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# Petroleum Releases At Underground Storage Tank Facilities

In Florida

United States Environmental Protection Agency Office O f Underground Storage Tanks

Peer Review Draft

– March 2005Peer Re view Draft

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### ICF Incorporated, L.L.C. provided support to develop this document under

Contract No. 68

- W0

- 0065.
Lynn Depont EP A Project Officer U.S. Environmental Protection Agency Washington, D.C. 20460Peer Re view Draft

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# Contents
Executi ve Summary To Be Added

................................ ................................ ... 1

Introduction

................................ ................................ ................................ ...... 2 Background

................................ ................................ ................................ ...... 2 Purpose Of The Study

................................ ................................ ....................... 3 Study Methodology

................................ ................................ ........................... 3
Valid Versus I nvalid Data

................................ ................................ ................................ ........ 3 Type Of Data Collected

................................ ................................ ................................ ............ 4 Data Collection

................................ ................................ ................................ .......................... 4 Developing And Applying Data Collection Forms

................................ ................................ . 4 Data Review And Quality Control

................................ ................................ .......................... 5 Summary And Analysis Of Release And Use Data

................................ ................................ 5 

## Results

................................ ................................ ................................ ............... 6
Valid And Invalid Data

................................ ................................ ................................ ............ 6 Release Sources

................................ ................................ ................................ ......................... 7 Release Caus es ................................ ................................ ................................ ........................... 7 Releases From Dispensers

................................ ................................ ................................ ........ 8 Releases From Piping

................................ ................................ ................................ .............. 10 Releases During Fuel Delivery

................................ ................................ ............................... 15 Releases From Tanks

................................ ................................ ................................ .............. 16 Pump (Turbine) Releases

................................ ................................ ................................ ....... 20 Other Release Sources

................................ ................................ ................................ ............ 21 Volume Of Releases

................................ ................................ ................................ ................ 22 Environmental Media Affected By UST Releases

................................ ................................ 23 Method Of Release Discovery

................................ ................................ ................................ 25 Performance Of Leak Detection Methods

................................ ................................ ............ 26 

## Discussion Of Results

................................ ................................ ...................... 28

Appendix A

- Data Collection Forms

................................ ............................ A

- 1 Appe ndix B

- Statistical Method s ................................ ................................ . B

- 1 Appendix C

– Data Summary Tables A nd Statistical Result s ...................... C

- 1Peer Re view Draft

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# List Of Figures

Figure 1: Summary Of Reasons For Invalidating Data

................................ ................................ .. 6 Figure 2: Sources Of UST Releases

................................ ................................ ................................ 7 Figure 3: Summary Of Known Causes For All Releases

................................ ............................... 8 Figure 4: Known Causes Of Dispenser Releases

................................ ................................ ............ 9 Figure 5: Known Causes Of Piping Releases

................................ ................................ ............... 10 Figure 6: Known Causes Of Fiberglas s Piping Releases

................................ .............................. 11 Figure 7: Known Causes Of Steel Piping Releases

................................ ................................ ...... 12 Figure 8: Known Causes Of Approved Synthetic Material Piping Releases

................................ 12 Figure 9: Piping Releases And Use Versus Piping Material Of Construction

............................. 13 Figure 10: Known Causes Of Releases During Fuel Delivery

................................ ..................... 15 Figure 11: Known Causes Of Tank Releases

................................ ................................ ............... 17 Figure 12: Summary Of Known Causes For Steel Tank Releases

................................ ............... 18 Figure 13: Summary Of Known Causes For Fiberglass Tank Releases

................................ ....... 19 Figure 14: Tank Releases And Use Versus Tank Material Of Construction

................................ 19 Figure 15: Known Causes For Pump (Turbine) Releases

................................ ............................. 21 Figure 16: Known Causes For Other Releases

................................ ................................ ............. 22 Figure 17: Proportion Of Releases From Each Source Affecting Water

................................ ...... 24 Figure 18: Total Number Of Releases Affecting Water By Source

................................ ............. 25 Figure 19: Method Of Release Discovery

................................ ................................ .................... 26



# List Of Tables

Table 1: Dispenser Releases And Secondary Containment

................................ ............................ 9 Table 2: Effe ct Of Secondary Containment On Piping Releases

................................ ................. 14 Table 3: Piping Releases And Pump Type

................................ ................................ ................... 14 Table 4: Fuel Delivery Releases And Overfill Protection Methods

................................ ............. 16 Table 5: E

ffect Of Secondary Containment On Tank Releases

................................ .................... 20 Table 6: Release Volumes For The Different Sources

................................ ................................ . 23 Table 7: Releases Affecting Groundwater And Surface Water By Source Of Release

................ 23 Table 8: Proportions Of All Releases Identified And Not Identified By Tank Leak Detection Methods Compared To Frequency Of Use

................................ ................................ ........... 27 Table 9: Failures And Successes For Electronic And Mechanical Line Leak Detecto rs

............. 27Peer Review Draft

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### 1 

## Executive Summary To Be AddedPeer Review Draft

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### 2 

## Introduction

In this document, the U.S. Environmental Protection Agency (EPA) presents analyses of data related to liquid underground storage tank (UST) releases 1 

### in Florida discover ed and reported between January 1995 and April 2002

. The following sections discuss the background and purpose of the study, the methodology used to gather and analyze the data
, the study results (including data

summary and st

atistical analyses )
, and a di scussion of the results

. The appendices contain

the forms used to gather the data, an explanation of the statistical methodology used in th

e evaluation, and data tables and statistical analyses

.



## Background

In 1984, Congress responded to the increasing threat to groundwater posed by leaking underground storage tanks by adding Subtitle I to the Resource Cons ervation and Recovery Act

. This legislation required EPA to develop a comprehensive regulatory program for USTs storing petroleum or certain hazardo us substances in order to protect the environment and human health from releases. In 1988, EPA issued regulations for owners and operators of UST systems covering leak detection and prevention, including minimizing the potential for USTs to corrode. (The regulations also cover additional requirements, such as financial responsibility and corrective action, not discussed in this report.) The regulatory requirements were phased in over ten years; the final deadline was December 22, 1998.

Federal and st

ate regulations helped EPA achieve its mandate. As a result of these regulations, USTs are now significantly more protective of human health and the environment than those installed before the requirements were implemented. Today UST systems have leak det ection, spill, overfill
, and c orrosion protection equipment

. Some states have additional requirements , such as secondary containment. States are reporting f ewer releases. In the early 1990s, the average number of releases reported nati onwide exceeded 50 ,000 per year. I n the mid 1990s, the national average was over 25,000; in 2004, the number of reported confirmed releases across the country was less than 8,000. Despite these improvements, however, releases from new and upgraded UST systems continue. T o better understand where and why these releases are occurring
, EPA’s Office of Underground Storage Tanks initiated an effort to evaluate the performance of new and upgraded UST systems. The specific objectives of the overall UST system evaluation effort are to:

• Identify the most common sources and causes of releases.

• Determine how successful leak detection methods are at detecting releases.

• Determine what, if any, improvements are needed in the UST program.
This study is one piece of EPA’s overall effort to evaluat e UST systems. For this study
, EPA entered into a partnership with the Florida Department of Environmental Protection ( FDEP )

1 Florida uses the term discharge to describe a release to the environment that cannot be quickly cleaned up. EPA will refer to these discharges as releases throughout this report.Peer Review Draft

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### 3 to assemble and analyze data on tank system incidents and releas es in Florida

. 2 

### F DEP was an ideal partner becaus e of their willingness to assist with the data collection effort, earlier compliance deadlines than the federal requirements , superior compliance records (including annual inspection records), a nd ability to provide the type of information needed for the s tudy. Because FDEP manages both USTs and aboveground stora g e tanks in an integrated program, Florida gathered data for both types of tank systems

. However, for purposes of this study , EPA limited the analysis to releases from UST s only

. 3



## Purpose Of T he

Study

The purpose of this study i s to quantify UST system performance by analyzing releases from U ST systems in Florida

. 4 

### The study provides information on the sources and causes of releases from UST systems. In addition, it examines how often leak de tection methods are succeeding or failing to detect releases from UST systems. When tank or piping is the source of a release, the study evaluates the construction details of the tank or piping and compares the releases from different construction types t o their frequency of use. The study also analyzes UST system age when the release was report ed , the volume of the release, environmental media affected, and secondary containment.



## Study Methodology

This section provides a brief overview of the study me thodology. The study methodology included the following steps:

• Specify criteria for including data

.
• Determine the specific type of data to be collected.

• Determine how and where data would be collected.

• Develop and apply data collection instruments (forms ).

• Collect, review
, and compile the data.

• Compile corresponding baseline data on UST system equipment use

.
• Develop data summaries and analyses.

Valid Versus Invalid Data

Florida requires owners and operators to repo rt releas e s ( of product to the environm

ent that cannot be quick ly cleaned up) and incidents ( small releases that can be quickly cleaned up or that do not reach the environment and false alarms ) when they occur . EPA and FDEP established criteria for determining which data would be included in t he data gathering and analysis based on the study objectives of developing information on the sources and causes of

2 As used in this document, the terms release and incident refer to events that require preparation and submittal of a Discharge Report Form (#62

- 761

- 900(1)) or Incident Notification Form (#62

- 761

- 900(6)), respectively, to the Florida Department of Environmental Prote ction (FDEP). 3 EPA may conduct additional analysis on the UST incident and AST release and incident data at a later date. 4 This study analyzes liquid releases. Vapor releases are not included in this study.Peer Review Draft

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### 4 releases from new and upgraded UST systems. EPA and FDEP co nsidered a data point invalid under any of the following conditions:

• Unknown r e lease source.

• Release occurred before July 1, 1992 ( final compliance date for Florida UST upgrade regulations)

.
• Tank system was installed prior to September 1, 1984 (date the first Florida UST regulations went into effect) and the release was discovered d uring closure activities.

• The component which was the release source did not meet regulatory requirements.

• The release source was a non

- regulated tank system.

• The release source was not associated with a tank system or filling (delivery or fue ling) activi ty

.
• Multiple tank systems were present and it was not clear which one was the release source.

• No release to the environment occurred, nor was information available to identify the occurrence as an incident.
Type O f Data Collected

EPA and FDEP collect ed a range of i nformation to describe the tank/piping systems and the release. For tank and piping systems, inspectors gathered various information, includ ing the installation date, material of construction, corrosion protection information

, type of overf

ill protection, type of leak detection and the presence and type of secondary containment. Inspectors also gathered information about releases, includ ing the release discovery date, source, cause, method of d iscovery , media affected and release volume.

D ata Collection
FDEP contracted with current and former county inspectors from nine of the largest counties in Florida ( Brevard, Broward, Dade, Duval, Hillsborough, Orange, Palm Beach, Pinellas, and Sarasota ) to collect the data

. These counties represent over 60 percent of the more than 6,500 UST and AST releases reported to Florida between January 1995 and April 2002. The inspectors reviewed and collected information from the files of facilities identified by FDEP as having reported one or more release s since January 1, 1995. 5 

### FDEP chose to have county inspectors collect the data because the inspectors were familiar with the structure and content of FDEP files and able to find and interpret the info rmation quickly and accurately.
Developing A nd Applying Data Collection Forms
EPA and FDEP developed releas e and incident data collection forms to facilitate data collection and to record information in a consistent format suitable for database entry and analysis ( Appendix A

contains these forms) . To help en sure the inspectors interpreted and applied the forms consistently, EPA and FDEP also developed instructions that included decision

- making rules and examples of how specific situations should be recorded. In order to

5 Prior to 1998, FDEP used one form to report both incidents and releases. Thus, some facilities identified as having a reported release between 1995 and July 1998 may in fact have reported an incident (based on the current FDEP definition, which is used in this study). In such situations, the inspe ctors who collected data for this study recorded the relevant information on an incident information form.Peer Review Draft

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### 5 effectively manage the large amounts o f d ata being collected, EPA us ed a database to enter and

a nalyze the data.
Data Review And Quality Control
EPA and FDEP implemented measures to ensure the quality of the data collected and analyzed in this study. Before data collection began, EPA and FD EP held conference calls with the Florida county inspectors (who would gather the data ) to discuss written instructions and provide examples of possible incident and releas e scenarios. As data colle ction

progressed
, FDEP discussed lessons learned with ins pectors

. Inspectors reviewed files, completed data col lection forms, and submitted files and forms electronically to FDEP and EPA. Both agencies review ed each data collection form for completeness and accuracy and , if necessary, supporting file informati

on. If EPA or FDEP found a problem , it was corrected by getting additional information from the inspector or reviewing the supporting file information.
EPA performed two types of quality control checks after entering data into the database. First, an in dividual who was not involved in the original data entry process selected 10 percent of the data entry forms at random from each batch of forms. The individual verified that the information in the database was identical to the information on the selected data forms, including any corrections made during the agency review

. Second, EPA queried th e database to tabulate the data and then reviewed the tabulations for inconsistencies. EPA highlighted any anomalies, reviewed related documentation, and upda ted t he database as necessary.
Summary And Analysis O f Release And Use Data

EPA summarized the data and then performed an analysis us ing a variety of parametric and no nparametric statistical methods

. Appendix B provides a de scription of the statistical metho ds used

. Appendix C presents a summary of the data and results of the statistical analyses

. EPA performed statistical analyses to determine whether the sources, causes, and methods of id entification were significantly different, marginally different , or not different . In addition, EPA compared detailed release source information (e.g., the percent of tank releases from single

- walled fiberglass tanks) to the corresponding use information (e.g., percent of tank s that are single

- walled fiberglass) to determ ine whether there were significant or marginal statistical differences

. Comparing releases to use is necessary to determine whether or not the frequency of releases for a given source is simply a function of its frequency of use. For example, if a specif

ic tank type is used 90 percent of the time but has only 10 percent of tank releases, then that tank type is performing well relative to its use . However, if a tank type is used 10 percent and accounts for 90 percent of tank releases, then that tank type is performing poorly relative to its use. EPA also compared the volumes of releases from different release sources and the differences in media affected by releases from tanks and piping systems. Finally, EPA compared the age distribution of releases (th e time from installation to release discovery) to the age distributions of tanks and piping systems in use.
EPA compiled data on the various UST system construction characteristics for the UST population in the nine count ies included in the study. This u se data came from two separate

sources

–the releases and incident s data set generated by this data

- gathering effort (referred to as R&I data) and from the FDEP database containing information on all USTs in the nine countiesPeer Review Draft

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### 6 (referred to as FDEP data). E PA believes the R&I data generally represent tank and piping use over the period of th

e study and FDEP data represent tank and piping use as of January 2003. EPA use d both data sets because some R&I data on the collection form

was not complete; either the re was no particular characteristic of interest on the form or there was no information available to the data collector. For example, the data collection forms did not provide unknown as a possible response in the section on tank secondary containment. T hus, a lack of information on secondary containment in the discharge or incident databases may indicate either that: the tank does not have secondary containment or the person completing the data collection form did not or could not determine whether secon dary containment was present. In these situations, EPA also relied on the FDEP data for use information. To remove potential bias from the R&I data for tank and piping releases, EPA did not include tank use information from a data point where the tank wa s the source of the release. Likewise, piping use information does not include data points where piping was identified as the source of the release

.



## Results

Valid A nd Invalid Data

FDEP collected data on 2,280 releases , including 512 valid UST releases and 130 valid AST releases. EPA

considered a data point invalid for purposes of this study for one or more of the reasons discussed in the Study Methodology section (see page 3)

. Figure 1 shows the relative frequency of reasons for invalidating data. T he most common reason (57 percent) is that the source of

release was unknown ( or not specified in the record). Other common reasons for invalidating data were that the release was discovered at closure and the system was ins talled before September 1984 (2 5 percent) and the facility was not in compliance with the UST regulations (10 percent)

. 6



### Figure 1: Summary Of Reasons F or Invalidating Data

57%

25%

10% 2% 7%

0% 20% 40% 60% 80%

Source

Unknown Closure &

Install Before 9/84 Leaking

Component Did Not Meet Regulations Release

Occurred Before 7/92 Other

Reason For Being InvalidPercent Of Invalid Data Points.

6 EPA classified 1,693 records as invalid.Peer Review Draft

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### 7 The following sections discuss the results of data analysis for UST r eleases. As noted above
, the statistical methods and the detailed results of the statistical analy ses are provided in Appendices B and C , respectively.

Release Sources
Figure 2 summarizes the sources of releases for the data. A total of 524 releases were reported from 512 records (some records reported multiple sources). Dispensers, piping, and delivery problems account for 25 percent, 23 percent, and 19 percent of releases, respectively
, and are the three most frequent sources of releases. T he remainder of releases came from tanks, turbine p umps, and other sources

. People putting product or used oil in monitoring wells (intentional or accidental), personal vehicles, and fill pipes are the most common other sources.
Figure 2: Sources O f UST Releases

25% 23%
19%

12% 10% 11%

0% 10% 20% 30%

Dispenser Piping Fuel Delivery Tank Pump (Turbine) Other

Release SourcePercent Of Releases.



### The proportions of relea ses from disp ensers and pipin g ar e significantly greater than releases from all other individual sources. The proportion of releases a ssociated with fuel delivery is significantly greater than the proportions of releases from tanks and turbine pumps. The difference b etween the number of piping and dispenser releases is not large enough to conclude that dispenser releases occur more frequently than piping releases.

Release Causes

Releases from UST systems were attributed to a wide range of causes ( Figure 3). Loose components accounted for the largest proportion of releases for any sing le known cause (23 percent ), followed by physical/me chanical damage (16 percent ) , overfill (15 percent) , and spills (14 percent) . Toget her, spills and over fills were responsible for 2 9 percent of all releases. The cause was unknown for 17 percent of releases.Peer Review Draft

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### 8 Figure 3: Summary O

f Known Causes F or All Releases ( 435 Known Causes Identified F or 524 Releases)

23%

16% 15% 14%

9%

5% 4% 4% 11%

0% 10% 20% 30%LooseComponentPhys/MechDamageOverfillSpillPunctureVehicleAccidentCorrosionImproperInstallOther

Release CausePercent Of All Releases



### W hile there are significant differences among the frequencies of the differ ent causes, the relative frequencies of causes vary substantially for different sources of release s

. These differences are discussed in the following sections. Fueling of tanks or vehicles ( which can result in spills, overfills, and deli veries to monitor ing wells ) appear s to be the most common class of ca uses. T he proportion of releases due to improper ins tallation may be un derreported because improper installation is hard to identify in the field after a release has occurr ed. D eliveries to monitoring w ells were the most frequent other cause.

Releases F rom Dispensers

R eleases from dispensers were the most frequent source, accounting for 25 percent of all releases. Releases from dispensers include not only releases from inside the dispenser housing, but also releases from hoses and nozzles. The cause was unknown for 36 percent of dispenser releases. Figure 4 pro vides a breakout of known c a u ses for dispenser releases

. The most common known causes of dispenser releases were loose components (41 perce nt), vehi

cle accidents (17 percent), physical or mechanical damage (13 percent) , and s pills ( 12 percent ). Releases due to loose components occur significantly more frequently than releases from any other known dispenser cause. Releases from dispensers du e to vehicle accidents, physical/mechanical damage, and spills occur significantly more frequently than releases due to the less common causes (corrosion, puncture, and improper installation). Vandalism and human error were the two most common other cause s.Peer Review Draft

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### 9 Figure 4: Known C auses O f Dispenser Releases (83 Total Known Dispenser Release Causes )

41%

17% 13% 12%

5% 2% 1% 8%

0% 10% 20% 30% 40% 50%LooseComponentVehicleAccidentPhys/MechDamageSpillImproperInstallPunctureCorrosionOther

CausePercent Of Dispenser Releases



### EPA evaluated the potential effectiveness of under

- dispenser containment (UDC) on the frequency of dispenser releases. Table 1 shows release and use data for dispensers with and without UDC. Looking at the R&I u se data, r eleases from dispensers without UDC were slightly less frequent (33 percent) than dispensers that use UDC (36 percent). This difference is no t significant . While this analysis does not indic ate any effect by UDC on the frequency of dispenser releases, t hese results are subject to potential reporting bias

because the data collection form only prompted inspectors to indicate if UDC was present and did not provide a means for indicating no UDC o r whether the presence of UDC was unknown. Thus, some of the facilities without dispenser releases characterized as not having UDC might be fac ilities where the presence or

absence of UD C was not determi ned. Therefore , EPA also evaluat ed dispenser second ary c ontainment using the FDEP data . Based on th at data, EPA found the use of dispenser containment is much more common than indicated by the data collected in this study and dispenser releases occur significantly more frequently

–approximately twice as often

–when dispenser containment is not present. EPA believes the FDEP data is more accurate, indicating that UDC appreciably reduces the frequency of releases from dispensers.

