EPA-650/4-74-005-g
March 1976 Environmental Monitoring Series
GUIDELINES FOR DEVELOPMENT
OF A QUALITY ASSURANCE PROGRAM:
VOLUME VII - DETERMINATION
OF SULFURIC ACID MIST
AND SULFUR DIOXIDE EMISSIONS
FROM STATIONARY SOURCES
Office of Research and Development
U.S. Environmental Protection Agency
Washington, D.C. 20460
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Agency and approved for publication. Approval does not signiiy that
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mental Protection Agency, nor does mention of trade names or commer-
cial products constitute endorsement or recommendation for use.
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EPA-650/4-74-005-g
GUIDELINES FOR DEVELOPMENT
OF A QUALITY ASSURANCE PROGRAM:
VOLUME VII - DETERMINATION
OF SULFURIC ACID MIST
AND SULFUR DIOXIDE EMISSIONS
FROM STATIONARY SOURCES
by
J.W. Buchanan and D.E. Wagoner
Research Triangle Institute
Research Triangle Park, North Carolina 27709
Contract No. 68-02-1234
ROAP No. 26BGC
Program Element No. 1HA327
EPA Project Officer Steven M. Bromberg
Environmental Monitoring and Support Laboratory
Office of Monitoring and Technical Support
Research Triangle Park, North Carolina 27711
Prepared for
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Research and Development
Washington, D.C. 20460
March 1976
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ABSTRACT
Guidelines for the quality control of stack gas analysis for sulfuric
acid mist and sulfur dioxide emissions by the Federal reference method are
presented. These include:
1. Good operating practices;
2. Directions on how to assess performance and to qualify data;
3. Directions on how to identify trouble and to improve data quality;
4. Directions to permit design of auditing activities.
The document is not a research report. It is designed for use by
operating personnel.
This work was submitted in partial fulfillment of contract Durham 68-02-
1234 by Research Triangle Institute under the Sponsorship of the Environmental
Protection Agency. Work was completed as of November, 1975.
iii
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TABLE OF CONTENTS
SECTION
II
PAGE
III
2.0
2.1
2.2
2.3
2.4
3.0
3.1
3.2
3.3
IV
4.0
4.1
4.2
4.3
4.4
V
APPENDIX A
APPENDIX B
APPENDIX C
APPENDIX D
INTRODUCTION
OPERATIONS MANUAL
GENERAL
APPARATUS SELECTION AND REQUIREMENTS
PRESAMPLING PREPARATION
ON-SITE MEASUREMENTS
POST-SAMPLING OPERATIONS (BASE LABORATORY)
MANUAL FOR FIELD TEAM SUPERVISOR
GENERAL
ASSESSMENT OF DATA QUALITY (INTRATEAM)
SUGGESTED PERFORMANCE CRITERIA
COLLECTION AND ANALYSIS OF INFORMATION TO
IDENTIFY TROUBLE
5
11
15
29
39
43
43
45
47
49
MANUAL FOR MANAGER OF GROUPS OF FIELD TEAMS 57
GENERAL 57
FUNCTIONAL ANALYSIS OF THE TEST METHOD 61
ACTION OPTIONS 73
PROCEDURES FOR PERFORMING A QUALITY AUDIT 81
DATA QUALITY ASSESSMENT 85
REFERENCES 97
METHOD 8 99
ILLUSTRATED AUDIT PROCEDURES AND
CALCULATIONS m
GLOSSARY OF SYMBOLS us
GLOSSARY OF TERMS m
iv
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LIST OF ILLUSTRATIONS
FIGURE NO. PAGE
1 Sequence of operations to be performed. 6
2 Wet test meter calibration data. 21
3 Sample control chart for standardized barium perchlorate
solution. 55
4 Sample control chart for range of duplicate measurements. 55
5 Summary of data quality assurance program. 60
6 Added cost versus data quality (CV) for selected action
options, for SO-/H9SO.. data. 77
O t- *T
7 Added cost versus data quality (CV^) for selection
action options for S03/H2SO. data. 78
8 Example illustrating p < 0.10 and satisfactory data
quality. 89
9 Example illustrating p > 0.10 and unsatisfactory data
quality. 89
10 Flow chart of the audit level selection process. 92
11 Average cost versus audit level (n). 95
8-1 Sulfur acid mist sampling train. 100
8-2 Field data. 107
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LIST OF TABLES
TABLE NO. PAGE
1 Suggested performance criteria 47
2 Assumed means and coefficients of variations of
variables in influencing emissions rate determinations
for S02 63
3 Variance analysis for V 67
mstd
4 Variance analysis for Ccn 67
bU2
5 Variance analysis for Q 68
6 Variance analysis for reproducibility of ER 69
7 Assumed within - laboratory, between - laboratory, and
laboratory bias components of variability for given
action options 75
8 Computation of mean difference, d~, and standard
deviation of differences, s. 90
d
9 Sample plan constants, k for P {not detecting a lot
with proportion p outside limits L and 11} < 0.1 91
vi
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SECTION I INTRODUCTION
This document presents guidelines for developing a quality assurance pro-
gram for Method 8, Determination of Sulfuric Acid Mist and Sulfur Dioxide
Emissions from Stationary Sources. This method was initially published by the
Environmental Protection Agency in the Federal Register,* and is reproduced as
appendix A of this report for convenience of reference.
This document is divided into four sections:
Section I, Introduction. The introduction lists the overall objectives of
a quality assurance program and delineates the program components necessary to
accomplish the given objectives.
Section II, Operations Manual. This manual sets forth recommended operat-
ing procedures to insure the collection of data of high quality, and instruc-
tions for performing quality control checks designed to give an indication or
warning that invalid data or data of poor quality are being collected, allowing
for corrective action to be taken before future measurements are made.
Section III, Manual for Field Team Supervisor. This manual contains
directions for assessing data quality on an intralaboratory basis and for
collecting the information necessary to detect and/or identify trouble.
Section IV, Manual for Managers of Groups of Field Teams. This manual
presents information relative to the test method (a functional analysis) to
identify the important operations variables and factors, and statistical prop-
erties of and procedures for carrying out auditing procedures for an independ-
ent assessment of data quality.
The objectives of this quality assurance program for Method 8 are to:
1. Minimize systematic errors (biases) and maintain precision
within acceptable limits in the measurement process,
2. Provide routine indications for operating purposes of
satisfactory performance of personnel and/or equipment,
3. Provide for prompt detection and correction of conditions that
contributes to the collection of poor quality data, and
4. Collect and supply information necessary to describe the quality
of the data.
Reference to be supplied in final version of document.
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To accomplish the above objectives, a quality assurance program must contain
the following components:
1. Recommended operating procedures,
2. Routine training of personnel and evaluation of performance of
personnel and equipment,
3. Routine monitoring of the variables and parameters that may have a
significant effect on data quality,
4. Development of statements and evidence to qualify data and detect
defects, and
5. Action strategies to increase the level of precision/accuracy in
the reported data.
Component (2) above will be treated in the final report of this contract. All
other components are treated in this document.
Implementation of a properly designed quality assurance program should
enable measurement teams to achieve and maintain an acceptable level of
precision and accuracy in their stack gas composition measurements. It will
also allow a team to report an estimate of the precision of its measurements
for each source emissions test.
Variability in emission data derived from multiple tests conducted at
different times includes components of variation from:
1. Process conditions,
2. Equipment and personnel variation in field procedures, and
3. Equipment and personnel variation in the laboratory.
In many instances time variations in source output may be the most significant
factor in the total variability. The deviation resulting from this component
of variation is minimized by knowing the time characteristics of the source
output and sampling over the complete output cycle.
Quality assurance guidelines for Method 8 as presented here are designed
to insure the collection of data of acceptable quality by prevention, detec-
tion, and quantification of equipment and personnel variations in both the
field and the laboratory through:
1. Recommended operating procedures as a preventive measure,
2. Quality control checks for rapid detection of undesirable
performance, and
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3. A quality audit to independently verify the quality of the
data.
The scope of this document has been purposely limited to that of a field
and laboratory document. Additional background information is contained in
the final report under this contract.
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SECTION II OPERATIONS MANUAL
2.0 GENERAL
This manual sets forth recommended procedures for the measurement of
sulfuric acid mist and sulfur dioxide emissions from stationary sources accord-
ing to Method 8 (ref. 1). (Method 8 is reproduced from the Federal Register
and included as appendix A of this document.) Quality control procedures and
checks designed to give an indication or warning that invalid data or data of
poor quality are being collected are written as part of the operating procedures
and are to be performed by the operator on a routine basis. In addition, the
performance of special quality control procedures and/or checks as presented
by the supervisor may be required of the operator on certain occasions. The
precision and/or validity of data obtained from this method depends upon equip-
ment performance and the proficiency with which the operator performs his
various tasks. From equipment calibration through on-site measurements, calcu-
lations, and data reporting, this method is susceptible to a variety of errors.
Detailed instructions are given for minimizing or controlling equipment error
and procedures designed to minimize personnel errors are recommended. Before
using this document, the operator should study Method 8 as written in appendix
A in detail. In addition, one is advised to read the Operations Manuals of
the quality assurance documents for Methods 2, 3, 4, and 6.
The sequence of operations to be performed is given in figure 1. Two
columns are used. The columns are numbered 1 through 22. Quality checkpoints
in the measurement process for which appropriate quality control limits are
assigned are represented by blocks enclosed by heavy lines. Other checkpoints
involve go/no-go checks, and subjective judgments by the operator with proper
guidelines for decisionmaking are spelled out in the procedures.
The precision/accuracy of data obtained from this method depends upon
equipment performance and the proficiency and conscientiousness with which the
field team members carry out their various tasks. Deviations from the recom-
mended operational procedure may result in the collection of invalid or poor
quality data.
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PRESAMPLING PREPARATION
1. SELECT THE EQUIPMENT APPROPRIATE
FOR THE PROCESS (SOURCE) TO BE
TESTED. CHECK THE EQUIPMENT FOR
PROPER OPERATION.
2. CALIBRATE TYPE-S PITOT TUBE,
NOZZLE DIAMETER, PROBE TEMPERATURE,
DRY GAS METER(S), AND ORIFICE
3. PACK EQUIPMENT IN A MANNER TO
PRECLUDE BREAKAGE OR DAMAGE
DURING HANDLING AND SHIPMENT.
MEASUREMENT
ON-SITE S02
4. TRANSPORT EQUIPMENT FROM FLOOR
LEVEL TO THE SAMPLING SITE BY
THE BEST MEANS AVAILABLE.
5. ASSEMBLE THE EQUIPMENT ON-SITE
AND PERFORM AN OPERATIONAL CHECK
(EVALUATION OF THE SYSTEM).
6. DETERMINE THE TRAVERSE POINTS
(SAMPLE POINTS) ACCORDING TO
METHOD 1.
DETERMINE THE INSIDE AREA OF
STACK BY (1) MEASURING THE
DIAMETER OR (2) MEASURING THE
CIRCUMFERENCE AND CORRECTING
FOR WALL THICKNESS.*
8. PERFORM THE VELOCITY TRAVERSE OF
THE STACK GAS USING THE QUALITY
ASSURANCE DOCUMENT FOR METHOD 2.
9. DETERMINE THE MOISTURE CONTENT OF 9
THE STACK GAS USING THE QUALITY
ASSURANCE DOCUMENT FOR METHOD 4
(IF APPLICABLE TO SOURCE).
*If the stack is rectangular, simple multiply two
adjacent sides together.
EQUIPMENT
SELECTION
AND CHECK
EQUIPMENT
CALIBRATION
PACKAGE
EQUIPMENT
FOR SHIPMENT
TRANSPORT
EQUIPMENT TO
TEST SITE
ASSEMBLE/CHECK
EQUIPMENT
ON-SITE
DETERMIME
TRAVERSE POINTS
(METHOD 1)
I
DETERMIME
INSIDE AREA
OF STACK
PERFORM
VELOCITY
TRAVERSE
(METHOD 2)
DETERMINE
MOISTURE CONTENT
(METHOD 4)
Figure 1. Sequence of operations to be performed.
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10.
11.
12.
13.
14.
15.
DETERMINE THE MOLECULAR WEIGHT OF
THE STACK GAS (WET BASIS) USING THE
QUALITY ASSURANCE DOCUMENT FOR
METHOD 3 AND THE RESULTS OF STEP 9
ABOVE
DETERMINE THE VOLUMETRIC FLOW RATE
OF THE SOURCE USING THE QUALITY
ASSURANCE DOCUMENT FOR METHOD 2.
SET NOMOGRAPH UTILIZING THE
PRELIMINARY STACK GAS PARAMETERS
PREPARE ABSORBING REAGENTS AND ADD
100 ml 80-PERCENT ISOPROPANOL (FIRST
IMPINGER) AND 100 ml OF 3-PERCENT
H2°2 "
10
11
12
13
(SECOND AND THIRD IMPINGERS).
SET UP SAMPLING TRAIN AND LEAK CHECK
SYSTEM
PERFORM SAMPLE COLLECTION (ISOKINETIC)
ACCORDING TO THE PROCEDURE GIVEN IN
SUBSECTION 2.3.3.
16. PERFORM LEAK CHECK AT END OF TEST.
17. QUANTITATIVELY RECOVER IMPINGER
SOLUTIONS.
14
15
16
17
DETERMINE
MOLECULAR
WEIGHT
(METHOD 3)
i
p
DETERMINE
VOLUMETRIC
FLOW RATE
(METHOD 2)
i
>
SET NOMOGRAPH
i
r
PREPARE
ABSORBING
REAGENTS.
ADD TO COLLEC-
TION SYSTEM.
1
r
SET UP TRAIN.
LEAK CHECK
TOTAL SYSTEM.
i
r
[COLLECT
SAMPLE
<
t
LEAK CHECK
SAMPLING TRAIN
18. VISUALLY INSPECT EQUIPMENT FOR DAMAGE
AFTER ALL MEASUREMENTS HAVE BEEN MADE
AND RECORDED.
19. PACK EQUIPMENT AND SAMPLES FOR SHIPMENT
BACK TO THE BASE LABORATORY.
18
19
JL
TRANSFER
COLLECTED
SAMPLES TO
SHIPPING
CONTAINERS
INSPECT
EQUIPMENT
FOR DAMAGE
PACK EQUIPMENT
AND SAMPLES
FOR SHIPMENT
Figure 1. Sequence of operations to be performed (continued).
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POST-SAMPLING OPERATIONS
20. PERFORM POST CALIBRATION AND
ANALYSIS OF SAMPLES FOR
SULFURIC ACID AND SULFUR
DIOXIDE
21. PERFORM CALCULATIONS UTILIZING
ALL FIELD AND CALIBRATION DATA.
22. FORWARD DATA WITH PERTINENT
REMARKS CONCERNING QUALITY CHECKS
FOR FURTHER INTERNAL REVIEW OR TO
USER.
20
21
22
PERFORM POST-
CALIBRATION
AND ANALYSIS
\
t
PERFORM
CALCULATIONS
REPORT
DATA
Figure 1. Sequence of operations to be performed (continued),
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For discussion purposes, the measurement process is divided into four
phases. They are:
1. Apparatus selection and requirements,
2. Presampling preparation,
3. On-site measurements, and
4. Post-sampling operations.
It is assumed that all apparatus is selected to satisfy the reference method
specifications and that the manufacturer's recommendations will be followed
when using a particular item of equipment (e.g., barometer, thermocouple, or
differential pressure gauge).
The presampling preparation phase consists of a preliminary site visit
(optional), equipment inspection and calibration, and the packing of equipment
for transporting to the test site area. Unpacking and assembly of equipment,
preliminary velocity traverse, determination of gas composition (molecular
weight), moisture determination, particulate sampling, data recording and
inspection, and packing the equipment for shipment back to the home laboratory
are included in the on-site measurement phase. Post-sampling operations
include calibration checks, analysis, calculations, and data reporting. Each
phase is discussed separately.
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10
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2.1 APPARATUS SELECTION AND REQUIREMENTS
2.1.1 Sampling.
The sampling system consists of a heated probe, pitot tube, collection
system, leak-free pump, dry test meter, and temperature monitoring system.
2.1.1.1 Probe. A glass probe (borosilicate glass) with electrical heating to
prevent condensation during sampling is used. The glass liner should be
protected with an outer sheath of stainless steel. The probe should have the
heating capability to maintain the stack gas temperature at >175° C (ref. 2).
The high-temperature (>425° C) probes may be fabricated from quartz. Stack
gas .should be cooled to about 300° to 375° C to minimize the changes in sample
concentration in contact with the sample probe.
2.1.1.2 Nozzle. A stainless steel nozzle with a sharp, tapered leading edge
is specified by the reference method. A set of three nozzles, approximately
0.6, 1, and 1.3 cm (I/A, 3/8, and 1/2 inch) in diameter will usually suffice for
most stack sampling applications. It is recommended that for certain situations,
such as high stack gas velocities or extreme moisture or stack temperature, that
one also have nozzles 0.5 and 1.6 cm (3/16 and 5/8 inch) in diameter (ref. 3).
These sizes are not stock items but are available by special order.
2.1.1.3 Pitot Tube and Differential Pressure Gauge and Stack Gas Temperature
Monitoring System. A Type-S or equivalent pitot tube attached to the probe is
required to monitor stack gas velocity. A differential pressure gauge, such
as an inclined manometer, and sufficient connecting lines are required. A
temperature measuring device attached or capable of being attached to the pitot
tube is required for monitoring stack temperature.
2.1.1.4 Filter Holder. A pyrex glass filter holder is specified by the
reference method. The filter support media should be a glass frit. The glass
frit should always be cleaned before sampling according to the manufacturer's
recommendations. A standard cleaning procedure is not applicable to all filter
supports due to the variation in construction materials. A filter holder
should be durable, easy to load, and leak free in normal applications. The
design of the filter holder must be such that the filter material is not torn
as the filter is tightened and the only flow through the holder is through the
filter.
11
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2.1.1.5 Filter Media. A glass-fiber media filter designed to remove 99.7
percent of the particulates larger than 0.3 ym (dioctylphthalate test) should
be used. The filter must be chemically inert.
2.1.1.6 Barometer. A calibrated barometer (shock-mounted spring system) for
measuring the barometric pressure should be used. An alternate is to obtain
the uncorrected barometric pressure from a nearby weather station.
2.1.1.7 Impingers and Container. Four impingers are connected in series with
inert joints. The first, third, and fourth impingers are of the Greenburg-
Smith design, modified by replacing the tip with a 1/2-inch ID glass tube
extending to 1/2 inch from the bottom of the flask. The second impinger is
of the Greenburg-Smith design with the standard tip. Upon purchase of a new
Greenburg-Smith impinger, fill the inner impinger tube with water. If the
water does not drain through the orifice in at least 6 to 8 seconds, the
impinger tip should be replaced or enlarged. This is required to prevent an
excessive pressure drop in the sampling system. The fourth impinger is
required (charged with silica gel) to remove moisture and to protect the
vacuum pump and dry test meter. The reference method requires that the conden-
sate trap be used to keep the effluent gas temperature to 20° C or less. Ice
containers are available in commercial trains or can be fabricated from closed-
pore styrofoam material. The efficiency of the ice bath can be increased by
the addition of salt.
2.1.1.8 Metering System. The metering system includes a vacuum gauge, leak-
free pump, thermometers capable of measuring temperatures to within 3° C, dry
gas meter with 2 percent accuracy, and related equipment to facilitate the
taking of isokinetic source samples. Individual items of equipment are:
1. The vacuum gauge for measuring sampling stream pressure
serves a twofold purpose: (1) a leak check of the sampling
train at 38 cm of mercury and (2) an indication (by vacuum
increase) of the buildup of particulate matter on the filter
media. The leak check is performed at 38 cm of mercury because
water starts to boil at higher vacuums and will tend to
saturate the silica gel (desiccant).
2. A leak-free vacuum pump is required for the sampling train
described in the reference method. At this time there are
12
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two commonly used vacuum pumps: (1) a modified sliding
fiber vane pump and (2) a diaphragm pump. The vacuum pump
must not bias the recorded sample volume (refs. 4,5).
3. A calibrated dry test meter with a temperature measuring
system to determine the average temperature of the gas
flowing through the meter and the total sample volume,
respectively, is required.
4. A calibrated orifice meter is used to monitor the sample
flow rate.
5. A dual inclined manometer or its equivalent is used to
measure the velocity head, AP, in the source duct and the
pressure drop, AH, across the calibrated orifice meter.
