p.1 

OAR Box 1208 

Prepped by Ollie Stewart 

Document Number: 

126) ll-E-12 

Docket Number: 

A-89-10 

Printed 5/9/2008 10:08:24 AM Sheet 126 of 127 
P.2 

LAW OPFICSS 

PHILIP J. HARTER 

SUITE 404 

2301 M STREET. N.W. 

WASHINGTON, O.C 20037 

(202) 8S7.I033 

FAX: (202) 887-1036 

January 24, 1990 mJUUULlii 

MEMORAND U 

To: EPA Negotiated Rulemaking Committee on Fugitive Emissions from Equipment Leaks and Interested" 

Parties 

Fr: Philip J. Harter 

Facilitator 

Re: Minutes of January 17-18 Meeting; Future Meetings; Workgroup Meetings; Miscellaneous Materials 

I enclose the minutes of the January 17-18 meeting that were prepared by Radian Corporation. As 

before, the materials that were distributed at the meeting are attached. I have also included an updated 

"statement" concerning the negotiations. As I explained before, several parties indicated that they had 

received calls about the negotiations, and it seemed appropriate to prepare a general statement about what 

the Committee is doing. I hope I captured the essence of our deliberations without prematurely 

crystallizing any notions that are still tentative and fluid. Use it as you see fit. I have also enclosed a 

tentative agenda for the meeting. 

Two workgroups have been scheduled before the next meeting: 

o The workgroup that will review the data base and make recommendations concerning it to the full 

committee will meet at 10:00 on Wednesday, January 31 in the 9th Floor Conference Room in 

EPA's Offices in the Mutual Building, 411 W. Chapel Hill Street, Durham, NC. 

o The Batch Processing workgroup will meet at 10:00 on Wednesday, February 21 at the offices of the 

Pharmaceutical Manufacturers Association, 1100 Fifteenth Street NW, Washington, DC; for 

additional information, contact Cheryl Sutterfield at 202-835-3548. 

Our meeting schedule is: 

o FebriMiry 22-23 at the Bristol Hotel, 2430 Pennsylvania Avenue NW, Washington, DC; 202-955-

6400. CMA made the arrangements for the meeting. Thus, if you wish to book a room at the 

hotel, identify yourself as with the CMA EPA Fugitives meeting. 

March 27-28 at the Pickett Suite Hotel, 2515 Meridian Parkway, Research Triangle Park, NC; 919-

361-4660. Note that as of February 1 the hotel's name will be changed to "Guest Quarters;" I am 

told that everything else will remain the same except breakfast which will be upgraded but for 

which you will now be charged. Again, when making reservations, identify yourself as an EPA 

Fugitive. 
P.3 

• April 25-26 at The Conservation Foundation, Suite 500, 1250 24th Street NW, Washington, DC. 

Since we will not be meeting at a hotel, we have not booked any rooms for this meeting. CF is 

about a five block walk from the Embassy Square Suites Hotel (202-659-2000) where our December 

meeting was held; it is about three blocks from the Bristol Hotel; and it is next door to the Westin 

(800-228-3000), the Park Hyatt (202-789-1234). There are bunches of other hotels within walking 

distance. Since that is "Earth Week", you may be well advised to make your reservation early. 

All the meetings will begin at 10:00 on the first day and 9:00 on the second. They will run until about 

5:00 on the first day and about 4:00 on the second. 
JL4 

ENVIRONMENTAL PROTECTION AGENCY 

NEGOTIATING COMMITTEE FOR 

CONTROL OF FUGITIVE EMISSIONS OF VOCs FROM EQUIPMENT LEAKS 

AGENDA FOR MEETING OF FEBRUARY 23-23 

Administrative 

o Introductions 

° Review of the Agenda: additions, subtractions, order 

o Minutes of January meeting: Any major heartburns 

Scope of the Standard 

o Sources included in the negotiations 

o Sources excluded from this standard 

o De minimis cutoff 

Data 

° Report of the Data Workgroup 

o Discussion of data 

o Additional data: availability and requirements 

Leak definition and allowable leakers: MACT 

Conceptual Approach to the Standard 

o Phasing 

o Incentives (bottom line of boxes) 

o Exit criteria (right column of boxes) 

° Miscellaneous points raised at prior meetings 

o Sampling strategies 

o Procedures for determining equivalent approaches 

Report of the Batch Processing Workgroup 

Emission Factors 

° Status of modelling approach 

o Matrix approach 

Approaches to assessing the cost of the standard 
P.5 

January 25, 1990 

STATEMENT CONCERNING EPA'S REGULATORY NEGOTIATION 

ON 

CONTROL OF FUGITIVE EMISSIONS OF VOCs FROM EQUIPMENT LEAKS 

Fugitive emissions of toxic chemicals and volatile organic compounds (VOCs) from equipment leaks -

such as valves, pumps, and flanges - are a significant source of air pollution. Indeed, by some estimates, 

leaks constitute between one and two thirds of all routine, non-accidental emissions from chemical plants. 

Moreover, because they are released near the ground, EPA believes their impact may be 10-40 times 

greater than equal releases from stacks. 

Current regulations basically require that equipment be inspected quarterly for leaks with a portable 

hydrocarbon detector. If concentrations exceed 10,000 ppm the source is identified as a "leaker," and 

maintenance is required. This approach is known as "leak detection and repair" (LDAR). 

The current LDAR program can reduce uncontrolled emissions by about 60-70 percent. The actual 

frequency rate and the associated emissions vary widely, however. No one is sure just what combination 

of factors guarantees low emissions nor how to achieve them through enforceable regulations. 

In addition, current regulatory approaches do not provide the means for calculating the level of emissions. Yet the accurate quantification of fugitive emissions from equipment leaks is becoming important. 

Specific emission levels are necessary for baseline and residual risk assessments for new regulations, for 

issuing permits for new facilities, and for establishing appropriate emission fees. Further, compames must 

report emissions under "The Community Right To Know Act." 

Not only does the current regulatory approach not achieve accurate estimates of the actual emissions, it 

does not provide incentives or credit to firms for establishing programs and facilities to achieve the best 

control. Nor does the approach ensure emission rates that are readily achievable. 

EPA recently convened a regulatory negotiation to address these shortcomings. Representatives of EPA; 

the chemical, petroleum, rubber, and pharmaceutical industries; environmental organizations; and state and 

local governments are working together to develop a consensus on: 

o a new standard based upon the maximum available control technology (MACT) for control of 
P.6 

fugitive emissions from equipment leaks; 

o emission factors for fugitive emissions of VOCs from equipment leaks, leading to a better quantification of the magnitude of the leaks; and 

o a format that couid be used to implement a risk based standard for toxic organic emissions of 

hazardous air pollutants from equipment leaks. Specific risk limits or goals will not be a subject of 

the negotiations, however. 

Thus far, the committee has reviewed conceptual approaches that would provide incentives for good 

performance and disincentives for poor performance. Basically, the approach being discussed would define 

a leak in terms of so many parts per million and an "allowable number of leakers", defined in terms of a 

percentage of all sources of fugitive emissions of a particular type, such as valves, flanges, or pumps, with a 

maximum number established for small plants. The plant would then be required to monitor the potential 

sources of fugitive emissions, and any leakers that are discovered must be repaired. If the screening shows 

consistent results below the allowable number of leakers, the momtoring could be done less frequently; if, 

on the other hand, it demonstrated leaks in excess of the allowable level, momtoring would be required 

more often. Random samples could also be used in plants with consistent levels below the specified level. 

There has been some discussion as to a program that would address plants that chronically fail to meet the 

performance level. The precise contours of the approach and how it would be phased in are still being 

discussed. 

This approach would apply most directly to processes that operate more or less continuously. Processes 

that operate only intermittently may pose some difficulty, however. Because of the unique aspects of these 

batch processes, the committee formed a workgroup to explore alternative regulatory approaches apphcable 

to them. Five were suggested to the committee: (1) building bagging, in which all emissions from an 

operation are discharged through a single vent that could be measured; (2) pressure testing of all lines to 

ensure that they are not leaking; (3) screening frequencies based on "time in use" as opposed to the general 

standard; (4) random screening during operations; and (5) screening only those components actually in use 

during the screening cycle. 

Other regulatory approaches were also discussed, as well as how a firm and the agency could assess 

other approaches to determine whether they would be "equivalent" to the generic standard. 
P.7 

The scope of the standard under discussion has been broadened beyond the source categories originally 

announced by EPA. The agency intends to develop generic standards that would be applicable to all 

chemical manufacturing facilities that use as raw materials or produce as intermediates, co-products, or final 

products any of the 191 chemicals listed in the proposed amendments to the Clean Air Act. The precise 

sources need to be further defined. 

The committee has been reviewing screening data from ethylene oxide and butadiene plants, as well as 

data from some other plants, as the basis for the standard. On the committee's suggestion, the data has 

been reformulated to show the percentage of leakers at varying leak definitions. Some aberrations in the 

data have been noted, and a workgroup will examine the data for presentation at the next committee 

meeting. 

The committee has also considered a couple of approaches for assessing emissions. That effort has 

largely been held in abeyance pending further development of the conceptual approach. It has briefly 

discussed a sequential samphng approach that could be used to accompUsh the random sampling aspects of 

the conceptual approach. The committee also acknowledged the need to examine the need for or level of a 

"cutoff" or "de minimis" level for application of the standard. While some criteria have been mentioned, it 

has not yet begun to define the lower limit of applicability. 

The committee's discussions, like all negotiations, are tentative until a final agreement is reached. The 

committee has expUcitly recognized that many parts of the standard depend on other parts, so that the 

specific levels and requirements hinge on other aspects of the deUberations. 

The committee is holding meetings approximately once per month, alternating between Washington and 

Durham. Meetings will be held on February 22 and 23 in Washington; March 27 and 28 in Durham; and 

April 25 and 26 in Washington. They wUl be announced in the Federal Register, and members of the 

pubhc are welcome to attend. 
P.8 

REGULATORY NEGOTIATION MEETING ON FUGITIVE EQUIPMENT LEAKS 

JANUARY 17-18, 1990 

PICKETT SUITE HOTEL 

DURHAM, NORTH CAROLINA 

DRAFT MEETING MINUTES 

These meeting notes summarize issues discussed and provide an informal 

record of administrative and logistical decisions made on schedules and action 

items. All presentation materials distributed during the two-day meeting are 

attached: 

Attachment 1 

Attachment 2 

Attachment 3 

Attachment 4 

Meeting Agenda 

Attendees January 17, 1990 

Revisions to December 6-7 meeting notes 

Draft Report to the Equipment Leaks Regulatory 

Negotiations Committee; Meeting Minutes-Batch Work 

Group 

Attachment 5: Presentation Slides-Alternative Leak Detection 

Techniques 

Attachment 6: Handout "Equivalent" Fugitive Emissions Control 

Program: Conceptual Basis 

Attachment 7: Presentation Slides-- Monitoring Plan Evaluation 

Attachment 8: December 22 data analyses package distributed to 

committee by Robert Pahel-Short -EPA 

Attachment 9: Handout of condensed data package—prepared by Mr. 

Majewski 

Attachment 10: Sequential Sampling Handout 

Attachment 11: Costs of Equipment Screening: Letter from Walter 

Brenner, Sun Refining and Marketing Co. 

Minutes of Previous Meeting 

The minutes of the previous full committee meeting (December 6-7, 

1989) were discussed. Changes in the minutes approved by the 

Committee are contained in Attachment 3. 

Batch Processing 

Dr. Jack Kace reported on the January 4, 1990 work group meeting 

on batch processes (see Attachment 4). Dr. Kace provided 

background information on the pharmaceuticals industry describing 

products that are manufactured using batch processes. Dr. Kace 

described several unique difficulties in applying the type of LDAR 

program currently being discussed by the committee to batch 

processes. Among the difficulties described was the scheduling of 

screening activities at a time when equipment was "in service" for 

one or more of the chemicals of interest, since the mix of 

products will change during any given month. Further, 

difficulties are 

cao.027 
P.9 

that even for processes using chemicals of concern, screening 

would involve accurately timing all LDAR activities to coincide 

with the stage of the process where the chemicals of concern are 

being used. 

The batch process workgroup identified five possible alternative 

leak detection techniques for batch processes: 1) building 

bagging, 2) pressure testing of all process lines, 3) establishing 

screening frequency based on "time-in-use", 4) random screening, 

and 5) screening only those components in use during a screening 

cycle. The workgroup plans to investigate the feasibility of each 

of the five alternatives. The next workgroup meeting is scheduled 

for 10:00 a.m., Wednesday, February 21 at the Pharmaceutical 

Manufacturers Association's office, at 1100 Fifteenth Street, NW, 

Washington DC. For additional information, interested parties 

should contact Ms. Cheryl Sutterfield at (202) 835-3548. 

Other Equivalent Regulatory Approaches 

Mr. Jerry Schroy of Monsanto presented two alternative leak 

detection techniques (see Attachment 5): 1) multi-component 

monitoring achieved through monitoring entire building exhaust 

(i.e., building bagging), and 2) use of industrial hygiene data to 

determine workplace concentration limits. Mr. Schroy stated that 

these techniques provide reliable cost-effective alternatives for 

meeting EPA's goal of reducing emissions. 

Mr. Ron Berglund of Union Carbide presented a conceptual program 

for, the control of fugitive leaks. The program was distinguished 

by the use of three types of directed inspections: 1) the 

judgement inspection program, whose purpose is to identify leaking 

components; 2) the information inspection whose purpose is to 

repair defective components; and 3) the source inspection, whose 

purpose is to prevent components from becoming leakers. 

The committee discussed the criteria that must be met to consider 

alternative regulatory approaches as equivalent to the regulatory 

approach should be defined. A proposal was made that any approach 

recognized as equivalent should be based on total emissions. 

Several members noted that using total emissions as the criterion 

would require the development of proper emission factors. 

Scope of the Standard 

Mr. Bob Ajax of EPA described the regulatory activities for 

wastewater, process vents, storage, and transfer that are being 

conducted by the Agency through the conventional rulemaking 

process. These rules, along with the negotiated equipment leak 

rules will apply to each source category that will be regulated. 

The Agency intends to expand the scope of the rules that are 

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P.10 

Data 

planned for adoption within the first two years after passage CAA 

revisions. The scope will go beyond the thirteen source 

categories originally discussed, and is now planned to include all 

categories of SOCMI sources that produce, and possibly all that 

use (as raw materials) chemicals in the CAA list (e.g., the 

current list of 191). Although organic chemical processes located 

in refineries or on refinery property would be affected, the 

Agency does not plan at this time, to include petroleum refinery 

processes among the source categories affected by this initial 

phase of rules. 

Prior to the January meeting, EPA distributed to all committee 

members a package containing an analysis showing the percent 

leakers by component type for various leak definitions (Attachment 

7 ). The analysis was performed on the ethylene oxide and 

butadiene screening data distributed during October. Mr. Majewski 

distributed a combined version of the data to the committee for 

discussion (Attachments). 

Some committee members expressed concern over the quality of the 

data, noting evidence that some data appear to have been rounded 

down or truncated. Committee members were requested to review the 

data in detail prior to resuming discussions on the quality of 

data and prior to deciding on the data subset to use in 

establishing the level of the standard. Frequency plots of the 

data will be distributed during the week of January 22 with the 

intent of discussing the data in detail in an interim workgroup 

meeting. Further discussions of the data by the full committee 

was postponed until the February meeting. The workgroup meeting 

on data quality is scheduled for Wednesday, January 31 at 10:00 at 

the EPA's Durham North Carolina office (Mutual Building), in the 

9th floor conference room. 

Several committee members said there was a sufficient quantity of 

data that were not of questionable quality to allow positions on 

the level of the standard to be formulated. A suggestion was made 

that a leak definition of 50 ppm and 4 to 5 percent leak frequency 

was supported for valves and flanges taking into account that some 

of the data is suspect. One proposal was that the committee begin 

by considering a leak definition at the lowest practical 

concentration, which should logically begin at instrument 

detection levels. 

Discussions continued on the role of cost in determining MACT and 

the specific language and intent of the CAA. Several members said 

that discussion of the level of the standard should not be 

considered apart from costs. Some said that MACT discussions 

should start by looking at the performance level demonstrated by 

the best controlled plants and ask why others cannot duplicate 

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P.11 

that performance level. Others said that the cost per level of 

control must be considered as an integral part of defining MACT. 

Concern was voiced over extrapolating emission levels that are 

achievable and affordable for the butadiene and ethylene oxide 

industries to cover all other affected industries. 

Conceptual Approach to the Standard 

An analysis of the conceptual LDAR approach discussed in the 

December meeting was presented the compared a monthly base to a 

quarterly base program (Attachment 9). Specifically, the analysis 

evaluated two elements for monthly and quarterly base programs: 

1) the probability of failing an inspection, and 2) the number of 

inspections required per year. During the presentation there was 

discussion about the number of program levels a plant would have 

to fall back if they sampled annually and found an unacceptable 

leak level. There was a consensus that a plant should not be 

required to go all the way back to the base monitoring frequency 

in those circumstances. 

Mr. Ajax summarized some of the key premises upon which the 

conceptual regulatory approach discussions have been centered, in 

the context of the time schedules expected in the CAA revision. 

The premises discussed included the use of allowable limits as 

performance standards and as a trigger for LDAR, incentives for 

decreased monitoring frequencies, and possible penalties for final 

nonconformance. 

Mr. Ajax presented the following items, which in his view appeared 

to be areas where a "general sense of agreement" exists among 

several of the committee members with respect to the conceptual 

regulatory approach. 

1. The best 10 or so ethylene oxide and butadiene plants 

reflect the performance of MACT--recognizing that data for 3 

to 5 plants may be suspect. 