Table 1 : Dispenser Releases And Secondary Containment

R&I Data FDEP Data Dispenser Secondary C ontainment Number O f

Dispenser Releases Percent O f

Dispenser Releases Records With

Non

- Dispenser Releases Percent Of Use UST Systems Percent Of Use Present 43 33% 202 36% 12,362 81% Not Present 87 67% 365 64% 2,833 19% Total 130 10 0% 567 100% 15,195 100%Peer Review Draft

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### 10 Releases F rom Piping

Cause s O f Releases. P iping was the sourc e for 23 percent of

UST releases

. Figure 5 shows the relative frequency of known piping causes. The cause was unknown for 21 percent of piping releases. Of known c auses, the more common were physical/mechanical damage (28 percent), loose components (26 percent) , and puncture (20 percent). Other less common caus es each accounted for eight

percent or less of

piping rel

eases

. All of the more common piping release caus es noted above occur significantly more frequently than the less common causes.

Figure 5: Known Causes Of Piping Releases * ( 97 Total Known Piping Release C auses)

28% 26%

20%

8% 6% 6% 8%

0% 10% 20% 30%

Phys/Mech Damage Loose

Component Puncture Corrosion Improper Install Vehicle

Accident Other

CausePercent Of Piping Releases

* Includes 111 releases from piping, plus 10 releases reported from both dispenser and pipi ng and one release reported from both piping and tank, but excludes 26 piping releases of unknown cause.



### Material Of Construction. Releases from fiberglass piping represent 77 percent o f all piping releases. Figure 6 shows a summary of known causes for fiberglass piping releases. The cause was unknown for 24 percent of fiberglass piping releases. L oose component, puncture, and physical/mechanical damage are the most common causes for fiberglass piping. These three causes occur significantly more often than any of the other known causes for fiberglass piping.
Note that corrosion was identified as the cause of 4 percent of fiberglass piping releases. However, fiberglass itself doesn’t corrode

–what corrodes are the metal connectors that may be include d as part of the fiberglass piping system. Releases from the metal connectors attached to fiberglass piping are included in the releases attributed to fiberglass piping. This applies equally to metal and approved synthetic material piping releases. EPA include s metal connectors in the releases by

piping construction because the data collection form did not specifically includePeer Review Draft

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### 11 metal connectors as a source of release. Some data forms indicated the specific location of the release in the comments area

. T here may be other cases where the metal connector was the source of release but that information was not recorded. Therefore, EPA could not be sure that all cases where the release occurred from the metal connector were identifi ed.
Figure 6 : Known Causes Of Fiberglass Piping Releases ( 71 Total Known Fiberglass Piping Release C auses)

28%

25% 25%

6% 4% 4%

0% 10% 20% 30%

Loose Component Phys/Mech

Damage Puncture Improper Install Corrosion Other

CausePercent Of Fiberglass Piping Releases



### Releases from steel piping represent 14 percent of all piping releases. Figure 7 shows a summary of known causes for steel piping releases. The cause was unknown for 13 p ercent of steel piping releases. C orrosion occurs more frequently than any other cause. However, the statistical analysis does not show that corrosion occurs significantly more often than any of the other causes. EPA looked at the type of cathodic prote ction (impressed current or galvanic anodes) used when corrosion was the cause of a steel piping release. However, there were insufficient data to perform any analysis.
Releases from piping made of approved synthetic material 7 

### represent nine percent of all piping releases. Figure 8 shows a summary of known causes of releases for piping made of approved synthetic material. The cause was unknown for 18 percent of releases for piping made of approved synthetic material. Physical/mechanical damage occurs more frequently than any other cause.

7 According to FDEP, approved synthetic material is flexible plastic piping.Peer Review Draft

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### 12 Figure 7 : Known Causes Of Steel Piping Releases ( 15 Total Known Steel Piping Release C auses)

33%

20% 20%

7% 7% 13%

0% 10% 20% 30% 40%

Corrosion Phys/Mech Damage Loose

Component Vehicle

Accident Improper

Install Other

CausePercent Of Steel Piping Releases



### Figure 8 : Known Causes Of Approved Synthetic Material Piping Releases ( 9 Total Known Approved Synthetic Material Pipin g Release C auses)

67%

22%

11%

0% 10% 20% 30% 40% 50% 60% 70% 80%

Phys/Mech Damage Loose Component Puncture
CausePercent Of Approved Synthetic Material PipingReleasesPeer Review Draft

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### 13 Figure 9 shows a comparison of piping releases and use by material of construction. T he proportion of rel

eases from fiberglass piping (77 percent) was not significantly different than the proportion of UST

s using fiberglass piping, bas ed on both the R&I data (7 1 percent) and the FDEP data (77 percent). Similarly, the proportion of releases from approved synthetic piping was not significantly different than the proportion of systems that used this type of piping. For steel piping, the data indicate the difference between the proportion of steel piping releases (14 percent) and the proportion of steel piping sy stems (21 percent) is marginally significant based on the R&I data. However, a significant and opposite relationship appears bas ed on comparison with the FDEP data that indicates 8 percent of piping is steel. EPA believes the FDEP data is an accurate reflection of steel pipe use in January 2003, while the R&I data is more indicative of steel pipe use over the period of the study

. Overall, the data suggest the material of construction does not strongly affect frequency of release s from piping when comparing piping release and use data

. Figure 9 : Piping Releases And Use Versus Piping Material O f Construction *

77%

14% 9%
0% 71%

21%

7% 1% 77%

8% 14%

2% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

Fiberglass Steel Approved Synthetic Material Other FDEP Approved Material Piping ConstructionPercent

Piping Releases Piping Use (R&I) Piping Use (FDEP)

* Excludes two rel

eases where the material of construction was unknown or not reported.


### Secondary Containment. The release data show th at 43 percent of piping releases were from secondarily

- contained piping

(Table 2 ) . This proportion is the same as the proportion of pip ing using secondary containment in the R&I data

. These results are subject to potential reporting bias, however, because the data collection form only prompted inspectors who completed the form to indicate if secondary containment was present and did not provide a means for indicating no seco ndary containment or unknown. Therefore
, the use of piping secondary containment may be underreported in the R&I data. EPA believes the FDEP data better reflects the use of secondarily

- contained piping. Based on thi s data, the use of piping secondary containment is much more common (60 percent compared to 43 percent) and the difference in the frequency of release s and use from secondarily

- contained piping is significant. Therefo re, these analyses suggest piping seco ndary containment is effective in reducing thePeer Review Draft

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### 14 frequency of piping releases. Further statistical analyses using the FDEP data shows that single

walled piping is nearly twice as likely to have a release to the environment as secondarily

contained piping

( s ee the statistical

analysis o n page C

- 11 )

.
Table 2 : Effect O f Secondary Containment On Piping Releases
R&I Data FDEP Data Piping Secondary Containment Number O f

Piping Releases Percent Of

Piping Release s Records With Non

- Piping Releases Percent Of

Us e U

ST Systems Percent Of

Us e Present 53 43% 214 43% 9,101 60% Not Present 69 57% 286 57% 6,026 40% Total 122 100% 500 100% 15,127 100%


### Pressure Versus Suction Pumps. Most UST s were identified as having pressure pumps (88 percent)

with t he remainder of UST s usin g suction pumps (12 percent). A s shown in Table 3 , the proportions of releases from piping at UST s with pressure and suction pumps closely matc hed the R&I use data . The differences in proportions of piping releases versus piping use are not sig nificant for either pump type. Thus, the data do not suggest a disproportionate probability of piping releases as sociated with either pressure or suction pumps.

Table 3 : Piping Releases And Pump Type
R&I Data Pump Type For Piping Releases Number O f

Piping Releas es Percent Of

Releases Records W ith Non

Piping Releases Percent Of Us e Pressure Pump 100 90 % 409 88 % Suction Pump 11 10 % 54 12 % Total 111 100 % 463 100%


### Compa rison Between Age Of Piping In Us e A nd Time T o Piping Releases (Use

Release Analy sis). All

of the comparisons to this point between frequency of rele ase s and use have been made without considera tion of piping age . Analyses that examine the relationship between age and release frequency can help address the relative performance over t ime of different piping configurations and materials of construction. EPA examined the relationship between the age distribution of piping in use and the age distribution of piping with releases in three ways

– average age comparison, young versus old pip ing comparison, and cumulative age distributions . In these analyses, EPA used FDEP data as the source of the age distribution of piping in use

. EPA determined the FDEP data to be a more appropriate source of information on the age of the piping in use bec ause the age of piping i n the R&I data is artificially limited by the date when a n UST release occurred

. First, EPA performed a use versus release comparison by material of construction and by type of product delivery system for average piping age. This analysis shows the average release age for fiberglass , steel, and pressurized piping is significantly lower than the average use age for that type of piping. The average release age for approved synthetic piping and suction piping was also lower than the average use age; however, these differences were not statistically significant.
Second, EPA compared releases to use for young and old piping. Young is defined as piping under a specified age and old is piping greater than that age. EPA analyzed fo ur di fferentPeer Review Draft

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### 15 age groupings : less than 5 years old, less than 10 years old, less than 15 years old, and less than 20 years old. For piping less than 5 years old, steel and fiberglass piping release s were marginally greater than corresponding use. For approved synthetic piping under 5 years old, releases were significantly lower than use. For piping less than 10 years old, fiberglass piping releases were significantly greater than corresponding use, steel piping releases were marginally greater than use, and ap proved synthetic piping releases were significantly lower than use. For piping less than 15 years old and piping less than 20 years old, there were no significant difference s between releases and use with one exception

–approved synthetic piping releases were marginally lower than corresponding use for synthetic piping less than 15 years old.

Third , EPA compared cumulative age distributions of piping in use to those of piping with releases. This statistical test looks at the difference between releases and use at each 5 year age increment by analyzing the overall shape of the age curve

. T he differences were significant for all piping combined , for fiberglass piping and for piping associated with pressure pump systems. Specifically, releases are not di stributed uniformly over the life of these piping systems; rather, they occur more frequent ly when the systems are less than 15 years old

. It is not surprising t o find the same for all piping, fiberglass piping, and piping associated with pressure pump sy stems because, as noted above, most piping is fiberglass, most pump systems are pressurize d systems, and most releases were from fiberglass and pressurized piping systems.
Releases During Fuel Delivery
As indicated in Figure 2, 19 percent of releases o ccurred during fuel delivery. Overfills and spills were identified as the cause of 50 percent and 43 percent of these releases, respectively (Figure 10 ). Loose components were associated with 3 percent of releases. All other causes were fuel deliveries t

o monitoring wells. There were no unknown causes for fuel delivery releases.
Figure 10 : Known Causes Of Releases During Fuel Delivery ( 101 Total Known Fuel Delivery Release Cause s)

50%

43%

3% 4%

0% 10% 20% 30% 40% 50% 60%

Overfill Spill Loose Component Other
CausePercent Of Fuel Delivery ReleasesPeer Review Draft

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### 16 To analyze the impact of overfill protection on releases, EPA compar ed the overfill protection used when a fuel delivery release occurred with the general use of overfill protection in both the R&I data and the FDEP data (Table 4 ). EPA could not evaluate the effectiveness of spill buckets because the UST systems without s pill buckets were reported as being out of compliance and, thus, were not classified as valid data points for the purposes of this study. In addition, the condition of spill buckets was not recorded.

Table 4 : Fuel Delivery Releases And Overfill Protecti on Methods *
R&I Data FDEP Data Overfill Protection Method Number Of

Delivery Releases Percent Of

Delivery Releases Records With Non

Delivery Releases Percent Of Use UST

Systems Percent Of

Use Ball Check Valve 36 77% 473 81% 11,122 67% Flow Shutoff 11 23% 105 18% 5,593 33% Total 47 100% 578 100% 16,715 100%

* Excludes high level alarms because an anomaly on the data collection form is likely to have resulted in underreporting of high level alarm use

. 

### The proportion of total releases occurring at USTs with ball check valves (77 percent) is slightly lower than USTs using ball check valves in the R&I data (81 percent), but the difference is not statistically significant. Similarly, the proportion of releases at USTs with flow shutoff (23 percent) is not

significantly different from USTs using this technology (18 percent). In addition, comparison of the frequency of release with the frequency of use based on the FDEP data also indicates no significant difference for either overfill protection method. Th us, the data suggest the type of overfill protection used does not affect the likelihood of UST releases.

Releases F rom Tanks

Cause s O f Release s . Tank releases represent 12 percent of all UST releases in the data. Figure 1 1 shows the known causes for tank releases. The cause w as unknown for 14 percent of tank releases. Puncture was the most common cause, identified in 31 percent of releases. Physical or mechanical damage (26 percent) and corrosion (19 percent) were also common causes of release s

. L

ess common causes (loose components, overfill, or improper installation) collectively accounted for 13 percent o f all tank releases. Eleven percent of tank release causes were listed as other and were primarily due to damage during removal and damage duri ng delivery. The more common causes of tank releases occur significantly more frequently than a ll of the less common causes

. The comparatively high frequency of puncture and physical or mechanical damage as the cause of release is not surpris ing given, a s discussed below, that the majority of tank releases were from fiberglass tanks

.Peer Review Draft

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### 17 Figure 11 : Known Causes Of Tank Release s ( 54 Total Known Tank Release Causes ) *

31%

26%

19%

9%

2% 2% 11%

0% 10% 20% 30% 40%

Puncture Phys/Mech

Damage Corrosion Loose Component Overfill Improper Install Other

CausePercent Of Tank Releases

* Includes 61 releases from tanks plus one release reported from both dispenser and a tank and one release from both piping and a tank.



### Material Of Construction. Releases from steel tanks 8 

### represent 30 percent of all tank releases. Figure 12 shows a summary of known causes for steel tank releases. The cause was unknown for 12 percent of ste el tank releases. Corrosion is the most frequent known cause representing 59 percent of steel tank releases. Corrosion occurs significantly more frequently than any other known cause for steel tanks. EPA looked at the type of corrosion protection (inter nal lining, impressed current, or galvanic anodes) used when corrosion was the cause of a steel tank release. For the ten steel tank releases due to corrosion, four came from tanks with impressed current and three each from tanks with galvanic anodes and from in ternally lined tanks. There were not enough data to support statistical analyses by corrosion protection type.

8 Fiberglass

- clad steel tan ks are considered as a separate category in this study and are not included when analyzing steel tanks.Peer Review Draft

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### 18 Figure 12 : Summary Of Known Causes For Steel Tank Releases

( 17 Total Known Steel Tank Release Causes)

59%

18%

12%

6% 6%

0% 10% 20% 30% 40% 50% 60% 70%

Corrosion Phys/Mech Damage Loose

Component Puncture Improper Install

CausePercent Of Steel Tank Releases



### Releases from fiberglass tanks represent 65 percent o f all tank releases. Figure 1 3 shows a summary of known causes for f iberglass tank releases. The cause was unknown for 17 percent of fiberglass tank releases. Puncture and physical/mechanical damage are the two most frequent

causes of releases for fiberglass tanks. Punctures occurred significantly more often than all other causes except physical/mechanical damage for which it wa s marginally greater. Physical or mechanical damage occurred significantly more often than loose compone nts and overfills.
Fiberglass

- clad steel, polyethylene (jacketed steel), and concrete tanks each had one release. There were insufficient data to analyze the causes of release for these tank types.
As was done for piping releases, EPA compared tank re leases and use by material of construction (Figure 14 ). The proportion of releases from fiberglass tanks (65 percent) was not significantly different than fiberglass tank use, based on both the R&I data and the FDEP data. Similarly, the analysis indicate s steel tank releases (30 percent) were not significantly different than the steel tank use (27 percent), based on the R&I data. In contrast with the R&I data for steel tanks, the FDEP data show steel tanks are used less often (18 percent), resulting in s teel tank releases being significantly greater than steel tank use for the FDEP data. Thus, the data do not suggest a clear conclusion regarding the frequency of release relative to use for steel tanks. In contrast, the data do clearly suggest that relea ses from fiberglass

- clad steel tanks (2 percent) are significantly less than the fiberglass

- clad steel tank use for both data sets (18 percent and 23 percent).Peer Review Draft

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### 19 Figure 1 3 : S ummary Of Known Causes For Fiberglass Tank Releases

(35 Total Known Fiberglass Tank Release C auses)

46%

31%

3% 3% 17%

0% 10% 20% 30% 40% 50% 60%

Puncture Phys/Mech Damage Loose

Component Overfill Other

CausePercent Of Fiberglass Tank Releases



### Figure 1 4 : Tank Releases And Use Versus Tank Material Of Construction

65%

30%

2% 2% 2% 55%

27%

18%

0% 0% 59%

18% 23%

0% 0% 0% 10% 20% 30% 40% 50% 60% 70%

Fiberglass Steel Fiberglass-Clad Steel Polyethylene Concrete
Tank ConstructionPercent

Tank Releases Tank Use (R&I) Tank Use (FDEP)Peer Review Draft

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### 20 Secondary Containment. To analyze the impact of secondary containment on releases, EPA com pared releases from secondarily

- contained tanks to both the R&I use dat a and FDEP

use data (Table 5 ). When examining the R&I use data, t he proportion of releases from tanks with secondary contain ment ( 6 percent) i s much lower than the proportion of tanks with secondary containment (23 percent). Th e difference is significant , to the extent that the chance of a release from a tank without secondary containment is approximately four times greater than from a tank with secondary containment (see the statistical analysis o n page C

- 10 ).

Table 5 : Effect O f Secondary Containment O n Tank Releases
R&I Data FDEP Data
Tank Secondary Containment Number O f Tank Releases P ercent O f

T ank Release s Records With

Non

- Tank Releases P ercent Of

Us e UST

Systems Percent Of

Us e Present 4 6% 144 23% 6317 42% Not Present 59 94% 484 77% 8878 58% To tal 63 100% 628 100% 15195 100%


### As with the piping analysis, EPA believes the R&I data undercount tank systems wi

th secondary containment and the FDEP data better reflects the use of these systems. When the FDEP data on tank use and releases are compare d , the difference between use and releases from secondar il y

- contain

ed tanks is even greater . The difference between the proportion of releases from tanks with secondary containment (6 percent) and the use of tanks with secondary containme nt (42 percent) i s significant
, resulting in the relative risk of a release from a tank without secondary containment being more than 10 times greater than from a tank with secondary containment (see the statistical analysis on page C

- 10 )

. Thus, the data strongly support that the presence of tank secondary containment results in fewer releases to the environment

from tanks.