Maintenance instructions for an inclined manometer are
contained in section 2.1.1.IB of the Quality Assurance
Document for Method 2. The differential pressure system
must have an accuracy of + 1.0 percent for any given reading.
6. A reproducible heating system is required to maintain the
probe at a temperature which prevents condensation prior
to the collection system (impinger).
7. A temperature measuring system is required to monitor the
stack gas temperature and the effluent gas temperature as
they exit from the last impinger.
2.1.2 Sample Recovery.
2.1.2.1 Glass Wash Bottles. Two or more glass wash bottles are needed for
quantitative recovery of collected samples.
2.1.2.2 Glass Sample Storage Containers. Two 1-i glass sample bottles are
required for each collected sample plus two glass containers to retain blanks
for each absorbing solution utilized in testing.
2.1.2.3 Graduated Cylinders. Two graduated cylinders (glass), 250 cu. and
1,000 mi, are required for sample recovery.
2.1.3 Analysis.
2.1.3.1 Pipettes. Several pipettes (volumetric, Class A), including 25 mi
and 100 mJl, are required.
13
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2.1.3.2 Burette. A 50-nA standard burette Is required for filtrations.
2.1.3.3 Erlenmeyer Flasks. Several 250-mJl Erlemneyer flasks are required for
filtration vessels.
2.1.3.4 Graduated Cylinder. One 100-mA graduated cylinder is needed for
additions of isopropanol.
2.1.3.5 Balance. One trip or top-loading balance with 300-g capacity and an
accuracy of + 0.05 g is required.
2.1.3.6 Dropping Bottle. One bottle (eye dropper) to add indicator solution
is required. This bottle (if needed for storage) should be of polyethylene,
since the indicator tends to deteriorate if stored in glass (ref. 3).
14
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2.2 PRESAMPLING PREPARATION
2.2.1 Preliminary Site Visit (Optional).
The primary objective of a preliminary site visit is to gather information
to design and implement an efficient source test. Prior preparation will result
in the prevention of unwarranted loss of time, unnecessary expenses, and injury
to test and/or plant personnel. A test plan developed from a thorough set of
parameters will result in more precise and accurate results. Test experience
and a complete repertoire of equipment may allow dropping the preliminary site
visit.
2.2.1.1 Process (Background Data on Process and Controls). It is recommended
that the testers, before a preliminary site visit is made or before performing
tests, become familiar with the operation of the plant (source). Data from
similar operations that have been tested should be reviewed if they are avail-
able. Background data on stack gas species should be noted for further consid-
eration of the final analytical results.
2.2.1.2 Sampling Site Preparedness. Each facility tested should provide an
individual who understands the plant process and who has the authority to make
decisions concerning plant operation to work with the team. This would include
decisions concerning whether the plant would be operated at normal load condi-
tions or at a rated capacity. If the source is cyclic in nature, information
must be made available as to the timing of the sequence and the duration of
the cycle. This individual or individuals will supervise installation of ports,
sampling platform, and electrical power. If the above installations are
already in existence, they must be examined for their suitability for obtaining
a valid test and for meeting minimum safety standards. If ports have to be
installed, specify 8- or 10-cm ports with plugs. Port locations should be
based upon Method 1 of the Federal Register (ref. 1). Port locations must be
based upon existing technical knowledge and sound judgment. An electrical
service should be available at the sampling area with 115-volt and 20-anp
service.
2.2.1.3 Stack Gas Conditions. The following should be determined on the
initial site survey, either by measurement or estimation:
15
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Tg = average stack gas temperature
avg
P = the static pressure (positive or negative)
s
AP = the average velocity heads,
% HO = moisture content,
M = gas constituent concentration.
S
The above parameters can be roughly determined using an inclined manometer
(0 to 12 cm), a Type-S pitot tube manual thermometer, or thermocouple attached
to the pitot tube with potentiometric readout device. The moisture content
(approximate) can be determined with a wet bulb/dry bulb (acid gases >10 ppm
SO will result in high results) technique or by condensation (Method 4) and
the gaseous constituents by hand-held indicator kits. Nomographs are useful
in checking and estimating preliminary data required (ref. 6).
2.2.1.4 Method and Equipment for Transporting Apparatus to Test Site. The
preliminary site visit (or correspondence) should include a logical plan
developed by the plant personnel and the tester on how the equipment can best
be transported to the sampling site. A presampling area must be designated
in which absorbing solution can be prepared and added to the collection system.
In addition to the above, it is recommended, when permitted, that pictures be
taken of the hoisting area and sampling area (ports, sampling platform) so
that any further discussion will be clarified.
2.2.2 Apparatus Check and Calibration.
2.2.2.1 Sampling Train. The design specifications of the H SO /SO train
used by EPA are given in appendix A of this document (figure 8-1). Commercial
models of this system are available. Each individual or fabricated train must
be in compliance with the specifications in the reference method. Each
individual train must be examined to see if it is in compliance with the
specifications in APTD-0581 or its equivalent (ref. 7). In addition, the
Office of Air Programs Publication No. APTD-0576, "Maintenance, Calibration,
and Operations of Isokinetic Source-Sampling Equipment" is a valuable
reference (ref. 8).
16
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2.2.2.2 Probti. Check the probe in the following manner:
1. Disassemble probe and check for breakage of inner liner or
damage to other parts of probe.
2. Clean all metal parts with acetone.
3. Reassemble probe, clean inner liner with brush with the
following solvents: tap water, D.I. water, and acetone.
In extreme cases, the glass liner can be cleaned with
stronger cleaning reagents.
4. Check to see if probe will heat to required temperature
(>175° C). The probe temperature can be profiled with a remote
reading thermometer or by a thermocouple with readout device.
5. The probe should be sealed on the nozzle side and checked for
leaks at a vacuum of 38 cm of mercury.
6. Cover open ends of probe with serum caps or equivalent.
At temperatures greater than 125° C or if asbestos string has been used as a
gasket between the glass probe and the union holding the nozzle to the probe
and probe sheath, there exists the probability of leakage. Most stacks have
a negative pressure; therefore, a leak would introduce diluent air into the
system and result in a low bias. This problem can be eliminated by:
1. sealing the sheath from the outside air with a rubber
stopper or its equivalent (ref. 7), and
2. drilling a 0.3-cm (1/8-inch) hole in the sheath on the opposite
side of the pitot tube just behind the nut.
This modification also prevents "out" gases from deterioration of the probe
from contaminating the stack sample (ref. 9).
2.2.2.3 Nozzle. Upon the purchase of each new nozzle, measure the inside
diameter to the nearest 0.0025 cm using a micrometer. Make 10 individual
measurements using different diameters each time, and calculate an average
diameter. The range (i.e., the difference in smallest and largest values) of
the 10 measurements should not exceed 0.0125 cm. Number the nozzle, and
record the number and diameter of the nozzle to the nearest 0.0025 cm in the
laboratory calibration log book. The diameter of the nozzle should be
visually checked before each field test. Nozzles should have a sharp knife
edge and be made of thin-walled tubing.
17
-------
2.2.2.4 Type-S Pitot Tube Against a Standard Pitot Tube. The Type-S pitot
tube should be calibrated against a standard pitot tube (or an NBS-calibrated
Type-S pitot tube) as recommended in the Quality Assurance Document: for Method
2. The Type-S pitot tube coefficient varies from one tube to another, as a
function of air velocity for the same pitot tube and according to its proximity
to the sampling probe and/or temperature sensor. For these reasons, it is
important to calibrate the Type-S tube over the velocity range that is expected
in the field operation and to orient the tube, probe, and temperature sensor
as shown in figure 8-1 of appendix A. For a detailed description and discus-
sion of the calibration procedure, see the Quality Assurance Document for
Method 2 (Determination of Stack Gas Velocity and Volumetric Flow Rate).
2.2.2.5 Stack Gas Temperature Measuring Device. A temperature measuring
device attachable to a pitot tube* and capable of measuring the stack gas
temperature to within 1.5 percent of the minimum absolute stack gas temperature
is required. A high-quality mercury bulb thermometer calibrated at ice water
and boiling water (corrected for local pressure) temperatures and readable to
the nearest 0.1° C is an acceptable laboratory standard for calibration of
temperature measuring devices. The calibration procedure is contained in
section 2.1.2.2 of the Quality Assurance Document for Method 2.
2.2.2.6 Dry Gas Meter and Orifice Meter. An initial check should be made of
the sampling train to check for proper operation of the pump, dry test meter,
vacuum gauge, and dry test meter thermometer(s). After the meter system
components have been checked, the vacuum system should be leak tested. This
is done by plugging the inlet side of the metering system, pulling a vacuum of
60 cm of mercury, and observing the dry test meter. If the leakage exceeds
-4 3
1.5 x 10 m /min, the leak(s) must be found and minimized until the above
specification is satisfied.
The dry gas meter should be calibrated before and after each field trip.
The after-calibration for one test serves as the before-calibration for the
next test. Calibration is performed by making simultaneous total volume
*See figure 8-1, appendix A, for spacial arrangement of temperature probe
relative to pitot tube orifice.
18
-------
measurements with a calibrated wet test meter and the dry gas meter in the
meter box. The wet test meter should be calibrated periodically against a
primary standard. The wet test meter must be of the proper capacity and
accuracy. For commercial sampling trains the wet test meter capacity must be
3
at least 0.03 m /revolution with a +1 percent accuracy. The wet test meter
must be of the proper capacity; otherwise, at the higher flow rates the linkage
in the wet test meter will slip, producing an erratic correlation with 'the
volume recorded by the dry test meter. A dry test meter is unacceptable as a
calibration standard due to the inability to check for valve float in the dry
test meter. The recommended calibration procedures are as follows:
1. Check the sampling system (dry test meter) for valve
float in the following manner (ref. 10).
a. Operate the sampling system at orifice readings
between 0.1 and 12 cm of water. Initially operate
3
the system at 0.02 m /min for 10 minutes before taking
data.
b. Take data through the above range «0.003 and 0.03
3
m /-min, once with the bypass closed and once with it
completely open. Time each setting for 1 minute.
Record the AH setting (orifice reading) and the initial
and final volume on the dry test meter.
c. Calculate AH@ from the two sets of data:
K AH
AH@ = .
Plot two curves (one with the bypass valve opened and
the other with it closed) of AH@ vs. the volume (V)
recorded by the dry test meter. If the values are
floating, the two curves will not coincide. Ideally,
the curves should coincide and be horizontal over the
whole range; in practice, the curve will probably
have a slight slope. This initial check for valve
float is performed only once upon building or pur-
chasing a sampling train. This must be repeated
-4
K = 0.56 in English units and 4.49 x 10 in metric units.
19
-------
whenever a new pump is installed in the system.
Valve float, if present, must be corrected.
2. Determination of AH@ and y is as follows:
a. The wet test meter is placed upstream of the sampling
system with its outlet connected to the inlet (sample
umbilical connection) of the meter box (ref. 4). These
connections must be leak free.
b. Operate the pump for 15 minutes to warm up the purrrp
and wet the surface of the wet test meter (~0.02 m~/min).
c. Collect and record as shown in figure 2 the calibration
data by setting AH on the orifice manometer and letting
a given volume of air pass through the wet test meter
(the larger the volume, the greater the accuracy).
Repeat the above procedures until the data are collected.
Always have the bypass valve opened. A stop watch or
laboratory timer is used to record the elapsed time (9)
of the calibration. The symbols in figure 2 are:
V = Gas volume passing through the wet test
3
meter, m
V = Gas volume passing through the dry test
meter, m
t? = Temperature of the gas in the wet test
meter, °C
t = Temperature of the inlet gas of the dry
i
test meter, °C
t = Temperature of the outlet gas of the dry
d
test meter, °C
t, = Average temperature of the gas in the dry
test meter, obtained by the average of t,
and t, , °C i
a
o
0 = Time of calibration run, minutes
AH = Orifice manometer setting, with a resultant
orifice meter pressure drop in cm of HO
20
-------
Date _
Calibration by
Wet test meter No.
Barometric pressure,
Dry gas meter No.
cm Hg
Wet test meter capacity
Date of wet test meter calibration
Orifice
manometer
setting,
AH,
(cm n?0)
0.21
0.50
0.7£.
1.25
2.5
3.75
5.0
6.2B
7.5
10.0
15.0
20.0
Gas volume
wet test
meter
^
0.075
0.075
0.075
0.150
0.150
0.3
0.3
0.3
0.3
0.3
0.3
0.3
Gas volume
dry gas
meter
v^
Temperature
Wet test
Meter
V
°c
Dry gas meter
inlet
*d1'
°C
Outlet
V
•c
Average
V
•c
Time
0,
min.
Average
Y
AH@
Calculations
AH
0.25
0.30
0.75
1.25
2.5
3.75
5.0
6.25
7.5
10.0
15.0
AH
13.6
0.0184
0.0368
0.0552
0.0920
0.1840
0.2760
0.3680
0.4600
0.5520
0.7360
1.1040
Y
Vb (td * 273)
vd pb + fie <** + 273>
AH@
0.0012 AH (tw + 273)e-j z
Pb (td + 273) Vw
Is -J
Figure 2. Wet test meter calibration data.
21
-------
Y = Ratio of accuracy of wet test meter to dry
test meter. Tolerance - +0.02
AH@ * Orifice pressure differential that gives
0.02 m3/min of air at 20°C and 76 cm of
mercury, in cm of HO. Tolerance = +0.40.
Calculate y and AH@ for each orifice manometer setting
and record on the calibration sheet as depicted in
figure 2. Plot curves of y and AH@ versus AH (orifice
manometer setting in cm of HO). The value of Y should
be 1.0 + 0.02. Adjust the linkage of the dry test: meter
(if needed) as directed by the manufacturer until this
tolerance is obtained. The value of AH@ should be 4.7
+0.7 with a variability of +0.40 over the range of
1.25 to 20 cm of water across the orifice. If this is
not obtained, adjust the orifice opening or replace the
orifice as directed in "Construction Details of Isokinetic
Source Sampling Equipment" (ref. 5) and recalibrate.
2.2.2.7 Pump. The vacuum pump should be serviced as recommended by the
manufacturer every 3 months or upon resultant erratic operations. Additional
pump oil, if applicable, should be available for field work.
2.2.3 Reagents and Miscellaneous Equipment.
2.2.3.1 Sampling. The first impinger reagent, which consists of 80 percent
Isopropanol*, is prepared by mixing 800 m£ alcohol with 200 m& of deionized,
distilled water. The second and third impinger absorbing reagent (hydrogen
peroxide, 3 percent) is prepared by diluting 100 m& of 30-percent hydrogen
peroxide to 1 £ with deionized, distilled water. Preweighed containers with
250 g silica gel (indicating type 6-16 mesh, dried at 175° C) are required
for sampling (one per test).
2.2.3.2 Sample Recovery. Deionized, distilled water will be required on
site for quantitative transfer of impinger solutions to storage containers.
*Tbe isopropanol must be peroxide free, to avoid oxidation of SO- and high
values for acid mist (ref. 27).
22
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2.2.3.3 Source Sampling Tools and Equipment. The need for specific tools and
equipment will vary from test to test. A listing of the most frequently used
tools and equipment is given below.
1. Equipment Transportation
a. Lightweight hand truck that can be used to transport
cases and be converted to a four-wheel cart for sup-
porting the meter box control unit;
b. A 1.3-cm (1/2-inch) continuous filament nylon rope with
large boat snap and snatch block for raising and lowering
equipment on stacks and roofs;
c. Tarpaulin or plastic to protect equipment in case of
rain; sash cord (0.6 cm) for securing equipment and
tarpaulin;
d. A canvas bucket is useful for transporting small items.
up and down the stack.
2. Safety Equipment
a. Safety harness with nylon and steel lanyards, large
throat snap hooks for use with lanyards for hooking
over guardrails or safety line on stack;
b. A fail-safe climbing hook for use with climbing
harness when climbing ladders having a safety cable;
c. Hard hats with chin straps and winter liners, gas
masks, safety glass and/or safety goggles;
d. Protective clothing including the following: appropriate
suits for both heat and cold, gloves (both asbestos and
cloth), and steel-toed shoes;
e. Steel cable (0.5 cm) with thimbles, cable clips and
turn buckles; these are required for installing a
safety line or securing equipment to the stack structure.
3. Tools and Spare Parts
a. Electrical and Power Equipment
1. Circular saw
2. Variable voltage transformer
3. Variable speed electrical drill and bits
23
-------
4. Ammeter-voltmeter-ohmeter (VOM)
5. Extension cords - light (#14 Avg) 2 x 25
6. Two or three wire electrical adapters
7. Three wire electrical
8. Thermocouple extension wire
9. Thermocouple plugs
10. Fuses
11. Electrical wire
Tools
1. Tool boxes (one large and one small)
2. Screwdrivers
one set flat blade
one set Philips
3. C-clamps (two), 15 cm and 7.5 cm
Wrenches
1. Open-end set, 1/4 inch to 1 inch
2. Adjustables (12 inch and 6 inch)
3. One chain wrench
4. One 12-inch pipe wrench
5. One Allen wrench set
Mis cellaneous
1. Silicone sealer
2. Silicone vacuum grease
3. Pump oil
4. Manometers (gauge oil)
5. Antiseize compound
6. Pipe fittings
7. Dry cell batteries
8. Flashlight
9. Valves
10. Thermometers (Dial, 15 to 90 cm) and a
remote reading thermometer (stack)
11. Vacuum gauge
12. SS tubing (0.6, 0.9, 1.2 cm), short lengths
13. Heavy-duty wire (telephone type)
14. Adjustable packing gland.
24
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2.2,3.4 Data Recording. Pack one large briefcase with at least the following:
1. Nomograph for maintaining isokinetic conditions
2. Data sheets or data notebook
3. Carbon paper
4. Slide rule or electronic calculator
5. Psychrometric charts
6. Combustion nomographs (refs. 3,9)
7. Pencils, pens
8. Calibration data, AH@, etc.
2.2.4 Package Equipment for Shipment.
This aspect of any source testing method in terms of logistics, time of
sampling, and quality of data is very dependent upon the careful packing of
equipment with regard to (1) accessibility in the field, (2) care of movement
on site, and (3) optimum functioning of measurement devices in the field.
Equipment should be packed with the assumption that it will receive severe
treatment during shipping and field operation. One major consideration in
shipping cases is the construction materials. Durable containers are the most
cost effective.
2.2.4.1 Type-S Pitot Tube and Probe. Pack the pitot tube and probe in a case
protected by polyethylene or other suitable packing material. An ideal con-
tainer is a wood case or equivalent (lined with foam) in which separate com-
partments are cut to hold the individual devices. It is also recommended that
inserts for the individual nozzles be provided. The case should have handles
that can withstand hoisting and be rigid enough to prevent bending or twisting
of the devices during shipping and handling.
2.2.4.2 Differential Pressure Gauge (Dual Inclined Manometer). Always close
all valves on the pressure gauge. Pack it in a suitable case for shipment.
Spare parts, such as 0-rings and gauge oil should also be packed.
2.2.4.3 Stack Temperature Measuring Device. The temperature measuring device
(thermocouple, thermistor, remote reading thermometer, etc.) should be protected
from breakage, i.e., placed in a tube or a suitable shipping container. If the
device is an integral part of the pitot tube, it can be shipped in the Type-S
pitot tube shipping case.
25
-------
2.2.4.4 Barometer. The barometer should be packed in a shock-mounted (spring
system) carrying case.
2.2.4.5 Pitot Tube Lines and Sample Line (Umbilical). All pitot lines and
sample lines should be coiled to use the smallest amount of space. The ends
should be connected together and sealed to prevent dust and dirt from impairing
their operation. For shipment all lines should be stored in a case (footlocker)
for protection and portability.
2.2.4.6 Glassware (Impingers, U-Joints, etc). A word of caution is needed in
the use of glassware. It is expensive and fragile, but with sensible handling
and packing, its failure rate and resultant costs are minimal. Generally,
breakage of glassware occurs during packing and movement to the sampling
facility. It is recommended that glass impingers be packed in a suitable case
(approximate dimensions 50 cm x 50 cm x 50 cm) with a three-tiered layer of
foam in which holes are cut to hold the glass bottom of the shipping case (ref.
10). A separate case lined with foam, with layers of 6-cm foam, can be used to
carry the rest of the individual glass joints, filter holders, and preweighed
filters. One major point to consider in shipping cases is the construction
materials. Durable containers, although more expensive to build, are the most
cost effective. A poorly constructed shipping case of cheap material will
quickly deteriorate.
