EPA-650/4-74-005-f
November 1975 Environmental Monitoring Series
GUIDELINES FOR DEVELOPMENT
OF A QUALITY ASSURANCE PROGRAM:
VOLUME VI - DETERMINATION
OF NITROGEN OXIDE EMISSIONS
FROM STATIONARY SOURCES
Office of Research and Development
US. Environmental Protection Agency
Washington, DC 20460
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EPA-650/4-74-005-f
GUIDELINES FOR DEVELOPMENT
OF A QUALITY ASSURANCE PROGRAM:
VOLUME VI - DETERMINATION
OF NITROGEN OXIDE 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
November 1975
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EPA REVIEW NOTICE
This report has been reviewed by the U.S. Environmental Protection
Agency and approved for publication. Approval does not signify that
the contents necessarily reflect the views and policies of the Environ-
mental Protection Agency, nor does mention of trade names or commer-
cial products constitute endorsement or recommendation for use.
RESEARCH REPORTING SERIES
Research reports of the Office of Research and Development, U.S. Environ-
mental Protection Agency, have been grouped into series. These broad
categories were established to facilitate further development and applica-
tion of environmental technology. Elimination of traditional grouping was
consciously planned to foster technology transfer and maximum interface
in related fields. These series are:
1. ENVIRONMENTAL HEALTH EFFECTS RESEARCH
2 . ENVIRONMENTAL PROTECTION TECHNOLOGY
3. ECOLOGICAL RESEARCH
4. ENVIRONMENTAL MONITORING
5 . SOCIOECONOMIC ENVIRONMENTAL STUDIES
6. SCIENTIFIC AND TECHNICAL ASSESSMENT REPORTS
9. MISCELLANEOUS
Tins report has been assigned to the ENVIRONMENTAL MONITORING
scries. This series describes research conducted to develop new or
improved methods and instrumentation for the identification and quantifica-
tion of environmental pollutants at the lowest conceivably significant
concentrations. It also includes studies to determine the ambient concentra-
tions of pollutants in the environment and/or the variance of pollutants
as a function of time or meteorological factors.
This document is available to the public for sale through the National
Technical Information Service, Springfield, Virginia 22161.
Publication No. EPA-650/4-74-005-f
11
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ABSTRACT
Guidelines for the quality control of stack gas analysis
for nitrogen oxides, except nitrous oxide, 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 Sponsor-
ship of the Environmental Protection Agency. Work was completed as
of Augast 1975.
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TABLE OF CONTENTS
SECTION PAGE
I INTRODUCTION 1
ii OPERATIONS mm. 4
2.0 GENERAL . 4
2.1 PLAN ACTIVITY MATRIX 8
2.2 EQUIPMENT SELECTION 19
2.3 EQUIPMENT CHECK AND CALIBRATION 24
2.4 PRESAMPLING PREPARATION 26
2.5 ON-SITE MEASUREMENTS 29
2.6 POST-SAMPLING OPERATIONS (LABORATORY) 33
111 MNUAL FOR FIELD TEAM SUPERVISOR *i
3.0 GENERAL 41
3.1 ASSESSMENT OF DATA QUALITY (INTRATEAM) 42
3.2 MONITORING DATA QUALITY 44
3.3 COLLECTION AND ANALYSIS OF INFORMATION
TO IDENTIFY TROUBLE 45
IV mm. FOR IWIAGER OF GROUPS OF FIELD TEAMS 53
4.0 GENERAL 53
4.1 FUNCTIONAL ANALYSIS OF THE TEST METHOD 57
4.2 ACTION OPTIONS 62
4.3 PROCEDURES FOR PERFORMING A QUALITY AUDIT 70
4.4 DATA QUALITY ASSESSMENT 73
V REERENCES 85
APPENLIX A fOOD 7 87
/fPENDIXB ILLUSTRATED AUDIT PROCEDURES AND CALCULATIONS 100
APPENDIX C GLOSSARY OF SYTCOLS 104
APPENDIX D GLOSSARY OF TERMS ioe
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LIST OF IUUSTWIONS
FIGURE NO. PAGE
1 Operational flow chart of the measurement process 5
2 N0¥ field data sheet 34
A
3 NO laboratory data sheet 37
/\
4 Typical calibration curve for determination of
NO concentration from absorbance 46
^
5 Quality control chart for d. '47
J
6 Interference of HC1 with the determination of NO 51
/\
7 Summary of data quality assurance program 56
8 Added cost versus data quality (CV) for selected
action options 67
9 Added cost versus data quality (CV.} for selected
action options 68
10 Example illustrating p<0.10 and satisfactory data
quality 78
11 Example illustrating p>0.10 and unsatisfactory data
quality 78
12 Flow chart of the audit level selection process 80
13 Average cost versus audit level (n) 84
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LIST OF TABlfS
TABLE NO. PAGE
1 Methods of monitoring variables 52
2 Estimates of reading errors in determination of V 60
3 Estimate for reproducibility of ER 61
4 Assumed within-laboratory, between-laboratory, and
laboratory bias for action options 64
5 Computation of mean difference, d, and standard
deviation of differences, sd 77
6 Sample plan constants, k for P {not detecting a lot
with proportion p outside limits L and U}£0.1 79
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SECTION I INTRODUCTION
This document presents guidelines for developing a quality assurance
program for Method 7, Determination of Nitrogen Oxide, Except Nitrous
Oxide, Emissions from Stationary Sources. This method was initially pub-
lished by the Environmental Protection Agency in the Federal Register,
December 23, 1971, and a later version 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
operating procedures to insure the collection of data of high quality,
and instructions 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 mea-
surements are made. A Plan Activity Matrix is included.
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 Manager 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
properties of and procedures for carrying out auditing procedures for an
independent assessment of data quality.
The objectives of this quality assurance program for Method 7 are to:
1. Minimize systematic errors (biases) and maintain precision
within acceptable limits in the measurement process,
?. Provide routine indications for operating purposes of
satisfactory performance of personnel and/or equipment,
3. Provide for prompt detection and correction of conditions that
contribute to the collection of poor quality data, and
4. Collect and supply information necessary to describe the quality
of the data.
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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 for all the methods 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 signifi-
cant factor in the total variability. The error 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 7 as presented here are
designed to insure the collection of data of acceptable quality by preven-
tion, detection, 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 WNUAL
2.0 GENERAL
This manual sets forth recommended procedures for determination of
nitrogen oxide emissions from stationary sources according to Method 7.
(Method 7 is reproduced and included as appendix A of this document.)
Quality control procedures and checks designed to give an indication or
warning that invalid or poor quality data 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 prescribed by the supervisor for assurance of
data quality may be required of the operator on special occasions.
The sequence of operations to be performed for each field test is
given in figure 1. Each operation or step in the method is identified by
a block. Quality checkpoints in the measurement process, for which appro-
priate quality control limits are assigned, are represented by blocks
enclosed by heavy lines. Other quality checkpoints involve go/no-go checks
and/or subjective judgments by the test team members with proper guidelines
for decisionmaking 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 operator performs his various tasks. From equipment checks through
on-site measurements, calculations, and data reporting, this method is
susceptible to a variety of errors. Detailed instructions are given for
minimizing or controlling equipment error, and procedures are recommended
to minimize operator error. Before using this document, the operator
should study Method 7 as reproduced in appendix A in detail. In addition,
the quality assurance documents of this series for Methods 2, 3, and 4
should be read and followed.
It is assumed that all apparatus satisfies the reference method
specifications and that the manufacturer's recommendations will be followed
when using a particular piece of equipment.
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EQUIR-ENT SELECTION
1. SELECT THE EQUIPMENT APPRO-
PRIATE FOR THE PROCESS (SOURCE)
TO BE TESTED. CHECK THE EQUIP-
MENT FOR PROPER OPERATION.
EQUIPMENT CHECK AND CALIBRATION
2. CALIBRATE EQUIPMENT WHEN FIRST
PURCHASED AND WHEN DAMAGED OR
ERRATIC BEHAVIOR IS OBSERVED.
(Subsection 2.3)
PRESAMPLING PREPARATION
3. OBTAIN PROCESS DATA, SELECT/
PREPARE SAMPLING SITE, DETERMINE
LOGISTICS FOR PLACING EQUIPMENT
ON-SITE, AND DETERMINE STACK
CONDITIONS Ts, Vs, Bw, and Md.
(Subsection 2.4.1)
4. CHECK OUT SAMPLE TRAIN AND
RELATED COMPONENTS.
(Subsection 2.4.2)
5. PACKAGE EQUIPMENT IN A MANNER
TO PREVENT BREAKAGE OR DAMAGE
DURING HANDLING AND SHIPMENT.
SHIP EQUIPMENT BY THE BEST
MEANS AVAILABLE. (Subsection
2.4.4)
ON-SITE NOX MEASUREMENT
6. MOVEMENT OF EQUIPMENT TO
SAMPLING SITE AND SAMPLE
RECOVERY AREA. (Subsection
2.5.1)
7. ASSEMBLE THE EQUIPMENT ON-SITE
AND PERFORM AN OPERATIONAL
CFICK. (EVALUATION OF THE
SYSTEM)
8. DETERMINE THE TRAVERSE
POINT (SAMPLE POINT) ACCORDING
TO METHOD ONE.
EQUIPMENT
SELECTION
EQUIPMENT CHECK
AND CALIBRATION
PRELIMINARY
SITE-VISIT
(OPTIONAL)
APPARATUS
CHECK
1
PACKAGE
EQUIPMENT
FOR SHIPMENT
TRANSPORT
EQUIPMENT
TO SITE
ASSEMBLE/CHECK
EQUIPMENT
ON-SITE
T
DETERMINE
TRAVERSE POINT
Figure 1. Operational flow chart of the measurement process.
5
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9. DETERMINE THE INSIDE AREA OF 9
STACK BY (1) MEASURING THE
DIAMETER, OR (2) MEASURING
THE CIRCUMFERENCE AND COR-
RECTING FOR WALL THICKNESS.
10. PERFORM THE VELOCITY TRAVERSE 10
OF THE STACK GAS USING THE
QUALITY ASSURANCE DOCUMENT
FOR METHOD 2.
11. DETERMINE THE MOISTURE 11
CONTENT OF THE STACK GAS
USING THE QUALITY ASSURANCE
DOCUMENT FOR METHOD 4.
12. DETERMINE THE MOLECULAR WEIGHT 12
OF THE STACK GAS (WET BASIS)
USING THE QUALITY AS'SURANCE
DOCUMENT FOR METHOD 3 AND THE
RESULTS OF STEP 11 ABOVE.
13. DETERMINE THE VOLUMETRIC FLOW 13
RATE OF THE SOURCE USING THE
QUALITY ASSURANCE DOCUMENT
FOR METHOD 2.
14. PREPARE ABSORBING REAGENT 14
AND/OR ACCURATELY PIPETTE
25 ml OF REAGENT INTO THE
COLLECTION FLASK(S).
15. EVACUATE FLASK(S), MEASURE 15
AND RECORD FINAL FLASK
PRESSURE AND AMBIENT
TEMPERATURE.
16. PERFORM SAMPLE COLLECTION 16
ACCORDING TO THE PROCEDURE
GIVEN IN SUBSECTION
(Subsection 2.5.3.3)
17. MEASURE AND RECORD THE 17
INTERNAL PRESSURE (ABSOLUTE)
OF THE COLLECTION FLASK(S).
18. MAKE SOLUTION ALKALINE BY 18
ADDING 1 N NAOH.
DETERMINE
INSIDE AREA
OF STACK
PERFORM
VELOCITY
TRAVERSE
(METHOD 2)
J_
DETERMINE
MOISTURE
CONTENT
(METHOD 4)
DETERMINE
MOLECULAR
WEIGHT
(METHOD 3)
DETERMINE
VOLUMETRIC
FLOW RATE
(METHOD 2)
PIPETTE 25 ml
ABSORBING
REAGENT INTO
SAMPLING FLASKS
JL
EVACUATE
FLASK(S) AND
RECORD DATA
COLLECT
SAMPLE
MEASURE AND
RECORD FLASK
PRESSURE
MAKE SOLUTIONS
ALKALINE WITH
1 N NAOH
Figure 1. Operational flow chart of the measurement process (continued)
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19. DISASSEMBLE AND INSPECT EQUIP- 19
MENT FOR DAMAGE SUSTAINED BUT
NOT DETECTED DURING SAMPLING.
20. PACKAGE EQUIPMENT AND SAMPLES 20
FOR RETURN TRIP TO BASE
LABORATORY.
POSMHING OPERATIONS
21. ANALYZE SAMPLES FOR OXIDES 21
OF NITROGEN BY THE PHENOL-
DISULFURIC ACID PROCEDURE
(Subsection 2.6.1)
22. PERFORM CALCULATIONS UTILIZING 22
ALL FIELD AND CALIBRATION
DATA (Subsection 2.6.2)
23. FORWARD THE DATA FOR FURTHER 23
INTERNAL REVIEW OR TO THE
USER.
DISASSEMBLE
AND CHECK
EQUIPMENT
PACK EQUIPMENT
AND SAMPLES
FOR SHIPMENT
PERFORM
ANALYSES
1
PERFORM
CALCULATIONS
REPORT
DATA
Figure 1. Operational flow chart of the measurement process,
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2.1 PLAN ACTIVITY MATRIX
This section consists of a Plan Activity Matrix which summarizes
the entire measurement procedure and includes acceptance criteria for
procurement of materials, preparation of reagents, calibration of equip-
ment and maintenance.
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2.2 EQUIPMENT SELECTION
In addition to the Plan Activity Matrix (section 2.1), a listing
of the required apparatus for a sampling train (configured as shown in
figure 7-1 of appendix A) and the reagents, along with certain miscellaneous
equipment and tools to aid in source testing, is given in subsection 2.3.
Additional specifications, criteria, and/or design features as applicable
are given here to aid in the selection of equipment to insure the collection
of data of consistent quality. All new items of equipment are inspected
visually for identification and damage before acceptance. Also, if applicable,
new equipment is calibrated according to section 2.3 as part of the acceptance
check. The descriptive title, identifcation number, if applicable, and the
results of the acceptance check are recorded in the procurement log book,
dated, and signed by the individual performing the check. Calibration data
generated in the acceptance check is recorded in the calibration log book.