C omparison Between Age Of Tanks A nd Time T o Tank Releases. EPA examined the relationship between the age distribution of tanks in use and the age dis tribution of releases from tanks in a similar

manner as described above for releases from piping

. The differences in the average ages of tank releases to the average age of tanks in use were not significant for any tank construction

. A lso
, the cumulative age distributions of all tanks and for steel and fiberglass tanks in use were not significantly different than the distributions of tank age at the time of release. EP A did not perform

comparisons for fiberglass

- clad steel tanks because the study data in clude so few release s from this type of tank.
Pump (Turbine)

Releases
Figure 15 shows the known causes of release s from turbine pumps 9



### . The cause was unknown for 12 percent of turbine pump releases. Of know n causes, loose component was the most common

cause of release (48 percent), followed by physical and mechanical damage (30 percent)

. A l

ess common cause

was improper installation (11 percent ). The most common other release causes for turbine pumps were all related to human error. Pump releases ca used by loose components were significantly more frequent than releases from any of the other known causes. Physical or mechanical damage was a significantly more frequent cause than any of the other

9 Pump (turbine) releases include releases from line leak detectors.Peer Review Draft

– March 2005 Do Not Cite Or Quot e 

### 21 causes except loose components. R eleases due to improp er installation were significantly more frequent than releases due to puncture.

Figure 15 : Known Causes F or Pump (Turbine) Releases ( 46 Total Known Pump Release Cause s)

48%

30%

11%

2% 9%

0% 10% 20% 30% 40% 50%

Loose

Component Phys/Mech

Damage Improper Install Puncture Other

CausePercent Of Pump (Turbine) Releases



### Other Release Sources

Other release sources are those identified as not fitting into one of the major categories previously discussed. Other sources primarily include releases from fill pipes , vapor recovery lines, vent lines (other than those releases occurring during deliv ery), and releases associated wi th personal vehicles

. Figu re 1 6 shows the distribution of known causes for other releases

. Four p ercent of other release source causes were unknown. Overfills, loose components, and spills are the major known causes of other releases. Most of the other release causes were due to either intentional or unintentional deliveries to monitoring wells. These deliveries are not associated with fueling, but rather putting fuel or used oil into a monitoring well by hand. Among the other sources, overfills were marginally greater than loo se components and significantly greater

than releases from the other identified causes. Releases due to loose components were significantly more frequent than other identified causes except spill s. Spills were significantly greater than all other less fr equent causes.Peer Review Draft

– March 2005 Do Not Cite Or Quot e 

### 22 Figure 1 6 : Known Causes F or Other Releases ( 53 Total Known Other Release Causes )

26%

17%

13%

4% 4% 2% 35%

0% 10% 20% 30% 40%

Overfill Loose

Component Spill Phys/Mech Damage Puncture Improper Install Other

Release CausePercent Of Other Releases



### Volume O f Releases
The sizes (volumes) of releases were reported for 31 percent of releases . Limited data on the distribution of release volumes are avai lab le for the most common sources ( Table 6 ) . The average volume released ranges from just ove r 1,150 gallons for piping to 3 3 gallons for

turbine pumps. Omitted from the table are releases attributed to multiples sources

–one from piping a nd dispenser ( 85 gallons) and one from ta nk and piping (10 gallons). Median releases are much smaller than the averages because of the skewed nature of the volume distributions. Most releases are small, but the averages are strongly affected by a few very large releas es. Because th e data are not normally distributed , confidence limits on the average releases were calculated using non

- parametric bootstrap sampling.
Of the known sources, piping and tanks have the highest average release volumes

– 1,152 and 696 gallons per release, respectively. The average volume for piping is strongly influenced by one very large release (25,000 gallons), without which the mean release would be about 525 gallons. The average release volume for dispenser releases is 260 gallons, less than fo r tanks and piping, but more than

twice as high as the averages for all other specified sources. These data suggest that t anks, piping, and dispensers are mo re likely to have a large release, though the median release size across release sources w as relatively similar.Peer Review Draft

– March 2005 Do Not Cite Or Quot e 

### 23 Table 6 : Release Volumes For The Different Sources

Release Source Number O f

Releases O f Known Volume Average

Release (G al lons ) Median

Release (G al lons ) Minimum

Release ( G al lons ) Maximum

Release ( G al lons ) Lower 95%

Confidence Limit O f Mean (G al lons )* Upper 95%

Confidence Limit O f Mean (G al lons ) Piping 39 1,152 50 2 25,000 202 2,701 Tank 17 696 50 5 3,500 228 1,283 Other 23 408 25 2 5,000 66 939 Dispenser 30 260 25 3 3,400 64 543 Fuel Delivery 43 126 50 1 1,250 64 208 Fill Pipe 3 93 55 25 200

-- -- Pump (Turbine) 6 33 23 10 75 15 54 Overall 161 491 40 1 25,000 231 878 * Confidence limits were calcu lated by resampling (bootstrap ) analyses of the data (10, 000 iterations for each

source )

.


### Environmental Media Affected B y UST Rele ases
Releases can affect both soil and water. However, because releases to water are of gre ate st concern , this section focuse s on the extent to which releas es from different sources impact ground water or

surface water

. Summary data show that more than 60 percent of all releases impacted water

( Table 7 )

. Note that

Florida has a high groundwater table. Therefore, the impacts to groundwater in this study may be higher than in states with lower groundwater tables. However, the relative likelihood of dif ferent release sources rea ching groundwater should be independent of groundwater depth

.
Table 7 : Releases Affecting Groundwater A nd Surface Water By Source O f Release Impacting Groundwater Impacting Surface W ater Total Impactin g Water Source Number

O f Releases Number Percent Number Percent Number Percent Percent Of Each Sources ’ Contribution To Total Water Impacts Fuel Delivery 101 64 63% 2 2 % 66 65 % 21% Dispenser 130 53 41 % 4 3 % 57 44 % 18% Piping 122 71 58 % 3 3 % 71 58 % 22% Pump (Turbine) 52 32 62 % 0 0 % 32 62 % 10%
Tank 63 54 86 % 1 2 % 54 86 % 17%
Other 56 35 63 % 4 7% 39 70 % 12% Total Media Affected 524 309 59 % 14 3 % 319 * 61 %

* Total does not sum because four releases affected both groundwater and surface water


### Figure 17 shows the proportion o f releases from each source affecting water. T he proportion of tank releases that impact groundwater

or surface water (called water) is larger (86 percent) than for any other release source, while dispensers have the lowest proportion of releases from a g

iven source impacting water (44 percent).Peer Review Draft

– March 2005 Do Not Cite Or Quot e 

### 24 Figure 17 : Proportion O f Releases F rom Each Source Affecting W ater

86%

65% 62% 58%

44% 70%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Tank Fuel Delivery Pump (Turbine) Piping Dispenser Other

Release SourcePercent Releases From Each SourceImpacting Water.



### Figure 18 shows a breakdown of the proportions of total releases affecting water from each source , reflecting both release volume and releas e frequency . The most frequent sources of releases to water are piping (22 percent) and fuel delivery mishaps (21 percent). Dispensers and tanks are the next frequent sources of releases to water at 18 percent and 17 percent, respectively. The proportio ns of releases to water from the four most common sources

–piping, fuel del ivery, dispensers, and tanks

–are significantly more frequent than releases from the less common

sources. Although the data in Figure 17 indicate a tank release is about twice as likely as a dispenser release to affect water, dispenser releases are about twice as common as tank releases, with the result that the overall frequency with which these two sources affect water is about the same (as shown in Figure 18).Peer Review Draft

– March 2005 Do Not Cite Or Quot e 

### 25 Figure 18 : Total Number Of Releases Affecting Water By Source

22% 21%
18% 17%

10% 12%

0% 10% 20% 30%

Piping Fuel Delivery Dispenser Tank Pump (Turbine) Other

Release SourcePercent Contribution To Total WaterImpacts.



### Method O

f Release Discovery

T he method of release discovery was reported for 99 percent of all release s. Of releases with a known method of discovery
, 26 percent were discovered by le ak detection methods ( F igure 19 ). The m ost common method of discovery was visual

and/or olfactory

(38 percent)
, i.e. , by seeing or smelling the release . Closure, defined as releases identified through clos ure in place or removal
, accounted for 15 percent of releases discovered

. Nearly one

- half of the releases in the other category, or 7 percent of all releases, were identified through compliance or maintenance inspections. Tank tightness testing or line tightness testing performe d for reasons other than leak detection 10 

### was re ported as the method of release discovery in only a small proportion of releases (5 percent) . These data are notable in that the majority of releases are identified by a means other than leak detection. However, most of the leak detection technologies ev aluated in this study are designed to only detect releases from tanks and piping, and the majority of releases (a bout 65 percent) come from non

- tank and non

- piping sources. The high proportion of releases that are first detected simply by seeing or smelli ng the release is noteworthy . This proportion is significantly greater than the proportions di scovered by any other method

.

10 Tank tightness testing or line tightness testing for leak d etection are included in the leak detection count, but tightness testing used for other purposes (e.g., to investigate a suspected release ) was separated into its own category.Peer Review Draft

– March 2005 Do Not Cite Or Quot e 

### 26 Figure 19 : Method O f Release Discovery (505 Total Releases With A Method Of Discovery Identified)

38%

26%

15%

5% 16%

0% 10% 20% 30% 40%

Visual/Olfactory Leak Detection Closure TTT Or LTT Performed For Other Reasons Other

Method Of DiscoveryPercent Of Releases



### Perform ance O f Leak Detectio n Methods
EPA gathered informati

on on the proportions of releases where specific leak detection methods failed or succeeded in detecting releases. Leak detection was identified as failing to detect 23 percent of release s and succeed ed in detecting 26 pe rcent of releases

. For the other 51 percent, EPA could either not make a determination or the leak detection device did not have an opportunit y to detect the release

.
Table 8 co mpares the frequencies with which specific technologies were identified as

su cceeding or failing to detect releases with the ir

frequencies of

use in the R&I data

. S everal leak detection technologies are identified as failing or succeeding significantly more or less frequently than their corresponding use. Groundwater monitoring, the most frequently used technology (52 percent of facilities), is reported to have both failed and succeeded in detecting releases significantly more frequently than it is used. Convers e ly, secondary containment/ interstitial monitoring, manual tank gaug ing, and automatic gauging are identified as succeeding and failing less often than they are used. Give n these results, EPA could not make any determinations of whether one leak detection method is better than another in terms of both succeeding and not f

ailing to detect a release.Peer Review Draft

– March 2005 Do Not Cite Or Quot e 

### 27 Table 8 : Proportions O f All Releases Identified A nd Not Ident ified B y Tank L eak Detection Methods Compared To Frequency O f Use

Leak Detection Method Number

Identified As Failed Percent Of

Identified Failures* Number

Identified As Succeeding Percent Of

Identified Successes * Number Used

(R&I Data)** Percent Use

(R&I Data)**

Groundwater Monitoring 70 73% 84 73% 396 52% Automatic Tank Gauging 1 1% 0 0% 106 14% Secondary/Interstitial 11 11% 8 7% 97 13% IC/TTT*** 9 9% 11 10% 54 7% Manual Tank Gauging 1 1% 1 1% 39 5% Line Tightness Testing 0 0% 9 8% 33 4% SIR*** 3 3% 2 2% 31 4% Vapor M onitoring 1 1% 0 0% 8 1% Total 96 100% 115 100% 764 100% * Dark shading = significan tly different from us e; l ight shading = margin a lly different. ** Excludes incidents involving false or faulty leak detection alarms. *** IC/TTT = inventory control/tank tightness testing; SIR = statistical inventory reconciliation.


### EPA also compared the frequencies of success and failure for electron ic and mechanical line leak detectors ( LLDs) with their corresponding use in the R&I data . The results of that analysis are shown in Table 9 . The frequencies at which electronic and mechanical LLDs succeed or fail to detect releases are not significantly differen t from their frequencies of us e. Thus, the data do not indicate either method is more or less effective than the other

.
Table 9 : Failures A nd Successes For Electronic A nd Mechanical Line Leak Detectors

Leak Detection Method Number

Identified As Failed Percent Of

Identified Failures Number

Identified As Succeeding Percent Of

Identified Successes Number Used

(R&I Data)* Percent Use

(R&I Data )*

Electronic LLD 4 17% 21% 4 63 18% Mechanical LLD 19 83% 79% 15 280 82% Total 23 100% 100% 19 343 100 % * Excludes incidents involving false or faulty leak detection alarms.Peer Review Draft

– March 2005 Do Not Cite Or Quot e 

### 28 

## Discussion O f Results

EPA and FDEP reviewed data from 2,28 0 releases or incident s in nine Florida counties

. From these, 512 sites were identified with releases from new or upgra ded UST systems and had sufficient and appropriate data to include in this study. EPA analyzed the data for sources, causes, component

- specific characteristics (such as material of construction and secondary containment) , method of release discovery , medi a affected, and release extent. Data for UST incidents and AST releases and incidents were not included in this report, but may be analyzed for futu re reports.

Releases And Causes
Dispensers, piping, and fuel delivery were the three most frequent sou rc es of releases. Tanks and turbine pumps were also common sources, but releases from these sources occurred significantly l

ess frequent ly than the three most frequent sources . Piping has been a frequent source of UST system releases since the inception of the program, as has fuel delivery. These sources persist despite release prevention requirements aimed at reducing these rel eases. Dispensers, however, have emerged as a frequent source of releases. Neither EPA nor most states have release prevention requirements for disp ensers. Tanks are a much less frequent source of release than dispensers, piping, and fuel delivery. This may indicate success in regulatory requirements aimed at reducing releases from tanks. Turbine pumps, in cluding the attached line leak detectors , are typically not subject to release prevention requirements, unless they are in contact with soil.
Loose components are the most frequent known cause of releases at 23 percent, occurring significantly more often than any other relea se cause. P hysical or mechanical damage , overfills, and spills each occurred about 15 percent of the time

. The most common class of known causes is associated with deliveries or vehicle fueling and includes spills
, overfills, and deliveries to monitoring

wells. The frequency of different known causes varies substantially by source and is discussed f

urther below. Please also note the proportion of releases due to improper installation is likely underreported because improper installation is hard to ident ify in the field after a release ha s occurred

. T hus this study does not allow EPA to say with certain t y the extent improper installation leads to UST system releases. Another important consideration is that while loose components and physical / mechanical damage are si gnificant causes of releases, EPA generally could not pinpoint the specific cause s for the loose component or damage

–be they poor materials, improper installation
, or improper or insufficient ope ration and maintenance

. Dispensers
Dispense rs were the most common sourc e of releases at 25 percent , occurring significantly more frequently than all other release sources except piping . Loose component s
w ere the most common known cause of dispenser releases at 41 percent , occurring significantly more frequently than any other known cause. Dispensers contain many different components , so there are many opportunities for connections to become loose. Vehicle accidents, physical or mechanical damag

e, and spills were also common causes of releases at dispensers

. The high occurrence of dispenser releases is an important finding because EPA and most states do not have any release prevention requirements for dispensers

. L ooking at UDC, t he presence of UDC significantly reduced the likelihood of a relea se from a dispenser when compared to FDEP data
,Peer Review Draft

– March 2005 Do Not Cite Or Quot e 

### 29 with dispenser releases occurring about twice as often at dispensers with out UDC than at those with UDC

. Piping
Piping was the second most frequent source of releases
, represent ing 23 percent of releases in the data

. Piping releases occurred significantly more frequently than all other release sources except dispensers. Physical / mechanical damage, loose component s, and puncture were the three most frequent known causes of piping releases. The relatively l arge percentage of releases due to puncture was somewhat surprising, and highlights the need to more carefully consider tank and piping location while performing co nstruction work at a n UST site. It is important to note, however, that the causes of releas es varied significantly by material of construction.
Fiberglass piping (includ ing any associated metal connectors) is the most commonly used piping and is the most frequ ent source of piping releases. Loose component, physical or mechanical damage, and pu nctures were the predominant known causes of fiberglass piping releases. C orrosion was iden tified as the cause of four percent of fiberglass piping releases. H owever, f

iberglass itself doesn’t corrode

–what corrodes are the metal connectors that are typ ically included at the ends of the fiberglass piping

. Releases from the metal connectors attached to fiberglass piping are included in the releases attributed to fiberglass piping . EPA could not separate these releases because the number of fiberglass pi ping releases from the metal portion of the piping run

could not be identified

. Corrosion was the primary known cause of releases from steel piping. However, due to the limited number of st

eel piping releases (14)
, EPA was not able to make statistically valid claims as to the relative freq uency of the different causes. As with fiberglass piping, steel piping may have had metal connectors and any releases that occu rred in those connectors was attributed to a release from the steel piping.
For approved sy

nthetic piping (flexible plastic piping), physical or mechanical damage was the primary known cause o f releases . As with the other piping constructions, any releases that occurred at metal connectors associated with the approved synthetic piping run were attributed to the synthetic piping.
None of the three primary materials of construction appeared to be any more or less likely to have a release, relative to their use. In other words, none of the three materials performed significantly better or w orse t han the other materials. Similarly, no distinction was observed between the performance of pressurized and suction piping systems.

EPA compared releases to use for single

- walled and secondarily

- contained piping

. Secondarily

- contained piping performed a t least as well as single

- walled piping with the R&I use data and significantly better than single

- walled piping when compared to the FDEP use data

. EPA believe s that, because of the way data could be entered on the form for the R&I data, the piping secon

dary containment captured in the R&I data woul d be the absolute minimum use of secondarily

- contained piping and very likely und ercounts the use of secondarily

- contained piping. Therefore, FDEP data is a more accurate represent ation of the use of secondari ly

contained piping. Using the FDEP use data for single

- w alled piping versus secondarily

-Peer Review Draft

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### 30 contained piping, s ingle

- wall ed piping was significantly more likely to h ave a release. In fact, single

- walled piping was approximately twice as likely to have a rel ease, relative to its use. Th erefore , secondarily

- contain ed piping is more effective than single

- walled piping at reducing the frequency of piping releases to the environment.

EPA also analyzed the relationship between pipin g age and release frequency b y material of construction and by type of product delivery system using t hree approaches

– average age comparison, young versus old piping compari s on, and cumulative age distributions

. The comparison of average ages showed the average age to release was l ower than the average age of piping in the ground for all piping constructions. The difference was statistically significant for fiberglass, steel, and pressurized piping. The comparison of release to use for y oung and old piping showed releases from fib erglass piping less than 10 years old is significantly higher than use of fiberglass piping of the same age. Similarly, releases from steel piping were marginally higher than use of steel piping of the same age. In contrast, releases from approved synthe tic piping less than 10 years old were significantly lower than use for approved synthetic piping of the same age. The cumulative age distributions found a significant rela tionship between fiberglass piping

age and the likelihood of a release. Specifical ly, fiberglass piping

less than 15 years old is more likely to have a release than older fiberglass piping. This relationship also held true for all piping and for pressurized piping systems. However, since fiberglass piping represented the majority of a ll piping releases and use, the relationship for all piping is likely influenced by the large number of fiberglass piping systems.
Fuel Delivery
Fuel delivery was another frequent source of releases at 19 percent, occurring significantly more frequently than all other sources except dispensers and piping. Nearly all fuel delivery releases were caused by spills or overfills at the time of delivery . Loose components and deliveries to monitoring wells collectively contributed to seven percent of these rel eases.
The large percentage of spills and overfills raises questions about the reliability of current spill and overfill prevention systems. EPA was not able to record and analyze the relative performance of different spill bucket sizes, materials of c onstruction, and general condition in the field because that d ata was not available in FDEP files. EPA was also not able to determine how many releases were due to poor, improper, or damaged equipment; improper or insufficient operation and maintenance; o r delivery driver accident or negligence. EPA analyzed how ball float valve and automatic shutoff overfill protection technologies performed, but neither method stood out as more or less effective than the other.