2.2.4.7 Metering System (Meter Box Assembly). A standard (commercial) unit
including pump, vacuum gauge, dry test meter, inclined manometer, etc., is
contained in one meter box. This meter box should be placed in a shipping
container lined with a cushion material such as polyurethane. If the vacuum
pump is not integral to the meter box, it should be packed in a shipping con-
tainer unless its housing is sufficient for travel. Additional pump oil should
be packed with the pump if oil is required for its operation.
2.2.4.8 Sample and Sample Recovery. All glass wash bottles or glass storage
containers should be packed with cushion material at the top and bottom of the
case with some form of dividers to separate the components. One shipping case
can contain the preweighed silica gel, glass wash bottles, and graduated
26
-------
cylinders. A water container and ice chest can be shipped as is. It is
recommended in certain cases that these two items be purchased on site. A
rule of thumb in source testing is "when possible, always carry a spare."
27
-------
28
-------
2.3 ON-SITE MEASUREMENTS
The on-site measurement activities include transporting the equipment to
the test site, unpacking and assembling the equipment, making duct measurements
and traverse points, velocity traverse, determination of molecular weight and
stack gas moisture content (in certain cases the moisture content can be
assumed to be zero), sampling for sulfuric acid mist and sulfur dioxide, and
data recording.
2.3.1 Transport of Equipment to the Sampling Site.
The most efficient means of transporting or moving the equipment from
floor level to the sampling site is decided during the preliminary site visit
(or prior correspondence).. Care should be exercised against damage to the test
equipment or injury to test personnel during the moving phase. A "laboratory"
type area should be designated for preparation of absorbing reagents, charging
the Lmpingers, sample recovery, and documentation.
2.3.2 Preliminary Measurements and Setup.
2.3.2.1 Duct Measurement. Measure the duct and determine the number of
traverse points by Method 1 or check traverse points as determined from pre-
liminary site visit (ref. 1).
2.3.2.2 Sample Box Logistics. Once the sampling points are selected and the
probe has been marked with either a china marker or heat-bonding fiberglass
tape, the most efficient setup for the sample box must be determined. A poor
choice will create a back-breaking and time-consuming sampling experience.
Several systems exist for sampling ranging from duo rails to monorails in which
the sampling box slides on a rolling track. Each individual sampling situation
will dictate the system of the sample box support. It is recommended that one
modify his sampling box to allow at least two alternate methods of support.
2.3.2.3 Stack Gas Moisture Content. Determine the moisture content of the
stack gases by Method 4 or its equivalent (ref. 3). If the particular source
has been tested before or a good estimate of the moisture is available, this
should be sufficient. The reference method uses the condensate collected
during the sampling for the moisture content used in final calculations.
29
-------
2.3.2.4 Molecular Weight of Stack Gas. Determine the dry molecular weight of
the gas stream by Method 3. It is recommended that the sample be of the
integrated type for two reasons: (1) the possibility of a more representative
sample and (2) the convenience of taking the sample at the stack and being able
to transport the sampling bag to a more suitable area for Orsat analysis.
2.3.2.5 Stack Temperature and Velocity Heads. Set up and level dual inclined
manometer and determine the minimum and maximum velocity head (AP) and the
scack temperature (T ), This is done most efficiently with a Type-S pitot tube
s
with a temperature sensing device attached. The AP's are determined with an
inclined manometer by drawing the pitot tube across the stack diameter in two
directions (90° traverses). This must be done in order to pick the correct
nozzle size and to set the nomograph. Incorrect selection of nozzle si^e and/or
setting of the nomograph may result in one not being able to reach the iso-
kinetic rate, thereby voiding the sample. Determine the static pressure as
directed in the Quality Assurance Document for Method 2.
2.3.3 Sampling.
The on-site sampling includes final selection of proper nozzle size, setting
the nomograph, loading the filter media into the filter holder, preparation and
assembly of the sampling train, initial leak test, inserting the probe into the
stack, sealing the port, sampling isokinetically while traversing, recording
data, and a final leak check of the sampling system. Sampling is the foundation
of source testing. The most critical problems in testing result from poor or
incorrect sampling. The analytical technique (laboratory) can never correct
for errors made in the field either by poor judgment or instrument failure.
If the initial site survey, apparatus check and calibration, and preliminary
measurement and setup on site have been implemented properly, the testing should
go smoothly with a minimal amount of effort.
2.3.3.1 Preliminary Setting of the Nomograph. The setup of the nomograph using
the parameters obtained in section 2.3.2 is given in detail in APTD-0576 (ref.
8). The section pertaining to nomographs is reproduced in appendix B for
convenience of reference. A reference table is included in the appendix for
checking the nomograph for correct design.
30
-------
2.3.3.2 Select Nozzle Size. After the nozzle size and appropriate probe
length have been selected, insert the nozzle in the probe sheath union and
tighten the union. Do not use wrenches; finger-tight is sufficient in most
cases. Uncontrolled pressure upon tightening the union will result in a broken
or cracked inner liner. The above precautions only apply to a glass probe.
Keep the ball joint and nozzle tip protected from dust and dirt with a serum
cap or equivalent. The presence of excess particulates in analytical filtra-
tion can cause an interference.
Caution; If the coefficient, C , of the Type-S pitot tube
being used is outside the range of 0.85 + 0.02,
2
compute the ratio (C /0.85) and multiply this
constant by the correction factor, C, obtained
from the nomograph. Use this new "C" factor in
setting the nomograph for isokinetic sampling
(see appendix B for further discussion).
2.3.3.3 Preparation and/or Addition of Absorbing Reagent to Collection System.
If preparation of absorbing reagent is necessary on site (all reagents should
be prepared fresh daily), follow directions as given in section 2.2.3.1 of this
document. Place 100 mfc (measured with a graduated cylinder) of 80% isopropanol
in the first impinger, 100 m& of 3% hydrogen peroxide in both the second and
third impingers, and approximately 250 g of silica gel in the fourth impinger.
The silica gel can be preweighed if a moisture determination is applicable.
The first and third impingers are of the Greenburg-Smith design with standard
tip. The second and fourth are of the Greenburg-Smith design with 1.25 cm
(1/2-inch) I.D. glass tube extending to 1.25 cm (1/2 inch) from the bottom
of the impingers.
2.3.3.4 Assembling Sampling Train. Assemble the glass impinger train as
follows:
1. Load the filter, making certain that the filter is centered
correctly in the holder with the sample sides toward the
probe. The filter should be tightened until the two halves
are secure. Overtightening the two halves can break the
filter holder or tear the filter.
31
-------
2. Seal the inlet of the filter holder and leak check at
>3B cm of Hg vacuum. The filter should be leak free.
3. Place the impingers and filter into the sample box and
assemble the sampling train.
4. A very light coat of silicone lubricant should be
applied to assure a leak-free system.
Note; Apply the lubricant in a manner to minimize or
prevent contact with the sample.
2.3.3.5 Leak Check. Leak check the sampling train by plugging the inlet to
the first impinger, turning on the vacuum pump, and opening the valve system
until the vacuum in the system reaches 38 cm of mercury. A leakage rate not
in excess of 0.005 m /min at 38 cm of mercury is acceptable. To release the
pressure in the system, do not turn off the pump until the following sequence
has been completed:
1. Slowly release the pressure in the system by carefully opening
(twisting) the glass ball in the inlet of the filter holder.
2. Shut the coarse valve (main vacuum valve).
3. When the vacuum gauge reads zero vacuum, remove the glass
ball and shut down the pump.
2.3.3.6 Installation of Probe. Mount the probe in the sampling box and connect
the probe to the inlet of the first impinger and leak check in the following
manner:
1. Seal the inlet of the probe nozzle with a serum cap.
2. Turn on vacuum pump.
3. Open the valve system and adjust the vacuum to 38 cm of
mercury.
4. Check the leak rate on the dry gas meter. A leakage rate
3
not in excess of 0.0005 m /min at 38 cm of mercury is
acceptable.
5. After completion of the leak check, release the pressure
as follows:
a. Slowly release vacuum by carefully opening
(squeezing) the serum cap until the system
32
-------
pressure is back to ambient (monitor with
built-in vacuum gauge);
b. Turn valve system off (coarse valve);
c. Turn off the vacuum pump.
Note: Operations 2.3.3.5 and 2.3.3.6 can be
combined, thereby requiring only one
initial leak check.
2.3.3.7 Taking of Sample. Turn the probe heater to its normal setting to
obtaLn 175° C. The meter box operator should now recheck his setting of the
nomograph while the sample box operator checks the ice around the impingers
and Couches the probe to see if it is heating properly. It is recommended that
a thermocouple be mounted next to the glass liner so that the probe temperature
can be monitored. One must realize that this probe temperature is just a point
measurement of the probe skin temperature. In lieu of this, the operator can
use his hand to check if the probe is heating properly.
As soon as the probe temperature is up to 175° C, the test can be per-
formed. During this time period prior to taking of the sample, record the
barometric pressure on the data log sheet.
1. Remove the plug or cap from the sampling port and remove the
dust (particulates) in the port walls by using a wire brush
or its equivalent. Remove the serum cap from the nozzle tip.
Record the initial volume of the dry test meter on the data
log sheet.
2. If the sample gas is hot, start at the traverse point
farthest from the port and draw the probe out as the test
continues. Asbestos gloves should be used in handling hot
sampling probes and pitot tubes.
3. Attach a proper electrical ground to the probe and
sampling system.
4. Insert the probe to the farthest traverse point with the
nozzle pointing directly into the gas stream and
immediately start the pump and adjust the coarse- and
fine-adjust valves until isokinetic conditions are
obtained. Note the time and record it on the log sheet.
33
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Maintain isokinetic conditions during the entire sampling
period. Sample an equal amount of time at each traverse
point. The time at each traverse point should be long
enough to set the sample rate and record the required data.
While sampling, reset the nomograph if:
a. The temperature in the stack changes more than + 15° C
for T < 550° C or + 30° C for T > 550° C, or
s — x
b. T (average temperature of meter) varies more than
m
± 5° C.
Note; The commercial nomographs are set up assuming
the composition of the stack gas is air
(Molecular weight -29+20 percent). An adjust-
ment must be applied when sampling streams other
than air.
Adjust the sampling rate for every point, and maintain the
isokinetic rate by continuous observation. Record the meter
volume at the end of sampling at each individual traverse point.
Take readings at each sampling point at least every 5 minutes
(or during sampling period at each traverse point). When
significant changes in stack conditions are observed, compen-
sating adjustments in flow rate should be made to maintain
isokinetic conditions. Record the traverse point number, stack
temperature (T ), velocity pressure head (AP cm of H_0), AH
s 2.
(orifice pressure differential, cm of H.O), gas temperature at
dry gas meter (T and T or T , °C), sample box tempera-
min mout av^
ture, condenser temperature, and the probe temperature if the
probe has a thermocouple and appropriate readout.
When sampling at one traverse point has been completed, move
the sampler to the next point as quickly as possible. Close
the control valve only when transferring the sampler from one
sample port to the other. Exclude the time required to transfer
the sampler from one port to another from the total sampling time,
Note: Movement from port to port is time consuming, and it is
recommended that longer probes be employed to allow only
34
-------
one move during a test if it is a circular stack. Probes
up to 10 feet can be managed without too much difficulty
provided there is adequate space on the sampling platform.
a. Monitor the vacuum through the system. An indication of
particulate buildup on the filter is an increase in vacuum.
Excess particulates could cause interference in the wet
chemical analysis. Loss in vacuum is an indication of a
broken impinger, connector, filter, or possibly a loose
connection.
b. Keep the impingers iced down (i.e., monitor the condenser
temperature) to hold the temperature below 20° C. Add
salt to the ice bath if necessary.
c. Check the line voltage with a voltmeter.
Caution; Digital temperature systems may read
erroneously with a drop in line voltage.
d. Make sure that the dual inclined manometer is level and that
the pitot lines and pitot tube are unobstructed. A signal
of trouble would be AP's not representative of the velocity
heads obtained in a preliminary site visit velocity traverse.
e. All data should be recorded on a log sheet as depicted in
figure 8-2 of appendix A. In addition, a column can be
added for recording the temperature of the probe if so
desired and the sample box reading can be changed to condenser
exit temperature.
7. At the completion of the test, close the coarse control valve on
the meter, remove the probe from the stack, and turn off the pump.
Place a serum cap or equivalent over the nozzle tip and leak check
the system at 5 cm of mercury vacuum above the operating vacuum
during the test. The leak-test vacuum should be no greater than
38 cm of mercury. (Do not boil the water in the impingers.) Follow
the same leak-test procedures as outlined in section 2.3.3.6. Seal
the end of the nozzle and disconnect the probe. Drain the ice bath
and purge the remaining part of the train by drawing clean ambient
air through the system for 15 minutes. Disconnect the pitot lines
35
-------
and umbilical. Protect pitot and umbilical connections with tape
or an appropriate equivalent. Record on the data log sheet the leak
3
rate in m /min and the vacuum at which the leak check was performed.
Check all connectors such as umbilical connect, pitot lines, glass
connections, etc., for evidence of malfunctions. Record all abnor-
malities on the data log sheet. This will not necessarily void the
sample but may help to improve the quality of sampling performance'.
2.3.4 Sample Recovery.
The reference method requires a quantative transfer of the impinger solu-
tions and filter to suitable storage containers. These transfers should be
done in a "laboratory-type" area to prevent contamination of the test samples.
2.3.4.1 Impinger Solution (80% Isopropanol). Recover impinger solution as
follows:
1. Transfer the isopropanol solution from the first impinger to a
250 m£ graduate cylinder.
2. Rinse the probe, first impinger, and all connecting glassware before
the filter with 80% isopropanol. Add the rinse solutions to the
250 m£ graduate.
3. Dilute to 250 m£ with 80% isopropanol.
4. Add the filter to the solution, mix, and transfer to a suitable
storage container.
Note: Record initial solution volume and total
rinse volume.
2.3.4.2 Impinger Solutions (3% Hydrogen Peroxide). Recover the impinger
solutions as follows:
1. Transfer the solution from the second and third impingers to a
1,000-mJl graduated cylinder.
2. Rinse all glassware between the filter and silica gel impinger with
deionized, distilled water and add the rinse water to the cylinder.
3. Dilute to a volume of 1,000 ro& with deionized, distilled water.
Transfer the solution to a suitable storage container.
Note; Record initial total impinger solution volume and
total rinse volume.
36
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2.3.5 Sample Logistics (Data) and Packing of Equipment.
The above procedures are followed until the required number of tests are
completed. If the glassware (impingers and connectors) are used in the next
test, they should be rinsed with distilled water (impingers and connectors)
and then with 80% isopropanol (first impinger). New silica gel should be added
to the sampling train. The following is recommended at the completion of
testing:
1. Check all sample containers for proper labeling (time and date of
test, location of testing, number of test, and any pertinent
documentation).
2. All data recorded during field testing should be recorded in
duplicate by carbon paper or by utilizing data sheets and a field
laboratory notebook. One set of data should be mailed to the base
laboratory and the other hand carried. This is a recommendation
that can prevent a very costly and embarrasing mistake.
3. All sample containers and equipment should be examined for damage,
noted in log book, and properly packed for shipment to the base
laboratory. All shipping containers should be properly labeled to
prevent loss of samples or equipment.
37
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38
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2.4 POST-SAMPLING OPERATIONS (BASE LABORATORY)
2.4.1 Apparatus Check.
2.4.1.1 Type-S Pitot Tube. The Type-S pitot tube is checked according to the
Quality Assurance Document for Method 2, Determination of Stack Gas Velocity and
Volumetric Flow Rate (ref. 11).
2.4.1.2 Dry Gas Meter and Orifice Meter (Sampling Train). A post check (a
post check for one test can serve as the presampling check for the next test)
should be made of the sampling train to check for proper operation of the pump,
dry test meter, vacuum gauge, and dry test meter thermometers. Leak check the
vacuum system. Determine Y and AH@ at 0.25, 0.8, 2.5, 5.0, 8.0, and 15.0 cm of
water as previously instructed in subsection 2.2.2.6 (2). This is a check on
the system for future testing and gives confidence in the data from the previous
field test. This is a recommended procedure to improve the data quality and to
prevent field sampling under assumed conditions.
2.4.2 Analysis (Base Laboratory).
The requirements for a precise and accurate analysis are an experienced
analyst and familiarity with the analytical method; calibration is of the utmost
importance, and neglect in this area cannot be accepted. The analytical method
is based on the insolubility of barium sulfate (BaSO.) and the formation of a
colored complex between barium ions and thorin indicator, [l-(O-arsonophenylazo)
-2-naphthol-3, 6-disulfonic acid, disodium salt], Aliquots from the impinger
solution are analyzed by titration with barium perchlorate to the orange-pink
endpoint.
2.4.2.1 Reagents (Standardization and Analysis).
1. Water—deionized, distilled.
2. Isopropanol.
3. Thorin indicator: l-(0-arsonophenylazo)-2-naphthol-3, 6-disulfonic
acid, disodium salt (or equivalent). Dissolve 0.20 g in 100 m&
distilled water.
4. Barium perchlorate: dissolve 1.95 g [Ba(C10.) .3 H20] in 200 m£
distilled water and dilute to 1 i with isopropanol. Standardize with
sulfuric acid (H SO,).
39
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5. Sulfurlc standard (0.01 N): Standardize against 0.01 N NaOH which has
been previously standardized against potassium acid phthalate [CfH.
6 4
(COOH) Cook primary standard].
2.4.2.2 Standardization of Sodium Hydroxide (0.01 N NaOH). Dry the potassium
acid phthalate for 1 to 2 hours at 110° C and cool. Accurately weigh about 1 g
KHP into each of three 250-mJl Erlenmeyer flasks and dissolve in 25 to 50 raZ of
distilled, deionized water (preferably freshly boiled and cooled). Add two
drops of phenolphthalein indicator and titrate with 0.1 N sodium hydroxide (NaOH)
to the first pink color that persists for 30 seconds. The base (NaOH, 0.1 N)
can be purchased commercially or prepared from reagent-grade NaOH. The 0.0 IN
NaOH is prepared by pipetting 50 m£ of the standardized solution into a 500 m£
volumetric flask and diluting to the mark with deionized, distilled water. The
final concentration of the base will be the standardized value divided by 10.
This solution should be made up fresh for each set of sample titrations.
2.4.2.3 Standardization of Sulfur Acid vs 0.01 N NaOH. The 0.01 N sulfuric acid
is standardized by pipetting 25 mH of the H SO, solution into a 250-mi Erlenmyer
which contains 25 mfc of water. A blank should be prepared that contains 50 m&
of distilled, deionized water. Add two drops of phenolphthalein indicator and
titrate with the above standardized 0.01 N NaOH until the first permanent pink
color that lasts for 30 seconds. All standards should be done in triplicate.
At the completion of the titrations, calculate the normality as the mean of the
three values obtained. This solution should be made up fresh for each set
of sample titrations.
2.4.2.4 Standardization of Barium Perchlorate (0.01 N). Pipette 25 mH of
sulfuric acid standard (0.01 N) into a 125-mJl Erlenmeyer flask. Add 100 mH of
reagent-grade isopropanol and two to four drops of thorin indicator and titrate
to a pink endpoint using the 0.01 N barium perchlorate. Run a blank which
contains 25 mSL of deionized, distilled water and 100 vA of isopropaniol.
Standardizations should be done in duplicate. All Thorin titrations should be
done against a white background. This will facilitate the detection of the
pink endpoint (orange-pink color). (The analyst unfamiliar with this titration
should, for practice, carry out titrations on aliquots at low, medium, and high
concentrations. Pipette various aliquots of 0.01 N N SO., add four times this
volume of 100% isopropanol and titrate with barium perchlorate to become
40
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familiar with the endpoint.) The presence of particulate matter can make the
detection of this endpoint quite difficult (ref. 12). The standardization
should be repeated before each set of titrations or every month, whichever is
longer.
2.4.2.5 Sample Analysis.
2.5.2.5.1 Isopropanol Solution. Analyze the isopropanol solution as follows:
1. Shake the container holding the isopropanol and filter for 1 minute.
2. Allow the solution to settle for 3 minutes.
3. Pipette a 100-m£ aliquot of sample into a 250-m& Erlenmeyer flask.
4. Add two to four drops of Thorin indicator and titrate the sample with
barium perchlorate (previously standardized) to a pink endpoint.
5. Repeat steps 3 and 4 on a second aliquot.
2.4.2.5.2 Hydrogen Peroxide Solution. Analyze the hydrogen peroxide solution
as follows:
1. Shake the container holding the contents of the second and third
impingers.
