EPA-R4-73-028B
JUNE 1973
Environmental Monitoring Series
GUIDELINES FOR DEVELOPMENT
OF A QUALITY ASSURANCE PROGRAM
Reference Method for the Determination
of Suspended Participates in the Atmosphere
(High Volume Method)
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Office of Research ond Development
U.S. Environmental Protection Agency
Washington, DC 20460
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EPA-R4-73-028B
GUIDELINES FOR DEVELOPMENT
OF A QUALITY ASSURANCE PROGRAM
Reference Method for the Determination
of Suspended Participates in the Atmosphere
(High Volume Method)
by
Franklin Smith and A. Carl Nelson, Jr.
Research Triangle Institute
Research Triangle Park, North Carolina 27709
Contract No. 68-02-0598
Program Element No. 1H1327
EPA Project Officer: Dr. Joseph F. Walling
Quality Assurance and Environmental Monitoring Laboratory
National Environmental Research Center
Research Triangle Park, North Carolina 27711
Prepared for
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
WASHINGTON, D.C. 20460
June 1973
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This report has been reviewed by the Environmental Protection Agency
and approved for publication. Approval does not signify that the
contents .necessarily reflect the views and policies of the Agency,
nor does mention of trade names or commercial products constitute
endorsement or recommendation for use.
ii
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PREFACE
. i
• Quality control is an integral part of any viable
environmental monitoring activity. The primary goals of
EPA's quality control program are to improve and document
the credibility of environmental measurements. To
achieve these goals, quality control is needed in nearly
all segments of monitoring activities and should cover
personnel, methods selection, equipment, and data
handling procedures. The quality control program will
consist of four major activities:
• Development and issuance of procedures
• Intra-laboratory quality control
• Inter-laboratory quality control
• Monitoring program evaluation and
certification
All these activities are essential to a successful quality
control program and will be planned and carried out
simultaneously.
Accordingly, this second manual of a series of five has
been prepared for the quality control of ambient air
measurements. These guidelines for the quality control
lii
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of suspended participate measurements in the atmosphere
have been produced under the direction of the Quality Control
Branch of the Quality Assurance and Environmental Monitoring
Laboratory of NERC-RTP. The purpose of this document is to
provide uniform guidance to all EPA monitoring activities in
the collection, analysis, interpretation, presentation, and
validation of quantitative data. In accordance with
administrative directives to implement an Agency-wide
quality control program, all EPA monitoring activities
are requested to use these guidelines to establish intra-
laboratory quality assurance programs in the conduct of
all ambient air measurements for suspended particulates. Your
comments on the utility of these guidelines, along with
documented requests for revision(s), are welcomed.
All questions concerning the use of this manual and
other matters related to quality control of air pollution
measurements should be directed to:
Mr. Seymour Hochheiser, Chief
Quality Control.Branch
Quality Assurance and Environmental
Monitoring Laboratory
National Environmental Research Center
Research Triangle Park, North Carolina 27711
iv
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Information on the quality control of other
environmental media and categorical measurements can be
obtained by contacting the following person(s):
Water
Mr. Dwight Ballinger, Director
Analytical Quality Control Laboratory
National Environmental Research Center
Cincinnati, Ohio 45268
Pesticides
Dr. Henry Enos, Chief
Chemistry Branch
Primate and Pesticide Effects Laboratory
Environmental Protection Agency
Perrine, Florida 33157
Radiation
Mr. Arthur Jarvis, Chief
Office of Quality Assurance-Radiation
National Environmental Research Center
Las Vegas, Nevada 89114
During the months ahead, a series of manuals will
be issued which describe guidelines to be followed during
the course of sampling, analysis, and data handling. The
use of these prescribed guidelines will provide a uniform
approach in the various monitoring programs which allows
the evaluation of the validity of data produced. The
implementation of a total and meaningful quality control
program cannot succeed without the full support of all
monitoring programs. Your cooperation is appreciated.
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TABLE OF CONTENTS
Section Page
1.0 INTRODUCTION 1
PART I. OPERATIONS MANUAL 3
2.0 GENERAL 3
2.1 Operating Procedures 6
FILTER SELECTION AND PREPARATION 6
SAMPLE COLLECTION 8
SAMPLE ANALYSIS 22
DATA PROCESSING 23
2.2 Flow Rate Calibration 24
2.3 Relative Humidity Indicator Calibration 34
2.4 Analytical Balance Calibration 34
2.5 Elapsed Time Indicator Check 34
2.6 Special Checks for Auditing Purposes 35
2.7 Special Checks to Detect and Identify Trouble 40
2.8 Maintenance 43
2.9 Facility and Apparatus Requirements 44
PART II. SUPERVISION MANUAL 49
3.0 GENERAL , 49
3.1 Assessment of High Volume Data 51
3.1.1 Assessment by Auditing Individual Variables 51
3.1.2 Assessment by Auditing With a Mobile Sampler 60
vi
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TABLE OF CONTENTS (Concl'd)
Section Page
3.2 Suggested Standards for Judging Performance
Using Audit Data 61
3.2.1 Suggested Performance Standards for Variables 61
3.2.2 Suggested Standards for Comparing With Mobile
Sampler 61
3.3 Collection of Information to Detect and Identify
Trouble 63
3.3.1 Identification of Important Variables 63
3.3.2 How to Monitor Important Variables 72
3.3.3 Suggested Control Limits 72
3.4 Procedures for Improving Data Quality 74
3.5 Procedures for Changing the Auditing Level to Give
the Desired Level of Confidence in the Reported Data 77
3.6 Monitoring Strategies and Cost 78
PART III. MANAGEMENT MANUAL 81
4.0 GENERAL 81
4.1 Data Quality Assessment 82
4.2 Auditing Schemes 89
4.3 Data Quality Versus Cost of Implementing Actions 103
4.4 Data Presentation 109
4.5 Personnel Requirements 111
4.6 Operator Proficiency Evaluation Procedures 112
REFERENCES . 115
APPENDIX A: REFERENCE METHOD FOR THE DETERMINATION OF
SUSPENDED PARTICULATES IN THE ATMOSPHERE
(HIGH VOLUME METHOD) A-l
vii
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LIST OF FIGURES
Figure Page
1 Sequence of Operations Required in the High Volume Method 4-5
2 Servicing Position of High Volume Sampler 9
3 Operating Position of High Volume Sampler 9
4 Examples of Nonuniform Border Resulting from
Poorly Aligned Filters 10
5 Flow-rate Recorder with Chart Installed 13
6 Example of Smudged Borders Resulting from Improperly
Folded Filters 17
7 Examples of Air Leaks Around the Filter Due to a
Worn Faceplate Gasket 18
8 Properly Prepared Filter Folder and Accompanying
Filter Mat with Recorder Chart 21
9 Typical Field Calibration Setup for Modified
High Volume Sampler 27
10 Percent Change in Flow Rate Versus Temperature
Variations (Orifice Calibration Unit) 29
11 Sample Calibration Sheet 31
12 Flow Chart of Quality Control Checks in the Auditing Program 52
13 Data Qualification Form 59
14 Particulate Concentration and Flow Rate as Functions of Time 71
15 Symmetrical Diurnal Concentration Pattern 71
16 Critical Values of Ratio s./a. Vs n 86
17 Data Flow Diagram for Auditing Scheme 92
18A Probability of d Defectives in the Sample if
the Lot (N = 100) Contains D% Defectives 93
18B Probability of d Defectives in the Sample if the
Lot (N = 50) Contains d% Defectives 94
viii
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LIST OF FIGURES (Concl'd)
Figure Page
19A Percentage of Good Measurements Vs. Sample Size
for No Defectives and Indicated Confidence Level 96
19B Percentage of Good Measurements Vs. Sample Size
for 1 Defective Observed and Indicated Confidence Level 97
20 Average Cost Vs. Audit Level 104
2 2
21 Added Costs Vs. WcC + T for Alternative Strategies 108
22 Sample QC Chart for Evaluating Operator Proficiency 113
ix
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LIST OF TABLES
Table Page
1 Sampling Site Evaluation Data 41
2 Apparatus Used in the High Volume Method 47
3 Suggested Performance Standards . 62
4 Methods of Monitoring Variables 73
5 Suggested Control Limits for Parameters and Variables 74
6 Quality Control Procedures or Actions 75
7 Critical Values of s /a 85
8 P(d defectives) 91
9 Required Auditing Levels n for Lot Size
N = 100 Assumming Zero Defectives 95
10 Costs vs. Data Quality 98
11A Costs If 0 Defectives are Observed and the
Lot is Rejected 99
11B Costs If 0 Defectives are Observed and the
Lot is Accepted 99
12 Costs in Dollars 100
13 Overall Average Costs for One Acceptance -
Rejection Scheme 102
14 Assummed Standard Deviations and Biases
for Alternative Strategies 107
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ABSTRACT
Guidelines for the quality control of total suspended particulate
measurements by the Federal reference method are presented. These
include:
1. Good operating practices
2. Directions on how to assess data and qualify data
3. Directions on how to identify trouble and improve data quality
4. Directions to permit design of auditing activities
5. Procedures which can be used to select action options and
relate them to costs
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
68-02-0598 by Research Triangle Institute under the sponsorship of
the Environmental Protection Agency. Work was completed as of May 1973.
xi
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1.0 INTRODUCTION
This document presents guidelines for implementing a quality
assurance program for measuring the mass concentration of suspended
particulates using the High Volume Method.
The objectives of this quality assurance program for the High Volume
Method of measuring suspended particulates are to:
1) provide routine indication, for operating purposes,
of unsatisfactory performance of personnel and/or
equipment.
2) provide for prompt detection and correction of
conditions which contribute to the collection of
poor quality data, and
3) collect and supply information necessary to describe
the quality of the data.
To accomplish the above objectives, a quality assurance program must
contain the -following components:
1) routine training'and evaluation of operators,
2) routine monitoring of the variables and
parameters which may have a significant effect on
data quality,
3) development of statements and evidence to qualify
data and detect defects, and
4) action strategies to increase the level of precision
in the reported data and/or to detect instrument
defects or degradation and to correct same.
Implementation of a quality assurance program will result in data
that are more uniform in terms of precision and accuracy. It will enable
each monitoring network to continuously generate data that approach the
highest level of accuracy attainable with the High Volume Method.
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This document is divided into three parts. They are:
Part I, Operations Manual - The Operations Manual sets forth
recommended operating procedures, instructions for performing control
checks designed to give an indication or warning that invalid or poor
quality data are being collected, and instructions for performing certain
special checks for auditing purposes.
Part II, Supervision Manual - The Supervision Manual contains
directions for 1) the assessment of high volume data, 2) collection of
information to detect and/or identify trouble, 3) applying quality control
procedures to improve data quality, and 4) varying the auditing or checking
level to achieve a desired level of confidence in the validity of the
outgoing data. Also, monitoring strategies and costs as discussed in
Part III are summarized in this manual.
Part III, Management Manual - The Management Manual presents
procedures designed to assist the manager in 1) detecting when data
quality is inadequate, 2) assessing overall data quality, 3) determining
the extent of independent auditing to be performed, 4) relating costs of
data quality assurance procedures to a measure of data quality, and
5) selecting from the options available the alternative(s) which will
enable him to meet the data quality goals by the most cost-effective
means. Also, discussions on data presentation and personnel requirements
are included in this manual.
The scope of this document has been purposely limited to that of a
field document. Additional background information is contained in the
final report under, this contract.
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PART I. OPERATIONS MANUAL
2.0 GENERAL
This Operations Manual sets forth recommended operating procedures
for measuring the mass concentration of suspended particulates using the
High Volume Method. 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 checks as prescribed by the
supervisor may be required of the operator on certain occasions.
The sequence of operations to be performed is given in Figure 1.
Two columns are used. The first column numbering 1 through 16 gives the
operating procedures in sequential order as one filter progresses through
the system. Calibration procedures that are performed periodically are
given in the second column. In general, Steps 1 through 7 and 12 through
16 are carried out in the laboratory, and Steps 8 through 11 are performed
at the sampling site. Quality checkpoints in the measurement process for
which appropriate quality control limits are assigned are represented by
blocks enclosed by heavy lines. Other checkpoints involve go/no-go checks
and subjective judgments by the operator with proper guidelines for
decision making spelled out in the procedures. Under normal conditions,
all calibrations are performed in the laboratory. (Additional calibrations
in the field, however, may be advantageous in certain situations.) Instruc-
tions for performing each operation are presented in the same order as they
appear in Figure 1. Calibration procedures follow the operating procedures
and are numbered as in Figure 1.
The accuracy and/or validity of data obtained from this method depends
upon instrument performance and the proficiency with which the operator
performs his various tasks. Deviations from the recommended operational
procedure may result in the collection of invalid data or at least reduce
the quality of the data. The operator should become familiar with the
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FILTER SELECTION AND PREPARATION
1. Select filters meeting
specification of reference
method. Analyze for surface
alkalinity.
2. Visual inspection of filters
for pinholes and other imper-
fections.
3. Permanently mark each filter
with a serial number.
4. Equilibrate filter in condi-
tioning environment 24 hours.
5. Check balance and weigh filter
to the nearest mg.
6. Record filter serial number
and tare weight in laboratory
log book.
7. Package filter for shipping
or storage.
WEIGH
FILTER
CALIBRATE/CHECK
CONDITIONING
ENVIRONMENT
CALIBRATE
ANALYTICAL
BALANCE
1. Check desiccant
or calibrate
hygrometer
2. Calibrate analytical
balance
Figure 1: Sequence of Operations Required in the High Volume Method
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SAMPLE COLLECTION
8. Installation of a clean filter
in the sampler.
9. Prepare sampler for operation
and make flow-rate measurements
and determine starting time.
10. Remove sample from sampler
and package for transport.
11. Record measurements and remarks
on filter folder.
SAMPLE ANALYSIS
12. Place sample in the conditioning
environment for 24 hours.
13. Check balance and weigh the
exposed filter to the nearest
mg.
DATA PROCESSING
14. Record sample weight and verify
. adequacy of previously recorded
data.
15. Perform necessary calculations
to get concentration in ug/m .
16. Record data in laboratory log
book and fill in the SAROAO fora
for reporting the data.
CALIBRATE
FLOWRATE
CALIBRATE
ELAPSED TIME
INDICATOR
3. Calibration of
sampler.
4. Calibration of
elapsed time
Indicator.
Figure 1: Sequence of Operations Required in the High Volume Method (Cont'd)
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manufacturer's operational Instructions and with the rules and regulations
concerning the High Volume Method as written in the Federal Register,
Vol. 36, No. 84, Part II, April 30, 1971 (see Appendix A of this document).
The operator is responsible for maintaining certain records.
Specifically log books must be maintained in the laboratory for recording
(1) filter processing data (i.e., tare weight, serial number, sampling
station, etc.), (2) calibration data (past calibration data and future
calibration schedules), and (3) maintenance information including a
historical record and future schedule. A site log book is maintained by
the operator and kept in the sampler shelter. This log book has the most
recent calibration data and schedules for future maintenance and cali-
brations. Initial and final flow rates are recorded in the log book for
each sampling period.
All directions are written for a nonautomated system. If an
automatic data management system is used, certain of these operations
will be performed automatically.
2.1 Operating Procedures
FILTER SELECTION AND PREPARATION
Step 1. Selection of Filter Media
A. Filter Collection Efficiency
Only filters having a collection efficiency of at least 99 percent
for particles of 0.3 ym diameter, as measured by the DOP test, should be
used. The manufacturer should be required to furnish proof of the
collection efficiency of a batch of new filters when purchased.
B. Filter Surface Alkalinity
It is recommended that only filters with a surface alkalinity between
6.5 and 7.5 on the pH scale be used. Surface alkalinity for a new batch
of filters can be determined by performing the analysis as described in A
of Section 2.6..
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Step 2. Visual Inspection of Filter
Each filter must be visually inspected with the aid of a light
table. Look for pinholes, loose particles and other defects such as
tears, creases or lumps. Remove loose particles with a soft brush.
Filters with other imperfections should be destroyed.
Step 3. Filter Identification
Assign a serial number to each filter. Stamp this number on
two diagonally opposite corners on opposite sides of the filter using a
numbering device. Apply gentle pressure to avoid damaging the filter.
Step 4. F i 11 er E quilib rat ion
Equilibrate the filter in the conditioning environment (see
Section 2.9 for a description of conditioning chamber and environment)
for 24 hours prior to weighing. This is necessary to avoid a significant
error in measuring the weight of the filter.
Step 5. Filter Weighing
* i.,i ,i— ...—...—— -M . .,..*iT.i ...i .W
Clean filters are usually processed in lots, that is, several at
one time. Before weighing the first filter, perform a balance check by
weighing a standard weight of between 3 and 5 grains.
