AMINOBIPHENYL, 4-
92-67-1
AMITROLE
61-82-5
AMMONIUM SULFAMATE
7773-06-0
ANILINE
62-53-3
ANTHRACENE
120-12-7
ARSENIC
7440-38-2
ASBESTOS
12001-29-5
ATRAZINE
1912-24-9
AZINPHOS-METHYL (GUTHION)
86-50-0
BARIUM AND COMPOUNDS
7440-39-3
BAYGON (PROPOXUR)
114-26-1
BENOMYL
17804-35-2
BENTAZON
25057-89-0
BENZO(G,H,I)PERYLENE
191-24-2
BENZOIC ACID
65-85-0
BENZOTRICHLORIDE
98-07-7
BENZYL ALCOHOL
100-51-6
BERYLLIUM
7440-41-7
BETA PROPIOLACTONE
57-57-8
BIPHENYL, 1,1-
92-52-4
BIS(2-CHLOROETHOXY)METHANE
111-91-1
BIS(2-CHLOROISOPROPYL)ETHER
108-60-1
BIS(CHLOROMETHYL)ETHER
542-88-1
BISPHENOL A
80-05-7

261-0300-101 / DRAFT December 16, 2017 / Page III-25
Table III-1
Compounds Excluded from Further Surface Water
Evaluation on Attainment of NR SHS for GW ≤ 2,500 TDS
SUBSTANCE
CAS
Number
BROMACIL
314-40-9
BROMOCHLOROMETHANE
74-97-5
BROMOMETHANE
74-83-9
BROMOXYNIL
1689-84-5
BROMOXYNIL OCTANOATE
1689-99-2
BUTADIENE, 1,3-
106-99-0
BUTYL ALCOHOL, N-
71-36-3
BUTYLATE
2008-41-5
BUTYLBENZENE, N-
104-51-8
BUTYLBENZENE, SEC-
135-98-8
BUTYLBENZENE, TERT-
98-06-6
CAPTAN
133-06-2
CARBARYL
63-25-2
CARBAZOLE
86-74-8
CARBOFURAN
1563-66-2
CARBON DISULFIDE
75-15-0
CARBOXIN
5234-68-4
CHLORAMBEN
133-90-4
CHLORIDE
7647-14-5
CHLORO-1, 1-DIFLUOROETHANE, 1-
75-68-3
CHLORO-1-PROPENE, 3- (ALLYL
CHLORIDE)
107-05-1
CHLOROACETALDEHYDE
107-20-0
CHLOROACETOPHENONE, 2-
532-27-4
CHLOROANILINE, P-
106-47-8
CHLOROBENZENE
108-90-7
CHLOROBENZILATE
510-15-6
CHLOROBUTANE, 1-
109-69-3
CHLORODIFLUOROMETHANE
75-45-6
CHLOROETHANE
75-00-3
CHLORONITROBENZENE, P-
100-00-5
CHLOROPHENOL, 2-
95-57-8
CHLOROPRENE
126-99-8
CHLOROPROPANE, 2-
75-29-6
CHLOROTHALONIL
1897-45-6
CHLOROTOLUENE, O-
95-49-8
CHLOROTOLUENE, P-
106-43-4
CHLORPYRIFOS
2921-88-2
CHLORSULFURON
64902-72-3

261-0300-101 / DRAFT December 16, 2017 / Page III-26
Table III-1
Compounds Excluded from Further Surface Water
Evaluation on Attainment of NR SHS for GW ≤ 2,500 TDS
SUBSTANCE
CAS
Number
CHLOROTHAL-DIMETHYL (DACTHAL)
(DCPA)
1861-32-1
CHROMIUM, TOTAL
7440-47-3
COPPER
7440-50-8
CRESOL, DINITRO-O-4,6-
534-52-1
CRESOL(S)
1319-77-3
CRESOL, O-(METHYLPHENOL, 2-)
95-48-7
CRESOL, M (METHYLPHENOL, 3-)
108-39-4
CROTONALDEHYDE
4170-30-3
CROTONALDEHYDE, TRANS-
123-73-9
CUMENE (ISOPROPYL BENZENE)
98-82-8
CYANAZINE
21725-46-2
CYCLOHEXANE
110-82-7
CYCLOHEXANONE
108-94-1
CYFLUTHRIN
68359-37-5
CYROMAZINE
66215-27-8
DI(2-ETHYLHEXYL)ADIPATE
103-23-1
DIALLATE
2303-16-4
DIAMINOTOLUENE, 2-4-
95-80-7
DIBENZOFURAN
132-64-9
DIBROMO-3-CHLOROPROPANE, 1,2-
96-12-8
DIBROMOBENZENE, 1,4-
106-37-6
DIBROMOETHANE, 1,2- (ETHYLENE
DIBROMIDE)
106-93-4
DIBROMOMETHANE
74-95-3
DICAMBA
1918-00-9
DICHLORO-2-BUTENE, 1,4-
764-41-0
DICHLORO-2-BUTENE, TRANS-1, 4-
110-57-6
DICHLOROACETIC ACID
79-43-6
DICHLOROBENZENE, P
106-46-7
DICHLORODIFLUOROMETHANE (FREON
12)
75-71-8
DICHLOROETHANE, 1,1-
75-34-3
DICHLOROETHYLENE, 1,1-
75-35-4
DICHLOROETHYLENE, TRANS-1,2-
156-60-5
DICHLOROPHENOL, 2,4-
120-83-2
DICHLOROPHENOXYACETIC ACID, 2,4-
(2,4-D)
94-75-7
DICHLOROPROPANE, 1,2-
78-87-5

261-0300-101 / DRAFT December 16, 2017 / Page III-27
Table III-1
Compounds Excluded from Further Surface Water
Evaluation on Attainment of NR SHS for GW ≤ 2,500 TDS
SUBSTANCE
CAS
Number
DICHLOROPROPIONIC ACID, 2,2-
(DALAPON)
75-99-0
DICHLORVOS
62-73-7
DICYCLOPENTADIENE
77-73-6
DIFLUBENZURON
35367-38-5
DIISOPROPYL METHYLPHOSPHONATE
1445-75-6
DIMETHOATE
60-51-5
DIMETHOXYBENZIDINE, 3,3-
119-90-4
DIMETHRIN
70-38-2
DIMETHYLAMINOAZOBENZENE, P-
60-11-7
DIMETHYLANILINE, N,N-
121-69-7
DIMETHYLBENZIDINE, 3,3-
119-93-7
DINITROBENZENE, 1,3-
99-65-0
DINOSEB
88-85-7
DIOXANE, 1,4-
123-91-1
DIPHENAMID
957-51-7
DIPHENYLAMINE
122-39-4
DIQUAT
85-00-7
DISULFOTON
298-04-4
DITHIANE, 1,4-
505-29-3
DIURON
330-54-1
ENDOSULFAN
115-29-7
ENDOSULFAN SULFATE
1031-07-8
ENDOTHALL
145-73-3
EPICHLOROHYDRIN
106-89-8
ETHEPHON
16672-87-0
ETHION
563-12-2
ETHOXYETHANOL, 2- (EGEE)
110-80-5
ETHYL ACETATE
141-78-6
ETHYL ACRYLATE
140-88-5
ETHYL DIPROPYLTHIOCARBAMATE, S-
(EPTC)
759-94-4
ETHYL ETHER
60-29-7
ETHYL METHACRYLATE
97-63-2
ETHYLENE CHLORHYDRIN
107-07-3
ETHYLENE GLYCOL
107-21-1
ETHYLENE THIOUREA (ETU)
96-45-7
ETHYLP-NITROPHENYL
PHENYLPHOSPHOROTHIOATE
2104-64-5

261-0300-101 / DRAFT December 16, 2017 / Page III-28
Table III-1
Compounds Excluded from Further Surface Water
Evaluation on Attainment of NR SHS for GW ≤ 2,500 TDS
SUBSTANCE
CAS
Number
FENAMIPHOS
22224-92-6
FENVALERATE (PYDRIN)
51630-58-1
FLUOMETURON
2164-17-2
FLUORIDE
16984-48-8
FLUOROTRICHLOROMETHANE (FREON
11)
75-69-4
FONOFOS
944-22-9
FORMIC ACID
64-18-6
FOSETYL-AL
39148-24-8
FURAN
110-00-9
FURFURAL
98-01-1
GLYPHOSATE
1071-83-6
HEXACHLOROETHANE
67-72-1
HEXANE
110-54-3
HEXAZINONE
51235-04-2
HEXYTHIAZOX (SAVEY)
78587-05-0
HMX
2691-41-0
HYDRAZINE/HYDRAZINE SULFATE
302-01-2
HYDROQUINONE
123-31-9
IPRODIONE
36734-19-7
IRON
7439-89-6
ISOBUTYL ALCOHOL
78-83-1
ISOPROPYL METHYLPHOSPHONATE
1832-54-8
KEPONE
143-50-0
LITHIUM
7439-93-2
MALATHION
121-75-5
MALEIC HYDRAZIDE
123-33-1
MANEB
12427-38-2
MANGANESE
7439-96-5
MERPHOS OXIDE
78-48-8
METHACRYLONITRILE
126-98-7
METHAMIDOPHOS
10265-92-6
METHANOL
67-56-1
METHOMYL
16752-77-5
METHOXYCHLOR
72-43-5
METHOXYETHANOL, 2-
109-86-4
METHYL ACETATE
79-20-9
METHYL ACRYLATE
96-33-3
METHYL CHLORIDE
74-87-3

261-0300-101 / DRAFT December 16, 2017 / Page III-29
Table III-1
Compounds Excluded from Further Surface Water
Evaluation on Attainment of NR SHS for GW ≤ 2,500 TDS
SUBSTANCE
CAS
Number
METHYL ETHYL KETONE
78-93-3
METHYL HYDRAZINE
60-34-4
METHYL ISOCYANATE
624-83-9
METHYL METHACRYLATE
80-62-6
METHYL METHANESULFONATE
66-27-3
METHYL PARATHION
298-00-0
METHYL STYRENE (MIXED ISOMERS)
25013-15-4
METHYL TERT-BUTYL ETHER (MTBE)
1634-04-4
METHYLCHLOROPHENOXYACETIC
ACID (MCPA)
94-74-6
METHYLENE BIS(2-CHLOROANILINE),
4,4’-
101-14-4
METHYLNAPHTHALENE, 2-
91-57-6
METHYLSTYRENE, ALPHA
98-83-9
METRIBUZIN
21087-64-9
MOLYBDENUM
7439-98-7
MONOCHLOROACETIC ACID
79-11-8
NAPHTHYLAMINE, 1-
134-32-7
NAPHTHYLAMINE, 2-
91-59-8
NAPROPAMIDE
15299-99-7
NITRATE-NITROGEN (TOTAL)
14797-55-8
NITRITE-NITROGEN (TOTAL)
14797-65-0
NITROANILINE, O-
88-74-4
NITROANILINE, P-
100-01-6
NITROGUANIDINE
556-88-7
NITROPHENOL, 2-
88-75-5
NITROPHENOL, 4-
100-02-7
NITROPROPANE, 2-
79-46-9
NITROSODIETHYLAMINE, N-
55-18-5
NITROSO-DI-N-BUTYLAMINE, N-
924-16-3
NITROSO-N-ETHYLUREA, N-
759-73-9
OCTYL PHTHALATE, DI-N-
117-84-0
OXAMYL (VYDATE)
23135-22-0
PARAQUAT
1910-42-5
PARATHION
56-38-2
PEBULATE
1114-71-2
PENTACHLOROBENZENE
608-93-5
PENTACHLOROETHANE
76-01-7
PENTACHLORONITROBENZENE
82-68-8

261-0300-101 / DRAFT December 16, 2017 / Page III-30
Table III-1
Compounds Excluded from Further Surface Water
Evaluation on Attainment of NR SHS for GW ≤ 2,500 TDS
SUBSTANCE
CAS
Number
PERCHLORATE
7790-98-9
PHENACETIN
62-44-2
PHENOL
108-95-2
PHENYL MERCAPTAN
108-98-5
PHENYLENEDIAMINE, M-
108-45-2
PHENYLPHENOL, 2-
90-43-7
PHORATE
298-02-2
PHTHALIC ANHYDRIDE
85-44-9
PICLORAM
1918-02-1
PROMETON
1610-18-0
PRONAMIDE
23950-58-5
PROPANIL
709-98-8
PROPANOL, 2- (ISOPROPYL ALCOHOL)
67-63-0
PROPAZINE
139-40-2
PROPHAM
122-42-9
PROPYLBENZENE, N-
103-65-1
PROPYLENE OXIDE
75-56-9
PYRENE
129-00-0
PYRIDINE
110-86-1
QUINOLINE
91-22-5
QUIZALOFOP (ASSURE)
76578-14-8
RDX
121-82-4
RONNEL
299-84-3
SIMAZINE
122-34-9
STRONTIUM
7440-24-6
STRYCHNINE
57-24-9
STYRENE
100-42-5
SULFATE
7757-82-6
TEBUTHIURON
34014-18-1
TERBACIL
5902-51-2
TERBUFOS
13071-79-9
TETRACHLOROBENZENE, 1,2,4,5-
95-94-3
TETRACHLOROETHANE, 1,1,1,2
630-20-6
TETRACHLOROPHENOL, 2,3,4,6-
58-90-2
TETRAETHYL LEAD
78-00-2
TETRAETHYLDITHIOPYROPHOSPHATE
3689-24-5
TETRAHYDROFURAN
109-99-9
THIOFANOX
39196-18-4
THIRAM
137-26-8

261-0300-101 / DRAFT December 16, 2017 / Page III-31
Table III-1
Compounds Excluded from Further Surface Water
Evaluation on Attainment of NR SHS for GW ≤ 2,500 TDS
SUBSTANCE
CAS
Number
TIN
7440-31-5
TOLUDINE, M-
108-44-1
TOLUDINE, O-
95-53-4
TOLUDINE, P-
106-49-0
TRIALLATE
2303-17-5
TRICHLORO-1,2,2-TRIFLUOROETHANE,
1,1,2-
76-13-1
TRICHLOROACETIC ACID
76-03-9
TRICHLOROBENZENE, 1,3,5-
180-70-3
TRICHLOROETHANE, 1,1,1-
71-55-6
TRICHLOROPHENOL, 2,4,5-
95-95-4
TRICHLOROPHENOXYACETIC ACID,
2,4,5- (2,4,5-T)
93-76-5
TRICHLOROPHENOXYPROPIONIC ACID,
2,4,5- (2,4,5-TP)
93-72-1
TRICHLOROPROPANE, 1,1,2-
598-77-6
TRICHLOROPROPANE, 1,2,3-
96-18-4
TRICHLOROPROPENE, 1,2,3-
96-19-5
TRIETHYLAMINE
121-44-8
TRIETHYLENE GLYCOL
112-27-6
TRIFLURALIN
1582-09-8
TRIMETHYLBENZENE, 1,3,4-
(TRIMETHYLBENZENE, 1,2,4-)
95-63-6
TRINITROGLYCEROL (NITROGLYCERIN)
55-63-0
TRINITROTOLUENE, 2,4,6-
118-96-7
VANADIUM
7440-62-2
VINYL ACETATE
108-05-4
VINYL BROMIDE (BROMOETHENE)
593-60-2
WARFARIN
81-81-2
ZINEB
12122-67-7

261-0300-101 / DRAFT December 16, 2017 / Page III-32
Conductivity: 1.90 ft/day
Gradient: .01 ft/ft
Groundwater flow represented by plume: 1,900 ft3/day =
14,000 gallons/day
Average concentrations in groundwater at surface water interface (g/L):
Benzene: 12,000
Toluene: 52,000
Ethylbenzene: 1,500
Total xylenes: 9,000
Using benzene for this example, the maximum average groundwater
concentration is 12,000
g/L
and the plume flow is 14,000 gallons/day or
0.014 million gallons/day (MGD).
Assuming all groundwater discharges to the stream, an evaluation of the
plume discharge to the stream can now be made with the above data using
PENTOXSD for each of the contaminants. The approach is described and
shown below for benzene:
Figures III-1 and III-2 are printouts from the PENTOXSD model for
Example 1. PENTOXSD shows that the recommended effluent limit for
benzene in this case is 181 μg/L, which is less than the 12,000 μg/L
maximum average groundwater concentration for benzene calculated for
this example. Therefore, a release of liability cannot be granted in this
case until the maximum average groundwater concentration is reduced to
at least 181 μg/L and other parameters in the example are shown to be at
acceptable levels.
ii)
Example 2: Groundwater Source at Distance from Surface Water
Discharge – Steady-State Conditions
In this example, all conditions are the same as for Example 1 except the
source is 100 feet from the stream. Additionally, one well is located
40 feet from the source in a downgradient direction toward the stream
containing benzene at a concentration of 6,500 μg/L. Assume that wells
cannot be drilled at the groundwater/surface water interface because of
existing buildings and other obstacles. However, enough onsite and
offsite data have been collected to reasonably calibrate a model and
establish that the plume is at or near steady-state conditions. A
groundwater solute transport model is chosen by the remediator to
estimate the flow and concentration of the contaminants into the river. For
purposes of this example, the QD and SWL5 spreadsheet applications will

261-0300-101 / DRAFT December 16, 2017 / Page III-33
be used. A plan view model such as QD is being used because it is
difficult or impossible to calibrate a cross-sectional model such as SWL5
using isoconcentration map data. Isoconcentration contours are usually
developed and drawn in the plan-view or horizontal dimension. Once the
model input parameters are finalized using the plan view model, they are
easily transferred for use into the cross-sectional model. The Department
does not require the use of these particular models; however, if another
surface water loading model is used, the rules incorporated into selection
of SWL5’s “edge criterion” for establishing the portion of the plume flow
and average concentration must be used.
In order to complete the analysis, input values for the following additional
parameters required by the model were developed during the site
characterization phase. Those parameters and how they were determined
for this example are as follows (See Figure III-3 for the actual values):
Longitudinal and Transverse Dispersion – fitted to plume data
(isoconcentration map) using QD
Vertical Dispersion – set to 0.0001 because the entire plume is assumed to
discharge into the stream and any vertically dispersed contamination
would enter the stream.
Lambda – starting values may be found from Appendix A, Table 5A,
Chapter 250 (and converted to the correct units).
Time – 11 years-established from historical records. Note that this is fixed
at 1 x 1099 days in SWL5 to assure that output is at steady-state
conditions. This assures that SWL5 will yield the maximum average
concentration for plumes emanating from a constant source.
Porosity – determined by laboratory analysis of undisturbed samples.
Dry Bulk Density – estimated at 2.65 * (1-porosity).
K
oc
– from Appendix A, Table 5, Chapter 250.
Fraction Organic Carbon – Can be estimated (Section III.A.1.b.ii).