2.2.1 Sampling
2.2.1.1 Sampling Probe. A glass probe (borosilicate glass) with provisions
for heating, with a filter (either in stack or heated out of stack) to
remove particulate matter. The glass liner should be protected with an
outer sheath of stainless steel. The sampling tip of the probe should
have retainers fabricated of glass to hold the particulate filter in
place. Heating is not required if the probe remains dry during the
purging period. It is recommended that an all-purpose probe have
provisions for heating. High temperature probes can be fabricated
from quartz. A knowledge of the stack gas composition and temperature
is necessary in order to select a probe of proper composition. Special
probes must be approved by the EPA.
2.2.1.2 Collection Flask(s). Two liter borosilicate round bottom flasks
with a short neck and 24/40 standard taper opening. The collection flask
should be protected against implosion or breakage by (1) tape, or by using
a (2) commercial unit encased in foam, or (3) a fabricated closed cell foam
system.
19
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2-2.1.3 Flask Valve(s). A T-bore stopcock is connected to a 24/40 standard
taper joint. Bores should be numbered and not switched to prevent leakage
problems. The T-bore should be marked to avoid turning the stopcock in the
wrong direction when sampling.
2-2-l-4 Temperature Gauge. Dial-type thermometer, or equivalent, capable
of measuring in 1° C (2° F) intervals from -5 to 50° C (25 to 125° F).
2.2.1.5 Vacuum Line. Sufficient tubing which is capable of withstanding
a vacuum of 75 mm (3 inches) Hg absolute pressure. This tubing must be
equipped with a "T" connection and a three-way valve (T-bore stopcock) or
its equivalent. When possible, glass ball-joint connections should be re-
placed by plastic components to minimize leakage problems.
Note: Plastic components must not contact the sample
gas before entering the flask.
2.2.1.6 Pressure Gauge. A U-tube manometer, 1 meter with 1 mm divisions,
or equivalent.
2.2.1.7 Pump. One vacuum pump capable of producing a vacuum of 21.75 mmHg
(3 inches Hg) absolute pressure in the sample flask.
2.2.1.8 Squeeze Bulb. A one-way bulb (rubber) to purge the sampling system.
2.2.1.9 Stopcock Grease. An inert, high vacuum, high temperature chloro-
fluorocarbon grease should be used.
2.2.1.10 Volumetric Pipette. A 25 m£ volumetric pipette for addition of
reagent to the collection flask.
2.2.1.11 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.
(b) A 1/2" 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 (1/4") for securing equipment and tarpaulin.
20
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(d) One 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 guard
rails 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 glasses and/or safety goggles.
(d) Protective clothing including the following: appropriate
suits for both heat and cold, gloves (both asbestos and
cloth) and steel-toes shoes.
(e) Steel cable (3/16") 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
(4) Ammeter-voltmeter-ohmeter (VOM)
(5) Extension cords - light (#14 Avg) 2 x 25
(6) 2 3- .tfire electrical adapters
(7) '-wire electrical triple taps
(8) Thermocouple extension wire
(9) Thermocouple plugs
(10) Fuses
(11) Electrical wire
(b) Tools
(1) Tool boxes (1 large, 1 small)
(2) Screwdrivers
1 set flat blade
1 set philips
(3) C-clamps (2) 6", 3"
21
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(c) Wrenches
(1) Open end set 1/4" to 1"
(2) Adjustables (12", 6")
(3) 1 chain wrench
(4) 1 12" pipe wrench
(5) 1 Allen wrench set
(d) Miscellaneous
(1) Silicone sealer
(2) Silicone vacuum grease
(3) Pump oil
(4) Manometers (gauge oil)
(5) Anti-seize compound
(6) Pipe fittings
(7) Dry cell batteries
(8) Flashlight
(9) Valves
(10) Thermometers (Dial (6"-36")
and a remote reading thermometer
(11) Vacuum gauge
(12) SS tubing (1/4", 3/8", 1/2") short lengths
(13) Heavy-duty wire (telephone type)
(14) Adjustable packing gland
(4) Data Recording
(a) Data sheets or data notebook
(b) Carbon paper
(c) Slide rule or electronic calculator
(d) Psychometric charts
(e) Combustion nomographs (Ref. 15)
(f) Pencils, pens
2.2.2 Sample Recovery
2.2.2.1 Volumetric Pipette or Dropper. A 25 m£ volumetric pipette or
dropper for neutralization. The pipette (25 mfc) can also be used to
add 25 n£ of reagent to the flask before sampling (2.2.1.10).
22
-------
2.2.2.2 Storage Containers. An adequate number of leak-free glass or
polyethylene bottles for recovery of samples. The containers should be
packed in a cushioned container (box or foot locker) for shipment.
2.2.2.3 Wash Bottle. A glass or polyethylene wash bottle for rinsing
(transferral) of sample solution to storage containers.
2.2.2.4 Glass Stirring Rod. A stirring rod (glass or polyethylene) is
required to check the pH of the absorbing reagent.
2.2,2.5 pH Indicating Paper. pH paper with the range of 7-14 is required
to test the alkalinity of the absorbing reagent.
2.2.2.6 Barometer. A calibrated barometer (shock mounted) for measuring
the barometric pressure. An alternate is to obtain the uncorrected
barometric pressure from a nearby weather station and correct for altitude.
2.2.3 Analysis
2.2.3.1 Steam Bath. A steam bath is required to evaporate the absorbing
solution. A hot plate is not acceptable for this analysis, as it may cause
sample loss by spattering.
2.2.3.2 Beakers or Casseroles. A reactor vessel is required for the
evaporation step. Beakers of borosilicate glass or porcelain evaporating
dishes are acceptable. Beakers (glass) must be discarded or used for
other purposes when the bottoms become etched.
2.2.3.3 Polyethylene Policemen. One stirring rod (polyethylene policemen)
is required for each sample and standard. A glass stirring rod is not
recommended.
2.2.3.4 Volumetric Glassware. Several volumetric pipettes are required
(1, 2, and 10 m£) . One transfer pipette (10 m£ with 0.1 m£ divisions)
and one 100 mH volumetric flask for each sample. Twol,000m£ volumetric
flasks are required for the blank and standard nitrate. Additional
volumetric flasks (50 m&) are required for aliquots (for analysis) and
dilution of samples that fall outside the calibration range (absorbance >
400 yg standard).
2.2.3.5 Spectrophotometer. A spectrophotometer which is capable of
measuring the absorption at 410 nm (or the peak maximum). A set of neutral
density filters and a filter for wavelength calibration should be available
(ref. 17).
23
-------
2.2.3.6 Buret. A 50 mS, buret or its equivalent for addition of ammonium
hydroxide to the reaction vessel.
2.2.3.7 Graduated Cylinder. A 50 mil graduated cylinder with 1.0 mA
divisions for additions of distilled water.
2.2.3.8 Analytical Balance. One analytical balance that weighs to 0.1 rag.
A set of calibration weights to check the accuracy of the balance (jh 0.3 mg).
2.3 EQUIPMENT CHECK AND CALIBRATION
2.3.1 Sampling Train
The design specifications of the NO train used by the EPA is given
in Appendix A of this document ( figure 7-1). Commercial models of this
system are available. Each individual commercial or fabricated train must
be in compliance with the specifications in the reference method.
2.3.2 Probe (Filter)
Clean the probe internally by brushing, first using tap water, then
distilled, deionized water followed by acetone and allow it to dry in the
air. In extreme cases the glass liner can be cleaned with stronger reagents.
In either case the object is to leave the glass liner chemically inert to
oxides of nitrogen. If the probe is equipped with a heating system, check
to see if it is operating properly. The probe should be sealed on the
filter side and checked for leaks at a pressure of < 380 mm (15 inches) of mercury
The probe must be leak-free under these conditions. The glass liner should
be sealed inside the metal sheath to prevent diluent air from entering the
source.
2.3.3 Collection Flask, Flask Valve and Evacuation System
The collection flask and valve (in contact with sample gas) should
be cleaned with a strong detergent and hot water, rinsed with tap water,
and distilled, deionized water. Periodically, the glassware can be cleaned
with a grease remover such as decahydronapthalene (C _H ) followed by
acetone and then by the procedure above. An alternate procedure is to use
dichromate cleaning solution. Assemble the clean flasks and valves and
fill with water (room temperature) to the stopcock. Measure the volume to
+ 10 m£ by transferring the water to a graduate. Do three volume determinations
and use the mean value. Number and record the volume mean value
24
-------
on the flask or foam encasement and in the laboratory log book.
This volume measurement is required only on the initial calibration
provided the flask valves are not switched. Lubrication of stopcocks
and joints should be with a chemically inert lubricant. An inert hy-
drogen-free chlorofluorocarbon lubricant can be used. The evacuation
system as depicted in appendix A is assembled and a vacuum of 3 inches
of mercury absolute pressure is produced in each flask. The vacuum
should be held for at least one minute without appreciable fluctuation
[_<_ 10 ram (0.4 in.) Hg] ; if this is not obtained, check for leaks.
2.3.4 Temperature Gauge
All thermometers should be checked versus a mercury bulb thermometer
at room temperature. Accuracy of + 1° C (2° F) is sufficient.
2.3.5 Reagents
2.3.5.1 Sampling. The absorbing reagent is prepared by adding 2.8 mil
of concentrated sulfuric acid (H0SO.) to 1 liter of distilled, deionized
2 4
water. Mix well and add 6 m& of 3 percent hydrogen peroxide (H^O,,) . Pre-
pare a fresh absorbing solution weekly and do not exposa to extreme heat
or direct sunlight. All reagent must be ACS grade or equivalent. If the
reagent must be shipped to the field site, it is advisable that the
absorbing reagent is prepared fresh on-site. All reagents must be reagent
grade.
Note: If the concentration of peroxide solution
(H.,0,,, 3 percent) is in question, analyze with
0.1N permanganate in acid solution.
2.3.5.2 Sample Recovery. A sodium hydroxide solution (IN) is pre-
pared by dissolving 40 g NaOH in distilled water and diluting to 1
liter. This solution can be transferred to a polyethylene 1,000 ml
(32-oz.) jar for shipment. Distilled, deionized water and pH paper
are required to test basicity and for transferral of samples.
25
-------
2.3.5.3 Analysis. All reagents must be ACS reagent grade. The following
reagents are needed for analysis and standardization:
(1) Fuming sulfuric acid - 15 to 18% (by weight) free sulfur
trioxide (SO.,)
(2) Phenol - White solid reagent grade
(3) Sulfuric Acid - concentrated reagent
(4) Standard solution - dissolve 2.1980 g dried potassium nitrate (KN03)
in distilled water and dilute to 1 liter in a volumetric flask.
For the working standard solution, pipette 10 ml of the resulting
solution into a 100 m£ volumetric flask and dilute to the mark.
Note: One m& of the working standard solution is equivalent
to 100 Vg nitrogen dioxide.
(5) Water - deionized, distilled.
(6) Phenoldisulfuric acid solution - dissolve 25 g of pure white
phenol (no discoloration) in 150 m5, concentrated sulfuric acid
on a steam bath. Cool, add 75 m& fuming sulfuric acid, and
heat at 100° C (212° F) (on a steam bath) for two hours. Store
in a dark, stoppered bottle.
2.4 PRESAMPLING PREPARATION
2.4.1 Preliminary Site Visit (Optional)
The main purpose 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, expenses, and injury
to test and/or plant personnel. A test plan conceived from a thorough set
of parameters will result in more precise and accurate results. This
preliminary investigation (on-site) is optional and not a requirement. An
experienced test group can, in some cases, obtain sufficient information
on the source through communications with the plant engineer. The infor-
mation should include pictures (or diagrams) of the facilities. In most
cases, there is no substitute for an on-site presurvey.
2.4.1.1 Process(Background Data on Process and Controls). It is recommended
that the tester, before a preliminary site visit is made or before performing
tests, become familiar with the operation of the plant. Data from similar
operations that have been tested should be reviewed if they are available.
26
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The role of certain combustion effluents as interfering substances have
not been ascertained; therefore, any background data on stack gas
species should be noted for further consideration of the final analytical
results (refs. 4.12).
2.4.1.2 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 conditions or at a rated capacity. If the source is cyclic in
nature, information must be available as to the time 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 in obtaining a valid test and that all facilities meet
minimum safety standards. If ports have to be installed, specify 4-inch
ports with plugs. Port locations should be based upon Method 1 of the
Federal Register (ref. 14). 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-amp service.
2.4.1.3 Stack Gas Conditions. The following should be determined on the
initial site survey, either by measurement or estimation:
1. T = average stack gas temperature.
avg
2. P = the static pressure (positive or negative).
o
3. AP = the average velocity heads.
avg
4. B approximate moisture content.
wo
5. M = molecular weight calculated from approximate gas
constituent concentrations
The above parameters can be roughly determined using an inclined manometer
(0-5 inches), a Type-S pitot tube, manual thermometer or thermocouple
attach d to the pitot tube with potentiometric readout device. The moisture
content (approximate) can be determined with wet bulb-dry bulb and the
gaseous constituents by hand-held indicator kits. Nomographs are useful in
checking and estimating your preliminary data required (ref. 15).
27
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2.4.1.4 Methods and Equipment for Transporting Apparatus to Test Site.
Ropes, block and tackle, and other hoisting equipment should belong in the
repertoire of any stack sampler. The initial site visit should include a
preconceived plan between plant personnel and tester on how the equipment
can best be transported to the sampling site. Electric forklifts, when
available, should be utilized if needed. In addition to the above, it is rec-
ommended, when permissible, that pictures be taken of the hoisting area and
sampling area, so that any further discussions (either by letter or
telephone) will be clarified.
2.4.2 Apparatus Check
Previously used equipment should be visually checked for damage and/
or excessive wear before each field test. Items should be repaired or
replaced as applicable if judged to be unsuitable for use by the visual
inspection.
Table 1 is designed to serve as a sample checklist for the three
phases of a field test. It is meant to serve as an aid to the individuals
concerned with procuring and checking the required equipment, and as a
means for readily determining the equipment status at any point in time.
The completed form should be dated, signed by the field crew supervisor,
and filed in the operational log book upon completion of a field test.
This includes initiating the replacement of worn or damaged items of equip-
ment. Procedures for performing the checks are given in the appropriate
subsections of this operation manual, a check is placed in the proper row
and column of table 1 as the check/operation is completed. Each team will
have to construct its own checklist according to the type of sampling
train and equipment it uses.
2.4.3 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 packing of equip-
ment with regard to (1) accessibility in the field, (2) ease of movement on
site and (3) optimum functioning of measurement devices in the field. Equip-
ment should be packed under the assumption that it will receive severe
treatment during shipping and field operation. One major consideration in
28
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shipping cases is the construction materials. Durable containers are
the most cost effective.