Tank s
Tanks represented 12 percent of all re leases. Releases from tanks occur red significantly less frequently than releases from dispensers, piping, and fuel del iveries. Puncture and physical

or mechanical damage w

ere the most frequent known cause s of tank releases , followed by

corros ion. However, the known causes of tank releases varied significantly by material of construction.
Releases from steel tanks represent ed 30 percent of all tank releases. Corrosion (at 59 percent) was by far the most frequent known cause of releases f rom steel tanks. Unfortunately,Peer Review Draft

– March 2005 Do Not Cite Or Quot e 

### 31 there was insufficient data to analyze the differences between steel tanks protected by impressed current systems and galvanic systems.
Puncture and physical/mechanical damage were the most frequent known causes of releases from f

iberglass tanks, representing nearly all of the known causes. Fiberglass

- clad steel, polyethylene (jacketed steel), and concrete tanks did not have enough releases to compare the ir respective release causes.
Fiberglass tanks were both the most commonly used tanks and the tanks with the m ost releases. In comparing us e to releases, fiberglass tanks did not appear to release significantly more or less frequently than would be expected given their frequency of use. Steel tanks appeared m

ore likely to relea se using t he FDEP data
, but no more likely to have a release u sing the R&I data . Since EPA cannot identify one use data set as more appropriate in this case, th e Agency could not draw a clear

conclusion as to the relative likelihood of a release from a st eel tank. Fiberglass

- c lad steel tank s , however, performed quite well relative to their use. They represent approximately 20 percent of tanks in use, but account for only one of t he 63 tank releases (less than two percent ).

Secondar y containment signif icantly reduced the likelihood of a tank release when compared to tank use

. Using the R&I data, s ingle

- walled tanks were four times more likely to have a release than secondarily

- contained tanks. Using the FDEP data
, which EPA believes to be more represe ntative of seconda rily

- contained tank use , single

- walled tanks were ten times more likely to have a release. Thus, the data strongly support that the presence of tank secondary containment results in fewer releases from tanks to the environment.

EPA al so examined the relationship between tank age and likelihood of tank releases. There were no significant differences between use and releases , either for tanks in general or for any specific material of construction.
Pumps (Turbines)

Releases from tur bine pumps (including line leak detectors) represented 10 percent of releases in the data. Loose components were the most frequent known cause of releases for turbine pumps . Physical/mechanical damage was the second most frequent known cause, followed by

improper installation. Interestingly, improper installation was identified more frequently for pumps (as a percentage of total causes) than for either tanks or piping. This may be because pumps are typically not buried and are more readily inspected , ma king improper installation easier to determine

.
Release Volumes And Environmental Impacts

Release size was not available for 69 percent of releases ( release volume can be difficult to determine). Most

identified release s were fairly smal l . The me dian

release size was 40 gallons and no more than 5 5 gallons for any individual source

. The release volume data shows that large releases are more likely to come from tanks and piping, followed by dispensers. The largest recorded release (25,000 gallons) cam e from piping. These large releases lead to average release sizes of more than 1,000 gallons for piping, nearly 700 gallons for tanks, and more than 250 gallons for dispensers.Peer Review Draft

– March 2005 Do Not Cite Or Quot e 

### 32 While size can be a strong indicator of a release ’ s likelihood of having sig nificant environmental

or human health impacts, impacts to water (groundwater or surface water) is probably even more important. More than 85 percent of releases from tanks impacted water, compared with only 44 percent of dispenser releases. Releases fro m fuel deliveries, pumps, and piping reached water a pproximately 60 percent of the time. Florida has relatively high groundwater, so the water impact rates identified in this study may be higher than normal, but the relative likelihood of impacting water across sources should be similar for areas with lower groundwater

. Coupling release frequency with likelihood of impacting groundwater
, the data show piping and fuel delivery releases as having the most water impacts, followed by dispensers and tanks.

M ethod O f Detection

And Leak Detection Performance
Seeing or smelling a release wa s the most common method of release discovery
, occurring at 38 percent of releases . This number may even be undercounted because many releases discovered during an inspecti on were attributed to the other release discovery category. Releases found at c losure represent ed 15 percent of release discoveries.

Leak detection successfully detected 26 percent of all releases. Conversely, leak detection was specifically identified as failing to detect 23 percent of releases. For the remaining release s , the success or failure of leak detection could not be determined because either the data could not determine whether leak detection failed or the leak detection device did not have an opportunity to detect the release. While only a relatively small percentage of releases were discovered by leak detection, two important factor s to be considered are : most leak detection devices are not designed to detect relea ses from some of the more frequent sources of releases (such as fuel deliveries or dispensers ) and some release rates may be too small for the leak detection method to detect . It is als o important to point out that when a leak detection method was identified as failing, EPA could not determine the exact reason for the leak detection method failure

–whether it was faulty equipment ; improper installation, operation or maintenance ; or insufficient performance standards. Nonetheless, since leak detection identified only one

- quarter of releases raises questions about the effectivene s s of the current approach to leak detection

. EPA also compared specific leak detection methods. However, EPA could not determine that any one leak detection method was better than others in terms of both successfully detecting and not failing to detect a release.Peer Review Draft

– March 2005 Do Not Cite Or Quote 

### A

- 1 

## Appendix A

– Data Collection Forms

Appendix A

contains Florida’s two data collection fo rms used by the inspectors:

• Storage Tank System Release Investigation Information Form

• DEP Storage Tank System Incident Investigation Information FormPeer Review Draft

– March 2005 Do Not Ci te Or Quote 

### B

- 1 

## Appendix B

- Statistical Methods

EPA used a

number of statistical tests to evaluate the data related to releases from underground storage tanks in Florida (Table B

- 1). These tests include parametric and non

parametric procedu

res selected based on the nature of th e comparisons being made and the data being evaluated, as discussed in the following sections.

Table B

- 1 : Statistical Tests Used I n The Analysis O f Florida UST Release Data Data Evaluated Statistical Tests

Used Nature O f Comparisons

Releases by s ource z

- test proportions of releases from individual sources Causes of release by s ource z

- test proportions of all releases and releases from each source

z

- test proportions of releases by cause from steel and fiberglass tanks,

proport ions of total releases from tanks made of different materials Tanks materials and c auses Fisher's exact test proportions of releases by cause from steel tanks (small numbers)

z

- test proportions of releases by cause from steel, fiberglass, approved

synt hetic piping, proportions of total releases from piping made of different materials Piping m aterials and c auses

Fisher's exact test proportions of releases by cause from steel, approved synthetic liners (small numbers)

z

- test proportio ns of releases from tanks, piping, dispensers with and without

secondary containment (R&I data only), proportions of releases versus type of tank spill containment Secondary containment and overfill p rotection Odds ratio and

confidence limits frequencies of r elease with frequencies of us e (separate analyses with

use data from R&I, FDEP data sets) Release i dentification z

- test proportions of releases detected by different methods

Leak d etection z

- test proportions of successes and failures to detect releases versus use by individual type of leak dete ction technologies and for electronic and mechanical line leak detectors Contamination by

s ource, m edia z

- test proportions of releases from different sources affecting groundwater and/or surface water, proportions of releases from systems with pressure

or suction pumps affecting groundwater and/or surface water Release v olumes non

- parametric

bootstrap nonparametric confidence limits on release volumes from different

sources Tanks, piping use,

r elease z

- test pro portions of releases versus us e data (separa te comparisons using R&I data, FDEP data), for steel, fiberglass, fiberglass

- clad steel tanks, fiberglass, steel, and approved synthetic piping; binary comparisons of

use versus release proportions for tanks, piping secondary containment, releases from pre ssure, suction piping

t

- test average age of tanks, piping systems versus average age at release

discovery (age data from FDEP)

z

- test and Fisher’s exact test p roportions of releases versus use data (FDEP data) for tanks and piping

by material of construction and age Age at release discovery versus population a ge

Kolmorgorov

Smirnov test comparisons of profiles of release age versus tank/piping agePeer Review Draft

– March 2005 Do Not Ci te Or Quote 

### B

- 2 B

- 1

. The z

- Test For Difference O f Proportions

The z

- test for difference of proportions tests the hypothesis that two independent proportions, p 1 

### and p 2 

### , are equal. The statistic (z) is calculated as (Sheskin, p. 379):

(B

- 1)

(B

- 2)

Where: n 1 

### , n

2 

### = number of observations (e.g., tank systems or records) in the sample X 1 

### , X 2 

### = number of successes (e.g., number of releases) in the sample p 1 

### , p 2 

### = sample proportions = X 1 

### /n 1 

### , X 2 

### /n 2 

### P = weighted average of the sample proportions
Using a two

- sided test

, the hypothesis that the proportions are equal can be d iscarded

w ith 95 percent certai

nty (or p = 0.05) if z is greater than or equal to the critical value of 1.96. This value c orresponds to the point on the normal (Gaussian) distribution which excludes five percent of the total probability density (2.5 percent on each end). The difference in prop ortions is characterized as marginally significant ( 0.05 < p = 0.10) if z = 1.65 and z < 1.96 . T he z value indicating a 90 percent certainty is 1.65

. The two

- tailed test is used in non

- directional

situations where there is no reason to believe that eithe r p 1 

### or p 2 

### is greater or less than the other; it is more demanding (less likely to identify a difference in proportions as significant) than the one

- tailed test.
In some cases, the proportions being compared are both drawn from the same set of observation

s (all records). In that case, the z

- calculation is:

(B

- 3)

(B

- 4)

where: N is the total number of observations (records)

P is the average of the sample proportions
The underlying assumption of the z

- test is that the two proportions are independent of one another and are the result of sets of Bernoulli trials having a c onstant probability of

success. The z

- test is less reliable when the ns and Xs are relatively small. Where relatively few observati

ons are available (see Section B

- 2), th e Fisher’s Exact Test was used to evaluate differences in proportions

. 

# ( ) z p p P P N

P X X N = − −

= + 1 2 1

1 2 2 / ( ) /

( ) / 

# ( ) z p p P P n P P n

P X X n n = − − +

−

= + + 1 2 1 1 1 2

1 2 1 2 / ( ) / ( ) /

( ) / ( )Peer Review Draft

– March 2005 Do Not Ci te Or Quote 

### B

- 3 B

- 2. Fisher’s Exact Test

When the number of observations is small, the non

- parametric Fisher’s Exact Test is considered to be superior to the z

- test for judging the difference in f requencies of outcomes. Sheskin (p. 368) states that most sources recommend that parametric tests (Chi

- squared, z

test) not be used when the total number of observations (N, or n 1 

### + n 2 

### as defined in equations B

- 1 through B

- 4) is le ss than approximately 2 0. In the analysis of the data, EPA used the Fisher’s Exact Test to evaluate the significance of the difference in proportions of tank and piping releases associated with different causes (corrosion, puncture, etc.) where the numbers of observations was l

ess than 20

.
This non

- parametric (distribution

- independent) procedure tests the hypothesis that two sets of results (successes) in a number of observations (trials) are equal. Put another way, the procedure provides an estimate of the probability that t he observed difference in proportions could have arisen by chance, assuming both samples came from the same population. A low p

- value indicates that the proportions being compared are significantly different.
Calculation of the test statistic (p

- value) is computationally intensive, involving exact evaluations of the probability that the specific permutations of results (n 1 

### successes in X 1 

### trials, n

2 

### successes in X

2 

### trials) could have arisen by chance, relative to all other permutations. (See Sheskin, pp . 371

- 376). In this analysis, EPA calculated p

- values using the Fisher’s Exact Test algorithm in the STATISTICA ® 

### Version 5.0 package and the SAS ® 

### version 8 package. EPA characterized p

- values less than or equal to 0.05 as indications that two proportions were significantly different from o ne another. EPA characterized p

- values greater than

0.05 and less than or equal to 0.10 as marginally different from one another

.
B

- 3. Yates

- Corrected Chi

- Squared
Fisher’s Exact Test is theoretically valid for large s amples. However, because the test involves factorials, beyond a certain number of observations the calculation exceeds th e precision achievable with a personal computer . Thus for large n (greater than about 200 per cell), EPA employed either the z

- test d escribed above, or the Yates

- Corrected chi

- squared test for the difference of p roportions. In the analysis, EPA used the Yates

- Corrected chi

squared test to test the differences in raw rates ( e.g., numbers of releases divided by the numbers of tank system

s from the FDEP data) across different materials of construction.

The chi

- squared procedure is a standard method for evaluating the distribution of 2 by 2 tables, that is, for comparing two groups of observations that differ in frequency of a binary outc ome according to whether they receive a certain treatment. The Yates correction is a marginal adjustment to the values in the cells that improves the reliability of the test by accounting for contin uity of the outcome variables.Peer Review Draft

– March 2005 Do Not Ci te Or Quote 

### B

- 4 The Yates

- corrected chi

- s quared statistic (? 2 

### ) is calculated as:

(B

- 5)

Where i and j refer to the two groups being compared, and where O and E are analogous to the numbers of successes (e.g, releases, etc.) observed in one group versus the other. In a large sample fr om a homogeneous distribution, O and E would be equal, so the value of ? 2 

### would be zero. The calculated ? 2 

### value is compared to a table of critical values, and again, the difference in proportions is considered significant if the p

- value is less than or
e qual to 0.05 and marginally significant if the p

- value was greater than 0.05 and less than or equal to 0.10. EPA calculated the Yates

- Corrected Chi

- Squared values using STATISTICA

® 

### . Detailed summaries of the STATISTICA ® 

### ou tputs are provided in Appendix C

.
B

- 4. t

- test For Differences O f Means

The Student’s t

- test is the standard parametric (distribution

- dependent) test used to test for the difference of means of two or more samples. The t

- statistic is calculated as:



## t x x n n n n 

# s s ( ) 

## ( ) / / / )



# (

1 2 2 1 2 1 2
1 2

2
2 +

− 

## = − + (B

- 6)

where: x 1 

### , x 2 

### = Means of group 1, group 2

s 1 2 

### , s 2 2 

### = Sample standard deviations of groups 1, 2

n 1 

### , n 2 

### = N umber of observations in groups 1, 2
As shown in the equation, the t

- statistic has (n

1 

### + n 2 

### - 2 ) degrees of freedom. Differences in means are characterized as significant if th e t

- value with the appropriate degrees of freedom exceeds tabulated critical values for p = 0.05, and marginally significant if the t

- value exceeds the critical value fo r p = 0.10 but does not exceed the critical values for p = 0.05 . EPA used the STATISTICA ® 

### software package for all t

- tests.

B

- 5. Odds Ratio

EPA also estimate d the degree to which releases were associated with the use or absence of secondary containment for tanks, piping
, and dispensers. An ideal measure would be relative risk, the ratios of the numbers of releases per tank system with and without secondary containment. However, this measure was not directly accessible due to the nature of the data avai

lable (data related to releases and use came from different tank systems .) Therefore, E

PA calculated odds ratios for the presence/absence of secondary containment, as a surrogate measure of secondary containment performanc e. Sample data used in the calcu lation of odds ratios are shown in Table B

- 2

. 

# ( )

c 2 2 

### 0 5

= − − 

    

    

# ∑ ∑ O E

E ij ij

ij j i 

### .Peer Review Draft

– March 2005 Do Not Ci te Or Quote 

### B

- 5 Table B

- 2 : Sample Of Data Used In The Calculation O f Odds Ratios

Tank Secondary Containment Releases (R&I

Tank Releases) Use (R&I Data, Tank

System s W ith No Tank Releases) Present 4 144 Not Present 59 484

The odds ratio for the presence or absence of secondary containment versus releases can be calculated as the ratio of the products of diagonal elements of the table (Sheskin, p. 405). That is, odds ratio = (144 * 59) / (4 * 484) = 4.39. This result ca n be interpreted as the data indicate that the odds of finding secondary containment on a tank with no release is 4.39 times higher than the odds of finding secondary containment on a tan k that has had a release. An odds ratio of 1.0 would imply no differ ence in the frequency of secondary containment at tanks with releases. Where the values of releases are low compared to use , the numerical value of relative risk will be clo se to the numerical value for the odds ratio but, as noted above, it is not possib le to directly estimate relative risk (the relative probability of release given the presence or absence of secondary containment) from these data.
It can be shown that the natural log of the odds ratio is normally distributed. A normal z

- value for the o dds ratio ( OR ) can be calculated as:


## (OR) / SE z ln = (B

- 7)

Wher e the standard error (SE) of the odds ratio is given by:

SE = 1/n 1 + 1/n 2 + 1/n 3 + 1/n 4 (B

- 8)

Where n

1 

### through n

4 

### are the numbers of

observations in the four cells of the table. Using these formulas, SE = 0.53, and z = 4.55. Thus, the odds ratio in this example is significantly greater than 1.0 (since the p

- value associated with z = 4.55 is less than 0.001). Confidence limits on the odds ratio were also calculated using the standard error

.Peer Review Draft

– March 2005 Do Not Ci te Or Quote 

### B

- 6 B

- 6. Kolmorgorov

- Smirnov Test
The Kolmorgorov

- Smirnov (K

- S) test evaluates the probability that two cumulative distributions (such as cumulative numbers of releases over time) might have arise n by chance, rather than as a result of a real difference in the distributions. EPA used the K

- S test in the analysis to compare the time distributions of releases from tanks and piping with the distribution of ages of tank systems with the same character istics. A significant K

- S statistic indicates that the distributions are different over time, but does not indicate the nature of the difference. For example, i n the UST analysis for piping, all of the significant K

- S test statistics are found where the average age of piping releases from the R&I data are significantly less th

at the average age of tank systems in the FDEP data, that is, releases seem to occur at higher frequencies f rom piping at younger tank systems

.
The K

- S test is simple and robust, e ven when there are relatively few observations. The test statistic for the K

- S test is simply the largest vertical distance between two cumulative distributions. The calculation of the statistic can be illustrated u sing the data in Table B

- 3 that compare s the distribution of the age of all of the tanks in the FDEP data with the age distribution of releases from th e s e type s of tanks.

Table B

- 3: Age Distribution O f All Tanks A nd Releases

Age Distribution Cumulative Distributions Cumulative Proportions Age Use Releases Use Releases Use Releases Difference (M) 0

- <5.0 2,044 3 2,044 3 0.132 0.070 (0.062) 5

- <10 1,785 9 3,829 12 0.247 0.279 0.032 10

- <15 4,650 13 8,479 25 0.547 0.581 0.034 15

- <20 4,549 10 13,028 35 0.841 0.814 0.027 20

- <25 1,439 5 14,467 40 0.933 0.930 0.003 25

- <30 419 1 14,886 41 0.960 0.953 0.007 30

- <35 411 2 15,297 43 0.987 1.000 0.013 35

- <40 125 0 15,422 43 0.995 1.000 0.005 40

- <49 78 0 15,500 43 1.000 1.000 0.000 Total 15,500 43 15,500 43 1.000 1.000

--


### The left

- hand columns o f the table show the numbers of tanks in the data set in specified tank system

age groups ( u se ), and the numbers of releases tanks in the same age groups (r eleases). The numbers of tanks and releases are then re

- expressed in cumulative form and are conver ted to cumulative probability distributions (proportions), starting at zero (no tanks, no releases) and ending at 1.0 (all tanks, all releases).
The next step is to find the maximum difference between the proportions of tanks and proportion of releases at any point in the age distribution. It can be seen in the final column of the table that the maximum difference occurs at 0

- 5 years, which corresponds to about 13 percent on the use

distribution, but only about 7 percent on the release di stribution. Th is difference ( 0.062) is M, the value that is used in the probability calculation.Peer Review Draft

– March 2005 Do Not Ci te Or Quote 

### B

- 7 The p

- values associated with different values of M for given degrees of freedom are tabulated in statistics texts. However, when the number of observations is large enoug h, the p

- value can also be estimated using the Chi

- Squared Approximation, as follows: 1



### ( B

- 9)

Where: ? 2 

### = Chi

- squared value (two degrees of freedom) M 

### = Maximum vertical distance from K

- S test

n 1 

### , n 2 

### = number of observations (tan ks, releases)
The p

- value can thus be calculated using the CHIDIST function in Excel ® 

### , and two distributions are characterized as significantly different if the resulting p

- value is less than or equal to 0.05 and marginally different if the p

- value was g reater than

0.05 and less than or equal to 0.10. For the example data set, the chi

- squared value corresponding to M = 0.062 is 0.66, and the corresponding p

- value is 0.72. Thus, the two distributions are not significantly different.