261-0300-101 / DRAFT December 16, 2017 / Page III-34
Figure III-1
Example 1 – PENTOXSD Model Inputs

261-0300-101 / DRAFT December 16, 2017 / Page III-35
Figure III-2
Example 1 –PENTOXSD Model Output

261-0300-101 / DRAFT December 16, 2017 / Page III-36
Once a satisfactory output matching the overall plume geometry at
11 years was achieved using QD, the flow and transport terms of QD,
except for time, were input into SWL5. The output from QD and SWL5 is
shown in Figures III-3 and III-4.
The model indicates that the maximum average concentration in
groundwater is 1.28 mg/L for benzene and the total flow through the
plume is 0.00026 MGD. The model output indicates that PENTOX is
required as the next step. These values (after any necessary conversion)
then become the input values for existing discharge flow and discharge
concentration of benzene in PENTOXSD. Note that the average
concentration in the benzene plume is lower than in the first example
because of first-order decay and dispersion. However, note also that,
because the plume has dispersed, the cross-sectional flow is somewhat
greater.
Documentation for using SWL5 to estimate plume flow, concentrations
and mass loading is provided on the LRP web page under “Guidance and
Technical Tools.”
Figures III-5 and III-6 are printouts from the PENTOXSD model run for
Example 2. In this case, the recommended effluent limit for benzene is
1,994 μg/L, which is greater than the maximum average benzene
concentration of 1,278 μg/L calculated with SWL5. Therefore, attainment
of surface water criteria for benzene has been demonstrated. If attainment
of the other parameters in the example with surface water criteria were
also demonstrated, a release of liability would be conveyed.

261-0300-101 / DRAFT December 16, 2017 / Page III-37
Figure III-3
Example 2 – Quick Domenico Model Output
ADVECTIVE TRANSPORT WITH THREE DIMENSIONAL DISPERSION,1ST ORDER DECAY and RETARDATION - WITH CALIBRATION TOOL
Project:
TGM Example 2
Date:
Prepared by:
BECB
Contaminant:
Benzene
SOURCE
Ax
Ay
Az
LAMBDA
SOURCE
SOURCE
Time (days)
CONC
(ft)
(ft)
(ft)
WIDTH
THICKNESS
(days)
(MG/L)
>=.001
day-1
(ft)
(ft)
12
2.00E+01
1.00E+00
1.00E-04
0.0008
100
10
4015
Hydraulic
Hydraulic
Soil Bulk
Frac.
Retard-
V
Cond
Gradient
Porosity
Density
KOC
Org. Carb.
ation
(=K*i/n*R)
(ft/day)
(ft/ft)
(dec. frac.)
(g/cm
3)
(R)
(ft/day)
1.92E+00
0.01
0.358
1.7
58
1.00E-03
1.275418994
0.042049934
x(ft)
y(ft)
z(ft)
100
0
0
x(ft)
y(ft)
z(ft)
Conc. At
100
0
0
at
4015 days =
mg/l
AREAL
CALCULATION
MODEL
DOMAIN
Length (ft)
200
Width (ft)
100
20
40
60
80
100
120
140
160
180
200
100
0.000
0.000
0.000
0.000
0.001
0.001
0.002
0.003
0.003
0.003
50
4.466
3.323
2.469
1.830
1.351
0.991
0.720
0.517
0.365
0.253
0
8.932
6.646
4.939
3.660
2.701
1.980
1.437
1.029
0.724
0.499
-50
4.466
3.323
2.469
1.830
1.351
0.991
0.720
0.517
0.365
0.253
-100
0.000
0.000
0.000
0.000
0.001
0.001
0.002
0.003
0.003
0.003
Field Data:
Centerline Conc.
Concentration
12
6.5
Distance from Source
0
40
2.701
Point Concentration
NEW QUICK_DOMENICO.XLS
SPREADSHEET APPLICATION OF
"AN ANALYTICAL MODEL FOR
MULTIDIMENSIONAL TRANSPORT OF A
DECAYING CONTAMINANT SPECIES"
P.A. Domenico (1987)
Modified to Include Retardation
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
0
100
200
300
conc
distance
Centerline Plot (linear)
Model
Output
Field
Data
0.100
1.000
10.000
100.000
0
100
200
300
conc
distance
Centerline Plot (log)
Model
Output
Field
Data

261-0300-101 / DRAFT December 16, 2017 / Page III-38
Figure III-4
Example 2 – SWLOAD Model Output
METHOD FOR ESTIMATNG FLOW, AVERAGE CONCENTRATION AND MASS LOADING TO SURFACE WATER FROM GROUNDWATER
Project:
TGM Example 2
Date:
Contaminant:
Benzene
Prepared by:
BECB
SOURCE
CONC
Ax
Ay
Az
LAMBDA
SOURCE SOURCE
(units)
(ft)
(ft)
(ft)
WIDTH THICKNESS
Time
mg/l
>.0001
>.0001
>=.0001
day-1
(ft)
(ft)
(days)
12
20
1 1.00E-04
0.0008
100
10
1.00E+99
Hydraulic
Hydraulic
Soil Bulk
Frac.
Retard-
V
Cond
Gradient
Porosity
Density
KOC
Org. Carb.
ation
(=K*i/n*R)
(ft/day)
(ft/ft)
(dec. frac.)
(g/cm
3)
(R)
(ft/day)
1.92E+00
0.01
0.358
1.7
58
1.00E-03
1.275419 0.04204993
-93.875
-75.1
-56.325
-37.55
-18.775
0
18.775
37.55
56.325
75.1
93.875
Edge Criterion (mg/l)
0.005
0
0.0026474 0.1047209 0.9030088 2.23625869 2.72096528
2.7574273 2.7209653 2.2362587 0.9030088 0.1047209 0.002647
Higest modeled conc.
2.75743
-1.0438
0.0026474 0.1047209 0.9030088 2.23625869 2.72096528
2.7574273 2.7209653 2.2362587 0.9030088 0.1047209 0.002647
-2.0876
0.0026474 0.1047209 0.9030088 2.23625869 2.72096528
2.7574273 2.7209653 2.2362587 0.9030088 0.1047209 0.002647
SURFACE WATER LOADING GRID
-3.1314
0.0026474 0.1047209 0.9030088 2.23625869 2.72096528
2.7574273 2.7209653 2.2362587 0.9030088 0.1047209 0.002647
Distance to Stream (ft)
100
-4.1752
0.0026474 0.1047209 0.9030088 2.23625869 2.72096528
2.7574273 2.7209653 2.2362587 0.9030088 0.1047209 0.002647
Plume View Width (ft)
187.75
-5.219
0.0026474 0.1047209 0.9030088 2.23625869 2.72096528
2.7574273 2.7209653 2.2362587 0.9030088 0.1047209 0.002647
Plume View Depth (ft)
10.438
-6.2628
0.0026474 0.1047209 0.9030088 2.23625869 2.72096528
2.7574273 2.7209653 2.2362587 0.9030088 0.1047209 0.002647
-7.3066
0.0026474 0.1047209 0.9030088 2.23625869 2.72096528
2.7574273 2.7209653 2.2362587 0.9030088 0.1047209 0.002647
-8.3504
0.0026474 0.1047209 0.9030088 2.23625869 2.72096528
2.7574273 2.7209653 2.2362587 0.9030088 0.1047209 0.002647
PENTOX NEEDED
-9.3942
0.0026473
0.10472 0.9030005 2.23623813 2.72094027 2.75740196 2.7209403 2.2362381 0.9030005
0.10472 0.002647
-10.438
2.587E-06 0.0001023 0.0008823 0.00218489 0.00265846 0.00269408 0.0026585 0.0021849 0.0008823 0.0001023 2.59E-06
Average Groundwater Concentration
1.27773 mg/l
Plume Flow
0.00041 cfs
0.00026 MGD
Mass Loading to Stream
1279.85 mg/day
PA DEPARTMENT
OF ENVIRONMENTAL PROTECTION
SWLOAD5B.XLS
A METHOD FOR ESTIMATING
COMTAMINANT LOADING TO SURFACE
WATER
based on
P.A. Domenico (1987)
Modified to Include Retardation

261-0300-101 / DRAFT December 16, 2017 / Page III-39
Figure III-5
Example 2 – PENTOXSD Model Inputs

261-0300-101 / DRAFT December 16, 2017 / Page III-40
Figure III-6
Example 2 – PENTOXSD Model Output

261-0300-101 / DRAFT December 16, 2017 / Page III-41
B.
Guidance for Attainment Demonstration with Statistical Methods
1.
Introduction
The requirement to apply statistical methods to verify the cleanup of a site is emphasized
in Act 2. Sections 302, 303 and 304 of Act 2 (35 P.S. §§ 6026.302-304) require that
attainment of a standard be demonstrated by the collection and analysis of samples from
affected media (such as surface water, soil, groundwater in aquifers at the point of
compliance) through the application of statistical tests set forth in regulation. The Act
also requires the Department to recognize those methods of attainment demonstration
generally recognized as appropriate for that particular remediation.
Statistical methods are emphasized because there is a practical need to make decisions
regarding whether a site meets a cleanup standard in spite of uncertainty. The uncertainty
arises because we are able to sample and analyze only a small portion of the soil and
groundwater at a site, yet we have to make a decision regarding the entire site.
The purpose of this section is to provide guidance for the use of statistics to demonstrate
that a site has attained a cleanup standard under Act 2. It is intended to address certain
key issues pertinent to the sampling and statistical analysis under Act 2, to provide
references for proper statistical analysis and, if necessary, to provide examples of
applying statistical procedures in detail. It is not intended to address every statistical
issue.
For statistical attainment issues not addressed directly in this manual or in 25 Pa. Code
Chapter 250, a person may consult the latest ITRC and EPA documents for additional
guidance. The 2013 ITRC document
Groundwater Statistics and Monitoring
Compliance
and EPA guidance documents (EPA 1992b, 1992c, 1996, 2002b, 2009) are
particularly helpful. They provide detailed statistical procedures for demonstration of
attainment and data analysis.
For groundwater characterization, remediators should consult Appendix A of this manual
“Groundwater Monitoring Guidance” which provides general information on
groundwater monitoring and sampling issues, such as monitoring well construction,
locations and depths of monitoring wells, and well abandonment procedures. The
Groundwater Monitoring Guidance provides a good summary of various statistical
methods used for groundwater characterization.
For conducting statistical analyses, remediators may wish to utilize EPA’s ProUCL
Statistical Software for Environmental Applications. This free program is available on
EPA’s website and accompanied with a Technical Guide. ProUCL is able to run most of
the statistical applications summarized in this section of the TGM.
Other standard statistics-related tests may be used to perform the procedures to
demonstrate attainment as appropriate. If necessary, professional services should be
obtained.

261-0300-101 / DRAFT December 16, 2017 / Page III-42
When we consider applying statistical methods to demonstrate the attainment of a risk-
based cleanup standard, it is important to realize that three components may influence the
overall stringency of this cleanup standard:
The first component is the magnitude, level, or concentration that is deemed
protective of human health and the environment. The development of risk-based
cleanup standards is addressed in the regulations and Department’s risk
assessment guidances.
The second component of the standard is the sampling that is done to evaluate
whether a site is above or below the standard.
The final component is how the resulting data are compared with the standard to
decide whether the remedial action was successful (a statistical analysis).
Persons overseeing cleanup must look beyond the cleanup level and explore the sampling
and statistical analysis that will allow evaluation of the site relative to the cleanup level.
This guidance is intended to address statistical analysis and sampling components that
may affect the stringency of cleanup standards.
2.
Data Review for Statistical Methods
Preliminary data review for statistical analysis (also known as exploratory data analysis
in the DEP Groundwater Monitoring Guidance Manual; PA DEP, 2001) includes the use
of graphical techniques and calculation of summary statistics. By reviewing the data both
numerically and graphically, one can learn the “structure” of the data and identify
limitations for using the data. Graphical methods include histograms, probability plots,
box charts, and time-series plots to visually review the data for trends or patterns. EPA
and most statistical texts recommend that time-series data should be graphed. This visual
approach allows for a quick assessment of the statistical features of the data.
Calculations of summary statistics are typically done to characterize the data and make
judgments on the central tendencies, symmetry, presence of outliers, etc. Preliminary
data review is critical in selecting additional appropriate mathematical procedures.
Graphical and parametric statistical procedures discussed here are included in many
introductory statistics textbooks (e.g., Iman and Conover, 1983 and Ott, 1988) and are
available in many computer statistics packages.
a)
Summary Statistics
Basic summary statistics can be used to characterize groundwater monitoring
data. Summary statistics include median, interquartile range (IQR), mean,
standard deviation, and range. Median and IQR are determined from percentiles.
Median is the 50th percentile and IQR is the 25th to 75th percentile. Median
indicates the “center” of data values. The mean is another measure of center but
only if data are normally or symmetrically distributed. Mean and standard
deviation are required values with parametric procedures. Range is the minimum
to maximum values. Procedures for such summary statistics are found in
introductory statistics texts.

261-0300-101 / DRAFT December 16, 2017 / Page III-43
b)
Graphical Procedures
Refer to ITRC (2013) for a general reference on graphical procedures.
Histogram
- A histogram is a graphic display of frequency distribution. The area
within the bar represents the relative density of the data.
Boxplots
- A boxplot summarizes a data set by presenting the percentile
distribution of the data. The “box” portion indicates the median and interquartile
range (IQR). IQR is the middle 50 percent of data. Difference in the size of box
halves represents data skewness.
Normal and symmetrical distributions will have equal size box halves. Extreme
outliers are displayed as individual points that are recognized easily. Boxplots
can be constructed by hand; however, many computer statistical packages will
prepare them.
The boxplot of a lognormal distribution will have noticeably different-sized box
halves. Lack of IQR overlap for different data sets will indicate a probable
significant difference. Boxplots of seasonally grouped data can be used to detect
data seasonality.
Time Series Plots
- A time series plot displays individual data points on a time
scale. A monthly scale can help to identify seasonal variation. A yearly scale
also can identify possible trends. Superimposing data from multiple sampling
locations may provide additional information. Improved trend information is
often available with data smoothing.
Control Charts
- Control charts are used to define limits for an analyte that has
been monitored at an uncontaminated well over time. This procedure is a
graphical alternative to prediction limits.
A common technique is the Shewhart-CUSUM control chart that plots the data on
a time scale. Obvious features such as trends or sudden changes in concentration
levels could then be observed. With this method, if any compliance well has a
value or a sequence of values that lie outside the control limits for that analyte, it
may indicate statistically significant evidence of contamination.
The control chart approach is recommended only for uncontaminated wells, a
normal or lognormal data distribution with few nondetects, and for a dataset that
has at least eight independent samples over a one-year period. This baseline is
then used to judge the future samples. See the EPA Guidance (EPA, 2009,
Chapter 20).
3.
Statistical Inference and Hypothesis Statements
A statistical procedure that is designed to allow the extrapolation from the results of a
few samples to a statement regarding the entire site is known as statistical inference.