2. Pipette a 25-m£ aliquot of sample into a 250-m£ Erlenmeyer flask.
Add 100 m£ of isopropanol.
3. Add two to four drops of Thorin indicator and titrate with barium
perchlorate to a pink endpoint.
Note: When Thorin titrations are being carried out,
a completely white background is mandatory to
distinguish the endpoint.
4. Repeat steps 2 and 3 on a second aliquot.
2.4.2.5.3 Blanks. Titrate all blanks identically as performed on the respec-
tive samples. All samples must be corrected for its respective blank.
2.4.3 Calculations.
Calculation errors due to procedural or mathematical mistakes can be a
large component of total system error. Therefore, it is recommended that every
third set of calculations be repeated or spot checked, preferably by a team
member other than the one that performed the original calculations. If a
difference greater than a typical roundoff error is detected, the calculations
41
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should be checked step by step until the source of error is found and corrected.
A computer program is advantageous in reducing calculation errors. A standard-
ized computer program could be developed to treat all raw field data. If a
computer program is used, the original data entry should be checked, and if
differences are observed, a new computer run made.
2.4.3.1 Sample Volume. Calculate the sample volume at standard conditions
(76 cm of mercury, 20° C) by using equation 8-1 of appendix A. Average the dry
gas meter temperatures ( Tmin (°C) and T^^ (°C) ) to obtain the average
temperature, Tffl (°C), of the gas flowing through the meter during the test.
Determine the average orifice pressure drop by totaling the AH values at
each traverse point and dividing by the total number of traverse points. Ori-
fice pressure readings and the calculated average in cm of water should be
rounded to two significant digits (e.g., 0.12 or 1.2).
2.4.3.2 Sulfuric Acid Concentration. Calculate the concentration of sulfuric
3
acid at standard conditions on a dry basis in g/m by using equation 8-2 of
appendix A. The volume of V , /V is determined by the total dilution volume
v soln a J
of the sample and the aliquot taken for titration.
2.4.3.3 Sulfur Dioxide Concentration. Calculate the concentration of sulfur
3
dioxide at standard conditions on a dry basis in g/m by using equation 8-3
of appendix A.
2.4.3.4 Emission Rates. The emission rates for H SO and S0_ are determined
by the equation ER = Q xC , ,. , where Q = volumetric flow rate of the
S tl_bU, (,oU_^ S
3 £. * i
effluent in m /hr at standard conditions on a dry basis as determined by the
Q
quality control document for Method 2 (ref. 11), and H?SO.(SO ) = the concen-
tration of sulfuric acid (sulfur dioxide), as determined in subsections 2.4.3.2
and 2.4.3.3, respectively.
42
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SECTION III MANUAL FOR FIELD TEAM SUPERVISOR
3.0 GENERAL
The term "supervisor" as used in this document applies to the individual
in charge of a field team. He is directly responsible for the validity and the
quality of the field data collected by his team. He may be a member of an
organization which performs source sampling under contract to government or
industry, a government agency performing source sampling, or an industry perform-
ing its own source sampling activities.
It is the responsibility of the supervisor to identify sources of uncer-
tainty or error in the measurement process for specified situ?tions and, if
possible, eliminate or minimize them by applying appropriate quality control
procedures to assure that the data collected are of acceptable quality.
Specific actions and operations required of the supervisor for a viable quality
assurance program are summarized in the following listing.
1. Monitor/Control Data Quality
a. Direct the field team in performing field tests according to the
procedures given in the Operations Manual.
b. Perform or qualify results of the quality control checks (i.e.,
assure that checks are valid).
c. Perform necessary calculations and compare quality control checks
to suggested performance criteria.
d. Make corrections or alter operations when suggested performance
criteria are exceeded.
e. Forward qualified data for additional internal review or to user.
2. Routine Operation
a. Obtain from team members immediate reports of suspicious data
or malfunctions. Initiate corrective action or, if necessary,
specify special checks to determine the trouble; then take
corrective action. Document the corrective action taken.
b. Examine the team's log books periodically for completeness and
adherence to operating procedures.
c. Approve data sheets, calibration checks, etc., for filing.
-------
3. Evaluation of Operations
a. Evaluate available alternative(s) for accomplishing a given
objective in light of experience and needs.
b. Evaluate operator training/instructional needs for specific
operations.
Consistent with the realization of the objectives of a quality assurance
program as given in section I, this section provides the supervisor with brief
guidelines and directions for:
1. Collection of information necessary for assessing data quality on an
intrateam basis;
2. The use of performance criteria to aid in the collection of data of
acceptable precision and accuracy;
3. Isolation, evaluation, and monitoring of major components of system
error.
The above three topics will be discussed in the order that they appear iri
this manual. In subsection 3.1 a method of assessing data quality on an intra-
team basis is given. This method involves calculating a sample standard
deviation using the six replicate runs required in a field test and calculating
90 percent confidence limits for the average of the six replicates.
Subsection 3.2 presents suggested criteria for judging equipment perform-
ance and frequency of calibration.
Directions for collection and analysis of information to identify trouble
and subsequently control data quality within acceptable limits are given in
the third subsection.
44
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3.1 ASSESSMENT OF DATA QUALITY (INTRATEAM)
Sulfuric acid concentration, (L, g *, and sulfur dioxide concentration,
Ccn , for a particular field test is the average of six replicates for each
S°2
concentration. Intratearn assessment of data quality as discussed herein pro-
vides for an estimate of the precision of the measurements. Precision in this
case refers to repeatability, i.e., the within-laboratory variability, and is
expressed as a coefficient of variation. This precision statement combines
variability due to process changes and random measurement errors. Measurement
bias (see subsection 4.1.2 for a discussion of bias) could occur from an error
due to sampling train leaks, insufficiently heated sampling probe, or failure
to sample proportionally. However, if the operating procedures given in the
Operations Manual are followed, the bias should be small in most cases. An
independent quality audit which would make possible a bias estimate is suggested
and discussed in section IV, the Management Manual.
3.1.1 Calculating Precision of Field Data.
Each field test is comprised of at least three sample runs. Using the
sample runs as replicates, a standard deviation can be calculated. This calcu-
lated standard deviation is a combined measure of the measurement and process
variabilities. The standard deviation is calculated by
1/2
V r- r\ *•
s{C} -
5
where s{c} = Standard deviation for the six concentrations
C.,., = Concentration for the i concentration
C = Mean concentration
throughout this document, C is used to mean a single concentration determina-
tion. The notation C is used to represent the result of a field test, and is
the average of six replicates. Since concentrations of two chemical species
are measured in Method 8, general statements about concentrations C and C can
be assumed to apply to both sulfuric acid and sulfur dioxide.
45
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and 5 = Number of concentration determinations minus 1, or the number of
degrees of freedom.
3.1.2 Reporting Data Quality.
It is recommended that the average measured sulfuric acid and sulfur
dioxide concentrations be reported with 90 percent confidence limits,. Assuming
the values of C are normally distributed (this is usually a valid assumption
since sample means tend to be normally distributed even for nonnormal parent
distributions) and using s{C} as calculated in 3.1.1 above to estimate the
standard deviations, confidence limits can be calculated for the true (L,
"H2S04
and C values using the Student t-distribution with r - 1 « 5 degrees of
b°2
freedom. This assumes no bias in the average values. The average rnea&ured
value with 90 percent confidence limits is reported as:
~C + 2.02 s{C>
o
where C - The average of six replicates, g/m
3
s{C} = Estimated standard deviation of C based on 6 replicates, g/m
2.02 = 95* percentile of the Student t-distribution with 5 degrees
of freedom which yields a 90 percent confidence interval.
For example, if for a given field test C » 2 g/m and s{c) was calculated to be
0.08 g/m , the reported value with 90 percent confidence limits would be
2.0 g/m3 + (2.02) (0.08 g/m3)
or the true concentration, C , would be assumed to be in the interval
1.84 g/m3 <_ C(t) j< 2.16 g/m3 .
The utility of the above statement follows from the fact that if this
procedure for computing confidence limits is followed, then 90 percent of the
time the true C value will be contained within the given limits (assuming that
C is not biased).
46
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3.2 SUGGESTED PERFORMANCE CRITERIA
Data assessment as discussed in the previous subsection is based on the
premise that all variables are controlled within a given level, thereby guard-
ing against large undetected biases in the measurement process. These levels
of suggested performance criteria are the values given in the Operations Manual
for determining when equipment and/or personnel variability is out of control.
Criteria for judging performance are summarized in table 1.
Table 1. Suggested performance criteria
Suggested criteria for field equipment performance:
(a) Dry gas meter: 0.98 <_ y <_ 1.02
(b) Barometer: + 5 mmHg
(c) Thermometers: + 1° C
(d) Stack temperature
measuring system: + 3° C
(e) Sampling train leakage: < 1 percent of sampling flow
rate at 250 mmHg
(f) Probe heating system: Uniform heating of probe, with
a minimum temperature of 175° C
at exit end and at a flow rate
of 2 fc/min at room temperature
Suggested criteria for analytical procedure;
(a) Duplicate samples: <_ 5 percent of mean
(b) Standard 0.01 N barium
perchlorate: < 0.0005 N of mean
47
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48
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3.3 COLLECTION AND ANALYSIS OF INFORMATION TO IDENTIFY TROUBLE
Ln a quality assurance program, one of the most effective means of pre-
venting trouble is to respond immediately to indications of suspicious data or
equipment malfunctions. There are certain visual and operational checks that
can be performed while the measurements are being made to help insure the
collection of data of good quality. These checks are written as part of the
routinfe operating procedures in section II. In order to effectively apply
preventative-type maintenance procedures to the measurement process, the super-
visor must know the important variables in the process, know how to monitor
the critical variables, and know how to interpret the data obtained from
monitoring operations. These subjects are discussed in the following subsections.
3.3.1 Identification of Important Variables.
Determination of the sulfuric acid and sulfur dioxide concentrations
requires a sequence of operations and measurements that yields as an end result
two numbers that serve to represent the average sulfuric acid and sulfur dio-
xide emission rates for that field test. There is no way of knowing the
accuracy, i.e., the agreement between the measured and true value, for a given
field test. However, a knowledge of the important variables and their charac-
teristics allows for the application of quality control procedures to control
the effect of each variable at a given level during the field test, thus pro-
viding a certain degree of confidence in the validity of the final result.
A functional analysis of this method of measuring sulfuric acid and
sulfur dioxide emission rates from a stationary source was made to try to
identify important components of system error. Also, results of a collaborative
study of Method 8 (ref. 13) showed the following: for sulfuric acid, the
precision was proportional to the mean concentration, (L, crv ; for sulfur dioxide,
V°4
the precision was independent of the mean concentration, Ccn . The numerical
b02
results were used as an estimate of overall system error, while the individual
error components were estimated using engineering judgment in a manner such
that their combined variability was consistent with overall system error.
Variability in emissions data derived from multiple restrictions includes
components of variation from:
49
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1. Process conditions,
2. Equipment and personnel in field procedures, and
3. Equipment and personnel in the laboratory.
In many instances, time variations in source output may be the most sig-
nificant factor in the total variability. In order to judge the relative
magnitudes of measurement variability and process output variability, process
parameters should be monitored througiout the test. Process information is
also required if the sulfuric acid and sulfur dioxide emission rates are to be
given as a function of fuel input. The exact process data to be obtained are
dependent upon the process being tested. In general, all factors which have a
bearing on the emissions should be recorded at approximately 15-minute intervals.
It is important to realize that the largest measurement errors can result
from poor technique, such as an insufficient purge of the sampling train after
sample collection, failure to maintain the probe at a given temperature, or
failure to adequately leak check the sampling train. Such deviations from
recommended procedures generally cannot be evaluated or corrected. It is impor-
tant to detect and eliminate such occurrences while the test is in progress.
Collaborative test results (ref. 13) indicate that most of the total variability
in the method occurs during sample collection rather than the analysis phase.
Sources of variation involving equipment include:
1. The dry gas meter,
2. The sampling probe heater,
3. Sampling train leaks,
4. Impinger solution temperature, and
5. Vacuum pump malfunctions.
These sources of variation are controlled either by a calibration or calibration
check before each field test or by special checks immediately before, during,
and immediately after the field test.
Assuming good technique, i.e., neglecting the possibility of gross errors
due to sampling and/or analysis mistakes, the major error sources of the
measurement process are discussed and the effect of each source on the measured
mass emission rates is estimated in a functional analysis (subsection 4.1).
The relationship of a particular variable or error source to the final measured
value should be obtained from this subsection, and a summary of the important
parameters is given. Specific subjects to be discussed include:
50
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1. Equipment calibration,
2. Sampling train leaks,
3. Proportional sampling,
4. Sample recovery,
5. Reagent standardization,
6. Sample blanks, and
7. Calculations.
3.3.1.1 Equipment Calibration. Equipment calibration is the crux of any
quality assurance program. It is important that the calibration procedure be
carried out correctly, that the calibration standards are properly maintained,
and that the frequency of calibration is adequate.
The quality assurance document of this series for Method 2 (ref. 14)
should be adhered to for calibration of apparatus used in determining the
volumetric flow rate of the source being tested.
The dry gas meter, including its temperature measuring device, is cali-
brated to achieve an acceptable level of accuracy in the sample volume at
standard conditions. An error in the sample volume is directly reflected in
the concentration measurements and subsequently in the mass emission rates.
3.3.1.2 Sampling Train Leaks. Sampling train leaks result in measured sample
volumes larger than the true sample volume. Leaks also introduce errors in
the collected H SO and SO that cannot be corrected in most cases. Sampling
train leaks must be kept sufficiently small so that the resulting error will
not significantly increase total system variability.
3.3.1.3 Anisokinetic Sampling. Anisokinetic sampling can occur from error in
the calibration constants of the pitot tube, orifice meter, and nozzle diameter.
It can also result to a lesser degree, usually from measurement error in the
moisture content and molecular weight of the stack gas. Errors from the above
sources will not be directly reflected in the percent of isokinetic sampling
calculation. Therefore, it is important to determine each parameter as
accurately as possible, either through calibrations or careful measurements.
Failure, or in some instances the inability, to make adjustment in the
sampling rate as the stack gas velocity varies can result in anisokinetic
sampling. Use of a nomograph can be a cause of anisokinetic sampling because
51
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of (1) any inaccuracy in the nomograph, (2) use of preset values for C , AH@,
P
and M (these errors can be eliminated by using actual values and adjusting the
correction factor on the nomograph), and (3) operator error in setting the
nomograph. The sum of these errors is quantified to a certain extent by the
percent of isokinetic sampling calculation.
Deviation from isokinetic sampling cannot be related directly to error in
the measurement process (see subsection 4.1). However, failure to maintain
isokinetic sampling conditions under otherwise normal operations reflects the
lack of alertness and, perhaps even the level of competency, of the field crew.
3.3.1.A Sample Recovery. Sample recovery, including purging of the sampling
train and rinsing of the impingers and connecting tubes to quantitatively re-
cover the sample, can be critical to the precision and accuracy of the measure-
ment .
3.3.1.5 Reagent Standardization. An error in the standardized barium perchlorate
solution (subsection 2.4.2.4) is directly reflected in the H SO, and S0_ con-
centrations and mass emission rates.
3.3.1.6 Sample Blanks. The use of blanks is important in correcting the
field sample for contaminants contained in the reagents and not part of the
collected sample. Also, the routine measurement of blanks should preclude
errors due to the use of contaminated reagents.
3.3.1.7 Calculations. Calculations for this method are known to be a major
source of error. Some calculations involve several terms and should only be
attempted (for the final report) at a desk or work table and preferably with
the aid of a calculator or at least a good slide rule. A computer program
using raw data as an input is highly recommended for making the final calcula-
tions .
As a check, it is recommended that all calculations be independently
repeated from raw data.
3.3.2 How to Monitor Important Variables.
In general, if the procedures outlined in the Operations Manual are
followed, the major sources of measurement variability will be in control.
It is felt, however, that the supervisor should visually check certain parameters
52
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and operations periodically while measurements are being made to insure good
operator technique and the proper use of equipment. The parameters and opera-
tions to check are the same as those recommended for the auditor as listed in
subsection 4.3.2.
Results of the calibration checks for the dry gas meter, rotameter,
thermometer, and pitot tube should be checked before each field test. Any item
of equipment not satisfying the suggested performance criteria of table 1
should be calibrated or replaced.
Also, actual involvement in or observance of such on-site operations as
(1) sampling train leak check before and after sample collection, (2) purging
the sampling train after sample collection, and (3) sample recovery should
serve as a means of monitoring these important operations.
There appears to be a need for more actual field data on several of the
parameters or variables involved in this measurement method in order to better
judge their influence on measurement variability. One of the most effective
means of identifying and quantifying important sources of variability is through
the use of quality control charts. Quality control charts will provide a basis
for action with regard to the measurement process; namely, whether the process
is satisfactory and should be left alone, or is out of control (or approaching
control limits) and action should be taken to find and eliminate the causes of
excess variability. The quality control charts can be evaluated after a period
of time to determine the range of variation that can be expected for each
variable charted under normal operating conditions.
For Method 8, five control charts are recommended as follows:
1. A chart for the successive BaCIO, normality determinations,
2. Range charts for duplicate determinations of both H-SO, and S°2
concentrations, and
3. Relative range charts for the CV of both "c and (L cn as determined
S02 24
from each set of six determinations.
It is good practice to note directly on control charts the reason for
out-of-control conditions, if determined, and the corrective actions taken.
It is also good practice to maintain control charts in large size, e.g., 8-1/2 x
11 inches or larger and to keep them posted on a wall for viewing by all con-
cerned, rather than have them filed in a notebook.
53
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3.3.2.1 Pitot Tube Calibration Coefficient. A sample control chart for pitot
tube calibration checks is given in the quality assurance document of this
series for Method 2, Determination of Stack Gas Velocity and Volumetric Flow
Rate (type-S pitot tube), page 38 (ref. 14).
3.3.2.2 Control Chart for Normality of Standardized Barium Perchlorate
Solution. For a given batch of standardized barium perchlorate, it is assumed
that later checks should not deviate more than + 5 percent from the otiginal
value. Using + 5 percent* as the action limits for checking and preparing new
reagents, a control chart for the standardized barium perchlorate solution can
be constructed. For this example, an original standardized value of 0.0100 N.
is used and the control chart would be as shown in figure 3. It is important
to recognize and attempt to determine the reason for trends away from the
assumed standard value of 0.01 N.
Each time the barium perchlorate solution is restandardized, that value
is plotted on the control chart and connected to the previous plotted value by
a straight line.
It is recommended that any time the most current standardization value
deviates more than + 5 percent from the original or the previous value, all
reagents used in standardizing the barium perchlorate solution should be
checked and/or restandardized. If no problems are detected in these reagents,
then a new batch of barium perchlorate should be prepared and standardized.
It is also recommended that the latest standardization value be used in
subsequent sample analyses.
3.3.2.3 Control Chart for Duplicate Samples. The within-laboratory standard
3
deviation (a) for the Method 8 analytical phase is estimated as 0.0035 g/m
for SO (ref. 13). If 2 a is taken as the warning limit magnitude and 3 a
as the action limit magnitude, a control chart can be constructed as in figure
4. The difference for duplicate analyses (to be made on two out of the six
samples taken per field test) is calculated as
Ml - C(1) - C(2)
*This is a suggested initial action limit, which should be tightened if expe-
rience indicates that better precision is either possible or necessary for
acceptable results.
54
-------
0.0105
0.0104
0.0102
0.0100
0.0098
0.0096
0.0095
UCL =0.0105
ORIGINAL NORMALITY
J-CL_= £.009 5
i i r
567
CHECK NUMBER
10
Figure 3. Sample control chart for standardized barium
perchlorate solution.
0.0105
0.0070
0.0035
0
ACTION LIMIT
WARNING LIMIT
1 2 2 4 5 6 7 8 9 10 1 1 12 1 3 14 15 16 1 7 18 19 20 21 22 23 24
DUPLICATE MEASUREMENT NUMBER
Figure 4. Sample control chart for range of duplicate
measurements of S0.
55
-------
where C,^ = Original determination of concentration
C(2\ = duplicate determination of concentration.
The magnitude of d (the number obtained, ignoring the sign), symbolized
as |d|, is plotted each time a duplicate measurement is made. The analysis
procedure, reagents, and apparatus should be checked and appropriate action
taken any time one of the following criteria is exceeded:
1. One point falls outside the control limit;
2. Two consecutive points fall between the warning limit and control
limit;
3. Seven consecutive points fall above the a line (on figure 4,
0.0035 g/m3).