2.4.3.1 Probe. Pack the probe in a case protected by polyethylene or
other suitable packing material. An ideal container is a wooden case or
equivalent lined with foam material in which separate compartments are
cut to hold the individual devices. This case can also contain a pitot
tube for velocity determinations. The case should have handles that can
withstand hoisting and be rigid enough to prevent bending or twisting of
t'ra devices during shipping and handling.
2.4.3.2 Collection Flasjc and Valve. The collection flasks and valves
should be packed securely in a suitable shipping container. An ideal
shipping container is a case or foot locker of approximately the following
dimensions: 30" x 15" x 15". This container when lined with foam
will accomodate eight collection flasks with the appropriate mated flask
valves.
2.4.3.3 Evacuation System, Temperature Gauges, Vacuum Lines and Reagents.
A sturdy case lined with foam material can contain the evacuation manifold,
squeeze bulb, manometer, and reagent for sampling and recovery.
2. .3.4 Evacuation Pump. The vacuum pump should be packed in a shipping
container unless its housing is sufficient for travel. Additional pump
oil should be packed with the pump if oil is required for its operation.
2.4.3.5 Glass Storage Containers. All glass storage containers must be
packed with cushion material at the top and bottom of the case with some
form of dividers to separate the components.
2.5 ON-SITE MEASUREMENTS
The on-site measurement activities include transporting the equipment
to the test site, unpacking and assembling the equipment, confirming duct
measurements and traverse points (if volumetric flow rate is to be deter-
mined), velocity traverse, molecular weight determination of the stack
gas, moisture content, sampling for oxides of nitrogen, and data recording.
2.5.1 Transport of Equipment to the Sampling Site
The most efficient means of transporting or moving the equipment from
29
-------
floor level to the sampling site as decided during the preliminary site
visit should be used to place the equipment on-site. Care should always
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 reagent and charging of the flasks.
Utilization of plant personnel or equipment (winches and forklifts) in
movement of the sampling gear is highly recommended.
2.5.2 Preliminary Measurements and Set Up
The reference method outlines the determination of the concentration
of oxides of nitrogen in the gas stream. The volumetric flow rate must be
determined utilizing Reference Methods 1, 2, 3, and 4 if the mass emission
rate is to be determined (ref. 14). Consult the Quality Assurance
Document for Method 2 for a more thorough discussion of the determination
of the volumetric flow rate (ref. 16).
2.5.3 Sampling
The on-site sampling includes preparation and/or addition of the
absorbing reagent to collection flasks, setup of the evacuation system,
connection of the electric service, preparation of probe (leak check and
addition of particulate filter), insertion of probe into the stack,
sealing the port, evacuation of flasks, sampling and recording of the
data, and a final leak-check.
2.5.3.1 Preparation and/or Addition of Absorbing Reagent to Collection
Flasks. If preparation of absorbing reagent is necessary on-site, follow
directions as given in section 2.3.5.1 of the document. Pipette 25 m£ of
absorbing reagent into sample flask. Place a properly lubricated flask
valve into the collection flask with the valve turned in the purge posi-
tion. Lubrication of joints is intended to prevent leaks and should not seal
the bore of the stopcock or contaminate the sample.
2.5.3.2 Assembling Sampling Train. Assemble the sampling train as shown
in figu :e 7-1 of the reference method (contained as appendix A of this
document) and perform the following:
(1) Visually check probe for liner separation, (racks, etc.)
(2) Place a loosely packed filter of glass or quartz wool in the end
of the probe.
30
-------
(11) Turn the flask valve to the "purge" position at the conclusion
of collection.
(12) Shake the flask for five minutes.
The particulate filter should be changed at the end of each sampling run.
This is to help to prevent plugging of the probe.
2.5.4 Sample Recovery
The reference method requires a sample absorption period of
>^ 16 hours. If the laboratory is close by, the samples
may be left in the flasks for return to the laboratory. Otherwise
the appropriate data must be taken in the field, solutions made
alkaline and transferred to glass storage containers.
2.5.4.1 Flask Pressure, Temperature and Barometric Pressure. After the
absorption period is cpmpleted (>_ 16 hours), record the barometric pressure
and the room temperature on a data sheet and a field laboratory notebook.
(1) Shake the flask and contents for 2 minutes.
(2) Connect one leg of the sample flask valve to the open-end
manometer.
(3) Turn the stopcock to open the flask to the manometer.
(4) Record the flask pressure by reading the difference between the
mercury levels in the manometer.
(5) Transfer the flask contents to a container for shipment or to a
250 ml beaker or porcelain evaporating dish for analysis.
(Transferral to a beaker or evaporating dish is only done in
the laboratory.)
(6) Rinse the flask with several portions of distilled water.
Note: A quantitative transfer is required. No less than 2
rinses are acceptable. The total rinse should be
< 10 mi. The total rinse should be the same for all
flasks.
(7) A blank should be prepared by pipetting 25 ml of absorbing
solution into a clean sample bottle and adding the same volume of
distilled water as used in rinsing the flask in (6) above.
31
-------
(3) Insert the probe into the stack to the sampling point and seal
the opening around the probe.
2.5-3.3 Evacuation, Purge, and Sample. A sample is taken by the following:
(1) Turn the pump and flask valves to the "evacuate" positions.
The flask should be evacuated to 76 mm (3 inches) of mercury absolute
pressure or until the apparent boiling point is reached (bubbling
of absorbing solution).
(2) Turn the pump valve to the "vent" position and turn off the pump.
Check the manometer for fluctuations. The manometer should stay
stable (£10 mm (0.4 inches) Hg) for at least a minute. If the
mercury level changes, check and eliminate the problem.
(3) Record the initial volume of the flask, temperature, and baro-
metric pressure on a data sheet or in a field laboratory note-
book.
(A) Turn the flask valve to the "purge" position.
(5) Turn the pump valve to the "purge" position.
(6) Purge the probe and the vacuum line using the one-way squeeze bulb.
(7) If condensation occurs in the probe or the flask valve, the probe
must be heated until(upon purginp) the condensation disappears.
(8) Turn the pump valve to the "vent" position.
(9) Turn the flask valve to the "sample" position and allow sample
to enter the flask > 15 seconds. The object here is to get a
good sample. This will usually require approximately 15 seconds.
A longer period of time indicates that the probe is plugged.
A generally accepted period of sampling is less than 30 seconds.
(10) Record final flask pressure.
A "good" sample includes sufficient oxygen for the conversion of all NO to
NO . Without excess molecular oxygen present in the flask, some NO will
remain and the datum obtained for NO concentration will be biased low. If
x
it is suspected that there is not enough oxygen, then terminate sampling
before flask pressure has reached stack pressure (with minimum 50 mm to g
differential) and open to the atmosphere. This is not normal procedure and
should not be done unless the situation so requires.
32
-------
(8) Prior to shipping or analysis, add sodium hydroxide (NaOH, I N)
dropwise (about 25 to 35 drops) into both the sample and the
blank until alkaline to pH paper,
Note: Test for alkalinity by touching the top of a glass rod
into the sample blank and then applying this to a moistened
strip of pH paper. The solution is considered alkaline
when a pH range of 9-12 is attained.
Caution: Do not do this in the presence of ammonia fumes.
This will give a false test for alkalinity.
2.5.5 Sample Logistics (Data) and Packing of Equipment
The above procedures are followed until the required number of tests
are completed. The following is recommended at the completion of testing:
(1) Check all sample containers, or collection flasks for proper
labeling. (Time and date of test, location of testing, number
of test, and any other pertinent documentation.) Mark the height
of the liquid level in the sample container to determine whether
or not leakage occurred during transport.
(2) All data recorded during field testing should be recorded in
duplicate by carbon paper or by utilizing data sheets (figure 2)
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 embarrassing
mistake.
(3) All sample containers, flasks and equipment should be properly
packed for shipment to the base laboratory. All shipping con-
tainers should be properly labeled to prevent loss of samples or
equipment.
33
-------
PLANT DATE _
SAMPLE
COLLECTED BY RUN NO.
PROBE TEMPERATURE REAGENT (ABSORBING)
SETTING PREPARATION DATA
COLLECTION
DATA CLOCK TIME
VOLUME OF FLASK
FLASK NO. AND VALVE, m£
BAROMETER Va, VOLUME OF ABSORBING
PRESSURE, mm Hg _, SOLUTION, ma
Pc, INITIAL ABSOLUTE Pf, FINAL ABSOLUTE
PRESSURE, mm Hg PRESSURE, mm Hg
Tis INITIAL TEMPERATURE Tf, FINAL TEMPERATURE
OF FLASK, [°C +273] OF FLASK [°C +273](ABSOLUTE)
Figure 2. NO field data sheet,.
2.6 POST-SAMPLING OPERATIONS (LABORATORY)
2.6.1 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.
Extrapolation of standardization curves at very low and high concentrations
is not justified. Blanks must be used to correct for reagent and sample
conditions.
2.6.1.1 Calibration of Spectrophotometer (Wavelength and Linearity). Calibra-
tion of the wavelength scale should be checked periodically, at least once
each calendar quarter. The absorption spectrum of a didymium glass has been
found useful for this purpose. For checking the transmittance scale, a set
of neutral density filters is satisfactory. The reference method calls for
samples and standards absorbance to be determined at 410 nm. The spectra pro-
duced by scanning samples and standards in a calibrated dual-beam instrument
or IA a single beam instrument (ref. 17) produce a maximum absorbance at ~405 nm.
It is recommended that standardization curves and samples be done at a constant
wavelength of 405 + 5 ran. Calioration is a critical part of the analytical
technique and should be done with great care.
34
-------
2.6.1.2 Recommended Procedures in Operating a Spectrophotometer. The
correct manipulation of sample cells is critical. The following points
should be adhered to:
(1) Cuvettes are not always matched; therefore, one should
designate the "blank" and sample cells. Do not interchange
the cells during an analysis.
(2) Do not touch the bottom of the cuvette with your fingers.
(3) Rinse the cuvette at least twice with the solution you are
about to measure.
(4) Remove lint, liquid, etc., with a lens tissue or its equivalent.
(5) Careless technique is unacceptable.
2.6.1.3 Standardization and Analysis of Samples. Add 0.0 to 4.0 mH of
working standard solution (1 m& = 100 ug N0?) to a series of beakers. To
each beaker add 25 m& of absorbing reagent and add sodium hydroxide (IN)
dropwise until alkaline. Check for alkalinity by touching a glass rod to
the solution and then to pH paper (pH range 9-12). A series of solutions,
for example, would be 0, 1, 2, 3, and 4 m&. Analyze the standards and sample
as follows:
(1) If the sample has been shipped in a container, transfer the contents
to a 50 m£ volumetric flask, using several small portions of distilled
water.
Note: Before transfer of sample, check the level in the container to
confirm whether or not any sample was lost during shipment. If
loss is detected, it should be recorded on the analytical data
sheet, and the sample discarded.
Dilute to the mark with dibtilled, deionized water, Trans-
fer a 25 mfc aliquot to a porcelain evaporating dish or a 250-mi, beaker.
(2) Standards and samples must be alkaline before evaporation.
(3) Evaporate the solution (standards, blanks, and sample solutions) to
dryness on a steam bath and then cool.
Note: Do not evaporate these solutions on a hot plate. Do not evaporate
to bone dryness.
(4) Add 2 mii phenoldisulfonic acid reagent to the dried residue and titurate
thoroughly with a stirring rod.
(5) Add 1 mi, distilled water and four drops of concentrated sulfuric acid.
Heat the solution in a steam bath for three minutes with occasional
stirring.
(6) Cool, add 20 m£ distilled water, mix well by stirring.
-------
(7) Add concentrated ammonium hydroxide dropwise (a 50 m£ burette
is helpful) with constant stirring until alkaline to pH paper.
Check for alkalinity by touching a glass rod to the solution
and then to a piece of pH paper.(pH = 9-12).
(8) Transfer the solution to a 100-m& volumetric flask and wash the
*
beaker three times with 5-m£ portions of distilled water.
Dilute to the mark and mix thoroughly.
(9) If the sample contains solids, transfer a portion of the solution
to a clean, dry centrifuge tube and centrifuge or filter a portion
of the solution.
(10) Measure the absorbance of each sample at 410 nm (or the previously
determined analytical wavelength—=* 405 nm) using the blank
solution as a zero.
(11) Dilute the sample and the blank with a suitable amount of distilled
water (to double, triple, etc. the original volume) if absorbance
fall outside the range of the calibration curve.
Note: The calibration curve should be verified at a low, medium
and high concentration with each sample run.
(12) Record all pertinent data on the laboratory data sheet (figure 3).
2.6.2 Calculations
Calculation errors due to procedure or mathematical mistakes can be
a large component of total system error. Therefore, it is recommended that
each set of calculations be repeated or spot checked every third calcu-
lation, preferably by a team member other than the one that performed
the original calculations. If a difference greater than five per-
cent is detected, the calculations 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 standardized 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.
2.6.2.1 Calibration Curve, Spectrophotomer Calibration. Each working
standard (0.0 mfc , 1.0 m£, 2.0 m£, 3.0 m£ and 4.0 ml) should be analyzed
as directed in subsection 2.5.. 1.3. Plot a calibration curve of absorbance
versus yg N0~ per sample from the data obtained. Check visually for linearity.
36
-------
RUN NO.
DATE COLLECTED
DATE ANALYZED
LIQUID LEVEL CHECK
Kc, CALIBRATION
FACTOR
A, ABSORBANCE
OF SAMPLE
F, DILUTION
FACTOR
m = tag OF
N0y AS NO?
C (EMISSION,
mg/scm)
v Tstd(Vf - Va)
Pstd
A', BLANK
ABSORBANCE
Vsc (CORRECTED SAMPLE
VOLUME, rm>)
Qs, VOLUMETRIC
FLOW RATE
SAMPLES ANALYZED
BY
(Pf PA / N (Pf PA
VTf" V ~~^-K) Vf~rJ
(Equation 7-2)
m = 2 KC AF
(Equation 7-3)
= K
sc
(Equation 7-4)
Figure 3. NO laboratory data sheet
37
-------
All samples must be mixed thoroughly and the absorbance measured using
the blank solution as a zero reference. An alternate approach is to
measure the sample absorbance (A..) and correct for the blank absorbance
(A").
Determine the spectrophotometer calibration factor using equa-
tion 7-1.