261-0300-101 / DRAFT December 16, 2017 / Page III-44
Statistical inference allows decision making under uncertainty and valid extrapolation of
information that can be defended and used with confidence to determine whether the site
meets the cleanup standard.
The goal of statistical inference, the process of extrapolating results from a sample to a
larger population, is to decide which of two complementary hypotheses, null hypothesis
and alternative hypothesis, is likely to be true.
In general, statistical inference procedures include the following steps:
(1)
A null hypothesis and its alternative hypothesis are drawn up. The null
hypothesis is developed in such a way that the probability of Type I error can be
determined. The Type I error is an error that we falsely reject the null hypothesis,
when the null hypothesis is true. Type I error is also known as false positive
error.
(2)
Decide the level of significance,
?.
This controls the risk of committing a Type I
error.
(3)
Establish a decision rule for each scale of decision making that is derived from
step 4 of the Data Quality Objectives (DQO) process. (See Section III.F.2 for
more information on the DQO process).
(4)
Determine the sample size, n. This is the number of environmental samples
needed to make decision. Obtain data through the implementation of sampling
and analysis plan.
(5)
Apply the decision rule to the data. The null hypothesis is rejected or not
rejected. Rejection of the null hypothesis implies acceptance of the alternative
hypothesis.
Section 250.707(d)(1) of the regulations has specified the ground rules of hypothesis
statements under Act 2. For demonstration of attainment of Statewide health or site-
specific standards, the null hypothesis (H
o
) is that the true site arithmetic average
concentration is at or above the cleanup standard, and the alternative hypothesis (H
a
) is
that the true site arithmetic average concentration is below the cleanup standard. When
statistical methods are to be used to determine that the background standard is exceeded,
the null hypothesis (H
o
) is that the background standard is achieved and the alternative
hypothesis (H
a
) is that the background standard is not achieved.
To understand the rationale of hypothesis testing, let us consider a nonstatistical
hypothesis testing example - the process in which an accused individual is judged to be
innocent or guilty in a criminal court. Under our legal system, we feel that it is a more
grievous mistake to convict an innocent man than to let a guilty man go free. Therefore,
the accused person is presumed to be innocent under our legal system. The burden of
proof of his guilt rests upon the prosecution. The prosecutor must present sufficient
evidence to the jury in order to convict the defendant, while the defendant’s lawyer
would want to throw any reasonable doubt into the evidence presented by the prosecutor
in order to get an acquittal verdict for the defendant. Using the language of hypothesis

261-0300-101 / DRAFT December 16, 2017 / Page III-45
testing, we want to test a null hypothesis (H
o
) that the accused man is innocent. That
means that an alternative hypothesis (H
a
) exists, that the defendant is guilty. The jury
will examine the evidence and decide whether the prosecution has demonstrated
sufficiently that the evidence is inconsistent with the null hypothesis (H
o
) of innocent. If
the jurors decide that the evidence is inconsistent with H
o
, they reject that hypothesis and
therefore accept the alternative hypothesis (H
a
) that the defendant is guilty.
Similar to the above legal process example, because we feel that it is a more serious
mistake to declare a contaminated site to be uncontaminated than to declare an
uncontaminated site to be contaminated under the Statewide health and site-specific
standards, we choose the following null hypothesis statement: the true site arithmetic
average concentration is at or above the cleanup standard. The null hypothesis is
assumed to be true unless substantial evidence shows that it is false. The demonstration
of attainment must be presented with sufficient evidence in order to show that the
postremediation condition at the site is not consistent with the null hypothesis. We use
“true site arithmetic average concentration” here because arithmetic average
concentration is representative of the concentration that would be contacted at a site over
time and toxicity criteria that are used to develop cleanup standards are based on long-
term average exposure. The arithmetic average is appropriate regardless of the type of
statistical distribution that might best describe the sampling data. We do not use
geometric average concentration because the geometric mean of a set of sampling data
bears no logical connection to the cumulative intake that would result from long-term
contact with site contaminants.
It should be noted that the above hypothesis statements referring to the arithmetic average
concentration does not force everyone to use 95% upper confidence limit (UCL) to infer
the true site arithmetic average concentration. Methods other than the 95%UCL, such as
tests for percentiles or proportions, also may be used provided that a person can
document that high coverage of the true population mean occurs, (i.e., the value used in a
method equals or exceeds the true site arithmetic average concentration with high
probability).
For the background standard, the null hypothesis (H
o
) is that the background standard is
achieved and the alternative hypothesis (H
a
) is that the background standard is not
achieved. The background standard is not risk-based. These hypothesis statements will
allow some site concentrations to be higher than some background reference-area
measurements without rejecting the null hypothesis. These hypothesis statements are
consistent with EPA guidance documents (EPA, 2009). If we reverse the hypothesis
statements and presume that the background standard is not achieved, we would require
most site concentrations to be less than the reference measurements in order to declare a
site to be clean. In considering the cost of remediation, both the Department and EPA
believe that this requirement is unreasonable.
4.
Selection of Statistical Methods
a)
Factors Affecting the Selection of Statistical Methods
The selection of statistical methods for use in assessing the attainment of cleanup
standards depends on the characteristics of the environmental media. In soils,

261-0300-101 / DRAFT December 16, 2017 / Page III-46
concentrations of contaminants change relatively slowly, with little variation from
season to season. In groundwater, the number of measurements available for
spatial characterization is limited and seasonal patterns may exist in the data. As
a result of these differences, separate procedures are recommended for the
differing problems associated with soils and groundwater.
The selection of statistical methods also depends on remediation standards. There
are three types of remediation standards under Act 2: background standards,
Statewide health standards, and site-specific standards. Background standards are
developed using background data. Many SHS and site-specific standards are risk-
based standards that are concentration limits based on risk assessment
methodologies. At some sites, a site-specific standard might use an engineering
control, such as capping a site to eliminate pathways. The cap must be designed
to meet certain engineering specifications prescribed in numerical levels. A
background standard is not a single number, but rather a range of numbers. A
statistical method used to demonstrate the attainment of the background standard
is used to compare the distribution of data for a background reference area to the
distribution of data for the impacted area. Different statistical methods are used to
demonstrate the attainment of a risk-based concentration limit.
As a result of the above factors, recommended statistical approaches are
addressed separately based on environment media and remediation standards.
The flowchart in Figure III-7 provides a summary of recommended statistical
methods described in the Chapter 250 regulations. Since Act 2 also requires the
Department to recognize those methods of attainment demonstration generally
recognized as appropriate for a particular remediation, the Department will also
accept other appropriate statistical methods that meet the performance standards
described in 25 Pa. Code § 250.707(d)(2).
Statistical methods generally can be classified into two categories: parametric
procedures and nonparametric procedures. The selection of a parametric or a
nonparametric procedure depends on the distribution of the data, the percentage of
nondetects, and the database size. However, both procedures have assumptions
that must be met to be considered valid analyses.
Parametric Procedure
- Assumptions of parametric procedures include a
specific data distribution such as normal (also known as Gaussian or the bell-
shaped curve) or lognormal (normality achieved by log-transforming the data),
and data variances that are similar. In addition, the data are assumed to be
independent.
Nonparametric Procedure
- Assumptions for nonparametric tests also are
important. Nonparametric procedures assume equal variances and that the type
(shape) of distribution of the population is the same. In other words,
nonparametric methods do not require a specific type of data distribution, which
is different from assuming a normal distribution when using parametric statistics.

261-0300-101 / DRAFT December 16, 2017 / Page III-47
Nonparametric procedures may be preferred because they:
are free from normal distribution assumptions, thereby eliminating the
need for normality tests and data transformations;
are resistant to effects of outliers; and
are usable when censored (i.e., less than detection values) data are present.
b)
Recommended Statistical Procedures
In consideration of the factors described above, 25 Pa. Code § 250.707 provides
recommended statistical procedures that can be used to demonstrate attainment of
cleanup standards. The following discussions provide background information of
these recommended methods.
i)
Soil Risk-Based Standards
For risk-based standards, the selection of statistical parameters, such as
mean, median or an upper percentile, to use in the statistical assessment
decision depends on the toxicity criteria. Mean and median are useful for
cleanup standards based on carcinogenic or chronic health effects and
long-term average exposure. Upper proportion or percentile should be
used if the health effects of the contaminant are acute or worst-case
effects. Because the SHS values are based on the evaluation of
carcinogenic or chronic health effects and long-term average exposure, the
Cleanup Standards Scientific Advisory Board (CSSAB) has recommended
that mean or median should be the statistical parameter of choice. The
regulations allow the remediator to use the 75%/10X rule or the 95% UCL
of arithmetic mean to demonstrate attainment of the SHS in soils. The
75%/10X rule is valid ONLY for the SHS. For UST release sites that
have only localized (soil) contamination as defined in the storage tank
program’s Underground Storage Tank Closure Guidance, and where the
confirmatory samples taken in accordance with this TGM result in fewer
samples being taken than otherwise required [including the sampling
procedure for petroleum contaminated soils outlined in
§ 250.707(b)(1)(iii)(B)], all sample results must meet the SHS. For the
site-specific standard, the regulations recommend the use of the 95% UCL
of the arithmetic mean to demonstrate attainment in soils.
Sections 250.707(b) and (c) of the regulations discuss statistical tests
appropriate to demonstrating compliance of surface soils with the
Statewide health and site-specific standards.

261-0300-101 / DRAFT December 16, 2017 / Page III-48
Figure III-7
Flow Chart of Recommended Statistical Methods

261-0300-101 / DRAFT December 16, 2017 / Page III-49
(a)
75%/10X Rule
The 75%/10X rule is a statistical ad hoc rule that tests whether the
true site median concentration is below the cleanup standard. This
rule requires that 75% of the samples collected for demonstration
attainment be equal to or below the risk-based cleanup standard
and that no single sample result exceeds the risk-based standard by
more than ten times. (See 25 Pa. Code § 250.707(b)(1)(i)).
For the 75%/10X rule, the number of sample points required for
each distinct area of contamination is specified in § 250.703(d) of
the regulations and is as follows:
For soil volumes equal to or less than 125 cubic yards, at
least eight (8) samples.
For soil volumes up to 3,000 cubic yards, at least
twelve (12) sample points.
For each additional volume of up to 3,000 cubic yards, an
additional twelve (12) sample points.
Additional sampling points may be required based on site-
specific conditions.
This recommendation of 8 to 12 samples at minimum is based on a
simulation study using lognormal distributions (CSSAB 1996).
Because the heterogeneity of a volume of soil increases as the
volume increases, the number of samples required to accurately
demonstrate attainment would also increase.
In a situation where compliance with two different SHS MSCs are
required, such as an MSC for surface soil and another MSC for
subsurface soil, two separate attainment tests, each applying the
75%/10x rule, would be required (0-2 feet and 2-15 feet).
It should be noted that the 75%/10X rule should not be used to
demonstrate attainment of the site-specific standard. The site-
specific standard is based on site-specific risk assessment
methodology, including the assumption that a receptor’s long-term
exposure is related to the true site arithmetic average concentration
of a contaminant. Therefore, the 75%/10X rule is not appropriate
for the site-specific standard.
(b)
The 95% Upper Confidence Limit (UCL) of Arithmetic Mean
Using 95% UCL of the arithmetic mean as described in 25 Pa.
Code § 250.707(b)(1)(ii) and 250.707(c) is well documented in
various EPA risk assessment or statistical guidances (EPA, 1989,

261-0300-101 / DRAFT December 16, 2017 / Page III-50
1992c, 1996, 2002a). It should be noted that this statistical test
may be applied to each distinct area of contamination for
demonstration of attainment at a site. Site characterization data
may not be suitable for inclusion in determining a 95% UCL for
attainment demonstration.
The following formula can be used for calculating sample size
(number of discrete soil samples) needed to estimate the mean:
n
d
=
2
{(Z
1-
+ Z
1-?
)/(C
s
-
1
)}
2
where
?
is the false positive rate;
 
is the false negative rate; Z
1-?
and Z
1-
are the critical values for the normal distribution with
probabilities of 1-? and 1-; C
s
is the cleanup standard; μ
1
is the
value of population mean under the alternative hypothesis for
which the specific false negative rate () is to be controlled;
 
is an
estimate of true standard deviation of the population.
Please note that the above equation may generate exceedingly
large sample size numbers (e.g., >>50). When some adjustments
of the sample size are necessary based on practical and cost
considerations, a person may use the equation to generate a smaller
sample size by increasing the false negative rate or the detection
difference C
s
1
. Professional judgment should be used in
calculating sample size versus the reliability of the statistical test.
The false positive rate must not be greater than 0.20 for a
nonresidential site or 0.05 for a residential site
(§ 250.707(d)(2)(vii)).
Procedures to calculate 95% UCL of arithmetic mean are provided
in Sections III.B.6 and III.B.7 of this TGM.
The following decision rule is used to determine if a site meets the
cleanup standard:
If 95% UCL of arithmetic mean is greater than or equal to
C
s
, conclude that the sample results do not meet the
cleanup standard.
If 95% UCL of arithmetic mean is less than C
s
, conclude
that the sample results meet the cleanup standard.
Note that this rule uses the 95% UCL of the arithmetic mean to
estimate the limit of the population mean. The decision rule is
consistent with the hypothesis statements.
The primary assumptions of this method are independence of the
data, and sample mean is approximately normally distributed or
data are lognormally distributed. Examples of normal and

261-0300-101 / DRAFT December 16, 2017 / Page III-51
lognormal distributions are shown in Figure III-8. When the
population is normally distributed, the sample mean is normally
distributed, no matter the sample size. However, if the population
distribution is unknown, Central Limit Theorem states that the
distribution of sample means of random samples with fixed sample
size (n) from a population with an unknown distribution will be
approximately normally distributed provided the sample size (n) is
large. This means that moderate violation of the assumption of
normality for the population is acceptable when sample size is
large.
For sample sizes up to 50, EPA recommends to use Shapiro Wilk
test for testing normality (EPA, 2009). Other tests for normality,
such as Shapiro-Francia test and other goodness-of-fit tests are
discussed in EPA’s Unified Guidance (EPA, 2009). To test the
independence of data, ordinary-runs test (Gibbons, 1990) can be
used.
Figure III-8: Examples of Normal Distribution and Lognormal Distribution
An important consideration regarding the 95% UCL of arithmetic
mean is the use of composite sampling approach. Unless
composite sampling is considered inappropriate (such as for
volatile organic compounds (VOCs)), data from composite
sampling can be more cost-efficient to estimate population mean
and population variance than discrete sampling (Edland et al.,
1994; Patil et al., 1994). Composite sampling can reduce the
laboratory analysis cost. Composite sampling may be considered,
if appropriate, to obtain the 95% UCL of arithmetic mean.
Equations to calculate the 95% UCL of arithmetic mean for
composite sampling are available (Edland et al., 1994; Patil et al.,
1994).

261-0300-101 / DRAFT December 16, 2017 / Page III-52
(c)
No Exceedance Rule
For cleanup of releases of petroleum products where full site
characterization has not been conducted and remediation is guided
by visual observation and/or field screening, the no exceedance
rule must be used as described in 25 Pa. Code § 250.707(b)(1)(iii)
as follows:
For sites where there is localized contamination as defined in the
document “Closure Requirements for Underground Storage Tank
Systems” (DEP technical document No. 263-4500-601), samples
shall be taken in accordance with that document.
For sites with contamination that does not qualify as localized
under that document, samples shall be taken from the bottom and
sidewalls of the excavation in a biased fashion that concentrates on
areas where any remaining contamination above the SHS would
most likely be found. The samples shall be taken from these
suspect areas based on visual observation and the use of field
instruments. If a sufficient number of samples has been collected
from all suspect locations and the minimum number of samples has
not been collected, or if there are no suspect areas, then the
locations to meet the minimum number of samples shall be based
on a random procedure. The number of sample points required
shall be determined in the following way:
For 250 cubic yards or less of excavated contaminated soil,
five samples shall be collected.
For each additional 100 cubic years of excavated
contaminated soil, one sample shall be collected.
For excavation involving more than 1,000 cubic yards of
contaminated soil, the Department will approve the
confirmatory sampling plan.
Where water is encountered in the excavation and no
obvious contamination is observed or indicated, a minimum
of two of the soil samples identified above shall be
collected just above the soil/water interface. These samples
shall meet the MSC determined by using the saturated soil
component of the soil-to-groundwater numeric value.
Where water is encountered in the excavation and no
obvious contamination is observed or indicated, a minimum
of two water samples shall also be collected from the water
surface in the excavation.
All sample results shall meet the SHS.

261-0300-101 / DRAFT December 16, 2017 / Page III-53
For sites where there is a release to surface soils resulting in
excavation of 50 cubic yards or less of contaminated soil, samples
shall be collected as described above, except that two samples shall
be collected.
ii)
Groundwater Risk-Based Standards
Statistical tests appropriate to demonstrating compliance with groundwater
standards are presented in 25 Pa. Code § 250.707(b)(2). Groundwater
cleanup activities generally include site investigation, groundwater
remediation, a post-treatment period allowing the groundwater to stabilize,
sampling and analysis to assess attainment, and possible post-cleanup
monitoring. Different statistical procedures are applicable at different
stages in this cleanup process. The statistical procedures used must
account for the changes in the groundwater system over time due to
natural or man-induced causes. The specific statistical procedures used
depend on the goals and quality of the monitoring data. The methods
selected should be consistent with the goals of the monitoring. For
example, a remediator may want to use regression analysis to decide when
to stop treatment of groundwater. Regression analysis can be used to
detect trends in contaminant concentration levels over time, to determine
variables that influence concentration levels, and to predict chemical
concentrations at future points in time. After terminating groundwater
treatment, a remediator may want to use time trend analysis or plotted data
to find if the groundwater has stabilized. After the groundwater has
reached a steady state, the remediator may compare monitoring well
concentrations to background reference well concentrations to determine
whether the post-cleanup contamination concentrations are acceptable
compared to the cleanup standards and may perform trend analysis or use
plotted data to determine whether the post-cleanup contamination
concentrations are likely to remain acceptable.
Once the groundwater has stabilized, it is recommended to use the 95%
UCL of the mean (EPA, 2002a) or the following CSSAB ad hoc rule to
compare with groundwater risk-based standards: In monitoring wells
beyond the property boundary, the attainment criteria would be 75% of the
sampling results from any given well below the standard with no
individual value being more than 2 times the standard (75%/2X rule).
This rule would have to be met in each individual monitoring well.
To use the CSSAB ad hoc rule, eight samples from each compliance well
must be obtained during eight consecutive quarters. A shorter sampling
period (25 Pa. Code § 250.704(d)) requires the use of the no exceedance
rule (25 Pa. Code § 250.704(d)(3)) with written approval of the
Department.