When criterion 1 is exceeded, the six samples for that field test should
be reanalyzed, after the cause of the excess variability has been located and
corrected. Exceeding the second or third criteria will usually indicate poor
technique and the need for additional supervision/training.
Separate control charts should be kept for analysis of both sulfuric acid
and sulfur dioxide. The control chart for acid mist should plot |%d| rather
than |d|, since the precision of acid mist measurements is said to be propor-
tional to the mean concentration level.
It would be desirable to maintain separate control charts for the relative
range of CV of both SO and H SO, for each set of six determinations.
56
-------
SECTION IV MANUAL FOR MANAGER OF GROUPS OF FIELD TEAMS
4.0 GENERAL
The guidelines for managing quality assurance programs for use with Test
Method 8, Determination of Sulfuric Acid Mist and Sulfur Dioxide Emissions
from Stationary Sources, are given in this part of the field document. This
information is written for the manager of several teams for measuring source
emissions and for the appropriate EPA, State, or Federal administrators of these
programs. It is emphasized that if the analyst carefully adheres to the oper-
ational procedures and checks of section II, then the errors and/or variations
in the measured values should be consistent with the performance criteria as
suggested. Consequently, the auditing routines given in this section provide
a means of determining whether the stack sampling test teams of several organi-
zations, agencies, or companies are following the suggested procedures. The
audit function* is primarily one of independently obtaining measurements and
performing calculations where this can be done. The purpose of these guide-
lines is to:
1. Present information relative to the test method (a functional
analysis) to identify the important operations and factors;
2. Present a methodology for comparing action options for improving
the data quality and selecting the preferred action;
3. Present a data quality audit procedure for use in checking
adherence to test methods and validating that performance
criteria are being satisfied;
4. Present the statistical properties of the auditing procedure in
order that the appropriate plan of action may be selected to yield
an acceptable level of risk to be associated with the reported
results,
These four purposes will be discussed in the order stated in the sections
which follow. The first section will contain a functional analysis of the
test method with the objective of identifying the most important factors
*The independent audit is only one device available to a manager. He may also
wish (for example) to make quality control comparisons of field data obtained
within and among teams; i.e., to obtain CV and CV values from field data.
57
-------
which affect the quality of the reported data and of estimating the expected
variation and bias in the measurements resulting from equipment and operator
errors.
Section 4.2 contains several actions for improving the quality of the data;
for example, by improved analysis techniques, instrumentation, and/or training
programs. Each action is analyzed with respect to its potential improvement
in the data quality as measured by its precision. These results are then com-
pared on a cost basis to indicate how to select the preferred action. The cost
estimates are used to illustrate the methodology. The manager or supervisor
should supply his own cost data and his own actions for consideration. If it
is decided not to conduct a data audit, sections 4.1 and 4.2 would still be
appropriate as they contain a functional analysis of the reference method and
of alternative methods or actions.
There are no absolute standards with which to compare the routinely
derived measurements. Furthermore, the taking of completely independent
measurements at the same time that the routine data are being collected (e.g.,
by introducing two sampling probes into the stack and collecting two samples
simultaneously) is not considered practical due to the constrained environ-
mental and space conditions under which the data are being collected. Hence,
a combination of an on-site system audit, including visual observation of
adherence to operating procedures and a quantitative performance quality audit
check, is recommended as a dual means of independently checking on the source
emissions data.
The third section contains a description of a data quality audit procedure.
The most important variables identified in section 4.1 are considered in the
audit. The procedure involves the random sampling of n stacks from a lot size
of N = 20 stacks (or from the stacks to be tested during a 3-month period, if
less than 20) for which one firm is conducting the source emissions tests.
For each of the stacks selected, independent measurements will be made of the
indicated variables. These measurements will be used in conjunction with the
routinely collected data to estimate the quality of the data being collected
by the field teams.
The data quality audit procedure is an independent check of data collection
and analysis techniques with respect to the important variables. It provides
a means of assessing data collected by several teams and/or firms with the
58
-------
potential of identifying biases/excessive variation in the data collection
procedures. A quality audit should not only provide an independent quality
check, but also identify the weak points in the measurement process. Thus
the auditor, an individual chosen for his background knowledge of the measure-
ment process, will be able to guide field teams in using improved techniques.
In addition, the auditor is in a position to identify procedures employed by
some field teams which are improvements over the current suggested ones, either
in terms of data quality and/or time and cost of performance. The auditor's
role will thus be one of aiding the quality control function for all field
teams for which he is responsible, utilizing the cross-fertilization of good
measurement techniques to improve the quality of the collected and reported
data.
The statistical sampling and test procedure recommended is sampling by
variables. This procedure is described in section 4.4. It makes maximum use
of the data collected, and it is particularly adaptable to the small lot size
and consequently the small sample size applications. The same sampling plans
can be employed in the quality checks performed by a team or firm in its own
operations. The objectives of the sampling and test procedure are to charac-
terize data quality for the user and to identify potential sources of trouble
in the data collection process for the purpose of correcting the deficiencies
in data quality.
Section 4.4.4 describes how the level of auditing, sample size n, may be
determined on the basis of relative cost data and prior information about the
data quality. This methodology is described in further detail in the final
report on the contract. The cost data and prior information concerning data
quality are supplied to illustrate the procedure and these data must be
supplied by the manager of groups of field teams depending upon the conditions
particular to his responsibility.
Figure 5 provides an overall summary of the several aspects of the data
quality assurance program as described in these documents. The flow diagram
is subdivided into four areas by solid boundary lines. These areas corres-
spond to specific sections or subsections of the document as indicated in the
upper right hand corner of each area. The details are considered in these
respective sections of the document and will not be described here.
59
-------
Pollutant
Measurement
Method
Functional
Analysis
Subsection 4.1
Estimate Ranges
and Distributions
of Variables
_L
Identify and Rank
Sources
Bias/Variation
Perform Overall
Assessment
Section III
Develop Standards
for Q. C.
Procedure
Subsection 4.2
Institute
QC Procedure
for Critical
•Variables
No
QC
Procedure
Indicates
Measurement
Process
OK
Continue to Use
Measurement Meth.
as Specified
(Optional)
No
Evaluate Action Options
for Improving Data
Quality
Select Optimal
Action and
Implement
Modified
Measurement
Method
Subsections 4.3 and 4.4
Develop Standards
for Audit Procedure
Quality Using
Audit Data
Data
Quality
Satisfactory
Yes
Continue to Use
Measurement Method
as Specified
Figure 5. Summary of data quality assurance program.
60
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4.1 FUNCTIONAL ANALYSIS OF THE TEST METHOD
Test Method 8, Determination of Sulfuric Acid and Sulfur Dioxide Emissions
from Stationary Sources, is described in the Federal Register and reproduced in
appendix A of this document. This method is used to determine the concentrations
of sulfuric acid and sulfur dioxide in stack gas. Results from this method
combined with the volumetric flow rate as measured by Method 2 yield sulfuric
acid and sulfur dioxide emission rates for the source being tested.
A functional analysis of the measurement process is performed to identify
and, where possible, quantify important sources of variability. Estimates of
the error ranges associated with intermediate measurements are made using pub-
lished data if available, and engineering judgment if data are not available.
Extensive use is made of the results from a collaborative test of the method
(ref. 13) for overall variability and for the division of variability due to
the sample collection and analysis phases of the process. A variance analysis
is performed to show the influence of the intermediate measurements on the
measured sulfuric acid and sulfur dioxide concentrations and the emission rates.
The functional analysis is discussed in two parts. First, the governing
mathematical relationships are given, and estimated means and coefficients of
variation are given for each variable. A variance analysis is then performed,
identifying the most critical variables. An approximate model is given for
estimating overall variability, using only the most critical variables.
Special symbols and definitions used in the functional analysis include
the following:
C = A single determination of (H_SO or SO„) concentration at standard
3
conditions, on a dry basis, g/m .
_ 3
C = The average concentration of six repetitions, g/m .
CV{C} = Within-laboratory coefficient of variation (same laboratory,
personnel, equipment, and sample), percent.
CV. {C} =• Between-laboratory coefficient of variation (variation in simul-
b
taneous determinations of C by different laboratories at the same
true value of C), percent.
CV {c} = Laboratory bias coefficient of variation (variability in concen-
Li
tration determinations due to changes in personnel, equipment and
procedural details), percent.
61
-------
CV{C}// 6 » Repeatability coefficient of variation for concentration deter-
minations based on six replicates, percent.
2 o
'L {C} + CV {c}/6 = Reproducibility coefficient of variation for a
field test result based on six replicates, percent.
= CV(R)
4.1.1 Variable Evaluation and Error Range Estimates.
The emission rates of sulfuric acid and sulfur dioxide are calculated
from measured values by the relationship
~\ i /•)
PR n N(Vt - V
-------
Table 2. Assumed means and coefficients of variations of variables
in influencing emissions rate determinations for S02
Variable
N
V
m
T"
m
P
m
(1 - B )
x wo
C
P
(/SF)avg
As
P
(T )
s avg
Ms
Assumed
mean
value
7 mH
5 dimensionless
0.01 normal
28 i
294° K
760 mm of Hg
0.90
0.85 dimensionless
7 (mm of HjO)
0.7 m2
760 mm of HG
294° K
28.8 g/mole
Within- laboratory
coefficient of
variation
CV{X} percent
3.90
0.50
0.10
0.50
0.25
0.10
0.15
0.50
0.85
0.50
0.20
0.50
0.35
Between-laboratory
coefficient of
variation
CVb{X} percent
5.50
1.00
1.00
1.25
0.50
0.30
0.30
1.00
1.70
1.00
0.40
1.00
0.71
63
-------
The first four variables in table 2 are the only ones unique to this
method. The remaining variables are common to methods 2, 3, and 4 and are
discussed in the quality assurance documents of this series dealing with those
methods. Estimates of the variance of the first four variables in table 2
[(V - V ,), (V /V ) , N and V ] are discussed in the following subsections.
t tb soln am
4.1.1.1 Volume of Tit rant (V^ -V ,). The difference in the volumes of
- 1 - ^-
titrant used in the sample and the blank, symbolized by (V - V ,), is a direct
t tb
measure of the quantity of SCL or SO,/H SO. absorbed in the sample solution.
The component of error or variability of this term attributable to the analysis
phase of the measurement method; i.e., the actual volume determinations of V
and V , , and the ability to detect the endpoint in the titration, should be
relatively small. However, the above term directly reflects the variability
due to sample collection. Any difference in the masses of SO. and acid mist
in a given volume of stack gas and that retained in the absorbing solution after
sampling that volume of gas will result in the same percent difference in the
volumes of titrant that the sample would have required (had there been no error
in sample collection) and the volumes actually required in the analysis.
Differences in the true masses of H SO. and SO. in a given volume of stack
gas and the measured value can result from:
1. Incomplete purging of the sampling train after sample collection.
This would lead to high H2SOA an<^ ^ow ^9 values> since SO- remain-
ing in the 80% isopropanol solution would oxidize to sulfate;
2. Less than 100 percent collection efficiency of the absorbing solution;
3. Loss of SO due to reactions with particulate matter trapped by the
particulate filter (ref. 16);
4. Loss of sample during sample recovery.
There are no data available for estimating the variability of these terms.
The coefficients of variation of 3.9 and 5.5 (for within-laboratory and
between-laboratory variabilities) as given in table 2 are taken from the
Quality Assurance Guidelines document for Method 6, which involves collection
and analysis of sulfur dioxide only. Variability in sulfuric acid mist (on
a percentage basis) would be much larger, due to the lower concentration of
H.SO. relative to SO. (ref. 15).
24 2
64
-------
4.1.1.2 Fraction of Total Solution Volume Titrated (V /V ). The sample
• so In—a—
volume is determined by transferring the contents of the sample bottles (see
subsection 2.3.4) into 250-m£ (H SO ) and 1,000-nA (SO ) graduated cylinders
and diluting to volume. Errors due to the graduated cylinders, incomplete
transfer, and diluting to volume should be small in most cases. A pipette
is used to measure the aliquot, V , and (neglecting operator mistakes) should
SL
exhibit negligible variability. The estimated coefficients of variations of
0.5 and 1.0 percent (for within-laboratory and between-laboratory, respectively)
do not significantly increase the total variability of the measurement method.
4.1.1-.3 Normality of Barium Perchlorate Titrant (N) . By exercising proper
care, the normality of the barium perchlorate titrant should be repeatable to
the fourth decimal place. Since the titrant is approximately 0.01 N, the fourth
decimal place would be equivalent to 1.0 percent. Coefficients of variation
of 0.1 and 1.0 percent are used for this analysis, as shown in table 2. The
small value of 0.1 is used for fixed within-laboratory repeatability since the
same batch of titrant is used for all samples from a given field test. Hence,
there should be little variability. However, the variability between labora-
tories and for that matter between batches within a laboratory would be
expected to be significantly larger. Thus, a CV of 1.0 percent is assumed.
4.1.1.4 Sample Volume (V ). Variability in the measured sample gas volume at
meter conditions can result from
1. Calibration variability (of the dry gas meter),
2. Imprecision of the dry gas meter,
3. Sampling train leaks,
4. Meter reading errors.
The coefficients of variation given in table 2 of 0.50 and 1.25 percent are
estimates of what can be expected of a properly trained and motivated field
team.
To simplify the variance analysis, the overall equation can be written
in terms of concentration and volumetric flow rate. That is,
ER = C x Q
65
-------
3
where the concentration, C, in g/m is given by
N(Vt - V
-------
Table 3. Variance analysis for Vm
'std
Variable
V
m
P
m
T
m
Assumed CV^} (CV2{X» x ^
1.56 (1.31)
0.09 (0.08)
0.25 (0.19)
&££t " B»8hted CV*(X)
1 1.56
1 0.09
1 0.25
(CV2{X})
(1.31)
(0.08)
(0.19)
m
std
m
std
} o 1.90 (1.58)
{V } =» 1-38 (1.26)
,
b m
std
Table 4. Variance analysis for C
SO,
Variable
N
(Vt - Vtb>
(Vsoln/Va>
V
rastd
Cso2
Assumed CV2{X}(CV2{X})
b
1.0 (0.01)
30.25 (15.21)
1.00 (0.25)
1.90 (1.58)
x Weighting a
factor (
1
1
1
1
CVb -
CVCS02> '
Weighted
:v2{x} (cv2(x»
1.0 (0.01)
30.25 (15.21)
1.00 (0.25)
1.90 (1.58)
3;:i; «;;;»
67
-------
Table 5. Variance analysis for Q
Variable Assumed CV*{X} x "^/^a
b coefficient
1 - B 0.09 1.23
wo
C 1.00 1.0
P
A 1.00 1.0
P 0.16 0.25
s
(*^P) 2.89 1.00
(T ) 1.0 0.25
s avg
M 0.50 0.25
s
<*„
Weighted
0.11
1.00
1.00
0.04
2.89
0.250
0.125
CV* {Q } = 5.42
D S
CV, {Q } = 2,33%
b s
aThe weighting coefficient for 1 - B is 1/(1 - B ) , and assuming B
to be 0.10, this yields l/(.9)2 = 1.23.
68
-------
Table 6. Variance analysis for reproducibility of ER
Variable
c
QS
Assumed CV2{X}
CVL< V - 17-*
CV2{CS()2}/6 - 2.1
5.42
Weighting
Factor
1
; i
i
Weighted
CV2{X}
17.1
2.8
5.4
CV2{ER) - 25.3
ER b
CV^ER} - 5.0%
and for values in table 2, CVT{C } becomes
Li ''^'o
34.12 = CV^C.,. } + 17.1,
L O\Jn
then CVL{CS02} ' "-1
and CVT{C } = 4.1 percent.
L ^'-'9
The reproducibility coefficient of variation then is taken as
V
CV(R) = CV^{C_ } -
CV(R) - 4.5 percent
based on six replicates.
The collaborative study of Method 8 (ref. 13) shows that the precision of
the SO. data is independent of the mean S02 concentration level, whereas the
precision of the H?SO,/SO_ data is proportional to the mean level. A similar
study of Method 6 (ref. 17) indicates that the precision of the SO measure-
ments is proportional to the mean level. The analysis by barium-thorin
69
-------
titration is identical in both methods, but there are differences in the
collection techniques. Method 8 collection is by way of Greenburg-Smith
impingers and sampling is isokinetic, whereas Method 6 uses midget: impingers
and samples proportionally. In any event, any statistical differences (if
real) must arise from the collection techniques rather than the analyses. This
document takes the position that, in view of the questions raised by the
statistics obtained in these two studies, it is not appropriate to undertake a
detailed variance analysis of Method 8 without further testing. The numbers
used in the foregoing discussion have been lifted from the guidelines document
for Method 6 and serve only to illustrate how such an analysis can be carried
out.
There is more opportunity for error in the sulfuric acid mist determina-
tion, since the concentration range is normally much lower than that for sulfur
dioxide. Any SO not purged from the isopropanol impinger tube and filter
system may be oxidized to sulfate, with resulting high bias in the SO /H SO
determination. The greater uncertainty in this measurement is reflected in the
collaborative study, which (excluding the high values) gives the following
coefficients of variation: CV = 58.5 percent, CV, =• 66.1 percent, and CVT =
b L
30.8 percent. Not excluding the high values yields a CV of 95.8 percent.
Prompt analysis of the isopropanol impinger, immediately after thorough system
purging, may minimize high bias due to S0_ oxidation, but in general it is
expected that the precision of the mist determination will be quite poor.
4.1.2 Interferences.
4.1.2.1 Cations From Particulates. The poor endpoint visibility of the barium
ion-thorin titration is mentioned in subsection 2.4.2.4. A detailed field
study (ref. 18) indicates that this problem is due to the presence of inter-
fering cations (sodium and potassium). The intorduction of a fine, neutral
pH,* particulate filter in the sampling train greatly sharpens the endpoint.
4.1.2.2 Nitric Oxide. Nitric oxide does not interfere with Method 8 results
(ref. 16).
*A glass fiber filter is not acceptable due to the natural alkalinity of the
glass .
-------
4.1.3 Bias Analysis.
The collaborative study of Method 8 (ref. 13) does not attempt to determine
bias for the method, but does indicate that the analytical phase (the barium-
thorin titration) is accurate. A small negative bias of 1 to 3 percent, falling
within the 95 percent confidence interval, was evident.
High SO /H SO results and corresponding low SO data would indicate fail-
•J £• *T ^
ure to purge the system rigorously after sampling. A field evaluation of
Method 6 (ref. 19) showed that up to 14 percent of the SO may be retained in
the isopropanol bubblers if purging is not carried out. In view of the low
H SO /SO concentration ratios normally sampled, incomplete purging would
surely bias the mist results. There seems to be no experimental confirmation
of this in the literature.
Subsection 4.1.1.1 indicates other possible reasons for incomplete
sample collection, all of which would negatively bias the results. However,
there is no way to quantify the loss of sample due to these possibilities.
Assuming reasonable care in following the recommended collection and
analysis procedure, results from Method 8 should be unbiased or very slightly
negatively biased. Field personnel should be aware of the possibility of
introducing a negative bias due to any of the reasons listed in section 4.1.1.1,
or because of such problems as sampling train leaks. No evidence is available
indicating a positive bias in the method.
71
-------
72
-------
4.2 ACTION OPTIONS
Suppose it has been determined as a result of the functional analysis and/
or the reported data from the checking and auditing schemes, that the data qual-
ity is not consistent with suggested standards or with the user requirements.
Poor data quality may result from (1) a lack of adherence to the control procedures
given in section II—Operations Manual, or (2) the need for an improved method or
instrumentation for taking the measurements. It is assumed in this section that
(2) applies, that is, the data quality needs to be improved beyond that attain-
able by following the operational pro'cedures given for the reference method.
The selection of possible actions for improving the data quality can best
be iiade by those familiar with the measurement process. For each action, the
variance analysis can be performed to estimate the variance, standard deviation,
and coefficient of variation of the pertinent measurement(s). In some cases it
is difficult to estimate the reduction in specific variances that are required
to estimate the precisions of the pertinent measurements. In such cases, an
experimental study should be made of the more promising actions based on pre-
limxnary estimates of precision/bias and the costs of implementing each action.
In order to illustrate the methodology, three actions and appropriate
combinations thereof are suggested. Variance and cost estimates are made for
each action, resulting in estimates of the overall precision of each action.