2. To achieve MACT goals and based on common sense, the leak 

definition level should be as low as practical. 

3. Further evaluation is needed to determine the lowest 

practical leak definition. 

4. Some suggested that discussions on the level of the standard 

for valves and flanges should start in the range of 50 ppm 

and 4 to 5 percent leak rates based on the available data. 

5. A compliance/penalty scheme needs to be considered to bring 

into final conformance those plants that chronically fail to 

achieve the performance level defined by the allowable 

limit. 

6. Random sampling is a desirable goal if it is practical. 

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P.12 

Mr. Ajax distributed a handout (Attachment 10) showing some 

examples of how sequential sampling could be used to accomplish 

the goal of random sampling. The text of the handout was 

developed for woodstoves compliance schemes but the attached 

tables were developed specifically for scenarios related to this 

equipment leak program. Mr. Ajax walked through an example of the 

approach using a 500 inspection cutoff scenario (page EL-5 of 

handout). The key variables considered by the approach include 

"alpha"- which is the probability of falsely (incorrectly) 

identifying a plant as a leaker (based on leak definition of Ho), 

and "power" - which is the probability of truly (correctly) 

identifying a plant as a leaker as compared to the ad hoc value 

(Ha). In the example on page EL-5, the "acceptance number" 

identifies the allowed number of leakers for a given number of 

screened components that would constitute compliance. For 

example, if 110 components were screened and 0 leakers were found 

(page EL-7) the plant could stop sampling and be considered in 

compliance. If however 8 leakers were found (the "rejection 

number") during the screening of those 110 components the plant 

would be considered out of compliance. 

Emission Factors 

CMA reported that little effort had been spent on the conceptual 

model since the last meeting. The committee generally agreed that 

the conceptual model has a much greater significance in light of 

the equivalency issue. CMA agreed to take the lead on developing 

information for the emission factor discussion at the next 

meeting. 

The committee briefly discussed the concept of assigning default 

emission factors based upon the LDAR program "box". This concept 

was introduced in the December meeting and is outlined in 

Attachment 4 of the December meeting minutes. 

Approaches for Assessing Costs 

Some committee members said that many of the affected sources will 

have no existing control program in place and therefore the 

incremental cost of control for those facilities would be 

significantly greater than for industries currently performing 

LDAR. Mr. Ajax suggested that a worst case cost estimate could be 

made by comparing monthly LDAR to the SOCMI factors with quarterly 

LDAR. 

Attachment 11 describing cost for equipment screening was 

distributed. 

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P.13 

Cutoffs 

One suggestion was that cost be used as an indicator for 

determining logical cutoffs. Emission magnitude and in-line 

concentration were also proposed as possible cutoff criteria. 

Action Items 

EPA will take the lead in developing an annotated outline of the 

conceptual rule. The annotated rule will be an expansion of the 

"strawman" rule drawing on the earlier list of 24 issues. EPA 

will distribute the outline prior to the February meeting, if 

possible. 

CMA will take the lead in the emission factor area and in the 

further investigation of the conceptual model. 

CMA will distribute data packages for discussion in the January 31 

data quality workgroup meeting. 

Pharmaceutical Manufacturers Association (PMA) will continue to 

investigate feasibility of alternative approaches for batch 

processes. 

Future Meetings 

Data quality workgroup: January 31 at 10:00 a.m., EPA/Mutual 

Building, 9th floor conference room, Durham NC. 

Batch Processes workgroup: February 21 at 10:00 a.m., PMA Offices, 

1100 Fifteenth Street, NW, Washington D.C. 

The next meeting of the full Negotiation Committee is scheduled to 

be held in Washington D.C. on February 22-23, 1990. The location 

of the meeting will be identified in the transmittal memorandum. 

March 27 and 28; Durham, N.C.-- Location to be determined. 

April 25 and 26; Washington D.C.-- Location to be determined. 

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MmC^ftMT 1 

ENVIRONMENTAL PROTECTION AGENCY 

NEGOTIATING. COMMITTEE FOR 

CONTROL OF FUGITIVE EMISSIONS OF VOCs FROM EQUIPMENT LEAKS 

AGENDA FOR MEETING OF JANUARY 17-18 

Administrative 

o Review of the Agenda: additions, subtractions, order 

o Minutes of December meeting: .Any major heartburns 

Report of the Batch Processing Workgroup 

Data 

° Analysis of ethylene oxide and butadiene screening data distributed in December 

<*> Status of agreement for bagging 

«*> Additional data: availabihty and requirements 

Conceptual Approach to the Standard 

o Phasing 

<*• Incentives (bottom Une of boxes) 

<"> Exit criteria (right column of boxes) 

o MisceUaneous points raised at prior meetings 

Emission Factors 

° Status of modelling approach 

o Matrix approach 

Conceptual approach to leak definition and allowable leakers 

Approaches to assessing the cost of the standard 

Procedures for determining equivalent approaches 

a J 
P.15 

/OT^C^ftMT 

ENVIRONMENTAL PROTECTION AGENCY 

NEGOTIATING COMMITTEE FOR 

CONTROL OF FUGITIVE EMISSIONS OF VOCs FROM EQUIPMENT LEAKS 

ATTENDEES LIST FOR MEETING OF JANUARY 17-18, 1990 

NAME 

Robert Majewski 

Al Bickum 

Gus VonBodungen 

Harvel Rogers 

Karen Hom e 

Deborah Dalton 

Philip Harter 

Bob Ajax 

David Dunn 

Tom Kittleman 

Allen Hershkowitz 

Jack Kace 

Larry Goodheart 

Linda Curran 

Meredith Miller 

Bruce Grumstrup 

Rick Colyer 

Walt Brenner 

Karen Fidler 

Ed Moretti 

Bill Schikora 

Jim Hess 

Charlie Anderson 

Mary Ann Gorko 

Kathy Bailey 

Jerry Schroy 

David Markwordt 

Ron Berglund 

Al Wehe 

Bob Hinkson 

Charles Bennett 

Bob Rowland 

Bob Strieter 

Ellen Siegler 

Scott Throwe 

Martin E. Rock 

Miriam Levon 

James F. Murphy 

Kathy Kaufman 

Glenn Rives 

Robert Pahel-Short 

AFFILIATION 

NESCAUM 

IISRP, 

Louisiana DEQ-Air Quality 

JCAPCD 

TACB 

EPA - Reg Neg Project 

Facilitation 

U. S. EPA 

Sterling Chemicals, Inc. 

CMA (DuPont) 

NRDC 

PMA (Roche) 

API (Chevron) 

Amoco Oil 

Fisher Controls 

Fisher Controls 

EPA/OAQPS 

Sun Co. 

CMA 

Radian Corp. - RTP 

Chevron Corp. 

DuPont 

Sherex Chemical Co. 

DuPont 

CMA 

Monsanto 

EPA/OAQPS 

Union Carbide 

EPA/OAQPS 

Mobay Synthetics 

Ashland Petroleum Co. 

Pfizer Inc. 

API 

API 

EPA/OAQPS/SSCD 

OMNI Envirn. Service Inc 

ARCO 

W.R. Grace & Company 

EPA/OAR/OPAR 

Radian Corp - RTP 

EPA/OAQPS 
P.16 

ATTACHMENT 3 

REVISIONS TO DECEMBER MINUTES 

Second bullet under Conceptual Approach (Page 2) 

o Under Phase III of the conceptual approach, the program would 

shift to a performance standard. Screening results would be 

compared to the standard and if the leak frequency is found to be 

less than the allowable limit, monitoring would be allowed using a 

random sample or a less frequent approach. The frequency of 

monitoring would be based on the results of previous screenings 

(i.e., less frequent monitoring required for plants that 

consecutively demonstrate leak rates less than, for example, half 

the allowable limit). The normal monitoring frequency during 

Phase III would be quarterly for plants achieving the allowable 

limit. 

First bullet under Emission Factor (Page 4) 

o Attachment 9 contains a handout showing bar charts and tables 

showing leak frequencies and emission factors for the EO and BD 

plants. Attachment 10 contains a tabular summary listing the 

component characteristics (i.e., valve type, material of 

construction, packing type, etc.,) for EO and BD plants with leak 

frequencies on both ends of the spectrum. 
P.17 

/OTACCiftMT 41 

Draft Report to the Equipment Leaks Regulatory Negotiations Committee 

ffeeting mnutes - Batch Processing Work Group 

January 4, 1990 - Washington, D.C. 

The production operations in the pharmaceutical industry were 

summarized. An excerpt from the USEPA Effluent Guideline Development 

Document describing the four industry subcategories was distributed (copy 

attached). 

The chemical synthesis subcategory of pharmaceutical manufacturing 

was described and further divided into three groups: continuous operations 

with dedicated equipment, batch operations with dedicated equipment, and 

batch operation with multipurpose equipment. Both batch groups share 

the need for very high manpower requirements to do fugitive testing. 

The problem is more severe in the multipurpose equipment group. The typical 

pharmaceutical product takes five steps (or sequences of unit operations). 

Each step typically has five major pieces of equipment. 

The batch sequence in one major piece of equipment was described 

(see attached process flow diagram and process instrumentation diagram). 

Fugitive sources in batch production operations are generally in operation 

much less than continuous operations and thus have a lower pollution 

potential. 

The following alternative leak testing techniques for batch processes 

were discussed: 

(1) Process "Bubble" 

The total fugitive losses from the process would be determined by 

measuring the concentration in the exhaust air from an enclosure around 

the process or by use of area monitors or similar techniques. Allowable 

emissions from a batch process will be difficult to calculate. 
P.18 

(2) Pressurized Testing 

A part of the process would be pressurized or placed under vacuum 

and the pressure change versus time determined. If acceptable, no further 

testing is needed. If the pressure test is unacceptable, must test 

components, repair leaks, and retest. The system could also be tested 

with a surrogate (i.e. helium, nitrogen). 

(3) Time in Use Ratio 

The components would be tested by screening techniques while in use 

at conditions expected to result in maximum emissions. Because of the 

high manpower requirement for this type of testing, and the fact that 

these sources only emit when in use, sources in use with, hazardous air 

pollutants would be required to be tested according to the following 

formula: 

Process Run Time Fugitive Testing Requirement 

up to 8760 hrs/yr - same as continuous 

up to 6570 hrs/yr - 3/4 as frequently as continuouse 

up to 4380 hrs/yr - 1/2 as frequently as continuous 

up to 2190 hrs/yr - 1/4 as frequently as continuous 

up to 1095 hrs/yr - 1/8 as frequently as continuous 

minimum testing requirement - every 2 yrs for pumps and agitators 

(4) Randomized Approach 

Test all components in random manner independent of process conditions. 

This could be applied to all components or only flanges and valves. 

(5) Components In Use 

Test all components in service at the time of the fugitive test. 

Report percent leakers found versus components in use. 
P.19 

Other CoBBgnts 

Components under vacuum should be exempt from these rules since their 

emission is regulated as a point source. 

Method twenty-one for screening is very time consuming. Alternative 

testing using catalytic testers (such as Gastrac NGX-600) is sufficient 

for screening purposes. 

A 500 ppm standard for pumps would require capital expenditures to 

upgrade or replace pumps with packed seals or single mechanical seals. 

The cost-benefit for this may be unreasonable. 

Any equivalent approach should have a deadline on USEPA and State 

approval. USEPA should publish criteria by which they would judge an 

alternative method. A default should be included whereby the equivalent 

method is automatically approved if USEPA takes no action in one year 

or that the source is not subject to the rule until USEPA acts on their 

request. 

The production schedule for a pharmaceutical plant was distributed 

and discussed (copy attached) to show the complexity of fugitive testing. 

OVA meter readings are likely to be inaccurate on batch processes 

that employ a mix of solvents since the meter must be calibrated to one 

solvent. 

Some production operations require "maximum containment." To protect 

workers we should use a fugitive measurement approach that does not require 

the testers to risk exposure. 

Double mechanical, seals are a problem in pharmaceutical applications. 

Concern was raised about seal fluid leakage into the product. 
P.20 

Equipment life is longer in many batch operations because the pump, 

agitator, etc. is only in use part of the year. 

Conclusion 

The group agreed that many potentially useful alternatives were 

discussed. These alternatives must be developed further. It was 

recommended that the work group continue to meet to complete this task. 
P.21 

Attendees 

Jack Kace 

Tom White 

Rick Colyer 

Harvel Rogers 

Al Bickum 

David Donniger 

David Dunn 

Ralph V. Johnson 

Mary Legatski Synthetic Organic Chemical Manufacturers Assoc, 

Joe O'Lair 

William J. Bareford 

Bob Rowland 

Jim Hagan 

Catherine Ehlhardt 

Craig F. Seyfried 

Robert Baldisserotto 

Cheryl Sutterfield 

Karen Fidler 

Hoffmann-La Roche 

PMA 

EPA 

Jefferson Co. APCC 

Goodyear/11SRP 

Natural Resources 

Sterling Chemicals 

Dixie Chemical Co. 

Synthetic Organic 

DuPont - Chambers 

DuPont - Chambers 

Pfizer Inc. 

Inc. 

) 

Defence 

(SOCMA) 

Chemical 

Works 

Works 

Smith Kline - French 

Eli Lilly & Company 

Wyeth-Ayerst 

Hoffmann-La Roche 

PMA 

Inc. 

Council 

Manufacturers 

J 
P.22 

DEVELOPMENT DOCUMENT FOR PROPOSED EFFLUENT LIMITATIONS 

GUIDELINES, NEW SOURCE PERFORMANCE STANDARDS AND PRETREATMENT STANDARDS 

FOR THE 

PHARMACEUTICAL MANUFACTURING 

POINT SOURCE CATEGORY 

ANNE GORSUCH 

ADMINISTRATOR 

FREDERIC A. EIDSNESS, JR. 

ASSISTANT ADMINISTRATOR 

FOR WATER 

STEVEN SCHATZOW 

DIRECTOR 

OFFICE OF WATER REGULATIONS AND STANDARDS 

JEFFERY D. DENIT 

DIRECTOR, EFFLUENT GUIDELINES.DIVISION 

DEVEREAUX BARNES 

ACTING CHIEF, ORGANIC CHEMICALS BRANCH 

y

f0iS 

Frank H. Hund, Ph.D. 

Daniel S. Lent 

Joseph S. Vital is 

Proiect Officers 

November 1982 

Effluent Guidelines Division 

Office of Water 

U.S. Environmental Protection Agency 

Washington, D.C. 20460 • 
P.23 

Puerto Rico has close to 10 percent of the industry and is 

becoming a major pharmaceutical manufacturing center. 

Table 111 — 2 breaks down the industry by manufacturing 

subcategory. These process-based subcategories were used for a 

review of the industry, although these distinctions were not 

carried through for purposes of developing the newly proposed 

regulations. Subcategory D (formulating/mixing/ compounding) is 

the most prevalent pharmaceutical manufacturing operation, with 

80 percent of the plants in the industry engaged in this 

activity. Fifty-eight percent of the plants have operations in 

only Subcategory D. The remainder also have operations in other 

subcategories. 

Table III-3 summarizes the total number of batch, continuous, and 

semi-continuous manufacturing operations by subcategory for the 

entire pharmaceutical industry. Batch-type production is the 

most common type of manufacturing technique for each of the four 

subcategories. 

C. MANUFACTURING PROCESSES 

One of the most important generalizations which can be made about 

the wastewaters produced and discharged by the pharmaceutical 

industry is their extreme, diversity. Products, processes, and 

the materials to which wastewater is exposed vary greatly. With 

the goal of relating those discharges with some common 

characteristics, subcategories based on unit manufacturing 

processes were defined. The broad manufacturing processing areas 

considered were (a) fermentation, (b) biological and natural 

extraction, (c) chemical synthesis, and (d) formulation. 

One characteristic of processing in this industry is that the 

ratio of finished product to the quantity of raw materials, 

solvents, and other processing materials is generally very low. 

This is most apparent in natural extraction (Subcategory B), 

followed by fermentation (A), synthesis (C), and formulation (D * , 

respectively. 

1. Fermentation 

Fermentation is the usual method for producing most antibiotics 

and steroids. The fermentation process involves three basic 

steps: inoculum and seed preparation, fermentation, and product 

recovery. 

Production of a fermentation pharmaceutical begins with spores 

from the plant master stock. The spores are activated with 

water, nutrients, and warmth; they are then propagated through 

33 
P.24 

they can contribute to priority pollutant waste loads. Phenol is 

a commonly used disinfectant. 

• o 

Sometimes a fermentation batch can become infested with a phage, 

a virus that attacks microorganisms. Although phage infestation 

is rare in a well-operated plant, when it occurs, very large 

wastewater discharges may be necessary in a short period of time. 

Usually the batch is discharged early and its nutrient pollutant 

concentration is higher than that, of spent broth. 

The pollution contribution of the spent beer arises from the fact 

that the beer contains substantial food materials such as sugars, 

starches, protein, nitrogen, phosphate, and other nutrients. 

Methods for treating the fermentation wastes are generally 

biological in nature. Although the spent- beers, even in a highly 

concentrated form, can be satisfactorily handled by biological 

treatment systems, it is less likely to upset the system if the 

wastes are first diluted to some degree. Dilution normally 

results from the equalization of fermentation wastes with the 

other waste streams. As a result, a satisfactory, biological 

reduction of the contaminantis can be achieved. 

The 308 data shows generally that wastewaters from Subcategory A 

plants generally are characterized by high BOD, COD, and TSS 

concentrations, large flows, and a pH range of about 4.C to 8.C. 