Record the actual and measured weights in the laboratory log book
along with the date and operator's initials.
If the actual and measured values differ by more than + .5 mg (O.OOOSg),
report it to the supervisor before proceeding.
If the actual and measured values agree to within +_ .5 mg, proceed to
weigh each filter to the nearest mg. Clean filters must not be folded for
weighing. A special balance pan is required to accommodate 20.3 by 25.4 cm
filters.
Step 6. Documentation
Record the tare weight and serial number of each filter in the
laboratory log book.
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Step 7. Filter Handling
Place the weighed filters in a folder or suitable container to
protect them from damage before use. Filters must not be folded or
creased prior to use.
Supply weighed filters, filter folders, glassine envelopes and
suitable mailing envelopes to each sampling station operator as required.
SAMPLE COLLECTION
Step 8. Installation of Clean Filter
To facilitate filter installation, place the sampler in the
servicing position as illustrated in Figure 2 (Figure 3 shows the normal
operating position). Place the sampler in the servicing position by
raising the sampler until the filter holder is above the top level of the
shelter; then rotate the unit one-eighth turn so that the motor assembly
hangs from the top of the filter holder. During inclement weather
(i.e., rain, snow, sleet, or high winds), it is suggested that the sampler
be removed completely to a protected area. Extreme care should be exer-
cised to prevent damage to the clean filter during this operation.
Remove the faceplate by loosening the four wing nuts and rotating the
bolts outward. Place the filter, rough side up, on the wire screen. Center
the filter on the screen so that when the faceplate is in position, the
gasket will form an airtight seal on the outer edge (1/2 inch) of the
filter. When aligned correctly, the edges of the filter should be parallel
both to the edges of the screen behind it and to the faceplate gasket
above it. The results of poorly aligned.filters are shown in Figure 4.
Note1 the uneven white border around the filter. Results of a correctly
aligned filter can be seen in Figure 8 on page 21.
Once the filter is aligned and the faceplate is in place, the four
wing nuts are tightened so that the gasket is airtight against the filter.
Tighten diagonally opposite wing nuts first to prevent distortion of the
cast iron frame, and to give a more even tightening of the wing nuts.
8
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,:.«**
i .• , . .•,
'•.;•. ' .
Figure 2; Servicing Position of High Volume Sampler
. m
Figure 3: Operating Position of High Volume Sampler
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Figure 4 '• Examples of Nonunifora Border Resulting from
Poorly Aligned Filters
10
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Excessive tightening of the wing nuts should be avoided to help minimize
the tendency of the filter to stick to the gasket and to guard against
permanent damage to the gasket itself.
The entire motor assembly (sampler) is rotated and lowered to its
normal operating position as shown in Figure 3.
Also, while the sampler is removed from the shelter or before the new
filter is installed, the inside surfaces of the shelter lid and area
around the filter holder should be cleaned of loose particles by wiping
with a clean rag.
Step 9. Operational Checks
A. Flow-Rate Measurements
1. Sampler Equipped With Rotaineter
Make flow-rate measurements while the sampler is at normal
operating temperature. This requires a warmup time of at least 5 minutes
before a valid measurement can be obtained.
Connect the rotameter to the sampler, using the same tubing as was
used to calibrate, and place or hold in a vertical position at eye level.
Read the widest part of the float. Use the calibration chart to convert
3
the reading to .cubic meters per minute rounded to the nearest 0.03 m /min
(see Section 2.2 for use of calibration chart).
Flow rates are measured at the beginning and end of a sampling
period. Additional measurements at different times during the sampling
period may be required in special instances.
Precautions to be taken when making flow-rate measurements include:
a) After connecting the rotameter to the sampler, observe
for at least one minute before taking a reading. If a
gradual change in flow rate is observed do not take a
reading until an equilibrium is reached. A gradual
change will usually be observed when the rotameter is
at a substantially different temperature from the
sampler exhaust air and may require 2 to 3 minutes
to equilibrate.
11
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b) If a clock switch is used to start and stop the
sampler at preset times, in order to minimize
errors due to weather changes or changes in the
collected particulates, it may be necessary to
make flow-rate measurements within 30 minutes of
the actual start and stop times.
2. Sampler Equipped With Continuous Flow Recorders
Prepare the recorder for operation as follows:
a) Record on the backside of the new chart the filter
number, station and sampler numbers, start time,
and date of start time.
b) Remove any moisture from inside the recorder case
by wiping with clean cloth. Carefully insert the
new chart into the recorder, being careful not to
bend the pen arm beyond its limits of travel. An
easy way to do this is to push in on the extreme
top of the pen arm with the right hand to raise the
pen head while inserting the chart with the left
hand. A properly installed chart is shown in
Figure 5. Be careful not to damage or weaken the
center tab on the chart and make certain that the
tab is centered on the slotted drive so that the
chart will rotate the full 360 degrees in 24 hours
with no binding or slippage.
c) Check to see that the pen head rests on zero (i.e.,
the smallest diameter circle on the chart). If it
does not, tap the recorder lightly to make certain
the pen arm is free; if it still does not read
zero, adjust to zero with the adjustment screw
(follow manufacturer's direction for specific
recorder).
12
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Figure 5: Flow-rate Recorder with Chart Installed
13
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d) Check the time indicated by the pen. If it is in
error, rotate the chart in a clockwise direction,
by inserting a screwdriver or coin into the
slotted drive in the center of the chart face,
until the correct time is indicated. Remember that
if the sampler is started with a clock switch, the
correct time for the recorder chart is the starting
time on the clock switch.
e) With an eyedropper put a small amount of ink into the
hole in back of the pen tip.
f) Turn on sampler (never turn on the sampler unless a
filter is in place or the transducer and recorder may
be damaged) and observe long enough to determine
whether the transducer and recorder are operating
properly.
g) Turn off sampler and set the clock switch for correct
start and stop times.
3. Routine Flow-Rate Checks
Record the initial and final flow-rate readings for each sample in
the log book maintained in the sampler.
After each calibration, average the first four initial flow-rate
measurements. Future initial flow rates deviating more than + 10 percent
/from this average should be investigated. If the change has been gradual
' •
over a period of time a calibration is required.
When large deviations occur between successive samples, the operator
should wait 5 minutes and make an additional reading. If the second
reading falls within + 10 percent of the average, continue normal operatipn.
If the second reading falls out of bounds, 1) check the line voltage, and/or
2) replace the filter. A calibration check is made if neither of the above
checks identifies the trouble (see Section 2.6 for instructions on perform-
ing calibration check). Continue normal operations if the calibration
check is satisfactory, and perform a complete calibration if the check is
unsatisfactory (see Section 2.2 for calibration procedures). Samplers
j. equipped with a continuous recorder should be observed for at least 5 minutes
'<\ before recording the initial flow rate.
14
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The same procedure is used for final flow-rate measurements except
that a larger range, say + 20 percent of the average, should be used.
Valid limits can be determined for each sampling site as data are avail-
able. A final flow rate deviating from the average by more than 20 percent
may result from short-term inversions and humidity fluctuations. The
occurrence of such conditions is noted on the data sheet for that sample.
33
rlf a final flow rate less than 0.57 m /min (20 ft /min) is observed, the
sample is voided because at this low air flow the motor heats up and a
valid flow-rate measurement cannot be obtained.
B. Time Measurements
Sampling period start and stop times, for samplers not equipped with
a clock switch or elapsed time meter, are determined by the operator who
starts the sampler and the operator who stops the sampler respectively.
If different operators are involved, they set their watches to a common
reference in order to arrive at an accurate sampling period time. Such
a reference could be an office clock which is checked daily or the local
telephone company giving time-of-day service.
Start and stop times for samplers equipped with a clock switch are
taken from the clock settings. The clock is checked, and set if
necessary, for the correct time at each filter change. These clocks
cannot be set or read to less than + 15 minutes and, therefore, must
be accompanied by an elapsed time indicator accurate to at least + 4
minutes for a 24-hour period to satisfy the reference method specifications,
The elapsed time is recorded on the filter folder along with the start and
stop times.
For samplers equipped with neither an elapsed time indicator nor a
continuous flow-rate recorder, the local power company should be contacted
to see if the power has been off anytime during the sampling period. If
so, the length of time that the power was off and the source of the infor-
mation are recorded on the filter folder on the line for remarks.
A
Samples should be voided when the sampling period is less than
|23 hours or greater than 25 hours.
15
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Step 10. Sample Handling
A. Removing Exposed Filter
Place the sampler in the servicing position (see Figure 2). Remove
the faceplate and remove the exposed filter from the supporting screen by
grasping it gently at the ends (not at the corners) and lifting it from
the screen. Fold the filter lengthwise at the middle, with the exposed
side in. If the collected sample is not centered on the filter (i.e., the
unexposed border is not uniform around the filter) fold the filter
accordingly so that sample touches sample only. Results of an improperly
folded filter are illustrated in Figure 6, the smudge marks can be seen
extending across the right-hand border. This renders the sample useless
for certain analyses where the collected sample has to be subdivided into
equal portions.
Place the filter in a filter folder and glassine envelope and then
in a mailing envelope if the sample is to be mailed to the laboratory.
For samplers equipped with a flow-rate recorder, the associated
recorder chart is removed (see instructions for installing chart, Section 2b
of Step 9), the stop time is recorded on the backside, and the chart is
placed inside the filter folder with the inked side against the filter
folder and the back (clear) side against the filter. This prevents ink
from getting on the filter and interfering with future chemical analyses.
B. Routine Checks
The following checks should be made when removing an exposed filter.
1) Check the filter for signs of air leakage. Leakage may
result from a) a worn faceplate gasket as illustrated
in Figure 7, b) an improperly installed gasket as
illustrated in Figure 4, or c) over-tightening of the
faceplate gasket, cutting the filter along the gasket
interface.
16
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Figure 6: Example of Smudged Borders Resulting from
Improperly Folded Filters, Leaking Gasket
and Poor Alignment
17
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Figure 7: Examples of Air Leaks Around the Filter Due
to a Worn Faceplate Gasket or Improper
Installation
18
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If at any time a leakage is observed, void the
sample and take corrective action before starting
another sampling period. Corrective action would
be to replace the gasket, take more care in install-
ing the filter, or applying more caution in
tightening the gasket according to the cause of the
leakage. Generally a gasket deteriorates slowly and
the operator can tell well in advance, by an
increasing fuzziness of the sample outline, to change
the gasket before a total failure results.
2) Visually inspect the gasket face to see if glass
fibers from the filter are being left behind. This
is a sign of over-tightening the gasket. Tighten
the gasket just enough to prevent leakage.
3) The operator should check the exposed filter for
physical damage that may have occurred during sampling
or after sampling. Physical damage to the filter
after the sample has been collected does not always
invalidate the sample. For example, accidentally
tearing a corner off while removing the filter does
not invalidate the sample if all pieces of the filter
are included in the folder. However, any loss of
sample due to leakages during the sampling period or
to the loss of loose particulates from the filter after
sampling (e.g., loss of particulates when folding the
filter) invalidates the sample. The operator should
mark 'all such samples void and forward them to the
laboratory. Bugs such as gnats loosely attached to
the filter should be removed by hand or with teflon-
tipped tweezers. If they are embedded in the
particulates note this on the folder and do not try
to remove them.
19
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4) The appearance of the particulates should be checked.
Any changes from the normal color, for example, may
indicate new emission sources or construction activity
in the area, etc. The change should be noted on the
filter folder along with any obvious reasons, if there
are any, for the change.
Step 11. Document at ion
In most instances the filter folder is the only immediate contact
between the field operator and the laboratory personnel. Therefore, the
field operator(s) must include on this folder all the information necessary
for the analysis of the filter as well as information on any conditions or
circumstances that might invalidate the sample or cause it to deviate from
the normal. Figure 8 shows an exposed filter, filter folder with recorded
data, and the recorder chart. The following information must be recorded
on the folder by the indicated individuals. In some cases a separate data
sheet is used for recording the data allowing the filter folder to be
reused several times.
A. Operator Who Starts the Sampler
1. Filter number
2. Station number
3. Sampler number
4. Starting time
5. Initial flow rate (if using rotameter)
6. Date and initials
7. Summary of any unusual conditions that may
affect results (e.g., subjective evaluation
of the pollution that day, construction
activity, meteorology, etc.)
B. Operator Who Removes Sample
1. Stop time, and if available, elapsed time.
2. Final flow rate (or flow-rate chart must
accompany the sample)
3. Date and initials
4. Summary of existing conditions that may affect
results (see A7 above, and 3 and 4 of Step 10)
20
-------
Figure 8: Properly Prepared Filter Folder and
Accompanying Filter Mat with Recorder
Chart
21
-------
C. Person Who Transfers Sample to Laboratory (if not
done by person who takes sample)
1. Receiving date and initials
2. Shipping date and initials
SAMPLE ANALYSIS
Step 12. Sample Equilibration
The exposed filter is placed in the conditioning environment for
24 hours (see Section 2.9 for a description of conditioning chamber and
environment). The 24-hour equilibration period should be adhered to (e.g.,
20 to 28 hours) for uniformity of results. Many samples show a continued
weight loss for several days, thus, unequal conditioning periods induce
errors when data from different tests are compared.
If the conditioning environment is an air-conditioned room where
filter preparation, weiphing, and conditioning activities are performed,
a hygrometer should be maintained out of the air-conditioning draft but
in a location which receives good circulation. The relative humidity
must be checked daily when exposed filters are being conditioned. Any
relative humidity less than 50 percent and constant to within + 5 percent
is satisfactory. Temperature should be maintained to + 3°C at any level
comfortable to the persons working in the room. It is important that
relative humidity and temperature be the same for sample equilibration
and filter equilibration (Step 4). Thus, they both should be done at
the same facility or at facilities maintained at the same conditions.
If the conditioning environment is a desiccating chamber, a
desiccating agent such as indicating activated alumina should be used.
The desiccant should be checked daily and replaced when necessary as
indicated by a color change in the desiccant.
Care should be exercised when placing filters in the desiccator or
contitioning environment to make sure that the filter does not come in
contact with loose dirt particles or the desiccant which might adhere to
the filter and be weighed. Also, the filter should not be placed in a
position such that some of the sample might fall or be knocked loose.
22
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Also, when removing the exposed filter from the mailing envelope or
glassine envelope, check to see if any of the collected particulates have
come loose and are in the envelope. Recover as much of the particulates
as possible using a small camels' hair brush to brush out the envelope.
Gnats and/or other bugs embedded in the particulates are removed with
teflon-tipped tweesers, being careful not to displace any more of the
particulate matter than necessary. If the number is excessive, greater
than 10, report it to the supervisor for a decision on whether to accept
or reject the sample.
Step 13. Gravimetric Analysis
Perform a balance check as specified in Step 5. Weigh exposed
filters to the nearest milligram on the analytical balance. Record filter
weights in the laboratory log book.
The weighing area should be in the conditioning environment if
possible, otherwise the analytical balances should be as close as possible
to the conditioning chamber in an area that is relatively free of air
currents and maintained at the same temperature as the chamber. The
filter must be weighed immediately, certainly no more than 5 minutes,
after removal from the conditioning environment.
DATA PROCESSING
Step 14. Documentation and Sample Verification
The exposed filter weight is recorded in the laboratory log
book and on the filter folder.
At this point all documentation is checked and compared for
completeness and accuracy. The filter number on the filter, filter folder,
and flow-rate chart (if included) should be the same and match the one in
the laboratory log book. All data necessary for computing the concen-
tration must be recorded on the filter folder as well as information on
sampling date and location. The sample is voided if the filter numbers
don't match or if any of the other pertinent data are missing.
23
-------
The exposed filter is also inspected once again for signs of air
leakage or physical damage to the filter that the operator may have
overlooked but that could still invalidate the sample. Also, flow-rate
values, environmental conditions, and operator remarks should be checked
before the sample is declared valid.
Step 15. Calculations
Calculate the volume of air sampled and the mass concentration
of suspended particulates as instructed in Sections 9.2 and 9.3 of
Appendix A, respectively. Note that the equation for volume of air
sampled in 9.2.2 of Appendix A is in error. It should be
Qi + Qf
V = -^~ — - x T.
For samplers equipped with a flow-rate recorder the calculations are
performed as described in Addenda A of Appendix A.
Step 16. Document and Report Data
Daily concentration levels with required identifying information
are recorded in micrograms per cubic meter on the SAROAD Daily Data Form.
See Users Manual: SAROAD (Storage and Retrieval of Aerometric Data) ,
APTD-0663, for detailed instructions for accomplishing this. The original
calculations should be filed in the laboratory log book.
2.2 Flow Rate Calibration
A. Calibration of Orifice Unit
The orifice calibration unit with different resistance plates, as shown
in Figure B3 of Appendix A, is the specified unit for calibrating the
flow rate of both rotameter and flow- rate recorder equipped samplers.