The actions are as follows:*
AO: Reference Method
Al: Photometric endpoint detection (cost is $800/20 field tests**)
A2: Crew training workshop (cost is $1,000/20 field tests)
A3: Calculations by standard computer program (cost is $200/20 tests)
A4: (Al + A3): Improved endpoint detection plus calculations by com-
puter (total cost of $1,000/20 tests).
*Actions presented here are same as those outlined in the corresponding
quality assurance document for Method 6, in view of the similarity of
Methods 6 and 8.
**Equipment costs are amortized over 5 years, at 20 tests per year, and
allowance is made for the continuing cost of supplies and labor.
73
-------
The costs given for each action are additional costs above that of the refer-
ence method. The assumptions made concerning the reduction in the variances
(or improved precisions) are given in the following for each action.
AO: Reference Method. The functional analysis (section 4.1.3) does not
anticipate a bias in Method 8, and provided the procedures (both
field and laboratory) stipulated in the method are rigorously adhered
to, unbiased results should be obtained. The collaborative study
(ref. 13) indicates that the sulfuric acid mist data has precision
proportional to the mean and thus expressed as a percent of the mean.
The SO data precision, on the other hand, is independent of the mean
and expressed in absolute units of grams/cubic meter. If the high
(outlying) values are excluded, the results for H SO, and S0» are as
follows:
SO/H.SO. CV = 58.5, CV, = 66.1, CVT = 30.8
_> 2 4 b L
S00 a = 0.106 a, = 0.114 a = 0.044.
2 b L
For convenience it is assumed that these estimates of precision will
be affected in a corresponding way; i.e., if a given strategy improves
CV for mist determination, it will also improve a for SO. and by a
proportional amount. Given the strategies suggested, this is a
reasonable assumption. Other possible strategies, especially if
concerned with certain areas of the sample collection phase, might
have differing effects on the quality of acid mist and SO- data.
Table 7 gives assumed effects of Al, A2, A3, and A4 on the
precision of Method 8. The within-laboratory, between-laboratory
and laboratory bias components of variability are symbolized as P,
P , and P, and apply to both SO /H SO. and SO . These symbols (i.e.,
P, P, , and P ) represent CV, CV, , and CVT , respectively for acid
b L b L
mist variability and o, o , and O respectively for SO variability.
D L 2-
Al: Photometric Endpoint Detection. A major problem associated with
Method 8 is the poor visibility of the thorin titration endpoint.
Photometric endpoint detection could greatly improve precision by
eliminating visual estimation of endpoint color and intensity. Unless
the photometric technique became highly standardized, however, there
74
-------
Table 7. Assumed within-laboratory, between-laboratory, and laboratory
bias components of variability for given action options.
AO
Al
Reference
Photometric endpoint
detection
Pr\
y
*b
P <"b>R
0.8 PR 0.9 (Pb)R
Added
cost
per 20
D field
y
rl tests
(P| )n 0
0.99 (PL)R $ 800
A2 Crew training workshop 0.8 PR
A3 Calculations by stand- 1.0 PR
ard computer program
0.8 (Pb)R 0.8 (PL)R $1,000
0.89 (Pb)R 0.8 (PL)R $ 200
A4 (Al + A3)
0.78 PR 0.80 (Pb)R 0.79 (PL)R $1,000
would remain differences in technique among various laboratories, so
that the improvement in P, is assumed not as great, and thus P is
D Lf
virtually unchanged.
A2: Crew Training Workshop. From discussing this method with experienced
field testers, it is felt that the method requires an operator who
understands the system and its capability. Early detection of out-
of-control conditions by the operator can substantially improve data
quality. It is assumed here that crew training could affect all
sources of variability, and therefore an improvement in all three
measures of variability is shown. A 1-week course a year, or special
on-the-job training, is estimated to cost approximately $1,000 per
20 field tests.
A3: Calculations by Computer. This recommended option serves a twofold
purpose:
1. It eliminates human error (in the field) in calculation of the
acid mist and S09 concentrations. There remains, of course, the
possibility of errors due to computer malfunction, keypunch
error and the like.
75
-------
2. It largely eliminates the illegal practice of discarding "bad"
runs and the reporting of only "acceptable" data by field
personnel, since the raw field data is submitted.
Another comparable option could be the use of "canned" programs
written for the various commercially available programmable calcula-
tors. These could be made available by EPA, thus allowing local cal-
culation but standardizing the number of significant digits carried
in each step, the treatment of roundoff and all other aspects of the
calculation steps.
Since one reason for laboratory bias, P , could be improper cal-
L
culation technique, A4 should in general reduce P . This is a system-
Ju
atic error (bias). In addition, a small percentage (about 3 percent)
of random calculation errors contribute to P. If both P and P are
L
reduced, then P, should also be improved.
b
Figure 6 shows the results in terms of cost and data quality for acid
mist.* Data quality for this purpose is given as CV, the within-laboratory
coefficient of variation. The figure then illustrates options for the individ-
ual laboratory to consider. The manager of a number of teams would be more
interested in how CV, varies with cost, and this is given in figure 7. It must
be emphasized that figures 6 and 7 are given for illustrative purposes only and
should not in themselves be considered as basis for action by a laboratory or
a group of laboratories. Both the reductions in CV and CV,, as well as costs,
are estimates based on professional judgment. In particular, the values of CV
and CV, are based solely on judgment and there is no experimental evidence to
support these values. The figures illustrate that in principle it is possible
to reduce the variability of Method 8 by a number of modifications of the
method, and that there is a cost associated with each modification.
Figures 6 and 7 also show "cost of reporting bad data" curves, which
assume that the cost increases as the data quality decreases. These function
curves must be determined for each specific situation according to the moni-
toring objectives of the laboratory or group of laboratories.
^Comparable charts for SO could be constructed, but are not included, since the
only difference in construction would be in the scale range of the abscissa.
76
-------
to
1—
U_
t-
o
_J
UJ
i — i
U.
UJ
UJ
D.
O
O
UJ
O
0
-------
CO
L
r~
OO
l^j
i-
a
UJ
U_
t
p~
UJ
3
a:
UJ
a.
H-
1/1
o
o
Q
UJ
Q
1100 -
1000 -
900 -
800 -
700 -
600 -
500 -
400 -
300 -
200 -
100 -
BEST ACTION
OPTIONS
COST OF REPORTING
POOR QUALITY DATA
10.0 20.0 30.0 40.0
b
QA2,
\
\
\
A4
QA1
50.0 60.0 70.0
66.1
Figure 7. Added cost versus data quality (CVb) for selection action
options, for SO./H SO data.
78
-------
Once determined for a given situation, graphs such as figures 6 and 7 can
be used to select an "optimal" monitoring strategy, i.e., one which gives
maximum increase in data quality for minimum cost. Usually, the strategy point
lying closest to the point of intersection of the two curves should be selected.
In figures 6 and 7, this point is A3. Note that option A2 is not "best" since
it lies to the right of the dashed line; i.e., A2 will not yield as large an
improvement in data quality per dollar of cost as A4.
In some instances a manager may need to know the total cost of attaining a
prescribed reduction in variability. Figures 6 and 7 can be used to find the
method which most nearly meets the requirement. The cost of implementing the
method, plus the cost of reporting bad quality data when that method is used,
gives total cost.
It is, of course, possible to implement a combination of two or more action
options, with costs being additive and precision values being multiplicative
(assumed independent). For example, if one chooses to implement both Al and
A2, the total cost would be $1,800 and the values of CV and CV, would be 0.64 P
and 0.72 (P, )-, respectively.
D K
79
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-------
4.3 PROCEDURES FOR PERFORMING A QUALITY AUDIT
"Quality audit" as used here implies a comprehensive system of planned and
periodic audits to verify compliance with all aspects of the quality assurance
program. Results from the quality audit provide an independent assessment of
data quality. "Independent" in this case implies that the auditor prepares a
reference sample of sulfate and has the field team analyze the sample. The
field team should not know the true sulfate concentration. From these data,
both bias and precision estimates can be made for the analysis phase of the
measurement process only.
The auditor, i.e., the individual performing the audit, should have ex-
tensive background experience in source sampling, specifically with the
characterization technique that he is auditing. He should be able to establish
and maintain good rapport with field crews.
The functions of the auditor are summarized in the following list:
1. Observe, and where possible duplicate and verify procedures and
techniques of the field team during sampling.
2. Check/verify applicable records of equipment calibration checks and
quality control charts in the field team's home laboratory.
3. Compare the audit sulfate value with the field laboratory test value.
4. Randomly recheck, if possible, actual field analyses.
5. Inform the field team of the comparison results specifying any area(s)
that need special attention or improvement.
6. File the records and forward the comparison results with appropriate
comments to the manager.
4.3.1 Frequency of Audit.
The optimum frequency of audit is a function of certain costs and the
desired level of confidence in the data quality assessment. A methodology for
determining the optimum frequency, using relevant costs, is presented in the
final report for this contract. Costs will vary among field teams and types of
field tests. Therefore, the most cost-effective auditing level will have to be
derived using relevant local cost data according to the procedure given in the
final report on this contract.
81
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4.3.2 Collecting Sampling Information.
While on site, the auditor should observe the field team's overall per-
formance of the field test. Specific operations to observe should include, but
not be limited to:
1. Setting up and leak testing the sampling train;
2. Preparation and pipetting of absorbing solutions into bubblers and
impingers;
3. Sample collection, specifically the following techniques;
a) achievement of isokinetic sampling rate, b) system purging,
c) leak checks.
4. Sample recovery and preparation for shipment.
The above observations can be used in combination to make an overall
evaluation of the team's proficiency in carrying out this portion of the field
test.
4.3.3 Collecting Laboratory Information.
The auditor must also observe the analytical phase of Method 8. Here he
should observe the following:
1. Sample aliquotting technique. This is particularly important, to
verify that standard analytical technique is being followed.
2. Titration technique, particularly endpoint detection.
3. Calculation procedure.
The analysis phase of Method 8 can be audited with standard sulfate solu-
tions, as discussed in reference 13.
4.3.3.1 Comparing Audit and Routine Values of Concentrations. In. field tests,
the audit and routine (field team) values are compared by
d, = C, - C
j j aj
where d. = The difference in the audit and field tftst results for the j
J 3
audit, mg/m .
C . = Audit value of concentrations (acid mist and SO.) for j audit,
aj 3 2
mg/m .
3
C. = Concentrations obtained by the field team, mg/m .
Record the values of d for both species in the quality audit log book.
82
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4.3.4 Overall Evaluation of Field Team Performance.
In a summary-type statement, the field team should be evaluated on its
overall performance. Reporting the d. value as previously computed is an ade-
quate representation of the objective information collected for the analysis
phase of the audit. However, immeasurable errors can result from nonadherence
to the prescribed operating procedures and/or from poor technique in executing
the analytical procedures. These error sources have to be estimated subjectively
by the auditor. Using the notes taken in the field, the team could be rated on
a scale of 1 to 5 as follows:
5 - Excellent
4 - Above average
3 - Average
2 - Acceptable, but below average
1 - Unacceptable performance.
In conjunction with the numerical rating, the auditor should include justifica-
tion for the rating. This could be in the form of a list of the team's strong
and weak points.
83
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84
-------
4.4 Data Quality Assessment
Two aspects of data quality assessment are considered in this section.
The first considers a means of estimating the precision and bias of the reported
data, e.g., reporting the bias, if any, and the standard deviation associated
with the measurements. The second consideration is that of testing the data
quality against given standards, using sampling by variables. For example,
lower and upper limits, L and U, may be selected to include a large percentage
of the measurements. It is desired to control the percentage of measurements
outside these limits to less than 10 percent. If the data quality is not con-
sistent with the L and U limits, then action is taken to correct the possible
deficiency before future field tests are performed and to correct the previous
data when possible.
4.4.1 Estimating the Precision/Accuracy of the Reported Data.
Methods for estimating the precision (standard deviation) and accuracy
(bias) of the acid mist and SO- concentrations were given in section 4.1. This
section will indicate how the audit data collected in accordance with the pro-
cedure described in section 4.3 will be utilized to estimate the precision and
accuracy of the measures of interest. Similar techniques can be also used by
a specific firm or team to assess its own measurements. The differences between
the field team results and the audited results for the respective measurements
are
d » C. - C .
j j aj
Let the mean and standard deviation of the'differences d , where j=l, ... n be
denoted by d, and s,, respectively. Thus
u
Ed./n,
j
and
s
n
d
j-l
- d)2/(n
1/2
85
-------
Now d is an estimate of the bias in the measurements (i.e., relative to the
audited value). Assuming the audited data to be unbiased, the existence of a
bias in the field data can be checked by the appropriate t-test, i.e.,
See ref. 20 for a discussion of the t-test.
If t is significantly large, say greater in absolute value than the tabu-
lated value of t within n - 1 degrees of freedom, which is exceeded by chance
only 5 percent of the time, then the bias is considered to be real, and some
check should be made for a possible cause of the bias. If t is not significantly
large, then the bias should be considered zero, and the accuracy of the data is
acceptable.
The standard deviation s, is a function of both the standard deviation of
d
the field measurements and of the audit measurements. Assuming the audit values
to be more accurate than the field measurements, then s, values are an estimate
d
of a{SO } and o{H2SO }, the population standard deviations for SO and H SO
concentration measurements. The estimated standard deviations, s , may be
directly checked against assumed values of a{SO } and a{H SO.}, by using the
statistical test procedure
2 *
rr
CT{so2)
2
where x /f is the value of a random variable having the chi-square distribution
2
with f = n - 1 degrees of freedom. If x /f is larger than the tabulated value
exceeded only 5 percent of the time, then it would be concluded that the test
procedure is yielding more variable results due to faulty equipment or opera-
tional procedure.
The measured values should be reported along with the estimated biases,
standard deviations, the number of audits, n, and the total number of field
tests, N, sampled (n _<_N). Estimates, i.e., s, and d which are significantly
*From this point the analysis is carried out for S02 only. An analysis for
acid mist would be done in a similar fashion. It would be unduly repetitive
to do both analyses in this document.
86
-------
different from the assumed population parameters, should be identified on the
data sheet.
9
The t-test and x -test described above and in further detail in the final
report on this contract, are used to check on the biases and standard deviations
separately. In order to check on the overall data quality as measured by the
percent of measurement deviations outside prescribed limits, it is necessary
to use the approach described in subsection 4.4.2 below.
4.4.2 Sampling by Variables.
Because the lot size (i.e., the number of field tests performed by a team
or laboratory during a particular time period, normally a calendar quarter) is
small, N » 20, and because the sample size is, consequently, small (of the
order of n = 3 to 8) , it is important to consider a sampling by variables
approach to assess the data quality with respect to prescribed limits. That is,
it is desirable to make as much use of the data as possible. In the variables
approach, the means and standard deviations of the sample of n audits are used
in making a decision concerning the data quality.
Some background concerning the assumptions and the methodology is repeated
below for convenience. However, one is referred to one of a number of publi-
cations having information on sampling by variables; e.g., see refs. 20-26.
The discussion below will be given in regard to the specific problem in the
variables approach, which has some unique features as compared with the usual
variable sampling plans. In the following discussion, it is assumed that only
S0? measurements are audited as directed in section 4.3. The difference between
the team-measured and audited values of SO is designated as d., and the mean
difference over n audits by d is
Theoretically, (SO ) and (SO.) should be measures of the same S09 concentra-
£. JL 3. ^
tion and their difference should have a mean zero on the average. In addition,
this difference should have a standard deviation equal to that associated with
the measurements of S0? .
87
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Assuming three standard deviation limits, the values 3cr - -12.0 mg/m
and +12.0 mg/m define the respective lower and upper limits, L and U, outside
of which it is desired to control the proportion of differences, d . Following
the method given in ref. 24, a procedure for applying the variables sampling
plan is described below. Figures 9 and 10 illustrate examples of satisfactory
and unsatisfactory data quality with respect to the prescribed limits L and U.
The variables sampling plan requires the following information: the sample
mean difference, d, the standard deviation of these differences, s,, and a
d
constant, k, which is determined by the value of p, the proportion of the dif-
ferences outside the limits of L and U. For example, if it is desired to con-
trol at 0.10 the probability of not detecting lots with data qualities p equal
to 0.10 (or 10 percent of the individual differences outside L and U), and if
the sample size n » 7, then the value of k can be obtained from table 2 of
ref. 24. The values of d and s, are computed in the usual manner; see table 8
d
for formulas and a specific example. Given the above information, the test
procedure is applied, and subsequent action is taken in accordance with the
following criteria:
1. If both of the following conditions are satisfied,
"d - k sd _> L = -12 mg/m3
d + k s < U = +12 mg/m3
u —
the individual differences are considered to be consistent with the
prescribed data quality limits, and no corrective action is required.
2. If one or both of these inequalities is violated, possible deficiencies
exist in the measurement process as carried out for that particular
lot (group) of field tests. These deficiencies should be identified
and corrected before future field tests are performed. Data correc-
tions should be made when possible, i.e., if a quantitative basis is
determined for correction.
3
*12.0 mg/m assumes, for calculation purposes, an SO concentration mean of
3 3 3
100 mg/m , with a - 4.0 mg/m , so that 3a - 12.0 mg/m .
88
-------
p = p, + p,, < 0.10
Figure 8. Example illustrating p < 0.10 and satisfactory data
quality.
p (percent of measured
differences outside
limits L and U) > 0.10
Figure 9. Example illustrating p > 0.10 and unsatisfactory data quality.
89
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Table 8. Computation of mean difference, d, and
standard deviation of differences, s.
General
d= (S02)
dl
d2
d3
d4
d5
d6
d?
Zdj
- "j
d ~ — J-
n
2 Edj
Sd "
-.-/
Formulas
J ' (S°2>aj
d?
d2
d3
d4
U * +12 mg/m3.
d
Therefore, both conditions are violated and the lot of N = 20 measurements is
not consistent with the prescribed quality limits. The plan is designed to aid
in detecting lots with 10 percent or more defects (deviations falling outside
90
-------
Table 9. Sample plan constants, k for P {not detecting a lot
with proportion p outside limits L and U) £ 0.1
Sample Size n p ~ 0.2 p -= 0.1
3 3.039 4.258
5 1.976 2.742
7 1.721 2.334
10 1.595 2.112
12 1.550 2.045
the designated limits L and U) with a risk of 0.10; that is, on the average,
90 percent of the lots with 10 percent or more defects will be detected by this
sampling plan.
4.4.3 Cost Versus Audit Level.
The determination of the audit level (sample size n) to be used in assess-
ing the data quality, with reference to prescribed limits L and U, can be made
either: (1) on a statistical basis, by defining acceptable risks for type I
and type II errors, knowing or estimating the quality of the incoming data,
and specifying the described level of confidence in the reported data; or
(2) on a cost basis, as described herein. In this section, cost data asso-
ciated with the audit procedure are estimated or assumed for the purpose of
illustrating a method of approach and identifying which costs should be
considered.
A model of the audit process, associated costs, and assumptions made in
the determination of the audit level is provided in figure 10. It is assumed
that a collection of source emissions tests for N stacks is to be made by a
particular firm, and that n measurements (n < N) are to be audited at a cost,
C = b + en, where b is a constant independent of n and c is the cost per stack
A
measurement audited. In order to make a specific determination of n, it is
also necessary to make some assumptions about the quality of the source
emissions data from several firms. For example, it is assumed in this analysis
that 50 percent of the data lots are of good quality, i.e., one-half of the
firms are adhering to good data quality assurance practice, and that 50 percent
of the data lots are of poor quality. Based on the analysis in sections 4.1,
91
-------
Collection of Source Emission
Tests (Lots of Size N)
SOZ of Lots
< 102 Defective
^
Acceptable
Quality
Not Acceptable
Quality
Audit n
Measurements
H
t
C - b+cn «• $600
A
50t of Lots
10Z Defective
Audit n
Measurements
Select Audit
Parameter n, k
1
Data Declared
to. be of
Acceptable
Duality
Data Declared
not to be of
Acceptable
Quality
Report
Data
Data Declared
to be of
Acceptable
Quality
Institute Action to
Improve Data Quality
(Correct Data if
Possible)
Expected Coat of
Treating Poor
Quality Data as
Good Quality Data
C^,D - $15,000
Expected Cost of
Falsely Inferring
Data are of Poor
Quality Cp|G -
$10,000
Expected Cost
Saving of Taking
Correct Action withl
Respect to Poor
Figure 10. Flow chart of the audit level selection process.