2. Biological and Natural Extraction 

Many materials used as pharmaceuticals are derived from such 

natural sources as the roots and leaves of plants, animal glands, 

and parasitic fungi. These products have numerous and diverse 

pharmaceutical applications ranging from tranquilizers and 

allergy relief medications to insulin and morphine. Also 

included in this group is blood fractionation, which involves the 

production of plasma and its derivatives. 

35 
P.25 

known to be used as precipitating agents. Phenol was identified 

as an equipment sterlizing chemical as well as an active 

ingredient. . Otherwise, priority pollutants are found to be used 

only as processing solvents. Some identified as solvents were 

benzene, chloroform, and 1,2 dichlorbethane. 

Solvents are used in two ways in extraction operations. First, 

they are used to remove fats and oils that would contaminate the 

products. These "defatting" extractions use an organic liquid 

that dissolves the fat but not the product material. Solvents 

are also used to extract the product itself. Plant alkaloids, 

when treated with an alkali, become soluble in such selected 

organic solvents as benzene, chloroform, or 1,2 dichloroethane. 

Ammonia is used in many extraction operations since it is 

necessary to control the pH of water solutions from both animal 

and plant sources to achieve separation of valuable components 

from waste materials. Ammonium salts are used as buffering 

chemicals and aqueous or anhydrous ammonia is used as an 

alkalizing reagent. The high degree of water solubility of 

ammonium salts prevents unwanted precipitation of* =>-a. c; also, 

ammonia does not react chemically with animal or plant tissue. 

Such basic materials as hydroxides and carbonates of alkali 

metals do not have these advantages. 

The principal sources of wastewater from biological/natural 

extraction operations are (a) spent raw materals (waste plasma 

fractions, spent eggs, spent media broth, plant residues, etc.); 

{b) . floor and equipment washwaters; (c) chemical wastes (spent 

solvents and the like); and (d) spills. 

In general, the bulk of the spent raw materials is collected and 

sent to an incinerator or landfill. Likewise, the nonrecoverable 

portions of the spent solvents are incinerated or landfilled. 

However, in both cases, portions of the residual materials find 

their way into a plant's wastewater. Floor and equipment 

washings and spills also contribute to the ordinary waste 

discharge. 

Although pollutant information for the biological/natural 

extraction operations in the pharmaceutical data base was 

limited, that which was available lent itself to a preliminary 

analysis. Generally, wastewaters from Subcategory B plants are 

characterized by low BOD, COD, and TSS concentrations; small 

flows; and pH values of approximately 6.0 to 8.0. 

3. Chemical Synthesis 

Most of the compounds used as drugs today are prepared by 

chemical synthesis (generally by a batch process). The basic 

37 
P.26 

Each pharmaceutical is usually manufactured in a "campaign" in 

which one or more process unit is employed for a few weeks or 

months to manufacture enough compound to satisfy its projected 

sales demand. Campaigns are usually tightly scheduled, with 

detailed coordination extending from procurement of raw materials 

to packaging and labeling of the product. For a variable period 

of time, therefore, a process unit actively manufactures a 

specific compound. At the end of this campaign, another is 

scheduled to follow. The same equipment and operating personnel 

are used to make a completely different product, utilizing 

different raw materials, executing a different recipe, and 

creating different wastes. 

The synthetic pharmaceuticals industry uses a wide variety of 

priority pollutants as reaction and purification solvents (43). 

Water was reported to be used more often than would be expected 

in an industry whose products are organic chemicals. However, 

benzene and toluene were the most widely used organic solvents 

since they are stable compounds that do not easily take part in 

chemical reactions. Similar ring-type compounds (xylene, 

cyclohexane, pyridine, etc.) also were reported as being used in 

the manufacture of synthesized pharmaceuticals or resulting from 

unwanted side reactions. 

Solvents serve several functions in a chemical synthesis. They 

dissolve gaseous, solid, or viscous reactants to bring all 

reactants into close molecular proximity. They serve to transmit 

heat to or from the reacting molecules. By physically separating 

molecules from each other, they slow down some reactions that 

would otherwise tafte place too rapidly and that would result in 

excessive temperature increases and unwanted side reactions. 

There are other less obvious uses of solvents, however. One of 

these is the use of a solvent in the control of reaction 

temperature. It is common practice in a batch-type synthesis to 

select a solvent whose boiling point is the same as the desired 

reaction temperature and which is compatible with the reaction. 

Heat is then applied to the. reaction mass at a rate sufficient to 

keep the mixture continuously boiling. Vapors that rise from the 

reaction vessel are condensed and the liquefied solvent is 

allowed to drain back into the reaction vessel. Such refluxing 

prevents both overheating and overcooling of the reactor contents 

and can automatically compensate for variations in the rate of 

release or absorption of chemical energy. 

Essentially all production plants operate solvent recovery 

facilities that purify contaminated solvent for reuse. These 

facilities usually contain distillation columns and may also 

include extraction facilities where still another solvent is used 

to separate impurities. Many of the wastes from the synthetic 

39 
P.27 

Although pharmaceutically active ingredients are produced in bulk 

form, they must be prepared in dosage form for use by the 

consumer. Pharmaceutical compounds can be formulated into 

tablets, capsules, liquids, or ointments. 

Tablets are formed in a tablet press machine by blending the 

active ingredient, filler, and binder. Some tablets are coated 

by tumbling with a coating material and drying. The filler 

(usually starch, sugar, etc.) is required to dilute the active 

medicinal to the proper concentration, a binder (such as corn 

syrup or starch) is necessary to bind the tablet particles 

together. A lubricant (such as magnesium stearate) may be added 

for proper tablet machine operation. The dust generated duringthe mixing and tableting operation is collected and is usually 

recycled directly to the same batch. Broken tablets are 

generally collected and recycled to the granulation operation in 

a subsequent lot. After the tablets have been coated and dried, 

they are bottled and packaged. 

Capsules are produced by first forming, the hard gelatine shell. 

These shells are produced by machines that dip rows .of rounded 

metal dowels into a molten gelatine solution and then strip the. 

capsules from the dowels after the capsules have cooled and 

solidified. Imperfect empty capsules are remelted and reused, if 

possible, or sold for glue manufacture. Most pharmaceutical 

companies purchase empty capsules from a few specialist 

producers. 

The active ingredient and any filler are mixed before being 

poured by machine into the empty gelatine capsules. The filled 

capsules are bottled and packaged. As in the case of tablet 

production, some dust is generated. Although this is recycled, 

small amounts of waste dust must be disposed of. Some glass and 

packaging waste from broken bottles and cartons also result from 

this operation. 

Liquid preparations can be formulated for injection or oral use. 

In either case, the liquid is first weighed and then dissolved in 

water. Injectable solutions are bulk sterilized by heat or 

filtration and then poured into sterilized bottles. Oral liquid 

preparations may be bottled directly without the sterilization 

steps. 

Wastewaters are generated by general cleanup operations, spills, 

and breakage. Bad batches may create a solid waste disposal 

problem. 

The primary objective of mixing/compounding/formulation 

operations is to convert the manufactured products into a final, 

usable form. The necessary production steps have typically small 
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ATTACHMENT 1 

TYPICAL GROTON PRODUCTION DATA 
P.32 

/OTAOEiftMT 

Fugitive Emissions Negotiated Regulations Proposal 

Equivalence 

The reason for my presentation is to highlight industry's need for 

specific equivalent methods of compliance to be incorporated in the next 

set of fugitive emission regulations and to offer examples of possible 

"alternative methods of emission limitations". The presentation will be 

made by myself and Ron Berglund of Union Carbide. The methods of 

equivalence to be discussed are industrial hygiene data sets, 

multicomponent bagging (ie., bag a building) and cluster monitoring. I will 

discuss the first two topics and Ron will discuss the later topic. 

The existing fugitive emission regulations established by the EPA for 

specific chemicals (eg., Subpart J- National Emission Standard for 

Equipment Leaks (Fugitive Emissions Sources of Benzene) call for Leak 

Detection and Repair (LDAR) or allow the owner to propose an "alternative 

means of emission limitation" (Paragraph 61.242(c)). However, this 

general option to use "alternative means of emission limitation" requires 

extensive test data for each site proposed by an owner (Paragraph 61.244) 

and requires the approval of the Director. The rigorous requirements for 

equivalence in and of themselves inhibit the development of alternative 

control methods which could prove to be more effective than control 

options such as Leak Detection and Repair. The lack of guidance for those 

implementing the rules on what constitutes an equivalent method also 

prevents initiation of requests for "alternative means of emission 

limitations". The protocol given in the example, for implementing an 

"alternative means of limitation", in Subpart J is far too restrictive and 

costly. The regulations should provide some approved alternative methods 

of compliance to encourage the development of emission control 

technology. 

The suitability of Leak Detection and Repair approaches is also 

questionable based on the present Synthetic Organic Manufacturing 

Industry (SOCMI) emission factors and equations. They are questionable 

because of the high emission values and the conservative nature of the 

EPA's risk assessment protocols. Data presented by the EPA to the 

committee, and to the National Air Pollution Control Technology Advisory 

Committee (NAPCTAC) last summer, indicate that compliance for some 

chemicals may not be possible using LDAR methodologies. 

Equivalence Page 1 

Jerry M. Schroy 

.^.. . -. _ . •^-....-• ~ 
A general equivalence option should be included in the regulatory 

package considered by this committee. The methodology should be 

written to allow innovative approaches to limiting equipment leaks and 

innovative proofs of those reductions. Today we will describe a few 

options which should be considered for inclusion in such a regulatory 

package. 

To understand how industry deals with fugitive emissions the 

committee should realize that fugitive emissions impact both the 

workplace and the environment beyond the workplace. The two exposure 

concerns are inseparable. This understanding coupled with the realization 

that concentrations of specific chemicals in the workplace are far easier to 

detect than those beyond the plant fence lines leads to a better 

understanding of the specific control approaches that can minimize 

emissions. Specifically, the application of a control practice depends on the 

ability to recognize that a problem exists and the yardstick that will be 

used to measure the best control strategies. The Agency applied this 

approach when it set the initial emission criteria for vinyl chloride because 

analytical detection limits prevented use of general environmental samples 

to demonstrate compliance. The rules call for controlling the sources at 

levels measured in the operating unit not at the fence line. Subsequent 

vinyl chloride rules called for leak detection and repair but there is 

insufficient data available to determine, if the change in the rules resulted 

in emission reduction. 

The committee should also recognize that the fugitive emission Leak 

Detection and Repair program used by the EPA was based on general (VOC) 

emissions, not the specific toxic chemical emissions. With the present 

Clean Air Act proposals the focus is specific chemicals and their health 

based impacts. The data received by the EPA from industrial testing 

programs demonstrate that the SOCMI emission factors do not apply to all 

chemicals. The general VOC fugitive rules recognized the differences 

between the Chemical Industry and refineries when the leak frequencies 

were established. The emission rate data also showed differences but the 

Agency chose to be conservative and keep the refinery emission factors. 

Recent data presented to the Agency on butadiene, ethylene oxide and 

toluene diisocyanate emissions show that emissions rates are below levels 

predicted by the SOCMI VOC emission factors and differences in processes 

result in differences in emissions. Similar data were available for 

acrylonitrile when the focus of the regulations were VOCs but the 

discussion of specific chemicals versus VOCs was not considered relevant. 

It has been shown that it is possible to achieve lower fugitive emission 

levels for some chemicals based on quantification of specific chemical 

Equivalence Page 2 

Jerry M. Schroy 
P.34 

emissions, but it is not possible to show compliance with any risk based 

standard using the existing SOCMI fugitive emission factors because the 

mass emission estimates are to large. The use of workplace criteria are 

also not possible for chemicals such as ethylene or propane because 

workplace exposure criteria are not based on health practices. 

With the move to apply the Maximum Achievable Control Technology 

(MACT) followed by an assessment of the risk for residual emissions there 

is only one issue, specific chemical health impacts. To understand the 

impacts it will be necessary for industry to determine the risk involved in 

applying MACT prior to expenditure of any resources. If the risks are not 

understood at the start of the program it would be possible to expend large 

quantities of resources and then have to curtail operations because MACT 

is not sufficient to meet the risk level dictated by the Agency's present 

assessment practices. The committee should understand that when 

industry deals with specific chemical toxicity issues for both the workplace 

and general environment there is only one set of control options used to 

minimize equipment leaks. Installation of control technology is necessary 

as demonstrated by present industry practices. It is not possible to meet 

strict exposure criteria in the workplace, such as the vinyl chloride 

workplace exposure standards, simply by the work practice of avoiding 

contact. This is also true for a majority of other specific chemicals which 

must be controlled to very low levels. 

The control of fugitive emissions for specific chemicals is the goal of 

most industrial hygiene programs used in industry today. The limitation 

of chemical losses to the workplace and ultimately to the environment is 

one of the most positive methods of minimizing the exposure of workers 

and those residing in the general environment and for chemicals which 

have very low workplace exposure limits it may be the only method. 

Engineering controls for achieving this level of exposure control include 

workplace monitoring programs, analytical equipment which takes 

frequent samples from various parts of an operation unit and use of 

engineering controls such as quarter turn valves, mechanically sealed 

pumps and agitators and process sampling equipment that collects only the 

quantity of sample needed. For closed buildings, the continuous 

monitoring of building ventilation air and/or exhaust streams makes the 

monitoring of mass emission rates easier and provide a clearer picture of 

the exposure impacts on both the worker and general environment. It also 

makes the risk assessments easier to quantify. 

The committee should try to picture a production unit in a closed 

building with area monitoring devices operating over a period of several 

Equivalence Page 3 

Jerry M. Schroy 
P.35 

years. The results of such monitoring efforts yield a clear picture of the 

average emission rate from all fugitive emission component, plus 

uncontrolled release points not covered by EPA fugitive emission 

categories. The same information is provided by area monitoring systems 

in open structures but with less precision. The area monitors provide a 

clear picture of average conditions and of periods when there is an 

unexpected release from a component failure. These systems are not used 

in all processes because of costs. However, they are used extensively in 

processes where worker exposure and loss to the general environment are 

a concern. Industrial hygiene monitoring in many chemical plants also 

offers the same picture of average and unexpected emissions levels. 

When the industrial hygiene exposure limits or guidelines (eg., 

TLVs) are set they are based on assessing the risks of exposure. These 

standards therefore provide a better method of limiting exposure to the 

worker and general environment than do MACT criteria. In fact' the limits 

or guidelines for the workplace are equivalent to levels that would be set 

by toxicologists for general environmental exposure. When considering . 

alternative means of limiting emissions the committee should recommend 

to the Agency that for toxic chemicals with low workplace exposure data, 

compliance with workplace concentrations set by the Agency using the 

industrial hygiene data would constitute compliance with fugitive limits 

established by the EPA. 

We recommend the establishment of a set of workplace 

concentration limits as an equivalent program using industrial hygiene 

data from all forms of personnel and area monitoring protocols. This 

approach will offer a straight forward method of dealing with specific 

chemicals and provide industry with an incentive to minimize emissions 

impacting workers and the general environment. 

The use of workplace industrial hygiene data sets for verification of 

compliance with Agency established criteria as an approach to defining an 

equivalent program will provide: 1) rapid response because industrial 

hygiene data collection programs are in place for many chemicals not 

regulated by any agency, 2) regulation of many chemicals under the 

proposed revision to the CAA with minimum Agency effort and 3) 

utilization of data collected under programs for compliance with either 

company derived limits or OSHA established limits would eliminate 

duplicate data collection programs freeing more money for application to 

control technology development thus encouraging reduce emissions. 

Equivalence Page 4 

Jerry M. Schroy 
P.36 

Meeting Comments 

The committee members indicated a willingness to consider "bag a 

building" approaches to compliance testing if the methodology could be 

demonstrated. The methodology is included in CMA Fugitive Emission 

Guidance Documents, Volume 1. The committee was less willing to deal 

with the open structure area monitoring approaches although they 

indicated a willingness to review specific proposals which are supported 

by validation data. 

Equivalence Page 5 

Jerry M. Schroy 
P.37 

^TOCTftMT 

UNION CARBIDE CORPORATION 

P. O. BOX S361. SOUTH CHARLESTON. VV. VA. 25303 

January 10, 1989 

EPA Negotiating Committee for Control 

.of Fugitive Emissions of VOC from Equipment Leaks 

(Distribution List Attached) 

Subject: "Equivalent" Fugitive Emissions Control Program: 

Conceptual Basis 

So far in the Regulatory Negotiating Committee meetings, a number of 

options for an effective fugitive emissions regulation have been outlined and 

discussed; additional ideas were solicited, and the group appears to be headed 

towards a concensus on the standard regulating format. In the interest of 

inducing continued fruitful discussions on "equivalent" mechanisms for 

regulatory control of fugitive emissions sources, I am attaching a document 

entitled "A Total Quality Control Approach to Fugitive Emissions Regulation 

and Control," which is based on the internal program being developed within 

Union Carbide. This document outlines the conceptual basis for an 

"equivalent" approach to a fugitive emissions regulation which is based on 

total quality principles. This approach is component directed, and is 

designed to focus the monitoring requirement towards components with the 

highest potential to leak, and to minimize the monitoring needed for 

components which are shown to have a low potential to leak. The approach is 

compatible with internal emission reduction programs that are being developed 

by Union Carbide and other chemical companies. Yet, it should still assure 

that for the entire affected industries, the regulatory constraints (as in 

monitoring requirements) are in direct proportion to the fugitive emission 

levels of their respective operations. I would like for the "equivalency" 

portion of any new regulation to be flexible enough to include alternate 

approaches such as this one. 

I hope to be able to discuss this approach at the Regulatory 

Negotiation Committee meeting on January 1$, and will invite your comments at 

that time. 