However, this orifice calibration unit itself must first be calibrated
against a positive displacement primary standard.
-------
Directions for calibrating the orifice calibration unit against the
primary-standard are given in Section 8.1.1 of Appendix A.
The orifice calibration unit should remain virtually unchanged over
a period of several years under normal use. Its calibration against a
standard serves primarily as a check for changes due to some form of
physical damage. '
The orifice calibration unit should be calibrated with a primary
standard when it is first purchased. A deviation of more than + 4 percent
at any point from the average calibration curve furnished by the manu-
facturer probably means that the orifice has been damaged in shipment and
should not be accepted (Ref. 1).
Orifice units in use should be visually inspected for visible signs
of damage to the orifice before each use. A calibration check should be
made anytime the unit, especially the orifice itself, appears to have any
nicks or dents.
Calibration checks against a primary standard should be made once a
year for all orifice units. The manufacturer's average calibration curve
should continue to be used unless the new calibration deviates from it by
more than + 4 percent at any one point along the curve. When deviations
from the manufacturer's average calibration curve are larger than
+ 4 percent and there are no visible signs of damage to the orifice, the
calibration should be repeated by another operator. If the large
deviations persist (after the primary standard has been checked and
found satisfactory) a new average calibration curve is constructed using
the results from at least five sets of calibration data.
B. Sampler Calibration
Samplers must be calibrated when first purchased, after major
maintenance on the sampler (e.g., replacement of motor or motor brushes),
any time the flow-rate measuring device (i.e., rotameter or recorder) has
to be replaced or repaired, or any time a one-point calibration check
(see Section 2.6 for a description of this check) deviates more than
+_ 6 percent from the calibration curve.
25
-------
It is expected.that samplers will have to be returned to the laboratory
for routine maintenance and calibration after 25 to 30 operating days. This
is based on the average brush life of a sampler operating on 100 volts.
Samplers operating on line voltage (120 volts) will require brush replace-
ment and thus calibration more often.
Calibrations performed in the laboratory must be corrected or repeated
on site for samplers operating at stations where ambient barometric pressure
or temperature is significantly different from those in the laboratory.
The orifice calibration unit with a set of resistance plates is used
to calibrate either or both the rotameter and recorder equipped high
volume samplers in the field or in the laboratory.
Figure 9 shows the apparatus required for the calibration of a high
volume sampler in the field. The apparatus was arranged in this manner
for illustration purposes only. In actual practice it is recommended that
the sampler and recorder be left in the shelter while calibrating. Speci-
fically, care should be taken not to restrict the air flow into the orifice
unit or out of the motor unit. The calibration setup for the rotameter
equipped sampler is exactly the same with the exception that a rotameter
replaces the flow rate recorder in Figure 9.
In using the orifice calibration unit to calibrate a sampler,
corrections must be made to the indicated flow rate if the ambient baro-
metric pressure or temperature is substantially different from the
pressure or temperature values recorded when the orifice unit was
calibrated. Calculate the corrected flow rate as follows:
[T P 11/2
'21
where
'llT.^
Q = corrected flow rate, m /rain;
Q1 = uncorrected flow rate read from the orifice unit
calibration curve for a given pressure in inches
of water;
TI = absolute temperature when orifice unit was
calibrated, °K;
P. = barometric pressure when orifice unit was
calibrated, mmHg;
26
-------
Figure 9: Typical Field Calibration Setup
for Modified High Volume Sampler
27
-------
T- = absolute temperature while calibrating the
sampler, same units as T , and
P» = barometric pressure while calibrating sampler,
same units as P .
For a given pressure (i.e., P = ?„) Figure 10 shows the percentage change
of Q versus temperature differences. If T_ is greater than T.. , the
percentage change is positive; if !„ is less than T , the percentage change
is negative. The same procedure is used to correct for pressure differences,
1. Sampler Equipped with Rotameter
Equipment Setup - The equipment is connected as shown in Figure 9,
with the exception that a rotameter is used instead of the pressure
transducer and recorder.
1) Replace the filter adapter with the orifice calibration
using the resistance plate with 18 holes (seventeen in
a circle and one in the center of the plate) to approxi-
mate the resistance of a clean filter.
2) Connect the rotameter to pressure tap at exhaust end of
high volume motor with a section of tubing (rotameter
just replaces the recorder in Figure 9). This is a
positive pressure, so connection is made at the bottom
of the rotameter. The rotameter and tubing used in
calibration must be used when making flow-rate readings
in the field.
3) Connect the manometer to the orifice calibration unit.
Caution: The orifice unit exerts a negative or vacuum
pressure. The manometer end not connected to the
orifice unit must be open to the atmosphere.
28
-------
sv
H g ,
fa o 3
C
•rl
w
T = 293°K (20°C)
ft-
10
15
20
Figure 10: Percent Change in Flow Rate Versus Temperature
Variations (Orifice Calibration Unit)
29
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Calibration Procedure
1) Plug sampler into 120 volt source, while checking
manometer to insure that the orifice pressure drop
does not exceed the range of the manometer. Let the
sampler run for about 5 minutes.
2) Read the manometer pressure in inches of water,
record on calibration data sheet (Figure 11). Convert
to flow rate using the orifice unit calibration chart
(correct for temperature and pressure using the
equation on page 26 if needed) and record in column 3
of the calibration data sheet.
3) Set the rotameter reading (wide part of float) as near
as possible to the correct flow rate, as determined in 2
above (if the rotameter has arbitrary units, set to the
normal flow rate expected with a clean filter), by
adjusting the brass hexagonal nut at the top of the
rotameter. Once adjusted, tighten the lock nut and
seal to prevent the setting from changing.
4) Record the rotameter reading in Column 4 of the
calibration data sheet.
5) Replace the resistance plate in the orifice unit with
the one with the next fewer number of holes.
6) Turn on the sampler and record on the calibration data
sheet the manometer pressure in inches of water, the
corrected flow rate from the calibration chart, and the
rotameter reading.
7) Repeat Steps 5 and 6 for the remaining resistance plates
getting a total of 5 or 6 different flow rates.
8) On graph paper, plot rotameter readings (Column 4) versus
flow rate in m /min (Column 3).
9) Construct a best-fit, smooth curve to the 5 or 6 points
by eye or by a curve fitting technique such as a least
squares fit.
30
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CALIBRATION DATA SHEET
Orifice Unit No.
Initials
Sampler No.
Date
Indicator No.
(Rotameter/Recorder)
Barometer
mniHg
Temperature
Run
Number
1
Manometer
in. Water
2
Actual
(Corrected)
Flow Rate
m3/min
3
Indicator
Reading
4
Figure 11: Sample Calibration Sheet
31
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10) Recheck any point that deviates more than + 5 percent
from the smooth, best-fit curve. Calculate the
percent deviation by taking the flow rate of the
point in question as Q and the flow rate from the
calibration curve as Q for the same rotameter reading
and compute
Q0 - Q
percent deviation = x 100.
Replot the point as the average of the two values.
2. Sampler Equipped with Transducer and Recorder
Equipment Setup - The equipment is connected as illustrated in
Figure 9 (see page 26 for proper cautions to take in setting up equipment)
1) Replace the filter adapter with the orifice calibration
unit using the 18-hole resistance plate to simulate a
clean filter.
2) Connect one leg of the manometer to the orifice cali-
bration unit and vent the other leg to the atmosphere.
3) Install a clean recorder chart and check the recorder
for proper operation. Zero the pen if necessary
(see 2b of Step 9).
Calibration Procedure
1) Connect the sampler directly to a 120 V source,
bypassing the step-down transformer if it is normally
used. Let the sampler run for about 5 minutes.
2) Read the differential pressure as indicated by the
manometer and record the reading in Column 2 of the
calibration data sheet (Figure 11). Convert to flow
2
rate in m /min using the orifice unit calibration chart
(using the correction for temperature and pressure if
applicable) and record in Column 3.
32
-------
1
3) Adjust the span of the recorder so that the recorder
pen is indicating the correct flow rate (if the
recorder chart is in arbitrary units, set to the
normal flow rate expected with a clean filter).
4) Shut the sampler off. Check zero and reset if necessary.
If it is necessary to make a zero adjustment, then
Steps 2, 3 and 4 are repeated until no span or zero
adjustments are required. Record the recorder chart
deflection in Column 4 of the calibration data sheet.
5) Change the resistance plate now in the orifice calibra-
tion unit to the one with the next fewer number of
holes.
6) Turn on the sampler and convert the differential
pressure as given by the manometer to the corrected
flow rate.
7) Record the manometer pressure in inches of water, the
actual corrected flow rate from the calibration chart
2
in m /min, and the recorder deflection on the calibra-
tion data sheet as shown in Figure 11.
8) Repeat Steps 5, 6 and 7 for the remaining resistance
plates getting a total of five or six different flow
rates.
9) Plot on graph paper the recorder deflection (Column 4)
3
versus flow rate in m /min (Column 3).
10) Construct a best-fit, smooth curve through the 5 or 6
points by eye or by a curve fitting technique such as a
least squares fit.
11) Recheck any point that deviates more than + 5 percent
from the smooth curve. Calculate the percent deviation
by taking the flow rate of the point in question as
Q and the flow rate from the calibration curve as Q
for the same recorder deflection and compute
Q - Q
percent deviation «• ° —- x 100.
33
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2.3 Relative Humidity Indicator Calibration
The relative humidity indicator used for monitoring the conditioning
environment should be checked against a wet-bulb, dry-bulb psychrometer
or equivalent every six months. At least a two-point calibration should
be made by comparing readings made in the conditioning environment and
then.moving the relative humidity indicator outdoors or perhaps just out
of the conditioning room for a second comparison. If the indicator
readings are within + 6 percent of the psychrometer values, continue to
use the relative humidity indicator. If they disagree by more than
+ 6 percent, either have the indicator calibrated or purchase a new one.
2.4 Analytical Balance Calibration
The balance calibration should be verified when the balance is first
purchased, any time the balance has been moved or subjected to rough
handling, or when a standard weight cannot be weighed within +0.5 mg of
its stated weight. Weighing a set of at least 5 standard weights,
covering the weight range normally encountered in weighing filters, can
serve as a verification. If at any time one or more of the standard
weights cannot be measured within +0.5 mg of its stated value, have the
balance recalibrated. The manufacturer should perform the calibration
and subsequent adjustments.
2.5 Elapsed Time Indicator Check
The elapsed time indicator should be checked every six months against
a time piece of known accuracy over a 24-hour period. This could be
accomplished on site or in the laboratory. If the indicator shows any
sign^ of being temperature sensitive, it should be checked on site during
each season of the year.
A gain or loss of more than 4 minutes in a 24-hour period warrants
an adjustment or replacement of the indicator.
34
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2.6 Special Checks for Auditing Purposes
In making special checks for auditing purposes it is important that
all checks be performed without any special preparation or adjustment of
the system (see Section 3.1 for further discussion). It is felt that
when first starting a quality assurance program, seven special checks are
required to properly assess data quality. The necessity of continued
performance of each check can be evaluated as auditing data become
available. A checking or auditing level of 7 checks out of 100 sampling
periods is used here for illustration purposes. The supervisor will
specify the auditing level to be used according to monitoring requirements.
For the case where one sample is collected every sixth day, an
auditing level of 1 check per month is recommended. This would result in
an auditing level of approximately 3 checks (n = 3) for a lot size of
15 (N = 15) for data reported quarterly. Directions for performing each
of the checks are given here. Proper use of the resulting data along with
desirable control limits is given in Section 3.1 of the Supervision Manual.
A. Analysis of Filter Surface Alkalinity
It is recommended that filter surface alkalinity (pH) be audited at
the beginning of a quality assurance program. It is further recommended
that only filters with a pH between 6.5 and 7.5 be used. If auditing
results show that the manufacturer can consistently supply filters that
are within an acceptable pH range, this check may be discontinued. Perform
the check in the following manner.
1) Randomly select 7 filters out of every 100 filters.
2) Remove a small sample (e.g., a 3" x 3" square) from
one filter. Place the sample in a small beaker and
cover with 15 ml deionized water. Bring to a slow
boil for 1 minute. Cool to room temperature. Measure
the pH with a pH meter. If a pH meter is not avail-
able, use fresh indicating litmus paper, such as
Fisher Scientific Short Range Alkacid Test Papers.
35
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3) Record the 7 measured pH values and forward to the
supervisor. This check should be made as part of
Step I in Figure 1. The supervisor will reject
the lot if a pH outside the range of 6.5 to 7.5 is
measured.
B. Weighing Checks
Weighing checks are made as soon as practical before or after the
regular weighing. No more than 30 minutes should elapse between weighings
of exposed filters when the weighing is carried out in the conditioning
environment and even less if the filters are removed from the conditioning
environment. Weighing checks are performed as part of Steps 5 and 13 in
Figure 1, pages 4 and 5.
The check must be independent, i.e., performed by a person other than
the one doing the regular weighings. Treat these as go/no-go checks, i.e.,
if one check exceeds the control limits, reweigh all filters arid use the
check values as the correct ones. If, however, no check exceeds the limits,
the check values are recorded but no changes are made in the original
weights.
Clean Filters - Clean filters are normally weighed in batches. This
allows for the sampling to be performed and corrections to be made before
the filters are used.
1) Divide into lot sizes of 100 or less and weigh.
2) Randomly select and reweigh 7 filters from each
lot of 100.
3) If any one of the 7 check weights differs more than
1.0 mg from the original weight, reweigh all the
filters in that lot.
4) Record both weights in the laboratory log book with
the filter number. Use the weight determined by the
check as the correct one. The lot is accepted with
no changes made if all checks differed from the
original weights by less than 1.0 mg.
36
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Exposed Filters - Due to the necessity of weighing exposed filters
immediately after a 24-hour conditioning period, it may be impossible to
have lot sizes greater than 10 or 20. In order to allow for corrections
to the lot, it is necessary to perform the audit as the filters are
weighed, regardless of the size of the lot.
1) Randomly select and reweigh 4 out of every lot size
of 50 or less (this would mean 100% checking if 4
or less exposed filters are weighed at one time).
If lot sizes of 50 or greater are possible, reweigh
7 from each lot.
2) Reweigh all filters in a lot if any check differs by
more than + 2.7 mg (assuming a = 0.9 mg) from the
original weight.
3) Accept the lot with no change if all checks are within
+2.7 mg of the originals.
4) Record original and check weights in the laboratory
log book.
C. Flow-Rate Check
Flow-rate checks should be independent and random; that is, a person
other than the regular operator makes the check. Also, the regular
operator should not know in advance when the check is to be made. The
check is made in the following manner.
1) As part of the routine operations the regular operator
services the sampler and measures the initial flow
rate, Q , as directed in A of Step 9, page 11.
2) Make an independent measurement within 15 minutes or
less of the operator's measurement. Record the check
value, Q., in the site log book.
i i
3) Make an additional flow-rate measurement, Q within
+ 1 hour of the midpoint of the sampling period.
Record the value in the site log book.
37
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4) Within 15 minutes or less of the regular operator's
final flow-rate measurement, make an independent
check and record the value in the site log book
as Qf.
5) The regular operator makes a final flow-rate measure-
ment, Q,;, and records it in the site log book.
6) Values of Q., Q.', Q', Q,, and Q' are reported to the
i i m t r
supervisor.
D. Calibration Check
Independent calibration checks should be made on site. Portable
calibration equipment as shown in Figure 9, page 27 is used. Perform
calibration checks according to the following procedure.
1) Set up equipment.
2) Select one of the resistance plates and obtain the
actual flow rate, Q , and the rotameter reading,
*— Si
following the calibration procedures given on page
30, Section 2.2.
3) Convert rotameter reading to flow rate, Q , using
the calibration curve and making corrections for
ambient temperature and pressure.
4) Compute
0-0
r a
percent difference = * 100.
a
5) Report the percent difference to the supervisor.
6) If the percent difference is as large as 6, a
complete calibration should be performe.d before
sampling is resumed.
38
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E. Elapsed Time Between Collection and Analysis
Elapsed time between sample collection and analysis .is important in
estimating error due to loss of weight of sample particulates having high
organic matter content.
The recommended minimum auditing level is 7 checks (n=7) out of
every 100 samples (N=100) for networks generating 100 or more samples per
quarter, and n=3, N=15 where sampling occurs every sixth day.
Perform the check by randomly selecting the samples to be checked.
From the data sheet, obtain the end time and date of the sampling period,
and obtain the time and date of the weighing of the exposed filter from
the filter processing data log book.
Determine the elapsed time in days, and subtract 1 for the conditioning
period. Report this value to the supervisor.