92
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good quality data is defined as that which is consistent with the estimated
precision/bias using the reference method. Thus if the data quality limits L
and U are taken to be the lower and upper 3cr limits, corresponding to limits
used in a control chart, the quality of data provided by firmly adhering to the
recommended quality assurance procedures should be such that at most about
0.3 percent defective measurements (i.e., outside the limits defined by L and U)
are made. Herein, good quality data is defined as that containing at most
10 percent defective measurements. The definition of poor quality data is some-
what: arbitrary; for this illustration it is taken as 25 percent outside L and U.
In this audit procedure, the data are declared to be of acceptable
quality if both of the following inequalities are satisfied:
"d + ks , < U
d
"d - ks , > L
d
where d and s. are the mean and standard deviation of the data quality charac-
teristic (i.e., the difference of the field and audited measurements) being
checked. The data are not of desired quality if one or both inequalities are
violated, as described in section 4.3. The costs associated with these actions
are assumed to be as follows:
C = Audit cost = b + en. It is assumed that b is zero for this example,
A
and c is taken as $600/measurement.
CL.I- = Cost of falsely inferring that the data are of poor quality, P,
P|G
given that the data are of good quality, G. This cost is assumed to
be one-half the cost of collecting emissions data for N = 20 stacks
(i.e., 0.5 x $1,000 x 20 = $10,000). It would include the costs of
searching for an assignable cause of the inferred data deficiency
when none exists, of partial repetition of data collection, and of
decisions resulting in the purchase of equipment to reduce emission
levels of specific pollutants, etc.
C I = Cost of falsely stating that the data are of good quality, G, given
that they are of poor quality, P. This cost is assumed to be
$15,000 (* 0.75 x $1,000 x 20), and is associated with health effects,
litigation, etc.
93
-------
Cpip = Cost savings resulting from correct identification of poor quality
data. This cost is taken to be $7,500, i.e., equal to one-half of
Cp|G or equal to 0.375 x $1,000 x 20, the total cost of data
collection.
These costs are given in figure 11. The cost data are then used in con-
junction with the a priori information concerning the data quality, to select
an audit level n. Actually, the audit procedure requires the selection of the
limit^ L and U, n, and k. L and U are determined on the basis of the analysis
of section 4.1. The value of k is taken to be the value associated with n in
table 9 of section 4.4.2, i.e., the value selected on a statistical basis to
control the percentage of data outside the limits L and U. Thus, it. is only
necessary to vary n and determine the corresponding expected total cost E(TC)
using the following cost model
E(TO - -CA - 0.5 Pp|G Cp|G + 0.5 Pp|p Cp|p - 0.5 PG|P CG|P
where the costs are as previously defined. The probabilities are defined in a
way similar to defining corresponding costs:
P |_ = Probability that a lot of good quality data is falsely inferred to
I
be of poor quality, due to the random variations in the sample mean
d and standard deviation, s,, in small samples of size ri.
d
P I = Probability that a lot of poor quality data is correctly identified
as being of poor quality.
P_I„ = Probability that a lot of poor quality data is incorrectly judged
1
to be of good quality, due to sampling variations of d and s.
These three probabilities are conditional on the presumed lot quality and
are preceded by a factor of 0.5 in the total cost model, to correspond to the
assumed precentage of good (poor) quality data lots.
In order to complete the determination of n, it is necessary to calculate
each of the conditional probabilities, using the assumptions stated for a series
of values of n (and associated k, which is given in table 5). The computational
procedure is given in the final report of this contract. These calculations
were made for the cases n = 3, 5, 7, and 10 and for two degrees of control on
the quality of the data that can be tolerated, i.e., p = 0.2 and p == 0.1, the
portion outside the limits L and U for which it is desired to accept the data
94
-------
$8000
$6000
o
H
Hi
o
o
a
60
n)
J-i
$4000 •
$2000 •
P
2 3
456
Audit Level (n)
8 9
Proportion defective measurements in the
P{Acc. lot with p} < 0.1
Figure 11. Average cost versus audit level (n).
95
-------
as good quality, with probability less than or equal to 0.10. These computed
probabilities are then used in conjunction with the costs associated with each
condition, applying the cost model equation above to obtain the average cost
versus sample size n for the two cases p = 0.1 and 0.2. The curves obtained
from these results are given in figure 11. It can be seen from these curves
that the minimum cost is obtained by using n = 5 independent of p. However,
it must be recognized that the costs used in the example are for illustrative
purposes and may vary from one region to another; thus, within the reasonable
uncertainty of the estimated costs, it is suggested that p = 0.2 is more cost
effective; this tends to permit data of poorer quality to be accepted.
96
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SECTION V REFERENCES
1. "Standards of Performance for New Stationary Sources," Federal Register
Vol. 36, No. 247, December 23, 1971.
2. Driscoll, J., Becker, J., and Herbert, R., "Validation of Improved Chemical
Methods for Sulfur Oxide Measurements from Stationary Sources," EPA-R2-72-
105, National Environmental Research Center, Research Triangle Park, N.C.
27709.
3. Brenchley, David L., Turley, C., David, and Yarmac, Raymond F., "Industrial
Source Sampling," Ann Arbor Sciences Publishers, Inc., 1971.
4. Koisch, F. Paul, Stack Sampling News, Vol. 1, No. 2, 1973.
5. Smith, W. S., Stack Sampling News, Vol. 1, No. 7, 1974.
6. Smith, Walter S., and Grove, D. James, "Stack Sampling Monographs for Field
Estimations," Entropy Environmentalists, Inc., Research Triangle Park,
N.C., 1973.
7. Martin, R. M., "Construction Details of Isokinetic Source Sampling Equip-
ment," Publication No. APTD-0581, Air Pollution Control Office, EPA,
Research Triangle Park, N.C., 1971.
8. Rom, J. J., "Maintenance, Calibration, and Operation of Isokinetic Source
Sampling Equipment," Publication No. APTD-0576, Office of Air Programs,
EPA, Research Triangle Park, N.C., 1972.
9. Smith, W. S., Stack Sampling News, Vol. 1, No. 1, 1973.
10. Smith, W. S., Stack Sampling News, Vol. 1, No. 7, 1974.
11. Smith, Franklin, and Nelson, A. Carl, Jr., "Guidelines for Development of
a Quality Assurance Program; Reference Method for the Determination of
Suspended Particulates in the Atmosphere (High Volume Method)," EPA-R4-
73-028b, Environmental Protection Agency, Research Triangle Park, N.C., 1973.
12. Galeano, S. F. , Tucker, T. W. ,, and Duncan, L. , "Determination of Sulfur
Oxides in the Flue Gas of the Pulping Process," JAPCA, Vol. 22, No. 790,
1972.
13. Hamil, H. F., Camann, D. E., and Thomas, R. E., "Collaborative Study of
Method for the Determination of Sulfuric Acid Mist and Sulfur Dioxide
Emissions from Stationary Sources," EPA-650/4-75-003, Environmental
Protection Agency, Research Triangle Park, N.C., 1974.
97
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14. Smith, Franklin, Wagoner, D. E., and Nelson, A. C., "Determination of
Stack Gas Velocity and Volumetric Flow Rates," EPA Contract 68-02-1234,
1HA327, Research Triangle Institute, Research Triangle Park, N.C.,
February 1974.
15. Driscoll, J. N., and Berger, A. W., "Improved Chemical Methods for
Sampling and Analysis of Gaseous Pollutants From the Combustion of Fossil
Fuels," Vol. I, "Sulfur Oxides," prepared for EPA by Walden Research
Corporation, Cambridge, Mass.
16. Driscoll, John N., Flue Gas Monitoring Techniques, Ann Arbor Sciences
Publishers, Inc., 1974.
17. Hamil, Henry F., Camann, David F., and Thomas, Richard E., "The Collabora-
tive Study of EPA Methods 5, 6 and 7 in Fossil Fuel-Fired Steam Generators,"
EPA-650/4-74-013, 1974.
18. Driscoll, John N., et. al., "Validation of Improved Chemical Methods for
Sulfur Oxides from Stationary Sources," Walden Research Corp., EPA Contract
No. 68-02-009, 1972.
19. Hamil, Henry F. , "Laboratory and Field Evaluations of EPA Methods 2, 6, and
7," EPA Contract 68-02-0626, Southwest Research Institute, San Antonio,
Texas 78284.
20. Cramer, H., The Elements of Probability Theory, John Wiley & Sons, 1955.
21. Statistical Research Group, Columbia University, C. Eisenhart, M. Hastay,
and W. A. Wallis, eds., Techniques of Statistical Analysis, New York:
McGraw-Hill, 1947.
22. Bowker, A. H., and Goode, H. P., Sampling Inspection Variables, New York:
McGraw-Hill, 1952.
23. Hald, A., Statistical Theory with Engineering Applications, New York:
John Wiley & Sons, 1952.
24. Owen, D. B., "Variables Sampling Plans Based on the Normal Distribution,1'
Technometrics, Vol. 9, No. 3, August 1967.
25. Owen, D. B., Summary of Recent Work on Variables Acceptance Sampling with
Emphasis on Non-normality," Technometrics, Vol. 11, 1969, pp. 631-37.
26. Takogi, Kinji, "On Designing Unknown Sigma Sampling Plans Based on a Wide
Class on Non-Normal Distributions," Technometrics, Vol. 14, 1972,
pp. 699-78.
27. Private communication with Dr. J. Knoll of the Quality Assurance Branch,
EMSL-EPA.
98
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APPENDIX A METHOD 8--DETERMINATION OF SULFURIC ACID MIST
AND SULFUR DIOXIDE EMISSIONS
FROM STATIONARY SOURCES
1. Principle and Applicability
1.1 Principle. A gas sample is extracted isokinetically from the stack.
The acid mist (including sulfur trioxide) and the sulfur dioxide are separated
and both fractions are measured separately by the barium-thorin titration method.
1.2 Applicability. This method is applicable for the determination of
sulfuric acid mist (including sulfur trioxide) in the absence of other partic-
ulaze matter and sulfur dioxide from stationary sources only when specified by
the test procedures for determining compliance with the new source performance
staidards. Collaborative tests have shown that the minimum detectible limits
3 -7 3
of the method are 0.05 mg/m (0.03 y 10 Ib/ft ) for sulfur trioxide and
3 -73
1.2 mg/m (0.74 x 10 Ib/ft ) for sulfur dioxide. No upper limits have been
established.
2. Apparatus
2.1 Sampling. A schematic of the sampling train used in this method is
shewn in figure 8-1; it is similar to the Method 5 train except that the filter
position is different and heating of the filter holder is not required.
Commercial models of this train are available. However, if one desires to build
his own, complete construction details are described in APTD-0581; for changes
from the APTD-0581 document and for allowable modifications to figure 8-1, see
the following subsections.
The operating and maintenance procedures for the sampling train are
described in APTD-0576. Since correct usage is important in obtaining valid
results, all users should read the APTD-0576 document and adopt the operating
and maintenance procedures outlined in it, unless otherwise specified herein.
Further details and guidelines on operation and maintenance are given in
Method 5 and should be read and followed whenever they are applicable.
2.1.1 Probe nozzle—Stainless steel (316) with sharp, tapered leading
edge. The angle of taper shall be < 30° and the taper shall be on the outside
tc preserve a constant internal diameter. The probe nozzle shall be of the
bL.ttonhook or elbow design, unless otherwise specified by the administrator.
TVe wall thickness of the nozzle shall be less than or equal to that of a 20-
99
-------
•H
01
I
a>
ca
•H
3
'O
•H
U
a
•H
t.0
I
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-------
gauge tubing, i.e., 0.165 cm (0.065 in.) and the distance from the tip of the
nozzle to the first bend or point of disturbance shall be at least two times
the outside nozzle diameter. The nozzle shall be constructed from seamless
stainless steel tubing. Other configurations and construction material may be
used with approval from the Administrator.
A range of sizes suitable for isokinetic sampling should be available,
e.g., 0.32 cm (1/8 in.) up to 1.27 cm (1/2 in. or larger if higher volume
sampling trains are used) inside diameter (ID) nozzles in increments of 0.16 cm
(1/16 in.). Each nozzle shall be calibrated according to the procedures out-
lined in the calibration section.
2.1.2 Probe liner—Porosilicate or quartz glass, with a heating system
to prevent visible condensation during sampling.
2.1.3 Pitot tube—Type S, or other device approved by the administrator,
attached to probe to allow constant monitoring of the stack gas velocity. The
face openings of the pitot tube and the probe nozzle shall be adjacent and
parallel to each other, not necessarily on the same plane, during sampling.
The free space between the nozzle and pitot tube shall be at least 1.9 cm
(0.7!) in.). The free space shall be set based on a 1.3-cm (0.5-in.) ID nozzle.
If the sampling train is designed for sampling at higher flow rates than that
described in APTD-0581, thus necessitating the use of larger sized nozzles, the
largest sized nozzle shall be used to set the free space.
The pitot tube must also meet the criteria specified in Method 2 and
calibrated according to the procedure in the calibration section of that method.
2.1.4 Differential pressure gauge—Inclined manometer capable of measuring
velocity head to within 10 percent of the minimum measured value. Beloxj a
differential pressure of 1.3 mm (0.05 in.) water gauge, micromanometers with
sensitivities of 0.013 mm (0.0005 in.) should be used. However, micromanometers
are not earily adaptable to field conditions and are not easy to use with
pulsating flow. Thus, methods or other devices acceptable to the administrator
may be used when conditions warrant.
2.1.5 Filger holder—Borosilicate glass with a glass frit filter support
and a silicone rubber gasket. Other materials of construction may be used
with approval from the administrator. The holder design shall provide a posi-
tive seal against leakage from the outside or around the filter.
101
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2.1.6 Impingers—Four, as shown in figure 8-1. The first and third shall
be of the Greenburg-Smith design with standard tips. The second and fourth shall
be of the Greenburg-Smith design, modified by replacing the insert with an
approximately 13-mm (0.5-in.) ID glass tube, having an unconstricted tip located
13 mm (0.5 in.) from the bottom of the flask. Similar collection systems, which
have been approved by the administrator may be used.
2.1.7 Metering system—Vacuum gauge, leak-free pump, thermometers capable
of measuring temperature to within 3° C (5.4° F), dry gas meter with 2 percent
accuracy, and related equipment, or equivalent, as required to maintain an
isokinetic sampling rate and to determine sample volume. When thes metering
system is used in conjunction with a pitot tube, the system shall enable checks
of isokinetic rates.
2.1.8 Barometer—Mercury, aneroid, or other barometers capable of meas-
uring atmospheric pressure to within 2.5 mmHg (0.1 in. Hg). In many cases, the
barometric reading may be obtained from a nearby weather bureau station, in
which the station value shall be requested and an adjustment for elevation
differences shall be applied at a rate of minus 2.5 mmHg (0.1 in. Hg) per 30 m
(100 ft) elevation increase.
2.1.9 Temperature gauge—Thermometer, or equivalent, to measure tempera-
ture of gas leaving impinger train to within 3° C (5° F).
2.2 Sample recovery.
2.2.1 Wash bottles—Polyethylene or glass, 500 mJl (two).
2.2.2 Graduated cylinders—250 m£, 1 £. (Volumetric flasks may also be
used.)
2.2.3 Storage bottles—Leak-free polyethylene bottles, l,000-m£ size
(two for each sampling run).
2.3 Analysis.
2.3.1 Pipette—Volumetric 25 m£, 100 m£.
2.3.2 Burette—50 m£.
2.3.3 Erlenmeyer flask—250 m&. (One for each sample blank and standard.)
2.3.4 Graduated cylinder—100 m£.
2.3.5 Trip balance—300-g capacity, to measure to + 0.5 g.
2.3.6 Dropping bottle—To add indicator solution, 125-m& size.
102
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3. Reagents
Unless otherwise indicated, it is intended that all reagents conform to the
specifications established by the Committee on Analytical Reagents of the
American Chemical Society, where such specifications are available; otherwise
use best available grade.
3.1 Sampling.
3.1.1 Filters—Glass fiber filters, without organic binder exhibiting at
least 99.95 percent efficiency (<_ 0.05 percent penetration) on 0.3 micron dioctyl
phthalate smoke particles. The filter efficiency test shall be conducted in
accordance with ASTM standard method D 2986-71. Test data from the supplier's
quality control program is sufficient for this purpose.
3.1.2 Silica gel—Indicating type, 6-16 mesh. If previously used, dry
at 175° C (350° F) for 2 hours. New silica gel may be used as received.
3.1.3 Water—Deionized, distilled, to conform to ASTM specifications
D1193-72, type 3.
3.1.4 Isopropanol, 80%—Mix 800 mil of isopropanol with 200 ml of deionized
distilled water. Note: Experience has shown that only ACS-grade isopropanol
is satisfactory.
3.1.5 Hydrogen peroxide, 3%—Dilute 100 ml of 30 percent hydrogen perox-
ide to 1 I with deionized, distilled water. Prepare fresh daily.
3.1.6 Crushed ice.
3.2 Sample recovery.
3.2.1 Water—Deionized, distilled, to conform to ASTM specifications
D1193-72, type 3.
3.2.2 Isopropanol, 80%—Mix 800 ml of isopropanol with 200 ml of deionized
distilled water. Note: Experience has shown that only ACS-grade isopropanol is
satisfactory.
3.3 Analysis.
3.3.1 Water—Deionized, distilled, to conform to ASTM specifications
D1193-72, type 3.
3.3.2 Isopropanol, 100%.
3.3.3 Thorin indicator—l-(o-arsonophenylazo)-2-naphthol-3, 6-disulfonic
acid, disodium salt, or equivalent. Dissolve 0.20 g in 100 ml of deionized
distilled water.
103
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3.3.4 Barium perchlorate (0.01 N)—Dissolve 1.95 g of barium perchlorate
trihydrate (Ba(C10^)2 • 3H20) in 200 m& deionized distilled water and dilute
to I H with isopropanol. Standardize with sulfuric acid as in section 5.2.
This solution must be protected against evaporation at all times. (Bad- may
also be used.)
3.3.5 Sulfuric acid standard (0.01 N)—Purchase or standardize to + 0.0002
N against 0.01 N NaOH which has previously been standardized against primary
standard potassium acid phthalate.
4. Procedure
4.1 Sampling.
4.1.1 Pretest preparation—Follow the procedure outlined in Method 5,
section 4.1.1, except that the filter need not be weighed or identified. If
the effluent gas is considered to be dry, i.e., moisture free, the silica gel
need not be weighed.
4.1.2 Preliminary determinations—Follow the procedure outlined in Method
5, section 4.1.2.
4.1.3 Preparation of collection train—Follow the procedure outlined in
Method 5, section 4.1.3, except for the second paragraph and use figure 8-1
instead of figure 5-1. Replace the second paragraph with: Place 100 m£ of
80% isopropanol in the first impinger, 100 m£ of 3% hydrogen peroxide in both
the second and third impingers, and about 200 g of silica gel in the fourth
impinger. Retain a portion of the reagents for use as blank solutions.
4.1.4 Leak-check procedure—Follow the procedure outlined in Method 5,
section 4.1.4, except that the probe heater shall be adjusted to the minimum
temperature required to prevent condensation.
4.1.5 Train operation—Follow the procedure outlined in Method 5, section
4.1.5, except record the data required on the example sheet shown in figure 8-2.
During the sampling period, observe the line between the probe and the first
impinger for signs of condensation. If it occurs, adjust the probe heater
setting upward to the minimum temperature required to prevent condensation.
After turning off the pump and recording the final readings at the conclusion
of each run, remove the probe from the stack and disconnect it from the train.
Drain the ice bath and purge the remaining part of the train by drawing clean
ambient air through the system for 15 minutes at the average flow rate used for
104
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sampling. Note: Clean ambient air can be provided by passing air through a
charcoal filter.
4.2 Sample recovery.
4.2.1 Container No. 1—Transfer the contents of the first impinger to a
250-mJl graduated cylinder. Rinse the probe, first impinger, and all connecting
glassware before the filter with 80% isopropanol. Add the rinse solution to the
cylinder. Dilute to 250 m& with 80% isopropanol. Add the filter to the solu-
tion, mix, and transfer to the storage container. Protect the solution against
evaporation. Mark the level of liquid on container and identify the sample
container.
4.2.2 Container No. 2—Transfer the solutions from the second and third
impingers to a 1,000 mi graduated cylinder. Rinse all glassware between the
filter and silica gel impinger with deionized. distilled water and add this
rinse water to the cylinder. Dilute to a volume of 1,000 m£ with deionized,
distilled water. Transfer the solution to a storage container. Mark the level
of liquid on container. Seal and identify the sample container.