Very truly yours, 

R. L. Berglund 

Attachment 

3377m 
P.38 

A TOTAL QUALITY CONTROL APPROACH TO FUGITIVE 

EMISSIONS REGULATION AND CONTROL 

R. L. Berglund 

Union Carbide Chemicals and Plastics Company Inc. 

For Presentation Before 

The Environmental Protection Agency Negotiating Committee 

for Control of Fugitive Emissions of VOC From Equipment Leaks 

January 16, 1990 

Abstract 

A fugitive emissions regulatory approach, based upon Total Quality 

Control (TQC) principles is proposed as 'equivalent' to the standard Leak 

Detection & Repair (LD&R) programs presently under consideration by the 

Fugitive Emissions Regulatory Negotiation Committee. In this program, an 

initial screening of all affected components in a process unit (which may 

represent several quarters for new units) will be used to classify the 

components into two groups. Those which have screening values less than some 

deminimus value (say 50 ppm), will be classified as 'Acceptable,' and will 

be monitored in future quarters at some greatly reduced schedule (say 5% per 

quarter) to assure that the population has not changed. Those components 

which have screening values above the deminimus value (as well as special 

problem components, such as components with dynamic seals) will be classified 

as Questionable and will be monitored during all subsequent quarters until 

these components are corrected, repaired, or replaced. The expectation is 

that ga the Questionable components are either indicating that they have 

some inherent defect or are designed to allow some leakage in order to operate 

properly, which gives them a greater potential to become "leakers," while the 

Acceptable components have no such apparent defect, and (provided the system 

is not upset or the components do not wear out), therefore, should continue to 

function for a lengthy time without becoming "leakers." By focusing attention 

through the monitoring activity towards the components which have the greatest 

potential to leak, rather than diluting this monitoring among all the 

components in the process unit regardless of their leak potential, the 

operating staff will become more aware of the potentially leaking sources. 

Ultimately, historical trends on these components can be studied and long-term 

solutions developed. In addition, tight units will be monitoring at a greatly 

reduced schedule, and all units will have an incentive to correct defective 

components in the Questionable category (to remove them from the regular 

monitoring list), even if they are not "Leakers. The program is schematically 

represented in Figure 4 and developed on the next page. 
P.39 

Introduction 

During 1988 and 1989, extensive fugitive emission studies were 

conducted in the acrolein, butadiene (BD), ethylene oxide (EO) and phosgene 

production industries (1,2). In these studies, over 93,000 valves, flanges, 

pumps and other pieces of equipment were monitored. The screening results of 

these studies are summarized in Figure 1. 

Figure 1 presents the percentage of "Leakers" (components with 

screening values above i0,000 ppm) for four critical component types as 

observed in these industrywide studies. Clearly, significant differences 

between the four industry groups and the original EPA screening results can be 

observed from this comparison. Yet, the critical question that arose upon 

examining these results was: 

What is the Difference that Makes the Difference" 

between these industries. 

To evaluate the different "practices" used by the four industries 

which might explain these trends, a survey was prepared and distributed to all 

the participants. This survey was focused on the three fundamental aspects of 

fugitive emissions control: (1) programs for monitoring for a leak, (2) 

practices for maintaining or repairing the leak, once it is detected, and 

(3) procedures for preventing the occurrence of a leak through special design 

standards. Based upon the aggregation of the qualitative responses to these 

survey results, few generalizations regarding the design, monitoring, and 

maintenance practices in the four industries could be developed. However, 

several apparent strategic similarities in the operating philosophies of the 

plants with the lowest emissions (the "Benchmark" plants or industries) might 

be established. Basically, in the Benchmark operations, the unit staff are 

trained to be sensitive to leaks, and have reached a point where they do 

not tolerate leaks. A combination of rapid detection of leakage, continued 

maintenance of components, when combined with focused design changes, has 

allowed low leakage to be achieved (4). 

In considering these operations, several critical caveats need to be 

made with respect to the regulatory significance of the results. 

o Today's performance in the Benchmark units didn't just 

happen; low fugitive emissions are the cumulative results 

of years of effort. 

o This performance was achieved despite the fact that the 

Benchmark units or components were often not under a 

required fugitive emissions regulatory control program. 

o Low fugitive emissions is accomplished primarily through 

the use of conventional technology, rather than new 

technology (bellows valves, etc.). 

o New technology is selectively used where it makes good 

engineering sense. Bellows valves and sealless pumps, 

if misused, may actually present bigger problems than 

they solve. 
Overall, the one theme that pervades the operation of these Benchmark 

industries is that, while advanced technology can and should be used, the 

achievement of low levels of fugitive emissions is a direct result of the 

awareness to leaks developed within the operations and engineering staffs. 

The effective fugitive emissions control program would begin when the 

operations staff recognizes its function in reducing fugitive emissions, its 

role in finding the leaks, repairing the leaks, and recording the results. 

The program becomes mature when the data is analyzed and used to modify the 

design of the unit and the selection of components which allow operation at 

lower fugitive emissions levels. 

The key that unlocks the program is the inspection or monitoring 

activity. In an operation which must rely on component maintenance to achieve 

low fugitive emissions levels, a successful monitoring or inspection program 

will be needed to direct the maintenance activity, and ultimately to focus the 

design changes. In addition, the monitoring activity should be designed to 

enhance the awareness of the operations staff to fugitive emissions from 

equipment leaks. Therefore, to be effective, the monitoring program must 

concentrate on the components posing the greatest potential to leak, rather 

than being dispersed among all the components in the process unit. Similarly, 

the maintenance activity should be directed to those leaks posing the greatest 

severity. 

To develop a Total Quality Control (TQC) approach to a fugitive 

emissions regulatory program which strives for continuous improvement (5), it 

will be important to understand the role of monitoring or inspection, and the 

general concept of equipment reliability as they relate to fugitive emissions. 

Monitoring Function 

It is generally acknowledged that inspections are inherently 

wasteful. Preferred would be a program to design out the leakage defect, or 

assure that it is not introduced into the process through fool proofing of the 

maintenance and installation operations. However, according to Shigeo Shingo 

(6) who introduced the "Poka Yoke" or "foolproofing" concepts for quality 

programs in Operations units, source inspections are a necessary aspect of a 

program striving for a zero defect operation. Shingo has proposed three 

different types of inspections, depending upon their purpose. These are: 

o Judgement Inspections -- to discover defects 

Focus on quantifying defects 

o Informative Inspections -- that reduce defects 

Focus on classifying and repairing defects 

o Source Inspections -- that eliminate defects 

Focus on determining cause 

If inspections only occur as part of a regulatory audit, they will 

generally fit the first category: to discover the defects (leakage) from the 

unit. Such an inspection might be used to generate a SARA 313 estimate for 

the unit, or check if the components in the unit have been appropriately 

classified. The purpose of the Judgement Inspection is simply to find the 
P.41 

leaking component. By comparison, the purpose of the Informative Inspection 

is to also transmit information about the general distribution of defects and 

leaks in the operation back to the operation staff which then takes action to 

eliminate the leaks. If records are maintained, trends studies and improvements initiated which result in the elimination of leakage, then the program 

would fit the final category. A Source inspection would be described as an 

inspection method which rather than stimulating feedback and action in 

response to leaks is based on the idea of discovering errors or conditions 

that give rise to leaks, and, by performing feedback and action at the defect 

stage, keep those defects from turning into leaks, or allow them to be quickly 

detected. The key to a successful program is a policy that resides in the 

absolute need to control the operation such that once the potential for a leak 

is detected, it is prevented from turning into a severe occurrence. 

The role that these different monitoring functions can play in a 

regulatory program for the control of fugitive emissions can be better 

understood from a general review of the concept of equipment reliability. 

Component Reliability 

The failure rate for most components follows the curve shown in 

Figure 2 which is called the life characteristic curve, the failure rate 

curve, or more commonly the "bathtub" curve (7). Here there are three types 

of failures, called by some, quality failures, stress-related failures, and 

wearout failures. The sum total of these failures gives the overall failure 

rate for a population of components (percentage of components failing per unit 

time). The "bathtub" curve will usually consist of three distinct regions, 

generally dominated by one of these failure mechanisms. Understanding each of 

these regions is important for developing an effective control program. 

Decreasing Failure Rate Region (Quality Failures) 

Region I is typically the portion of the curve that has the largest 

percent contribution from manufacturing unreliability. The region is also 

called the decreasing failure rate region, or the "break-in" region. This 

region of the curve is where most production and warranty failures occur, and 

is often influenced by failures caused by mishandling or improper installation. Some of the causes of failures during the break-in period are 

summarized in Table 1. 

By inspection it can been seen that a product will experience 

break-in failures because: 

1. There are no well-defined manufacturing processes and 

installation procedures that will assure low fugitive 

emissions. 

2. There is not a system in place to enforce conformance to 

procedures that do exist. 

3. There is not a process to detect and eliminate the causes 

of these failures. 
P.42 

In general, this break-in portion of the curve represents the early 

failure of substandard equipment, which may be due to latent material defects, 

poor assembly methods, and poor quality control. Often, an inspection program 

of components after delivery, and a short period of in-plant leak testing can 

be used to eliminate these early failures from the population. Similarly, 

screening of the entire population of components for leakage would be most 

useful when the population is operating in the Region I portion of the bathtub 

curve [first few quarters for a new unit (i.e., NSPS), or after instal1ation 

of a new component]. 

Constant Failure Rate Region (Useful Life Region) 

The flat middle portion of the failure rate curve represents the 

design failure rate for the specific product as present during its useful life 

in the operating unit. This region has also been called the Constant Failure 

Rate Region which implies that during this useful-life portion, representing 

the normal operating period, the failure rate is relatively constant. But, it 

might be decreased by redesign or restricting usage. It has been suggested 

that Region II will include nonrandom as well as random failures. One example 

of a manufacturing-caused nonrandom failure deals with use of materials which 

will wear with use, i.e., whose critical dimensions do not conform to the 

necessary specification. Under some conditions, these could be a valve stem, 

or a bellows seal. Also included might be the recurrent failure of a repaired 

leak. 

Table 2 represents some of the causes of unreliability found in 

Region II. As can be noted, the relative contribution of problems which are 

the responsibility of the design process far outweight those which are 

manufacturing or installation controlled. A key assumption that can be used 

in a fugitive emissions control program is that by the time the components 

have been in operation long enough to be within its "useful life" period, 

those that have an inherent potential for ultimately becoming a leaker will 

already be giving some indication of leakage (i.e., above some deminimus 

screening value). 

Increasing Failure Rate Region (Wearout Failures) 

Finally, as products age, they reach a wearout phase characterized by 

an increasing failure rate (Region III). The Increasing Failure Rate or 

"Wearout" region is caused by failure mechanisms which slowly change the 

component in an irreversible way, such as corrosion, mineral deposits, 

friction, fatigue, or chemical reaction. Generally, materials selection and 

tolerance of the design for the use determine the useful life of the 

component. Yet, from a more pragmatic viewpoint, if manufacturing defects 

were present, they will show up before the end of design life is reached. 

Table 3 illustrates some of the causes of failures during the wearout 

phase. Again, many of the categories are still a function of the design. 

This holds true whether one is talking about systems, equipment, components, 

or devices. A key term first introduced in explaining the Region III wearout 

failures (although implied in Region II pattern failures) is preventive 

maintenance. Preventive maintenance did not appear to play a role in Region I 
P.43 

or Region II failures, but would ultimately affect the Wearout Failures. If 

an impending failure were properly diagnosed, the component, or parts of the 

component would have been replaced prior to final failure. 

Approach to Conceptual Regulatory Program 

Using quality and reliability principles, the fundamental basis of 

this fugitive emissions control program lies in the assumption that a 

component which has been in operation through a break-in period, and has no 

indication of a defect (below the deminimus screening value) will be 

Acceptable, and should have a low probability of leaking during the near 

future. Whereas, a component which has some indication of leakage or defect 

(screening value above this deminimus value) will be Questionable, and 

should have a higher probability of leaking at greater levels in the future. 

Monitoring of the entire population for defects and leaks would be most 

effective when the population of components is present in the early "break-in" 

period of operation, or the later "wear-out" period. During or following the 

initial break-in period of monitoring, it would be appropriate to continue to 

monitor the remaining questionable components on a regular schedule, and to 

monitor the acceptable components at some reduced "maintenance" level. A unit 

with a questionable component will have the incentive to repair or replace it 

so as to remove it from the regular monitoring list. Continuous improvement 

progress can be readily observed from the number of "leakers" in the unit, and 

by how many components transfer from the questionable to acceptable list. 

An effective fugitive emissions detection and repair program can be 

developed from a correct utilization of the three types of inspection, and an 

adequate understanding of the life-cycle characteristic curve. All three of 

the inspection types can be included in the program (see Figure 3). An 

initial "informative" screening of the components in the unit can be used to 

divide the components into the two categories: those which are Acceptable, 

with screening values below the deminimus (e.g., < 50 ppm), and those which 

are Questionable, with screening values above this deminimum (e.g.,>50 

ppm). A long-term program of continuous improvement will focus the 

Monitoring/Repair action towards the questionable components depending upon 

their screening value. All questionable components will be "tagged," and the 

"sources" monitored during all future monitoring cycles (quarterly) as long as 

the screening value remains questionable. These questionable components 

would have the greatest likelihood of leaking and should provide the bulk of 

the Unacceptable components or "leakers" during each screening cycle. If 

the amount of "Leaking" or Unacceptable components detected during the "Source 

Inspection" exceeds the tolerated limit, then the screening cycle for the 

"Source Inspection" will be reduced from (from quarterly to monthly). In 

addition, insights developed from the "source inspection" focused on these 

questionable components may allow the units to find out additional information 

on the defects and causes of eventual leakage as well as maintain an awareness 

of these potential leaking sources in the operations staff. 

Acceptable components will also be monitored, but at some greatly 

reduced schedule, as in a judgement inspection. The schedule and selection 

of acceptable components to be monitored will be statistically determined 

(perhaps 5% per quarter), such that any emerging trends will be spotted (e.g., 

a whole population of valves on a certain stream that begin to wear out). 
P.44 

Components will be reclassified based upon their screening values in this 

inspection and the Unacceptable components repaired. If the amount of 

leaking components detected during the judgement inspection exceeds the 

tolerated limit, the screening cycle for judgement inspection will be reduced 

(from quarterly to monthly). If three such exceedances occur, then the entire 

population of acceptable components should be rescreened, and the population 

reclassified. 

Overall, the informative screening would be used to initially 

classify the components in the unit, the source monitoring would be focused 

on the questionable components to find out additional information on the 

defects and causes of eventual leakage, and the judgement monitoring would 

be directed to the acceptable components to determine if the population 

distribution changes through some undetected defect, a process upset, or as 

some of the components begin to wear out. 

If and when the leak definition changes from the present 10,000 ppm, 

the definition of an Unacceptable component can change to correspond to the 

new leak definition. In addition, the information gathered in the Source 

Inspection monitoring should allow a rapid transition to the new lower leak 

definition. 

CONCLUSION 

In conclusion, this Total Quality Control Approach is being presented 

as an "Equivilent" alternative to the existing fugitive emissions regulation 

and the other approaches presently being discussed by this Regulatory 

Negotiation Committee. While the monitoring requirement in this program could 

be greatly reduced over that in some of the present proposals, such monitoring 

will be reduced only to the extent that the unit is shown to have a decreasing 

number of potentially leaking components. The monitoring that is continued 

will be focused on components with the greatest potential to leak, but also 

includes a statistical sampling of other components. The results of the 

focused monitoring can be used by the process unit operating staff to strive 

for continuous reductions in fugitive emission levels, and by regulatory 

agencies to audit emissions levels from a facility. We recommend that the 

"equiviiency" portion of the proposed regulation be made flexible enough to 

include alternate approaches such as this one. 
P.45 

References 

1. Berglund, R. L., J. A. Mullins, L. S. Parrett, R. R. Romano, and J. L. 

Randail, "Equipment Leaks: Results of Industrywide Studies of 1,3 

Butadiene, Ethylene Oxide, and Phosgene Production Facilities," paper 

#89-120.4, presented at the 82nd Annual Meeting of the Air and Waste 

Management Association, June 30, 1989, 

2. Berglund, R. L., D. A. Wood, and T. J. covin, "Fugitive Emissions from the 

Acrolein Production Industry," paper presented at the AWMA International 

Specialty Conference: SARA Title III, Section 313, Industry Experience in 

Estimating Chemical Releases, April 6, 1989. 

3. Radian Corporation, "Fugitive Emissions from the Phosgene Production 

Industry: a Field Study," Final Report, June 1989. 

4. Berglund, R. L., J. A. Mullins, L. S. Parrett, and R. R. Romano, "Fugitive 

Emissions from Equipment Leaks: Results of Industrywide Studies in the 

Butadiene, Ethylene Oxide, and Phosgene Production Industries." Paper 

presented at the 1989 Summer National AIChE meeting, August 21, 1989. 

5. Feigenbaum, A. V. Total Quality Control, McGraw Hill, New York, 1983. 

6. Shigeo, Shingo, Zero Quality Control: Source Inspection and the Poka-yoke 

System, Productivity Press, Cambridge, MA, 198TT. 

7. Elkins, D. "Reliability in Production," Chapter 7 in Handbook of 

Reliability Engineering and Management, ed. W. G. Ireson and C. F. Coombs, 

Jr., McGraw Hill, Inc., flew York, 1988. 