F. Data Processing Check
In auditing data processing procedures, it is convenient and allows
for corrections to be made immediately if checks are made soon after the
original calculations have been performed. In particular, this allows for
possible retrieval of additional explanatory data from field personnel
when necessary. For networks generating as many as 100 samples per quarter,
the recommended auditing level of 7 checks (n=7) for a lot size of 100
(N=100) can be followed. Networks consisting of one or two samplers
operating every sixth day, the minimum level of 4 checks (n=4) for all
lot sizes less than 50 (N<50) should be used.
The check must be independent; that is, performed by an individual
other than the one who originally reduced the data. The check is made
starting with the raw data on the data sheet or flow-rate recorder chart
and continuing through recording the concentration in yg/m on the SAROAD
form.
If the mass concentration of suspended particulates computed by the
check, S.P. , differs from the original value, S.P. , by as much as
+ 3 percent, all samples in that lot are checked and corrected. The check
value is always given as the correct value.
Check values are recorded in the data log book and reported to the
supervisor.
39
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2.7 Special Checks to Detect and Identify Trouble
The following checks may be required when: 1) a quality assurance
program is first initiated in order to identify potential problem areas,
and 2) at any later time when it becomes increasingly difficult to meet
the performance standards of the auditing program to identify and evaluate
trouble areas. The required information is primarily a description of the
sampling site ambient environment. Specific areas of required information
are:
1) average concentration of acid gases,
2) average percent of organic matter present in
collected particulates,
3) average particulate concentration,
4) average flow-rate change per 24-hour sampling
period,
5) diurnal pattern of parfciculate matter, and
6) source voltage variation for 24-hour sampling
period.
A. Average Concentration of Acid Gases
This information is not required if the ambient atmosphere is known
to be free of such acid gases as SO- and NQ~.
Values can be derived from previous measurements made on site or in
the general site area. In many cases a good estimate can be made from a
knowledge of the emission sources in the area. The primary requirement
is to know, in general, whether or not there are acid gases in the ambient
atmosphere. An absolute value is not required.
Record the measured/estimated concentration values of S0_ and NO- on
the form for site evaluation data as shown in Table 1.
40
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Table 1: Sampling Site Evaluation Data
Parameter
Value
1. Average Concentration of
Acid Gases
2. Average Percent of Organic
Matter in Particulates
3. Average Suspended Particu-
late Concentration
4. Average Flow-Rate Change
per 24 hours
5. Diurnal Particulate Pattern
6. Source Voltage Variation
per 24 hours
S02(yg/in
% O.M.
S.P.(yg/mJ)
AQ(m3/min)
(present as a graph)
(present as a graph)
B. Organic Matter as a Percent of Total Particulate Matter
An average value for organic content of particulate matter for a
given site can be determined from previous measurements made on site or
in the general area around the.site. In order to obtain valid results, the
collected particulates should be analyzed for organic matter immediately
after the 24-hour conditioning period. The test is usually made in terms
of benzene soluble organics. In some cases an estimate may be adequate
if there is a good knowledge of the emission sources in the area.
Record the measured/estimated percentage on the form for site
evaluation data as shown in Table 1.
C. Average Particulate Concentration
From previous data (e.g., from the previous year's data), obtain an
average concentration level. If no previous data are available, use data
from nearby sites and previous experience to make an estimate. If an
estimate is used in the beginning, average each quarter's data and use that
average until a year's data have been collected. Use the annual mean when
available.
Record the measured/estimated value of particulate concentration on
the form for site evaluation data as shown in Table 1.
41
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D. Average Change in Flow Rate for a 24-Hour Sampling Period
Obtain the initial and final flow rates from at least 20 sampling
periods. Compute
AQ = Q± - Qf
for each period.
Compute the average flow rate change, AQ, by adding all the AQ's
and dividing their sum by the number of AQ's used.
Record AQ on the form for site evaluation data as shown in Table 1.
E. Diurnal Pattern of Particulate Matter
3 3
If AQ from D above was less than 0.30 m /min (-11 ft /min), this
3
information is not needed. For cases where AQ > 0.30 m /min, construct a
graph of suspended particulate concentration versus time for a typical or
average 24-hour sampling period for that site. Relative comparisons of
the lowest and highest values and the approximate times of their occur-
rence during the sampling period are of importance. Data from measurements
made with a tape sampler (e.g., hour or two hour averages), or other
methods giving averages for time periods of 4 hours or less, can be used to
construct the graph. In some areas a reasonable estimate of the diurnal
pattern can be made from a knowledge of the operating'cycle of the local
emission sources.
Construct a graph from the measured/estimated values and attach to
the form for site evaluation data as shown in Table 1.
F. Source Voltage Variation for 24-Hour Sampling Period
For a given sampling site and with the sampler operating, monitor
the source voltage over the 24-hour sampling period. This can be done
with a continuous recording device or an indicating voltmeter read and
recorded every hour. This check should be performed on at least two
different week days.
42
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Plot the source voltage (hourly values) versus time (label and use
strip chart record if used) and attach to the form for site evaluation
data as shown in Table 1.
2.8 Maintenance
The three most frequently required maintenance actions include
replacement of the sampler motor brushes, replacement of the faceplate
gasket, and cleaning of the rotameter.
A. Sampler Motor
Motor brushes usually require replacement after 400 to 500 hours of
operation at normal line voltage (115V). The brushes should be replaced
before they are worn to the point that motor damage can occur. The
optimum replacement interval must be determined from experience.
Manufacturer's instructions should be followed in replacing the brushes.
B. Faceplate Gasket
A worn faceplate gasket is characterized by a gradual blending of the
interface between collected participates and the clean filter border. Any
decrease in the original sharpness of this interface indicates the need
for a new faceplate gasket.
The old gasket can be removed with a knife and the surface properly
cleaned. A new gasket is then sealed to the faceplate with rubber cement
or double-sided adhesive tape.
C. Rotameter
Small particles may become lodged in the air cavity of the rotameter
resulting in erratic behavior of the float. Alcohol is a safe fluid to
use for cleaning the rotameter. The rotameter should be cleaned and
calibrated at any sign of foreign particles or moisture deposits in the
air column or erratic behavior of the float. Also, the rotameter should
be cleaned prior to routine calibration. The rotameter is discarded if
any physical damage such as a crack in the plastic sleeve is observed.
43
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2.9 Facility and Apparatus Requirements
A. Facility
Primary facilities required in High Volume sampling are a central
laboratory and individual sampling stations. The laboratory should be
equipped for filter/sample processing and for calibrations and
maintenance.
1. Filter Conditioning and Weighing Area
Ideally the filter conditioning area would be a room large enough
to accommodate filter processing, equilibration, weighing operations, and
filter library. The room would be equipped with the necessary air
conditioning equipment to maintain a preset temperature and relative
humidity. Also, relative humidity and temperature measurement instruments
are required.
In the event that room is not available, a desiccating chamber, such
as a converted oven, refrigerator, incubator or a commercially manufactured
chamber equipped with trays for holding desiccant and v-shaped racks
approximately 4" high for holding filters may be used. The weighing area
should be located next to the conditioning chamber in an area that is
relatively free of air currents.
In all cases the conditioning environment should be free of acidic or
basic gases that may react with the filter media or the collected parti-
culates during filter/sample conditioning.
2. Calibration Area
To help insure a minimum of calibration error, a permanent
calibration area should be established in the laboratory. The area should
be equipped with an orifice calibration unit, a differential manometer,
and a positive displacement meter. Temperature and barometric pressure
indicators should be available also.
44
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3. Maintenance Area
A sufficiently large area should be designated as the maintenance
and test area. It should be equipped with the tools required for routine
sampler maintenance, such as brush or motor replacement, and auxiliary
equipment maintenance, such as the adjustment and repair of pressure
transducer and flow-rate recorders.
B. Apparatus
Specifications for the apparatus are given in Section 5 of Appendix A.
Table 3 is a listing of the apparatus with approximate costs. Costs are
computed for placing a sampler (standard and modified) on site complete
for sampling, and for the laboratory equipment, which would be prorated
across several sampling stations.
Certain items of equipment listed as additional sampler equipment
are not required in the reference method, but if used could increase
data quality.
A filter paper cartridge provides a means for allowing the filter
changes to be made in the laboratory and provides protection for the clean
and/or exposed filter during transit to or from the sampling site. The
cartridge reduces the risk of loss of sample or otherwise invalidation of
a sample when changing filters during adverse weather conditions.
The 7-day timer and elapsed time indicator allow one to service the
sampler at his convenience and to have the sampler operate at some preset
time by setting the 7-day timer. An accurate measurement of the sampling
time is given by the elapsed time indicator.
In special situations it may be desirable to maintain as nearly as
possible a constant flow rate. Constant flow regulators have been
developed which maintain the flow rate to within 10 percent of its initial
value. In certain situations when a flow regulator is not available, but
the flow rate is known to vary due to variations in the power line voltage,
a constant voltage regulator can be used between the voltage source and
the sampler to maintain a constant source voltage.
45
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Paper supplies (not listed in Table 3) required in the High Volume
Method include manila folders (see Figure 8), glassine envelopes to
protect the sample against absorption of moisture during transit, and
suitable mailing envelopes large enough to accept the folded filter and
filter folder and small enough to hold them firmly so that the filter
cannot move around relative to the folder.
In addition to the above paper supplies, three record books suitable
for use as a laboratory data log book, a calibration log book, and a
maintenance log book must be purchased.
46
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Table 2: Apparatus Used in the High-Volume Method
1.
2.
3.
Item of Equipment
Standard Shelter
Sampler (Less Filter Holder)
Additional Sampler Equipment
a) 8" x 10" stainless steel
filter holder
b) Filter paper cartridge
[need 2 /sampler]
c) 7 day timer
d) Elapsed time indicator
e) Constant flow regulator
f) Constant voltage regulator
g) Step-down transformer
h) Pressure transducer &
continuous flow rate recorder
i) Rotameter
COST OF SAMPLER ON SITE
4.
Calibration
a) Positive displacement
meter (std)
b) Orifice calibration unit
c) Barometer & thermometer
^ost*' ^sedated Standard
,_72 Error Sampler
$ 56 /
85 /
28 /
Loss of
34* Sample
39*
30* Time
150* Flow rate
270* Flow rate
26 /
94 Flow rate
9 /
$ 204
1,000
74
100
Modified
Sampler
/
/
/
S
S
$ 289
Filter Conditioning Envir.
a) Conditioning room or
desiccator
Weighing
a) Balance
b) Air pollution weighing
chamber
7.
Filter Preparation
a) Light source
b) Numbering device
LABORATORY EQUIPMENT COST
1,000 or 300
850
230
30
20
$ 4,125 or $3,425
Not computed in cost
47
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PART II. SUPERVISION MANUAL
3.0 GENERAL
Consistent with the realization of the objectives of a quality
assurance program as given in Section 1.0, this manual provides the
supervisor with brief guidelines and directions for:
1) the collection and analysis of information necessary
for the assessment of high volume data quality,
2) isolating, evaluating, and monitoring major
components of system error,
3) changing the physical system to achieve a desired
level of data quality,
4) varying the auditing or checking level to achieve
a desired level of confidence in the validity of
the outgoing data, and
5) selecting monitoring strategies in terms of data
quality and cost for specific monitoring requirements.
This manual provides brief directions that cannot cover all
situations. For somewhat more background information on quality assurance
see the Management Manual of this document. Additional information
pertaining to the High Volume Method can be obtained from the final report
for this contract and from the literature referenced at the end of the
Management Manual.
Directions are written in terms of a 24-hour sampling period and
an auditing level of n=7 checks out of a lot size of N=100 for illus-
tration purposes. Special instructions for auditing operations where
sampling is performed every sixth day are given also. Information on
additional auditing levels is given in the Management Manual.
Specific actions and operations required of the supervisor in
implementing and maintaining a quality assurance program as discussed in
this Manual are summarized in the following listing.
49
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1) Data Assessment
a) Set up and maintain an auditing schedule.
b) Qualify audit results (i.e., insure that checks
are independent and valid).
c) Perform necessary calculations and compare with
suggested performance standards.
d) Make corrections or alter operations when standards
are exceeded.
e) Forward acceptable qualified data, with audit results
attached, for additional internal review or to user.
2) Routine Operation
a) Obtain from the operator immediate reports of suspi-
cious data or malfunctions. Initiate corrective action
or, if necessary, specify special checks to determine
the trouble; then take corrective action.
b) On a daily basis, evaluate and dispose of (i.e., accept
or reject) data that have been identified as question-
able by the operator.
c) Examine operator's log books periodically for complete-
ness and adherence to operating procedures.
d) Approve filter processing data sheets, calibration
data, etc., for filing by operator.
e) File auditing results.
3) Evaluation of Operations
a) Evaluate available alternative monitoring strategies
in light of your experience and needs.
b) Evaluate operator training/instructional needs for
your specific operation.
50
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3.1 Assessment of High Volume Data
Procedures for implementing and maintaining an auditing program to
assess data quality are presented in this section. Two auditing programs
are discussed. The first and preferred program involves auditing indi-
vidual variables. The second program consists of auditing the entire
measuring process by comparing the final results from the field sampler
to the results obtained with a reference sampler. This second method is
presented here as an alternative to be used in situations where imple-
mentation of the first program is impossible or impractical.
Throughout this discussion and the rest of this document, the term
"lot" is used to represent a set or collection of objects (e.g., measure-
ments or observations), and the "lot size" designated as N is the number
of objects in the lot. The number of objects in the lot to be tested or
measured is called the "sample size" and is designated by n. The term
"auditing level," used interchangeably with "checking level," is fully
described by giving the sample size, n, and the lot size, N.
3.1.1 Assessment by Auditing Individual Variables
A valid assessment of a lot of high volume data can be made at a
given level of confidence with information derived from special checks.
Figure 12 summarizes the quality control checks applied at various check
points in the measuring process. Each check or operation is represented
by a box. The numbers at the top left hand side of each box identify
the step in the process, as given in Figure 1 of the Operations Manual,
at which the check is performed.
Boxes enclosed by heavy lines represent 100 percent sampling; i.e.,
these checks will be performed for each filter passing through the system.
All other checks are to be performed at the prescribed auditing level.
All but three of the checks are treated on a go/no-go basis. That is, a
standard is defined and the lot or individual item is accepted or
rejected on the basis of the check results. Certain rejected lots are
corrigible, i.e., they are capable of being corrected. Specifically,
lots rejected because of weighing or data processing errors are accepted
after the errors have been located and corrected.
51
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*
*
*•
Report
"ll- "l2- -"• "l7
CO Supervisor
Perform
One Point
Calibration Check
Report
dn. =22. — . o27
Determine Delay
Between Collection
and Analysis.
Report
H d A
31' 32' * 37
Mobile
Reference
Samp le r
-O
^—
r
i
..j
_ — ,
i
"• •-.
I
Analysis for
Filter Surface
Alkalinity
1
Visual
Inspection
of Filter
1
Weighing
Clean
Filter
I
Flow-Rate
Check
i
T
Sampling
Period (T)
1 1
Unusual
Conditions
i I
Weigh
Exposed
Filters
1- 1
Data
Processing
i
Is 1
Report to
Supervisor
as
Valid Samples
1
Assemble Data
Into Homogeneous
Lots of 100 Samples
I
Forward
For Additional
Internal Review
or to the User
Analyze 7 out of every 100 filters. Accept the
lot if 6.5 < pH < 7.5 for all filter*
(see Section 2.2).
Inspect each filter and accept if there are
no visible defects (see Step 2. Section 2.1).
Revelgh 7 out of 100 filters. Accept the lot if
1) all check weights are within + 1.0 a* of the
original weights, or 2) all filters have been '
revelghed and corrected (see Section 2.2.).
Perform 7 flow-rate checks out of 100 sampling
periods. Identify sample as a defect if d^. i. 9
and take corrective action (see B.3 of
this section).
Accept sample if 23 hours <_ T _<_ 25 hours.
Othervlset mark void and forward It to the
supervisor.
Accept if no unusual conditlone are evident,
e.g., construction activity in the area, large
number of bugs collected on filter, loss of sample
during handling and/or transit, obvious equipment
malfunctions, etc.
Reweigh 4 out of 50 or less, or 7 out of 100.
Accept the lot if; 1) all check weights are within
+ 2.7 mg of the original weights, or 2) all filters
have been revelghed and corrected (see
Section 2,2).
Rede calculations on 7 out of 100 samples. Accept
the lot If; 1) all check calculations are within
+ 3 percent of the original, or 2) all calculations
have been redone and corrected (see Section 2.2).
Report all valid samples to the supervisor.
Summarize audit results. Transcribe high
volume data to SAROAD Corn. Attach audit
results to SAROAD fora.
Forward all acceptable qualified data, with
audit results attached, for further Internal
review or to the user.