261-0300-101 / DRAFT December 16, 2017 / Page III-54
iii)
Soil Background Standards
The determination of attainment of soil background standards is based on
a comparison of the distributions of the background concentrations of a
regulated substance with the concentrations in an impacted area. The
regulations allows a person to use highest measurement comparison,
combination of Wilcoxon Rank Sum (WRS) test and Quantile test, or
other appropriate methods to demonstrate attainment of background
standards (25 Pa. Code §250.707(a)(1)). No matter which method is used,
the regulations require that the minimum number of samples to be
collected is ten from the background reference area and ten from each
cleanup unit. This requirement of ten samples is to ensure that any
selected statistical test has sufficient power to detect contamination. The
regulations do not specify the false negative rate because it is more
appropriate to determine the false negative rate on a site-specific basis.
For the background standard, the false negative rate is the probability of
mistakenly concluding that the site is clean when it is contaminated. It is
the probability of making a Type II error.
Background soil sampling locations must be representative of background
conditions for the site, including soil type and depth below ground surface.
Randomization of sampling at background reference and onsite locations
must be comparable. EPA (EPA, 1992c) recommends that samples be
collected from background reference areas and cleanup units based on a
random-start equilateral triangular grid. When a triangular grid may miss
the pattern of contamination, EPA recommends the use of an unaligned
grid (Gilbert, 1987, p. 94) to determine the sampling locations.
(a)
Wilcoxon Rank Sum Test
This procedure (also known as Mann-Whitney U test) is a
nonparametric test for differences between two independent
groups. See EPA, 2009, ITRC (2013) and § 250.707(a)(1)(ii) of
the regulations.
For the WRS test, the EPA states that Noether’s formula may be
used for computing the approximate total number of samples to
collect from the background reference area and in the cleanup unit
(EPA 1992c).
?
?
?
?
N
Z
Z
c
c
R
?
?
?
?
?
1?
1?
2
2
12 1
05
1
?
Pr
.
(Noether’s formula) = total number of required samples.
where
?
= specified Type I error rate

261-0300-101 / DRAFT December 16, 2017 / Page III-55
    
= specified Type II error rate
Z
1-?
= the value that cuts off (100?)% of the upper tail
of the standard normal distribution
Z
1-
= the value that cuts off (100)% of the upper tail
of the standard normal distribution
c
= specified proportion of the total number of
required samples, N, that will be collected in the reference
area
m
= number of samples required in the reference area
= c x N
Pr
= specified probability greater than 1/2 and less
than 1.0 that a measurement of a sample collected at a
random location in the cleanup unit is greater than a
measurement of a sample collected at a random location in
the reference area. This value is specified by the user. See
Section 6.2.2 of EPA, 1992c for methods to determine Pr.
R
= expected rate of missing or unusable data
n
= number of samples required in the cleanup unit =
N – m
The underlying assumptions for the WRS test are random
sampling, independence assumption of selecting sampling points,
and that the distributions of the two populations are identical in
shape and dispersion. The distributions need not to be symmetric.
When applied with the Quantile test, the combined tests are most
powerful for detecting true differences between two population
distributions. When using the combined test, caution should be
exercised to ensure that the underlying assumption of equal
variance is met. An appropriate test for dispersion, such as
Levene’s test can be used. Unequal dispersion of data due to
higher concentration of contaminant at the site should be properly
addressed.
Procedures and an example of using the WRS test are in
Section III.B.8.
(b)
Quantile Test
The Quantile test (Johnson et al. 1987), described in 25 Pa. Code
§250.707(a)(1) § 250.707(a)(1)(ii), is performed by first listing the
combined reference-area and cleanup-unit measurements from

261-0300-101 / DRAFT December 16, 2017 / Page III-56
smallest to largest, as was done for the WRS test. Then, among the
largest r measurements (i.e., r is the number of measurements) of
the combined data sets, a count is made of the number of
measurements, k, that are from the cleanup unit. If k is sufficiently
large, then we conclude that the cleanup unit has not attained the
reference-area cleanup standard. The Quantile test is more
powerful than the WRS test for detecting when only one or a few
small portions of the cleanup unit have concentrations larger than
those in the reference area. Also, the Quantile test can be used
when a large proportion of the data is below the limit of detection.
See Chapter 7 of the EPA attainment guidance (EPA, 1992c). See
ProUCL Version 4.0 (2007) for further details.
For Quantile test, EPA recommends to use look-up tables to
determine the number of measurements that are needed from the
background reference area and the cleanup unit (Section 7.2 of
EPA, 1992c).
Procedures and an example of using the Quantile test are in
Section III.B.9 of this TGM. The null hypothesis (H
o
) and
alternative hypothesis (H
a
) statements for the Quantile test are:
H
o
:
?
= 0,
?
/
 
= 0
H
a
:
?
> 0,
?
/
 
> 0
where
?
= the proportion of the soil in the cleanup unit that has not been
remediated to background reference levels
?/
= amount (in units of standard deviation,
)
that the
distribution of 100?% of the measurements in the remediated
cleanup unit is shifted to the right (to higher measurements) of the
distribution in the background reference area
The underlying assumptions for Quantile test are random
sampling, independence assumption of selecting sampling points,
and that the distributions of the two populations have the same
dispersion (variance).
iv)
Groundwater Background Standards
Background conditions include two general categories. The first is
naturally occurring background or area-wide contamination. The second
is background associated with a release of regulated substances at a
location upgradient from the site that may be subject to such patterns and
trends.

261-0300-101 / DRAFT December 16, 2017 / Page III-57
For naturally occurring background or area wide contamination, it is
recommended that a minimum of 12 samples be collected from any
combination of upgradient monitoring wells, provided that all data
collected are used in determination of background concentrations. This
same number of samples must then be collected from monitoring wells
impacted by a release on the site during the same sampling event. In both
cases, this sampling may be accelerated such that all samples are collected
as quickly as possible, so long as the frequency does not result in serial
correlation in the data. The resulting values may be compared using
nonparametric or parametric methods to compare the two populations,
such as using the combination of WRS test and Quantile test described
previously. When comparing with the background results, the sampling
results in the onsite plume may not exceed the sum of the arithmetic
average and three times standard deviation calculated for the background
reference area (25 Pa. Code §250.707(a)(1) § 250.707(a)(3)(vii)).
For background associated with a release of regulated substances at a
location upgradient from a property, the background groundwater
concentrations will be determined at the hydrogeological upgradient
property line of the property, or a point hydrogeologically upgradient from
the upgradient property line that is unaffected by the release (25 Pa. Code
§250.204(f)(8).
Attainment of the background standard must be demonstrated wherever
the contamination occurs. Some mass of a particular contaminant may be
added to groundwater on the property. However, that additional mass
cannot result in concentrations which exceed the concentration measured
at the property line, nor can it be used to allow releases on the property. In
some cases, contaminants may degrade in groundwater (e.g. chlorinated
solvents). In situations such as these where biodegradation is occurring,
the total contaminant mass must not increase at the POC for the site.
Background concentrations are not related to a release at the site
(Section 103 of Act 2).
In the event contamination migrates off the property, concentrations at the
downgradient property boundary must be equal to or less than the
background concentrations measured where groundwater enters the
property. If a release on-property has occurred, the plume migrating
beyond the property boundary must also meet the background standard
(25 Pa. Code § 250.203(a)).
For background associated with an upgradient release of regulated
substances, allows the use of the nonparametric tolerance limit procedure
(25 Pa. Code § 250.707(a)(2). The nonparametric tolerance limit
procedure requires at least 8 samples from each well over 8 quarters to
have sufficient power to detect contamination. When the nonparametric
upper tolerance limit is established for upgradient data, data from
downgradient compliance wells can be compared to the limit. A
resampling strategy must be used when an analyte exceeds the

261-0300-101 / DRAFT December 16, 2017 / Page III-58
nonparametric upper tolerance limit. The well is retested for the analyte
of concern, and the value is compared to the nonparametric upper
prediction limit. These two-phase testing strategies can be very effective
tools for controlling the facility-wide false positive rate while maintaining
a high power of detecting contamination.
5.
Additional Information on Statistical Procedures
This section provides an overview regarding various other statistical methods available to
use to determine if a cleanup activity is successful. The EPA Addendum (EPA, 1992a),
EPA Groundwater Attainment (EPA, 1992b), EPA Soil Reference-Based Standards
Attainment (EPA, 1992c), EPA QA/G-9 (EPA, 1996), and EPA Unified Guidance (2009)
describe and provide examples for both the parametric and nonparametric methods. See
additional discussions in Helsel and Hirsch (1992), Conover (1980), Gilbert (1987), and
Davis and McNichols (1994, Parts I and II), and ITRC’s Groundwater Statistics and
Monitoring Compliance (2013). It is important to note that EPA’s ProUCL, free
statistical software for environmental applications, can run all of the tests summarized in
the following sections.
a)
Interval Tests
Statistical Intervals
- Statistical interval tests can be used independently for
comparing with a numerical value or in combination with other tests for
comparing populations. Statistical intervals include three main types: tolerance
intervals, prediction intervals, and confidence intervals. Which ones are used
depend on the goals of the data analysis.
Tolerance Intervals
- Tolerance intervals will typically be the most useful
interval test. They are used to determine the extent of data that is within a
standard (like an MCL) or ambient level. Parametric tolerance intervals can be
computed by assuming a lognormal distribution.
Prediction Intervals
- Prediction intervals are used to determine if the next one
or more samples are within the existing data distribution at a certain confidence
level. The prediction interval contains 100 * (1-
?
value) percent of the
distribution. A smaller
?
value will include a larger range of data. Prediction
intervals are used for intrawell (single well) comparisons, and with comparison of
a compliance well with a background well.
Confidence Intervals
- Confidence intervals contain a specified parameter of the
distribution (such as the mean of the data) at a specified confidence level.
Confidence intervals do not address extreme values. The step-by-step procedures
to calculate the upper confidence of mean are provided in Sections III.B.6
and III.B.7.
b)
Tests for Comparing Populations
The following tests are some of the EPA’s recommended tests for analysis of
groundwater data between upgradient and downgradient well groups,

261-0300-101 / DRAFT December 16, 2017 / Page III-59
downgradient wells and a health-based standard, or of intrawell (single well)
comparisons. This does not include all potentially satisfactory statistical tests.
Analysis of Variance (ANOVA)
- ANOVA includes a group of procedures used
for comparing the means of multiple (3 or more) independent groups such as
upgradient wells and downgradient wells. The ANOVA methods are used to
determine if there is statistically significant evidence of contamination at
downgradient wells compared to an upgradient well, or groups of wells.
The one-way ANOVA method is described with examples in Section 17 of the
EPA Unified Guidance (EPA, 2009). This is the EPA recommended procedure
for comparing data that do not violate the assumptions of normal distribution and
approximately equal variances.
However, as the number of wells (or groups) increases at a site, the power of
ANOVA to detect individual instances of contamination decreases. For this
reason, tolerance and prediction intervals with retesting provisions are often much
better procedures to use.
Kruskal-Wallis Test
- If assumptions of the one-way ANOVA test are “grossly”
violated, the nonparametric Kruskal-Wallis test is used for more than
2 independent groups of data. It can be used for comparison of upgradient water
quality to water quality from many downgradient wells in one procedure.
Alternatively, if the wells are grouped by some characteristic (e.g., depth,
geology, location, season), comparisons among other groups can be made.
If the null hypothesis (no change) is rejected by Kruskal-Wallis (i.e., the test
statistic exceeds the tabulated critical value), then pairwise comparisons should be
made to determine what wells are contaminated (see Gilbert (1987),
Section 18.2.2; the EPA Addendum (1992a), Section 3.1; and the EPA Unified
Guidance (2009), Section 17.1.2). The underlying assumptions are the
distributions of the independent populations are identical in shape (variance), but
the distributions need not to be symmetric.
t-test
- The t-test is a parametric, ANOVA type of test used to assess differences
in means of two independent groups. This test assumes normal distributions and
equal variances for both groups. The t-test is best limited to situations where the
data sets are too small to use nonparametric procedures. For example, if
background water quality is limited to two or three samples, the t-test can be used
to test for differences between background and compliance data.
c)
Trend Tests
Considerations
- When monitoring data have been collected over several years or
more, trend tests allow the determination of the change in distribution of data over
time. In addition to water quality trends, a time series of monitoring data may
contain characteristics of seasonality and serial correlation. Other complicating
factors include changes in laboratories or procedures involving the sampling and
analysis of the analyte.

261-0300-101 / DRAFT December 16, 2017 / Page III-60
Seasonality and serial correlation interfere with trend tests either by reducing the
power to detect trends or giving erroneous probabilities. Correction for
seasonality is available for tests presented here. Serial correlation exists if a data
point value is at least partially dependent on nearby data point values. For a given
data set, serial correlation decreases with increasing temporal distance between
samples. Harris,
et al.
(1987) reported difficulty detecting serial correlation in
10 years or less of quarterly groundwater data. Therefore, correction is not
recommended for quarterly data. Serial correlation correction is available for the
Seasonal Kendall trend test (Hirsch and Slack, 1984), but has reduced power with
small data sets and is not recommended for a monthly time series that is less than
5 years.
Parametric Trend Tests
- Parametric trend tests are based on regression methods
and allow compensation for exogenous effects (outside influences). Regression
analysis between two variables can be used to calculate the correlation coefficient
(r). The closer r is to one, the closer the relationship is between the two variables.
A t-test of correlation can be done on r to see if it is significant (see Davis, 1987,
Chapter 2; EPA, 1996, Section 4.3.2; EPA, 2009).
Mixed (i.e., parametric and nonparametric methods) methods also are available
when removing the effects of exogenous variables. Helsel and Hirsch (1992)
present a thorough review of trend analysis. Methods for detecting trends also are
presented in Chapter 16 of Gilbert (1987).
Because regression techniques are based on the assumption of a normal
distribution of the data, a nonparametric approach may have to be used.
Nonparametric Trend Tests
- The Mann-Kendall trend test is a nonparametric
test for monotonic (steadily upward or downward) trend. (Gilbert, 1987;
Section 4.3.4 of EPA, 1996; Section 17.3.2 of EPA, 2009).
This test requires constant variance in data. Non-constant variance may be
changed to constant variance with a power transformation. Logarithm
transformation is usually most appropriate. This transformation does not affect
the test statistic. Decision rules, exact test tables, normal approximation formulas,
and correction for ties can be found in Helsel and Hirsch (1992); Gilbert (1987)
and many introductory statistics texts. When a trend is present, the slope of fitted
line can be estimated using Sen’s estimator (see Gilbert, 1987; Section 4.3.3 of
EPA, 1996; Section 17.3.3 of EPA, 2009).
The Seasonal Kendall trend test is a seasonally corrected Mann-Kendall trend test.
This should be applied when time series graphs or boxplots of data indicate the
presence of seasonal variation. See Chapter 17 of Gilbert (1987).
The following sections present the methodology of several statistical tests which
may be utilized in the course of demonstrating attainment of an Act 2 standard.
Again, it is worthwhile to note that statistical computer software, such as EPA’s
ProUCL, has been developed to perform these tests.

261-0300-101 / DRAFT December 16, 2017 / Page III-61
6.
Calculation of UCL of Mean When the Distribution of the Sampling Mean is
Normal
The following is a step-by-step description of the approach used to calculate confidence
limits of an arithmetic mean when the distribution of the sampling mean is normal. For
data sets of lognormal distribution, the approach in Section III.B.7 should be used
instead.
1.
Calculate the sample mean by dividing the sum of the total readings by the total
number of readings:
X
= (X
1
+ X
2
+ Xn)/n
2.
Calculate the sample variance (Sb
2
) by taking the sum of the squares of each
reading minus the mean and dividing by the degrees of freedom (df, the total
number of samples minus one):
Sb
2
= [(X
1
-
X
)
2
+ (X
2
-
X
)
2
+ +(Xn-
X
)
2
]/(n-1)
3.
Calculate the standard deviation (Sb) by taking the square root of the variance
(Sb
2
):
Sb =
?
Sb
2
4.
Calculate the standard error of the mean (Sx). Standard error is inversely
proportional to the square root of the number of samples (increasing n from 4 to
16 reduces Sx by 50%) where Sx equals Sb/
n
. [Note: The above procedure is
for simple random samples. For systematic sampling, the calculation of standard
error should follow instructions in Section 6.5 of EPA soil attainment guidance
(EPA, 1989b). For multiple systematic sampling, the equation to calculate
unbiased estimate of variance is also available (Gilbert, 1987, p. 97).]
5.
Since the concern is only whether the upper limit of a confidence interval is below
or above the Act 2 regulatory threshold (RT), the lower confidence limit (LCL)
need not be considered. The upper confidence limit (UCL) can be calculated
using the one-tailed (one-sided) t values with n-1 degrees of freedom (df) derived
from a table of the student’s t distribution, t
1-a, n-1
(Table III-3).
6.
The 95% UCL (?=0.05; one-sided) is calculated by using the following formula
and substituting the values determined above plus the appropriate t value obtained
from the student’s t table where UCL equals
X
+t
1-a, n-1
*Sx.
The UCL number resulting from this formula will indicate with a 95% probability
that it is either above or below the Act 2 regulatory threshold (RT) developed for
the regulated substance subjected to the test.