3414m 
10.0 

8.0 

6.0 

Average 

Leak Rate 

% 4.0 EPA Study (24 Plants) 

Butadiene Industry (13 Plants) 

Ethylene Oxide Industry (12 Plants) 

Acrolein Industry (2 Plants) 

Phosgene Industry (13 Plants) 

Flanges Purftps Valv©9 Valves 

(Liquid Service) (Gas Service) 

Figure 1: A Comparison of Leak Frequencies for Critical Components 

In Acrolein, Butadiene, Ethylene Oxide and Phosgene industries 

Relative to the Original! EPA Studies 
P.47 

-NEWEQUIPMENT 

LEAKAGE 

t 

z 

CO 

< 

UJ 

QC 

O 

BREAK-IN 

PERIOD 

NORMAL 

OPERATING 

PERIOD 

WEAROUT 

PERIOD 

TIME 

FIGURE 2: Typical Life Characteristic Curve 

For a Population of Components 

(The 'Bathtub' Curve) 
P.48 

"JUDGEMENT 

INSPECTION" 

ACCEPTABLE 

SCREEN ALL 

COMPONENTS 

CLASSIFY 

"INFORMATIVE 

INSPECTION" 

"SOURCE 

INSPECTION" 

QUESTIONABLE 

STATISTICAL 

SCREENING 

100% 

SCREENING 

- Compliance 

- Random Leaks 

- Upset 

- Wearout 

Problem Areas 

Trends 

Causes 

Indicators 

Figure 3: Three Types of "Inspection"Activities In A Fugitive 

Emissions Regulation And Control Program. 
FIIGURE 4: A Total Quality Approach To Fugitive Emissions Regulation And Control 

"Judgement" 

Inspection 

UA>XA%4= 

=» 

Initial Leak 

Detection & Repair 

Audit: Obtain Screening Data 

'Informative" Inspection 

Regulatory Program 

,«*=>> Develop Emission Estimate 

* ^ Before & After Repairs 

USE.ffllfl||ilifM||ulf||§| 

EPA: Curves or Factors r,v*M 

industry.:SC^^e^"or.;-Pactors 

Internal Industry Program 

*» 

U A > X A % < = 

3 Times 

Rescreen 

5% Of 

Components ~^m~ 

"Source" 

Inspection 

=£> 

Rescreen 5% 

Of Components 

Monthly 3~r^ 

Rescreen All 

Acceptable 

Components 

"F 

•ifc-

• * > 

Questionable 

>50ppm 

Unacceptable 

**10,000ppm 

REPAIR 

Rescreen 

100% Of H > W U Q >X Q% 

Components 

QUARTERLY 

MONITORING 

MONTHLY 

MONITORING 
P.50 

Table 1: Break-In (Region I) Failure Causes 

1. Inadequate test specifications—components or engineering 

2. Inadequate Quality control 

3. Inadequate manufacturing processes or tooling—unstable 

4. Inadequate Materials 

5. Improper handling 

.6. Marginal components 

7. Overstressed components 

8. Improper setup or installation' 

9. Improper use procedures 

10. Inadequate understanding of installation environment 

11. Inadequate training 

12. Incomplete final test 

13. Subsystem interaction 

Table 2 'Useful Life' (Region II) Failures 

1. Insufficient design margins 

2. Misappl ication--overstress 

3. Use in wrong environment 

4. Inadequate design margins 

5. Cause 'unknown' factors 

6. Predictable failure levels for design 

7. Inherent manufacturing leakage rate—sampling errors. 

Table 3: Wearout {Region III) Failures 

1. Scratching 

2. Material wear, corrosion, friction 

3. Aging 

4. Misalignment 

5. Loose hardware 

6. Inadequate or improper preventive maintenance 

7. Assembly interference fits 

8. Incipient stresses 

NOTE: The above tables, and many of the concepts included in the reliability 

section of this analysis, have been adapted from the Handbook of 

Reliability Engineering and Management, edited by W. Grant Ireson, and 

Clyde F. Coombs, Jr., 1988. 

3375m 
P.51 

ATTACHMENT 7 

^^f=LsnfT- ClUR£e7\JT~ 

Monitoring Plan Evaluation 

D. Berengut 

J. L. Hess 

T. A. Kittleman 

January 17,1990 
P.52 

Monitoring Plans 

Quarterly Base 

Monthly Base 

Reference: Minutes of December 6-7 Meeting, January 2,1990 
P.53 

Quarterly Base Plan (Q) 

1 

Insj 

Bad 

>ectio 

ction 

Monthly 

Inspection 

t 

1 Bad 

Inspection 

1 

Quarterly 

Inspection 

n 

2 Consecutive 

Good Inspections 

2 Consecutive 

Qsmsi Inspections 

Semianuual 

Inspection 

) 

2 Consecutive 

Good Inspections 

Annual 

mspe CUUI1 
P.54 

Good Performance 

GOOD Less than or equal 

the allowable percent 

leakers 

EXCELLENT Less than or equal 

one-half the allowable 

percent leakers 

BAD Greater than the 

allowable percent leakers 
P.55 

Monthly Base Plan (M) 

1 Bad 

Inspection 

2 Consecutive 

Good Inspections 

1 Bad 

Inspection 

1 Bad 

Inspection 

l£gojL 

but not 

Excellent 

Inspection 

Quarterly 

Inspection 

2 Consecutive 

Gj2Qd. Inspections 

Semiannual 

Inspection 

1 

2 Consecutive 

Excellent Inspections 

Annual 

Inspection 

2 Consecutive 

Excellent Inspections 
P.56 

The likelihood of being at a 

monitoring frequency can be 

determined for both plans. 

This likelihood will be 

different for different plants 

depending on how a plant 

performs over time. 
In other words, characteristics depend 

on the chance of a plant exhibiting 

good performance over time. 

We looked at two characteristics of 

monitoring plans 

• long run chance of falling 

under a given inspection 

frequency (eg. monthly, 

quarterly, etc.) 

• Average number of inspections 

per year 
P.58 

Interpretation of a "Plant Exhibiting 

Good Performance Over Time" 

Time Percent Leakers 

1.7% 

2.1% 

0.1% 

2.3% 
P.59 

Monitoring Plan Characteristics 

Chance of Being at 

this Monitoring Frequency: 

Chance of: Semi. 

Plan £ojul Excellent Monthly Quarterly Annual Annual 

M 0.50 0.25 0.75 0.19 0.05 0.02 

Q 0.50 — 0.69 0.23 0.06 0.02 

M 0.70 0.35 0.51 0.25 0.18 0.06 

Q 0.70 — 0.35 0.33 0.16 0.16 

M 0.90 0.45 0.19 0.15 0.49 0.16 

Q 0.90 — 0.04 0.18 0.15 0.63 

M 0.99 0.50 0.02 0.02 0.72 0.24 

M 0.99 0.98 0.02 0.02 0.02 0.94 

Q 0.99 — 0.00 0.02 0.02 0.96 
P.60 

Monitoring Plan Characteristics 

Chance of: Average Number of 

Plan Good Excellent Inspections Per Year 

M 0.50 0.25 6.7 

Q 0.50 — 6.1 

M 

Q 

M 

Q 

M 

M 

0.70 

0.70 

0.90 

0.90 

0.99 

0.99 

0.35 

. . . 

0.45 

• *•*• 

0.50 

0.98 

3.9 

2.9 

2.2 

1.3 

1.6 

1.0 

Q 0.99 - 1.0 
P.61 

Conclusions 

Monthly Base Plan and Quarterly Base Plan 

are not different for those plants least able to 

meet the good performance criteria 

For plants able to easily meet the good 

performance criteria, the Monthly Base 

Plan can require a much higher monitoring 

burden (1.5 times) than the Quarterly Base 

Plan 

There is a greater incentive for improving 

performance with the Quarterly Base Plan 
\) t I <ff f 

MThCUMEMTB *' 

UNITED STATES ENVIRONMENTAL PROTECTION AGENCY 

Office of Aii Quality Planning and Standards 

Research Triangle Park, North Carolina 27711 

December 22, 1989 

Harvel M. Rogers, Jr. 

Air Pollution Control District of Jefferson Co. 

Suite 300 

914 East Broadway 

Louisville, KY 40204 

Dear Mr. Rogers: 

Enclosed please find the analysis of the ethylene oxide and butadiene screening data you requested at the Equipment Leak Regulatory Negotiations 

meeting on December 6-7, 1989. This analysis looks at the percent of 

screening values by component type which are greater than leak definitions 

at 10, 25, 50, 75, 100, 250, 500, 750 and 1000 ppm. The analysis uses the 

screening value data for the twelve butadiene and ten ethylene oxide plants 

transmitted previously. 

Column titles may need a little explanation. The combination of "study" 

and "epa_no" represents a plant (or unit) identifier. Where listed "phase" 

equals 1 for equipment in gas service and 2 for liquid service. Phase is not 

listed for flanges and pumps. The last column is the percent leakers at 

different leak definitions, such that "pleak_10" is percent'leakers at 10 ppm 

and "pleak-500" is percent leakers at 500 ppm. Within each equipment 

type and leak definition category, the plants are listed in order of ascending 

percent leakers. 

I am not currently planmng to create bar charts of these data for the next 

meeting. Please let me know if you feel that bar charts are necessary. 

Sincerely, 

Robert Pahel-Short, MD-13 

Standards Development Branch 

Emissions Standards Division 
_R£3_ 

Enclosure: 

cc: Bob Ajax 

Alfred W. Bickum 

Gus Von Bodungen 

Bruce V. Bowers 

Linda Curran 

Deborah Dalton 

David Doniger 

David Dunn 

Thomas A. Kittleman 

Karen Fidler 

Anupom Ganguli 

Philip J. Harter (w/o enclosure) 

Allen Hershkowitz 

Jack Kace 

Bob Majewski 

Les Montgomery 
study 

eo 

eo 

eo 

bd 

bd 

bd 

eo 

eo 

eo 

bd 

eo 

eo 

bd 

bd 

bd 

bd 

eo 

bd 

bd 

eo 

bd 

bd 

study 

eo 

eo 

eo 

eo 

eo 

eo 

eo 

bd 

bd 

eo 

bd 

bd 

eo 

bd 

bd 

bd 

bd 

bd 

bd 

eo 

bd 

bd 

epa_no equip 

7 valves 

5 valves 

10 valves 

2 valves 

9 valves 

3 valves 

3 valves 

2 valves 

1 valves 

4 valves 

6 valves 

8 valves 

11 valves 

12 valves 

5 valves 

6 valves 

9 valves 

1 valves 

10 valves 

4 valves 

8 valves 

7 valves 

epa_no equip 

10 valves 

5 valves 

9 valves 

3 valves 

2 valves 

8 valves 

7 valves 

9 valves 

2 valves 

6 valves 

3 valves 

12 valves 

1 valves 

11 valves 

4 valves 

1 valves 

5 valves 

10 valves 

8 valves 

4 valves 

7 valves 

6 valves 

phase 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

l 

1 

1 

1 

1 

1 

phase 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

pleak 10 

0.00 

0.67 

1.46 

1.77 

2.54 

3.95 

4.46 

5.38 

5.99 

6.82 

8.18 

8.25 

14.29 

17.59 

19.23 

20.79 

23.89 

32.51 

33.33 

35.51 

49.19 

83.33 

pleaJc 10 

0.00 

0.52 

1.86 

2.44 

3.03 

3.39 

3.60 

3.73 

3.88 

4.19 

7.39 

9.02 

9.52 

15.29 

17.17 

18.27 

24.12 

28.68 

43.89 

58.81 

66.43 

97.24 
P.65 

study epa_no equip pleak_10 

eo 7 flange 0.00 

bd 9 flange 0.10 

eo 10 flange 1.37 

eo 2 flange 1.71 

eo 3 flange 3.17 

bd 12 flange 3.87 

bd ll flange 4,08 

eo 8 flange 4.43 

eo 1 flange 5.65 

bd 10 flange 8.23 

bd 1 flange 10.00 

bd 5 flange 10.04 

eo 6 flange 10.27 

eo 9 flange 11.03 

bd 3 flange 14.00 

bd 4 flange 14.29 

bd 7 flange 24.82 

bd 8 flange 40.00 

eo 4 flange 50.84 

bd 2 flange 86.67 

study epano equip pleak_10 

eo 5 pumps 0.00 

eo 7 pumps 6.67 

bd 4 pumps 8.57 

bd 9 pumps 10.31 

eo 8 pumps 11.76 

eo 2 pumps 12.50 

bd 11 pumps 16.67 

ep 6 pumps 25.00 

bd 12 pumps 25.00 

bd 3 pumps 25.37 

bd 2 pumps 28.00 

bd 1 pumps 37.50 

eo 10 pumps 40.91 

eo 9 pumps 50.00 

eo 3 pumps 63.64 

bd 10 pumps 66.67 

bd 5 pumps 66.67 

eo 1 pumps 68.00 

bd 8 pumps 83.33 

eo 4 pumps 90.91 

bd 6 pumps 100.00 
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P.67 

study epa_no equip pleak_25 

eo 7 flange 0.00 

bd 9 flange 0.10 

eo 10 flange 1.37 

bd 7 flange 1.46 

bd 12 flange 1.66 

eo 2 flange 1.71 

eo 1 flange 2.82 

eo 3 flange 3.17 

bd 11 flange 3.40 

eo 8 flange 3.80 

bd 2 flange 4.67 

bd 5 flange 6.02 

bd 10 flange 6.96 

eo 6 flange 7.53 

bd 3 flange 9.33 

bd 1 flange 10.00 

eo 9 flange 10.54 

bd 4 flange 11.43 

bd 8 flange 12.59 

eo 4 flange 31.60 

study epa_no equip pleak_25 

eo 5 pumps 0.00 

bd 4 pumps 2.86 

eo 7 pumps 6.67 

bd 9 pumps 10.31 

eo 8 pumps 11.76 

eo 2 pumps 12.50 

bd 11 pumps 16.67 

eo 6 pumps 20.83 

bd 12 pumps 25.00 

bd 3 pumps 25.37 

bd 2 pumps 28.00 

bd 1 pumps 37.50 

eo 10 pumps 40.91 

eo 3 pumps 45.45 

eo 9 pumps 50.00 

bd 5 pumps 50.00 

eo 1 pumps 52.00 

bd 6 pumps 61.11 

bd 10 pumps 66.67 

eo 4 pumps 81.82 

bd 8 pumps 83.33 
P.68 

study epa_no equip phase pleak 50 

eo eo eo bd bd eo eo bd bd eo eo eo bd eo bd eo bd bd bd bd bd bd 

study eo eo eo bd eo eo bd eo eo eo eo bd eo bd bd bd bd bd bd bd bd bd 

7 

5 

10 

2 

9 

3 

1 

3 

4 

2 

8 

6 

6 

4 

5 

9 

11 12 

1 

7 

10 

8 

epa no 10 

5 

3 

2 

1 

9 

7 

8 

2 

6 

7 

9 

4 

12 

3 

4 

5 

1 

11 10 

8 

6 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

equip 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

l 

1 

1 

1 

1 

l 

l 

l 

1 

phase 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

0.00 

0.67 

1.46 

1.77 

2.54 

2.57 

3.24 

3.48 

3.71 

4.62 

5.15 

5.45 

6.10 

6.54 

10.10 

14.29 

14.29 

15.34 

16.26 

16.67 

28.57 

32.97 

pleak 50 

0.00 

0.52 

1.33 

1.38 

1.39 

1.46 

2.10 

2.40 

2.60 

2.86 

2.88 

3.73 

5.95 

6.53 

7.35 

9.13 

11.02 

11.65 

13.35 

26.04 

27.59 

33.17 
P.69 

f 

study eo bd eo bd eo bd eo bd bd eo eo bd bd bd eo eo eo bd bd bd 

study bd eo bd eo bd eo eo bd eo eo bd bd bd bd eo eo eo bd bd eo bd 

epa_no equip 7 flange 9 flange 1 flange 7 flange 

10 flange 

12 flange 2 flange 3 flange 

11 flange 3 flange 8 flange 5 flange 2 flange 

10 flange 6 flange 4 flange 9 flange 4 flange 1 flange 8 flange 

epa_no equip 

10 pumps 5 pumps 4 pumps 7 pumps 9 pumps 8 pumps 2 pumps 

11 pumps 6 pumps 9 pumps 

12 pumps 3 pumps 2 pumps 1 pumps 1 pumps 3 pumps 

10 pumps 6 pumps 5 pumps 4 pumps 8 pumps 

pleak 50 

0.00 

0.10 

0.56 

0.73 

1.37 

1.66 

1.71 

2.67 

2.72 

3.17 

3.80 

3.90 

4.00 

5.70 

6.85 

7.30 

9.07 

10.00 

10.00 

11.11 

pleak 50 

0.00 

0.00 

2.86 

6.67 

10.31 

11.76 

12.50 

16.67 

20.83 

25.00 

25.00 

25.37 

28.00 

37.50 

40.00 

40.91 

40.91 

50.00 

50.00 

54.55 

75.00 
P.70 

study epa_no equip phase pleak_75 

eo eo eo bd eo bd eo bd bd eo eo eo bd eo bd bd eo bd bd bd bd bd 

study eo eo eo eo bd eo bd eo eo eo eo eo bd bd bd bd bd bd bd bd bd bd 

7 

5 

10 

2 

3 

9 

1 

4 

3 

6 

2 

4 

6 

8 

5 

1 

9 

11 

7 

12 10 

8 

epa no 10 

5 

1 

3 

2 

9 

7 

2 

6 

8 

7 

4 

9 

12 

3 

4 

5 

1 

11 

6 

8 

10 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

equip 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

valves 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

l 

1 

1 

1 

l 

1 

1 

phase 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

0.00 

0.67 

1.46 

1.77 

2.40 

2.54 

2.74 

3.23 

3.48 

4.55 

4.62 

4.67 

4.76 

4.90 

8.65 

13.79 

14.29 

14.29 

14.29 

14.66 

28.57 

29.73 

pleak 75 

0.00 

0.52 

0.83 

1.22 

1.38 

1.46 

2.10 

2.16 

2.29 

2.40 

2.45 

3.52 

3.73 

6.26 

7.35 

8.64 

9.98 

10.83 

13.11 

23.25 

25.08 

25.28 
P.71 

study bd eo bd eo bd eo bd eo bd bd bd eo eo eo _ , bd eo bd bd bd eo 

study ep bd eo bd bd eo eo bd eo bd eo bd bd bd eo bd eo eo bd eo bd 

epa_no equip 7 flange 1 flange 1 flange 7 flange 9 flange 

10 flange 

12 flange 2 flange 3 flange 5 flange 

11 flange 3 flange 8 flange 4 flange 2 flange 6 flange 

10 flange 8 flange 4 flange 9 flange 

epa_no equip 7 pumps 

10 pumps 5 pumps 4 pumps 9 pumps 8 pumps 2 pumps 

11 pumps 6 pumps 

12 pumps 9 pumps 3 pumps 2 pumps 1 pumps 1 pumps 6 pumps 

10 pumps 3 pumps 5 pumps 4 pumps 8 pumps 

pleak 75 

0.00 

0.00 

0.00 

0.00 

0.10 

1.37 

1.66 

1.71 

2.67 

2.72 

2.72 

3.17 

3.80 

3.93 

4.00 

5.48 

5.70 

8.15 

8.57 

9.07 

pleak 75 

0.00 

0.00 

0.00 

2.86 

10.31 

11.76 

12.50 

16.67 

20.83 

25.00 

25.00 

25.37 

28.00 

31.25 

36.00 

38.89 

40.91 

40.91 

50.00 

54.55 

66.67 

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P.75 

bd bd 

study epa_no equip pieak_250 

®?