S*e Section 3.1 for discussion of these audit checks.
$** Section 3.1.2 for discussion of mobile soapier.
Figure 12: Flow Chart of Quality Control Checks in the Auditing Program
52
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The three checks not treated on a go/no-go basis are; 1) flow-rate
check, 2) calibration check, and 3) a check of elapsed time between
collection and analysis. These checks are performed at the prescribed
auditing level. Action for correcting system deficiencies can be taken
as the result of any one check, however, there is usually no clear-cut
way of correcting previous data. Therefore, results of these three
checks are reported and used in assessing data quality as described in
Section 4.1 of the Management Manual.
A. Required Information
The seven checks to be performed at the prescribed auditing rate are:
1) filter surface alkalinity,
2) weighing of clean filters,
3) flow-rate check,
4) calibration check,
5) weighing of exposed filters,
6) elapsed time interval between sample collection
and analysis, and
7) data processing check.
Auditing Checks 2, 4, 5 and 7 are required for all monitoring
situations while certain conditions may eliminate the need for one or
more of Checks 1, 3, and 6.
It is not necessary to audit the filter surface alkalinity (Check 1)
if the manufacturer has performed control checks during the manufacturing
process and certifies that the filter pH is between 6.5 and 7.5.
Otherwise, it is recommended that this audit be performed.
The flow-rate check (Check 3) as described in Section 2.6 of the
Operations Manual is not required when the sampler is equipped with a
continuous flow-rate recorder.
A check of the elapsed time between collection and analysis (Check 6)
is not required of networks in which the operator delivers the exposed
filter to the laboratory for conditioning and analysis within less than
53
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24 hours of the sampling period end time or for sampling sites where the
organic content is less than 10 percent of total particulates. It is
recommended that the audit be performed for any situation in which the
sample is mailed to the laboratory for analysis and organic matter
constitutes more than 10 percent of total particulates by weight.
Directions for performing the above 7 listed checks are given in the
Operations Manual, Section 2.6. Directions for insuring independence and
proper randomization in the auditing process and for the evaluation of the
results are presented in this section.
B. Collection of Required Information
1. Filter Surface Alkalinity
This check can be performed by the operator or any individual
capable of following the procedures given in A of Section 2.6 in the
Operations Manual. If the pH range of 6.5 to 7.5, or any other specified
range, is to be adhered to, the lot is rejected anytime a pH is measured
outside the range (see A of Section 2.6 concerning rejecting lots) or
accepted as good after 7 filters have been analyzed and all pH values are
within the prescribed range.
Report the limits of the acceptable range and the auditing level.
2. Weighing Clean Filters
The weighing check should be independent, i.e., performed by
someone other than the person performing the original weighings.
Directions for randomly selecting the 7 filters for reweighing and
performing the check are given in B of Section 2.6.
The lot is accepted as good if 1) all check weights are within
+ 1.0 mg of the original weights or 2) all filters have been reweighed.
Report the standard (e.g., + 1 mg) used to judge the weighing
process, and the auditing level, on the form in Figure 13 of C below.
-------
3. Flow- Rate Check
Procedure for Performing the Check - Samples from individual sites
should be combined into lots. For sites where 50 or more samples are
collected each quarter, a minimum of 7 randomly spaced checks per quarter
is recommended. A minimum of 3 checks per quarter is recommended for
sites operating every sixth day, thereby generating 15 or less samples a
quarter.
Randomly select 7 sampling periods from the coming quarter for sites
where the lot size is expected to be as large as 50. Record dates. The
operator should not be aware of when the checks are to be performed.
For sites where the lot size is 15 or less, randomly select 1 sampling
period each month. Record these dates and perform flow-rate checks as
scheduled.
Directions for performing the check are given in C of Section 2.6.
Treatment of Data - Obtain from the operator values of Q , Q, , Q ,
-- *• i i m
Qr, and Qf as described in Section 2.6.
Calculate the average flow rate using Q and Qf as measured by the
operator by
where j is the j check performed during the auditing period.
Qc by
i i
Calculate the average flow rate using the check values Q., 0 , and
Note that if the measurement Q was not measured within + 1 hour of the
m
true midpoint of sampling period, AQ' should be computed by the following
formula:
55
-------
It is highly recommended that the measurement Q* be made within the above
time constraints so that the first equation can be used in the calculation.
Next, compute the percentage difference in the two average flow rates
by
AQ ! - AQ
d = -
Report 'd,.., d „ --- , d,7 and the auditing level on the form in
Figure 13 of C below.
b. Calibration Check
Procedure for Performing Check - A calibration check can be made
by the same individual and on the same day as the flow-rate check in 3 above.
Directions for performing the check are given in D of Section 2.6.
Treatment of Data - Report the percent difference values as determined
by the operator (see Section 2.6) in the order that the checks were made
as d_ , d , d2~, --- , d_ , and the auditing level on the form in Figure 13
of C below.
5. Weighing Exposed Filters
Perform the check as instructed in B of Section 2.6 of the
Operations Manual. These checks should be made immediately prior to or
after the regular weighings. An auditing level of n=7 is recommended for
lot sizes of N=50 to N=100, and a level of n=4 for lot sizes of N < 50.
In order that corrections can be made to the lot, it is suggested that
lot be made up of filters that are to be weighed at one sitting regardless
of how small the number.
In all cases the lot is accepted as good if 1) all check weights are
within + 2.7 mg of the original weights or 2) all filters have been
reweighed and corrected.
Report the standard (e.g., + 2.7 mg) used to judge the weighing process
and the auditing level on the form in Figure 13 of C below.
56
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6. Elapsed Time Between Sample Collection and Analysis
Procedure for Performing the Check - For sites where this audit
is applicable* the same auditing level and schedule that was set up for
flow-rate checks and calibration checks can be used. Directions for
performing the check are given in E of Section 2.6 in the Operations Manual.
Treatment of Data - Obtain the delays (D.., D2> , D7) in days as
reported by the operator and compute
where
d3. = -[0.008 (% of OM)(D )]*
j is the j check performed during the sampling period,
% of OM is the percent organic content of organic matter as
given in Table 1 of the Operations Manual, and
D. is the delay (days) between collection and analysis
for the j audit check.
Report values of d,-, d_?, , d,_ and the auditing level on the form
in Figure 13 of C below.
7. Data Processing Check
Perform an independent data processing check on the same samples
as were selected for reweighing in 5 above. Directions for performing the
check are given in F of Section 2.6 in the Operations Manual.
The lot is accepted without change if all check calculations are
within + 3 percent of the original calculations. If one check calculation
differs by more than + 3 percent from the original, all samples are
recalculated and the check calculation reported as the correct concentration
of suspended participates.
Report the standard (e.g., + 3 percent) used to judge the data
processing operation and the auditing level on the form in Figure 13 in C
below.
Derivation of this equation is discussed in Section 3.3.1.
57
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C. Treatment of Collected Information
1. Identification of Defects
One procedure for identifying defects is to evaluate auditing
checks in sets, i.e., d-jd-.d.,.. counts as one set, d 2d-2d_- another,
etc., --- d.yd-^d,-. If one or more members of any set are defective, it
counts as one defect. No more than one defect can be declared per set.
Corrigible errors should be corrected when found and are not, therefore,
discussed here.
Any set of auditing checks in-Hhich, the value of d.. . , d~., or-d. .
^_____ __ — -- — -~ - — - ±3 — °~> t-3 — = - ""jj
is greater than +=g=j4i,ll=»be-.cons-i-de.r-ed>_a_defe£t. This value is assumed
to be approximately the 3o value for each of the three parameters. As
field data from the auditing program become available, this limit or
standard should be reevaluated and adjusted, if necessary. All values
of d«. are negative and d.-. will be negative most of the time although
small positive values may occur occasionally. Values of d? . are expected
to be normally distributed with a mean of zero.
2. Reporting Data Quality
Each lot of data submitted with SAROAD forms or tapes should be
accompanied by the minimum data qualifying information as shown in
Figure 13. The individual responsible for the quality assurance program
should sign and date the form. As an illustration, values from Section 3.2,
Suggested Standards for Judging Performance, are used to fill in the blanks
in Figure 13. The reported auditing rate is the rate in effect at the
beginning of the auditing period. An increase or decrease in auditing
rate during the auditing period will be reflected by the total number of
checks reported. The reason for change should be noted on the form.
Check values (i.e., d 's, d..'s and d _'s) are calculated as directed
in Section 3.1.B and reported as a percent to the nearest whole number.
All reported check values exceeding the definition of a defect should be
marked for easy recognition by circling on the form.
Attach the data qualification form to the SAROAD form and forward for
additional internal review or to the user.
58
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Supervisor's Signature
Reporting Date
Parameter
Filter Surface Alkalinity
Weighing of Clean Filters
Weighing of Exposed Filters
Data Processing Check
Parameter
Flow-Rate Check
Calibration Check
Elapsed Time Between
Collection and Analysis
Standard Used
6.5 <. pH <_ 7.5
+ 1 rag
+ 2.7 mg
+ 3% of S.P.*
Definition of
Defect
d21
> 9
> 9
> 9
Audit Level
n=7, N=100
n=7, N=100
n=7, N _> 50; or (n=4, N<50)
n=7, N >_ 50; or (n=4, N<50)
Audit Level
n=7, N=100; or (n=3, N=15)
n=7, N=100; or (n=3, N=15)
n=7, N=100; or (n=3, N=15)
* 3
S.P. = concentration of suspended particulates in yg/m as computed by
the operator.
Number of Defects Reported
(should be circled in the table below)
Audit
Flow-Rate Check
f — 1 fi.,.j f*t i
Calibration Check
Elapsed Time Between
Collection and Analysis
dll
J
d21
d31
(
d!2
-
22
d3?
Sieck \
d!3
j
d23
d33
Values (]
>ercer
dlj
«
2j
d3j
it)
dln
A
d2n
d3n
Figure 13: Data Qualification Form
59
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\
3.1.2 Assessment by Auditing with'a Mobile Sampler
An alternate method of auditing the High Volume Method, which in
certain situations might be feasible, is to use a mobile sampler as a
reference.
A network operating several samplers in a reasonably small area
(ekg., city or county) might find this method more convenient than
auditing individual variables. However, the realiability of this procedure
is directly dependent on the quality of the mobile sampler and how well
it is maintained.
For this method a high volume sampler equipped with a continuous
flow-rate recorder, a constant voltage regulator, elapsed time indicator,
and a constant flow regulator would be maintained by the office of the
director and used as a reference. The reference sampler should be oper-
ated in accordance with the procedures given in the Operations Manual.
For example, Checks 2, 4, 5, 6, and 7 as listed in A of Section 3.1.1
should be made each time the mobile sampler is used. Check 1, filter
surface alkalinity, should be auditid at least at a level of n=7, N=100;
and only filters from lots where all 7 check values were between 6.5 and
7.5 used. A record should be maintained of the checks performed on the
reference sampler and reported with the data if requested by the manager.
An audit would be to place the reference sampler adjacent to (but no
closer than 3 feet) the field sampler (see Ref. 1 for discussion on
positioning the sampler) and sample simultaneously.
The percent difference in the concentration of suspended particulates
as measured by the field sampler, S.P.p, and the reference sampler, S.P.R,
is computed by
S.P. — S.P.
percent difference - dj = 0.5(5.^ + S.P^.)* 10°'
Based on the results of a collaborative test (Ref. 1) showing a
repeatability of the method of 3.0 percent of the mean value, a defect
would be defined at the 3a* level as
If a = 3.0 percent of S.P. for each sampler, then dj would have a standard
deviation of 4.2 percent of the mean value. This gives a 30 value of
approximately 13 percent. gQ
-------
The auditing level for field samplers would be the same as that given
in the previous section, i.e., n=7, N«100.
Only values of d.'s and the auditing level would need be reported.
3.2 Suggested Standards for Judging Performance Using Audit Data
3.2.1 Suggested Performance Standards for Variables
Suggested standards for judging performance are given in Table 3.
Most of these standards are best estimates based on experience and
information available in the literature. They should be reevaluated
and adjusted as data from the quality assurance program become available.
Characteristics of the parameters and variables given in Table 3 are
discussed in Section 3.3.
Standards for operation are based on the estimated lo, 20, and 30
values for each of the parameters. At the recommended auditing level,
i.e., n=7, N=100, there would be a total of 21 audits in an auditing period.
If a normal error distribution is assumed, then only 0.3 percent of the
audits would exceed + 9 or 3a, 5 percent would exceed ;+ 6 or 20, and only
36 percent would exceed + 3 or 10 for a properly operating process. A
defect is defined at the 30 level and should not occur more than once per
lot. From the total 21 audits two or more values exceeding the 20 value
(+ 6) or 8 or more values exceeding the lo value (+ 3) for an auditing
period indicate a larger-than-normal variance in the data, and correctional
changes in the operation should be made.
3.2.2 Suggested Standards for Comparing with Mobile Sampler
Suggested Standards for Defining Defects
1. A value of |d | >_ 13.
Standard for Audit Levels
2. Suggested minimum auditing rates are: number of audits. n=7;
lot size, N=100; allowable number of defects (i.e., |d.| >_ 13)
per lot, d-0. ^
61
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Table 3: Suggested Performance Standards
Parameter
1. Flow- Rate Check
.2. Calibration Check
3. Elapsed Time Between
Collection and Analysis
Parameter
4. Filter Surface
Alkalinity
5. Weighing of Clean
Filters
6. Weighing of Exposed
Filters
7. Data Processing
Check
Definition for
Defining Defects
dlj >9
d23 >9
U3J > 9
Standards for
Corrigible Errors
6.5 <_ pH <_ 7.5
+ 1 mg
+ 2.7 mg
+ 3% of S.P.
Suggested Minimum
Standards for Audit Rates
n=7, N=100; or (n=3, N=15)
n=7, N=100; or (n=3, N=15)
n=7, N=100; or (n=3, N=15)
Suggested Minimum
Standards for Audit Rates
n=7, N=100
n=7, N=100
n=7, N > 50; or (n=4, N<50)
n=7, N >_ 50; or (n=4, N<50)
Standards for Operation
8. If at any time d=l is observed (i.e., a defect is observed for either
d..., d_ . , or d_.) increase the audit rate to n=20, N=100 or n=6, N=15
J-J <<»J »J
until the cause has been determined and corrected.
10.
If at any time d=2 is observed (i.e., two defects are observed in the
same auditing period), cease operation until the cause has been deter-
mined and corrected. When data collection resumes, use an auditing
level of n=20, N=100 (or n=6, N=15) until no values greater than +_ 6
are observed in three successive audits.
If at any time two (2) values of d ., d2., or d«. exceeding + 6 or
three values exceeding + 3 are observed, 1) increase the audit rate to
n=20, N=100 or n=6, N=15 for the remainder of the auditing period,
2) perform special checks to identify the trouble area, and 3) take
necessary corrective action to reduce error levels.
d without a subscript as used here represents the number of defects
observed in a lot of data.
62
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Suggested Standards for Operation
3. If at any time |d.| ^13 increase the auditing rate to n=»20, N=100
until the cause has been determined and corrected.
4. If at any time two (2) values of d are observed to exceed 13
during an auditing period, cease gathering data until the cause
is determined and corrected. Use an auditing level of n=20,
N=100 when the sampling is resumed until three successive audits
are below 8.4.
5. If at any time two (2) values of d exceed 8.4 or three (3)
values exceed 4.2 in an auditing period, 1) increase the auditing
rate to n=20, N=100, 2) perform special checks to locate trouble
areas, and 3) carry out corrective actions to reduce the error
level.
3.3 Collection of Information to Detect and Identify Trouble
In a quality assurance program one of the most effective means of
preventing trouble is to respond immediately to reports from the operator
of suspicious data or equipment malfunctions. Application of proper
corrective actions at this point can reduce or prevent the collection of
poor quality data. Important error sources, methods for monitoring
applicable variables, and suggested control limits for each source are
discussed in this section.
3.3.1 Identification of Important Variables
Measurement of the mass of suspended particulate matter in the
ambient atmosphere by the High Volume Method requires a sequence of
operations and events that yield as an end result a number that serves to
represent the average mass of suspended particulates per. unit volume of
air over the sampling period. Techniques for dynamic calibration of high
volume samplers using test atmospheres containing known concentration of.
particulates are not available. Therefore, there Is no way of knowing
the accuracy of the values derived from high volume sampling. However,
numerous experiments and studies have been performed to identify and
evaluate factors which influence the final results. Major sources of
63
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error as identified by a functional analysis of the High Volume Method
are discussed below. The parameters are grouped according to whether they
influence particulate weight, flow rate, sampling time, or the measured
concentration directly. Data processing errors are also discussed.