261-0300-101 / DRAFT December 16, 2017 / Page III-62
7.
Calculation of UCL of Mean of a Lognormal Distribution
Following is a step-by-step description of the approach used to calculate confidence
limits of an arithmetic mean when the distribution of the data set is lognormal. This
method is used in risk assessment by EPA (EPA, 1992d).
1.
Transform all sample data Xi to Yi (i = 1,2,….n) using the natural logarithm
function:
Yi = ln Xi
2.
Calculate the arithmetic mean of transformed data by dividing the sum of the
transformed data by the total number of data:
Y
= (Y
1
+ Y
2
+ Yn)/n
3.
Calculate the variance (Sy
2
) of transformed data by taking the sum of the squares
of each data minus the mean and dividing by the degrees of freedom (df, the total
number of samples minus one):
Sy
2
= [(Y
1
-
Y
)
2
+ (Y
2
-
Y
)
2
+ +(Yn-Y
)
2
]/(n-1)
4.
Calculate the standard deviation (Sy) by taking the square root of the variance
(Sy
2
):
Sy =
?
Sy
2
5.
Since the concern is only whether the upper limit of a confidence interval is below
or above the Act 2 regulatory threshold (RT), the lower confidence limit (LCL)
need not be considered. The UCL can be calculated using the one-tailed
(one-sided) H
1-a
values associated with sample size n from the table of H
1-a
for
computing a one-sided upper 95% confidence limit on a lognormal mean.
6.
The 95% UCL (?=0.05; one-sided) is calculated by using the following formula
and substituting the values determined above plus the appropriate H
1-a
value
obtained from the table of H
1-a
where UCL equals
exp?Y
?
05
. *Sy
?
Sy * H
?
/ n
?1
2
1?
.
The UCL number resulting from this formula will indicate with a 95% probability
that it is either above or below the Act 2 regulatory threshold (RT) developed for
the regulated substance subjected to the test.
Note: The H
1-a
tables can be found in “Selected Tables in Mathematical
Statistics, Volume III, American Mathematical Society,” pp. 385-419, C. E. Land,
1975. A subset of Land’s tables also can be found in “Statistical Methods for

261-0300-101 / DRAFT December 16, 2017 / Page III-63
Environmental Pollution Monitoring,” Tables A10-A13, R. O. Gilbert, 1987. The
value of H
1-a
depends on Sy, n, and the confidence level
?.
If H
1-a
is required for
values of Sy and n not given in the tables, Land (1975) indicated that four-point
Lagrangian interpolation appeared to be adequate with these tables.
The equation used in four-point Lagrangian interpolation is:
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
y
fx
yxx
xxxx
x
xx
xx
x
xxyxxxx
x
xx
xx
x
xxxxyxx
x
xx
xx
x
xxxx
xxy
x
xx
xx
x
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
1
2
3
4
1
2
1
3
1
4
1
2
3
4
2
1
2
3
2
4
1
2
3
4
3
1
3
2
3
4
1
2
3
4
4
1
4
2
4
3
where
y
f x
1
1
?
()
y
fx
2
2
?
(
)
y
fx
3
3
?
()
y
fx
4
4
?
(
)
The interpolation procedure may include four interpolation steps which are
performed along the columns of the table and one interpolation step performed
along the rows of the table. The following example illustrates the procedure to
apply the four-point Lagrangian interpolation:
The above table only provides values for sample sizes of 3, 5, 7, and 10, and Sy
values of 0.1, 0.2, 0.3 and 0.4. To interpolate a value for a sample size of 6 and
an Sy value of 0.25, the first step is to interpolate a value corresponding to an Sy
of 0.25 and a sample size of 3 using the four-point Lagrangian interpolation
equation, where
x
= 0.25
x
1
= 0.10
y
1
= 2.750
H
1-A
Sample Size, n
Table
3
5
7
10
0.1
2.750 2.035 1.886 1.802
0.2
3.295 2.198 1.992 1.881
Sy 0.3
4.109 2.402 2.125 1.977
0.4
5.220 2.651 2.282 2.089

261-0300-101 / DRAFT December 16, 2017 / Page III-64
x
2
= 0.20
y
2
= 3.295
x
3
= 0.30
y
3
= 4.109
x
4
= 0.40
y
4
= 5.220
The result of this interpolation step is
y
=
f
(0.25)
?
3.667.
The second step is to interpolate a value corresponding to Sy of 0.25 and a sample
size of 5 using the four-point Lagrangian interpolation equation, where
x
= 0.25
x
1
= 0.10
y
1
= 2.035
x
2
= 0.20
y
2
= 2.198
x
3
= 0.30
y
3
= 2.402
x
4
= 0.40
y
4
= 2.651
The result of this interpolation step is
y
=
f
( 0 . 25 )
2.295.
The third step is to interpolate a value corresponding to an Sy of 0.25 and a
sample size of 7 using the four-point Lagrangian interpolation equation, where
x
= 0.25
x
1
= 0.10
y
1
= 1.886
x
2
= 0.20
y
2
= 1.992
x
3
= 0.30
y
3
= 2.125
x
4
= 0.40
y
4
= 2.282
The result of this interpolation step is
y
=
f
( 0 . 25 )
2.055.
The fourth step is to interpolate a value corresponding to an Sy of 0.25 and a
sample size of 10 using the four-point Lagrangian interpolation equation, where
x
= 0.25

261-0300-101 / DRAFT December 16, 2017 / Page III-65
x
1
= 0.10
y
1
= 1.802
x
2
= 0.20
y
2
= 1.881
x
3
= 0.30
y
3
= 1.977
x
4
= 0.40
y
4
= 2.089
The result of this interpolation step is
y
=
f
( 0 . 25 )
1.927.
The last step is using the results obtained from steps 1 - 4 to perform another
four-point Lagrangian interpolation to generate a value corresponding to an Sy of
0.25 and a sample size of 6, where
x
= 6
x
1
= 3
y
1
= 3.667
x
2
= 5
y
2
= 2.295
x
3
= 7
y
3
= 2.055
x
4
= 10
y
4
= 1.927
The resulted interpolation value is 2.087.
8.
Procedure and Example for Conducting the Wilcoxon Rank Sum Test
Procedure
For each cleanup unit and pollution parameter, use the following procedure to compute
the WRS test statistic and to determine on the basis of that statistic if the cleanup unit
being compared with the background reference area has attained the background
standard.
1.
Collect the m samples in the reference area and the n samples in the cleanup unit
(m + n = N).
2.
Measure each of the N samples for the pollution parameter of interest.
3.
Consider all N data as one data set. Rank the N data from 1 to N; that is, assign
the rank 1 to the smallest datum, the rank 2 to the next smallest datum, and the
rank N to the largest datum.

261-0300-101 / DRAFT December 16, 2017 / Page III-66
4.
If several data are tied, i.e., have the same value, assign them the midrank, that is,
the average of the ranks that would otherwise be assigned to those data.
5.
If some of the reference-area and/or cleanup-unit data are less-than data (i.e., data
less than the limit of detection) consider these less-than data to be tied at a value
less than the smallest measured (detected) value in the combined data set. Assign
the midrank for the group of less-than data to each less-than datum. For example,
if there were 10 less-than data among the background reference and cleanup-unit
measurements, they would each receive the rank 5.5, which is the average of the
ranks from 1 to 10. The assumption that all less-than measurements are less than
the smallest detected measurement should not be made lightly because it may not
be true for some pollution parameters, as pointed out by Lambert et al. (1991).
However, the development of statistical testing procedures to handle this situation
are beyond the scope of this document.
i.
The above procedure is applicable when all measurements have the same
limit of detection. When there are multiple limits of detection, the
adjustments given in Millard and Deveral (1988) may be used.
ii.
Do not compute the WRS test if more than 40% of either the reference-
area or cleanup unit measurements are less-than values. However, still
conduct the Quantile test.
6.
Sum the ranks of the n samples from the cleanup unit. Denote this sum by WRS.
7.
If both m and n are less than or equal to 10 and no ties are present, conduct the
test of H
o
(cleanup standard attained, Pr = 1/2) versus H
a
(cleanup standard not
attained, Pr > 1/2) by comparing WRS to the appropriate critical value in
Table A.5 in Hollander and Wolfe (1973). Then go to Step 12 below.
8.
If both m and n are greater than 10, go to Step 9. If m is less than 10 and n is
greater than 10, or if n is less than 10 and m is greater than 10, or if both m and n
are less than or equal to 10 and ties are present, then consult a statistician to
generate the required tables.
9.
If both m and n are greater than 10 and ties are not present, compute
Equation A3-1 and go to Step 11.
i.
?
?
1 12
12
?
?
?
?
mn N
WRS
nN
Zrs
(A3-1)
10.
If both m and n are greater than 10 and ties are present, compute
i.
?
?
          
?
?
?
?
?
?
?
?
?
?
?
?
g
j
nm
N
t
j
t
j
NN
WRS
nN
Zrs
1
2
/12
1
1
1
1 /2
(A3-2)

261-0300-101 / DRAFT December 16, 2017 / Page III-67
ii.
where g is the number of tied groups and t
j
is the number of tied
measurements in the jth group.
11.
Reject H
o
(cleanup standard attained) and accept H
a
(cleanup standard not
attained) if
Zrs
(from Equation A3-1 or A3-2, whichever was used) is greater than
or equal to Z
1-?
, where Z
1-?
is the value that cuts off 100?% of the upper tail of
the standard normal distribution.
12.
If H
o
is not rejected, conduct the Quantile test.
EXAMPLE
TESTING PROCEDURE FOR THE WILCOXON RANK SUM TEST
1.
Suppose that the number of samples was determined using the following
specification:
 
= specified Type II error rate = 0.30
?
= specified Type I error rate = 0.05
c = specified proportion of the total number of required samples, N, that will be
collected in the reference area = 0.50
Pr = specified probability greater than 1/2 and less than 1.0 that a measurement of
a sample collected at a random location in the cleanup unit is greater than a
measurement of a sample collected at a random location in the reference
area = 0.75
R = expected rate of missing or unusable data = 0.10
For these specifications we found that m = n = 14 based on Noether’s formula.
2.
Rank the reference-area and cleanup-unit measurements from 1 to 28, arranging
the data and their ranks as illustrated. Measurements below the limit of detection
are denoted by ND and assumed to be less than the smallest value reported for the
combined data sets. The data are lead measurements (mg/kg).
3.
The sum of the ranks of the cleanup unit is
WRS = 3 + 7 + ... + 27 + 28 = 272.
4.
Compute Zrs using Equation A3-2 because ties are present. There are t = 5 tied
values for the g = 1 group of ties (ND values). We obtained:
?
?
?
?
? ?
?
Zrs
?
?
?
?
?
?
?
272 1428 1
2
14 1412 28 1 55 5 1
2828 1
/
*
*

261-0300-101 / DRAFT December 16, 2017 / Page III-68
?
?
69
21704
318
.
.
5.
From the table of z (Table III-4) we find that Z
1-?
= 1.645 for
?
= 0.05 (? = 0.05,
the Type I error rate for the test, was specified in Step 1 above). Since 3.18 >
1.645, we reject the null hypothesis H
o
: Pr = 1/2 and accept the alternative
hypothesis H
a
: Pr > 1/2.
6.
Conclusion:
The cleanup unit does not attain the cleanup standard of Pr = 1/2. This test result
occurred because most of the small ranks were for the reference area and most of
the large ranks were for the cleanup unit. Hence, WRS was large enough for H
o
to be rejected.
Example - Wilcoxon Rank Sum Test
Reference Area
Cleanup Unit
Data
Rank
Data
Rank
ND
3
ND
3
ND
3
ND
3
ND
3
39
6
48
7
49
8
51
9
53
10
59
11
61
12
65
13
67
14
70
15
72
16
75
17
80
18
82
19
89
20
100
21
150
22
164
23
193
24
208
25
257
26
265
27
705
28
WRS = 272

261-0300-101 / DRAFT December 16, 2017 / Page III-69
9.
Procedure and Example for Conducting the Quantile Test
Table Look-Up Procedure
A simple table look-up procedure for conducting the Quantile test when m and n are
specified
a priori
is given in this section. It is assumed that m and n representative
measurements have been obtained from the reference area and the cleanup unit,
respectively. The procedure in this section is approximate because the Type I error rate,
?,
of the test may not be exactly what is required. However, the difference between the
actual and required levels will usually be small. Moreover, the exact
?
level may be
computed.
The testing procedure is as follows:
1.
Specify the required Type I error rate,
?.
The available options in this document
are
?
equal to 0.01, 0.025, 0.05 and 0.10.
2.
Turn to Table A.6, A.7, A.8, or A.9 in Appendix A of EPA 1992 guidance
document (EPA, 1992c) if
?
is 0.01, 0.025, 0.05, or 0.10, respectively.
3.
Enter the selected table with m and n (the number of reference-area and cleanup-
unit measurements, respectively) to find
values of r and k needed for the Quantile test.
actual
?
level for the test for these values of r and k (the actual
?
may
differ slightly from the required
?
level in Step 1)
4.
If the table has no values of r and k for the values of m and n, enter the table at the
closest tabled values of m and n. In that case, the
?
level in the table will apply to
the tabled values of m and n, not the actual values of m and n. However, the
?
level for the actual m and n can be computed using the following equations:
?
?
?
?
?
?
?
?
?
?
mnr
ni
r
i
mn
n
ik
r
(A4-1)
where
a
b
a
bab
?
?
?
!
!(
)!
and
a
!
?
a
*(
a
?1)*(
a
?2)*.....*3*
2 *1
5.
Order from smallest to largest the combined m + n = N reference-area and
cleanup-unit measurements for the pollution parameter. If measurements less
than the limit of detection are present in either data set, assume that their values
are less than the rth largest measured value in the combined data set of

261-0300-101 / DRAFT December 16, 2017 / Page III-70
N measurements (counting down from the maximum measurement). If fewer
than r measurements are greater than the limit of detection, then the Quantile test
cannot be performed.
6.
If the rth largest measurement (counting down from the maximum measurement)
is among a group of tied (equal-in-value) measurements, then increase r to include
that entire set of tied measurements. Also increase k by the same amount. For
example, suppose from Step 3 we have r = 6 and k = 6. Suppose the 5th through
8th largest measurements (counting down from the maximum measurement) have
the same value. Then we would increase both r and k from 6 to 8.
7.
Count the number, k, of measurements from the cleanup unit that are among the r
largest measurements of the ordered N measurements, where r and k were
determined in Step 3 (or Step 6 if the rth largest measurement is among a group of
tied measurements).
8.
If the observed k (from Step 7) is greater than or equal to the tabled value of k,
then reject H
o
and conclude that the cleanup unit has not attained the reference
area cleanup standard (? = 0 and
?/
= 0).
9.
If H
o
is not rejected, then do the WRS test. If the WRS test indicates the H
o
should be rejected, then additional remedial action may be necessary.
EXAMPLE
TABLE LOOK-UP TESTING PROCEDURE FOR THE QUANTILE TEST
1.
We illustrate the Quantile test using the measurements listed in the example of
Section III.B.8. There are 14 measurements in both the reference area and the
cleanup unit. Suppose we specify
?=
0.05 for this Quantile test.
2.
Turn to Table A.8 in EPA 1992 guidance (EPA, 1992c; because the table is for
?
= 0.05). We see that there are no entries in that table for m = n = 14. Hence,
we enter the table with n = m = 15, the values closest to 14. For n = m = 15 we
find r = 4 and k = 4. Hence, the test consists of rejecting the H
o
if all 4 of the
4 largest measurements among the 28 measurements are from the cleanup unit.
3.
The N = 28 largest measurements are ordered from smallest to largest in the
Example of Section III.B.8.
4.
From the Example of Section III.B.8, we see that all 4 of the r = 4 largest
measurements are from the cleanup unit. That is, k = 4.
5.
Conclusion:
Because k = 4, we reject the H
o
and conclude that the cleanup unit has not
attained the cleanup standard of?? = 0 and
?/
= 0. The Type I error level of this
test is approximately 0.05.