A_ + 2A0 + 3A0 + 4A,
K = 100 X 2 3 4
c A 2 . . 2 . . 2 ^ . 2
A + A0 + A0 4 A,
1234
where
K = Calibration factor.
c
A = Absorbance of the 100 yg N0? standard (1 m.£ = 100 yg NO ) .
A = Absorbance of the 200 yg NO standard.
A = Absorbance of the 300 yg NO standard.
A, = Absorbance of the 400 yg N0~ standard.
2.6.2.2 Sample Volume. Calculate the sample volume at standard conditions
on a dry basis [760 mmHg (29.92 in Hg), 293° K (528° R)] by using the
following equation.
X /vf - V \ i P P. \ /P P.
v = _Jt|_U ±1 | _i _ _i ) = Kfv, _ 25) M- - -i 1 (Equation 7-2)
' \ •*- e~ •*-_•/
where
Q r* P \ T T
O1— •LA_J \ -*• JT •*-•/ XJ- /\J-f •*-•/
std \ f i / \ f i/
°K
K = 0.3855 — 77— for metric units
mmHg
°R
= 17.65 - - ^— for English units.
in. Hg s
V = Sample volume at standard conditions (dry basis) , m£.
s c
T , = Absolute temperature at standard conditions, 293°K (528°R) .
std
P = Pressure at standard conditions, 760 mm (29.92 in. Hg) .
V = Volume of flask and valve, m£ .
V = Volume of absorbing solution, 25 m£.
3.
P = Final absolute pressure of flask, mm Hg (in. Hg) .
P. = Initial absolute pressure of flask, mm Hg (in. Hg) .
T = Final absolute temperature of flask, °K (°R) .
T. = Initial absolute temperature of flask, °K (°R) .
38
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Temperatures are converted to degrees Kelvin (Pankin) [(273 + °C) or
(460 + °F)] and all pressures are recorded to the nearest mm (tenths of
an inch) of mercury. The absolute pressure in a flask is the barometric
pressure minus the difference in the two legs of the U-tube manometer.
2.6.2.3 Total yg NO- per Sample. Calculate the total yg NO per sample
by
m = 2 K AF (Equation 7-3)
where
K = Calibration factor (spectrophotometer)
£ = Sample absorbance (corrected for blank)
F = Dilution factor (i.e., 25/5, 25/10, etc., required only if
sample dilution was needed to reduce the absorbance into the
range of calibration; otherwise F = 1.)
2 = 50/25 the aliquot factor. (If other than a 25 mi aliquot
was used for analysis, the corresponding factor must be
substituted.)
2.6.2.4 Sample Concentration and Emission Rate. Calculate the sample
concentration on a dry basis at standard conditions by equation 7-4.
C = K ~- (Equation 7-4)
sc
where
C = Concentration of NO as NO,,, dry basis, corrected to standard
conditions, mg/dscm (Ib/dscf ) .
K = 103 iHl for metric units
(m )
= 6.243 x 10~5 --- for English units.
&
m = Mass of NO as NO in sample, yg (2.5.2.3)
X Z.
V = Sample volume at standard conditions (dry basis), m& (2.6.2.2).
The emission rate is determined by either of the following equations:
ER = iriln = Q x C (Metric units)
where
Q = Volumetric rate of the effluent in scm/min at standard conditions
on a dry basis.
C = NO concentration in mg/scm.
x °
39
-------
or
where
ER(r—) = Q x C (English units)
\ nr / s
Q = volumetric flow rate of the effluent in ft /hr at standard
conditions on a dry basis as determined by the Quality Control
document for reference Method 2 (ref. 16).
C = NO concentration in Ib/scf.
X
40
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SECTION III mm. P3R FIELD TEAM SUPERVISOR
3.0 GENERAL
The term "supervisor", as used in this document, applies to the indi-
vidual 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 that performs source sampling under con-
tract to government or industry, a government agency performing source
sampling, or an industry performing its own source sampling activities.
It is the responsibility of the supervisor to identify sources of
uncertainty or error in the measurement process for specified situations
and, if possible, to eliminate or minimize them by applying appropriate
quality-control procedures to assure that the data collected are of accept-
able quality. Specific actions and operations required of the supervisor
for a viable quality-assurance program are summarized in the following list.
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 perfor-
mance 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.
b) Examine the team's log books periodically for completeness
and adherence to operating procedures.
c) Approve data sheets, data from calibration checks, etc., for
filing.
41
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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. Isolation, evaluation, and monitoring of major components of
system error.
3. Collection and analysis of information necessary for controlling
data quality.
3.1 ASSESSMENT OF DATA QUALITY (INTRATEAM)
Intrateam or within-team assessment of data quality as discussed herein
provides for an estimate of the: precision of the measurements made by a
particular field team. Precision in this case refers to replicability: i.e.,
the variability among replicates, and is expressed as a standard deviation.
This technique does not provide the information necessary for estimating
measurement bias (see subsection 4.1.3 for a discussion of bias) which might
occur, for example, from failure to collect a representative sample, sampling
train leaks, or inadvertent exposure of the sample to ambient air. However,
if the operating procedures given in the Operations Manual (section II) are
followed, the bias should be small in most cases. The performance of an inde-
pendent quality audit that would make possible an interteam assessment of
data quality is suggested and discussed in subsection 4.2 of the Manual for
Managers of Groups of Field Teams.
The primary measurement of interest here is the concentration of nitrogen
oxides (except nitrous oxide) in the sample. The data from which this concentra-
tion is derived are:
1. An absorbance reading which is converted to an equivalent mass
of nitrogen dioxide by means of a calibration of the spectro-
photometer with standard nitrate solutions.
2. A sample volume, corrected to standard temperature and pressure.
42
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3.1.1 Absorbance Determination
Collaborative studies of Method 7 (refs. 1,3) showed that, for
the analytical part of this method, the laboratory-to-laboratory varia-
tion was largely due to daily within-laboratory measurement variations
rather than significant biases from laboratory to laboratory. This within-
laboratory variation is due largely to the failure to check and recalibrate
spectrophotometers on a daily basis. A second factor involved larger
errors when sample concentrations were low, i.e., below 2 yg/m£. Optimal
analytical conditions for minimizing replicate variability would then in-
volve daily (or even more frequent) calibration checks and the use of only
the upper portion of the working curve (from about 2 to 4 pg/m8. concentra-
tion) for sample analysis. Section 3.2 will include a control chart for
monitoring spectrophotometer response by means of control (known) nitrate samples.
3.1.2 Sample Volume Determination
The sample volume is a function of the flask volume, absorbing
solution volume, initial and firal pressure readings, and initial and
final temperature readings. Calibration of the flask and valve volume
is a relatively large source of error, and it is therefore recommended that
the volume be obtained as the mean of three determinations. Provided that
reasonable care is exercised in making the temperature and pressure readings,
these measurements will not introduce a significant error into the volume de-
terminations.
The largest potential source of variability in volume determination
is calculation error. Use of a general Method 7 computer program would
eliminate this problem and has been strongly recommended (refs. 1,3). Field
teams should be cautioned that calculation errors are prevalent in this method,
and advised to double-check each calculation before reporting the data. It
would also be advisable to keep a visible record posted of the number of
calculation errors found (by audit or otherwise), by date and name of person.
This w mid provide a negative incentive to exercise care in carrying out the
data processing steps.
43
-------
3.1.3 Interference of Hydrogen Chloride
The field team should be alert to the possible presence of hydrogen*
chloride in the stack gas. Certain types of coal, in particular, contain
chlorides and release HC1 on burning (ref. 12). This is a negative interferent,
and the results will be biased, in an approximately linear fashion, with HC1
concentration (ref. 4). It would be possible to make an approximate correction
for this effect if the HC1 concentration were known, but this is not likely.
However, it should be anticipated in a qualitative way that the results are
highly questionable if HC1 is a component of the stack gas.
3.2 MONITORING DATA QUALITY
In general, if the procedures outlined in the operations manual are
followed, the major sources of variability will be in control. It is felt,
however, that as a means of verification of data quality, as well as a
technique for monitoring personnel and equipment variability, quality control
charts are highly desirable. These provide a basis for action with regard
to the measurement process: namely, whether the process is satisfactory and
should be left alone, or whether the process is out of control and action
should be taken to find and eliminate the causes of excess variability.
For Method 7 it is appropriate to have a chart to monitor variability
and accuracy of the analytical phase. The chart should plot the results of
reference (audit) samples dispersed randomly throughout an analysis period.
Specifically, the difference, d., between the true value, C (T) , and the
J INUrt
measured value, C (M) , is divided by the true value and the resulting
I'll-' /-J
number multiplied by 100 to convert to a percent, i.e.,
This value, d., is then plotted versus audit date. An upper warning limit
and upper control limit, as well as the corresponding lower limits, are
provided to serve as indicators of data quality. These limits are normally
established by experience; i.e., over a period of time the precision of the
technique can be established and a reasonable value for the standard devia-
tion of d. can be assigned. Warning limits are then taken as +2a and -2o,
and control (or action) limits as +3o and -3o.
44
-------
Collaborative tests for Method 7 (refs. 1,3) showed that, because
of dubious spectrophotometer recalibration practices, most of the re-
producibility variation occurs in the analytical phase. It should be
possible to reduce this analytical variation by more stringent calibra-
tion practices. Judging from a typical calibration curve such as is
given in a collaborative study (ref. 1) and reproduced in this docu-
ment as figure 4, if one restricts sample concentrations to those giving
absorbances from about 0.3 to 0.5 the calibration error should be minimized.
This can be done in some cases by dilution, but in other cases it will be
impossible due to the sample itself being of low concentration. For pur-
poses of illustration, a a of 4% is assumed in this document. The warning
and control limits are then 8% and 12%, respectively. A quality control
chart is shown in figure 5. The audit values are plotted sequentially as
they are obtained and connected to the previously plotted point with a
straight line. Corrective action, such as review of operating technique
and/or calibration check, should be taken any time one of the following
criteria is exceeded:
1. One point falls outside either the upper or lower
control (3a) limit.
2. Two consecutive points fall between the warning and
control limits.
3. Three consecutive points fall outside the o range
(here assumed to be +4%).
Quality control charts also serve to point up method bias in an obvious
visual way; i.e., if a large number of points fall on the same side of the
center line representing the "true" reference value, an attempt should be
made to identify a possible cause or causes.
3.3 COLLECTION AND ANALYSIS OF INFORMATION TO IDENTIFY TROUBLE
. n a quality assurance program, one of the most effective means of
preventing 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
assure the collection of data of good quality. These checks are written
as part of the routine operating procedures in section II. In order to
45
-------
calibration data point
standard regression
line
regression through
origin
1.0
2.0 3.0 4.0
Standard Concentration, ug/ml, 1J07
5.0
Figure 4. Typical calibration curve for determination
of NO concentration from absorbance.
-------
12.0 -
UPPER CONTROL LIMIT
8.0
UPPER WARNING LIMIT
4.0
-4.0
-8.0
LOWER WARNING LIMIT
-12.0
LOWER CONTROL LIMIT
11 13 15
Audit Numbers (j)
Figure 5. Quality control chart for d.,
47
-------
effectively apply preventative-type maintenance procedures to the
measurement process, the supervisor 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 stack gas composition requires a sequence of
operations and measurements that yields, as an end result, a number that
represents the average concentration of a component gas for that field
test. There is no way of knowing the accuracy, i.e., the agreement between
the measured and the true value, for a given field test. However, a
knowledge of the important variables and their characteristics allows the
application of quality control procedures to control the effect of each
variable at a given level during the field test, thus providing a certain
degree of confidence in the validity of the final result.
Several variables can affect the expected precision and accuracy
of measurements made by Method 7. Certain of these are related to analysis
uncertainties and others to the collection procedure. Major sources of error
are:
1. Spectrophotometer-Related Errors. Because these errors are the
single largest cause of both inaccuracy and imprecision in Method D, it is
very important to carry out calibrations (of both the wavelength scale and
transmittance scale) at least once each calendar quarter. However, it is
essential that the calibration be checked every time an analysis is done.
The check is accomplished by carefully preparing standard nitrate solutions
at low, medium, and high absorbance levels. Because of the advisability of
restricting analyses to the 0.3 to 0.5 absorbance range, a good set of
calibration check standards would have nitrate concentrations of 2.0, 3.0,
and 4.0 yg/m£. Whenever there is a discrepancy of greater than the 3a
value for the analytical procedure, a checking-rechecking process involving
the use of another set of standard solutions and recalibration of the spectio-
photometer must be carried out until the cause of the discrepancy is de-
termined and corrected.
48
-------
A second check on spectrophotometer performance is how closely
the calibration curve regresses to zero absorbance at zero nitrate con-
centration. It has been suggested (ref. 1) that the curve be forced through
the origin, either graphically or by linear regression.
2. Data Processing Errors. Calculation errors are prevalent in
Method 7. The collaborative studies recommend that a computer program be
written to carry out all calculations, and that all data processing be
carried out by the EPA.
So long as calculations are done in the field, it is necessary to
emphasize to all personnel involved that great care must be taken to avoid
careless errors. It is imperative that each person understand the calcu-
lation, so that when a miscalculation produces a clearly erroneous result
the person involved will be able to recognize that an error has occurred.
The magnitude of data processing errors can be estimated from the
auditing program, which involves periodic calculation checks and the cor-
rection of errors turned up by these checks. On a day-to-day basis, however,
it is important that field personnel be impressed with the importance of
rechecking all calculations before submission to the team supervisor.
3. Method Errors. Because Method 7 is very tedious, especially
in the time involved and techniques of the analytical phase, there are numerous
opportunities for sample loss and/or contamination. It is difficult to
systematically monitor technique errors in pipetting, aliquotting, and the
like. Such errors can hopefully be minimized through careful instruction
and supervision of field and laboratory personnel. Again, it is important
that the personnel involved have an understanding of the method in order to
be able to detect obvious mistakes and either make a correction or void the
sample. Auditing of the analytical technique by reference samples will un-
cover serious systematic technique errors.
4. Interference of Hydrogen Chloride. At least one study (ref. 4)
has sb iwn that Method 7 results are affected by the presence of HC1, either as
the dry gas or in the form of hydrochloric acid. If HC1 is a possible com-
ponent of the stack gas being sampled, it is important to obtain at least a
rough estimate of its concentration. Hydrogen chloride acts as a negative
49
-------
interferent, and the magnitude of the effect is dependent on HC1 concen-
tration. Figure 6 is taken from an SWRI study (ref. 4) which shows
that at high concentrations the effect is quite large. Driscoll (ref. 12)
suggests the removal of chloride by an excess of silver sulfate and filtra-
tion, prior to the evaportation step. Another study (ref. 13) indicates
that chloride is effectively precipitated as lead chlorofluoride. Method 7
makes no provision for elimination of chloride or any of several other inter-
ferents and it is not acceptable to modify the reference method. It is de-
sirable to be aware of possible interferents, however, in order to antici-
pate the collection of bad data in their presence.