B

- 7

. Bootstrap Confi dence Limits
Limited data were available concerning the amounts of product released from various sources. The release volume data were found to be irregularly distributed and often skewed (many low values, a few very high values). For the analysis, EPA used nonparametric bootstrap methods to derive robust (distribution

- independent) estimates of upper and lower confidence limits on the mean volumes released.
Briefly stated, the bootstrap method involved taking random samples from the raw release data, and evaluating the distribution of the resulting mean values. For example, if there were 16 releases from a source, we took 10,000 samples of 16 values (with replacement) from those data. The distributions of the mean values from these random samples can

be shown to have a Student’s t

- distribution with a standard error that can be estimated based on the sampling results. The Studentized upper and lower 95 percent confidence limits on the mean can then be easily calculated. (Davison and Hinkley, pp 191, f f) The bootstrap sampling was performed using the Visual Basic for Applications (VBA) capability of Excel 



### .

1 

### When (n 1 

### and n 2 

### ) are suitably large, the quantity o f the right

- hand side equation B

- 9 is known to have a chi

- squared distribution with two degrees of freedom (Sheskin, p 326). Above n 1 

### = n 2 

### = 25, the K

- S test critical values can be approximated by well

- behaved functions that are consistent with the Chi

- squared distribution to approximately one percent accuracy. (Sheskin, Table A

- 23). 

### c 2 2 1 2

1 2 

### 4 = +       M n n

n n *Peer Review Draft

– March 2005 Do Not Ci te Or Quote 

### B

- 8 References:

Da vidson, A.C., Hinkley, D.V., Bootstrap Methods and Their Application , Cambridge University Press, 1997.

Sheskin, D. J., Handboo k of Parametric and Nonparametric Statistical Procedures, Second Edition , Chapman and Hall, 2000.

Mason, Robert D

. Statistical Techniques in Business and Economics, Fourth Edition
, Richard D. Irwin, 1978Peer Review Draft

– March 2005 Do Not Cite Or Quote 

### C

- 1



## Appendix C

– Data Summary Tables And Statistic al Result s
Appendix C contains release and use data summary tables and the results of the statistical analysi s of that data. Appendix C contains the following:
Summary Of Releases By Source .............................................

...................... C

- 2 Causes Of Releases F r om Each Source ....................................

.................. C

- 3 Tank Materials And Release Causes .......................................

................... C

- 7 Piping Materials And Release Causes .......................................

....................... C

- 8 Summary Of Statistical Tests For Secondary Containment (Tanks, Piping, Dispensers) And Overfill Protection .....................

........................ ............... C

- 10 Methods Of Release Identification ..........................................

.................. C

- 14 Analysis Of Leak Detection Frequency Of Success, Failure, A nd Use .................. C

- 15 Contaminat ion Of Groundwater And Surface Water By Source Of Release ......

...... C

- 16 Release Volumes ...............................................................

.................. C

- 1 7 Analysis Of Tank And Piping Use Versus Releases .....................

.................. C

- 18 Tank And Piping Age Distributions

............. ............... .................. ............. C

- 21 t

- T est For Mean Ages .........................................................

.................. C

- 2 2 Fisher’s Exact And Z

- Tests For Piping Ages ................................................ C

- 23 K

- S Test For Tank Ages ......................................................

.................. C

- 2 5 K

- S Test For Piping Ages ...................................................

................... C

- 2 6Peer Review Draft - March 2005

Summary Of Releases By Source

Source Number Of Releases Percentage Of Releases Percentage Of

Records Piping 122 23.3% 23.8% Dispenser 130 24.8% 25.4% Fuel Delivery 101 19.3% 19.7% Tank 63 12.0% 12.3% Pump (Turbine) (Includes Line Leak Detector) 52 9.9% 10.2% Others* 56 10.7% 10.9% Total Releases 524 100.0% Number Of Records** 512

** There were 512 records in the data set; 12 records identified two sources each.

Calculation of z-statistics: z = (p1 - p2) / sqrt (P * (1-P) * (1 / N))

Source 1 Source 2 p1 p2 p1-p2 P 1-P 1/N z p-value Piping Versus Dispenser 0.23 0.25 -0.02 0.24 0.76 0.002 -0.82 0.413 Fuel Delivery 0.23 0.19 0.04 0.21 0.79 0.002 2.24 0.025 Tank 0.23 0.12 0.11 0.18 0.82 0.002 6.76 0.000 Pump (Turbine) (Includes Line Leak Detector) 0.23 0.10 0.13 0.17 0.83 0.002 8.22 0.000 Dispenser Versus Fuel Delivery 0.25 0.19 0.06 0.22 0.78 0.002 3.06 0.002 Tank 0.25 0.12 0.13 0.18 0.82 0.002 7.55 0.000 Pump (Turbine) (Includes Line Leak Detector) 0.25 0.10 0.15 0.17 0.83 0.002 8.99 0.000 Fuel Delivery Tank 0.19 0.12 0.07 0.16 0.84 0.002 4.57 0.000 Pump (Turbine) (Includes Line Leak Detector) 0.19 0.10 0.09 0.15 0.85 0.002 6.06 0.000

Tank Pump (Turbine) (Includes Line Leak Detector) 0.12 0.10 0.02 0.11 0.89 0.002 1.54 0.124

Shading: = significant (p = 0.05) = marginally significant (0.05 < p = 0.10) * Other releases include: 16 people putting product or used oil into monitoiring wells (intentional or accidental), 13 personal vehicles, 11 fill pipes, 6 people spilling during deposits of waste oil, 2 components leaking due to damage during removal, 2 vent lines, 2 stage II vapor recovery lines, 1 airplane, 1 day tank, 1 fitting, and 1 pump riser.

Appendix C C-2Peer Review Draft - March 2005

Causes Of Releases From Each Source

Source Number Of Releases* Percent Of

Releases Loose Component Vehicle Accident Spill Phys/Mech Damage Improper

Install Puncture Corrosion Overfill Other Number Of Known Causes 1 Number Of

Unknown Causes Unknowns As Percentage Of

Total Causes Piping 122 23.3% 25 6 0 27 6 19 8 0 6 97 26 21.3% Dispenser 130 24.8% 34 14 10 11 4 2 1 0 7 83 47 36.2% Fuel Delivery 101 19.3% 3 0 43 0 0 0 0 51 4 101 0 0.0% Tank 63 12.0% 5 0 0 14 1 17 10 1 6 54 9 14.3% Pump (Turbine) (Includes Line Leak Detector) 52 9.9% 22 0 0 14 5 1 0 0 4 46 6 11.5% Others** 56 10.7% 9 0 7 2 1 2 0 14 19 54 2 3.6% Total Releases 524 100.0% 98 20 60 68 17 41 19 66 46 435 90 17.2% Percentage Of All Releases With Known Causes 22.5% 4.6% 13.8% 15.6% 3.9% 9.4% 4.4% 15.2% 10.6%

Calculation of z-statistics: z = (p1 - p2) / sqrt (P * (1-P) * (1 / N))

p1 p2 p1-p2 P 1-P 1/N z p-value

Loose Component Versus Vehicle Accident 0.225 0.046 0.179 0.136 0.864 0.002 10.922 0.000 Spill 0.225 0.138 0.087 0.182 0.818 0.002 4.726 0.000 Phys/Mech 0.225 0.156 0.069 0.191 0.809 0.002 3.661 0.000 Improper Install 0.225 0.039 0.186 0.132 0.868 0.002 11.467 0.000 Puncture 0.225 0.094 0.131 0.160 0.840 0.002 7.459 0.000 Corrosion 0.225 0.044 0.182 0.134 0.866 0.002 11.102 0.000 Overfill 0.225 0.152 0.074 0.189 0.811 0.002 3.923 0.000 Vehicle Accident Versus Spill 0.046 0.138 -0.092 0.092 0.908 0.002 -6.637 0.000 Phys/Mech 0.046 0.156 -0.110 0.101 0.899 0.002 -7.633 0.000 Improper Install 0.046 0.039 0.007 0.043 0.957 0.002 0.713 0.476 Puncture 0.046 0.094 -0.048 0.070 0.930 0.002 -3.943 0.000 Shading: = significant (p = 0.05) Corrosion 0.046 0.044 0.002 0.045 0.955 0.002 0.232 0.817 = marginally significant (0.05 < p = 0.10) Overfill 0.046 0.152 -0.106 0.099 0.901 0.002 -7.390 0.000 Spill Versus Phys/Mech 0.138 0.156 -0.018 0.147 0.853 0.002 -1.083 0.279 Improper Install 0.138 0.039 0.099 0.089 0.911 0.002 7.259 0.000 Puncture 0.138 0.094 0.044 0.116 0.884 0.002 2.844 0.004 Corrosion 0.138 0.044 0.094 0.091 0.909 0.002 6.842 0.000 Overfill 0.138 0.152 -0.014 0.145 0.855 0.002 -0.817 0.414 Phys/Mech. Versus Improper Install 0.156 0.039 0.117 0.098 0.902 0.002 8.236 0.000 Puncture 0.156 0.094 0.062 0.125 0.875 0.002 3.911 0.000 Corrosion 0.156 0.044 0.113 0.100 0.900 0.002 7.831 0.000 Overfill 0.156 0.152 0.005 0.154 0.846 0.002 0.266 0.791 Improper Install Versus Puncture 0.039 0.094 -0.055 0.067 0.933 0.002 -4.613 0.000 Corrosion 0.039 0.044 -0.005 0.041 0.959 0.002 -0.481 0.630 Overfill 0.039 0.152 -0.113 0.095 0.905 0.002 -7.997 0.000 Puncture Versus Corrosion 0.094 0.044 0.051 0.069 0.931 0.002 4.163 0.000 Overfill 0.094 0.152 -0.057 0.123 0.877 0.002 -3.650 0.000 Corrosion Versus Overfill 0.044 0.152 -0.108 0.098 0.902 0.002 -7.590 0.000 * The total number of causes is greater than the number of releases because one release had two causes.

All Releases ** Other causes include: 20 deliveries to monitoring wells, 7 improper removals, 6 human errors, 5 vandalisms, 3 contractor errors, 2 customer driveoffs, 2 damage during delivery, and 1 leaking filter.

Appendix C C-3Peer Review Draft - March 2005

Piping Loose Component Versus Vehicle Accident 0.26 0.06 0.20 0.16 0.84 0.010 5.26 0.000 Spill 0.26 0.00 0.26 0.13 0.87 0.010 7.58 0.000 Phys/Mech 0.26 0.28 -0.02 0.27 0.73 0.010 -0.46 0.647 Improper Install 0.26 0.06 0.20 0.16 0.84 0.010 5.26 0.000 Puncture 0.26 0.20 0.06 0.23 0.77 0.010 1.45 0.146 Corrosion 0.26 0.08 0.18 0.17 0.83 0.010 4.59 0.000 Overfill 0.26 0.00 0.26 0.13 0.87 0.010 7.58 0.000 Vehicle Accident Versus Spill 0.06 0.00 0.06 0.03 0.97 0.010 3.52 0.000 Phys/Mech 0.06 0.28 -0.22 0.17 0.83 0.010 -5.67 0.000 Improper Install 0.06 0.06 0.00 0.06 0.94 0.010 0.00 1.000 Puncture 0.06 0.20 -0.13 0.13 0.87 0.010 -3.94 0.000 Corrosion 0.06 0.08 -0.02 0.07 0.93 0.010 -0.78 0.433 Overfill 0.06 0.00 0.06 0.03 0.97 0.010 3.52 0.000 Spill Versus Phys/Mech 0.00 0.28 -0.28 0.14 0.86 0.010 -7.92 0.000 Improper Install 0.00 0.06 -0.06 0.03 0.97 0.010 -3.52 0.000 Puncture 0.00 0.20 -0.20 0.10 0.90 0.010 -6.49 0.000 Corrosion 0.00 0.08 -0.08 0.04 0.96 0.010 -4.09 0.000 Overfill 0.00 0.00 0.00 0.00 1.00 0.010 N/A N/A Phys/Mech. Versus Improper Install 0.28 0.06 0.22 0.17 0.83 0.010 5.67 0.000 Puncture 0.28 0.20 0.08 0.24 0.76 0.010 1.91 0.056 Corrosion 0.28 0.08 0.20 0.18 0.82 0.010 5.02 0.000 Overfill 0.28 0.00 0.28 0.14 0.86 0.010 7.92 0.000 Shading: = significant (p = 0.05) Improper Install Versus Puncture 0.06 0.20 -0.13 0.13 0.87 0.010 -3.94 0.000 = marginally significant (0.05 < p = 0.10) Corrosion 0.06 0.08 -0.02 0.07 0.93 0.010 -0.78 0.433 Overfill 0.06 0.00 0.06 0.03 0.97 0.010 3.52 0.000 Puncture Versus Corrosion 0.20 0.08 0.11 0.14 0.86 0.010 3.23 0.001 Overfill 0.20 0.00 0.20 0.10 0.90 0.010 6.49 0.000 Corrosion Versus Overfill 0.08 0.00 0.08 0.04 0.96 0.010 4.09 0.000

Dispenser Loose Component Versus Vehicle Accident 0.41 0.17 0.24 0.29 0.71 0.012 4.84 0.000 Spill 0.41 0.12 0.29 0.27 0.73 0.012 5.97 0.000 Phys/Mech 0.41 0.13 0.28 0.27 0.73 0.012 5.68 0.000 Improper Install 0.41 0.05 0.36 0.23 0.77 0.012 7.84 0.000 Puncture 0.41 0.02 0.39 0.22 0.78 0.012 8.52 0.000 Corrosion 0.41 0.01 0.40 0.21 0.79 0.012 8.88 0.000 Overfill 0.41 0.00 0.41 0.20 0.80 0.012 9.25 0.000 Vehicle Accident Versus Spill 0.17 0.12 0.05 0.14 0.86 0.012 1.25 0.212 Phys/Mech 0.17 0.13 0.04 0.15 0.85 0.012 0.92 0.357 Improper Install 0.17 0.05 0.12 0.11 0.89 0.012 3.53 0.000 Puncture 0.17 0.02 0.14 0.10 0.90 0.012 4.46 0.000 Corrosion 0.17 0.01 0.16 0.09 0.91 0.012 4.98 0.000 Overfill 0.17 0.00 0.17 0.08 0.92 0.012 5.53 0.000 Spill Versus Phys/Mech 0.12 0.13 -0.01 0.13 0.87 0.012 -0.33 0.741 Improper Install 0.12 0.05 0.07 0.08 0.92 0.012 2.37 0.018 Puncture 0.12 0.02 0.10 0.07 0.93 0.012 3.39 0.001 Corrosion 0.12 0.01 0.11 0.07 0.93 0.012 3.97 0.000 Overfill 0.12 0.00 0.12 0.06 0.94 0.012 4.61 0.000 Phys/Mech. Versus Improper Install 0.13 0.05 0.08 0.09 0.91 0.012 2.68 0.007 Puncture 0.13 0.02 0.11 0.08 0.92 0.012 3.68 0.000 Corrosion 0.13 0.01 0.12 0.07 0.93 0.012 4.24 0.000 Overfill 0.13 0.00 0.13 0.07 0.93 0.012 4.85 0.000 Improper Install Versus Puncture 0.05 0.02 0.02 0.04 0.96 0.012 1.18 0.240 Corrosion 0.05 0.01 0.04 0.03 0.97 0.012 1.93 0.054 Overfill 0.05 0.00 0.05 0.02 0.98 0.012 2.86 0.004 Puncture Versus Corrosion 0.02 0.01 0.01 0.02 0.98 0.012 0.82 0.410 Overfill 0.02 0.00 0.02 0.01 0.99 0.012 2.01 0.044 Corrosion Versus Overfill 0.01 0.00 0.01 0.01 0.99 0.012 1.42 0.156

Appendix C C-4Peer Review Draft - March 2005

Fuel Delivery Loose Component Versus Vehicle Accident 0.03 0.00 0.03 0.01 0.99 0.010 2.47 0.014 Spill 0.03 0.43 -0.40 0.23 0.77 0.010 -9.49 0.000 Phys/Mech 0.03 0.00 0.03 0.01 0.99 0.010 2.47 0.014 Improper Install 0.03 0.00 0.03 0.01 0.99 0.010 2.47 0.014 Puncture 0.03 0.00 0.03 0.01 0.99 0.010 2.47 0.014 Corrosion 0.03 0.00 0.03 0.01 0.99 0.010 2.47 0.014 Overfill 0.03 0.50 -0.48 0.27 0.73 0.010 -10.79 0.000 Vehicle Accident Versus Spill 0.00 0.43 -0.43 0.21 0.79 0.010 -10.45 0.000 Phys/Mech 0.00 0.00 0.00 0.00 1.00 0.010 N/A N/A Improper Install 0.00 0.00 0.00 0.00 1.00 0.010 N/A N/A Puncture 0.00 0.00 0.00 0.00 1.00 0.010 N/A N/A Corrosion 0.00 0.00 0.00 0.00 1.00 0.010 N/A N/A Overfill 0.00 0.50 -0.50 0.25 0.75 0.010 -11.68 0.000 Spill Versus Phys/Mech 0.43 0.00 0.43 0.21 0.79 0.010 10.45 0.000 Improper Install 0.43 0.00 0.43 0.21 0.79 0.010 10.45 0.000 Puncture 0.43 0.00 0.43 0.21 0.79 0.010 10.45 0.000 Corrosion 0.43 0.00 0.43 0.21 0.79 0.010 10.45 0.000 Overfill 0.43 0.50 -0.08 0.47 0.53 0.010 -1.60 0.111 Phys/Mech. Versus Improper Install 0.00 0.00 0.00 0.00 1.00 0.010 N/A N/A Puncture 0.00 0.00 0.00 0.00 1.00 0.010 N/A N/A Corrosion 0.00 0.00 0.00 0.00 1.00 0.010 N/A N/A Overfill 0.00 0.50 -0.50 0.25 0.75 0.010 -11.68 0.000 Improper Install Versus Puncture 0.00 0.00 0.00 0.00 1.00 0.010 N/A N/A Corrosion 0.00 0.00 0.00 0.00 1.00 0.010 N/A N/A Overfill 0.00 0.50 -0.50 0.25 0.75 0.010 -11.68 0.000 Puncture Versus Corrosion 0.00 0.00 0.00 0.00 1.00 0.010 N/A N/A Overfill 0.00 0.50 -0.50 0.25 0.75 0.010 -11.68 0.000 Corrosion Versus Overfill 0.00 0.50 -0.50 0.25 0.75 0.010 -11.68 0.000