261-0300-101 / DRAFT December 16, 2017 / Page III-71
Note: The exact Type I error level,
?,
for this test is not given in Table A.8 in EPA 1992
guidance (EPA, 1992c) because the table does not provide r, k, and
?
for m = n = 14.
However, the exact
?
level can be computed using Equation (A4-1).
The remediator is reminded that the Quantile Test can be run using EPA’s ProUCL free
statistical software, version 4.0.
REFERENCES
CLEVELAND, W.S., 1993, Visualization Data, Hobart Press, Summit, N.J., 360 pp.
CONOVER, N.J., 1980, Practical Nonparametric Statistics, 2nd ed., John Wiley and
Sons, New York, 493 pp.
COCHRAN, W.G., 1977, Sampling Techniques, 3rd ed., John Wiley and Sons, New
York.
DAVIS, C.B., and MCNICHOLS, R.J., 1994, Ground Water Monitoring Statistics
Update: Part I: Progress Since 1988, in Ground Water Monitoring and Remediation,
pp. 148-158.
DAVIS, C.B., and MCNICHOLS, R.J., 1994, Ground Water Monitoring Statistics
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EDLAND, S. D., and van BELLE, G., 1994, Decreased Sampling Costs and Improved
Accuracy with Composite Sampling, in Chapter 2 of Environmental Statistics,
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GIBBONS, J.D., 1990, Nonparametric Statistics, Chapter 11 of Handbook of Statistical
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New York.
GILBERT, R.O., 1987, Statistical Methods for Environmental Pollution Monitoring, Van
Nostrand Reinhold, New York, 320 pp.
HARRIS, J., LOFTIS, J.C., and MONTGOMERY, R.H., 1987, Statistical Methods for
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HELSEL, D.R., and HIRSCH, R.M., 1992, Statistical Methods in Water Resources,
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HIRSCH, R.M., and SLACK, J.R., 1984, A Nonparametric Trend Test for Seasonal Data
with Serial Dependence, in Water Resources Research, v.20, no.6, pp. 727-735.
IMAN, R.L., and CONOVER, W.J., 1983, A Modern Approach to Statistics, John Wiley
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ITRC (Interstate Technology & Regulatory Council), 2013. Groundwater Statistics and
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JOHNSON, R.A., VERRILL, S., and MOORE II, D.H., 1987, Two Sample Rank Tests
for Detecting Changes That Occur in a Small Proportion of the Treated Population, in
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LAMBERT, D., PETERSON B., and TERPENNING, I., 1991, Nondetects, Detection
Limits, and the Probability of detection, Journal of the American Statistical association,
86, 266-277.
MILLARD, S. P., and DEVERAL, S. J., 1988, Nonparametric Statistical Methods for
Comparing Two Sites Based on Data with Multiple Nondetect Limits. Water Resources
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OGDEN ENVIRONMENTAL AND ENERGY SERVICES CO., INC., 1997, Final
Report, Act 2 Cleanup Standards, Evaluation of Proposed Chapter 250, Work
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OTT, L., 1988, An Introduction to Statistical Methods and Data Analysis, 3rd ed., PWS-
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PA APPLICABILITY AND ATTAINMENT SUBCOMMITTEE (PA AASC).
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Publishers, Boca Raton, 418 pp.
PETTYJOHN, W.A., 1982, Cause and effect of Cyclic Changes in Ground Water
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USEPA, 1989. Risk Assessment Guidance for Superfund: Volume 1 - Human Health
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USEPA 1992a, Statistical Analysis of Groundwater Monitoring Data at RCRA Facilities:
Addendum to Interim Final Guidance, Office of Solid Waste, EPA/530-R-93003.
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261-0300-101 / DRAFT December 16, 2017 / Page III-74
Table III-2: Random Number Table
67 35 39 82 14
21 81 21 96 81
65 41 49 04 80
38 34 13 03 15
96 42 55 62 54
43 25 59 81 92
29 54 98 87 58
77 38 02 09 27
06 83 23 00 90
63 39 04 52 72
93 16 47 22 58
33 01 43 61 70
10 55 75 64 68
40 17 24 98 10
53 93 00 31 43
76 77 01 14 64
62 38 18 48 04
77 42 32 38 34
34 34 91 42 14
98 51 98 29 05
69 46 32 94 85
32 27 87 78 37
73 39 25 48 92
91 57 68 52 55
11 08 99 13 55
79 92 47 00 30
13 95 52 30 16
41 45 60 80 42
90 05 38 89 84
04 33 13 21 72
84 35 41 19 11
63 65 09 06 44
43 71 87 58 78
95 27 91 41 54
10 42 38 55 83
18 57 74 64 75
42 79 88 46 32
90 31 29 09 90
07 59 89 22 74
50 05 90 43 37
14 18 29 77 76
54 35 67 41 92
09 28 91 97 68
05 60 09 22 47
04 96 99 06 24
49 02 18 20 81
94 15 81 23 52
28 84 83 75 19
13 55 96 13 70
49 79 66 85 27
49 44 95 16 39
39 13 83 99 97
38 48 63 01 40
03 95 68 71 39
36 99 24 29 55
62 07 74 32 26
41 64 83 37 57
55 37 51 98 24
99 16 02 88 85
13 65 61 81 59
75 35 06 72 07
45 22 98 59 25
90 22 41 03 96
33 89 33 58 78
01 32 36 92 82
12 50 08 09 64
33 54 62 98 24
41 72 97 33 34
11 73 67 33 79
95 62 31 23 87
16 95 18 38 50
33 78 48 00 83
01 43 77 97 26
74 84 53 05 49
29 75 77 02 32
76 23 56 61 20
15 68 82 18 28
35 82 40 18 40
31 78 53 98 45
21 87 21 31 95
74 26 53 14 97
14 09 11 22 65
74 81 52 44 80
03 86 84 78 02
55 45 90 71 49
93 69 54 96 15
66 92 23 22 51
38 42 26 71 37
01 70 87 82 47
97 83 49 24 10
85 99 75 39 81
83 56 56 87 09
32 47 40 14 72
95 74 21 08 69
47 94 65 84 88
86 43 28 23 92
54 05 55 03 89
12 57 75 16 83
36 93 99 23 59
67 24 69 74 30
22 91 19 64 96
84 66 44 09 48
80 12 65 25 43
76 36 68 27 47
52 35 61 03 33
65 82 01 56 34
08 22 38 56 21
68 55 13 18 97
45 90 91 27 25
92 06 69 84 31
51 41 63 38 07
27 96 11 21 06
24 45 33 45 37
44 40 67 80 81
39 80 77 98 43
97 80 96 04 25
30 36 44 40 25
84 23 42 79 14
41 11 64 23 14
38 29 48 18 65
89 63 32 14 59
33 78 24 52 88
02 79 97 35 74
67 96 31 61 18
00 44 59 88 88
54 14 28 53 79
48 05 74 00 98
15 74 72 91 47
45 90 66 55 38
99 60 85 09 01
77 14 06 84 47
46 88 91 03 36
75 64 77 72 11
96 46 87 33 07
29 48 37 86 66
67 33 09 75 00
76 85 28 80 71
36 29 40 32 52
52 72 89 43 05
89 50 25 84 26
75 48 93 50 88
27 76 21 90 66
48 55 88 37 76
57 00 14 83 60
67 20 35 37 18
75 86 22 20 23
27 17 67 16 38
16 33 28 72 13
47 84 57 36 12
75 86 75 23 51
40 41 19 44 32
22 13 31 25 77
28 93 89 37 04
52 71 49 87 72
32 30 69 94 36
70 94 88 25 57
99 94 82 56 91
38 22 09 52 01
84 00 60 04 91
53 10 10 51 94
42 06 41 49 47
44 71 23 61 25
64 16 16 04 48
20 65 84 89 71
43 89 73 79 80
90 55 23 36 61
93 34 69 43 83
38 03 93 00 03
13 04 77 54 90
61 26 88 01 26
22 71 21 14 59
41 29 51 06 96
62 92 63 96 16
62 48 56 86 21
16 58 33 07 41
65 63 59 60 55
36 77 10 63 48
11 60 55 27 52
73 11 95 03 79
46 12 07 26 52
74 20 65 77 78
83 37 34 09 07
47 57 86 13 47
91 17 32 50 29
72 25 87 96 71
12 16 90 59 89
14 66 72 99 45
88 86 45 48 35
26 30 34 73 46
78 29 91 46 44
52 14 41 65 84
73 55 53 00 76
43 83 09 28 13
82 07 62 72 74
60 34 43 69 26
19 87 80 56 89
83 28 45 99 87
37 02 53 39 74
08 91 23 30 13
59 59 10 57 10
29 13 62 89 16
81 78 54 60 92
31 01 04 83 60
16 42 66 81 37
42 39 74 64 40
37 30 72 00 39
53 83 30 75 48
44 30 38 98 76
94 55 60 35 12
22 82 36 18 48
66 17 13 28 82
64 10 76 67 69
53 39 05 71 22
35 13 39 97 27
48 26 94 74 53
86 41 73 49 70
03 41 05 77 28
37 71 01 30 86
36 42 65 97 78
09 34 36 56 01
56 52 43 82 45
20 20 45 49 83
52 73 63 70 47
89 93 77 32 26
73 70 50 75 10
17 89 69 72 84
80 48 78 32 51
66 12 29 79 90
25 11 33 37 44
25 47 18 40 74
11 29 91 99 26
43 90 15 09 64
20 54 89 91 59
01 93 40 33 04
46 91 86 33 90
96 68 63 61 19
29 71 05 42 14
05 84 10 36 27
60 49 40 84 92
29 23 10 45 05
29 12 44 07 75
41 74 25 36 05
49 36 50 27 64
37 51 92 47 32
05 02 21 20 71
79 00 54 24 24
32 03 96 86 98
90 65 41 87 39
29 39 75 07 20
14 94 28 87 23

261-0300-101 / DRAFT December 16, 2017 / Page III-75
EXAMPLE
USING THE RANDOM NUMBER TABLE (TABLE III-2)
Assume we need to select 10 random numbers with four digits between 0000 and 6000.
We need to select a starting point on the table and a path to be followed. The common
way to locate a starting point is to look away and arbitrarily point to a starting point.
Suppose the number we located this way was 3848. (It is located in the upper left corner
of the block that is in the third large block from the left and the third large block down.)
From here we will proceed down the column, then go to the top of the next set of
columns, if necessary. The first selected number is 3848. Proceeding down the column,
we find 5537 next. This is the second selected number. The number 9022 is next. This
number is discarded. Continue down this column, the selected 10 random numbers will
be 3848, 5537, 4172, 0143, 3582, 3842, 3247, 1257, 2445, and 0279. (The numbers
9022, 7481, 8012, 6855 and 8423 were discarded because they are greater than 6000.)

261-0300-101 / DRAFT December 16, 2017 / Page III-76
Table III-3: Student’s t-Distribution for Selected Alpha and Degrees of Freedom
?
for determining t
1-a,n-1
one-tailed
0.450
0.250
0.200
0.100
0.050
0.025
0.010
0.005
?
for determining t
1-a/2,n-1
two-tailed
0.900
0.500
0.400
0.200
0.100
0.050
0.020
0.010
1
0.158
1.000
1.376
3.078
6.314
12.706
31.821
63.657
2
0.142
0.816
1.061
1.886
2.920
4.303
6.925
9.925
3
0.137
0.765
0.978
1.638
2.353
3.182
4.541
5.841
4
0.134
0.741
0.941
1.533
2.132
2.776
3.747
4.604
5
0.132
0.727
0.920
1.476
2.015
2.571
3.365
4.032
6
0.131
0.718
0.906
1.440
1.943
2.447
3.143
3.707
7
0.130
0.711
0.896
1.415
1.895
2.365
2.998
3.499
8
0.130
0.706
0.889
1.397
1.860
2.306
2.896
3.355
9
0.129
0.703
0.883
1.383
1.833
2.262
2.821
3.250
10
0.129
0.700
0.879
1.372
1.812
2.228
2.764
3.169
11
0.129
0.697
0.876
1.363
1.796
2.201
2.718
3.106
12
0.128
0.695
0.873
1.356
1.782
2.179
2.681
3.055
13
0.128
0.694
0.870
1.350
1.771
2.160
2.650
3.012
14
0.128
0.692
0.868
1.345
1.761
2.145
2.624
2.977
15
0.128
0.691
0.866
1.341
1.753
2.131
2.602
2.947
16
0.128
0.690
0.865
1.337
1.746
2.120
2.583
2.921
17
0.128
0.689
0.863
1.333
1.740
2.110
2.567
2.898
18
0.127
0.688
0.862
1.330
1.734
2.101
2.552
2.878
df
19
0.127
0.688
0.861
1.328
1.729
2.093
2.539
2.861
20
0.127
0.687
0.860
1.325
1.725
2.0S6
2.528
2.845
21
0.127
0.686
0.859
1.323
1.721
2.080
2.518
2.831
22
0.127
0.686
0.858
1.321
1.717
2.074
2.508
2.819
23
0.127
0.685
0.858
1.319
1.714
2.069
2.500
2.807
24
0.127
0.685
0.857
1.318
1.711
2.064
2.492
2.797
25
0.127
0.684
0.856
1.316
1.708
2.060
2.485
2.787
26
0.127
0.684
0.856
1.315
1.706
2.056
2.479
2.779
27
0.127
0.684
0.855
1.314
1.703
2.052
2.473
2.771
28
0.127
0.683
0.855
1.313
1.701
2.048
2.467
2.763
29
0.127
0.683
0.854
1.311
1.699
2.045
2.462
2.756
30
0.127
0.683
0.854
1.310
1.697
2.042
2.457
2.750
40
0.126
0.681
0.851
1.303
1.684
2.021
2.423
2.704
60
0.126
0.679
0.848
1.296
1.671
2.000
2.390
2.660
120
0.126
0.677
0.845
1.289
1.658
1.980
2.358
2.617
?
0.126
0.674
0.842
1.282
1.645
1.960
2.326
2.576

261-0300-101 / DRAFT December 16, 2017 / Page III-77
Table III-4: Table of z for Selected Alpha
?
Z
1??
0.450
0.124
0.400
0.253
0.350
0.385
0.300
0.524
0.250
0.674
0.200
0.842
0.100
1.282
0.050
1.645
0.025
1.960
0.010
2.326
0.0050
2.576
0.0025
2.807
0.0010
3.090

261-0300-101 / DRAFT December 16, 2017 / Page III-78
C.
Storage Tank Program Guidance
1.
Corrective Action Process
The corrective action process (CAP) for storage tanks regulated under The Storage Tank
and Spill Prevention Act (35 P.S. §§ 6021.101-6021.2104) was established in 25 Pa.
Code Chapter 245 Subchapter D on August 21, 1993 (23 Pa.B. 4033), and revised on
December 1, 2001(31 Pa.B. 6615). These regulations provide a streamlined and flexible
approach to corrective action. In cases where interim remedial actions (e.g., excavation
of contaminated soil) can adequately address a release, the person performing the cleanup
is only required to submit one report (site characterization) to the Department. Where
localized contamination is associated with the closure of a regulated storage tank system,
the Department has offered a standardized closure report form, which may be used to
satisfy the site characterization report requirements. The regulation is flexible in that it
authorizes the Department to waive or combine elements of the CAP based on the
complexity of the release. For example, a responsible party may submit the site
characterization report and remedial action plan as one report in some instances.
The CAP regulations allow Act 2 cleanup standards to be used to demonstrate
remediation of releases from regulated storage tanks. In order to facilitate cleanups, the
Department has identified those regulated substances, or “chemicals of concern,” that
should be quantified by the laboratory for commonly encountered petroleum products.
These substances and the accompanying methodologies should be utilized to demonstrate
attainment for storage tank remediations as well as other remediations involving
petroleum products. Only these substances need to be analyzed and evaluated when
petroleum products are released if they are not contaminated by other sources. These
analytical requirements appear in the
Site Assessment Sampling Requirements at
Regulated Storage Tank System Closures
booklet number 2630-BK-DEP4699 and as
Table III-5 in this manual. The Department does not recommend analysis for indicator
parameters such as total petroleum hydrocarbons, as they have no standards established
by Act 2.
For remediations conducted under the CAP, the person performing the remediation must
demonstrate attainment of an Act 2 standard (25 Pa. Code § 245.313(b)). Upon approval
by the Department of the report demonstrating attainment, the person is eligible for Act 2
liability protection.
2.
Corrective Action Process Checklist
The flow chart in Figure III-9 shows the major steps and the decision-making process that
responsible parties must follow when a release from a regulated storage tank is
confirmed. This process was designed to be as flexible as possible in order to
accommodate the wide range of specific circumstances associated with releases. The
following are the major steps of the process:

261-0300-101 / DRAFT December 16, 2017 / Page III-79
Figure III-9
The Regulated Storage Tank Corrective Action Process Flowchart

261-0300-101 / DRAFT December 16, 2017 / Page III-80
If a release is confirmed, owners or operators must notify the DEP regional office
responsible for the county in which the release occurred, by telephone in
accordance with 25 Pa. Code § 245.305, within 24 hours of confirmation of a
release. In addition to basic facility and owner information, the notice must
provide, to the extent information is available:
?
the regulated substance involved;
?
the quantity of the regulated substance involved;
?
when and where the release occurred;
?
the affected environmental media;
?
impacts to water supplies, buildings, sewer or other utility lines;
?
interim remedial actions planned, initiated, or completed; and
?
a description of the release.
Within 15 days of the telephone notice, the owner or operator must follow up with
a written notification to the appropriate DEP regional office and any municipality
impacted by the release. This written notice must include the same information as
provided in the telephone notification and also should include any new
information obtained within the 15 days.
The owner or operator must provide follow-up written notification to the
Department and any impacted municipality regarding new impacts to
environmental media or water supplies, buildings or sewer or other utility lines,
not previously reported, within 15 days of their discovery.
The Department has prepared a form, number 2630-FM-BECB0082, which can
be used to satisfy the written notification requirements. In situations where the
release is small, contained and immediately cleaned up, this form may be all that
is necessary to complete the CAP.
Also, upon confirmation of a release, responsible parties must immediately
initiate interim remedial actions. These are required response actions from the
time a release is confirmed until the time a formal long-term remedial action plan
is implemented. Interim remedial actions help maintain or restore public health
and safety and prevent the additional release of a regulated substance to the
environment and the spread of contamination.
Interim remedial actions may be all that are necessary to adequately address
certain releases. These releases may involve spills and overfills, and cases where
a release is confined to the excavation zone of an underground tank.

261-0300-101 / DRAFT December 16, 2017 / Page III-81
While all appropriate interim remedial actions must be taken in order to bring a
release under control, the first priority at any release site is to identify and
eliminate any threat to the health and safety of onsite personnel or nearby
residents. See 25 Pa. Code § 245.306 for requirements for interim remedial
actions. These interim actions can include:
?
checking for and venting product vapors from sewer lines or buildings that
have been impacted;
?
calling emergency personnel such as local fire and public safety officials
for assistance where fire, explosion or safety hazards exist;
?
relocating residents until potentially explosive vapors have been reduced
to safe levels;
?
restricting access to the site by nonessential personnel and establishing a
buffer area around the site;
?
recovering free product leaking into subsurface structures such as
basements and sewers.
Attention should be turned to preventing any further release of the regulated
substance to the environment either concurrently with these emergency actions, or
as soon as any immediate threats to human health and safety have been eliminated
or reduced to acceptable levels. Depending on the circumstances of the release,
this may involve:
?
scheduling and conducting the necessary tests to identify and confirm all
sources of the release;
?
removing product from the storage tanks;
?
removing the storage tanks;
?
excavating product-saturated soils;
?
recovering free product on the water table;
?
recovering product from the excavation;
?
placing booms in, or interceptor trenches along, streams, gullies or
drainageways where surface water has been impacted or may be impacted;
and
?
identifying and sampling affected water supplies or water supplies with
the potential to be affected, and reporting sampling results to the
Department and water supply owner within five days of receipt from the
laboratory.