4.3 Analysis.
Note level of liquid in containers 1 and 2 and confirm whether or not any
sample was lost during shipment by noting this on analytical data sheet.
4.3.1 Container No. 1—Shake the container holding the isopropanol solu-
tion and the filter. If the filter breaks up, allow the fragments to settle
for a few minutes before removing a sample. Pipette a 100-m& aliquot of this
solu:ion into a 250-m£ Erlenmeyer flask, add 2 to 4 drops of thorin indicator,
and titrate to a pink endpoint using 0.01 N barium perchlorate. Repeat the
titr.ation with a second aliquot of sample and average the titration values.
Replicate titrations should agree within 1 percent.
4.3.2 Container No. 2—Thoroughly mix the solution in the container
holding the contents of the second and third impingers. Pipette a 10-m£ ali-
quot of sample into a 250 m£ Erlenmeyer flask. Add 40 nA of isopropanol,
2 to 4 drops of thorin indicator, and titrate to a pink endpoint using 0.01 N
barium perchlorate. Repeat the titration with a second aliquot of sample and
average the titration values. Replicate titrations should agree within 1
percent.
4.3.3 Blanks—Prepare blanks by adding 2 to 4 drops of thorin indicator
to 300 mJl of 80% isopropanol. Titrate the blanks in the same manner as the
samples.
105
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5. Calibration
5.1 Use methods and equipment as specified in Methods 2 and 5 and APTD-
0576 to calibrate the orifice meter, pitot tube, dry gas meter, thermometers,
and barometer.
5.2 Standardize the barium perchlorate solution with 25 mi of standard
sulfuric acid, to which 100 mi of isopropanol have been added.
6. Calculations
Note; Carry out calculations retaining at least one extra
decimal figure beyond that of the acquired data. Round
off figures after final calculation.
6.1 Nomenclature.
2 2
A = Cross sectional area of nozzle, m (ft )
n
B = Water vapor in the gas stream, proportion by volume
cu en = Sulfuric acid (including SO.) concentration, g/dscm
24
Z (Ib/dscf)
Cqn = Sulfur dioxide concentration, g/dscm (Ib/dscf)
2
I = Percent of isokinetic sampling
N » Normality of barium perchlorate titrant, g equiv,./liter
P, = Barometric pressure at the sampling site, mmHg (In. Hg)
Del IT
P = Absolute stack gas pressure, mmHg (in. Hg)
P = Standard absolute pressure, 760 mmHg (29.92 in. Hg)
S L O
T = Absolute average dry gas meter temperature (see figure 8-2),
m
°V /°D\
«. ^ F*./
T = Absolute average stack gas temperature (see figure 8-2),
s
°V / O"D\
JX ^ J\/
T „ = Standard absolute temperature, 293° K (528° R)
std
V = Volume of sample aliquot titrated, 100 ml for H SO, and
10 mfc for S02
V. = Total volume of liquid collected in impingers and silica
Ic
gel (see figure 8-2), mi
106
-------
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V » Volume of gas sample as measured by dry gas meter, dcm (dcf)
V . . • Volume of gas sample measured by the dry gas meter corrected
m v,s Co/
to standard conditions, dscm (dscf).
v - Stack gas velocity, calculated by Method 2, equation 2-7,
s
using data obtained from Method 8, m/sec (ft/sec).
V . = Total volume of solution in which the sulfuric acid or sulfur
dioxide sample is contained, 250 m£ and 1,000 vA, respectively.
V = Volume of barium perchlorate titrant used for the sample, m£.
V , « Volume of barium perchlorate titrant used for the blank, mi.
Q «• Total sampling time, min.
13.6 - Specific gravity of mercury.
60 = Sec/min.
100 = Conversion to percent.
6,2 Average dry gas meter temperature and average orifice pressure drop.
See data sheet (figure 8-2).
6.3 Dry gas volume. Correct the sample volume measured by the dry gas
meter to standard conditions (20° C and 760 mmHg or 68° F and 29.92 in. Hg) by
using equation 8-1.
AH
T . PU + TTT PV + AH/13.6
v = v std bar 13.6 _ „ „ bar
m(std) m T P „. m T
m std m
Equation 8-1
where :
K = 0.3855 °K/mmHg for metric units
= 17.65 °R/in. Hg for English units.
6.4 Volume of water vapor and moisture content. Use equations 5-2 and
5-3 of Method 5. If the effluent gas is considered to be dry, these calcula-
tions need not be carried out.
6.5 Sulfuric acid (including SO ) concentration.
N (V - V ) /oln
cu en = a Equation 8-2
H SO
v
m(std)
108
-------
where:
K - 0.04904 g/equivalent for metric units
1.08 x 10~4 /wx for English units.
6.6 Sulfur dioxide concentration.
N (V. - V )
C - K _ a Equation 8-3
bO
V
m(std)
where :
K = 0.03203 g/equivalent for metric units
= 7.05 x 10~5 oN for English units.
(g)(mx,)
6.7 Isokinetic variation.
6.7.1 Calculations from raw data.
100 T [K V, + (V /T ) (P, + AH/13.6)]
., _ s Ic m m bar
60 6 v P A
s s n
Equation 8-4
where:
K = 0.00346 mmHg-m3/ml-°K for metric units
3
= 0.00267 in. Hg-ft /m£-°R for English units
6.7.2 Calculations from intermediate values.
T V , ,N P ,100
T s m(std) std
T ^, v 0 A P 60 (1-B )
std s n s ws
s s n ws
where:
K = 4.323 for metric units
= 0.0944 for English units.
109
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6.8 Acceptable results. If 90 percent £ I _< 110 percent, the results are
acceptable. If the results are low in comparison to the standards and I is
beyond the acceptable range, the administrator may option to accept the results.
Use reference 7.4 of Method 5 to make judgments. Otherwise, reject the results
and repeat the test.
7. References
7.1 Atmospheric Emissions from Sulfuric Acid Manufacturing Processer,
U.S. DHEW, PHS, Division of Air Pollution, Public Health Service Publication
No. 999-AP-13, Cincinnati, Ohio, 1965.
7.2 Corbett, D. F., "The Determination of SO and SO in Flue Gases,"
£• J
Journal of the Institute of Fuel, 24; 237-243, 1961.
7.3 Martin, Robert M., "Construction Details of Isokinetic Source
Sampling Equipment," Environmental Protection Agency, Air Pollution Control
Office Publication No. APTD-0581.
7.4 Patton, W. F., and Brink, Jr., J. A., New Equipment and Techniques
for Sampling Chemical Process Gases, J. Air Pollution Control Assoc. 13,
162 (1963).
7.5 Rom, J. J., "Maintenance, Calibration, and Operation of Isokinetic
Source-Sampling Equipment," Office of Air Programs, Environmental Protection
Agency, Research Triangle Park, N.C., March 1972. APTD-0576.
7.6 Hamil, H. F., and Camann, D. E., Collaborative Study of Method for
the Determination of Sulfur Dioxide Emissions from Stationary Sources.
Prepared for Methods Standardization Branch, Quality Assurance and Environmental
Monitoring Laboratory, National Environmental Research Center, Environmental
Protection Agency, Research Triangle Park, N.C., 27709.
7.7 Annual Book of ASTM Standards. Part 23; Water, Atmospheric Analysis.
pp. 203-205. American Society for Testing Materials, Philadelphia, Penn. (1972
110
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APPENDIX B ILLUSTRATED AUDIT PROCEDURES AND CALCULATIONS
A flow chart of the operations involved in an auditing program, from
first setting desired limits on the data quality to filing the results, is
given in the following pages. Assumed numbers are used and a sample cal-
culation of an audit is performed in the flow chart. Each operation has
references to the section in the text of the report where it is discussed.
Ill
-------
MANAGER
LIMITS FOR DATA QUALITY CAN BE SET BY WHAT
IS DESIRED OR FROM THE NATURAL VARIABILITY
OF THE METHOD WHEN USED BY TRAINED AND
COMPETENT PERSONNEL. FOR THIS EXAMPLE, IT
IS ASSUMED THAT a{SOo} = 4.0 mg/m3 (subsec.
4.1)*, AND USING + 3 a{S02), THE LIMITS
ARE L = 12.0 mg/m3 AND U = +12.0 mg/m3.
2. FROM PRIOR KNOWLEDGE OF DATA QUALITY, ESTIMATE
THE PERCENTAGE OF FIELD MEASUREMENTS FALLING
OUTSIDE THE ABOVE LIMITS. IF NO INFORMATION
IS AVAILABLE, MAKE AN EDUCATED GUESS. IT IS
ASSUMED IN THIS EXAMPLE THAT 50 PERCENT OF THE
FIELD DATA ARE OUTSIDE THE LIMITS L AND U
(subsec. 4.4.3).
3. DETERMINE: (1) COST OF CONDUCTING AN AUDIT,
(2) COST OF FALSELY INFERRING THAT GOOD DATA
ARE BAD, (3) COST OF FALSELY INFERRING THAT
BAD DATA ARE GOOD, AND (4) COST SAVINGS FOR
CORRECTLY IDENTIFYING BAD DATA (subsec. 4.4.3).
4. DETERMINE THE AUDIT LEVEL EITHER BY (1) MINI-
MIZING AVERAGE COST USING EQUATION (22) OF
SUBSECTION 4.4.3, OR (2) ASSURING A DESIRED
LEVEL OF CONFIDENCE IN THE REPORTED DATA
THROUGH STATISTICS. FOR THIS EXAMPLE, THE
AUDIT LEVEL IS TAKEN AS n = 7.
5. BY TEAMS, TY^ES OF SOURCES, OR GEOGRAPHY,
GROUP FIELD TESTS INTO LOTS (GROUPS) OF ABOUT
20 THAT WILL BE PERFORMED IN A PERIOD OF ONE
CALENDAR QUARTER.
6. SELECT n OF THE N TESTS FOR AUDITING. COMPLETE
RANDOMIZATION MAY NOT BE POSSIBLE DUE TO AUDI-
TOR'S SCHEDULE. THE PRIMARY POINT IS THAT THE
FIELD TEAM SHOULD NOT KNOW IN ADVANCE THAT
THEIR TEST IS TO BE AUDITED.
7. ASSIGN OR SCHEDULE AN AUDITOR FOR EACH FIELD
TEST.
SET DESIRED
LOWER AND UPPER
LIMITS FOR DATA
QUALITY, L AND U
ESTIMATE AVERAGE
QUALITY OF FIELD
DATA IN TERMS OF
L AND U
DETERMINE OR
ASSUME RELEVANT
COSTS
DETERMINE AUDIT
LEVEL FROM
STATISTICS, OR
AVERAGE COST
GROUP FIELD TESTS
INTO LOT SIZES OF
ABOUT N = 20
RANDOMLY SELECT
n OF THE N TESTS
FOR AUDITING
ASSIGN/SCHEDULE
AUDITOR(S) FOR
FOR THE n AUDITS
3
*Based on a 100 mg/m sample mean and o = 4.0 mg/m
T
112
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AUDITOR
8. THE AUDITOR OBTAINS APPROPRIATE CALIBRATED
EQUIPMENT AND SUPPLIES FOR THE AUDIT
( subsection 4.3).
9. OBSERVE THE FIELD TEAM'S PERFORMANCE OF THE
FIELD TEST (subsection 4.3.2 AND 4.3.3) AND NOTE
ANY UNUSUAL CONDITIONS THAT OCCURRED DURING
THE TEST.
10. THE AUDITOR'S REPORT SHOULD INCLUDE (1) DATA
SHEET FILLED OUT BY THE FIELD TEAM ,
(2) AUDITOR'S COMMENTS, (3) AUDIT DATA SHEET
WITH CALCULATIONS , AND (4) A SUMMARY OF THE
TEAM'S PERFORMANCE WITH A NUMERICAL RATING
( subsection 4.3.4).
11. THE AUDITOR'S REPORT IS FORWARDED TO THE
MANAGER.
MANAGER
12. COLLECT THE AUDITOR'S REPORTS FROM THE n
AUDITS OF THE LOT OF N STACKS. IN THIS
CASE n = 7 AND ASSUMED VALUES FOR THE
AUDITS ARE d, =-12, d2 =6, d3 = 0,
d. - 20, d5' = 17.4, d6 = 8.1, and d7 = 0
(table 8).
13. CALCULATE cT AND sd ACCORDING TO THE SAMPLE IN
TABLE 8. RESULTS OF THIS SAMPLE CALCULATION
8
PREPARE EQUIPMENT
AND FORMS
REQUIRED IN AUDIT
10
SHOW d = 5.6 and s
tion 4.4.2).
= 11.6 (table 8, subsec-
14.
USE A t-TEST TO CHECK d FOR SIGNIFICANCE, FOR
THIS EXAMPLE t = (5.6 x /7)/4.0 = 3.70. THE
TABULATED t-VALUE FOR 6 DEGREES OF FREEDOM AT
THE 0.05 LEVEL OS 1.943; HENCE, d IS
SIGNIFICANTLY DIFFERENT FROM 0 AT THIS LEVEL.
ALSO, s . IS CHECKED AGAINST THE ASSUMED VALUE
OF 4.00amg/m3 BY A CHI-SQUARE TEST.
X2/f = sjj/a2{d} = (n.6)*/(4.00)2 = 8.4,
THE TABULATED VALUE OF x /6 AT THE 95 PER-
CENT LEVEL IS 1.64; HENCE, s, IS SIGNIFICANTLY
DIFFERENT FROM 4.0 mg/m3. a
11
12
13
14
OBSERVE OM-SITE
PERFORMANCE
OF TEST
PREPARE
AUDIT
REPORT
FORWARD
REPORT TO
MANAGER
COMBINE
RESULTS OF
n AUDITS
CALCULATE THE
MEAN, d, AND
STANDARD
DEVIATION, sd
_ TEST
d AND s.
113
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15. OBTAIN THE VALUE OF k FROM TABLE 9, FOR n = 7 15
AND p = 0.1. THIS VALUE IS 2.334, THEN
d + k sd = 32.7 mg/m3 AND 3 - k sd = -21.5 mg/m3
( subsection 4.4.2).
16. COMPARE THE ABOVE CALCULATIONS WITH LIMITS 16
L AND U (subsec. 4.4.2). FOR THIS EXAMPLE
d + k sd = 32.7 > U = 12.0mg/m3
cf - k S(j = -21.5 < L = -12.0 mg/m3
BOTH CONDITIONS'ARE VIOLATED.
17. STUDY THE AUDIT AND FIELD DATA FOR SPECIFIC 17
AREAS OF VARIABILITY, SELECT THE MOST COST-
EFFECTIVE ACTION OPTION (S) THAT WILL RESULT
IN GOOD QUALITY DATA (subsection 4.2). NOTIFY
THE FIELD TEAMS TO IMPLEMENT THE SELECTED
ACTION OPTION(S).
18. A COPY OF THE AUDITOR'S REPORT SHOULD BE SENT 18
TO THE RESPECTIVE FIELD TEAM. ALSO, THE DATA
ASSESSMENT RESULTS, i.e., CALCULATED VALUES OF
d, sd, AND COMPARISON WITH THE LIMITS L AND U
SHOULD BE FORWARDED TO EACH TEAM INVOLVED IN
THE N FIELD TESTS.
19. THE FIELD DATA WITH AUDIT RESULTS ATTACHED ARE 19
FILED. THE AUDIT DATA SHOULD REMAIN WITH THE
FIELD DATA FOR ANY FUTURE USES.
CALCULATE
d + k sd
AND
d - k sd
COMPARE
(16) WITH
L AND U
MODIFY
MEASUREMENT
METHOD
INFORM
FIELD TEAMS
OF AUDIT
RESULTS
FILE AND
CIRCULATE OR
PUBLISH FIELD
DATA
114
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APPENDIX C GLOSSARY OF SYMBOLS
This is glossary of symbols as used in this document. Symbols used and
defined in the reference method (appendix A) are not repeated here.
SYMBOL DEFINITION
N Lot size, i.e., the number of field tests to be treated as a
group.
n Sample size for the quality audit (section IV).
CV{x} Assumed or known coefficient of variation (100 a /y ) .
A X
/s
CV{X} Computed coefficient of variation (100 s /X) from a finite
A
sample of measurements.
a{X} Assumed standard deviation of the parameter X (population
standard deviation).
/\
T{X} Computed bias of the parameter X for a finite sample
(sample bias).
d. The difference in the audit value and the value arrived at by
the field crew for the j audit.
d Mean difference between C. and C . for n audits.
J aj
s Computed standard deviation of differences between C. and C .,
p Percent of measurements outside specified limits L and U.
k Constant used in sampling by variables (section IV).
P{Y} Probability of event Y occurring.
t, ,x Statistic used to determine if the sample bias, d, is
(n -1)
significantly different from zero (t-test).
2 2
X /(n -1) Statistic used to determine if the sample variance, s , is
2
significantly different from the assumed variance, Q , of
the parent distribution (chi-square test).
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APPENDIX C
SYMBOL
L
U
CL
LCL
UCL
C
C
a
C
m
GLOSSARY OF SYMBOLS (CONTINUED)
DEFINITION
Lower quality limit used in sampling by variables.
Upper quality limit used in sampling by variables.
Center line of a quality control chart.
Lower control limit of a quality control chart.
Upper control limit of a quality control chart.
Concentration reported by the field team for field test,
Concentration used in an audit check.
Measured value of a calibration sample.
Assayed or known value of a calibration sample.
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APPENDIX D
GLOSSARY OF TERMS
The following glossary lists and defines the statistical terms used in
this document.
Accuracy
Bias
Lot
Measurement method
Measurement process
Population
Piecision
Quality audit
Quality control
check
Sample
The degree of agreement of a measurement (or an average
of measurements of the same thing), X, with an accepted
reference or true value, T, usually expressed as the
difference between the two values, X - T.
The systematic or nonrandom component of measurement
error. A measure of lack of agreement. If the measured
value is compared with an assumed true value, bias is a
measure of lack of accuracy.
A specified number of objects to be treated as a group,
e.g., the number of field tests to be conducted by an
organization during a specified period of time (usually
a calendar quarter).
A set of procedures for making a measurement.
The process of making a measurement, including method,
personnel, equipment, and environmental conditions.
The totality of the set of items, units, or measurements,
real or conceptual, that is under consideration.
The degree of variation among successive, independent
measurements (e.g., on a homogeneous material) under
known conditions, and usually expressed as a standard
deviation or as a coefficient of variation.
A management tool for independently assessing data quality.
Checks made by the field and/or laboratory crew on certain
items of equipment and procedures to assure data of good
quality.
Objects drawn, usually at random, from the lot for check-
ing or auditing purposes.
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1 REPORT NO.
EPA-650/4-74-005g
3. RECIPIENT'S ACCESSION>NO.
4 TITLE ANDSUBTITLE
"Guidelines for Development of a Quality Assurance
Program: Determination of Sulfuric Acid Mist and
Sulfur Dioxide Emissions from Stationary Sources"
5. REPORT DATE
Marrh 1976
6. PERFORMING ORGANIZATION CODE
7 AUTHOR(S)
J. W. Buchanan
D. E. Wagoner
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Research Triangle Institute
P.O. Box 12194
Research Triangle Park, NC 27709
10. PROGRAM ELEMENT NO.
1HA327
11. CONTRACT/GRANT NO.'
68-02-1234
12. SPONSORING AGENCY NAME AND ADDRESS
Office of Research and Development
U.S. Environmental Protection Agency
Washington, D. C. 20460
13. TYPE OF REPORT AND PERIOD COVERED
14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
16. ABSTRACT
Guidelines for the quality control of stack gas analysis for sulfuric acid
mist and sulfur dioxide emissions by the Federal reference method are presented.
These include:
1. Good operating practices;
2. Directions on how to assess performance and to qualify data;
3. Directions on how to identify trouble and to improve data quality;
4. Directions to permit design of auditing activities.
The document is not a research report. It is designed for use by operating
personnel.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
Quality Assurance
Quality Control
Air Pollution
Gas Sampling
Stack Gases
b.IDENTIFIERS/OPEN ENDED TERMS C. COSATI Field/Group
13H
14D
13B
14B
21B
13 DISTRIBUTION STATEMENT
Unlimited
19. SECURITY CLASS (This Report/
Unclassified
21. NO OF PAGES
20. SECURITY CLASS (This page)
Unclassified
22. PRICE
EPA Form 2220-1 (9-73)
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