A. Factors Affecting Particulate Weight
Filter Surface Alkalinity. Flash fired glass-fiber filters are the
most frequently used filters for collecting suspended particulate matter
for gravimetric analysis. It has been shown (Refs. 2-4) that solid
matter is deposited on the fiber surfaces by oxidation of acid gases in
the sample air. It was also observed that the quantity of such matter
deposited in a given sampling period was not the same for all commer-
cially available glass-fiber filters. Although other reactions are
conceivable, the formation of sulfate was studied. It occurs during
the first 4 to 6 hours of sampling, and very little is formed after
6 hours (Ref. 2).
Tests conducted with 6.5-pH filters and 11-pH filters showed a
significantly larger sulfate to total particulates ratio for the 11-pH
filters (Ref. 3). Additional tests (Ref. 4) have shown that alkaline
filter media can yield erroneously high results for total particulate
matter, sulfates, nitrates, and other species existing as acid gases
in the sample air. From samplers operating side by side, one equipped
with a pH-11 filter and the other with a pH-6.5 filter, showed after
9 sampling periods that the average total particulate matter was higher
by 18 percent, sulfates by 40 percent, and nitrates by 60 percent for
pH-11 filters.
The quantity of solid matter deposited during a sampling period is
a function of filter pH, length of sampling period or volume of air
sampled, and the concentration of acid gases in the sample air. However,
even background levels of N02 and S0_, well below national air quality
standards, can induce significant errors when alkaline filters are
used.
64
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Relative Humidity Effect. Collected particulates are hygroscopic
in varying degrees. Samples collected from suburban, urban, and industrial
atmospheres were weighed after being conditioned for a minimum of 4 days at
'relative humidities varying from 0 to 100 percent (Ref. 5). The results
show less than a 1 percent increase in particulate weight in going from 0
to 55 percent relative humidity. However, the relationship is exponential
for relative humidities greater than 55 percent, showing a 5 percent
increase in particulate weight at a relative humidity of 70 percent and
approximately 15 percent weight increase at 80 percent relative humidity.
The industrial sample proved most hygroscopic with a 90 percent weight
increase at a relative humidity of 100 percent.
The above results point out the importance of maintaining the
conditioning environment at a relative humidity less than 55 percent. Also,
the humidity level should be the same for conditioning the exposed filter
as was used to condition the clean filter. In instances where the exposed
filter has to be removed from the conditioning environment for weighing,
the time interval between removal and weighing should be kept to a minimum.
An interval of less than 5 minutes is recommended.
Elapsed Time Between Sample Collection and Analysis. During the time
between sample collection and final weighing volatile matter having sub-
stantial vapor pressures may evaporate resulting in a significant
reduction in particulate weight.
Results from one set of tests (Ref. 6) indicates that the weight loss
is approximately proportional to the percent of organic matter initially
present in the collected sample. The greatest rate of loss is experienced
during the first 24 hours after collection. A lower but somewhat constant
rate of loss continues for several days, the number of which is again a
function of the initial content of organic matter.
The equation given for d,. in B of Section 3.1.1 allows one to
estimate the possible loss of particulate weight as a function of original
organic content and time delay between collection and analysis. This
relationship was developed from the data in Reference 6. It shows an
approximate loss of 1 percent for a 12-day delay and an initial organic
65
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content of 10 percent, and a weight loss of approximately 6 percent for
a 12-day delay of a sample containing 60 percent organic matter.
It is suggested that this could be an important source of error for
monitoring sites where the sample is mailed in for analysis and the average
organic content of the particulates is greater than 10 percent.
Weighing Errors. Two weighing processes are involved in the High
Volume Method. They are the weighing of clean filters and the weighing
of exposed filters. If not properly monitored, the weighing process can be
a source of significant error in the final result derived from the High
Volume Method. Fifty tare-weight weighings for each of five filters made
over a period of time in which the relative humidity of the conditioning
chamber was varied from 20 to 50 percent showed a maximum variation in
tare-weight weighings of 1.2 mg (Ref. 5). Another test showed a standard
deviation of approximately 0.8 mg for weighing clean filters after
successive 24-hour conditioning periods (Ref. 1). This same test showed
a standard deviation of 1.7 mg for weighing exposed filters after
successive 24-hour conditioning periods.
These data point out the importance of performing the weighings at the
appropriate time, i.e., just after the 24-hour conditioning period, and
the necessity of performing the audit or check within a few minutes either
before or after the regular weighing in order to expect good agreement
between the two weighings.
It is suggested that if the weighing and auditing procedures are
properly carried out, the variation between the original and check weights
of clean filters should not exceed +_ 1.0 tng and not more than +2.7 mg for
exposed filters.
B. Factors Influencing Flow Rate
Flow-Rate Reading Error. The general feeling of people reading the
3 3
rotameter is that they can read it to within + 0.03 m /min (+ 1 ft /min) .
3 3
For an average flow rate of 1.13 m /min (40 ft /min), this would be equiva-
lent to jh 2.5 percent. Under field conditions this error if not monitored
would probably be much greater than 2.5 percent.
66
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Calculating Average Flow Rate. Calculating the average flow rate from
initial and final values assuming a constant rate of change throughout the
sampling period can result in large errors. One report (Ref. 7) shows an
average bias ranging from -1.2 to 8.1 percent of the true average flow
rate, for 3 sets of data with 6 samples each. Bias is defined as the
difference in average flow rate as computed from the initial and final
measurements compared to the average derived from several measurements
made throughout the sampling period. These erorrs can result from
particulates plugging the filter resulting in a nonuniform decrease in the
flow rate over the sampling period or from variations in source voltage.
Nonuniform changes in flow rate are probably greatest in industrial areas
due to sticky particulates and can result in a -2 to +10 percent error
range in average flow-rate values.
A sampler equipped with a continuous flow-rate recorder does not have
the above problem. The true average flow rate can be estimated or calcu-
lated by hourly values to within 0.03 m /min (1 ft /min) from the recorder
chart. This represents a significant improvement in system accuracy.
Flow-Rate Calibration. Calibration of 12 new orifice units by
well-qualified individuals using positive displacement meters as primary
standards under laboratory conditions showed a standard deviation from the
mean of 2.1 percent (Ref. 1). Less qualified people using the orifice unit
to calibrate samplers in the laboratory and in the field would be expected
to yield a much larger standard deviation. Previous experience with high
volume samplers indicate that + 3 percent of the mean is a reasonable
value to use as a standard deviation for calibration error for a well
monitored operation. There is also a possible degradation in the calibra-
tion with time. Once sufficient field data are available an estimate of
its magnitude and characteristics can be made allowing for an optimum
calibration schedule to be derived.
Temperature and Pressure Effects on Flow Rate. For most regions in
the United States and for a specific elevation, temperatures usually range
from -4°C (25°F) to 38°C (100°F) and barometric pressure variations are on
the order of + 12.7 mmHg (0.5 in. Hg) (Ref. 8). Tests on a sampler equipped
67
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with a flow-rate recorder showed a maximum deviation from the calibration
curve of +7 percent to -10 percent in the indicated flow rate when going
from the extremes of 100°F and 29.0 inches of mercury to 25°F and 30.0
inches of mercury. Calibration conditions were 70°F and 29.5 inches of
mercury.
The above data point out the need for either calibrating on site or
making corrections for temperature and pressure if the ambient site
conditions are significantly different from the laboratory conditions.
C. Sampling Time
Timing Errors. The results of high volume sampling are not very
sensitive to the normal magnitudes of timing errors. For example, a
14-rainute error in a 24-hr sampling period results in a 1 percent error in
the measured concentration. The reference method specifies that times be
determined to the nearest 2 minutes. This can be accomplished with the
operators' watch or by using an elapsed time indicator on the sampler. In
the first instance there is no way of knowing of or compensating for power
failures or other interruptions occurring during the sampling period.
Samplers equipped with an elapsed time indicator or a continuous flow-rate
recorder would indicate such power interruptions and allow one to make
corrections.
D. Factors Affecting Measured Concentration Directly
Flow-Rate and Concentration as Functions of Time. - In certain
instances when both flow rate and particulate concentration vary during the
sampling period, significant errors in the measured average concentration
can occur. The example given in Figure 14 is taken as an extreme condition
2
where the concentration of suspended particulates varies from 353 yg/m
3 33
(10 yg/ft ) to 70.6 yg/m (2 yg/ft ) according to the following equation
where
S.P. = 141.2 (| + cos ~ t)
S.P. is the instantaneous concentration in yg/m , and
t is the time in hours.
68
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33 3
Also, the flow rate decreases from 1.7 m /min (60 ft /min) to 1.02 m /min
(36 ft /min) in a linear fashion according to the following relationship
where
Q - 1.7 -(0.03 m3/hr)t
o
Q is the flow rate in m /min, and
t is the time in hours.
The true average concentration, S.P., is seen to be the value at the
point where the concentration curve crosses 12 on the time axis, or
J 2 S.P.dt I 141.2[| + cos j£ t\
dt
S.P. -- 4 - —- -- — - : -- 212 yg/m3 (6 yg/ft3)
-
However, since the flow rate also varies with time the average concentra-
tion as would be measured by the high volume sampler, assuming no other
errors are involved, is expressed as:
ft, ;24 / \
S.P. Qdt I 141.2I-J+ cos -jAt (1.7 - 0.03 t)dt
I
(2k
2 Q dt (1.7 - 0.03 t)dt
' o
227 yg/m3 (6.42 yg/ft3).
This value differs from the true average concentration by + 7 percent.
The reverse case in which the concentration increases as the flow rate
decreases is illustrated by the dashed curve in Figure 14 and results in
a -6.7 percent deviation from the true average.
69
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In a situation such as that shown in Figure 15 in which the
concentration, exhibits a diurnal pattern which is symmetrical about the
midpoint of the sampling period, the true average concentration is realized
by the High Volume Method as long as the flow rate is a linear function of
time. In this case
and
S.P. = 353 [2 + sin ^ t + |) ]
Q = 1.7 - (0.03 m3/hr)t
Performing the same calculations as those done in the example in Figure 14
shows that the "measured" value is the same as the true value.
A deviation greater than + 7 percent from the true average
concentration due to this effect alone should be very rare. The only means
of reducing the magnitude of this error is to equip the sampler with a
constant flow-rate regulator (Ref. 9). At this time, however, existing
constant flow regulators are relatively expensive and are not considered
reliable for everyday use in the field.
An estimate of the possible error for a given site could be made by
using the local diurnal pattern of suspended particulate concentration
and normal or average drop in the flow rate over a 24-hour sampling period
to perform the above calculations. The error would not be significant
unless the change in flow rate is greater than 20 percent of the initial
flow rate, the diurnal pattern is extremely nonsymmetrical about the
midpoint of the sampling period, and the maximum concentration is at least
four times as great as the minimum.
E. Data Processing Errors
Data processing errors include errors in recording measured values and
calculations and in transcribing the calculated values to the SAROAD form.
The frequency and magnitude of these errors depend to a great extent on
the training and experience of the person performing the task.
70
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*T 353 (10)
^ 318 (9)
5 283 (8)
"]e 247 (7)
5 212 (6)
o 177 (5)
* 141 (4)
M
c 106 (3)
-------
An auditing program properly executed should greatly reduce the
probability of data processing errors larger than + 3 percent of the
measured concentration getting through the system.
3.3.2 How to Monitor Important Variables
Table 4 summarizes the important variables and how they are or can
be monitored. As can be seen from the table, variables 1, 2, 3, 4, and 6
are effectively monitored as part of the suggested auditing program. The
relative humidity of the conditioning environment is monitored with a
relative humidity indicator or an indicating desiccant as part of the
routine operating procedures. Voltage variation would probably be detected
as a nonlinear flow-rate drop by the auditing program and could be further
monitored with a voltmeter as a special check.
3.3.3 Suggested Control Limits
Appropriate control limits for individual variables will depend on
the level of performance needed. Table 5 gives suggested performance
standards for determining the average flow rate, calibration error, and
loss of particulates due to evaporation of organic matter. The standards
as given are no more than estimates of what can be achieved in the field.
They should be reevaluated and adjusted as audit data become available.
Suggested control limits for corrigible errors are given in
Table 3, Suggested Performance Standards, and are not repeated here.
Combining the means and standard deviations of the three parameters
gives a system bias of
bias = T = d + d2 + d = -0.06 * S.P.
and a standard deviation of
°T
-VT^s
72
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Table 4: Methods of Monitoring Variables
Variable
Method of Monitoring
1. Filter Surface Alkalinity
2. Weighing Process
3. Flow Rate Reading Errors
4. Nonlinear Flow-Rate Change
5. Relative Humidity of the
Conditioning Environment
6. Evaporation of Volatile
Organic Matter
7. Voltage Variation
8. Data Processing Error
Analysis of filters as" part of the
auditing program.
Reweighing of filters (clean and
exposed) as part of the auditing
program.
Independent initial and final flow-
rate readings performed as part of
the auditing program are compared to
the operator's regular readings.
Use of the three flow-rate readings ,
made as part of the auditing process
to compute an average flow rate and
compare to the value derived from
two readings.
Monitored daily as part of routine
operation by use of a relative
humidity indicator.
Monitoring the delay between
collection and analysis as part of
the auditing process.
A.C. voltmeter measuring voltage to
the sampler and read periodically
throughout the sampling period.
Monitored as part of the auditing
process.
It should,be noted here that the biases (i.e., d., d»> and d_) and
standard deviations (i.e., S., S_, and S.) as computed in Section 4.1 of
the Management Manual are percentages. To arrive at a value in yg/m ,
multiply the decimal equivalent by the S.P. of interest. For example,
3
for an S.P.- = 100 yg/m , the biases given in Table 5 would be
d"3 = -0.03 x 100 - -3 yg/m
73
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Table 5: Suggested Control Limits for Parameters and Variables
Parameter /Variable
1. Flow Rate Check .
2. Calibration Check
3. Elapsed Time Between
Collection and Analysis
(loss or organic
material)
Control Limits
Mean
d^-0.03 x s.P.
d"2=0
d"3=-0.03 x s.P.
Standard Deviation
a = 0.02 x S.P.
a- = 0.03 x S.P.
a- = 0.02 x S.P.
Upper Limit
+ 0.09 S.P.
+ 0.09 S.P.
+ 0.09 S.P.
An overall estimate of data quality would have to include error terms
for the corrigible errors as well as the above values. For more details
see Part III of this document.
3.4 Procedures for Improving Data Quality
Quality control procedures designed to control or adjust data quality
may involve a change in equipment or in operating procedures. Table 6
lists some possible procedures for improving data quality. The applica-
bility or necessity of a procedure for a given monitoring situation will
have to be determined from results of the auditing process or special checks
performed to identify the important variables. The expected results are
given for each procedure in qualitative terms. If quantitative data are
available or reasonably good estimates can be made of the expected change
in data quality resulting from implementation of each procedure, a graph
similar to that in Figure 21, Section 4.3 of the Management Manual can be
constructed. The values used in Table 14 and Figure 21 are assumed and
were not derived from actual data.
For making cost estimates, a reference system consisting of a sampler
equipped with a rotameter and the routine performance of those control
checks spelled out in the Operations Manual is assumed.
Equipment, manpower requirements, and the continuing cost of labor and
supplies are estimated for each procedure. For these estimates technician
time was valued at $5 per hour and engineering time at $10 per hour. Equip-
ment life was taken as 5 years. All calculations were based on a sample lot
of 100 and an average sampling rate of 60 samples per year per sampling site.
74
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Table 6: Quality Control Procedures or Actions
VJ
Ui
Procedure/Action
AO. Reference Condition
Al. Use Continuous Flow-
Rate Recorder
A2. Install a Constant
Voltage Regulator
A3. Take 3rd Flow-Rate
Reading
A4. Use Special Mailing
for Samples
AS. Use Local Laboratory
Description of Action
System using routine procedures
as given in the Operations
Manual
Replace the rotameter with a
pressure transducer and flow-
rate recorder.
Install a constant voltage
regulator in the power line.
Measure, 0 , as part of
routine operation.
Use special mailing such as
air mail for samples
Use a local laboratory (e.g.,
college or high school) to
condition and weigh samples
(implemented as temporary
measure only).
Expected Results
T = 0.06 x S.P. , ST = 0.04 x s.P.
Reduce; 3] =0, a1 = 0.01 x S.P.
Giving; T = -0.03 x S.P., 6T = 0.035 x S.P.
Reduce; 3, = -0.02 x S.P., 0] = 0.01 x S.P.
Giving; T = -0.05 x S.P., OT = 0.035 x S.P.
Reduce; d, = -0.01 x S.P., a, =.0.01 x S.P.
Giving; T = -0.04 x S.P., OT = 0.035 x S.P.