 7 flang

e 0.00 

bd 7 flange o.OO 

Da i flang

e 0.00 

eo 1 flange 0.00 

bd 9 flange 0.10 

bd 12 flange 0.55 

bd 3 flange 0.67 

f?

 2 flang

e 0.85 

bd 5 flange i.

06 

bd 11 flange 1.

36 

eo 1

0 flange 1.37 

eo 4 flang

e 1.5 4 

eo 8 flange 2.53 

bd 10 flange 2.53 

eo 3 flang

e 3.17 

bd 2 flang

e 4.00 

eo 6 flang

e 4 n 

eo 9 flange 6.'62 

8 flange 6.67 

4 flange 7.14 

study epa_no equip pieak_250 

eo 5 pumps 0.00 

-?« 4 pumps 0.00 

od 10 pumps 0.00 

eo 7 pump

s 0.00 

eo 8 pumps 0.00 

eo 2 pumps 0.00 

eo 6 pumps 8.33 

od 12 pumps 10.00 

Od 9 pumps 10.31 

od 11 pumps 16.67 

eo 3 pumps 18.18 

oo 1 pumps 18.75 

eo 1 pumps 20.00 

Od 3 pumps 23.88 

Od 2 pumps 24.00 

eo 9 pumps 25.00 

oa 6 pumps 27.78 

Od 5 pumps 33.33 

eo 4 pumps 36.36 

eo 10 pumps 40.91 

od 8 pumps 58.33 
P.76 

study eo eo eo eo eo bd . bd 

i eo od 

i eo bd bJ , d bd b•i , d eo 

i eo bd bd eo bd bd bj d . 

! 

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e|o ep ep ep eo b. L d 

i 

eo bd b»_ !d » 1- !a bd bd bd bd bd bd bd bd bd 

1 

i 

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epa_no equip 7 valves 5 valves 1 valves 4 valves 

10 valves 4 valves 6 valves 3 valves 2 valves 8 valves 7 valves 9 valves 3 valves 5 valves 2 valves 6 valves 1 valves 

12 valves 9 valves 

11 valves 

10 valves 8 valves 

phase 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

epa_no equip phase 

10 valves 5 valves 9 valves 8 valves 2 valves 1 valves 3 valves 6 valves -1 valves 

'-. valves 7 valves 7 valves 

12 valves 9 valves 5 valves 3 valves 4 valves 1 valves 6 valves 

11 valves 

10 valves 8 valves 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

pleak_500 

0.00 

0.00 

0.25 

0.93 1. 46 

1.56 

1.65 

1.72 

1.77 

2.32 

2.38 

2.54 

2.73 

2.88 

3.08 

3.64 

8.37 

8.45 

10.34 

14.29 

19.05 

19.46 

pleak_500 

0.00 

0.26 

0.40 

0.42 

0.43 

0.46 

0.66 

0.76 

1.10 

1.13 

1.30 

2.10 

2.65 

3.73 

3.74 

5.49 

5.80 

7.14 

7.80 

8.01 

15.47 

15.83 
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epa_no equip 1 flange 7 flange 1 flange 7 flange 9 flange 

12 flange 4 flange 3 flange 

11 flange 5 flange 2 flange 

10 flange 6 flange 

10 flange 8 flange 2 flange 3 flange 9 flange 4 flange 8 flange 

epa_no equip 8 pumps 5 pumps 4 pumps 2 pumps 7 pumps 

10 pumps 6 pumps 1 pumps 4 pumps 

12 pumps 9 pumps 1 pumps 3 pumps 5 pumps 6 pumps 

11 pumps 3 pumps 2 pumps 9 pumps 

10 pumps 8 pumps 

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ATTACHMENT 9 

Study EPA No. Equipment phase pleakJO 25 50 75 100 250 500 1 i'l Of' 

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17.17 

18.27 

24.12 

28.63 

43.39 

53.31 

66.43 

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3.69 

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35.63 

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39.87 

15.33 

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2.54 

3.43 

2.57 

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3.71 

5.45 

5.15 

14.29 

15.34 

10.10 

6.10 

14.29 

16.26 • 

23.57 

6.54 

32.97 

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0.00 

0.52 

1.46 

1.33 

2.60 

2.40 

2.10 

3.73 

1.33 

2.36 

7.35 

6.53 

1.39 

13.35 

9.13 

11.65 

11,02 

26.04 

27.59 

5.95 

2.88 

33.17 

0.00 

0.67 

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2.54 

3.43 

2.40 

4.62 

2.74 

3.23 

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14.29 

14.66 

3.65 

4.76 

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1.33 

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3.64 

10.33 

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25.28 

25.08 

3.52 

2.10 

23.25 

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1,46 

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2.54 

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4.62 

2,24 

2,75 

4.55 

4.33 

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12.07 

6.73 

4.34 

11.32 

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25.40 

3.74 

29.19 

14.29 

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0.66 

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2.45 

3.73 

1.25 

2.29 

6.94 

4.46 

0.74 

11.41 

7.93 

10.30 

3.32 

20.75 

23.67 

2.64 

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1.46 

1.77 

2,54 

3.20 

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2.39 

4.55 

3.09 

14.29 

10.34 

4.33 

2.17 

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0.93 

20.00 

2.38 

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0.76 

6.62 

3.37 

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0.00 

0.10 

1.37 

1.71 

3.17 

3.37 

4.03 

4.43 

5.65 

3.23 

10.00 

10.04 

10.27 

11.03 

14,00 

14.29 

24.32 

40.00 

50.34 

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25 

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3.30 

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0.63 

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0.94 

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1.37 

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4.66 

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1.37 

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6.67 

3.57 

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11.76 

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25.00 

25.00 

25.37 

28.00 

37.50 

40.91 

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63.64 

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40.91 

25.00 

13.18 

0,00 

16.67 

12.00 

50.00 

27.27 

16.67 

0.00 

0.00 

10.31 

0.00 

0.00 

16.67 

4.17 

10,00 

20,90 

24.00 

12.50 

40.91 

25.00 

13.64 

0.00 

16.67 

3.00 

50.00 

9.09 

16.67 

o.yo 

o.oo 

o.oo 

10.31 

0.00 

0.00 

16.67 

4.17 

10.00 

20.90 

20.00 

12.50 

40,91 

25,00 

9.09 

0,00 

16.67 

3.00 

•41.67 

9.09 

16.67 
P.84 

ATTOOHIMEINnr 1© 

UNITED STATES ENVIRONMENTAL PROTECTION AGENCY 

WASHINGTON, O.C. 20480 

rC*f 

OPFICE OF 

POLICY, PLANNING AND EVALUATION 

JUL I 

MEMORANDUM 

SUBJECT: Sequential Sampling Plan for the Wood Stove Standard 

FROM: 

TO: 

William P. Smith, Statistician 

Statistical Policy Branch (PM-223) 

John Rasnic, Chief 

Compliance Monitoring Branch (EN-341) 

The purpose of this memorandum is to transmit my work on a 

prcpcsed sampling plan for the Selective Enforcement Audit (SZA) 

cro cram o: :he Wood Stove Standard. 

The sampling plan is based on the. theory of sequential 

analysis. This method of statistical inference differs from the 

classical fixed sample size test procedures in that the number of 

observations necessary to make a decision is not predetermined. 

The decision to terminate or continue" testing is made at. each 

step of the process and depends on the outcome of the previous 

steps. 

The appeal of sequential testing for SEA is that on average 

the number of stoves that must be inspected at a facility to make 

a determination of compliance is appreciably less than that 

required for the most efficient fixed sample procedure. Testing 

will terminate as soon as there are sufficient data to support a 

conclusion. 

The sequential sampling theory presented here is based on 

the work of Abraham Wald. The source of the following discussion 

may be found in Abraham Wald, Sequential Analysis. John Wiley & 

Sons, 1947. 

The sequQntial sampling plans will b@ USQC£ during SEAs as 

follows; 

A series e£ stev©§ ar® drawn randomly without replacement 

froa th® total populatien ©f gtevos at thQ faeility and then 
jt®st®d. in tho.ooguoncQ in whieh thoy woro ooloetodo A "stage" of 

j the. proeeduro io dofinod ao tho eeaplotien e£ touting of on© 

jadddtienal ot©vo. H running eeunt, a, ©f thQ number ef observed 

defective \mito (io®., thes© net in eomplianee with each 

appropriato osiooien gtandard) is aaintainod. At ©ach stag®, 

this count n ean bo compared with tho computed acceptance and 

rejection numbers for that stage. If a de@§ net exceed the 

acceptance nuaber the audit is passed. If a is net less than the 

rejection nuaber, the audit is failed. If neither determination 

can be made, testing will normally continu®. 

j In' general, th© purpose of a Selective Enforcement Audit is 

£o deteraine whether P, the proportion of a population of stoves 

hot in compliance with the standard is greater than some 

acceptable quality level, PO. What is needed for a sequential 

t:est is a decision rule for which; 

i 

i 1. The risk of failing the procedur© when the true failure 

rate, P, is less than or equal to PO does not exceed alpha, the 

probability of making a type I error, and 

i 2. The chance of passing the procedure when the true failure 

rate is greater than some Pl (Pl > PO) does not exceed beta, the 

probability of making a type II error. 

The information that this test will provide will form the 

statistical basis for deciding whether the production facility is 

iiji compliance with the standard, or net. A facility is in 

compliance if zhe proportion, P, of defective wood stoves (stoves 

triat would fail to meet the conditions of the standard) in the 

production population does not exceed PO. A facility could be 

definitely classified as in noncompliance if the proportion 

defective was greater than some unacceptably high value, Pl. The 

statistical test will allow one to distinguish between these two 

states within acceptable error constraints. In general the 

closer the states ar® together the aore difficult they are to 

distinguish, i.e., it would be easier and require less testing to 

distinguish a compliance rate of 0.05 from 0.50 than froa 0.20, 

but you have less contrel of th© type II error rate within the 

grey area between tho tw© alternatives. This trade off is 

evident in the discussion of exhibits and figures that follows. 

i 

Discussion of JSmsaogAeal output 

I 

I Th© attaeh®d output consists of 16 exhibits and 16 

accompanying figures. These exhibits consist of a selection of 

tests that I hav© investigated; they ar® by no means exhaustive, 

but they were selected froa a bread spectrum of conditions that 

will likely exist in th® real world. Ideally ©no weuld wish te 

optiiaiz© limited resources te make a d®eisien with ainisua 

©rrer. Soa® ef tho eritieal variables that drivo tho £©s*a ef the 

i 

2 
RL8S 

doeision proeoduro ar©; 

1. Sho eeagliane® ratd PO 

2. Tho allowable error ratoo? 

3. Tho aasfisus permissible sample size; and 

4. The Population ©igo. 

If th© compliance rat©, PO, is say P0°0.05 then you would expect 

a facility in compliance to hav® at most 5% of th© stoves in 

production population to be defective,er te put it another way, 

the probability of a stove selected randomly froa this population 

being defective is about 1 in 20. Th® decision procedure aay 

wrongfully declare a facility in noncoapliance er wrongfully 

declare it in coapliance. The specification of th® sizes (alpha 

and beta) of these two typ® of errors is necessary to deteraine a 

test. The maximum cut-off level for saapling is usually 

specified because although the sequential test will terminate 

with certainty, it may require infinit© resources before it.does 

so. The specification of one other parameter, Pl, is necessary 

to completely deteraine the test; think of this parameter as 

needed to "peg" the power curve of the test — the power curve 

will go through the two points (PO,alpha) and (Pl, 1-beta) . The 

population size affects the errors and must be considered 

separately, i.e., separate tests are used for each range of 

production population. 

Exhibits. 1-4 are for P0=0.05, Pl=0.50, alpha=0.05, beta=0.1, 

maximum inspections^lO, and Pop=10*0,2 00', 3 00, 400 cr 

more. 

Exhibits 5-8 are for P0=0.05, Pl=0.20, alpha=0. 05', beta=0.1, 

maximum inspectiohs«25, and Pop=lC0,200,300, 400 o r 

more. 

Exhibits 9=12 are for PO-0.05, Pl-0.20, alpha=0.1, 

beta=0.1, maximum inspections=2 5, and Pop=100,200,300, 

4 00 or more. 

Exhibits 13-16 are for P0°0.05, Pl-0.30, alpha°0.1, 

beta-^0.1, maximum inspections=20, and Pop*=>100,200,3 00, 

400 or aere. 

Each osshibit contains twe tables: Test Procedure and Test 

Characterioties s 

The "Test Procedure" tabl® gives the decision rule at each 

j stage of the test. For example consider the sequential test 

i shown in Exhibit 8. This test procedure indicates that neither 

i decision can be aad© in the first 2 stages.' A paso doeiaion can 

I be aad© if tho first 13 stages all pas© (i.o. ger© failures) . A 

j fail deeisen will bo aado if tho first 3 tosto rooult in failure. 

, In a situation in whieh neither decision has yot boon made, e.g., 
P.87 

numbers (• a ^number of failures is bet^en !h. ^

 sta *e

 22). 

. ^~T **•*•» 1 is betv»«« ft .. ^ « ««fcween the two derH «.*«.. testing nu,t b. p.rforiH ' " ° an d 3 " «*»?. *•<), SaaSi^S 

necessary to make 1 ^_t2?!-

 h® avera*« number of ins S*.. tru e 

labelled "Average sampl/^LT" T *

 i S show * ^ S?*?!^! 

example these two properties a'rl i ,*,* *xaaPle in the exhibit ? 

x» F ^ r e SA and 8B

P

 TM^i^%^£^ curvfs^U 

t-t.y^V^Yi^ SS.^^

 t o

 ^l p you review these 

the audit program.

 t6St S tha t

 /<>« »ay wish to consider fl? 

Attachment 

i 

j 

cc: Doreen Cantor 
P.88 

A SEQUENTIAL SAMPLING PROCEDURE 

FOR THE WOOD STOVE STANDARD 

July'1, 1986 

PREPARED BY 

William P. Saith 

Statistical Policy Branch 

Offic© of Policy, Planning, and Program 

U.S. Envirena®ntal Preteetien 

Evaluation 
General 

The sampling plans proposed fer th© Selective Enforcement 

Audit Program (SEA) of th® Wood Stev© standard are based on the 

theory of sequential analysis. This method' of statistical 

inference differs froa the classical fixed sample size test 

procedures in that the nuaber of observations necessary to aak© a 

decision is not predetermined. The decision to terminate or 

continue testing is made at ©ach step ef th® process and depends 

on the.outcome of the previous steps. 

The appeal of sequential testing for SEA is that on averag© 

the nuaber of stoves that aust be inspected at a facility to make 

a determination of compliance is appreciably less than that 

required for the most efficient fix©d sample procedur©. Testing 

will terminate as soon as there ar© sufficient data to support a 

conclusion. 

The sequential sampling theory presented here is based on 

the work of Abraham Wald. The source of the following discussion 

may be found in Abraham Wald, Sequential Analysis, John Wiley & 

Sons,' 1947. 

The 

follows: 

sequential sampling plans will be used during SEAs as 

A series of stoves are drawn randomly without replacement 

from the total population of stoves at the facility and then 

tested in the sequence in which they were selected. A "stage" of 

the procedure is defined as the completion of testing of, one 

additional stove. A running count, m, of the number of observed 

defective units (i.e., those not in compliance with each 

appropriate emission standard) is maintained. At each stage, 

this count m can be compared with the computed acceptance and 

rejection numbers for that stage. If m does not exceed the 

acceptance nuaber the audit is passed. If m is not less than the 

rejection nuaber, the audit is failed. If neither determination 

\ can be made, testing will normally continue. 