3.3.2 How to Monitor Important Variables
Spectrophotometer readings and data processing errors are monitored
routinely by calibration checks and calculation checks. "Method" errors are
not separately monitored other than by observation of personnel actually
carrying out the operations of sampling and analysis. The presence and
approximate concentration of HC1 can be anticipated if the nature of the com-
busting material is known. Table 1 summaries the variables and how they can
be monitored.
50
-------
d
o
rt
(H
o
0)
tj
W)
•H
xzidd
51
-------
Table 1. Methods of monitoring variables
VARIABLE
METHOD OF MONITORING
1. a. Spectrophotometer
Wavelength Scale
Check against a didymium glass
spectrum.
b. Spectrophotometer
Absorbance Scale
Check against a set of neutral
density filters.
2. c. Spectrophotometer
Calibration Curve
Check against standard nitrate
solutions of low, medium, and
high concentration. Also check
by measurement of reference
samples.
3. Data Processing Errors
Recalculation before submission,
as well as auditing checks.
Method Errors
Periodic observation of personnel
actually doing sampling and
analysis.
4. HC1 Interference
Knowledge of gases, and approxi-
mate concentrations being emitted
at stack.
52
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SECTION IV MANUAL FOR MAflAGER OF GROUPS OF FIEUD TOTS
4.0 GENERAL
The guidelines for managing quality assurance programs for use with
Test Method 7—Determination of Nitrogen Oxide Emissions from Stationary
Sources, are given in this part of the field document. This information is
written for the manager of several teams that measure 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 operational
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 organizations, 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 pur-
pose of these guidelines 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 adher-
ence to test methods and for 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 accept-
able level of risk to be associated with the reported results.
These four purposes will be discussed in the order stated in the sec-
tions which follow. The first section will contain a functional analysis
of the test method, with the objectives of identifying the most important
factors L lat affect the quality of the reported data and of estimating the
expected variation and bias in the measurements resulting from equipment
and operator errors.
53
-------
Section 4.2 contains sever.al actions for improving the quality of the
data; for example, by improved analysis techniques, instrumentation, arid/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 compared 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 routirely
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 pitot tubes into the stack and collecting two
samples simultaneously) is not considered practical due to the constrained
environmental and space conditions under which the data are being collected.
Hence, a combination of an on-site system audit, including visual observa-
tion of adherence to operating procedures and a quantitative performance
quality audit check, is recommended as a dual means of independently check-
ing on the source emissions data.
The third section contains a description of a data quality audit pro-
cedure. The most important variables identified in section 4.1 are con-
sidered 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 col-
lection aid analysis techniques with respect to the important variables.
It provides a means of assessing data collected by several teams and/or
firms with the potential of identifying biases/excessive variation in the
data collection procedures. A quality audit should not only provide an
54
-------
independent quality check, but also identify the weak points in the measure-
ment process. Thus, the auditor, an individual chosen for his background
knowledge of the measurement 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 currently 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.A.1 It makes maximum
use of the data collected; it is particularly adaptable to the small lot
size and consequently to small sample size applications. The same sampling
plans can be employed in the qua]ity checks performed by a team or firm in
its own operations. The objectives of the sampling and test procedure are
to characterize 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 4.4.3 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 costs data and prior information con-
cerning data quality arc Mipplied 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 responsibi1ity.
Figure 7 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
correspond to specific sections or subsections of the document, as indicated
in the u^per right hand corner of each area. The details are considered in
these respective sections of the document and will not be described here.
55
-------
Pollutant
Measurement
Method
Functional
Analysis
Subsection 4.1
I Estimate Ranges
and Distributions
of Variables
Identify and Rank
Sources of
Bias/Variation
Perform Overall
Assessment
Subsection 4.2
Data
are of
Satisfactory
Quality
Evaluate Action Options
for Improving Data
Quality
Section III
Develop Standards
for Q. C.
Procedure
Institute
QC Procedure
for Critical
Variables
QC
Procedure
Indicates
Measurement
roces
Continue to Use
Measurement Meth.
as Specified
Cost of
Implementing
Actions
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
atisfactory
Continue to Use
Measurement Method
as Specified
Figure 7. Summary of data quality assurance program.
56
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4.1 FUNCTIONAL ANALYSIS OF THE TEST METHOD
Test Method 7—Determination of Nitrogen Oxide Emissions from
Stationary Sources—is described in the Federal Register of December 23,
1971, and a later version is reproduced as appendix A of this document.
This method is used to determine the concentration of nitrogen oxides
(except nitrous oxide) in the stack gas. In conjunction with the volu-
metric flow rate as measured by Method 2, a nitrogen oxides emission rate
may be determined for the source being tested.
A functional analysis of the measurement process is performed to iden-
tify and, where possible, quantify important sources of variability. Estimates
of the error ranges associated with intermediate measurements are made using
published data if available, and engineering judgment if data are not avail-
able. Use is made of the results from collaborative tests of the method
(refs. 1,2,3) for overall variability and for the division of variability due to
the sample collection and analysis phases of the process.
Special symbols and definitions used in the functional analysis include
the following:
C = NO concentration (as NO ) dry basis, corrected
INw X ^
X
to standard conditions, mg/scm.
C = The average NO concentration (as N0?) of three
x
repetitions, where each repetition is the
average of four measurements.
CV{X} = Within-laboratory coefficient of variation,
percent.
CV, {X} = Between-laboratory coefficient of variation,
b
percent.
CV {X} = Laboratory bias coefficient of variation (varia- '
JLJ
bility in NO determinations due to changes in
personnel, equipment, and procedural details),
percent.
CV{C }/Sl2 = Repeatability coefficient of variation for NO
1NVJ X
determinations based on twelve replicates, percent,
L{CNO } + Cv2{CNO }/12 = ReProducibility coefficient of variation for a
X X
test result based on twelve replicates, percent.
57
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4.1.1 Variable Evaluation and Error Range Estimates
The emission rate (mg/hr) of nitrogen oxides (as N02) is calcu-
lated from measured values by the relationship
ER = CNO ' Qs
x
where Q = volumetric flow rate, scm/hr and C has already been defined (4.1)
s NOX
Both the nitrogen oxides concentration (as N0?) and the volumetric flow
rate depend upon a number of variables. They are further broken down in
the following discussion:
C = Km/V
N0? sc
where K = 10 (mfc)(mg)
(m )(yg)
m
Total yg N02 per sample
V = Sample volume at standard conditions (dry basis), mi.
sc
In turn,
m = 2 K AF
c
where 2 = 50/25 = Aliquot ::actor
K = Spectrophotometet calibration factor
F = Dilution factor (1, unless sample dilution was required to
bring the absorb.ance into the calibrated range) .
A + 2A + 3A3 + 4A
K = 100 ~j- -y- =——=
A7 + A0 + A, + A.
1 2 j 4
where A = Absorbance of the 100 yg N02 standard
A? = Absorbance of the 200 yg N02 standard
V = Absorbance of the 300 yg N02 standard
A, = Absorbance of the 400 yg NO™ standard
58
-------
The volume, V , of the sample is calculated as
sc
V =
T , (Vf ~ V } fP, P.
std \ f an f i
sc P . , T,,
std If
where T , = 293° K .
std
P t , = 760 mmHg .
std
V = Volume of flask and valve, mO.
V = Volume of absorbing solution, 25 mSL,
a
P, = Final absolute pressure in flask, mmHg>
P. = Initial absolute pressure in flask, mmHg
T, = Final temperature of flask, K
T. = Initial temperature of flask, K .
Finally, the volumetric flow rate, Q , is a function of a number
of variables, as given below: _ -^
_ P
Q = 8.754 x 10^ (1-B ) C (/AP)
avg s
s
(T ) M
s avg s
where B = Proportion by volume of water vapor in the stack gas, dimensionless.
wo
C = Pitot tube calibration coefficient, dimensionless.
P
(/AP) ~ Average of the square roots of the velocity pressure head
avS i^
measurements, (mm HQ0) 2.
2
A = Stack cross-sectional area, m .
P = Absolute stack pressure, mmHg
(T ) = Average stack temperature, K.
s avg & r
M = Stack gas molecular weight on a wet basis, g/g-mole.
A systematic analysis of the variance of ER for NOV must include
X
estimates of the variances of each parameter mentioned above. A
variance analysis for Q has been done and appears in the Quality
o
Assurance Guidelines document for Method 6, Determination of Sulfur Dioxide
Emissions from Stationary Sources. The value of CV, {Q } is given as 2.33%.
D S
59
-------
The CV{C } must be determined in order to obtain an estimate of
CV{ER}, since X
CV2{ER} = CV2{r } + CV2{Q }.
NO s
x
CN_ depends on both the total mass of NO (as NO,,) and the volume of the
collected sample; i.e., on m and V . These must be examined for sources of
sc
variability.
A spectrophotometer calibration check must be made before each
analysis. A collaborative study (ref. 1) of Method 7 indicates that by far
the most significant source of reproducibility variation (93%) is attributable
to negligence in recalibration procedures. At low nitrate concentration
(1.25 pg NO^/m ), the analytical procedure was responsible for 100% of the
reproducibility variation. It is therefore highly desirable to avoid solu-
tion concentrations that give readings on the extreme lower end of the absorbance
scale. At a concentration of 3.75 pg NO^/mft, analytical and field procedures
accounted for about equal parts of the total reproducibility variation. As
a general statement, the calibration curves used in the collaborative test
were found to be so imprecise that concentration readings were from 5% to
8% in error. This translates directly to an equivalent error in the mass calcu-
lation. The C then may vary 5-8% unless a recalibration of the spectro-
v
photometer is carried out before each analysis. In addition, there is an uncer-
tainty in the value of V , which depends on measurements of temperature,
S C-
pressure, and volume. Table 2 lists reasonable reading errors in these
variables.
Table 2. Estimates of reading errors in determination of V
1.
2.
3.
Variable
Temperature
Pressure
Volume
Measurement Method
Dial thermometer
U-Tube manometer
Graduated cylinder
Error
± 1°K
+ 1 mm
+ 10 m£
Mean Values
300° K
700 mm
2,000 m£
% Error
0.33
0.14
0.50
60
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Propagating these errors through the equation for determination of
vsc> the maximum error in V should be about 0.8%. It is apparent
that the error in a determination of C depends largely on the accuracy
of the spectrophotometer calibration and sample readings.
An estimate of the reproducibility is given as 7.48%, as shown in table 3.
Table 3.. Estimate for reproducibility of ER
Variable Assumed CV2{X}*
X cvL{5Nox} = 46
CV2/i2 = 3
CV2fQg) = 5
ER (R)2 = 55
R = 7
.92
.57
.43
.92
.48
..
4.1.2 Interferences
Hydrogen chloride has been shown to be a negative interferent (ref. 4).
The effect appears to be linear with HC1 concentration and is drastic at high
concentrations. With a test gas of approximately 100 ppm NOX and 1120 ppm HC1,
results were 78% low. At HC1 concentrations below 100 ppm the effect becomes
minor (less than 10%).
4.1.3 Bias
The method shows no appreciable bias in either direction, so
long as the absorbing solution concentration remains sufficiently high, i.e.,
within the normal working range of the calibration curve (ref. 2).
CV {X} values are taken from a collaborative study (ref. 2), and are consistent
method — °c
61
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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 quality is not consistent with suggested standards or with the user
4
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 attainable by following the operational
procedures given for the reference method.
The selection of possible actions for improving the data quality can
best be made 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 measure-
ment (s). In some cases it is difficult to estimate the reduction in
specific variances that are required to estimate the precisions of the per-
tinent measurements. In such cases, an experimental study should be made
of the more promising actions based on preliminary estimates of precision/
bias and the costs of implementing each action.
In order to illustrate the methodology, five 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: Take aliquots of sample so as to have several replicate results
from each sample (cost of $400 /20 field tests)
A2: Take integrated rather than grab sample, and irradiate during
sample collection to shorten absorption/oxidation step (cost of
$200/20 field tests)
A3: Thermostat spectrophotometer, standard solutions and samples to
minimize absorbance variances due to temperature fluctuations
(cost of $250/20 field tests)
Equipment costs are amortized over five years, and allowance is made for
the continuing cost of supplies and labor.
62
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A4: Do all calculations by a standard computer program, thus
eliminating personnel errors in calculation of results (cost
of $200/20 field tests)
A5: Conduct one-week workshop for all personnel involved in the method,
to minimize technique errors (cost of $1,000/20 tests)
The costs given for each action are additional costs above that of the reference
method. The assumptions made concerning the reduction in the variances (or
improved precisions) are given in the following for each action.
Al: The reference method allows the taking of only one aliquot, so that
only one absorbance reading is obtained per sample. It would reduce
the danger of sample voiding due to laboratory handling error if
three aliquots were taken. Also, a mean of three absorbances would
be more precise than a single value. The major effect of Al then
would be to reduce the within-laboratory relative standard deviation,
CV. This in turn will reduce the between-laboratory deviation, CV^,
since the values for NO concentration from different laboratories
X
will be grouped more tightly about the "true" value. Without any
experimental data, it is impossible to verify the above assumptions,
and certainly the estimation of numerical values for CV, CV^, and
is subject to a great deal of uncertainty. The estimated values
as given in table 4 for AO through A5 serve to illustrate the
methodology of cost-benefit analysis. The actual costs must be
determined in each individual situation, and the actual changes
in CV, CV^, and CV^ could be determined as the various options
are implemented. Figure 8 plots added cost versus data quality
for the various options, and includes a function curve for the
assumed cost of reporting poor quality data.
A2: An integrated sample normally gives a more reliable indication of
mean stack gas composition than a series of grab samples, since
sharp fluctuations in composition are smoothed out over time. A
series of grab samples may yield a mean value for the concentration
of NO which is widely different from the true concentration, if
x
the timing of the grab samples is such that the mean does not
reflect the true mean averaged over time. The major effect of
63
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Table 4. Assumed within-laboratory, between-laboratory,
and laboratory bias for action options
AO
Al
A2
A3
A4
A5
Reference
Three Aliquots Per Sample
Integrated Sampling
Temperature Control During
Analysis
Calculations by Standard
Computer Program
Personnel Workshop
CV
CVR
0.58 CV*
K.