Tank Loose Component Versus Vehicle Accident 0.09 0.00 0.09 0.05 0.95 0.019 3.24 0.001 Spill 0.09 0.00 0.09 0.05 0.95 0.019 3.24 0.001 Phys/Mech 0.09 0.26 -0.17 0.18 0.82 0.019 -3.22 0.001 Shading: = significant (p = 0.05) Improper Install 0.09 0.02 0.07 0.06 0.94 0.019 2.38 0.017 = marginally significant (0.05 < p = 0.10) Puncture 0.09 0.31 -0.22 0.20 0.80 0.019 -4.05 0.000 Corrosion 0.09 0.19 -0.09 0.14 0.86 0.019 -1.97 0.049 Overfill 0.09 0.02 0.07 0.06 0.94 0.019 2.38 0.017 Vehicle Accident Versus Spill 0.00 0.00 0.00 0.00 1.00 0.019 N/A N/A Phys/Mech 0.00 0.26 -0.26 0.13 0.87 0.019 -5.67 0.000 Improper Install 0.00 0.02 -0.02 0.01 0.99 0.019 -1.42 0.155 Puncture 0.00 0.31 -0.31 0.16 0.84 0.019 -6.35 0.000 Corrosion 0.00 0.19 -0.19 0.09 0.91 0.019 -4.69 0.000 Overfill 0.00 0.02 -0.02 0.01 0.99 0.019 -1.42 0.155 Spill Versus Phys/Mech 0.00 0.26 -0.26 0.13 0.87 0.019 -5.67 0.000 Improper Install 0.00 0.02 -0.02 0.01 0.99 0.019 -1.42 0.155 Puncture 0.00 0.31 -0.31 0.16 0.84 0.019 -6.35 0.000 Corrosion 0.00 0.19 -0.19 0.09 0.91 0.019 -4.69 0.000 Overfill 0.00 0.02 -0.02 0.01 0.99 0.019 -1.42 0.155 Phys/Mech. Versus Improper Install 0.26 0.02 0.24 0.14 0.86 0.019 5.12 0.000 Puncture 0.26 0.31 -0.06 0.29 0.71 0.019 -0.90 0.367 Corrosion 0.26 0.19 0.07 0.22 0.78 0.019 1.31 0.190 Overfill 0.26 0.02 0.24 0.14 0.86 0.019 5.12 0.000 Improper Install Versus Puncture 0.02 0.31 -0.30 0.17 0.83 0.019 -5.84 0.000 Corrosion 0.02 0.19 -0.17 0.10 0.90 0.019 -4.05 0.000 Overfill 0.02 0.02 0.00 0.02 0.98 0.019 0.00 1.000 Puncture Versus Corrosion 0.31 0.19 0.13 0.25 0.75 0.019 2.20 0.028 Overfill 0.31 0.02 0.30 0.17 0.83 0.019 5.84 0.000 Corrosion Versus Overfill 0.19 0.02 0.17 0.10 0.90 0.019 4.05 0.000

Appendix C C-5Peer Review Draft - March 2005

Pump (Turbine) (Includes Line Leak Detector) Loose Component Versus Vehicle Accident 0.48 0.00 0.48 0.24 0.76 0.022 7.60 0.000 Spill 0.48 0.00 0.48 0.24 0.76 0.022 7.60 0.000 Phys/Mech 0.48 0.30 0.17 0.39 0.61 0.022 2.42 0.016 Improper Install 0.48 0.11 0.37 0.29 0.71 0.022 5.50 0.000 Puncture 0.48 0.02 0.46 0.25 0.75 0.022 7.15 0.000 Corrosion 0.48 0.00 0.48 0.24 0.76 0.022 7.60 0.000 Overfill 0.48 0.00 0.48 0.24 0.76 0.022 7.60 0.000 Vehicle Accident Versus Spill 0.00 0.00 0.00 0.00 1.00 0.022 N/A N/A Phys/Mech 0.00 0.30 -0.30 0.15 0.85 0.022 -5.75 0.000 Improper Install 0.00 0.11 -0.11 0.05 0.95 0.022 -3.25 0.001 Puncture 0.00 0.02 -0.02 0.01 0.99 0.022 N/A N/A Corrosion 0.00 0.00 0.00 0.00 1.00 0.022 N/A N/A Overfill 0.00 0.00 0.00 0.00 1.00 0.022 N/A N/A Spill Versus Phys/Mech 0.00 0.30 -0.30 0.15 0.85 0.022 -5.75 0.000 Improper Install 0.00 0.11 -0.11 0.05 0.95 0.022 -3.25 0.001 Puncture 0.00 0.02 -0.02 0.01 0.99 0.022 N/A N/A Corrosion 0.00 0.00 0.00 0.00 1.00 0.022 N/A N/A Overfill 0.00 0.00 0.00 0.00 1.00 0.022 N/A N/A Phys/Mech. Versus Improper Install 0.30 0.11 0.20 0.21 0.79 0.022 3.28 0.001 Puncture 0.30 0.02 0.28 0.16 0.84 0.022 5.19 0.000 Corrosion 0.30 0.00 0.30 0.15 0.85 0.022 5.75 0.000 Overfill 0.30 0.00 0.30 0.15 0.85 0.022 5.75 0.000 Improper Install Versus Puncture 0.11 0.02 0.09 0.07 0.93 0.022 2.39 0.017 Corrosion 0.11 0.00 0.11 0.05 0.95 0.022 3.25 0.001 Overfill 0.11 0.00 0.11 0.05 0.95 0.022 3.25 0.001 Puncture Versus Corrosion 0.02 0.00 0.02 0.01 0.99 0.022 N/A N/A Overfill 0.02 0.00 0.02 0.01 0.99 0.022 N/A N/A Corrosion Versus Overfill 0.00 0.00 0.00 0.00 1.00 0.022 N/A N/A

Others Loose Component Versus Vehicle Accident 0.17 0.00 0.17 0.08 0.92 0.019 4.43 0.000 Spill 0.17 0.13 0.04 0.15 0.85 0.019 0.77 0.444 Phys/Mech 0.17 0.04 0.13 0.10 0.90 0.019 3.15 0.002 Improper Install 0.17 0.02 0.15 0.09 0.91 0.019 3.76 0.000 Puncture 0.17 0.04 0.13 0.10 0.90 0.019 3.15 0.002 Corrosion 0.17 0.00 0.17 0.08 0.92 0.019 4.43 0.000 Shading: = significant (p = 0.05) Overfill 0.17 0.26 -0.09 0.21 0.79 0.019 -1.66 0.097 = marginally significant (0.05 < p = 0.10) Vehicle Accident Versus Spill 0.00 0.13 -0.13 0.06 0.94 0.019 -3.87 0.000 Phys/Mech 0.00 0.04 -0.04 0.02 0.98 0.019 -2.02 0.044 Improper Install 0.00 0.02 -0.02 0.01 0.99 0.019 -1.42 0.155 Puncture 0.00 0.04 -0.04 0.02 0.98 0.019 -2.02 0.044 Corrosion 0.00 0.00 0.00 0.00 1.00 0.019 N/A N/A Overfill 0.00 0.26 -0.26 0.13 0.87 0.019 -5.67 0.000 Spill Versus Phys/Mech 0.13 0.04 0.09 0.08 0.92 0.019 2.46 0.014 Improper Install 0.13 0.02 0.11 0.07 0.93 0.019 3.12 0.002 Puncture 0.13 0.04 0.09 0.08 0.92 0.019 2.46 0.014 Corrosion 0.13 0.00 0.13 0.06 0.94 0.019 3.87 0.000 Overfill 0.13 0.26 -0.13 0.19 0.81 0.019 -2.41 0.016 Phys/Mech. Versus Improper Install 0.04 0.02 0.02 0.03 0.97 0.019 0.83 0.408 Puncture 0.04 0.04 0.00 0.04 0.96 0.019 0.00 1.000 Corrosion 0.04 0.00 0.04 0.02 0.98 0.019 2.02 0.044 Overfill 0.04 0.26 -0.22 0.15 0.85 0.019 -4.60 0.000 Improper Install Versus Puncture 0.02 0.04 -0.02 0.03 0.97 0.019 -0.83 0.408 Corrosion 0.02 0.00 0.02 0.01 0.99 0.019 1.42 0.155 Overfill 0.02 0.26 -0.24 0.14 0.86 0.019 -5.12 0.000 Puncture Versus Corrosion 0.04 0.00 0.04 0.02 0.98 0.019 2.02 0.044 Overfill 0.04 0.26 -0.22 0.15 0.85 0.019 -4.60 0.000 Corrosion Versus Overfill 0.00 0.26 -0.26 0.13 0.87 0.019 -5.67 0.000

Appendix C C-6Peer Review Draft - March 2005

Tank Materials And Release Causes

Material Total Releases Total Known Causes Corrosion Phys/Mech Damage Puncture Loose Component Overfill Improper Install Other Unknown Steel 19 17 10 3 1 2 0 1 0 2 Fiberglass 41 35 0 11 16 1 1 0 6 6 Clad Steel (Composite) 1 1 0 0 0 1 0 0 0 0 Concrete 1 0 0 0 0 0 0 0 0 1 Polyethylene 1 1 0 0 0 1 0 0 0 0 Total 63 54 10 14 17 5 1 1 6 9

Calculation of z-statistics: z = (p1 - p2) / sqrt (P * (1-P) * (1 / N))

Cause Comparison By Material Of Construction p1 p2 p1-p2 P 1-P 1/N z p-value

Corrosion Versus Phys/Mech Damage 0.59 0.18 0.41 0.38 0.62 0.059 3.49 0.000 Puncture 0.59 0.06 0.53 0.32 0.68 0.059 4.67 0.000 Loose Component 0.59 0.12 0.47 0.35 0.65 0.059 4.06 0.000 Improper Install 0.59 0.06 0.53 0.32 0.68 0.059 4.67 0.000 Phys/Mech Damage Versus Puncture 0.18 0.06 0.12 0.12 0.88 0.059 1.51 0.132 Loose Component 0.18 0.12 0.06 0.15 0.85 0.059 0.68 0.493 Improper Install 0.18 0.06 0.12 0.12 0.88 0.059 1.51 0.132 Puncture Versus Loose Component 0.06 0.12 -0.06 0.09 0.91 0.059 0.86 0.392 Improper Install 0.06 0.06 0.00 0.06 0.94 0.059 0.00 1.000 Loose Component Versus Improper Install 0.12 0.06 0.06 0.09 0.91 0.059 0.86 0.392

Phys/Mech Damage Versus Puncture 0.31 0.46 -0.14 0.39 0.61 0.029 1.74 0.083 Loose Component 0.31 0.03 0.29 0.17 0.83 0.029 4.48 0.000 Overfill 0.31 0.03 0.29 0.17 0.83 0.029 4.48 0.000 Puncture Versus Loose Component 0.46 0.03 0.43 0.24 0.76 0.029 5.91 0.000 Overfill 0.46 0.03 0.43 0.24 0.76 0.029 5.91 0.000 Loose Component Versus Overfill 0.03 0.03 0.00 0.03 0.97 0.029 0.00 1.000

Fisher's Exact Test - Selected Steel Comparisons Comparison Yes No Comparison Yes No Corrosion 10 7 Corrosion 10 7 Phys/Mech Damage 3 14 Puncture 1 16 0.032 0.002

Comparison Yes No Comparison Yes No Corrosion 10 7 Corrosion 10 7 Loose Component 2 15 Improper Install 1 16 0.010 0.002

Material Of Construction p1 p2 p1-p2 P 1-P 1/N z p-value Steel Versus Fiberglass 0.30 0.65 -0.35 0.48 0.52 0.019 5.14 0.000 Composite 0.30 0.02 0.29 0.16 0.84 0.019 5.75 0.000 Concrete 0.30 0.02 0.29 0.16 0.84 0.019 5.75 0.000 Polyethylene 0.30 0.02 0.29 0.16 0.84 0.019 5.75 0.000 Fiberglass Versus Composite 0.65 0.02 0.63 0.33 0.67 0.019 9.90 0.000 Concrete 0.65 0.02 0.63 0.33 0.67 0.019 9.90 0.000 Polyethylene 0.65 0.02 0.63 0.33 0.67 0.019 9.90 0.000 Composite Versus Concrete 0.02 0.02 0.00 0.02 0.98 0.019 0.00 1.000 Polyethylene 0.02 0.02 0.00 0.02 0.98 0.019 0.00 1.000 Concrete Versus Polyethylene 0.02 0.02 0.00 0.02 0.98 0.019 0.00 1.000

Shading: = significant (p = 0.05) = marginally significant (0.05 < p = 0.10) Material Of Construction Comparisons Steel

Fiberglass

Fisher's Exact Test p-value:

Fisher's Exact Test p-value:

Appendix C C-7Peer Review Draft - March 2005

Piping Materials And Release Causes

Material Total Releases Total Known Causes Corrosion Phys/Mech Damage Puncture Loose Component Vehicle Accident Improper Install Other Unknown Steel 17 15 5 3 0 3 1 1 2 2 Fiberglass 92 71 3 18 18 20 5 4 3 22 Approved Synthetic Material 11 9 0 6 1 2 0 0 0 2 Total Of Known Materials And Causes 120 95 8 27 19 25 6 5 5 26 Unknown 2 2 0 0 0 0 0 1 1 0

Calculation of z-statistics: z = (p1 - p2) / sqrt (P * (1-P) * (1 / N))

Cause Comparison By Material p1 p2 p1-p2 P 1-P 1/N z p-value

Corrosion Versus Phys/Mech Damage 0.33 0.20 0.13 0.27 0.73 0.067 1.17 0.243 Puncture 0.33 0.00 0.33 0.17 0.83 0.067 3.46 0.001 Loose Component 0.33 0.20 0.13 0.27 0.73 0.067 1.17 0.243 Vehicle Accident 0.33 0.07 0.27 0.20 0.80 0.067 2.58 0.010 Improper Install 0.33 0.07 0.27 0.20 0.80 0.067 2.58 0.010 Phys/Mech Damage Versus Puncture 0.20 0.00 0.20 0.10 0.90 0.067 2.58 0.010 Loose Component 0.20 0.20 0.00 0.20 0.80 0.067 0.00 1.000 Vehicle Accident 0.20 0.07 0.13 0.13 0.87 0.067 1.52 0.129 Improper Install 0.20 0.07 0.13 0.13 0.87 0.067 1.52 0.129 Puncture Versus Loose Component 0.00 0.20 -0.20 0.10 0.90 0.067 2.58 0.010 Vehicle Accident 0.00 0.07 -0.07 0.03 0.97 0.067 1.44 0.150 Improper Install 0.00 0.07 -0.07 0.03 0.97 0.067 1.44 0.150 Loose Component Versus Vehicle Accident 0.20 0.07 0.13 0.13 0.87 0.067 1.52 0.129 Improper Install 0.20 0.07 0.13 0.13 0.87 0.067 1.52 0.129 Vehicle Accident Versus Improper Install 0.07 0.07 0.00 0.07 0.93 0.067 0.00 1.000

Corrosion Versus Phys/Mech Damage 0.04 0.25 -0.21 0.15 0.85 0.014 5.01 0.000 Puncture 0.04 0.25 -0.21 0.15 0.85 0.014 5.01 0.000 Loose Component 0.04 0.28 -0.24 0.16 0.84 0.014 5.48 0.000 Vehicle Accident 0.04 0.07 -0.03 0.06 0.94 0.014 1.03 0.303 Improper Install 0.04 0.06 -0.01 0.05 0.95 0.014 0.55 0.584 Phys/Mech Damage Versus Puncture 0.25 0.25 0.00 0.25 0.75 0.014 0.00 1.000 Loose Component 0.25 0.28 -0.03 0.27 0.73 0.014 0.54 0.592 Vehicle Accident 0.25 0.07 0.18 0.16 0.84 0.014 4.19 0.000 Improper Install 0.25 0.06 0.20 0.15 0.85 0.014 4.59 0.000 Puncture Versus Loose Component 0.25 0.28 -0.03 0.27 0.73 0.014 0.54 0.592 Vehicle Accident 0.25 0.07 0.18 0.16 0.84 0.014 4.19 0.000 Improper Install 0.25 0.06 0.20 0.15 0.85 0.014 4.59 0.000 Loose Component Versus Vehicle Accident 0.28 0.07 0.21 0.18 0.82 0.067 2.15 0.032 Improper Install 0.28 0.06 0.23 0.17 0.83 0.067 2.33 0.020 Vehicle Accident Versus Improper Install 0.07 0.06 0.01 0.06 0.94 0.014 0.49 0.626

Corrosion Versus Phys/Mech Damage 0.00 0.67 -0.67 0.33 0.67 0.111 4.24 0.000 Puncture 0.00 0.11 -0.11 0.06 0.94 0.111 1.46 0.146 Loose Component 0.00 0.22 -0.22 0.11 0.89 0.111 2.12 0.034 Vehicle Accident 0.00 0.00 0.00 0.00 1.00 0.111 N/A N/A Improper Install 0.00 0.00 0.00 0.00 1.00 0.111 N/A N/A Phys/Mech Damage Versus Puncture 0.67 0.11 0.56 0.39 0.61 0.111 3.42 0.001 Loose Component 0.67 0.22 0.44 0.44 0.56 0.111 2.68 0.007 Vehicle Accident 0.67 0.00 0.67 0.33 0.67 0.111 4.24 0.000 Improper Install 0.67 0.00 0.67 0.33 0.67 0.111 4.24 0.000 Puncture Versus Loose Component 0.11 0.22 -0.11 0.17 0.83 0.111 0.89 0.371 Vehicle Accident 0.11 0.00 0.11 0.06 0.94 0.111 1.46 0.146 Improper Install 0.11 0.00 0.11 0.06 0.94 0.111 1.46 0.146 Loose Component Versus Vehicle Accident 0.22 0.00 0.22 0.11 0.89 0.067 2.74 0.006 Improper Install 0.22 0.00 0.22 0.11 0.89 0.067 2.74 0.006 Vehicle Accident Improper Install 0.00 0.00 0.00 0.00 1.00 0.111 N/A N/A

Shading: = significant (p = 0.05)

= marginally significant (0.05 < p = 0.10) Steel

Fiberglass

Approved Synthetic Material

Appendix C C-8Peer Review Draft - March 2005

Fisher's Exact Test - Selected Steel Comparisons Comparison Yes No Comparison Yes No Comparison Yes No Corrosion 5 10 Phys/Mech 3 12 Puncture 0 15 Puncture 0 15 Puncture 0 15 Loose Comp 3 12 0.042 0.224 0.224

Comparison Yes No Comparison Yes No Corrosion 5 10 Corrosion 5 10 Vehicle Accident 1 14 Improper Install 1 14 0.169 0.169

Fisher's Exact Test - Selected Approved Synthetic Material Comparisons Comparison Yes No Comparison Yes No Comparison Yes No Corrosion 0 9 Corrosion 0 9 Phys/Mech 6 3 Phys/Mech 6 3 Loose Component 2 7 Vehicle Accident 0 9 0.009 0.471 0.009

Comparison Yes No Comparison Yes No Comparison Yes No Phys/Mech 6 3 Phys/Mech 6 3 Phys/Mech 6 3 Puncture 1 8 Loose Comp 2 7 Improper Install 0 9 0.050 0.153 0.009

Comparison Yes No Comparison Yes No Loose Component 2 7 Loose Component 2 7 Vehicle Accident 0 9 Improper Install 0 9 0.471 0.471

Material Of Construction Comparison

Material Of Construction p1 p2 p1-p2 P 1-P 1/N z p-value Steel Versus Fiberglass 0.14 0.77 -0.63 0.45 0.55 0.008 13.75 0.000
Approved Synthetic Material 0.14 0.09 0.05 0.12 0.88 0.008 1.71 0.088 Fiberglass Versus Approved Synthetic Material 0.77 0.09 0.68 0.43 0.57 0.008 14.94 0.000

Shading: = significant (p = 0.05)

= marginally significant (0.05 < p = 0.10) Fisher's Exact Test p-value: Fisher's Exact Test p-value:

Fisher's Exact Test p-value: Fisher's Exact Test p-value:

Fisher's Exact Test p-value:

Appendix C C-9Peer Review Draft - March 2005



### Summary Of Statistical Tests For Secondary Containment (Tanks, Piping, Dispensers) And Overfill Protection

Tanks

Number Of Releases Percent

Releases Records With

Non-Tank Releases Percent Use Number Of UST Systems Percent Use With Secondary Containment 4 6.3% 144 22.9% 6317 41.6% Without Secondary Containment 59 93.7% 484 77.1% 8878 58.4% Total 63 100% 628 100% 15195 100%

Calculation of z-statistics: z = (p1 - p2) / sqrt (P * (1-P) * (1 / N)) where 1/N = 1/n1+1/n2 if proportions are independent

Tanks With Secondary Containment -- Z-statistic

Significance Calculation p1 (Releases) p2

(Use) p1-p2 P 1-P 1/n1 + 1/n2 z p-value Releases Versus R&I Data 0.063 0.229 -0.166 0.214 0.786 0.0175 -3.06 0.002 Releases Versus FDEP Data 0.063 0.416 -0.352 0.414 0.586 0.0159 -5.66 0.000