' As an o&aaple of th® application of a sequential sampling 

! plan, coneider the decision rule for an infinite population, 

i (This decision rule appears in th® beginning of th® document and 

, is presented in Exhibit 8) . This test procedure indicates that 

1 neither decision can b® aad® in the first 2 stages. A pass 

1 decision can b© aad© if the first 13 stag©s all pass (i.e. zero 

| failures) . A fail d©eisen will bo made if tho first 3 tosts 

I result in failure. In a situation in whieh noithoj? doeioien hao 

, yet been aado, o.g., 1 failuro at stago If, additi©nal tooting io 

required. In this latter example, a pass doeioien will bo 

2 
P.90 

reached, if tho no3st 3 tooto all paoo (1 Sailuro at stago 22), ©r 

s fail doeioien will bo roaehed if tho nosst 2 te^ts all fail (3 

failuroo at otago 22). Thuo, whonover tho nuaber ©f failures io 

between tho tw© doeisien numbers (o.g., 1 is botween 0 and 3 at 

stage 14), additional testing aust be performed. 

eoaButation of Aeeeptane® aad adoption Nusfengg 

In general, th© purpose of a Selective Enforcement Audit is 

to deterain® wh©ther p, the proportion of a population of stoves 

not in compliance with the standard is greater than some 

acceptable quality level, PO. What is needed for a sequential 

test is a decision rule for which: 

1. Th® risk of failing the preeadur© wh@n th© true failure 

rate, P, is less than or equal te PO does not exceed alpha, the 

probability of making a typ© I error, and 

2. The chance of passing the procedure when the truo failuro 

rate is greater than some Pl (Pl > PO) does not exceed beta, th© 

probability of making a type II error. 

If we consider p(i,n), the probability of observing a given 

number, m, of defective (noncomplying). stoves at the nth 

stage of testing when p = p(i), then 

m n-m 

p(i,n) - C(n,m)p(i) (l-p(i)) 

for an infinite population and C(m,n) is the usual combinatoric 

of m units taken from n units without replacement. 

A sequential probability ratio test to test the failure rate 

of a production process considers the ratio of p(l,n) to p(0,n) 

at each stage of testing. That is, the ratio 

p(l,n)/p(0,n) 

when the populatien is very large (say 400 or more), is the test 

statistic of interest. It should then be noted that if Pl is 

closer to tho true P than PO, then this ratio will be high. Thus 

high ratio values are indicative of a high failure rate. If Po 

is closer t© thr true P, then th© ratio will be low, a low ratio 

indicating a low failur© rat®. 
P.91 

Tho doeXsien t© torminato tooting with a pass er. fail er te 

eentinuo tooting is based upon whethor 

a) I is p(l,n)/p(0,n) 

b) A < p(l,n)/p(0,n) 

c) B < p(l,n)/p(0,n) < 

(pass), 

(fail), or 

(continue testing). 

A and B are chosen to yield th® appropriate values of alpha and 

beta in the following manner: 

Froa a) it can be seen that in a pass situation, 

B*p(0,n) ' _> p(l,n). Thus the probability of observing a passing 

sequence when Pl is true is at aost B tia©s th© probability of 

observing the sequence when PO is true. Since this inequality is 

true- for any passing sequence, it is true over th© totality of 

passing sequences, E. That is, B6P(E|P0) > P(E|P1) where 

P(E|P0) and P(E|P1) are the probabilities of passing under PO and 

Pl, respectively. Now since the test terminates with probability 

one we may state that for passing sequences, P(E|P0) is equal to 

1-alpha, the chance of correctly passing, and P(E|P1) is equal to 

beta, the risk of incorrectly passing. THerefore it is true that 

B(l-alpha) > beta. 

Similarly from b) one can see that in a fail situation 

A*p(0,n) < p(l,n). Thus the probability of observing a failing 

sequence when Pl is true is at least A times the probability of 

observing such a sequence when PO is true. As in the case of the 

pass situation this inequality holds over the totality of failing 

sequences, F. Since the test terminates with probability one we 

have P(F)+P(E)»1, and so A(alpha) < 1-beta. 

Thus a lower bound for B is B'! 

bound for A is A'-""-(l-beta)/alpha. 

•beta/(1-alpha) and an upper 

Replacing A and B with these bounds does alter the values of 

alpha and beta, but 

differences are small. 

for small values of these risks the 

Substituting the bounds for A and B in c) yields 

B« < p(l,n)/p(0,n) < A' 

Taking logs in th© above inequality allows one to state that th® 

sequential probability ratio test will terminate at stage n if 
P.92 

a). a6ln[PlQ0/(P0Ql)] + n^lnfQl/QO] "< ln[B° 3 (pass) 

or 

b) ncin[?lQe/(P0Ql)3 + n ln[Ql/QO] > ln[A'] (fail) 

wher© Q0°1=P0 and Q1°1-=P1-. Coaputing formulas for the 

acceptance, a(n), and rejection, r(n), numbers for stage n are: 

a(n) « (ln[B«] + n ln[Q0/Ql]) / ln[PlQ0/(P0Ql) ] 

and 

r(n) ° (ln[A«] + n ln[Q0/Ql]) / ln[PlQO/(POQl)]. 

I . 

! Noninteger values of a(n) and r(n) ar© replaced by the largest 

J integer less than a(n) and th® smallest integer greater than 

' r(n), respectively. 

i 

i The above theory is applicable. ©ven when observations are 

J dependent, such as in the cas© of sampling from a finite 

| population without replacement. Say that of a production 

i population of size N to be tested, a finite nuaber of units, D, 

i are assuaed to be defective. Testing the hypothesis 

! Ho: D S [PO*N + 0.5] ° DO 

I versus 

! 

| HI: D > [P1*N + 0.5] - Dl 

where [.] represents the greatest integer function, is analygous 

to.the binomial test for infinite populations. The corresponding' 

p(0,n) and p(l,n) for a observed defectives at stage n of this 

test are 

i 

p(0,n) ***» h(a,n,D0,N) and p(l,n) *» h(a,n,Dl,N) 

where h(a,n,D,N) is th® usual hypergeoaetric probability. The 

possible events can be defined at each stage to be: 

Peosiblo laaediate 

fvont Conclusion Decision 

(1) a < n°N-*-D0 D < DO accept Ho 

(2) n-N+D0*i a < n=N->Dl D < Dl reject HI 

(3) n-N+Dl _s a < DO Test reject Ho 

(4) n-N+Dl < a _% Dl D > DO reject Ho 

(5) a > Dl D > Dl reject He 

Case (1) will net ©eeur fer tho truncated fera ©f tho tost that 

will used, i . e., n will bo eenstrained t© ssall valuos typically 
less than 2&- Steves. esso (2) io truo -enly when the number ©f 

observatieno, n, is greater than N°D1, tho maximum nuaber ef nen= 

def©etivo imito ©no could ebservo if at least Dl were defective. 

This iaplioo that n°N-«»Dl is tho ainiaua nuaber ef defective units 

on® weuli ©bsorvo if at least Dl were defective. Thus an 

observed a leso than n°N-$*Dl implies that D aust be less than Dl 

and the null hypothesis can bo accepted. Caso (3) Bakes sense 

only when (n-N-s-D0,D0) is a valid interval, which will bo the 

because n will be small relativo t© N. Case (3) is th© typical 

case and will bo th® sequential testing procedur©. Case (4) is 

true- only when n is greater than DO, where DO is the maximum 

nuaber of defective units one would observe out ef n observations 

if the true defective count were less than or equal te DO. Se an 

observed m greater than DO implies that the true number of 

defectives is greater than DO and the null hypothesis is 

rejected. If case (5) is truQ then D must b© greater than Dl and 

the null hypothesis can again be rejected. Th© only nontrivial 

case is then case (3) where th® sequential probability ratio test 

will be performed in order to aak® a decision. 

Characteristics of Sequential Testa 

The power function of a sequential test describes the risk 

of failing the test' as a function of the true proportion of 

defective stoves in the production at th© facility failing to 

meet the standards set for wood stoves. For the proposed SEA 

sampling plans EPA constrained this risk of failure to no more 

than 51 for values of P less than 0.10. For values of P greater 

than 0.20, it was desired that this risk be at least 90%. Thus 

when using the previous formulae to compute the acceptance and 

rejection numbers of the sequential tests, the values o.f 

Po,Pl,alpha, and beta are as follows: 

P0 

Pl 

alpha 

beta 

= 0.10 

= 0.20 

» 0.05 

« 0.10 

A second characteristic of the sequential procedure is the 

average sample nuab®r (ASN) function, which defines the number of 

observatieno necessary te reach a pass or fail decision as a 

function ©f tho true proportion of wood stoves in a production 

failing t© soot the standards, i.e., as a function of P. Tho 

power funetien and ASN curves fer the SEA d©eisi©n rule ar® shown 

for an infinit© population and §©veral finite populations of 

typical sizes that are executed to be encountered. 

€ 
Ho-amcBfc*.Qafi_feQ tho Qoelnleft mian 

T© faeilitato application ef tho decision rules developed 

above, tw© modifications wero made. First, the nuaber of 

decision ruloo te b© used was limited te four. This was 

accomplished by partitioning tho expected rang® of wood stove 

production to four intervals. One decision rul© was th©n 

s©lected for each interval for appliaetien te all volumes within 

that interval. The decision rule designed for the midpoint of 

each finite interval, will be used for that interval. The 

intervals s©lected ar© 1=99, 100-=199, 200-299, 300=399, and 400 

and above. Based on simulations using the parameter values for 

Po, Pl, alpha, and beta defined previously, th® fi'nit© population 

test for the last interval has characteristics- identical to that 

for infinite populations, so the infinit© population decision 

rule was'used for this interval. 

Second, the decision rules were at a fixed endpoint to 

assure termination of the procedure in' a reasonable number of 

tests. The stopping point chosen for each procedure was tho 

stage whose index equalled approximately one and one-half to two 

times the highest value of the ASN or a set maximum, whichever 

was the smaller. At each stopping point revised acceptance and 

rejection numbers were computed by taking the greatest integer 

function of the average of these two numbers as the new 

acceptance number, and that value plus one as the new rejection 

number. 

Validation of the Decision Rules 

The decision rules generated and. modified in the above 

manner were validated using Monte Carlo computer simulation. 

Replicate experiments were performed for values of P, the 

noncompliance rate, ranging as 0.01(0.01)0.99. Thirty-two 

thousand replications were performed for each size of P. These 

evaluations were performed for the endpoints of each population 

range for each decision rul®. Tabulation and graphs of the power 

and ASN functions ar© included in this document. 
P.95 

SINOGRAPHY 

Wald, Abraham, Sesuential Analysis. John Wiley and Sens, Inc., 

New York, 1947. 

U.S. EPA, "Analytical Development of Sampling Plans for Selective 

Enforcement Auditing of Light°Duty Vehicles and Light-Duty 

Trucks," Unpublished Internal Document, Office of Air, 

Noise, and Radiation, U.S. Environaental Protection Agency! 

1981. 
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P.98 

TABLE 1 continued 

Test Procedure 

| Number 

| of units 

| Inspected 

1 81 

| 82 

| 83 

| 84 

| 85 

| 86 

| 87 

| 88 

| 89 

| 90 

1 91 

| 92 

1 93 

| 94 

1 95 

| 96 

1 9 7 

| 98 

| 99 

| 100 

Acceptance 

Number 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 4 

Rejection | 

Number | 

5 1 

5 1 

5 | 

5 | 

5 | 

5 1 

5 1 

5 1 

5 | 

5 1 

5 I 

5 I 

5 I 

5 I 

5 I 

5 I 

5 I 

5 I 

5 I 

1 . 5 

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P.99 

BINOMIAL SEQUENTIAL TEST 

(Cutoff: 100 inspections) 

Ho: P <= 0.02 

Ha: P >= 0.04 

alpha: 0.05 

power: 0.50 

TABLE 2 

Test Characteristics 

Percent 

of units 

Defective 

5 

15 

25 

35 

45 

55 

65 

75 

85 

95 

Average 

Sample 

Size 

67.9 . 

29.7 

16.5 

11.5 

8.9 

7.2 

6. 1 

5.3 

4.7 

4.2 

Probability 

Rejecting 

HO 

0.51 

0.99 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

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TABLE 1 continued 

Test Procedure | Number j of units j Inspected 1 41 j 42 j 43 j 44 | 45 | 46 j 47 | 48 | 49 j 50 1 51 j 52 1 53 j 54 | 55 | 56 1 57 | ' 58 1 59 | 60 1 61 j 62 1 63 | 64 j 65 j 66 1 67 | 68 1 69 | 70 1 71 j 72 1 73 1 74 1 75 1 76 1 77 | 78 j 79 j 80 

Acceptance 

Number 

— --

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Rejection j 

Number j 

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iHrgro-junvO-oocri O 

rg CM rg CM 
OvOvOvOvOvo^vovDvo^oJOoooaoooooooooooovjvivjvjvjvjvjvjvjvioiwo^wwo^ffiai

O\000vl0>Ulit-WI_HO»000vl0>U1J-WWIJ O v D CO ~-J OMLn*-OJ[\)l-

, OvOOO-J(T>U-|*-U)t

MroMN)MNJN)MMMN.MMMMNNMMtsJtsJMM.-...(-

J

. MMMMMMMM

OOOOOOOOOOOOOOOOOOOOOOOOOOOOOvOvOvOvOvOvOvOvOvOvOv

VO 
K)NNNN)NNNNNNNMNNNNNNWNWNNN)WNNJNNMI\)NNNNNNN

iM*IWWUlUWWUUOJNNN)NNNWNNWI-'HHHHPPI-' p .OOOOOOO

o_oo•^JWUll^u^)HO_oo^l(^ul^w^J^

J

0_c»^J(JlU1(>u^op0^ooosllJ^ol^u^

UUUUUUUWUUUUUUUUUUUUUUUWUUUNNNINNNNINNII.NtO 

m 

l-'h-'MI-'.l-'l-'OOO
P.7 

TABLE 1 continued 

Test Procedure | Number | | | of units | Acceptance | j Inspected | Number j | 241 | 3 | 242 3 | 243 | 3 | 244 | 3 j 245 | 3 j 246 | 3 1 247 3 I .248 | 4 | 249 j 4 | 250 | 4 | 251 j 4 

252 j 4 | 253 | 4 j 254 j 4 | 255 ' | 4 | 256 j 4 | 257 j 4 j 258 j 4 j 259 j 4 | 260 j 4 | 261 | 4 | 262 | 4 | 263 j 4 j 264 | 4 | 265 | 4 1 266 | 4 | 267 | 4 j 268 | 4 | 269 | 4 | 270 j 4 j 271 | 4 | 272 j 4 | 273 j 4 

. j 274 | 4 | 275 j 4 | 276 j 4 j 277 | 4 | 278 j 4 | 279 | 4 | 280 | 4 

1 

Rejection j 

Number j 

i 

1 

12 | 

12 | 

12 j 

12 | 

12 | 

12 | 

12 j 

12 j 

12 | 

12 | 

12 | 

12 | 

12 j 

12 | 

12 | 

12 j 

12 | • 

12 j 

12 j 

12 j 

12 | 

12 | 

12 | 

12 j 

12 | 

12 j 

12 j 

12 | 

12 | 

12 | 

12 | 

12 j 

12 j 

12 | 

12 | 

13 | 

13 j 

13 | 

13 | 

13 | 

EL-11 
OJC~l_O_O0J0_0-_O0-_O_U_O_0_O_OU>U>U>U>_O_OMM M 

NHMHHHHHII HHOOOOOOOOOO_._-0_--__00000000(»0000(»

OvOOOvlWyifrWNHOvOOOvJWUli^ui.HOvOOOvl^Ul^WhOHOkOCOvlOiUli^W

0>O^C»CT»U1<JIU1U101<JlUlUlLn(J1(JlU1Ln(J1(J1U1(J1UlUnui(JIU1(J1(^(J1U1( ^ 

^fr*^frfr^^^*^WWUlUWWWWWU)UIU)UJWWWWU)UlWWWWUWWUl
P.9 

TABLE 1 continued 

Test Procedure | Number | j of units j j Inspected j | 321 | 322 | 323 j 324 j 325 

326 

j 327 I 328 | 329 | 330 | 331 | 332 | 333 | 334 | 335 I 336 | 337 I 338 

339 | 340 | 341 j 342 j 343 j 344 | 345 | 346 | 347 | 348 | 349 | 350 I 351 | 352 I 353 I 354 I 355 I 356 | 357 | 358 I 359 | 360 

1 

Acceptance | 

Number | 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

6 

7 

7 

7 

7 

7 

7 

7 

7 

7 

1 

Rejection | 

Number j 

l 

1 

14 | 

14 14 1 14 | 14 | 14 j 14 j 14 | 14 | 14 j 14 j 14 j 14 j 14 | 14 | 14 j 14 | 14 | 14 | 14 | 14 j 14 | 14 | 14 | 15 | 15 | 15 | 15 | 15 | 15 | 15 | 15 | 15 | 15 | 15 | 15 | 15 | 15 j 15 | 15 | 

EL-13 
P.10 

TABLE 1 continued 

Test Procedure | Number | I j of units | Acceptance | j Inspected | Number j | 361 | 7 | 362 | 7 | 363 j 7 | 364 | 7 | 365 | 7 | 366 | 7 | 367 | 7 | 368 j 7 | 369 | 7 | 370 | 7 1 371 j 7 j 372 | 7 | 373 | 7 | 374 j 7 j 375 | 7 1 376 | 7 

377 | 7 | 378 | 7 | 379 | 7 | 380 | 7 j 381 | 7 | 382 • j 7 j 383 | 7 j 384 | 7 j 385 | 7 | 386 | 7 | 387 j 8 | 388 | 8 | 389 | 8 | 390 j 8 I 391 | 8 | 392 | 8 | 393 j 8 j 394 | 8 | 395 | 8 I 396 j 8 | 397 | 8 | 398 | 8 | 399 | 8 | 400 | 8 