0.7 CVR
0.8 CV,.
K
1.0 CVR
0.8 CVD
R
cvb
(CVb>R
0.8(CVfe)*R*
0.7(CVb)R
0.9(CVb)R
0.90(CVb)R
0.8(CVb)R
CVL
(CVR
0.96(CVT)_
Li K
0.70(CVL)R
0.98(CVT)D
L K
0.8(CVL)R
0.73(CVL)R
ADDED COST
PER 20
FIELD TESTS
0
$ 400
$ 200
$ 250
$ 200
$1,000
**
Values stated to one place are estimations based on engineering judgment.
64
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A2 then should be to reduce the between-laboratory coefficient
of variation, CV^, since the values become more tightly clustered
about the "true" value and it is assumed that this reduction in
CVb is reflected in CV and CV^, both becoming smaller.
A3: Thermostating the spectrophotometer cells and solutions reduces
the small fluctuations in absorbance values due to temperature
changes, and thus reduces CV by making a closer correspondence
between the calibration conditions and sample analysis conditions.
This relatively small improvement in CV is assumed to carry over
to both CV^ and CV^, since it amounts to fixing a parameter;
namely, the temperature, which inAOis allowed to fluctuate with
ambient laboratory temperature. In order to justify the assumption
of a carry-over improvement in CV., it must be required that
laboratory thermometer calibrations be against an NBS set of
calibrated thermometers. Otherwise, different laboratories will
be reading absorbances at different temperatures due to inaccurate
calibration.
A4: This recommended option serves a twofold purpose:
1. It eliminates human error (in the field) in calculation of the
NOX concentration. There remains, of course, the possibility
of errors due to computer malfunction, key punch error, and
the like.
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 calculators,
These could be made available by EPA, thus allowing local calculation
but standardizing the number of significant digits carried in each
step, the treatment of round-off, and other aspects of the
calculation steps.
Since one reason for laboratory bias, CVr , could be improper
calculation technique, A4 should in general reduce CV^. This is
a systematic error (bias). In addition, a small percentage (about 3%)
65
-------
of random calculation errors contribute to CV. If both CVL and
CV are reduced, then CVj, should also be improved.
A5: From discussing this method with experienced field testers, it
is felt that the method requires an operator that 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 or
variability, and therefore an improvement in all three measures
of variability is shown.
Figure 8 shows the results in terms of cost and data quality.
Data quality for this purpose is given as CV, the within-laboratory
coefficient of variation. The figure then illustrates options for the
individual 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 9. It must be emphasized that figures 8 and 9 are given
for illustrative purposes only and should not in themselves be con-
sidered 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
b
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 7 by a number of modi-
fications of the method, and that there is a cost associated with each
modification.
Figures 8 and 9 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 monitoring objectives of the laboratory or group of
laboratories.
Once determined for a given situation, graphs such as figures
8 and 9 can be used to select an "optimal" monitoring strategy, i.e.,
one which gives maximum increase in data quality for minimum cost.
In both cases illustrated here, choosing strategy A2 would be optimal.
66
-------
00
t—
oo
1000 -
900 -
800 -
700 -
600 -
500 -
o
CM
§ 400
00
O
Q
UJ
Q
Q
300 -
200 -
100 -
QA5
BEST ACTION
OPTIONS
COST OF REPORTING
POOR QUALITY DATA
Figure 8. Added cost versus data quality (CV) for selected action options -
67
-------
co
t—
00
o
CNJ
DE
UJ
D-
00
O
0
0
cC
1000
900
800
700
600
500
400
300
200
100
OA5
COST OF REPORTING
POOR QUALITY DATA.
BEST ACTION
OPTIONS
45
cv
Figure 9. Added cost versus data quality (CV, ) for selected action options,
68
-------
In some instances a manager may need to know the total cost
of attaining a prescribed reduction in variability. Figures 8 and
9 can be used to find the method which most nearly meets the require-
ment. The cost of implementing the method, plus the cos.t 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 Al and A3
were both implemented, the total cost would be $650 ($400 + $250) and
the values of CV and CV, would be as given below.
CV
CV b
AO 6.56 (=CVR) 9.49 (=(CVb)R)
Al 0.58 (CVR) 0.8 (CVb)R
A3 0.8 (CVR) 0.9 (CVb)R
(A1 + A3) (0.58) (0.8) (CVR) (0.8) (0.9) (CVb)
= 0.46 (CVR) = (.72) (CVb)R
= 3.04 = 6.83
69
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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 NO in air and has the field
team analyze the sample. The field team should not know the true
NO concentration. From these data both bias and precision estimates can
be made for the analysis phase of the measurement process.
The auditor, i.e., the individual performing the audit, should have
extensive 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 procedures and techniques of the field team during on-site
measurements.
2. Have field team measure sample from a reference cylinder with
known NO concentration.
3. Check/verify applicable records of equipment calibration checks
and quality control charts in the field team's home laboratory.
4. Compare the audit value with the field team's test value.
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 appro-
priate 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
70
-------
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.
4.3.2 Collecting On-Site Information
While on site, the auditor should observe the field team's overall
performance of the field test. Specific operations to observe should in-
clude, but not be limited to:
1. Setting up and leak-testing the sampling train;
2. Preparation and pipetting of absorbing solution into sampling
flask;
3. Sample collection;
4. Sample absorption, 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.
Reference gas samples can be prepared by air dilution of cylinder NO
in N«. For details, see pages 2-5 of reference 3. These reference samples
should then be analyzed by the field team.
4.3.3 Collecting Home Laboratory Information
The auditor must also observe the analytical phase of Method 7. Here
he should observe the following:
1. Sample aliquotting technique. This is particularly important, to
verify that standard analytical technique is being followed.
2. Evaporation and chemical treatment of sample, including filtration
and washing steps.
3. Spectrophotometric technique, including -
a. Preparation of standard nitrate samples;
b. Technique of making absorbance measurements, including
measurement of blanks;
c. Preparation of calibration curve, including technique used for
drawing of curve (visual, linear regression);
d. Wavelength and absorbance calibrations using didymium glass and
filters.
4. Calculation procedure.
71
-------
The analysis phase of Method 7 can be audited with standard nitrate
solutions, as discussed on pages 33-36 of reference 3.
4.3.3.1 Comparing Audit and Routine Values of NO . In field tests
-j£
the audit and routine (field team) values are compared by
where
d. = The difference in the audit and field test results for the
J -th j- / 3
j audit, mg/m
m
(N09) = Audit value of N09 concentration, mg/
2. 3. Z
J 3
(N02) . = N0? concentration obtained by the field team, mg/m
Record the value of d. in the quality audit log book.
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 audit.
However, unmeasurable errors can result from nonadherence to the prescribed
operating procedures and/or from poor technique in executing the 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 conjv action 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.
72
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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 accuracy 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 vari-
ables. 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 consistent 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 NO concentration were given in section 4.1. This section will
X
indicate how the audit data collected in accordance with the procedure
described in section 4.2 will be utilized in order to estimate the precision
and accuracy of the measures of interest. Similar techniques can also be
used by a specific firm or team to assess their own measurements. The
differences between the field team results and the audited results for the re-
spective measurements are
d. = (N02). - (N02)aj.
Let the mean and standard deviation of the differences d., where j = l, ... n be
denoted by d, and s., respectively. Thus
and
n
sd =
V~^ - ?
> (d. - d) /(n - 1)
73
-------
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.,
t - d - 0
<- —
See ref. 5 for a discussion of the t-test.
If t is significantly large, say greater than the tabulated value of t
with 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 'ata is
acceptable.
The standard deviation s, is a function of both the standard deviation
d
of the field measurements and of the audit measurements. Assuming the audit
values to be much more accurate than the field measurements, then s is an
d
estimate of ofNC^}, the population standard deviation forNO_ measurements
The standard deviation, s,, can be utilized to check the reasonableness of
d *
the assumptions made in section 4.1 concerning afNO,,} . For example, the
estimated standard deviation, s , , may be directly checked against the assumed
value, crfNC^}, by using the statistical test procedure
o 2
2 s,
*_ = _!
f 2
2
where x /f is the value of a random variable having the chi-square distri-
2
bution with f = n - 1 degrees of freedom. If x /f is larger than the tabu-
lated 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 operational procedure.
Values for a{NO«} and ovfNC^} are found by multiplying the values of CV or
CV, by the assumed value of the mean concentration of NO,,. This converts
b ^
the percentages into concentrations.
74
-------
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
different from the assumed population parameters, should be identified on
the data sheet.
2
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 pos-
sible. 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 publications having information on sampling by variables; e.g., see
refs. 6-11. The discussion below will be given in regard to the specific
problem in the variables approach, which has some unique features as com-
pared with the usual variable sampling plans. In the following discussion,
it is assumed that only NCL measurements are audited as directed in section
4.3. The difference between the team-measured and audited value of NO
is designated as d., and the mean difference over n audits by d is
n
d = 1/n V (NOJ. - (N02)
75
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Theoretically, (NO-) and (NO'i should be measures of the same NO2 concentration
and their difference should have a mean of zero on the average. In addition,
this difference should have a standard deviation approximately equal to that
associated with the measurements of NCb.
3 *
Assuming three standard deviation limits, the values 3cr = -19.7 tng/m and
O
+ 19.7 mg/m define the respective lower and upper limits, L and U, out-
side of which it is desired to control the proportion of differences, d .
Following the method given in ref. 9, a procedure for applying the vari-
ables sampling plan is described below. Figures 10 and 11 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,,
d
and a constant, k, which is determined by the value of p, the proportion of
the differences outside the limits of L and U. For example, if it is de-
sired to control at 0.10 the probability of not detecting lots with data
qualities p equal to 0.10 (or 10 percent of the individual differences out-
side L and U), and if the sample size n = 7, then the value of k can be
obtained from table II of ref,, 9. The values of d and s, are computed in
the usual manner; see table 5 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:
* 3
19.7 mg/m assumes for calculation purposes an N00 concentration mean of
3 i
100 mg/m , with CV = 6.56%, so that 3cr = 3x6.56 = 19.7 mg/m
76
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Table 5. Computation of mean difference, d, and
standard deviation of differences, s
General Formulas
d =
dl
d
2
A
3
d,
4
d,
5
d.
6
d7
Ed.
J
I *
2
Sd
Sd
(N02).-(N02)a.
d2,
d2
2
2
d.
3
d2
4
d2
5
d.
6
2
d7
Ed2
J
Ed.
(Ed )2
9 T
Ed. - - J —
JT-)
LI
(n~ - lT ""
-V?
Specific Example
3
Data mg/m
-17.0 289
8.5 72
0.0 0
33.9 1149
25.4 645
12.7 161
0.0 0
+63.5 2316
d - +9.1 mg/m
9
s^ - 331
d
3
s * 18.2 mg/m
d
1. If both of the following conditions are satisfied,
d - k s > L = -19.7 mg/m
d —
3
d + k s, < U = +19.7 mg/m
d —
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 defi-
ciencies exist in the measurement process as carried out for that
77
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P - P, + Po < 0-10
Figure 10. Example illustrating p < 0.10 and satisfactory data quality.
p (percent of measured
differences outside
limits L and U) > 0.10
Figure 11. Example illustrating p > 0.10 and unsatisfactory data quality.
particular lot (group) of field tests. These deficiencies should
be identified and corrected before future field tests are performed.
Data corrections should be made when possible, i.e., if a quanti-
tative basis is determined for correction.
Table 6 contains a few selected values of n, p, and k for convenient
reference. Using the values of d and s in table 2, k = 2.334 for a sample
size n = /, and p = 0.10, the test criteria become
d - k sd = 9.1 - 2.334 x 18.2 = -33.4 < L =-19.7 mg/m3
d + k s.
9.1 + 2.334 x 18.2 = 51.6 > U =+19.7 mg/m"
78
-------
Table 6. Sample plan constants, k for P {not detecting a lot
with proportion p outside limits L and u} < 0.1
Sample Size n
3
5
7
10
12
p - 0.2
3.039
1.976
1.721
1.595
1.550
p - 0.1
4.258
2.742
2.334
2.112
2.045
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 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 de-
tected by this sampling plan.
4.4.3 Cost Versus Audit Level
The determination of the audit level (sample size n) to be used in
assessing 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
associated with the audit procedure are estimated or assumed, for the pur-
pose 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 12. 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 measurement audited. In order to make a specific deter-
mination of n, it is also necessary to make some assumptions about the
79
-------
Collection of Source Emission
Tests (Lots of Size N)
50% of Lots
< 10% Defective
Acceptable
Quality
Not Acceptable
Quality
Audit n
Measurements
bfcn = $600
50% of Lots
10% Defective
Audit n
Measurements
Select Audit
Parameter n, k
Yes
No
1
— — V. ib - a ^
X. d - ks, >L/^
X. d Jr
' \
Data Declared
to be of
Acceptable-
Quality
i
r l
1
Data Declared
not to be of
Acceptable
Quality
s
• J_
Report
Data
4, m
A f
' 1
\
i
Institute Action to
Improve Data Quality
(Correct Data if
Possible)
Data Declared
to be of
Acceptable
Quality
Expected Cost of
Treating Poor
Quality Data as
Good Quality Data
CG|P = $15'000
A
Expected Cost of
Falsely Inferring
Data are of Poor
Quality
$10,000
1
Expected Cost
Saving of Taking
Correct Action with
Respect to Poor
Quality Data
g =y$7,500
Figure 12 . Flow chart of the audit level selection process.
80
-------
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 as-
surance practice, and that 50 percent of the data lots are .of poor quality.
Based on the analysis in section 4.1, 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 3a limits, corresponding to limits used in a control chart, the
quality of data provided by firmly adhering to the recommended quality as-
surance procedures should contain at most about 0.3 percent defective mea-
surements (i.e., outside the limits defined by L and U). Herein, good
quality data is defined as that containing at most 10 percent defective mea-
surements. The definition of poor quality data is somewhat 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 ,
where d and s are the mean and standard deviation of the data quality char-
acteristic (i.e., the difference of the field and audited measurements)
being checked. The data are not of desired quality if one or both inequali-
ties are violated, as described in section 4.3. The costs associated with
these actions are assumed to be as iollows:
C. = Audit cost = b + en. It is assumed that b is zero for this exam-
A
pie, and c is taken as $600/measurement.