261-0300-101 / DRAFT December 16, 2017 / Page III-82
Interim remedial actions planned, initiated or completed are to be indicated during
the telephone notification and updated in the 15-day initial and any subsequent
written notification as required in 25 Pa. Code § 245.305. A more detailed
discussion of interim remedial actions conducted at the site of the release is to be
included in the site characterization report. This report is required to be submitted
to the Department within 180 days of reporting a release.
Any responsible party that affects or diminishes a water supply as a result of a
release must restore or replace the affected or diminished water supply at no cost
to the owner of the supply (35 P.S. § 6021.1303(b)). A water supply is affected if
a measurable increase in a concentration of one or more contaminants occurs
(e.g., benzene or MTBE) in the water supply. A water supply is diminished if the
quantity of water provided by a water supply is decreased. For example, a water
supply well may lose flow as a result of groundwater pumping during a
remediation effort. (See definition of “affect or diminish” in 25 Pa. Code
§ 245.1). The requirement to restore or replace an affected or diminished water
supply remains with the responsible party regardless of attainment of an Act 2
standard.
The responsible party must provide a temporary water supply (e.g., bottled water
or water tank) to residents whose water supply is affected or diminished by the
release no later than 48 hours after the responsible party receives information, or
is notified by the Department, that a water supply has been affected or diminished
(25 Pa. Code § 245.307(c)).
The responsible party must provide a permanent water supply within 90 days after
the responsible party receives information, or is notified by the Department, that a
water supply has been affected or diminished (25 Pa. Code § 245.307(d)). A
permanent water supply may include a well or hookup to a public water supply or
treatment system. Where the responsible party provides the affected party with
access to a public system, the responsible party is not required to pay for the
quantity of water being supplied.
Responsible parties must properly handle, store and manage excavated
contaminated soil which commonly results from tank closures and interim
remedial actions (25 Pa. Code § 245.308). In general, petroleum contaminated
soil is a residual waste regulated under the Solid Waste Management Act
(SWMA) (35 P.S. §§ 6018.101-6018.1003) and must:
?
be stored in accordance with the Department’s residual waste management
regulations (25 Pa. Code Chapter 299) relating to standards for storage of
residual waste;
?
be completely and securely covered for the duration of the storage period,
with an impermeable material of sufficient strength, anchoring or
weighting to prevent tearing or lifting of the cover, infiltration of
precipitation or surface water, and exposure of the soil to the atmosphere;

261-0300-101 / DRAFT December 16, 2017 / Page III-83
?
be stored in a manner to prevent public access to the storage area,
including use of fencing, security patrols or warning signs; and
?
not present a threat to human health or the environment and must either be
undergoing active treatment or disposed of within 90 days from the first
day of storage. Active treatment includes methods such as enhanced
bioremediation in piles, soil vapor extraction and low-temperature thermal
desorption. Active treatment does not include letting the soil pile sit in
place.
At the same time as the interim remedial actions are taking place, responsible
parties must conduct a site characterization to determine the extent and magnitude
of contamination which has resulted from the release. The CAP regulations
provide the objectives of any site characterization and a list of elements that may
be necessary or required to be conducted (25 Pa. Code § 245.309). This manual
also provides information which should be considered when conducting site
characterization work at storage tank release sites. A site characterization report
must be submitted to the appropriate DEP regional office within 180 days of
confirming the release (25 Pa. Code § 245.310(a)). It is very important that the
site characterization report identify the Act 2 cleanup standard selected for the
remediation. Interpretations of geologic and hydrogeologic data should be
prepared by a professional geologist licensed in Pennsylvania.
Where interim remedial actions (e.g., removal of contaminated soil) have attained
the SHS, and soil is the only medium of concern, the responsible party may
submit a site characterization report to DEP limited to the elements in 25 Pa.
Code § 245.310(b). In this case, the site characterization report should describe
the entire CAP from site characterization to demonstration of attainment of the
SHS.
Where soil contamination no more than three feet from the tank system is the only
contamination observed during the closure of a storage tank system, the
responsible party may submit the appropriate Storage Tank System Closure
Report Form to satisfy the requirements of the site characterization report
identified in 25 Pa. Code § 245.310(b). A completed closure report form,
including adherence to the confirmatory sampling protocol in the closure
guidance document appropriate for either aboveground or underground storage
tank systems, will be adequate to demonstrate that the requirements of the SHS
have been met. Note that the confirmatory sample locations in the closure
guidance do not apply if the contamination has extended more than three feet
from any part of the tank system. Also, because only limited sampling is required
in localized contamination situations, the most conservative medium-specific
concentrations (MSCs) are used as action levels. The most current action levels
are provided in Tables 3 and 4 in DEP Booklet number 2630-BK-DEP4699.
Where a site-specific standard is being pursued and a risk assessment report is
required under 25 Pa. Code § 250.405, the report should be submitted to the
appropriate DEP regional office with the site characterization report and should

261-0300-101 / DRAFT December 16, 2017 / Page III-84
contain those elements as described under the site-specific standard of this
manual.
If the comprehensive site characterization report indicates that the interim
remedial actions did not adequately address the release, and the background or
SHS is selected, responsible parties must develop and submit a remedial action
plan to the appropriate DEP regional office within 45 days of submission of the
site characterization report. In cases where the site-specific standard is chosen,
the remedial action plan is due 45 days after the Department’s approval of the site
characterization report (25 Pa. Code § 245.311).
The responsible party must implement the remedial action consistent with the
schedule in the remedial action plan upon reasonable notice or approval of the
remedial action plan by DEP. Remedial action progress reports must be
submitted quarterly to the appropriate DEP regional office (25 Pa. Code
§ 245.312).
When the standard(s) established in the remedial action plan has/have been
achieved, the responsible party must submit a remedial action completion report.
The remedial action completion report must demonstrate that the requirements of
one or more of the Act 2 standards have been met and include, if applicable, a
postremediation care plan (25 Pa. Code § 245.313).
In order to receive Act 2 liability protection, the cleanup standards for all
regulated substances stored in the tank system, as identified in the site
characterization report, must be achieved.
Petroleum-contaminated media and debris associated with certain underground
storage tanks ( e.g., soil and groundwater, but not free product) that fail the test
for D018-D043 TCLP only and are subject to the federal corrective action
regulations under 40 CFR Part 280 are specifically excluded as hazardous waste
(40 CFR § 261.4(b)(10). This exclusion does not apply to contaminated media
and debris from aboveground tanks, farm and residential motor fuel underground
storage tanks of less than 1,100-gallon capacity, as well as heating oil
underground storage tanks used for consumptive purposes at the property where
located (i.e., tanks not regulated under 40 CFR Part 280). Petroleum-
contaminated media and debris that are classified as hazardous waste are subject
to the deed notice requirements of SWMA (35 P.S. § 6018.405).
While the CAP regulations specify when the Department is to receive the site
characterization report, remedial action plan and remedial action progress reports,
the regulations also provide the Department with the flexibility to shorten or
extend the timeframes based on the circumstances of a particular release.
In addition, the CAP regulations establish Department review timeframes for site
characterization reports, remedial action plans and remedial action completion
reports. These reports are deemed approved if the Department does not take an
action within those timeframes unless the Department and the responsible party

261-0300-101 / DRAFT December 16, 2017 / Page III-85
agree in writing to an alternative timeframe. The review timeframes are as
follows:
?
The Department will review a site characterization report submitted under
Subsection 245.310(b) within 60 days of receipt, or a site characterization
report submitted under Subsection 245.310(a) selecting the site-specific
standard within 90 days of receipt.
?
Site characterization reports submitted under Subsection 245.310(a) for
the background or Statewide health standard will be reviewed within
60 days of receipt of a remedial action plan designed to attain those
standards. The review will include the remedial action plan.
?
Site characterization reports and remedial action plans for the background
or Statewide health standard which are submitted together will be
reviewed within 60 days of receipt.
?
A remedial action plan designed to attain the site-specific standard will be
reviewed within 90 days of receipt by the Department.
?
Remedial action completion reports for the background and Statewide
health standard will be reviewed within 60 days of receipt. A remedial
action completion report demonstrating attainment of the site-specific
standard will be reviewed within 90 days of receipt.
Responsible parties are strongly encouraged to properly identify the report or plan
being submitted in order to facilitate review of reports and plans by the
Department. Figure III-10 is a cover sheet which can be used with CAP
submissions.
3.
Use of the Short List of Regulated Substances for Releases of Petroleum Products
Petroleum products contain many regulated substances. However, it is not always
practical to examine all the regulated substances in a petroleum product. The Department
has developed a “short list” of regulated substances for various petroleum products
(Table III-5) to be analyzed to demonstrate attainment under any of the Act 2 cleanup
standards when a release of these petroleum products occurs and is uncontaminated by
other sources.
The Department will accept use of the short list to demonstrate attainment of the SHS if
the following conditions are also met:
1.
For soil media, no free liquids are left in the soil based on visual observation, and
the soil does not create an odor nuisance. An odor nuisance has occurred if the
Department has received a complaint concerning petroleum odors which, upon
investigation, can be attributed to petroleum contamination remaining in the soil.
2.
For groundwater media, no free-floating product exists at the point of compliance
(property line). Free-floating product must be recovered to the maximum extent

261-0300-101 / DRAFT December 16, 2017 / Page III-86
practicable and any remaining product cannot pose an unacceptable risk to human
health or the environment.
The rationale for the application of these conditions is that the SHS numeric values
cannot exceed their saturation and solubility limits in soil and groundwater, respectively.
Since the Department is accepting an attainment demonstration for the short list of
regulated substances rather than all regulated substances contained in a particular
petroleum product, these conditions are necessary to assure that all SHSs applicable to
the petroleum product are met.
If the remediator chooses to use the short list, and meets these conditions, then the
Remedial Action Completion Report approval will stipulate that Act 2 liability coverage
is for the short list substances only.
The short list of petroleum products may be periodically revised as determined necessary
by the Department. For sites in the CAP for which a site characterization report has been
submitted, attainment demonstration will be made using the previous list of substances.
Sites which commence investigations to characterize or verify releases after the date the
new list becomes effective should use the new list for characterization and attainment
demonstration purposes to avoid a disapproval.
4.
Maximum Extent Practicable
EPA has approved Pennsylvania’s UST program in 25 Pa. Code Chapter 245 as
consistent with federal law (68 FR 53520 (September 11, 2003)). EPA regulations under
40 CFR § 280.64 require owners and operators to remove “free product” to the maximum
extent practicable (MEP) as determined by the implementing agency. Section 280.64(b)
requires owners and operators to use abatement of “free product” migration as a
minimum objective for the design of the free product removal system. The Department
equates “free product,” as the EPA uses the term, to be equivalent to “separate phase
liquid” (SPL) as the Department has used that term in the past. Thus, to meet the
corrective action requirement for underground storage tanks in Pennsylvania, a
remediator must demonstrate the following two requirements, based upon technical data:
SPL has been removed to the MEP, and
the release has been demonstrated to attain an Act 2 cleanup standard.

261-0300-101 / DRAFT December 16, 2017 / Page III-87
Figure III-10
Corrective Action Process Report/Plan Cover Sheet

261-0300-101 / DRAFT December 16, 2017 / Page III-88
Table III- 5
Short List of Petroleum Products
PRODUCT
STORED
PARAMETERS TO BE
TESTED IN SOIL
ANALYTICAL METHOD
(REPORTED ON A
DRY WEIGHT BASIS)
PARAMETERS TO BE
TESTED IN WATER
ANALYTICAL METHOD1
Leaded Gasoline,
Benzene
EPA Method 5035/8021B or
Benzene
EPA Method 5030B/8021B,
Aviation Gasoline,
Toluene
5035/8260B
Toluene
5030B/8260B or 524.2
and Jet Fuel
Ethyl Benzene
Ethyl Benzene
Xylenes (total)
Xylenes (total)
Cumene (Isopropylbenzene)
(Isopropylbenzene)
Cumene (Isopropylbenzene)
(Isopropylbenzene)
Naphthalene
Naphthalene
Trimethyl benzene, 1,2,4-
(Trimethyl benzene, 1,3,4-)
Trimethyl benzene, 1,2,4-
(Trimethyl benzene, 1,3,4-)
Trimethyl benzene, 1,3,5-
Trimethyl benzene, 1,3,5-
Dichloroethane, 1,2-
Dichloroethane, 1,2-
Dibromoethane, 1,2-
Dibromide)
Dibromoethane, 1,2-(Ethylene
Dibromide)
EPA Method 8011 or 504.1
Lead (total)
EPA Method 6010B or 7420
Lead (dissolved)
EPA Method 6020, 7421,
200.7, 200.8, or 200.9
Unleaded
Benzene
EPA Method 5035/8260B
Benzene
EPA Method 5030B/8260B
Gasoline
Toluene
Toluene
or 524.2
Ethyl Benzene
Ethyl Benzene
Xylenes (total)
Xylenes (total)
Cumene (Isopropylbenzene)
(Isopropylbenzene)
Cumene (Isopropylbenzene)
(Isopropylbenzene)
Methyl tert-Butyl Ether (MTBE)
Methyl tert-Butyl Ether (MTBE)
Naphthalene
Naphthalene
Trimethyl benzene, 1,2,4-
(Trimethyl benzene, 1,3,4-)
Trimethyl benzene, 1,2,4-
(Trimethyl benzene, 1,3,4-)
Trimethyl benzene, 1,3,5-
Trimethyl benzene, 1,3,5-
Kerosene,
Benzene
EPA Method 5035/8260B
Benzene
EPA Method 5030B/8260B
Fuel Oil No. 1
Toluene
Toluene
or 524.2
Ethyl Benzene
Ethyl Benzene
Cumene (Isopropylbenzene)
(Isopropylbenzene)
Cumene (Isopropylbenzene)
(Isopropylbenzene)
Methyl tert-Butyl Ether
Methyl tert-Butyl Ether
Naphthalene
Naphthalene
Trimethyl benzene, 1,2,4-
(Trimethyl benzene, 1,3,4-)
Trimethyl benzene, 1,2,4-
(Trimethyl benzene, 1,3,4-)
Trimethyl benzene, 1,3,5-
Trimethyl benzene, 1,3,5-
Diesel Fuel,
Benzene
EPA Method 5035/8260B
Benzene
EPA Method 5030B/8260B
Fuel Oil No. 2
Toluene
Toluene
or 524.2
Ethyl Benzene
Ethyl Benzene
Cumene (Isopropylbenzene)
(Isopropylbenzene)
Cumene (Isopropylbenzene)
(Isopropylbenzene)
Methyl tert-Butyl Ether
Methyl tert-Butyl Ether
Naphthalene
Naphthalene
Trimethyl benzene, 1,2,4-
(Trimethyl benzene, 1,3,4-)
Trimethyl benzene, 1,2,4-
(Trimethyl benzene, 1,3,4-)
Trimethyl benzene, 1,3,5-
Trimethyl benzene, 1,3,5-

261-0300-101 / DRAFT December 16, 2017 / Page III-89
Table III-5 - Continued
Short List of Petroleum Products
PRODUCT
STORED
PARAMETERS TO BE
TESTED IN SOIL
ANALYTICAL METHOD
(REPORTED ON A
DRY WEIGHT BASIS)
PARAMETERS TO BE
TESTED IN WATER
ANALYTICAL METHOD1
4, 5 and 6, and
Naphthalene
5035/8260B
Naphthalene
5030B/8260B or 524.2
Lubricating Oils
Fluorene
EPA Method 8270C or 8310
Phenanthrene
EPA Method 8270C,
and Fluids
Anthracene
Pyrene
8310 or 525.2
Phenanthrene
Chrysene
Pyrene
Benzo(a)anthracene
Chrysene
Benzo(b)fluoranthene
Benzo(a)pyrene
Benzo(g,h,i)perylene
Used Motor Oil
Benzene
EPA Method 5035/8021B or
Benzene
EPA Method 5030B/8021B,
Toluene
5035/8260B
Toluene
5030B/8260B or 524.2
Ethyl Benzene
Ethyl Benzene
Cumene (Isopropylbenzene)
Cumene (Isopropylbenzene)
Naphthalene
Naphthalene
Pyrene
EPA Method 8270C or 8310
Pyrene
EPA Method 525.2
Benzo(a)anthracene
Benzo(a)anthracene
Chrysene
Chrysene
Benzo(b)fluoranthene
Benzo(b)fluoranthene
Benzo(a)pyrene
Benzo(a)pyrene
Indeno(1,2,3-cd)pyrene
Indeno(1,2,3-cd)pyrene
Benzo(g,h,i)perylene
Benzo(g,h,i)perylene
Lead (total)
EPA Method 6010B or 7420
Lead (dissolved)
EPA Method 6020, 7421,
200.7, 200.8, or 200.9
Mineral Insulating
Oil
PCB-1016 (Aroclor)
EPA Method 8082
PCB-1016 (Aroclor)
EPA Method 8082 or 508A
PCB-1221 (Aroclor)
PCB-1221 (Aroclor)
PCB-1232 (Aroclor)
PCB-1232 (Aroclor)
PCB-1242 (Aroclor)
PCB-1242 (Aroclor)
PCB-1248 (Aroclor)
PCB-1248 (Aroclor)
PCB-1254 (Aroclor)
PCB-1254 (Aroclor)
PCB-1260 (Aroclor)
PCB-1260 (Aroclor)
Trimethyl benzene, 1,2,4-
(Trimethyl benzene, 1,3,4-)
EPA Method 5035/8021B or
5035/8260B
Trimethyl benzene, 1,2,4-
(Trimethyl benzene, 1,3,4-)
EPA Method 5030B/8021B,
5030B/8260B or 524.2
Trimethyl benzene, 1,3,5-
Trimethyl benzene, 1,3,5-
Other Petroleum
Products
Blended
Petroleum
Products
Contact the DEP Regional Office Responsible for the County in Which the Tank is Located
Unknown
Petroleum
Products
Other Regulated
Substances
1 Samples from potable water supplies must be analyzed using a method applicable to drinking water.
Notes:
When reporting nondetects (ND), the data must be accompanied by a numerical quantitation limit that takes into account dilution, sample preparation, and
matrix effects.
The responsible party has the obligation to ensure that the analytical methodologies and techniques employed are suitable to provide data that meets the
minimal data quality objectives outlined and referenced in this document.
Laboratories must document that samples meet all applicable preservation requirements.

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As the implementing agency, the Department considers MEP under 40 CFR § 280.64 as
the extent of removal necessary to prevent migration of SPL to uncontaminated areas and
prevent or abate immediate threats to human health or the environment.
Migrating SPL is an SPL body and its associated phases that are documented to be
spreading or expanding laterally or vertically into previously uncontaminated areas.
Residual and mobile SPL and related terms are discussed further in Section V.D. of this
guidance.
In the majority of cases, releases at regulated storage tank sites are liquids with a density
less than water, or light non-aqueous phase liquids (LNAPLs). Recent advances in the
understanding of LNAPL behavior have illustrated that in some cases, continued attempts
to reduce LNAPL to a measured thickness in a monitoring well (e.g., 0.01 ft. or less) may
not be practicable. Even in cases where the presence of LNAPL is the only reason for
remediation, continued recovery of LNAPL may provide little positive impact on the
environment.
Demonstration of the requirements regarding removal of SPL to the MEP is further
described in Section V.D of this guidance.