1 

Rejection | 

Number | 

1 

1 

15 15 

15. 15 15 15 15 15 15 15 15 15 15 15 15 15 

. 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 

EL-14 

/ 

-
i^^^4^^^^^4-.^^4-^4-'^^^^i.^^^^^i.^^^rf_>t-it_i.^_>f_>f_i.*->(^rf-

i^_O0J0-_O_o_Ot00J(jJ0JMtN>MMbJWMMMM.I-'.l--

1

. h-'t-'h-'M . OOOOOOO

O*0O)vJWWi^UNHO»_00vl0lUl^WKJPOiDC0vl0iUlit.WNJHOv-a>vJ0>Uli|iUJl>

vOvOvOvO^^vOvOvOvO^vOvOvOvOvOvOvOvOvO0000CO(»0000COC0CO00a)C0C0a>0O(X>C»COC

on ui tn _iui_i_i_i_nui_i_i_i_i_iui_n(^uiuiwwLnwuicnLnuiuiuiuiui(^(ji(jioiuiui
P.12 

TABLE 1 continued 

Test Procedure 

1 Number | i 

of units | Acceptance | 

1 Inspected j Number | 

1 441 | 9 i 

1 442 | 9 1 

1 443 | 9 | 

1 444 j 9 l 

1 445 j 9 j 

1 446 j 9 1 

1 .447 | 9 | 

1 448 | g j 

1 449 | g 

1 450 | g 

! Jf

1

 ! 9

452 ' 

 9 , 

453 9 | 

1 454 j 9 | 

1 455 | g i 

1 456 | io 1 

457 | io | 

458 | io 1 

459 | io | 

460 | io | 

461 j io | 

462 • | io | 

46 3 j 10 | 

1 464 j 10 | 

I 465 | io | 

466 j 10 

467 | 10 | 

468 | io | 

469 | io | 

470 | 10 1 ' 

471 | 1

0 1 

472 | 10 1 

473 | 10 | 

474 | io | 

475 | io 1 

.1 476 | io | 

477 | io | 

478 | io 1 

479 | io • | 

1 480 j ,io j 

I 

1 

Rejection j 

Number j 

15 1 

1 

15 1 i 

15 1 1 

15 | i 

15 1 1 

15 | 

15 | 

1 

15 1 1 

15 1 1 

15 1 f 

15 1 1 

15 1 1 

15 | 1

15 I 1 

15 1 1 

15 1 1 

15 | 1

15 1 i 

15 | 

15 1 

1 

15 1 1 

15 1 1 

15 1 1 

15 1 1 

15 | 

15 1 

1 

15 1 1 

1_•5 - » 1 i 

15 1 i 

15 1 

15 1 

15 1 

1 

15 1 i 

15 1 1 

15 1 1 

15 1 1 

15** 1 1 

15 1 1 

15 1 1 

15 | 

EL-16 
in*->f_lt_.>P->{_IP-IP_£-£_iJ_.lt_!j_.4_>£_4_>l(->(_

OvOvOvOvOvOvOvOvOvOvOCOCOCOOOOOOOO

O-l00vjaiUl*>WNpOv00l)vJOM)l*.

*-..l-'..l-'.Mh-'l-'000000

U1U1U1U1U1U1U1U1U1U1U1U1U1UIU1U1U1U
P.M 

BINOMIAL 

(Cutoff: 

Ho: P <= 0.02 

Ha: P >= 0.04 

SEQUENTIAL TEST 

500 inspections) 

alpha: 0.05 

power: 0.90 

TABLE 2 

Test Characteristics 

Percent 

of units 

Defective 

5 

10 

15 

20 

25 

30 

35 

40 

45 

50 

55 

60 

65 

70 

75 

80 

85 

90 

95 

100 

Average 

Sample 

Size 

196.9 

63.5 

35.8 

25.8 

20.3 

16.9 

14. 2 

12.6 

11.2 

10. 1 

9.2 

8.3 

7.8 

7. 1 

6.6 

6.3 

5.9 

5.5 

5.3 

5.0 

Probability 

Rejecting 

Ho 

1 0.98 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1. }0 

1.00 

1.00 

EL-18 
4_>_0<j__0_OOJ_OOJ_0_OOJhJNhJtN)tN)MtN)tN)tN>W-..M.. . 

O^OOslOlUli^UlNHOvOOOsllJiW^UNHOvflt.vlOlUliliWNPOiDOOslOiUlitkUlNr ' 

..M.*-" . OOOOOOOOOOOOOOOO O I I I I I I I I I I I I I I I 

OiffiWWIJi01(^(7iUlUlUlUllJlWUlW(/lUl(^IJlUlUlU101Uli^J-i^4-J- 1 ^it>.il-*.*. 1 t-i( - I I I 

_> 
P.16 

TABLE 1 continued 

Test Procedure | Number j of units j Inspected 1 41 1 42 1 43 | 44 1 45 I 46 1 47 | 48 I 49 | 50 1 51 | 52 1 53 | 54 I 55 | 56 1 57 | 58 1 59 I 60 1 61 | 62 1 63 | 64 1 65 | 66 1 67 | 68 1 69 I 70 1 71 1 72 1 73 1 74 1 75 1 76 I 77 | 78 1 79 j 80 

Acceptance 

Number 

1 

1 

1 

1 

1 

1 

1 

1 

1 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

3 

3 

3 

3 

3 

3 

3 

3 

3 

3 

3 

3 

3 

3 

Rejection j 

Number j 

6 1 6 I 6 1 6 1 6 1 6 I 6 j 6 | 6 I 7 ' | 7 I 7 | 7 j 7 | 7 I 7 I 7 j 7 | 7 j 7 j 7 | 7 I 7 | 7 | 7 | 7 j 7 | 7 I 7 I '7 | 7 | 7 I 7 I 7 | 7 I 7 I 7 I 7 j 7 | 7 | 

EL-20 
P.17 

TABLE 1 continued 

Test Procedure 

| Number 

| of units 

| Inspected 

1 81 

I 82 

| 83 

| 84 

1 85 

| 86 

I 87 

| 88 

| 89 

| 90 

1 91 

| 92 

1 93 

| 94 

1 95 

1 96 

1 97 

| 98 

| 99 

I 100 

Acceptance 

Number 

3 

3 

3 

3 

4 

4 

4 

4 

4 

4 

4 

4 

4 

4 

4 

4 

4 

4 

4 

1 6 

Rejection | 

Number | 

7 | 

7 | 

7 I 

7 I 

7 | 

7 I 

7 | 

7 I 

7 I 

7 I 

7 I 

7 I 

7 | 

7 I 

7 I 

7 | 

7 | 

7 I 

7 | 

1 7 

EL-21 
P.18 

BINOMIAL SEQUENTIAL TEST 

(Cutoff: 100 inspections) 

Ho: P <= 0.04 

Ha: P >= 0.08 

alpha: 0.0.5 

power: 0.50 

TABLE 2 

Test Characteristics 

Percent 

of units 

Defective 

5 

15 

25 

35 

45 

55 

65 

75 

85 

95 

Average 

Sample 

Size 

43.2 

34.0 

18.1 

11.9 

8.9 

7.2 

6.2 

5.3 

4.7 

4.2 

Probability 

Re 

Ho 

jecting 

0.16 

0.92 

0.98 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

EL-22 
*WUWW_JCOWWWU)IV)t.N)N)l.tsirON)N)tgHHH.HPH.H M 

O^OOvlOlUl^WNHOiOOOvlOiUl^WNlHOiDOOvJiTiUli^WNHOiflOOslffiUli^UN ) 

I I I I I I I I I I I I I I I I I I I I I I I I I I I . I I I I I I I I I I I I I 

•^^^^^0^O^O^O^O^0*0^0>O^0^O\0^0^O*0*(TiO\ISIUIUIUIi^lJ^IJIIJIIJ\UllJIIJ\IJ\{^ I I I I 

CO 
P.20 

TABLE 1 continued 

Test Procedure | Number j of units j Inspected 1 41 j 42 1 43 | 44 1 45 | 46 1 47 j 48 I 49 | 50 1 51 j 52 | 53 | 54 I 55 1 56 57 | 58 1 59 | 60 1 61 | 62 1 63 | 64 1 65 | 66 1 67 j 68 1 69 I 70 1 71 I 72 1 73 1 74 1 75 1 76 1 77 1 78 1 79 1 80 

Acceptance 

Number 

— ----------

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

Rejection | 

Number j 

7 | 7 I 7 j 7 I 7 I 7 I 7 | 7 | 7 j 7 I 7 I 7 j 7 I 7 | 7 j 7 I 7 j 7 j 7 | 7 I 7 I 7 I 7 I 7 I 7 | 7 I ' 7 | 7 I 7 I 7 I 7 j 7 | 7 I 7 | 7 I 7 I 7 I 7 | 7 | 7 j 

EL-24 
P.21 

TABLE 1 continued 

Test Procedure 

| Number 

| of units 

| Inspected 

1 81 

| 82 

I 8 3 

| 84 

| 85 

| 86 

| 87 

| 88 

| 89 

| 90 

1 91 

| 92 

1 93 

| 94 

1 95 

| 96 

1 97 

| 98 

| 99 

| 100 

Acceptance 

Number 

1 

1 

1 

1 

1 

1 

l 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

2 

1 6 

Rejection | 

Number | 

7 | 

7 1 

7 | 

7 1 

7 | 

7 1 

7 • I 

7 | 

7 I 

7 | 

7 I 

7 I 

7 I 

7 I 

7 I 

7 I 

7 I 

7 I 

7 I 

1 7 

EL-25 
P.22 

BINOMIAL 

(Cutoff: 

Ho: P <= 0.04 

Ha: P >= 0.08 

SEQUENTIAL TEST 

100 inspections) 

alpha: 0.05 

power: 0.90 

TABLE 2 

Test Characteristics 

Percent 

of units 

Defective 

5 

15 

25 

35 

45 

55 

65 

75 

85 

95 

Average 

Sample 

Size 

88.3 

43.8 

22.8 

14.8 

11. 2 

-9.2 

7.7 

6.6 

5.9 

5.3 

Probability 

Rejecting 

Ho 

0.27 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

EL-26 
P.23 

BINOMIAL 

(Cutoff: 

SEQUENTIAL TEST 

100 inspections) 

Ho: 

Ha: 

P <= 0.04 

P >= 0.06 

alpha: 

power: 

0.05 

0.50 

TABLE 1 

Test Procedure 

Number 

of units 

Inspected 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 

Acceptance 

Number 

— ---

_ 

-------------------------

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

Rejection 

Number • — ----

6 

6 

6 

6 

6 

6 

6 

7 

7 

7 

7 

7 

7 

7 

7 

7 

7 

7 

7 

7 

7 

7 

7 

7 

7 

7 

7 

7 

7 

7 

7 

7 

7 

7 

7 

EL-27 
P.24 

1 

TABLE l continued 

Test Procedure 

1 Number | 

1 of units | Acceptance 

Inspected | Number 

j 41 | 0 

42 | 0 

43 1 0 

4454 | 0 

46 | 0 

47 1 o 

4

8 | 0 

4

9 | 0 

50 | 0 

51 1 1 

52 | ! 

53 | i 

54 | i 

55 | i 

1 56 j ! | 57 | i 1 58 j 1 ! 59 | x 1 60 | x ' 61 | i 62 | ! 63 1 1 1 64 | 1 1

 65 ' 1 

1 66 j 1 

j 67 | i 

1 68 j 1 | 69 | ! 70 | x 71 1 1 72 | 2 7 3 1 2 7 4 1 2 75 1 2 76 1 2 7 7 1 2 78 | 2 7 9 1 2 

1 80 | 2 

1 , 

1 1 Rejectio

n | 

1 Number | 

1 7 | 1 7 | 1 7 j 1 7 j 1 7 . | '

 7 | 

1' 7 | 1 7 | 1 7 | 1 . 7 | 1 7 | 1 7 | 1 7 | 1 7 | '

 7 | 

1 7 | 1 7 | 1 7 | ! 7 | 77 | 

 I 

7 I 7 | 7 I 7 j 7 | 7 j "7 1 7 j 7 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 77 | 

 I 

7 j 7 | 

EL-28 
h-vOvOvOvOvOvOvOvOvOvOCOCOOOOOOOOOOOC

OvOOO~-Jv7iCn*-OJtN).OvOOO-JCTiCn^-OJ[

o 

OJOjL-)OJOJOJOJOJtN)tN)tN)tN)tN)tN)"N)tN)tN)rN

(T 

^J-~J^J--J>~J^J--J-J-~J^J-J^J>-J^1^J-~J~J

IN) 

to 
P.26_ 

HO: 

Ha: 

BINOMIAL 

(Cutoff: 

P <= 0.04 

P >= 0.06 

SEQUENTIAL TEST 

100 inspections) 

alpha: 0.05 

power: 0.50 

TABLE 2 

Test Characteristics 

Percent 

of units 

Defective 

5 

15 

25 

35 

45 

55 

65 

75 

85 

95 

Average 

Sample 

Size 

72.3 

46.1 

27.8 

19. 3 

14.6 

11.3 

9.3 

8.1 

7.1 

6.3 

Probability 

Rejecting 

Ho 

0.21 

0.99 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

EL-30 
H — 

Cfl w 

W C 

_ O 

•rH 

-P 

S CD 

M Q, 

[H W 

s c W -H 

O

D 

O 

W O 

00 -

.

H 

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ri! *+H 

M O 

£ +J 

O 3 

S U 

M — 

m 

in o 

O <T> 

• • 

o o 

8 * • * 

rt u 

& CD 

D, _e 

•H O 

rt

<

= 0.04 

 Qk 

>

= 0.06 

d) 

t-i 

3 

-H *0 

CD 

W U 

. 4 O 

CQ VH 

3 04 

_ 

+J 

(fl 

QJ 

EH 

04 04 

o ro" 

a, ac 

| | | | | ^v^iO^vD^^vD^vOv_0U>vOvD^^v^vOv0vOvO^iOvO^VDVO^i_0vD^OvDW

i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i 

HNfn-fin>o.oo(roHNrn'*i/ivor^co(^OHNf«iTfinio._)(POHN.^in«)r

,

»

.rHrHrHrHrHrHrHrHrH(Nr\ir\i(NrNirsiCNi(Ni(Nirgroro.<.rorororo
Q

•d 

J 

C 

3 

CD 

3 

U 

•P *0 

u 

o 

c CD 

0

U 

o 

u 

4 

w +-

i-J w 

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^O^CU)^iC^Ov0^vDiDi£_)^ 0 v o vOvOvOvOvOvOvOvOvOvOvOvOvOvOvOvOvOvOvOvOvOvOvOvOV

I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I 

HNrn^_lM3.00ll>OHNM-f_1k0^a3mOHNm-l

l

_lvO.C00lOHNM-f-1U)>000

.-f-frfrll^^^^f-fln_)lrl^n-lln-^-^lrl-1-^_)_)^o^o^ovovo^Dvo^^.^^^^^r

v

. 
P.29 

TABLE l continued 

Test Procedure 

| Number 

| of units 

j Inspected 

1 81 

| 82 

1 83 

| 84 

1 85 

| 86 

| 87 

| 88 

| 89 

| 90 

1 91 

| 92 

1 • 93 

| 94 

1 95 

1 96 

1 97 

| 98 

| 99 

| 100 

Acceptance 

Number 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

1 5 

Rejection | 

Number j 

6 1 

6 1 

6 1 

6 1 

6 | 

6 I 

6 I 

6 I 

6 I 

6 I 

6 I 

6 I 

6 I 

6 | 

6 I 

6 I 

6 I 

6 I 

6 I 

1 6 

EL-33 
P.30 

BINOMIAL SEQUENTIAL TEST 

(Cutoff: 100 inspections) 

Ho: P <= 0.04 

Ha: P >= 0.06 

alpha: 0.05 

power: 0.90 

TABLE 2 

Test Characteristics 

Percent 

of units 

Defective 

5 

15 

25 

35 

45 

55 

65 

75 

85 

95 

Average 

Sample 

Size 

92.0 

39.7 

23.9 

17.1 

13.2 

11.0 

9.2 

8.0 

7.1 

6.3 

Probability 

Rejecting 

Ho 

0.3 3 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

1.00 

EL-34 
. 

-ST-

/OT/.__iJ__T H.H 

P.32 

Ktarouo W©oh Boflnory 

SMC. _30_fltr_flD_t3Q5_l 

C30(?feO(_lln)g ©®ff5il(pa(nlS7 

P 0 80x42 6 

Marcus Hook PA 19061 -0426 

January 12, 1990 

Mr. Robert Ajax 

U.S. EPA 

MD-13 

Research Triangle Park, NC 27711 

Dear Bob, 

At the December Reg-Neg meeting I told you that our 

eguipment screening cost is $1.75/component. I have since 

learned from our contractor (TEAM) that this is only a base 

price. Our true costs are closer to $2.75/component. For 

example, during 1989 61,750 components were screened at a 

cost of $169,170. This comes to $2.74/component. I have 

been told by TEAM that this price would hold for the 

Northeast from Washington to Northern New Jersey. Cost in 

the Northern New Jersey area is about $4/component. 

The reason for the difference between $1.75 and $2.75 is 

that during every screening session there are a certain 

number of extraordinary operations that must be performed. 

These are charged at an hourly rate and include: 

1. Replacing missing and damaged tags. 

2. Adding and removing components from the program. 

3. Screening "inaccessibles'•. 

4. On-the-Spot maintenance - tighten packing and 

flanges, plug or cap open ends, etc. 

I hope this information will be of help to you and you 

will us it when figuring VOC screening costs. 

Sincerely, 

SUN REFINING AND MARKETING COMPANY 

Walter Brenner 

Senior Environmental Specialist 

WBserg 

WB-RA12 

_ 

is