C 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 $1000 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 collec-
tion, and of decisions resulting in the purchase of equipment to
reduce emission levels of specific pollutants, etc.
81
-------
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.
C i = 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 C i or equal to 0.375 x $1,000 x 20, the total cost of data
collection.
These costs are given in figure 12 . The cost data are then used in
conjunction with the a priori information concerning the data quality, to
select an audit level n. Actually, the audit procedure requires the
selection of the limits 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 6 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(TC) = - CA - 0.5 Pp,G Cp|G + 0.5 Pp|p Cp|p - 0.5 PQ p CG|p (22)
where the costs are as previously defined. The probabilities are defined
in a way similar to defining corresponding costs:
P i = Probability that a lot of good quality data is falsely inferred
r lb
to be of poor quality, due to the random variations in the
sample mean d and standard deviation, s , in small samples of
size n.
P i = Probability that a lot of poor quality data is correctly identi-
fied as being of poor quality.
P i = Probability that a lot of poor quality data is incorrectly judged
G | P _
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 percentage of good (poor) quality data lots.
In order to complete the determination of n, it is necessary to calcu-
late each of the conditional probabilities, using the assumptions stated
82
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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 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 equation (22) 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 13. 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 sug-
gested that p = 0.2 is more cost effective; this tends to permit data of
poorer quality to be accepted.
83
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$8000
$6000
$4000
w
•u
oo
o
o
o
-------
SECTION V REERENCES
1. Henry F. Hamil and David E. Camann. "Collaborative Study of Method for
the Determination of Nitrogen Oxide Emissions from Stationary Sources
(Fossil Fuel Fired Steam Generators)." Final Report, EPA Contract
No. 68-02-0623, Southwest Research Institute, San Antonio, Texas 78284.
2. Henry F. Hamil et. al. "The Collaborative Study of EPA Methods 5, 6, and 7
in Fossil Fuel Fired Steam Generators Final Report." EPA Contract No.
68-02-0623, Southwest Research Institute, San Antonio, Texas 78284.
3. H. F. Hamil and R.E. Thomas. "Collaborative Study of Method for the Determina-
tion of Nitrogen Oxide from Stationary Sources (Nitric Acid Plants)."
Final Report, EPA Contract No. 68-02-0626, Southwest Research Institute,
San Antonio, Texas 78284.
4. Henry F. Hamil. "Laboratory and Field Evaluations ot EPA Methods 2, 6 and
7." Final Report, EPA Contract No. 68--02-0626. Southwest Research
Institute, San Antonio, Texas 78284.
5. H. Cramer. The Elements of Probability Theory. New York: John Wiley & Sons, 1955.
6. Statistical Research Group, Columbia University, C. Eisenhart, M. Hastay, and
W. A. Wallis, eds. Techniques of Statistical Analysis. New York: McGraw-
Hill, 1947.
7. A. H. Bowker and H. P. Goode. Sampling Inspection by Variables. New York:
McGraw-Hill, 1952.
8. A. Hald. Statistical Theory with Engineering Applications. New York: John
Wiley and Sons, 1952.
9. D. B. Owen. "Variables Sampling Plans Based on the Normal Distribution."
Technometries 9, No. 3 (August 1967).
10. D. B. Owen. "Summary of Recent Work on Variables Acceptance Sampling with
Emphasis on Non-normality." Technometrics 11 (1969):631-37.
11. Kinji Takogi. "On Designing Unknown Sigma Sampling Plans Based on a Wide
Class on Non-Normal Distributions." Technometrics 14 (1972): 669-78.
12. John N. Driscoll. "Flue Gas Monitoring Techniques." Ann Arbor Science
Publishers, Inc., Ann Arbor, Michigan 48106.
13. Herman H. Martens et. al. "Improved Phenoldisulfonic Acid Method for Determina-
tion of NO from Stationary Sources." Environmental Science and
Technology, December, 1973.
85
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14. "Standards of Performance for New Stationary Sources," Federal Register, Vol. 36,
No. 247, December 23, 1971.
15. Walter S. Smith and D. James Groye, "Stack Sampling Nomographs for Field
Estimations," Entropy Environmentalists, Inc., Research Triangle Park,
North Carolina, 1973.
16. Franklin Smith and D. E. Wagoner, and A. C. Nelson, "Determination of Stack
Gas Velocity and Volumetric Flow Rate," EPA Contract 68-02-1234,-! HA 327,
Research Triangle Institute, Research Triangle Park, North Carolina,
February 1974.
17. Charles N. Reilley and D. T. Sawyer, "Experiments for Instrumental Methods,"
McGraw-Hill Book Company, New York, 1961.
86
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APPENDIX A METHOD 7 - DETERMINATION OF NITR3GEN OXIDE
EMISSIONS FROM STATIONARY SOURCES
1. Fri ncj pie_and_Appl1cabi 1i ty
1.1 Principle. A grab sample is collected in an evacuated
flask containing a dilute sulfuric acid-hydrogen peroxide absorbing
solution, end the nitrogen oxides, except nitrous oxida, are
ir.sesurt-:d cylcrimctrically using the phenoldisulfonic rxid (PDS)
procedure,
1.2 Applicability. This method is applicable to the measure-
ment of nitrogen oxidss omitted from stationary sources only v/hen
specified by the test procedures for determining compliance with
new source performance standards. The fringe cf the method has been
determined to be 2 to 400 milligrams NO as N0« Per dry standard
cubic meter without having to dilute the sample.
2. App.:^-5tur,
2.1 Sampling (See Figure 7-1).
2.1.1 Probe—Borosilicate glass tubing sufficiently heated to
prevent water condc-nsation. end equipped with a filter (either in-st^ck
or heated out of stack) to remove particulate matter. Heating is
unnecessary if the probe remains dry during the purging period.
2.1.2 Collection flask-~Twc-liter borosilicate, round bottom
with short neck and 24/40 standard taper opening, protected against
implosion or breakage.
2.1.3 Flask valve--T-bore stopcock connected to a 24/40 standard
taper joint.
87
-------
•at.
O
LU
CO
TO
T3
CO
CJ
>
CO
CD
D)
c
"5.
E
ca
to
0)
88
-------
2.1.4 Temperature nauqe--0ial-type thermometer, or eaulvalent,
capable of measurinq "l°C (2°F) intervals from -5 to 50°C (25 to 125°F).
2.1.5 Vacuum line--Tubinq capable of withstanding a vacuum
of 75 mm l!g (3 in. Hq) absolute pressure, with "T" connection and
T-bore stopcock.
2.1.6 Pressure nauge---U-tube nanometer, 1-meter, v/ith 1-mm
(3f--in., v/ith 0.1-in.) divisions, or equivalent.
2.1.7 Pump—Capable of evacuating the collection flask to a
pressure equal to or less than 75 rm Hq (t in. f'g) absolute.
2.1.R Saueoze bulb—One-way
2.1.9 Volunetn'c pipette—25-ml.
2.1.10 Stopcock and around .ioint arease--A hinli vacuum, hinh
temperature chlorofluorocarbori grease is required. Holocarbon 25-5S
has been found to be effective.
2.1.11 Barometer—Mercury, aneroid, or other barometers cauable
of measuring eti.iosn'ncric pressure lo vrithin 2.B mm Hq (0.1 in. Ho).
In many cases, the barometric readinq rv.y be obtained from a nearby
weather bureau station, in which case the station value shall be
requested and an adjustment for elevation differences shall be applied
at a rate of minus 2.5 mm Hq (0.1 in. Hq) per 30 m (100 ft) elevation
increase.
2.2 Samnle recovery.
2.2.1 Volumetric pit>ette--0ne 25-ml ^or each samole.
2.2.2 Graduated cylinder--50-ml with 1-rnl divisions.
Mention of trade names or snecific products does not constitute
endorsement by the Fnvironniental Protection Aoencv.
89
-------
2.2.3 Storage containers--Leak-free polyethylene bottles.
2.2.4 Wash bottle—Polyethylnne or class.
2.2.5 Class stirring rod.
2.2.6 pH indicating test paper—To cover the pH range of 7-1 <1.
2.3 Analysis.
2.3.1 Volun£ln'c pipPttes--Tv.'o l~nil, t--/o P-nl, one 3-nl, one
4--nl and t'.'o 10-ml, r.nij one 25-nl for each s;.nnle and standard.
2.3.2 Porcelain evaporating dishes. 175 to 250-ml canacity
\\'ith lip for poiTinq, on? for each sample snd each stanJard. The
Coors -^COOb (shcrnoi./-fon',i5 195 ml) has heen found to he satisfactory
2.3.3 StPcini bach. (A hot plate is not accentoblo.)
2.3.4 Dropping tn'pettp or dropper--Threo required.
2.3.5 Polyethylene policeman—One for each sannle and each
standard.
2.3.6 Graduated cylinder--!00~ml v/ith 1-nil divisions.
2.3.7 Volunetric flasl's-'-PO-nl (one for each sample), 100-ml
(one for each sample, each standard and one for the working standard
KN03 solution), and one 1000-ml.
2.3.8 Spectrophotornetei—To measure absorbance at 410 nm.
2.3.9 Graduated pipette--10-ml, with 0.1-ml divisions.
2.3.10 pH Indicating test paper—To cover the pH range of 7-14.
2.3.11 Analytical balance—To measure to 0.1 mg.
3. Reagents
Unless otherwise indicated, it is intended that all reagents
conform to the specifications established by the Committee on
tlentior, or t.rac'e nr.PT^ or specific products does not constitute
endorsement by the fnvironnicjntal Protection Agency.
90
-------
Analytical Reagents of the American Chemical Society, where such
specifications are available; otherwise, use best available grade.
3.1 Sampling.
3.1.1 Absorbing solution—Cautiously add 2.8 ml concentrated
HpSO^ to 1 liter of deionized, distilled water. Mix well and add
G IT-! of 3 percent hydrogen peroxide, freshly nrenarec! from 30 percent
hydrooen pericxic'c solution. The solution should be used within
one week of its preparation. Po not expose to extreme heat or direct
sunlinht.
3.2 Sample recovery.
3.2.1 Sodium hycYoxide (1 P)--Dissolve 40 g NaOH in deionized,
distilled water and dilute to 1 liter.
3.2.2 1,'ater—Deionized, distilled to conform to ASTM specifica-
tions 01193 72, Type 3.
3.3 Analysis.
3.3.1 Funn'no sulfuric acid--!5 to IB percent by weight free
sulfur trioxide. Handle with caution.
3.3.2 Phenol--White solid.
3.3.3 Sulfuric acid—Concentrated, 95% minimum assay. Handle
with caution.
3.3.4 Potassium nitrate—Dried at 105-110° C for a minimum of
two hours just prior to preparation of standard solution.
3.3.5 Standard solution—Dissolve exactly 2.1980 g of dried
potassium nitrate (KNO^) in deionized, distilled water and dilute
to 1 liter with deionized, distilled water in a 1000-ml volumetric
91
-------
flask. For the working standard solution, dilute 10 M! of the
standard solution to 100 ml v/ith deionized distilled water. One rnl
of the working standard solution is equivalent to 100 yq nitrogen
dioxide (NOg).
3.3.6 Water~~Dcioni?.ed, distilled as in section 3.2.2.
3.?.7 Phenoldisiilfonic acid solution—Dissolve 25 g of pure
white phenol in 1"0 nil concentrated sulfuric acid on a steam bath.
Cool, add 75 ml fumino sulfcric acid, and heat at 100°C (212°F) for-
2 hours.- Store in a dark, stoppered bottle.
4. Procedure
4.1 Sampling.
4.1.1 Pipette 25 ml of absorbing solution into a sample flark,
retaining a sufficient quantity for use in preparing the calibration
standards. Insert the flask valve stooper into the flask with the
valve in the ''purge" position. Assemble the sampling train as shown
in figure 7-1 and place the probe at the sampling noint. Make sure
that all fittings are tight and leak free, and that all ground glass
joints have been properly greased with a high vacuum, high temperature
chlorofluorocarbon-based stopcock grease. Turn the flask valve and the
pump valve to their "evacuate" positions. Evacuate the flask to
75 nn Hg (3 in. Hg) absolute pressure, or less. Evacuation to a lower
pressure (approaching the vapor pressure of water at the existing
tenperaturc) is even more desirable. Turn the pump valve to its "vent"
position and turn off the pump. Check for leakage by observing the
92
-------
manometer for any pressure fluctuation. (Any variation qreater than
10 nm Hg (0.4 in. Hg) over a period of 1 minute is not. acceptable, and
the flask is not to be used until the leakp.oo problem is corrected.
Pressure in the flask is not to exceed 75 mm Hq (3 in. Hg) absolute
at the time sampling is commenced.) Record the volume of the flask
and valve (V,.), the flask terporature (T.). arid the barometric pres-
sure. Turn the t'lfisk valve ccunterclochn'so to its ''rurqe" position
and do the same with the pump valve. Purqe the probe and the vacuum
tube using the squeeze bulb. If condensation occurs in the probe
and the flask valve area, heat the probe and purae until the con-
densation disappears. Then turn the pump valve to its "vent" position.
Turn the flask valve clockwise to its "evacuate" position and record
the difference in the mercury levels in the manometer. The absolute
internal pressure in the flask (P.) is equal to the barometric pres-
sure loss the manometer reading. Immediately turn the flask valve to
the "sample" position and permit the gas to enter the flask, until
pressures in the flask and sample line (i.e., duct, stack) are
virtually equal. This will usually require about 15 seconds. A
longer period indicates a "plug" in the probe which must be corrected
before sampling is continued. After collecting the sample, turn the
flask valve to its "purge" position and disconnect the flask from
the sampling train. Shake the flask for at least 5 minutes.
4.1.? If the gas being sampled contains insufficient oxygen for
the conversion of HO to NO., e.g. an applicable suboart of the standard
93
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may require taking a sample of a calibration gas mixture of MO in fL,
then oxynsn shall be introduced into the flask to permit this con-
version. Oxygon may be injected into the flask after sampling or
the sampling may be terminated with a minimum of two inches of mer-
cury vacuum remaining in the flask. This final pressure is recorded
and then the flask is vented to the atmosphere until the flask pressure-
is almost equal to atmospheric pressure.