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D.
Mass Calculations
The following sections demonstrate methods to calculate groundwater and soil mass utilizing site
specific measurements of contaminants and volume of the specific soil or liquid plumes.
1.
Groundwater Mass Calculation
Calculate Water Volume (WV)
Water Volume(WV-ft
3
) = Length of plume(L) x Average Thickness of plume(H) x
Average Width of plume(W) x porosity(n)
Calculate Water Mass (WM)
Water Mass(WM-lb.) = Water Volume(WV-ft
3
) x 62.5 lb./ft
3
Calculate Mass of Contaminant
Water Mass(WM-lb.) x Contaminant Concentration(C-ppm)/ 10
6
= Contaminant
Mass(lb.)
2.
Soil Mass Calculation
These soil mass calculations provide a way of quantifying contaminants in soil that under
an Act 2 remediation would track the estimations of the mass of contaminants removed
from public exposure as a measure of program success. Contaminants removed from
public exposure can be any one or a combination of excavation and disposal, treatment or
pathway elimination measures. The mass calculations would not include areas of the site
where site characterization found concentrations to be at or below the applicable
standard. This area remains unchanged and thus there is no reduction in exposure as part
of the remediation.
M(x) = D(
soil
) x V(
total
) x C
ave
.(x)
Where:
M(x) = The mass of a specific contaminant in soil (lb)
D(
soil
) = Density of soil, assume to be a default value of 110 lb/ft
3
V(
total
) = Volume based on the soil site characterization data with respect to the horizontal
and vertical depth of the soil samples collected in areas above the applicable standard.
The volume sum of each plot would equate to the total volume.
C
ave
. (x) = The soil contaminant concentration would be the arithmetic mean
concentration of the contaminant throughout the soil column. This is the free and
absorbed phase of the soil contaminant in areas above the applicable standard and
expressed in lb
contaminant
/lb
soil
(ppmw = ppm/10
6
).

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E.
Long-Term Stewardship
1.
Introduction
Long-term stewardship is generally accepted as the establishment and maintenance of
physical and non-physical controls that are necessary to maintain the effectiveness of an
approved remedy at cleanup sites where remaining regulated substances do not allow for
the unrestricted use of the property. It also includes any long-term obligations (e.g.,
sampling, operation and maintenance, etc.) that ensure the effectiveness of the remedy
after completion of the response action.
This section provides general guidelines on the methodology of long-term stewardship,
which includes the use of a postremediation care plan. The plan shall be submitted as
part of the final report and approved by the Department. The approved postremediation
care plan will become a condition of attainment of the chosen standard(s) under Act 2.
The plan shall identify the activities that will be conducted after closure and the
frequency of those activities.
Answer the questions from the matrix in Table III-6, relative to your chosen standard(s),
to determine when a postremediation care plan is required. The proposed
postremediation care requirements shall be included in the cleanup plan for Department
approval, as specified in § 250.410(b)(5).
If any of the answers in the following matrix are yes, relative to the selected standard(s),
a postremediation care plan shall be included as part of the final report.
2.
Uniform Environmental Covenants Act
On Dec. 18, 2007, the Uniform Environmental Covenants Act (UECA) (27 Pa. C.S.
§ 6501-6517) was signed into law, and was subsequently implemented via Chapter 253,
adopted November 19, 2010 (40 Pa.B. 6654). UECA provides a standardized process for
creating, documenting and assuring the enforceability of activity and use limitations
(AULs) on contaminated sites. Under UECA, an environmental covenant will be
required whenever an engineering or institutional control is used to demonstrate the
attainment of an Act 2 remediation standard. Environmental covenants are legal
documents affecting property rights so remediators are encouraged to seek legal counsel
with respect to the contents of the environmental covenant. For the purposes of Act 2,
environmental covenants will take the place of deed notices in relation to any restrictions
required to attain or maintain the standard.
A model environmental covenant is provided on the LRP website. The model is provided
as an example of what type of information should be provided in an environmental
covenant. However, it is important to note that each site is unique, so the content of each
covenant will vary from site to site.
At some sites additional AULs may be put in place but not included in the environmental
covenant. Only those AULs that are necessary to attain and/or maintain the selected
standard are required for inclusion within the environmental covenant. In addition, the
property owner’s consent and signature are required to implement an environmental
covenant (27 Pa. C.S. § 6504).

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TABLE III-6
Postremediation Care Decision Matrix
Background
Yes
No
1.)
Is an ENGINEERING CONTROL(s) needed to
attain and/or maintain the background
standard?
2.)
Is an INSTITUTIONAL CONTROL(s) needed
to maintain the background standard?
3.)
Does the FATE & TRANSPORT analysis
indicate that the background standard may be
exceeded at the point of compliance in the
future?
4.)
Does the remediation rely on NATURAL
ATTENUATION?
Statewide Health
1.)
Is an ENGINEERING CONTROL(s) needed to
attain and/or maintain the Statewide health
standard?
2.)
Is an INSTITUTIONAL CONTROL(s) needed
to maintain the Statewide health standard?
3.)
Does the FATE & TRANSPORT analysis
indicate that the Statewide health standard,
including the solubility limitation in
Section 250.304(b), may be exceeded at the
point of compliance in the future?
4.)
Does the remediation rely on NATURAL
ATTENUATION?
5.)
If there are ECOLOGICAL IMPACTS
identified in the evaluation of ecological
receptors that must be addressed, will a
postremedy use be relied on to eliminate
complete exposure pathways, as set forth in
Section 250.311(e)(2)?
6.)
If there are ECOLOGICAL IMPACTS
identified in the evaluation of ecological
receptors that must be addressed, will
mitigation measures be implemented, as set
forth in Section 250.311(f)(v)? [If yes, follow
guidelines in Section 250.312(b)(1-3) for
reporting requirements.]
Site-Specific
1.)
Is an ENGINEERING CONTROL(s) needed to
attain and/or maintain the Site-specific
Standard?

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2.)
Is an INSTITUTIONAL CONTROL(s) needed
to maintain the Site-specific Standard?
3.)
Does the FATE & TRANSPORT analysis
indicate that the Site-specific Standard may be
exceeded at the point of compliance in the
future?
4.)
Does the remediation rely on NATURAL
ATTENUATION?
5.)
If there are ECOLOGICAL IMPACTS
identified in the evaluation of ecological
receptors that must be addressed, will a
postremedy use be relied on to eliminate
complete exposure pathways, as set forth in
Section 250.311(e)(2)?
6.)
If there are ECOLOGICAL IMPACTS
identified in the evaluation of ecological
receptors that must be addressed, will
mitigation measures be implemented, as set
forth in Section 250.311(f)? [If yes, follow
guidelines in Section 250.411(f)(1-3) for
reporting requirements.]

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3.
Institutional versus Engineering Controls
An institutional control, by definition of Act 2, is a measure taken to limit or prohibit
certain activities that may interfere with the integrity of a remedial action or result in
exposure to regulated substances at a site. These include, but are not limited to, fencing
or restrictions on the future use of the site (35 P.S. § 6026.103).
An engineering control, by definition of Act 2, is a remedial action directed exclusively
toward containing or controlling the migration of regulated substances through the
environment. These include, but are not limited to, permanent capping of contaminated
soils with parking lots or building slab construction, leachate collection systems,
groundwater recovery trenches, and vapor mitigation systems.
Example: A groundwater use restriction, as documented in an environmental covenant, is
an institutional control. An impermeable cap that prevents volatilization to the
atmosphere, controls contaminant migration via run-off and leaching to groundwater, and
limits dermal contact is an engineering control.
Institutional and engineering controls serve as AULs because they restrict the use of a
property. Institutional controls cannot be used to attain the background or Statewide
health standards (35 P.S. §§ 6026.302(b)(4) and 6026.302(e)(3)). Engineering and/or
institutional controls may be used to maintain all three standards.
Attaining
a standard
refers to steps or actions taken to complete the requirements, and therefore demonstrate
attainment, of an Act 2 standard.
Maintaining
a standard refers to steps or actions taken
to ensure the requirements of a standard that have already been completed continue to be
met in the foreseeable future. Table III-6 provides a decision matrix of postremediation
care requirements for each Act 2 standard.
Example: A property attains the SHS under current conditions which include drinking
water supplied by the municipality. This standard is then maintained in the future by
implementing an environmental covenant stating that groundwater is not to be used on
the property.
4.
Postremediation Care Plan
The postremediation care plan should include the following:
The reason(s) that the postremediation care plan is necessary (See 25 Pa. Code
§§ 250.204(g), 250.311, 250.312, 250.411(d), and 250.708).
A schedule of operation and maintenance of the controls. Include a description of
the planned maintenance activities and frequencies at which they will be
performed and future plans for submission of proposed changes.
Information regarding the submission of quarterly monitoring results and analysis,
or as otherwise approved by the Department, that demonstrates the effectiveness
of the remedy. Include a description of the planned monitoring activities and
frequencies at which they will be performed.

261-0300-101 / DRAFT December 16, 2017 / Page III-96
The proposed method for reporting any instances of nonattainment of the selected
standard(s).
The proposed measures to be taken to correct nonattainment conditions as they
occur. A postremediation care plan containing any language proposing any
potential future changes to the remedy will require the approval of the Department
at the time of the proposed change.
Information regarding the maintenance of records at the property where the
remediation is being conducted for monitoring, sampling and analysis. Include
the name, address and telephone number of the person or office to contact about
the site during the postremediation care period. This person or office shall keep
an updated postremediation care plan during the postremediation care period.
Documentation of a plan to maintain the mitigated ecological resource, report of
success or failure of the mitigation measure, and demonstration of sustaining the
measures up to five years from final report approval.
If requested by the Department, documentation of financial ability to implement
the remedy and the postremediation care plan.
5.
Postremediation Monitoring
In some situations, postremediation monitoring may be required as part of the
postremediation care plan. For example, postremediation monitoring is conducted to
determine any changes in groundwater quality after attainment of a standard(s). Unless
otherwise instructed by the Department, analytes to be included are those which were
monitored during assessment and remediation monitoring. All monitoring activities
should incorporate quality control and quality assurance provisions consistent with the
Chapter 250 regulations and policies.
Well locations for postremediation monitoring are generally selected from existing
monitoring wells used in the characterization and remediation phases. Where a source of
contamination is removed prior to impacting groundwater, postremediation monitoring
should continue at locations that will detect any residual contamination in the unsaturated
zone that might migrate to the groundwater.
a)
Duration
In most cases, postremediation monitoring requirements will be developed on a
case-by-case basis. The factors determining the duration of postremediation
monitoring are the same factors that determine whether a postremediation care
plan is necessary.
b)
Frequency
As stated in 25 Pa. Code § 250.204(g), postremediation monitoring will take place
on a quarterly basis unless otherwise approved by the Department. The interval
between sampling events should be short enough to allow for response and

261-0300-101 / DRAFT December 16, 2017 / Page III-97
correction of any problems that may cause nonattainment at the point of
compliance.
Factors that could influence the need for an alternative postremediation
monitoring schedule include site size, groundwater velocity, contaminant
characteristics and the vulnerability of a site to pulses of contaminant migration
during precipitation events.
c)
Cessation of Postremediation Monitoring
Postremediation monitoring may be terminated when monitoring provisions set
forth in the postremediation care plan are met, the engineering controls are no
longer needed, and it can be documented by fate and transport analysis that the
standard will not be exceeded in the future.
6.
Postremediation Care Attainment
A person may terminate postremediation care as approved in the final report if he can
demonstrate attainment of the standard(s) without the engineering controls in place, and
document by a fate and transport analysis that the standard will not be exceeded in the
future. An amendment to the postremediation care plan shall be submitted for approval
by the Department. The postremediation care plan shall be amended whenever changes
in operating plans or facility design, or events that occur during postremediation care,
affect the currently approved postremediation care plan.

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F.
One Cleanup Program
In March 2004, PA DEP and EPA Region 3 entered into a Memorandum of Agreement (MOA)
that outlines a procedure where sites remediated according to the LRP may also satisfy
requirements of several federal laws: the Resource Conservation and Recovery Act (RCRA)
(42 U.S.C. § 6901, et seq.), the Comprehensive Environmental Response Compensation Liability
Act (CERCLA) (42 U.S.C § 9601, et seq.), and the Toxic Substances Control Act (TSCA)
(15 U.S.C. § 2601, et seq.).
1.
Purpose
DEP and EPA sought to promote the One Cleanup Program initiative by working
together to achieve cleanups that protect human health and the environment by making
greater use of all available authorities, and selecting the optimum programmatic tools to
increase the pace, effectiveness, efficiency, and quality of cleanups. In effect, entering
into the One Cleanup Program can provide a remediator with a “one-stop shop” for state
and federal standards guiding the cleanup of brownfield sites.
2.
Provisions and Applicability
EPA has reviewed and evaluated the LRP and has determined that the LRP, as
implemented under the MOA, includes each of the four elements of a state response
program listed in CERCLA Section 128(a)(2):
Timely survey and inventory of brownfield properties.
Oversight and enforcement authorities adequate to ensure that a response action
will protect human health and the environment.
Mechanisms and resources to provide meaningful opportunities for public
participation.
Mechanisms for approval and a requirement for verification and certification that
the response activity is complete.
The One Cleanup Program applies only to remediation of properties conducted pursuant
to Act 2 provisions. As determined by PA DEP and USEPA, the following properties are
not eligible to enter in the program:
Permitted hazardous waste management units.
Properties proposed in the Federal Register to be placed on the National Priorities
List.
Properties that have been placed on the National Priorities List.
Properties that have been permitted under the SWMA and the PA Clean Streams
Law for which cleanup standards are different than those of the LRP.

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3.
Implementation
Under the MOA, DEP and EPA have agreed to work in a coordinated manner to avoid
possible duplication of efforts at properties, while ensuring that remediation of properties
continues in a timely fashion. DEP will notify EPA when properties are being addressed
under the LRP via written documentation for properties in Comprehensive Environmental
Response, Compensation and Liability Information System (CERCLIS) that are being
addressed under the LRP.
For all RCRA Corrective Action Facilities being remediated under the LRP, the
remediator will provide EPA with copies of reports. DEP and EPA will work in teams to
accomplish cleanup goals in an appropriate and efficient use of both agencies’ resources.
EPA will review reports submitted to DEP under the LRP to determine if the site data
meets RCRA Corrective Action obligations. If EPA determines that the site
characterization or final decision is not sufficient to characterize the nature and extent of
contamination, the EPA and DEP intend to work together to resolve the matter. If EPA
determines the proposed cleanup objectives and corrective measures are sufficient, EPA
plans to proceed with remedy selection procedures, including providing opportunity for
public comment and review. Once the remedy is implemented and EPA determines that
the media cleanup measures are met and corrective measures are satisfied, EPA will,
where appropriate, acknowledge that the remediator has completed its Corrective Action
obligations.
RCRA facilities enrolled in the One Cleanup Program may be subject to UECA
requirements (Section III.D of this TGM). As such, a model covenant for any activity
and use limitations which may be in effect for these facilities is located on the DEP
website on the ‘One Cleanup Program’ webpage.
4.
Benefits
In summary, by entering into the One Cleanup Program, site owners or operators may be
able to satisfy federal RCRA obligations and obtain liability relief under the Act 2
program. Interested parties can review the historic MOA, RCRA Corrective Action
Baseline Facilities that have entered the One Cleanup Program, and other useful
information on the PA DEP website on the One Cleanup Program tab.
Any owner, operator, or remediator interested in entering the One Cleanup Program
should consult with their assigned DEP Project Officer about opportunities and eligibility
requirements.

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G.
Data Quality and Practical Quantitation Limits
1.
Data Quality Objectives Process, Sampling, and Data Quality Assessment Process
An important issue regarding sampling and statistical analysis is the quality assurance
(QA) management considerations associated with these activities. Steps for the QA
management process, in general, can be divided into three phases: planning,
implementation and assessment. During the planning phase, a sampling and analysis plan
is developed based on Data Quality Objectives (DQO). The implementation phase
includes sampling execution and sample analysis. The assessment phase includes Data
Quality Assessment (DQA) (See 25 Pa. Code § 250.702(a)).
To help remediators design scientific and resource-effective sampling programs, EPA
provides guidance on developing DQO (EPA 1993). The DQO process allows a person
to define the data requirements and acceptable levels of decision errors, before any data
are collected. The DQO process should be considered in developing the sampling and
analysis plan, including the QA plan.
As stated in the EPA guidance (EPA 1993), the DQO process includes the following
seven steps:
State the problem.
Identify the decision.
Identify inputs to the decision.
Define the spatial and temporal boundaries of the decision.
Develop a decision rule.
Specify limits on decision errors.
Optimize the design for obtaining data.
Step 4 of the DQO process, defining the spatial and temporal boundaries of the decision,
is particularly important, because it prevents pooling and averaging data in a way that
could mask potentially useful information. Activities in this step include:
Define the domain or geographic area within which all decisions must apply.
Some examples are property boundaries, operable units, and exposure areas.
Specify the characteristics that define the population of interest. Identification of
multiple areas of concern—each with its own set of samples and descriptive
statistics—will help to reduce the total variability if the areas of concern (AOCs)
are defined so that they are very different in their contaminant concentration
profiles. For example, the top 2 feet of soil are defined as surface soil. Another
example is to define contaminated soil that has been impacted by SPL as SPL-
impacted soil.

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