Odds Ratio Standard Deviation Confidence Limits p-value R&I Data 4.39 0.53 3.4 - 12.3 0.0024 FDEP Data 10.50 0.52 9.5 - 28.9 0.0000

Shading: = significant (p = 0.05) = marginally significant (0.05 < p = 0.10) Tank Secondary Containment Releases And Incident Data (R&I) FDEP Data

Odds Ratio Information For Tanks With Secondary Containment (Releases Versus Use)

Appendix C C-10Peer Review Draft - March 2005



### Piping

Number Of Releases Percent

Releases Records With

Non-Piping Releases Percent Use Number Of UST Systems Percent Use Present 53 43.4% 214 42.8% 9101 60.2% Not Present 69 56.6% 286 57.2% 6026 39.8% Total 122 100% 500 100% 15127 100%

Calculation of z-statistics: z = (p1 - p2) / sqrt (P * (1-P) * (1 / N)) where 1/N = 1/n1+1/n2 if proportions are independent

Piping With Secondary Containment -- Z-statistic

Significance Calculation p1 (Releases) p2

(Use) p1-p2 P 1-P 1/n1 + 1/n2 z p-value Releases Versus R&I Data 0.434 0.428 0.006 0.429 0.571 0.0102 0.13 0.898 Releases Versus FDEP Data 0.434 0.602 -0.167 0.600 0.400 0.0083 -3.76 0.000

Odds Ratio Standard Deviation Confidence Limits p-value FDEP Data 1.97 0.18 1.6 - 2.8 0.0001
Shading: = significant (p = 0.05) = marginally significant (0.05 < p = 0.10) Odds Ratio Information For Piping With Secondary Containment (Releases Versus Use) Piping Secondary Containment Releases And Incident Data (R&I) FDEP Data

Appendix C C-11Peer Review Draft - March 2005



### Dispensers

Number Of Releases Percent

Releases Records With

Non-Piping Releases Percent Use Number Of UST Systems Percent Use Present 43 33% 202 36% 12362 81% Not Present 87 67% 365 64% 2833 19% Total 130 100% 567 100% 15195 100%

Calculation of z-statistics: z = (p1 - p2) / sqrt (P * (1-P) * (1 / N)) where 1/N = 1/n1+1/n2 if proportions are independent
Dispensers With Secondary Containment -- Z-statistic

Significance Calculation p1 (Releases) p2

(Use) p1-p2 P 1-P 1/n1+1/n2 z p-value Releases Versus R&I Data 0.331 0.356 -0.025 0.352 0.648 0.0095 -0.55 0.583 Releases Versus FDEP Data 0.331 0.814 -0.483 0.809 0.191 0.0078 -13.96 0.000

Odds Ratio Standard Deviation Confidence Limits p-value FDEP Data 8.83 0.19 8.5 - 12.8 0.0000

Shading: = significant (p = 0.05) = marginally significant (0.05 < p = 0.10) Odds Ratio Information For Dispensers With Secondary Containment (Releases Versus Use) FDEP Data

Dispenser Secondary Containment Releases And Incident Data (R&I)

Appendix C C-12Peer Review Draft - March 2005



### Overfill Protection

Number Of Releases Percent

Releases Records With

Non-Piping Releases Percent Use Number Of UST Systems Percent Use Ball Check Valve 36 77% 473 82% 11122 67% Flow-Shutoff 11 23% 105 18% 5593 33% Total 47 100% 578 100% 16715 100%

Calculation of z-statistics: z = (p1 - p2) / sqrt (P * (1-P) * (1 / N)) where 1/N = 1/n1+1/n2 if proportions are independent

Overfill Protection

Significance Calculation p1 (Releases) p2

(Use) p1-p2 P 1-P 1/n1+1/n2 z p-value Ball Check Valve Versus R&I Data 0.766 0.818 -0.052 0.814 0.186 0.0230 -0.89 0.374 Ball Check Valve Versus FDEP Data 0.766 0.665 0.101 0.666 0.334 0.0213 1.46 0.144 Flow Shut Off Versus R&I Data 0.234 0.182 0.052 0.186 0.814 0.0230 0.89 0.374 Flow Shut Off Versus FDEP Data 0.234 0.335 -0.101 0.334 0.666 0.0213 -1.46 0.144

Shading: = significant (p = 0.05) = marginally significant (0.05 < p = 0.10) Overfill Protection Method Releases And Incident Data (R&I) FDEP Data

Appendix C C-13Peer Review Draft - March 2005



### Methods Of Release Identification

Method Of Identification Number Of Releases Percent Leak Detection 131 25.9% Visual/Olfactory 193 38.2% TTT Or LTT (Not Leak Detection) 24 4.8% Closure * 76 15.0% Other ** 81 16.0% Total Known Methods Of ID 505 Unknown 7 * Includes 9 releases identified through close in place and 67 identified through removal. ** Includes 10 releases identified through water in tank and 71 identified by other means.

Calculation of z-statistics: z = (p1 - p2) / sqrt (P * (1-P) * (1 / N))

Method (1) Method (2) p1 p2 p1-p2 P 1-P 1/N z p-value

Leak Detection Versus Visual/Olfactory 0.259 0.382 -0.123 0.153 0.847 0.002 -7.65 0.000 TTT Or LTT (Not Leak Detection) 0.259 0.048 0.212 0.205 0.795 0.002 11.80 0.000 Closure 0.259 0.150 0.109 0.215 0.785 0.002 5.96 0.000 Visual/Olfactory Versus TTT Or LTT (Not Leak Detection) 0.382 0.048 0.335 0.266 0.734 0.002 17.01 0.000 Closure 0.382 0.150 0.232 0.099 0.901 0.002 17.43 0.000 TTT Or LTT (Not Leak Detection) Versus Closure 0.048 0.150 -0.103 0.099 0.901 0.002 -7.75 0.000

Shading: = significant (p = 0.05)

= marginally significant (0.05 < p = 0.10)

Appendix C C-14Peer Review Draft - March 2005

Analysis Of Leak Detection Frequency Of Success, Failure, And Use

Calculation of z-statistics: z = (p1 - p2) / sqrt (P * (1-P) * (1 / N)) where 1/N = 1/n1+1/n2 if proportions are independent

Leak Detection Method That Detected Release Number Of Releases Percent Releases R& I Records Percent Use p1-p2 P 1-p 1/n1 +1/n2 z p-value Groundwater Monitoring 84 73% 396 52% 21% 0.55 0.45 0.0100 4.26 0.000 TTT/IC* 11 10% 54 7% 2% 0.07 0.93 0.0100 0.95 0.340 Line Tightness Test 9 8% 33 4% 4% 0.05 0.95 0.0100 1.64 0.100 Secondary/Interstitial 8 7% 97 13% -6% 0.12 0.88 0.0100 -1.77 0.077 SIR 2 2% 31 4% -2% 0.04 0.96 0.0100 -1.22 0.223 Manual Tank Gauging 1 1% 39 5% -4% 0.05 0.95 0.0100 -2.03 0.042 ATG 0 0% 106 14% -14% 0.12 0.88 0.0100 -4.26 0.000 Vapor monitoring 0 0% 8 1% -1% 0.01 0.99 0.0100 -1.10 0.270 Total 115 100% 764 100%

Leak Detection Method Failed To Detect Release (For All Releases) Number Of Releases Percent Releases R& I Records Percent Use p1-p2 P 1-p 1/n1 +1/n2 z p-value Groundwater Monitoring 70 73% 396 52% 21% 0.54 0.46 0.0117 3.91 0.000 Secondary/Interstitial 11 11% 97 13% -1% 0.13 0.87 0.0117 -0.35 0.730 TTT/IC* 9 9% 54 7% 2% 0.07 0.93 0.0117 0.82 0.414 SIR 3 3% 31 4% -1% 0.04 0.96 0.0117 -0.44 0.659 ATG 1 1% 106 14% -13% 0.12 0.88 0.0117 -3.59 0.000 Manual Tank Gauging 1 1% 39 5% -4% 0.05 0.95 0.0117 -1.78 0.075 Vapor Monitoring 1 1% 8 1% 0% 0.01 0.99 0.0117 NA NA Line Tightness Test 0 0% 33 4% -4% 0.04 0.96 0.0117 -2.08 0.038 Total 96 100% 764 100%

Leak Detection Method Appearances In Records Use (Frequency Of

Appearance In Records) 1 Identified As

Failed Proportion Of

Failures To Detect Release Identified As

Succeeding Proportion Of

Successful Release Detection Groundwater Monitoring 396 52% 70 73% 84 73% ATG 106 14% 1 1% 0 0% Secondary/ Interstitial 97 13% 11 11% 8 7% TTT/IC 54 7% 9 9% 11 10% Manual Tank Gauging 39 5% 1 1% 1 1% Line Tightness Testing 33 4% 0 0% 9 8% SIR 31 4% 3 3% 2 2% Vapor monitoring 8 1% 1 1% 0 0% Total 764 100% 96 100% 115 100% 1. Except for results of false or faulty alarms

LLD Detected Release (For All

Releases) Number Of Releases Percent Releases R& I Records Percent Use p1-p2 P 1-p 1/n1 +1/n2 z p-value Electronic LLD 4 21% 63 18% 3% 0.19 0.81 0.0555 0.29 0.769 Mechanical LLD 15 79% 280 82% -3% 0.81 0.19 0.0555 -0.29 0.769 Total 19 100% 343 100%

LLD Failed To Detect Release (For All Releases) Number Of Releases Percent Releases R& I Records Percent Use p1-p2 P 1-p 1/n1 +1/n2 z p-value ELectronic LLD 4 17% 63 18% -1% 0.18 0.82 0.0464 -0.12 0.907 Mechanical LLD 19 83% 280 82% 1% 0.82 0.18 0.0464 0.12 0.907 Total 23 100% 343 100%

Leak Line Detection Appearances In Records Percent Use

(Frequency Of Appearance In Records) 1 Identified As

Failed Percent Of

Failures To Detect Release Identified As

Succeeding Percent

Successful Release Detection Electronic LLD 63 18% 4 17% 4 21% Mechanical LLD 280 82% 19 83% 15 79% Total 343 100% 23 100% 19 100% 1. Except for results of false or faulty alarms

Shading: = significant (p = 0.05) = marginally significant (0.05 < p = 0.10) * Tank Tightness Testing / Inventory Control

* Tank Tightness Testing / Inventory Control

Appendix C C-15Peer Review Draft - March 2005

Contamination Of Groundwater And Surface Water By Source Of Release

Number Percent Number Percent Number Percent Fuel Delivery 101 64 63.4% 2 2.0% 66 65.3% Dispenser 130 53 40.8% 4 3.1% 57 43.8% Piping 122 71 58.2% 3 2.5% 71 58.2% Pump (Turbine)** 52 32 61.5% 0 0.0% 32 61.5% Tank 63 54 85.7% 1 1.6% 54 85.7% Other*** 56 35 62.5% 4 7.1% 39 69.6% Total Media Affected 524 309 59.0% 14 2.7% 319 60.9% * Total does not sum because four releases impacted both surface and groundwater ** Includes six LLD releases *** Other includes seven fill pipe and one vent line release not included in the fuel delivery category

Calculation of z-statistics: z = (p1 - p2) / sqrt (P * (1-P) * (1 / N)) where 1/N = 1/n1+1/n2 if proportions are independent

Differences In Proportions Between Each Sources Contribution To Total Water Impacts

Releases (1) Releases (2) p1 p2 p1-p2 P 1-P 1/N z 2-tailed p-value Dispenser 0.207 0.179 0.028 0.193 0.807 0.00313 1.28 0.201 Piping 0.207 0.223 -0.016 0.215 0.785 0.00313 -0.68 0.495 Pump (Turbine) 0.207 0.100 0.107 0.154 0.846 0.00313 5.28 0.000 Tank 0.207 0.169 0.038 0.188 0.812 0.00313 1.72 0.086

Piping 0.179 0.223 -0.044 0.201 0.799 0.00313 -1.96 0.050 Pump (Turbine) 0.179 0.100 0.078 0.139 0.861 0.00313 4.04 0.000 Tank 0.179 0.169 0.009 0.174 0.826 0.00313 0.44 0.658

Pump (Turbine) 0.223 0.100 0.122 0.161 0.839 0.00313 5.93 0.000 Tank 0.223 0.169 0.053 0.196 0.804 0.00313 2.40 0.016

Pump (turbine) Versus Tank 0.100 0.169 -0.069 0.135 0.865 0.00313 -3.61 0.000

Differences In Proportions Of The Likelihood Of Each Source Impacting Water Releases (1) Releases (2) p1 p2 p1-p2 P 1-P 1/n1+1/n2 z p-value Dispenser 0.653 0.438 0.215 0.532 0.468 0.01759 3.25 0.001 Piping 0.653 0.582 0.071 0.614 0.386 0.01810 1.09 0.275 Pump (Turbine) 0.653 0.615 0.038 0.641 0.359 0.02913 0.46 0.642 Tank 0.653 0.857 -0.204 0.732 0.268 0.02577 -2.86 0.004

Piping 0.438 0.582 -0.144 0.508 0.492 0.01589 -2.28 0.023 Pump (Turbine) 0.438 0.615 -0.177 0.489 0.511 0.02692 -2.16 0.031 Tank 0.438 0.857 -0.419 0.575 0.425 0.02357 -5.52 0.000

Pump (Turbine) 0.582 0.615 -0.033 0.592 0.408 0.02743 -0.41 0.681 Tank 0.582 0.857 -0.275 0.676 0.324 0.02407 -3.79 0.000

Pump (Turbine) Versus Tank 0.615 0.857 -0.242 0.748 0.252 0.03510 -2.97 0.003

Contamination Of Groundwater And Surface Water By Pressure And Suction Pumps

Source Number Of

Releases Number Percent Number Percent Number Percent Pressure 100 58 58.0% 2 2.0% 58 58.0% Suction 11 5 45.5% 1 9.1% 5 45.5% Total Media Affected* 111 63 56.8% 3 2.7% 63 56.8% * Does not include 11 releases where type of pump system was not reported.

Differences In Proportions Of Releases From Each Pump Type Impacting Groundwater And/Or Surface Water Releases (1) Releases (2) p1 p2 p1-p2 P 1-P 1/N z p-value Pressure Suction 0.921 0.079 0.841 0.500 0.500 0.01587 13.35 0.000

Differences In Proportions Of Releases From Each Pump Type Impacting Groundwater And/Or Surface Water Releases (1) Releases (2) p1 p2 p1-p2 P 1-P 1/n1+1/n2 z p-value Pressure Suction 0.580 0.455 0.125 0.568 0.432 0.10091 0.80 0.425

Shading: = significant (p = 0.05)

= marginally significant (0.05 < p = 0.10) Source Number Of

Releases Percent Of Each Sources' Contribution To Total Water Impacts

16.9% Impacting Groundwater Impacting Surface Water Total Impacting

Water *

20.7%

17.9% 22.3% 10.0%

Impacting Groundwater Impacting Surface Water Total Impacting Water 12.2%

Fuel Delivery Versus

Dispenser Versus

Piping Versus

Piping Versus Dispenser Versus Fuel Delivery Versus

Appendix C C-16Peer Review Draft - March 2005

Release Volumes

Number Of Releases By Source And Number Of Gallons Discharged

Release Source 0 To 10 10 To 50 50 To 100 100 To 500 500 To 1000 1000 To 5000 > 5000 Unknown Total

Fuel Delivery 7 16 9 9 1 1 0 58 101 Dispenser 7 12 4 4 0 3 0 89 119 Fill Pipe 0 1 1 1 0 0 0 8 11 Other 5 10 0 5 1 2 0 20 43 Piping 4 17 5 5 4 2 2 72 111 Piping And Dispenser 0 0 1 0 0 0 0 9 10 Pump (Turbine) 2 2 2 0 0 0 0 46 52 Tank 3 7 1 1 1 4 0 44 61
Tank And Piping 1 0 0 0 0 0 0 0 1

Tank And Dispenser 0 0 0 0 0 0 0 1 1 Vent Line 0 0 0 0 0 0 0 2 2

29 65 23 25 7 12 2 349 512

Release Source Total Gallons

Discharged Average Median Minimum Maximum Lower 95% Confidence Limit Of Mean Upper 95%

Confidence Limit Of Mean Fuel Delivery 5,416 126 50 1 1,250 64 208 Dispenser 7,798 260 25 3 3,400 64 543 Fill Pipe 280 93 55 25 200

-- -- Other 9,387 408 25 2 5,000 66 939 Piping 44,947 1,152 50 2 25,000 202 2,701 Piping And Dispenser 85 85 85 85 85

-- -- Pump (Turbine) 200 33 23 10 75 15 54

Tank 11,831 696 50 5 3,500 228 1,283
Tank And Piping 10 10 10 10 10

-- -- Overall 79,954 491 40 1 25,000 231 878 Number Of Gallons

Amounts Released And Bootstrap Confidence Limits On Average Release Volumes*

* Bootstrap confidence intervals are derived by "resampling" the input data for each release source (10,000 iterations) to determine the distribution of mean values

Appendix C C-17Peer Review Draft - March 2005



### Analysis Of Tank And Piping Use Versus Releases

Tank Construction Materials

Material Number Of Releases Percent Releases Records With Non-Tank Releases* Percent Use Number Of UST Systems Percent Use Concrete 1 1.6% 1 0.2% 1 0.0% Fiberglass 41 65.1% 336 54.5% 8819 59.3% Clad Steel 1 1.6% 110 17.9% 3373 22.7% Polyethylene 1 1.6% 0 0.0% 6 0.0% Other FDEP-Approved Material 0 0.0% 1 0.2% 7 0.0% Steel 19 30.2% 168 27.3% 2657 17.9% Total 63 100.0% 616 100.0% 14863 100.0% Blank 0 7 262 Unknown 0 5 70 * Excludes records with tank releases

Calculation of z-statistics: z = (p1 - p2) / sqrt (P * (1-P) * (1 / N)) where 1/N = 1/n1+1/n2 if proportions are independent

Differences In Proportions Of Releases Compared To Use Based On R&I Data p1 (Releases) p2

(Use) p1-p2 P 1-P 1/n1 + 1/n2 z p-value Fiberglass 0.651 0.545 0.105 0.56 0.445 0.017 1.60 0.109 Clad Steel 0.016 0.179 -0.163 0.163 0.837 0.017 -3.33 0.001 Steel 0.302 0.273 0.029 0.275 0.725 0.017 0.49 0.625

Differences In Proportions Of Releases Compared To Use Based On FDEP Data p1 (Releases) p2

(Use) p1-p2 P 1-P 1/n1 + 1/n2 z p-value Fiberglass 0.651 0.593 0.057 0.59 0.41 0.016 0.93 0.354 Clad Steel 0.016 0.227 -0.211 0.23 0.77 0.016 -4.00 0.000 Steel 0.302 0.179 0.123 0.18 0.82 0.016 2.54 0.011

Comparison Of Steel Tank Releases And Use By Corrosion Protection Method Where Cause Is Corrosion

Corrosion Protection (Steel Tanks) Number Of Releases Percent Releases R& I Records (Non-Tank) Percent Use p1-p2 P 1-P 1/n1 + 1/n2 z p-value Impressed Current 4 40% 43 30.5% 9.5% 0.31 0.69 0.107 0.63 0.531 Sacrificial Anode 3 30% 74 52.5% -22.5% 0.51 0.49 0.107 -1.37 0.169 Lining 3 30% 24 17.0% 13.0% 0.18 0.82 0.107 1.03 0.301 Total 10 100% 141 100%

Shading: = significant (p = 0.05) = marginally significant (0.05 < p = 0.10)