4.2 Sample recovery.
4.2.1 Lt-t the flask set for a mini nun of 16 hours and then
shake the contents for 2 minutes. Connect the flask to a mercury
filled IJ-tuhc mar.orcter, open the valve from the flask to the
manometer,, and record the flask temperature (I,), the barometric
pressure and the difference between the mercury levels in the
manometer. The absolute internal pressure in the flask (PJ is
the barometric pressure less the manometer reading. Transfer the
contents of the flask to a leak-free polyethylene bottle. Rinse
the flask twice with 5-ml portions of deionized, distilled water
and add the rinse water to the bottle. Adjust the pH to 9 - 12 by
adding sodium1 hydroxide (1 M) dropwise (about 25 to 35 drops). Check
the pH by dipping a stirring rod into the solution and then touching
it to the pH test paper. Remove as little material as possible
during this step. Mark the height of the liquid level to deter-
mine whether or not leakage occurred during transport. Label
container to clearly identify its contents. Seal the container
for shipping.
94
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4.3 Analysis.
4.3.1 Note level of liquid in container and confirm whether
or not any sorple was lost durinn shipment by notino this on
analytical data sheet. Transfer the contents of the shipping con-
tainer to a 50-ml volui.tctric flask, rinse the container twice with
5-rnl portions of deiotii^d, distilled water, add the rinse water
to the flask and dilute to the mark with deionizod, distilled water.
fl'ix thorouohly and pipette a 25-ml aliauot into the porcelain evapo-
rotinn dish. Fvaporate the solution to dryn^ss on a steam bath and
allow to cool. • (Use only o steam bath--a hot ol?te is not acceptable.)
Add 2 ml phenoldisulfonic acid solution to the dried residue and triturate
thoroughly «''i Ui a polyethylene policeman. Make sure the solution
contacts all the residue. Add 1 nl deionizrd, distilled water and
four drops of concentrated sulfuric acid. Meat the solution on a
steam bath for 3 minutes with occasional stirrir.o. Cool, add 20 nil
deionizec1, distilled water, mix well by stirrinq and add concen-
trated ammonium hydroxide dropwise with constant stirrinq until nH
is 10 (as determined by pH paper). If the sample contains solids,
filter throuph Whatman No. 41 filter paper into a 100-ml volumetric
flask; rinse the evaporating dish with three 5-ml portions of de-
ioin'zed, distilled water and add these to the filter. Mash the
filter with at least three 15-ml portions of deionized, distilled
water. Add the filter washinqs to the contents of the volumetric
flask and dilute to the mark with deionized, distilled water. If
95
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solids are absent, transfer the solution directly to the 100-ml
volumetric flask and dilute to the nark v/ith deionized, distilled
water. Mix thoroughly and measure the absorbance at 4in nn using
the blank solution as a zero reference. Dilute the samole and the
blank vn'th a suitable amount of deionized, distilled water if ahsorbance
exceeds A», the absorbance of the "00 yg f!0« standard (See section 5.3).
5 • Q_oJ j_b r?.t i_cn_
5.1 Flask volume. Assemble the flask and flask valve and fill
v.'ith water to the stopcock. Measure the volume of water to ± 10 ml.
Number and record the volume on the flask.
5.2 Spectrcphotoiiieter calibration. Add 0.0 ml, 1.0 ml, 2.0 ml,
3.0 ml and 4.0 ml of the K'Nn workinn standard solution (1 ml = 100 jig
>J
N0?) to a series of five porcelain evaporatinq dishes. To each, add
25 ml of absorbing solution, 10 nl deionized, distilled water and
sodium hydroxide (1 N) dronwise until the pH is 9-12 (about 25 to
35 drons each). Retiinning with the evaporation step, follow the
analysis procedure of Section 4.3 to collect the data necessary
to calculate the calibration factor (Section 5.3). This calibration
procedure nust be repeated on each day that samples are analyzed.
5.3 Determination of spectrophotometer calibration factor K .
\*
A, + 2A? -f 3A~ -f 4A.
K = 100 —- - 4 - Equation 7-1.
96
-------
v.'here:
K * Calibration factor.
\*
A, = Absorbance of tho TOO yo NfL standard.
Ap = Absorhraice of the 200 yq NO standard.
A0 = Absorhfincp of the 300 y0 NO,, st.yndard.
O ' f.
A|/t = Absorbancr- of tho 400 yn N09 standard.
5.4 Barometer. Calibrate anainvt a mercury barometer.
5.5 Toiiiporatin-o nauno. Calibrate dial thtrnicmfitors
nercury-in-qlass thermometers.
6. Calcula'cions
Carry out the calculations, reteininq at leas I one extra decinal
figure beyond that of the acpuirod data. Round off finures after
final calculations.
6.1 Ncrrenclature.
A - Absorbance of sample
C = Concentration of NO as NO dry basis, corrected to
x <.
standard conditions, mq/dscn (lb/dscf).
F = Dilution factor (i.e., 25/5, 25/10, etc, required only
if sample dilution was needed to reduce the absorbance
into the range of calibration).
K = Spectrophotor.ieter calibration factor.
97
-------
m = Mass of NO as N05 in gas sample, yg.
X c
P^ = Final absolute pressure of flask, mm Hg (in. Hg).
P. = Initial absolute pressure of flask, mm Hg (in. Hg).
Pstd = standard absolute pressure, 760 mm Hg (2D.92 in. Ho)
T,. = Final absolute temperature of flask, K (°k).
Ti = Initial absolute temperature of ricisk, °K (°K).
Tstd = standard absolute temperature, J?G3°K (E28°R).
V - Seraple volume- ~t standard conditions (dry basis), r,;l
o **f
Vf ~ Volume of flask and v^lve, ml.
V = "oiur.e of absorbing solution, ?b ml.
a
2 - 50/25. the aliquot factor. (If other ti.on o 25-ml
aliquot was used for analysis, the corresponding
factor riu:t be substituted.)
6,2 Sample- volume, dry bets is, corrected to standard conditions.
sc
where:
Tstd /., v \
Pstd ( f &)
"f - Pi"
Tf T
= K (vf - 25 ml)
"pf
Jf
P.
TI
Equation 7-2
i/ n oocr K for metric units
K = °'3855 r^TTlg
= 17.65 ---Anr for FngHsh units
6.3 Total yg N02 Per sample
rn
Equation 7-3
Note: If other than a 25-ml aliquot is used for analyses,
the factor 2 must be substituted by a corresponding factor.
98
-------
6.3 Sample concentration, dry basis, corrected to standard
conditions.
C = K -v— - Equation 7-4
sc
where:
K = 103 rr.. for metric units
(nT) (jig)
-5 lb/crf r
= 6.243 x 10 --~£T for English units.
V \jl ''' *
7.1 Standard Methods of Chcrrical Arif'lysis. 6th ed. New York,
D. Van Nostrand Co., Inc., 1962, vol. 1, p. 3P9-330.
7.2 Standard Method cf Test Tor Oxides of Nitronsn in Gaseous
Combustion Products (Phcnoldiculfonic Acid Procedure), In: 1968 Book
of ASTM Standards, Pert 23, Philadelphia, Pa., 1968, ASTM Designation
D-16C8-50, p. 725-729.
7.3 Jacob, M.B., The Chemical Analysis of Air Pollutants, flew York,
N. Y., Intersclsnce Publishers, Inc., 1960, vol. 10, p. 351-3E6.
7.4 Beatty, R. L., Berger, L. B. end Schrenk, H. H., Detemii nation
of Oxides of Nitrogen by the Phenol disulfcnic Acid Method, R. I. 3687,
Bureau of Mines, U. S. Dept. Interior, February (1943).
7.5 Hami'l , H. F., end Camann, D. E., Collaborative Study of Method
for the Determination of Nitrogen Oxide Emissions from Stationary
Sources (Tossil Fuel-Fired Steam Generators), Southwest Research
Institute report for Environmental Protection Agency, October 5, 1973.
7.6 Hamil, H. F., and Thomas, R. E., Collaborative Study of
Method for the Determination of Nitrogen Oxide Emissions from
Stationary Sources (Nitric Acid Plants), Southwest Research Institute-
report for Environnental Protection Agency, May 8, 1974.
99
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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
calculation of an audit is performed in the flow chart. Each operation has
refeiences to the section in the text of the report where it is discussed.
100
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WNAGER
1. 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 o{N02} = 6.56 mq/m3
(subsec. 4.1)*, AND DSING_± 3 a {N02K THE ,
LIMITS ARE L = -19.7 mg/m3 AND U = 19.7 mg/mJ
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 = 5 (fig. 13).
5. BY TEAMS, TYPES OF SOURCES, OR GEOGRAPHY,
GROUP FIELD TESTS INTO LOTS (GROUPS) OF ABOUT
20, TO 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
THE n AUDITS
Based on a 100 mg/m sample mean and CV = 6.56%.
101
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AUDITOR
8. THE AUDITOR OBTAINS APPROPRIATE CALIBRATED 8
EQUIPMENT AND SUPPLIES FOR THE AUDIT
(subsec. 4.3).
9. OBSERVE THE FIELD TEAM'S PERFORMANCE OF THE 9
FIELD TEST (subsec. 4.3.? AND 4.3.3) AND NOTE ANY
UNUSUAL CONDITIONS THAT OCCURRED DURING
THE TEST.
10. THE AUDITOR'S REPORT SHOULD INCLUDE (1) DATA 10
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
(subsec. 4.3.4).
11. THE AUDITOR'S REPORT IS FORWARDED TO THE 11
MANAGER.
WNAGER
12. COLLECT THE AUDITOR'S REPORTS FROM THE n 12
AUDITS OF THE LOT OF N STACKS. IN THIS
CASE n = 7 AND ASSUMED VALUES FOR THE
AUDITS ARE d, =-17, d2 = 8.5, d3 = 0,
d. =33.9, ds = 25.4, dfi = 12.7, and d7 = 0
(table 5).
13. CALCULATE
-------
15. OBTAIN THE VALUE OF k FROM TABLE 6, FOR n = 7 15
AND p = 0.1. THIS VALUE IS 2.334, THEN
d + k sd = 51.6 mg/m3 AND 3 - k sd = -33.4 mp/m3
(subsec. 4.4.2).
16. COMPARE THE ABOVE CALCULATIONS WITH LIMITS 16
L AND U (subsec. 4.4.2). FOR THIS EXAMPLE
d~ + k sd =51.6 > U = 19.7 mg/m3
d - k sd = -33.4 < L = -19.7 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 (subsec. 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
103
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APPENDIX C GLOSSAL 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 Ox/Px)•
A
CV{X> Computed coefficient of variation (100 sxAx) from a finite
sample of measurements.
a{x) Assumed standard deviation of the parameter X (population
standard deviation).
/v
T{X} Computed bias of the parameter X for a finite sample
(sample bias).
d. The difference in the audit value and the value of NC^
arrived at by the field crew for the j audit.
d Mean difference between (N0«) . and (NO,) . for n audits.
2 3 2 aJ
s , Computed standard deviation of differences between (N00) . and
d ^ j
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/ ..,. Statistic used to determine if the sample bias, d, is
significantly different from zero (t-test).
2 2
X /(n -1) Statistic used to determine if the sample variance, s , is
r\
significantly different from the assumed variance, <3L , of
the parent distribution (chi-square test).
104
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APPENDIX C GLOSSARY OF SYMBOLS (CONTINUED)
SYMBOL DEFINITION
L Lower quality limit used in sampling by variables.
U Upper quality limit used in sampling by variables.
CL Center line of a quality control chart.
LCL Lower control limit of a quality control chart.
UCL Upper control limit of a quality control chart.
NO,, Nitrogen dioxide reported by the field team for field test,
(NO,,) Nitrogen dioxide concentration used in an audit check.
^- a
(N00) Measured value of a calibration gas.
<£ m
(NO-) Assayed or known value of a calibration gas.
105
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APPBIDIXD
GLOSSARY OF TERNS
The following glossary lists and defines the statistical terms as used
in this document.
Accuracy
Bias
Lot
Measurement method
Measurement process
Population
Precision
Quality audit
Quality control
L neck
Sample
A measure of the error of a process expressed as a
comparison between the average of the measured values
and the true or accepted value. It is a function of
precision and bias.
The systematic or nonrandora component of measurement
error.
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 measure-
ments, real or conceptual, that is under considera-
tion.
The degree of variation among successive, independent
measurements (e.g., on a homogeneous material) under
controlled 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 crew on certain items of
equipment and procedures to assure data of good
quality.
Objects drawn, usually at random, from the lot for
checking or auditing purposes.
106
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TECHNICAL xilPOnT DATA
IPn :',.' if -J l:*zr... ' ." - ".'. ; . r, -'••• :•< /."•' n''1 rl.li'irl
i
j
7
9
•'-- -V ,1 i \ J J. 3 P.LC1
EPA-650/4-74-005f
*ni_r. A\I.-' '. ^ MO T_t s FIEPO
fiiiirlpl "inpr for PlpvplnnrnpiTr of a Duality A^^uranrp i™uv
Program - Determination of Nitrogen Oxide Emissions 6' PfcRF
from Stationary Sources.
AUTHOPi ji B. PEPF
J. W. Buchanan, D. E. Wagoner
PCHFOrf,;ir,3 OP " ANIZATI O\ \A\lt AND ^ODPi.SS 10. PRC
Research Triangle Institute 1HA
P.O. Box 12194 11 CON
Research Triangle Park, North Carolina 27709 62-
12 Sf'ONSOni\G AGt.NCY NAX'l AND ADPrtESS 13. TYP
flffirp nf RpQPayrh anrl Dpupl nnmpnt
U.S. Environmental Protection Agency :4 SPO
Washington, D. C. 20460
•it N r ;; ACCLSSIOV NO.
RT DATE
ember
GI1MING ORGANIZATION COOt
ORMING ORGANIZATION hLHOHT NO
GRAM fcLfcMENT NO.
327
TRACT/GRANT NO.
02-1234
t" OF REPORT AND P F R i O O •_ "> V L P. ^ 'J
NSOR1NG AGENCY CODE
15 frOf PLEMFNTAFiY NOTES
16. ABSTRACT
Guidelines for the quality control of stack gas analysis for nitrogen oxides,
except nitrous oxide, emissions by the Federal reference methods 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 .
IV KC Y UGRO3 AND DPCU '. II V T A N f> L YS , E
ot£CR.rroHr> b.iDEMificns OPE. vi ENDF.
Quality assurance
Quality control
Air pollution
Gas sampling
Stack gases
Unlimitpfl llncla^-jfiprl
20 iCCURI VV tLAL.", , . (in;;
Unclassified
D TERMS ^. COSATI 1 n Id i ,r. 1.1,1
13H
14D
13B
14B
21B
113
Js'iV 22. PRICL
107
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