Reduce; 33 = -0.01 x s.P., o3 = 0.01 x s.P.
Giving; ? = -0.04 x S.P., OT = 0.035 x S.P.
Reduce; d"3 = 0, a3 = 0.01 x S.P.
Giving; T = -0.03 S.P., OT = 0.035 x S.P.
Costs
Equip
$ 33
$ 90
None
None
$100
Personnel
—
None
None
$ 35
None
$100
Total
—
$ 33
$ 90
$ 35
$ 25
$200
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A procedure for selecting the appropriate quality control procedure
to insure a desired level of data quality is given below:
1) Specify the desired performance standard, that is,
specify the limits within which you want the devi-
ation between the measured and the true concentration
to fall a desired percentage of the time. For
example, to measure within +_ 0.12 x S.P., 95 percent of
the time, the following performance standards must be
satisfied:
2) Determine the system's present performance level from
the auditing process, as described in Section 4.1 of
the Management Manual, by setting
and
dl + d2 + d3
2^2
y2 + °3
If the relationship of 1) above is satisfied, no
control procedures are required.
3) If the desired performance standard is not satisfied,
identify the major error components.
4) Select the quality control procedure(s) which will
give the desired improvement in data quality at the
lowest cost. Figure 21 in Section 4.3 of the
Management Manual illustrates a method for
accomplishing this.
The relative position of actions on the graph in Figure 21 will differ
for different monitoring networks according to type of equipment being
used, available personnel, and local costs. Therefore, each network would
need to develop its own graph to aid in selecting the control procedure
providing the desired data quality at the lowest cost.
76
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3.5 Procedures for Changing the Auditing Level to Give the Desired
Level of Confidence in the Reported Data
The auditing process does not in itself change the quality of the
reported data. It does provide a means of assessing the data quality.
An increased auditing level increases the confidence in the assessment.
It also increases the overall cost of data collection.
Various auditing schemes and levels are discussed in Section 4.2.
Numerous parameters must be known or assumed in order to arrive at an
optimum auditing level. Therefore, only two decision rules with two
levels of auditing each will be discussed here.
For conditions as assumed in C of Section 4.2 of the Management
Manual, a study of Figure 20, page 104, gives the following results. These
conditions may or may not apply to your operation. They are included here
to call attention to a methodology. Local costs must be used for conditions
to apply to your operation.
A. Decision Rule - Accept the Lot as Good If No Defects Are Found
(i.e., d = 0).
1) Most Cost Effective Auditing Level - In Figure 20 the two
solid lines are applicable to this decision rule, i.e.,
d = 0. The cost curve has a minimum at n = 7 or an audit-
ing level of 7 checks out of 100 sampling periods. From
the probability curve it is seen that at this auditing
level there is a probability of 0.47 of accepting a lot as
good when the lot (for N = 100) actually has 10 defects.
The associated average cost is 240 dollars per lot.
2) Auditing Level for Low Probability of Accepting Bad Data -
Increasing the auditing level to n = 20, using the same
curve in Figure 20 as in (1) above, shows a probability
of 0.09 of accepting a lot as good when the lot actually
has 10 defects. The average cost associated with this
level of auditing is approximately 425 dollars per lot.
77
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B. Decision Rule - Accept the Lot as Good If No More Than One (1)
Defect is Found (i.e., d <_ 1) .
1) Most Cost Effective Auditing Level - From the two dashed
curves in Figure 20 it can be seen that the cost curve has
a minimum at n = 14. At this level of auditing there is a
probability of 0.55 of accepting a lot of data as good when
it has 10 defects. The average cost per lot is approximately
340 dollars.
2) Auditing Level for Low Probability of Accepting Bad Data -
For an auditing level of n = 20 the probability of accepting
a lot with 10 percent defects is about 0.36 as read from the
d <_ 1 probability curve. The average cost per lot is
approximately 375 dollars.
It must be realized that the shape of a cost curve is determined by
the assumed costs of performing the audit and of reporting bad data. These
costs must be determined for individual monitoring situations in order to
select optimum auditing levels.
3.6 Monitoring Strategies and Cost
Selecting the optimum monitoring strategy in terms of cost and data
quality requires a knowledge of the present data quality, major error
components, cost of implementing available control procedures, and poten-
tial increase in system precision and accuracy.
Section 4.3 illustrates a methodology for comparing strategies to
obtain the desired precision of the data. Table 6 of Section 3.4 lists
control procedures with estimated costs of implementation and expected
results in terms of which error component(s) are affected by the control.
The expected results are estimates and were not derived from actual data.
Three system configurations identified as best strategies in
Figure 21 of the Management Manual are summarized here from Section 4.3
of the Management Manual.
Again, local costs and expected results derived from field data are
required to select optimum strategies by this method.
78
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A. Reference Method (AO)
Description of Method; This refers to a sampler equipped with a
rotameter for making flow-rate measurements. Routine operating procedures
as given in the Operations Manual are to be followed with special checks
performed to identify problem areas when performance standards are not
being met. An auditing level of n=7, N-100 is to be carried out for this
strategy. This method or strategy is identified as AO in Table 14 and
Figure 21 in the Management Manual.
Costs; Taken as reference or zero cost.
Data Quality; Data quality can be described by
S.P. - S.P. - T + 3a
i m — i
where
S.F.T = true average concentration of suspended
particulates, and
S.P. = measured average concentration of
suspended particulates.
Taking the hypothesized values of the bias and standard deviation from
Table 14 and using in the above relationship shows that for a true concen-
tration, S.P. , of 1
the following limits
tration, S.P. , of 100 yg/m , the measured value, S.P.^, would fall within
94 < S.P. < 118
m
approximately 99.7 percent of the time.
B. Modified Reference Method (Al)
Description of Method; This strategy is identical to the reference
method in A above except that a pressure transducer and a continuous recorder
are used to measure and record the sample air flow rate.
Costs; The average cost per 100 samples is estimated at 33 dollars
(see Section 3.4).
79
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Data Quality; From Table 6, values of bias and standard deviation
are seen to be T = 0.03 x s.P. and OT = 0.035 x s.P. The data quality
would be described by
S.P._ = S.P. - 0.03 x S.P.T + 3 x 0.035 x S.P._ •.
T m i — i
For a true concentration, S.P.,,,, of 100 yg/m the measured value, S.P. ,
I m
would fall within the limits
92 < S.P. < 114
m
approximately 99.7 percent of the time.
C. Modified Reference Method Plus Action .(Al + A4)
Description of Method; This method is identified as Al and A4 in
Figure 21 of the Management Manual. This method is the same as B above
with the addition of Action A4 which would reduce errors due to loss of
organic matter by minimizing time between collection and analysis.
Costs; Average cost per lot is estimated at 58 dollars.
Data Quality; From Table 6 the data quality would be described by
S.P._ = S.P. - 0.02 x S.P._ + 3 x 0.033 x S.P.T .
r m i — i
For a true concentration, S.P>T, of 100 ug/m the measured value, S.P. ,
would fall within the limits
92 < S.P. < 112 .
m
Results from these estimated values show that in going from Method A
to Method C, the data spread is decreased by about 16 percent and the
range is more evenly distributed about the true concentration value.
80
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PART III. MANAGEMENT MANUAL
4.0 GENERAL
The objectives of a data quality assurance program for the High
Volume Method of measuring the concentration of suspended particulate
matter in air were given in Section 1.0. In this part of the document,
procedures will be given to assist the manager in making decisions
pertaining to data quality based on the checking and auditing procedures
described in Sections 2.0 and 3.0. These procedures can be employed to:
1) detect when the data quality is inadequate,
2) assess overall data quality,
3) determine the extent of independent auditing to
be performed,
4) relate costs of data quality assurance procedures
to a measure of data quality, and to
5) select from the options available to the manager
the alternative(s) which will enable him to meet
the data quality goals by the most cost-effective
means.
Objectives 1 and 2 above are described in Section 4.1. The determination
of the extent of auditing is considered in Section 4.2. Finally,
Objectives 4 and 5 are discussed in Section 4.3. The cost data are
assumed and a methodology provided. When better cost data become
available, improvements can be made in the management decisions.
If the current reference system is providing data quality consistent
with that required by the user there will be no need to alter the physical
system or to increase the auditing level. In fact several detailed pro-
cedures could be bypassed if continuing satisfactory data quality is
Implied by the audit. However, if the data quality is not adequate, e.g.,
either a large bias and/or imprecision in the reported data, then
(1) increased auditing should be employed, (2) the assignable cause is
to be determined, and (3) the system deficiency corrected. The correction
can take the form of a change in the operating procedure, e.g., take a
mid-point flow-rate reading; or it may be a change in equipment such as
81
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the installation of a constant voltage regulator. An increase in the
auditing level will increase the confidence in the reported measure of
precision/bias and aid in identifying the assignable cause(s) of the
large deviations. The level of auditing will be considered in Section 4.2.
4.1 Data Quality Assessment
The audit procedure and the reported results can serve a two-fold
purpose. They can be used to (1) screen the data, by lots of say
N = 50 or 100, to detect when the data quality may be inadequate and
(2) calculate the bias and precision of the audited measurement and hence
estimate the bias/precision of the final reported concentration of suspended
particulate matter in the ambient air. In order to perform (1), suggested ^
standards are provided for use in comparing the audited results with the
reported values and a defect is defined in terms of the standards. This
approach requires only the reporting of the number of defects in the n
auditing checks. In the second method above, it is required to report the
measures of bias/precision in the audits as will be described below. These
values are then used in assessing the overall data quality. Approach (1)
is suggested as a beginning step even though it will not make maximum use
of the data collected in the auditing program. The simplicity of the
approach and the definition of a defective will aid in its implementation.
After experience has been gained in using the auditing scheme and in reporting
and calculating the results, it is recommended that (2) be implemented.
It is important that the audit procedure be independent of previously
reported results and be a true check of the system under normal operating
procedures. Independence can be achieved by providing a control sample
of unknown concentration to the operator and requesting that he measure and
report the concentration of the sample, or having another person perform the
check. To insure that the check is made under normal operating procedures,
it is required that the audit be performed without any special check of the
v
system prior to the audit other than that usually performed each sampling
H
period.
82
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A. Assessment of Individual Measurements
Assume for convenience that an auditing period consists of N = 100
days (or sampling periods) . Subdivide the auditing period into n equal
periods or nearly equal periods. Make one audit during each period and
compute the deviations (differences) between the audit values and the
stated values (or previously determined values as measured by the
operator) as indicated in the Supervision Manual. For example, if seven
audits (n = 7) are to be performed over 100 sampling periods (N = 100) ,
the 100 periods can be subdivided into 7 intervals (6 with 14 periods and
1 with 16 periods) . Select one day at random within each interval and
perform the suggested audits. The operator should not be aware of when
the checks are to be performed.
For sites operating every sixth day, a minimum of three audits per
quarter is recommended. Samples from individual sites can be grouped into
logical lots, e.g., all sites for which a single operator is responsible,
to form data lots of at least 50 samples. This approach insures that the
audit level will exceed n = 7 for the combined sites and resulting data.
In order to assess the data quality using measures of bias/precision,
the checks are to be combined for the selected auditing period and the
mean difference or bias and the standard deviation of the differences are
to be computed as indicated below.
The formulas for average bias and the estimated standard deviations
are the standard ones given in statistical texts (e.g., see Ref. 10).
The level of sampling or auditing, n, will be considered as a parameter to
be selected by the manager to assess the quality of data as required.
1) Flow-Rate Checks
n
*
Bias = d =
»
— »
n
where
d.. = percentage deviation of average flow rates,
^ TA^" and 2RJ"', as determined from the two-point
and three-point approximations (see page 55 of
Section 3.1).
83
-------
Standard Deviation = s,
1 J n-1
where
3 ~ T n-1
The factor 2 is inserted in the denominator to account for the fact that
the variance of the difference of two measurements, each with the same
variance, is twice the variance of an individual measurement.
84
-------
Individual checks on the standard deviations of the three audits
can be made by computing the ratio of the estimated standard deviation,
s., to the corresponding suggested performance standard, o., given in
Table 7. If this ratio exceeds values given in Table 7 for any one of
the audits, this would indicate that the source of trouble may be
assigned to that particular aspect of the measurement process. Critical
values of this ratio are given in Figure 16 as a function of sample size
and two levels of confidence. Having assessed the general problem area,
one then needs to perform the appropriate quality control checks to
determine the specific causes of the large deviations.
Table 7. Critical Values of
Level of
Confidence
90%
95%
Statistic
Si/0i
8i/0i
Audit Level
n=5
1.40
1.54
n=10
1.29
1.37
n=15
1.23
1.30
n=20
1.20
1.26
n=25
1.18
1.23
estimated standard deviation
a. = hypothesized or suggested standard deviation
Audit
Flow Rate Check
Calibration Check
Elapsed Time Between
Collection and Analysis
Overall Standard Deviation
Suggested Performance Standard
a- = 0.02 x S.P.
02 - 0.03 x s.P.
a3 = 0.02 x s.P.
ax - 0.041 x S.P.
85
-------
1.60
1.50
•H
m
« 1.40
-------
B. Overall Assessment of Data Quality
. The values cL , d-, and d-, s-, s2, and s, above measure the bias
and variation of the reported data for the three audits considered.
The biases and standard deviations of the remaining variables can be
estimated from the suggested standards under the assumption that the
data quality is consistent with the standards, or they may be obtained
by determining the effects of each bias and standard deviation on the
reported concentrations S.P.
1) Development of a Model
In order to be able to make objective decisions concerning the
High Volume Method for measuring the concentration of particulate matter
in air, it was helpful to develop a mathematical model of the process
since there is no way of generating a standard atmosphere to calibrate
the sampler. The measurement of particle concentration is dependent on
several parameters, operator effects, environmental conditions, calibra-
tion procedures, variation in instrumentation, and other variables and
effects, some of which are perhaps unknown to us. In developing the
model, data were collected from several publications and exploratory
experiments. If data were not available, engineering judgement concern-
ing the magnitude of the effects was used. Starting with the basic
2
deterministic equation for estimating the particle concentration (yg/m ),
an effects model was developed to include all of the parameters,
variables, and errors which could be identified as possible contributors
to the variation in the results. Ten error terms are included in the
model. The model and the estimated effects of each of the parameters
in the model are discussed in further detail in the Final Report on this
contract.
2) Identification of the Important Parameters
The next step in the modeling process was to use the model to
identify the critical parameters, i.e., those parameters which may cause
the greatest variation in the concentration, S.P., if their variation is
87
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of the order of magnitude assumed in the analysis. Two types of analyses
were employed to determine the critical parameters and the combined effect
of all of the parameters on the variation in the measured concentration,
S.P.
The first type was a sensitivity or ruggedness analysis which
identified and ranked the critical parameters, made certain checks on
the adequacy of a linear approximation to the developed model, and
estimated the variation (as measured by the standard deviation) of S.P.
through the use of a linear approximation. This latter technique was a
straightforward application of error analysis. The second analysis
procedure was a Monte Carlo simulation in which each of the parameters
was assigned a distribution of values; for example, the weighing error
was assumed to be normally distributed with given mean and standard
deviation. This simulation analysis provided a listing of the simulated
values of concentration in ascending order and calculated the mean and
standard deviation and other pertinent characteristics of this distribu-
tion. These analyses are described in some detail in the Final Report
of this contract.
Results from the above analyses may not be valid for one
specific situation, but should be a reasonably good evaluation of average
precision and accuracy obtainable over a large population of samplers. The
results indicate that if the operating procedures recommended in the
Operations Manual were adhered to, the measured data would have a mean
value very close to the true value (i.e., there would be no bias, T = 0)
and a standard deviation of approximately 6 percent of the mean value
(aw 0.06 x S.P.). This held true for simulated concentrations ranging
33
from about 50 Mg/m to 300 pg/m .
Values derived from the above analyses were used to arrive at
suggested performance standards, and to a certain extent, for suggested
control limits given for certain checks in the Operations Manual.
The standard deviation of S.P. is a measure of the precision or
variation of the reported values of S.P. as estimated by the model. It
is to be noted that this measure depends on the estimated standard
deviations of each of the variables and on the coefficients in the model,
which are dependent on the form of the model. These values can be
88
-------
checked using the biases and standard deviations computed from actual
field data. The true concentration of suspended particulates should fall
in the following interval where S.P. is the measured concentration,
m
s-P. - T 25*
approximately 95 percent of the time, or within the interval
S.P. - T + 3o_ ,
m — T
approximately 99.7 percent of the time. When computed from audit data,
the value 2a_ is actually dependent on the number of audits conducted.
If n is large, say about 25 or larger, the value 2 is appropriate.
In reporting the data quality, the bias, overall standard deviation,
and auditing level should be reported in an ideal situation (see
Section 4.4 for further discussion on data presentation). More restricted
information is suggested in the Supervision Manual as a minimal reporting
procedure.