Piping Use And Construction Material Releases And Incident Data (R&I) FDEP Data

Releases And Incident Data (R&I) FDEP Data

Appendix C C-18Peer Review Draft - March 2005

Materials Number of Releases Percent Releases Records with NonTank Releases* Percent Use Number Of UST Systems Percent Use Approved Synthetic Material 11 9.2% 36 6.7% 2053 14.1% Other FDEP Approved Material 0 0.0% 4 0.7% 217 1.5% Fiberglass 92 76.7% 386 71.3% 11131 76.5% Steel/Galvanized Metal 17 14.2% 115 21.3% 1147 7.9% Total Known Materials 120 100.0% 541 100.0% 14548 100.0% Blank 1 26 486 Unknown 1 5 93 * Excludes records with piping releases

Calculation of z-statistics: z = (p1 - p2) / sqrt (P * (1-P) * (1 / N)) where 1/N = 1/n1+1/n2 if proportions are independent

Differences In Proportions Of Releases Compared To Use Based On R&I Data p1 (Releases) p2

(Use) p1-p2 P 1-P 1/n1 + 1/n2 z p-value Fiberglass 0.767 0.713 0.053 0.72 0.277 0.010 1.18 0.239 Steel 0.142 0.213 -0.071 0.20 0.800 0.010 -1.76 0.079 Approved Synthetic Material 0.092 0.067 0.025 0.07 0.929 0.010 0.97 0.333

Differences In Proportions Of Releases Compared To Use Based On FDEP Data p1 (Releases) p2

(Use) p1-p2 P 1-P 1/n1 + 1/n2 z p-value Fiberglass 0.767 0.765 0.002 0.77 0.235 0.008 0.04 0.968 Steel 0.142 0.079 0.063 0.08 0.921 0.008 2.54 0.011 Approved Synthetic Material 0.092 0.141 -0.049 0.14 0.859 0.008 -1.55 0.121

Comparison Of Metal Pipe Releases And Use By Corrosion Protection Method Where Cause Is Corrosion

Corrosion Protection (Steel Piping) Number Of Releases Percent Releases R& I Records (Non-Tank) Percent Use p1-p2 P 1-P 1/n1 + 1/n2 z p-value Impressed Current 3 60% 23 32% 28.5% 0.33 0.67 0.214 1.31 0.191 Sacrificial Anode 2 40% 50 68% -28.5% 0.67 0.33 0.214 -1.31 0.191 Total 5 100% 73 100%

Shading: = significant (p = 0.05) = marginally significant (0.05 < p = 0.10) Pressure Versus Suction Pumps

Piping Releases With Pressure Versus Suction Pumps Number Of Releases Percent Releases Records With NonTank Releases* Percent Use Number Of UST Systems Percent Use Pressure Pump 100 90.1% 409 88.3% 11482 91.5% Suction Pump 11 9.9% 54 11.7% 1061 8.5% Total 111 100.0% 463 100% 12543 100% Blank 11 110 2626 * Excludes records with piping releases, where pump type is specified Releases And Incident Data (R&I) FDEP Data

Appendix C C-19Peer Review Draft - March 2005

Calculation of z-statistics: z = (p1 - p2) / sqrt (P * (1-P) * (1 / N)) where 1/N = 1/n1+1/n2 if proportions are independent

Differences In Proportions Of Releases p1 p2 p1-p2 P 1-P 1/n z p-value Pressure Versus Suction 0.901 0.099 0.802 0.500 0.500 0.00901 16.90 0.000

Differences In Proportions Of Releases Compared To Use Based On R&I Data p1 (Releases) p2

(Use) p1-p2 P 1-P 1/n1 + 1/n2 z p-value Pressure 0.901 0.883 0.018 0.89 0.113 0.011 0.523 0.601 Suction 0.099 0.117 -0.018 0.11 0.887 0.011 -0.523 0.601

Differences In Proportions Of Releases Compared To Use Based On FDEP Data p1 (Releases) p2

(Use) p1-p2 P 1-P 1/n1 + 1/n2 z p-value Pressure 0.901 0.915 -0.015 0.92 0.085 0.009 -0.547 0.585 Suction 0.099 0.085 0.015 0.08 0.915 0.009 0.547 0.585

Shading: = significant (p = 0.05) = marginally significant (0.05 < p = 0.10)

Appendix C C-20Peer Review Draft - March 2005



### Tank And Piping Age Distributions

FDEP Tank Age Distributions (Numbers Of USTs) FDEP Piping Age Distributions (Numbers Of USTs) Age All* Fiberglass Steel Clad Steel Age All* Fiberglass Steel/Galv.** Approv. Synth. Suction Pressure 0-<5.0 2044 1141 332 555 0-<5.0 1911 972 36 791 86 1601 5-<10 1785 947 196 538 5-<10 1722 1143 41 364 104 1390 10-<15 4650 2804 327 1297 10-<15 4506 3713 239 282 378 3143 15-<20 4549 2684 685 880 15-<20 4440 3351 379 372 237 3356 20-<25 1439 910 395 58 20-<25 1367 986 159 125 76 1034 25-<30 419 152 224 2 25-<30 410 272 70 33 39 306 30-<35 411 126 196 9 30-<35 394 282 61 26 48 264 35-<40 125 0 91 7 35-<40 125 78 38 0 13 84 40-<50 78 1 52 5 40-<50 78 54 7 0 7 44 Total 15501 8765 2498 3351 Total 14953 10851 1031 1993 988 11222 Time In Use Time In Use Mean 14.30 13.78 18.32 11.76 Mean 14.37 14.77 18.74 9.72 15.22 14.08 Std. Dev. 7.39 6.34 9.89 5.53 Std. Dev. 7.36 6.85 7.47 7.41 7.67 7.36 Median 14.42 14.33 18.17 13.08 Median 14.42 14.50 17.50 6.58 14.04 14.33

*total, average, std. dev., and median statistics include one tank with age >50 **total, average, std. dev., and median statistics for steel/galvanized tanks include one tank with age >50

Numbers Of Tank Releases Versus Age Numbers Of Piping Releases Versus Age Age All Tanks Fiberglass Steel Age All Piping Fiberglass Steel/Galv. Approv. Synth. Suction Pressure 0-<5.0 3 1 1 0-<5.0 20 15 2 3 2 18 5-<10 9 6 2 5-<10 28 24 1 3 2 24 10-<15 13 11 2 10-<15 24 19 3 2 4 20 15-<20 10 6 4 15-<20 11 9 2 0 0 11 20-<25 5 5 0 20-<25 0 0 0 0 0 0 25-<30 1 0 1 25-<30 2 1 1 0 1 0 30-<35 2 0 2 30-<35 0 0 0 0 0 0 35-<40 0 0 0 35-<40 0 0 0 0 0 0 40-<50 0 0 0 40-<50 0 0 0 0 0 0 Total 43 29 12 Total 85 68 9 8 9 73 Time To Release Mean 14.40 13.95 17.07 Mean 9.7 9.7 12.1 6.29 11.3 9.3 Std. Dev. 7.06 5.41 9.53 Std. Dev. 5.7 5.4 8.20 3.73 7.6 5.2 Median 13.20 13.20 16.02 Median 8.9 8.9 12.3 6.53 10.1 8.8 Time To Release * All >(fiberglass + steel + clad steel) because material of construction is not known for some tanks *All > (fiberglass + steel + approv synth) because material of construction is not known for some piping

Appendix C C-21Peer Review Draft - March 2005



### t-Test For Mean Ages

FDEP Tank Age Versus R&I Tank Releases

Tank Configuration FDEP Tank Age R&I Releases t-Value Degrees Of Freedom p
All Tanks 14.30 14.40 -0.08 15,542 0.935 Fiberglass Tanks 13.78 13.95 -0.15 8,792 0.884 Steel Tanks 18.32 17.07 0.44 2,508 0.661

FDEP Piping Age Versus R&I Piping Releases

Piping Configuration FDEP Piping Age R&I Releases t-Value Degrees Of Freedom p All Piping 14.37 9.65 5.90 15,036 0.000 Fiberglass Piping 14.77 9.73 6.05 10,917 0.000 Steel/Galvanized Piping 18.74 12.07 2.66 1,038 0.008 Approved Synth. Piping 9.72 6.29 1.31 1,999 0.191 Suction Piping 15.22 11.26 1.54 995 0.124 Pressure Piping 14.08 9.25 5.59 11,293 0.000


### Shading: = significant (p = 0.05) = marginally significant (0.05 < p = 0.10) Mean (Years) Mean (Years)

Appendix C C-22Peer Review Draft - March 2005

Fisher's Exact And Z-Tests For Piping Ages

ICF: Of piping whose age is less than the specified age, compare percent use and percent releases:

Material FDEP Use Data Percent Use Number Of Releases Percent

Releases

Fiberglass 972 54.0% 15 75.0% Steel/Galvanized 36 2.0% 2 10.0% Approved Synthetic Material 791 44.0% 3 15.0% Total <5 Years Old 1799 20

Fiberglass 9879 81.8% 53 81.5% Steel/Galvanized 994 8.2% 7 10.8% Approved Synthetic Material 1202 10.0% 5 7.7% Total >5 Years Old 12075 65

Calculation of z-statistics: z = (p1 - p2) / sqrt (P * (1-P) * (1 / n)) where 1/n = 1/n1+1/n2 if proportions are independent

p1 (Use) p2 (Releases) p1-p2 P 1-P 1/n z p - value Fisher's Exact p-value

Fiberglass 54.0% 75.0% -20.97% 54.26% 45.74% 0.051 1.87 0.06 0.07 Steel/Galvanized 2.0% 10.0% -8.00% 2.09% 97.91% 0.051 2.49 0.01 0.06 Approved Synthetic Material 44.0% 15.0% 28.97% 43.65% 56.35% 0.051 2.60 0.01 0.01

Material FDEP Use Data Percent Use Number Of Releases Percent

Releases

Fiberglass 2115 63.2% 39 81.3% Steel/Galvanized 77 2.3% 3 6.3% Approved Synthetic Material 1155 34.5% 6 12.5% Total <10 Years Old 3347 48

Fiberglass 8736 83.0% 29 78.4% Steel/Galvanized 953 9.1% 6 16.2% Approved Synthetic Material 838 8.0% 2 5.4% Total >10 Years Old 10527 37

p1 (Use) p2 (Releases) p1-p2 P 1-P 1/n z p - value Fisher's Exact p-value

Fiberglass 63.2% 81.3% -18.06% 63.45% 36.55% 0.02 2.58 0.01 0.01 Steel/Galvanized 2.3% 6.3% -3.95% 2.36% 97.64% 0.02 1.79 0.07 0.10 Approved Synthetic Material 34.5% 12.5% 22.01% 34.20% 65.80% 0.02 3.19 0.00 0.00 Piping <10 Years Old significant =

Piping <5 Years Old marginally significant = Piping <5 years old

Piping >5 years old

Piping <10 years old

Piping >10 years old

Appendix C C-23Peer Review Draft - March 2005

Material FDEP Use Data Percent Use Number Of Releases Percent

Releases

Fiberglass 5828 76.9% 58 80.6% Steel/Galvanized 316 4.2% 6 8.3% Approved Synthetic Material 1437 19.0% 8 11.1% Total <15 Years Old 7581 72

Fiberglass 5023 79.8% 10 76.9% Steel/Galvanized 714 11.3% 3 23.1% Approved Synthetic Material 556 8.8% 0 0.0% Total >15 Years Old 6293 13

p1 (Use) p2 (Releases) p1-p2 P 1-P 1/n z p - value Fisher's Exact p-value

Fiberglass 76.9% 80.6% -3.68% 76.91% 23.09% 0.014 0.74 0.46 0.57 Steel/Galvanized 4.2% 8.3% -4.17% 4.21% 95.79% 0.014 1.75 0.08 0.13 Approved Synthetic Material 19.0% 11.1% 7.84% 18.88% 81.12% 0.014 1.69 0.09 0.097

Material FDEP Use Data Percent Use Number Of Releases Percent

Releases

Fiberglass 9179 78.6% 67 80.7% Steel/Galvanized 695 5.9% 8 9.6% Approved Synthetic Material 1809 15.5% 8 9.6% Total <20 Years Old 11683 83

Fiberglass 1672 76.3% 1 50.0% Steel/Galvanized 335 15.3% 1 50.0% Approved Synthetic Material 184 8.4% 0 0.0% Total >20 Years Old 2191 2

p1 (Use) p2 (Releases) p1-p2 P 1-P 1/n z p - value Fisher's Exact p-value

Fiberglass 78.6% 80.7% -2.16% 78.58% 21.42% 0.012 0.48 0.63 0.69 Steel/Galvanized 5.9% 9.6% -3.69% 5.97% 94.03% 0.012 1.41 0.16 0.16 Approved Synthetic Material 15.5% 9.6% 5.85% 15.44% 84.56% 0.012 1.47 0.14 0.17 Piping >20 years old

Piping <20 Years Old Piping <15 years old

Piping <20 years old Piping >15 years old

Piping <15 Years Old

Appendix C C-24Peer Review Draft - March 2005



### K-S Test For Tank Ages

FDEP Tank Age Distributions (Numbers Of Tanks) Cumulative Distributions (Tank Age) Age All* Fiberglass Steel Clad Steel Age All Fiberglass Steel Clad Steel 0-<5.0 2,044 1,141 332 555 0-<5.0 0.132 0.130 0.133 0.166 5-<10 1,785 947 196 538 5-<10 0.247 0.238 0.211 0.326 10-<15 4,650 2,804 327 1,297 10-<15 0.547 0.558 0.342 0.713 15-<20 4,549 2,684 685 880 15-<20 0.840 0.864 0.616 0.976 20-<25 1,439 910 395 58 20-<25 0.933 0.968 0.775 0.993 25-<30 419 152 224 2 25-<30 0.960 0.986 0.864 0.994 30-<35 411 126 196 9 30-<35 0.987 1.000 0.943 0.996 35-<40 125 0 91 7 35-<40 0.995 1.000 0.979 0.999 40-<49 78 1 52 5 40-<49 0.999935488 1 1 1 Total 15,501 8,765 2,498 3,351

Average 14.30 13.78 18.32 11.76 Std. Dev. 7.39 6.34 9.89 5.53 Median 14.42 14.33 18.17 13.08 **total, average, std. dev., and median statistics include one tank with age >50

Number Of Tank Releases Versus Age Cumulative Distribution (Tank Releases) Age All Tanks Fiberglass Steel Age All Tanks Fiberglass Steel 0-<5.0 3 1 1 0-<5.0 0.070 0.034 0.083 5-<10 9 6 2 5-<10 0.279 0.241 0.250 10-<15 13 11 2 10-<15 0.581 0.621 0.417 15-<20 10 6 4 15-<20 0.814 0.828 0.750 20-<25 5 5 0 20-<25 0.930 1 0.750 25-<30 1 0 1 25-<30 0.953 1 0.833 30-<35 2 0 2 30-<35 1 1 1 35-<40 0 0 0 35-<40 1 1 1 40-<49 0 0 0 40-<49 1 1 1 Total 43 29 12

Average 14.40 13.95 17.07 Std. Dev. 7.06 5.41 9.53 Median 13.20 13.20 16.02

Age All Tanks Fiberglass Steel 0-<5.0 0.062 0.096 0.050 5-<10 0.032 0.003 0.039 10-<15 0.034 0.063 0.074 Shading: = significant (p = 0.05) 15-<20 0.027 0.037 0.134 = marginally significant (0.05 < p = 0.10) 20-<25 0.003 0.032 0.025 25-<30 0.007 0.014 0.031 30-<35 0.013 0.000 0.057 35-<40 0.005 0.000 0.021 40-<49 0.000 0.000 0.000 M 0.062 0.096 0.134 Chi-squared 0.66 1.06 0.85 p-value 0.72 0.59 0.65 Time In Use

Time To Release

Differences In Cumulative Distributions, KolmorgorovSmirnov Test Results

Appendix C C-25Peer Review Draft - March 2005

K-S Test For Piping Ages

FDEP Piping Age Distributions (Numbers Of Installations) Cumulative Distribution (Piping Ages) Age All* Fiberglass Steel/Galv.** Approv. Synth. Suction Pressure Age All Fiberglass Steel/Galv. Approv. Synth. Suction Pressure 0-<5.0 1911 972 36 791 86 1601 0-<5.0 0.128 0.090 0.035 0.397 0.087 0.143 5-<10 1722 1143 41 364 104 1390 5-<10 0.243 0.195 0.075 0.580 0.192 0.267 10-<15 4506 3713 239 282 378 3143 10-<15 0.544 0.537 0.306 0.721 0.575 0.547 15-<20 4440 3351 379 372 237 3356 15-<20 0.841 0.846 0.674 0.908 0.815 0.846 20-<25 1367 986 159 125 76 1034 20-<25 0.933 0.937 0.828 0.970 0.892 0.938 25-<30 410 272 70 33 39 306 25-<30 0.960 0.962 0.896 0.987 0.931 0.965 30-<35 394 282 61 26 48 264 30-<35 0.986 0.988 0.955 1.000 0.980 0.989 35-<40 125 78 38 0 13 84 35-<40 0.995 0.995 0.992 1.000 0.993 0.996 40-<50 78 54 7 0 7 44 40-<50 1 1 0.999 1.000 1 1 Total 14953 10851 1031 1993 988 11222 Time in Use Average 14.37 14.77 18.74 9.72 15.22 14.08 Std. Dev. 7.36 6.85 7.47 7.41 7.67 7.36 Median 14.42 14.50 17.50 6.58 14.04 14.33 *All > (fiberglass + steel + approv synth) because material of construction is not know for some piping **total, average, std. dev., and median statistics for steel/galvanized tanks include one tank with age >50

Number Of Piping Releases Versus Age Cumulative Distribution (Piping Releases) Age All Piping Fiberglass Steel/Galv. Approv. Synth. Suction Pressure Age All Fiberglass Steel/Galv. Approv. Synth. Suction Pressure 0-<5.0 20 15 2 3 2 18 0-<5.0 0.235 0.221 0.222 0.375 0.222 0.247 5-<10 28 24 1 3 2 24 5-<10 0.565 0.574 0.333 0.750 0.444 0.575 10-<15 24 19 3 2 4 20 10-<15 0.847 0.853 0.667 1 0.889 0.849 15-<20 11 9 2 0 0 11 15-<20 0.976 0.985 0.889 1 0.889 1 20-<25 0 0 0 0 0 0 20-<25 0.976 0.985 0.889 1 0.889 1 25-<30 2 1 1 0 1 0 25-<30 1 1 1 1 1 1 30-<35 0 0 0 0 0 0 30-<35 1 1 1 1 1 1 35-<40 0 0 0 0 0 0 35-<40 1 1 1 1 1 1 40-<50 0 0 0 0 0 0 40-<50 1 1 1 1 1 1 Total 85 68 9 8 9 73 Time To Release Average 9.7 9.7 12.1 6.29 11.3 9.3 Std. Dev. 5.7 5.4 8.20 3.73 7.6 5.2 Median 8.9 8.9 12.3 6.53 10.1 8.8

Age All Piping Fiberglass Steel/Galv. Approv. Synth. Suction Pressure 0-<5.0 0.107 0.131 0.187 0.022 0.135 0.104 5-<10 0.322 0.379 0.259 0.170 0.252 0.309 10-<15 0.303 0.316 0.360 0.279 0.314 0.303 Shading: = significant (p = 0.05) 15-<20 0.135 0.139 0.215 0.092 0.074 0.154 = marginally significant (0.05 < p = 0.10) 20-<25 0.044 0.049 0.061 0.030 0.003 0.062 25-<30 0.040 0.038 0.104 0.013 0.069 0.035 30-<35 0.014 0.012 0.045 0.000 0.020 0.011 35-<40 0.005 0.005 0.008 0.000 0.007 0.004 40-<50 0.000 0.000 0.001 0.000 0.000 0.000 M 0.322 0.379 0.360 0.279 0.314 0.309 Chi-squared 8.75 9.69 1.16 0.62 0.88 6.92 p-value 0.013 0.008 0.561 0.733 0.64 0.031 Differences In Cumulative Distributions, Kolmorgorov-Smirnov Test Results

Appendix C C-26