If the overall reported percisions /biases of the data meet or
satisfy the requirements of the user of the data, then a reduced auditing
level may be employed; on the other hand, if the data quality is not
adequate, assignable causes of large deviations should be determined
and appropriate action taken to correct the deficiencies. This determina-
tion may require an increased checking or auditing of the measurement
process as well as the performance of certain quality control checks,
e.g. , monitor voltage variations over 24-hour sampling period.
4.2 Auditing Schemes
Auditing a measurement process costs time and money. On the other
hand, reporting poor quality data can also be very costly. For example,
the reported data might be used to determine a relationship between
health damage and concentrations of certain pollutants. If poor quality
A positive bias in the measurement must be subtracted from the measured
value when estimating the true concentration.
89
-------
data are reported, it is possible that invalid inferences or standards
derived from the data will cost many dollars. These implications may
be unknown to the manager until some report is provided to him referencing
his data; hence, the importance of reporting the precision and bias with
the data.
As a result of the cost of reporting poor quality data it is
desirable to perform the necessary audits to assess the data quality
and to invalidate unsatisfactory data with high probability. On the
other hand, if the data quality is satisfactory, an auditing scheme will
only increase the data measurement and processing cost. An appropriate
tradeoff or balance of these costs must be sought. These costs are
discussed in Section C below.
Now consider the implication of an auditing scheme to determine or
judge the quality of the reported data in terms of an acceptance sampling
scheme. Let the data be assembled into homogeneous lots of N » 50 or
100 sampling periods. Suppose that n periods are sampled in the manner
suggested in Section 4.1. That is, the N » 50 or 100 sampling periods are
subdivided into equal time intervals (as nearly equal as possible) then
one day is selected at random during each interval. Figure 17 gives a
diagram of the data flow, sampling, and decision making process for
an auditing level of n = 7.
A. Statistics of Various Auditing Schemes
Suppose that the lot size is N = 100 periods (days), that n » 7
periods are selected at random, and that there are 5% defectives in the
100, or 5 defectives. The probability that the sample of 7 contains
0, 1, ..., 5 defectives is given by the following.
90
-------
p(0 defectives)
and for d defectives
p(d defectives)
5 95)
\d/\7-d/ s
/i rtV.\ > a _ •> •
The values are tabulated below for d = 0, 1, ..., 6 and for the two
data quality levels.
Table 8: P(d defectives)
d
0
1
2
3
5
6
D=5%
0
0
0
0
0
=
Data
Defectives
.6903
.2715
.0362
.0020
.00004
0
Quality
D=15%
0.
0.
0.
0.
0.
^$
Defectives
3083
4098
2152
0576
0084
0
Figure 18A gives the probabilities of d = 0 and d <_ 1 defectives as
a function of sample size. The probability is given for lot size N = 100,
D = 5 and 15% defectives, for sample sizes (auditing levels) from 1 to 25.
For example, if n = 10 measurements are audited and D = 5% defectives, the
probability of d=0 defectives is 0.58. Figure 18B gives the probabilities
for lot size N = 50, for D = 6, 10, and 20% defectives, and for d = 0.
and d <^ 1. These curves will be used in calculating the cost relationships
of Section C.
_ fl!5l/\7!88!/ = 9S-94---89 _ Q 6903
C00\ / 100 !\ 100-99---94
i) (nw.)
91
-------
Data Flow
Lot 1
N - 100
Days
Lot 2
N - 100
Days
Sample
n = 7
Periods (days)
Observe
d = 0 defects
Observe
d = 1 defect
Calculate Costs of
Accepting and
Rejecting the Lot
Accept Data If
1. Cost Comparison
Favors This Action
2. Data Quality Is
Acceptable
Reject Data
Otherwise
Figure 17: Data Flow Diagram for Auditing Scheme
92
-------
1.0" •LTm.LU
CO
9)
*J
3
CO
-------
I
.g
CO
+J
o
0)
«4-l
*
•s
0.4
0.2 -
10%
20%
10 15
Sample Size (n)
20
25
Figure 18B: Probability of d Defectives in the Sample If the
Lot (N = 50) Contains D% Defectives.
This graph is for a lot size of N = 50. Only whole numbers of defectives
are physically possible; therefore, even values of D (i.e., 6, 10, and
20 percent) are given rather than the odd values of 5 and 15 percent as
given in Figure ISA. *
-------
B. Selecting the Auditing Level
One consideration in determining an auditing level n used in assessing
the data quality is to calculate the value of n which for a'prescribed
level of confidence will imply that the percent of defectives in the lot is
less than ten percent, say, if zero defectives are observed in the sample.*
Figures 19A and 19B give the percentage of good measurements in the lot
sampled for several levels of confidence, 50, 60, 80, 90, and 95%. The
curves in 19A assume that 0 defectives are observed in the sample, and
19B, 1 defective observed in the sample. The solid curves on the figures
are based on a lot size of N = 100; two dashed curves are shown in
Figure 19A for N = 50; the differences between the corresponding curves
are small for the range of sample sizes considered.
For example, for zero defectives in a sample of 7 from a lot of
N = 100, one is 50% confident that there are less than 10% defective
measurements among the 100 reported values. For zero defectives in a
sample of 15 from N = 100, one is 80% confident that there are less than
10% defective measurements. Several such values were obtained from
Figure 19A and placed in Table 9 below for convenient reference.
Table 9: Required Auditing Levels n
for Lot Size N = 100
Assuming Zero Defectives
Confidence Level
50%
60%
80%
90%
95% ;
D = 10%
7
9
15
20
= 25
15%
<5
6
10
15
18
20%
<5
<5
8
11
13
*
Obviously, the definition of defective need not always be the same and
must be clearly stated each time. The definitions employed herein are
based on results of collaborative test programs.
95
-------
100
CO
4J
g
§
co
S
o
3
a
9)
O
J-l
-------
100
80
o>
4J
5 60
-------
C. Cost Relationships
The auditing scheme can be translated into costs using the costs
of auditing, rejecting good data, and accepting poor quality data.
These costs may be very different in different geographic locations.
Therefore, purely for purposes of illustrating a method, the cost of
auditing is assumed to be directly proportional to the auditing level.
For n = 7 it is assumed to be $155 per lot of 100. The cost of rejecting
good quality data is assumed to be $600 for a lot of N = 100. The cost
of reporting poor quality data is taken to be $800. To repeat, these
costs given in Table 10 are assumed for the purpose of illustrating a
methodology of relating auditing costs to data quality. Meaningful
results can only be obtained by using correct local information.
Table 10: Costs vs. Data Quality
Data Quality
"Good"
D <_ 10%
Incorrect Decision
"Bad"
D > 10%
Correct Decision
Reject Lot of
Data
Lose cost of performing
audit plus cost of reject-
ing good quality data.
(-$600 - $155)
Lose cost of performing
audit, save cost of not
permitting poor quality data
to be reported. ($400 - $155)
Accept Lot of
Data
Correct Decision
Lose cost of performing
audit. (-$155)
Incorrect Decision
Lose cost of performing
audit plus cost of declaring
poor quality data valid.
(-$800 - $155)
Cost of performing audit varies with the sample size; is assumed to be
$155 for n = 7 audits per N = 100 lot size.
98
-------
Suppose that 50 percent. of the lots have more than 10 percent
defective and 50 percent have less than 10 percent defective. (The
percentage of defective lots can be varied as will be described in the
final report.) For simplicity of calculation, it is further assumed
that the good lots have exactly 5 percent defectives and the poor quality
lots have 15 percent defective.
Suppose that n = 7 measurements out of a lot N = 100 have been audited
and none found to be defective. Furthermore, consider the two possible
decisions of rejecting the lot and accepting the lot and the relative costs
of each. These results are given in Tables 11A and 11B.
Table 11A: Costs If 0 Defectives are Observed and the Lot is Rejected
Reject Lot
•
D = 5%
D = 15%
Correct
Decision
P2 = 0.31
C2 = 400 - 155
Incorrect
Decision
Pl = 0.69
Cl = -600 - 155
Net Value ($)
P-L^ = -$521
P2C2 = $76
Cost =
-$445
Table 11B: Costs If 0 Defectives are Observed and the Lot is Accepted
Accept Lot
D = 5%
D - 15%
Correct
Decision
PI = 0.69
C3 = -155
' -
Incorrect
Decision
P2 = 0.31
C4 = -800 - 155
Net Value ($)
P;LC3 = -$107
P2C, = -$296
Cost =
= -$403
99
-------
The value P1(P2' in tne above table is the probability that the
lot is 5% (15%) defective given that 0 defectives have been observed.
For example,
probability that the lot is 5% defective
and 0 defectives are observed
'lot is 5% defective and
0 defectives observed
rlot is 15% defective ancT
0 defectives observed
0.5(0.69)
_
0.5(0.69) + 0.5(0.31)
0.69.
[probability that the lot is 15% defective
\ and. 0 defectives are observed
1
lot is 5% defective
0 defectives observed
and\~T7
.a-)* •(
lot is 15% defective and^
0 defectives observed
0.5(0.31)
0.5(0.31) + 0.5(0.69)
0.31.
It was assumed that the probability that the lot is 5% defective is 0.5.
The probability of observing zero defectives , given the lot quality is 5%
or 15%, can be read from the graphs of Figures ISA or 18B.
A similar table can be constructed for 1, 2, ..., defectives and the
net costs determined. The net costs are tabulated in Table 12 for 1, 2,
.and 3 defectives. The resulting costs indicate that the decision preferred
from a purely monetary viewpoint is to accept the lot if 0 defectives are
observed and to reject it otherwise. The decision cannot be made on this
basis alone. The details of the audit scheme also affect the confidence
which can be placed in the data qualification; consideration must be given
to that aspect as well as to cost.
Table 12: Costs in Dollars
Decision
Reject Lot
Accept Lot
d = number of defectives
0
-445
-403
1
-155
-635
2
+101
-839
3
+207
-928
100
-------
D. Cost Vs. Audit Level
After the decision criteria have been selected, an average cost can
be calculated. Based on the results of Table 12, the decision criterion
is to accept the lot if d = 0 defectives are observed and to reject the
lot if d = 1 or more defectives are observed. All the assumptions of
the previous section are retained. The auditing level is later varied
to obtain the data in Figure 20.
One example calculation is given below and summarized in Table 13.
The four cells of Table 13 consider all the possible situations which can
occur, i.e., the lots may be bad or good and the decision can be to
either accept or reject the lot based on the rule indicated by Table 12.
The costs are exactly as indicated in Tables 11A and 11B. The probabilities
are computed as follows.
q1 = (prob. that the lot is 5% defective and 1 or
_L . " ~~
more defects are obtained in the sample)
= (prob. that the lot is 5% defective)(prob. 1 or
more defectives are obtained in the sample
given the lot is 5% defective)
= 0.5 (0.31) = 0.155
Similarly q_, q_, and q, in Table 13 are obtained as indicated below.
q2 = 0.5 (0.69) = 0.345
q3 = 0.5 (0.69) = 0.345
q4 = 0.5 (0.31) = 0.155
The sum of all the q's must be unity as all possibilities are considered. The
value 0.5 in each equation is the assumed proportion of good lots (or poor
quality lots). The values 0.31 and 0.69 are the conditional probabilities
that given the quality of the lot, either d = 0 or d = 1 or more defectives
are observed in the sample. Further details of the computation are given
in the final report of this contract.
101
-------
Table 13: Overall Average Costs for One
Acceptance - Rejection Scheme
Decision
Reject any lot of
data if 1 or more
defects are found.
Accept any lot of
data if 0 defects
are found.
Good
D =
ql =
Cl =
q =
C3 =
Lots
5%
0.155
-$755
0.345
-$155
Bad
D =
q2 =
C2 =
q4 =
C4 =
Lots
15%
0.345
$245
0.155
-$955
qlCl + q2C2 = -$ 32
q3C3 + q4C4 = -$2°2
Average Cost = -$234
In order to interpret the concept of average cost, consider a large
number of data lots coming through the system; a decision will be made
on each lot in accordance with the above and a resulting cost of the
decision will be determined. For a given lot, the cost may be any one of
the four costs, and the proportion of lots with each cost is given by the
q's. Hence the overall average cost is given by the sum of the product of
q's by the corresponding C's.
In order that one may relate the average cost as given in Table 13
to the costs given in Table 12, it is necessary to weight the costs in
Table 12 by the relative frequency of occurrence of each observed number
of defectives, i.e., prob(d). This calculation is made below.
No. of
Defectives
d = 0
1
2
3
4
Decision
Rule
Accept
Reject
Reject
Reject
Reject
Costs ($) from
Table 12
- 403
- 155
101
207
244
Prob(d)
0.50
0.34
0.1255
0.030
0.0042
Cost x Prob(d)
-$201.5
- 52.7
12.6
6.2
1.0
Totals 0.9997
-$234.4
102
-------
Thus the value -$234 is the average cost of Table 13 and the weighted
average of the costs of Table 12. The weights, Prob(d) , are obtained
as follows:
Prob(d=0) = Prob(lot is good and d=0 defectives are observed)
+ Prob(lot is poor quality and d=0 defectives are observed)
=. 0.5(0.69) + 0.5(0.31) - 0.50 .
This is the proportion of all lots which will have exactly 0 defectives
under the assumptions stated. For d = 1, 2, 3, and 4, the values of the
probabilities in parentheses above can be read from Table 8.
Based on the stated assumptions the average cost was determined for
several auditing levels as indicated in Table 13. These costs are given
in Figure 20. One observes from this figure that n = 7 is cost effective
given that one accepts only if zero defectives are observed. (See curve
for d = 0.)
If the lots are accepted if either 0 or 1 defectives are observed,
then referring to the curve d <_ 1, the best sampling level is n = 15.
The curve of probability of d = 0 (d <_ 1) defectives in a lot of N = 100
measurements if there are 10% defectives, is also given on the same
figure.
Another alternative is to accept all data without performing an
audit. Assuming that one-half (50%) of the lots contain more than 10%
defectives, the average cost on a per lot basis would be 0.5(-$800) = -$400.
This, however, would preclude qualification of the data. Regardless of
cost, it would be an unacceptable alternative.
4.3 Data Quality Versus Cost of Implementing Actions
The discussion and methodology given in the previous section were
concerned with the auditing scheme (i.e., level of audit or sample size,
costs associated with the data quality, etc.). Increasing the level
of audit of the measurement process does not by itself change the
quality of the data, but it does increase the information about the
103
-------
$400
CO
CD
to
O
oo $300
(0
H
0)
cd
M
0)
£
$200
Cost if
d = 0
I
Probability
if d - 0
5 10 15
Audit Level (Sample Size)
20
D
O
0)
N
•H
00
IW
O
0)
tH
!
(A
CO
>
•8
J3
O
M
Figure 20: Average Cost Vs. Audit Level
(Lot Size N = 100)
-------
quality of the reported data. Hence,', fewer good lots'will.be rejected
and more' poor quality data will-be rejected..' If the results of. the ..
audit imply thaf'certairi process measurement variables are major contrib-
utors to the total error or variation in the reported S.P., then alterna-
tive strategies for reducing these variations need to be investigated.
This section illustrates a methodology for •-comparing the strategies to
obtain the desired precision of thfe data. In practice it would be
necessary to experiment with one or more strategies, determine the
potential increase in precision, relate the precisions to the relative
costs as indicated'herein. Several strategies are considered, but only
a few of the least costly ones 'would be acceptable as illustrated in
Figure 21. The assumed values o;f the standard deviations and biases for;
each type audit are not based on actual data, except 'for the reference
method. In this case values were taken from Ref. 1. These values are
probably smaller1 than those experienced':iri'-the field.
Several alternative auctions or strategies can be taken to increase
the precision'of the reported data. For example, if :the voltage
variations are 'large, the flow rate will vary and, depending upon the
diurnal variation, will cause variation in S.P. Similarly the nature of
the particulate matter may cause a large decrease in the flow rate.
Under these conditions additional control equipment for one or more of
the environmental effects can reduce the variation of the measured
responses by calculated amounts and thus reduce the error of the
reported concentrations. In this manner, the cost of the added controls
can be related to the data quality as measured by the estimated bias/
precision of the reported results. Because there is a significant bias,
the measure of variation of the reported results is taken as the square
root of the mean square error, i.e., M =
In order to determine a cost efficient procedure, it is necessary
to estimate the variance for each source of error (or variation) for
each strategy and then select the strategy or combination of strategies
which yield the desired precision with minimum cost. These calcula-
tions are summarized in Table 14 with assumed costs of equipment and
control procedures.
105
-------
Suppose chat it is desired to make a statement that the true S.P.
is within 12 ug/m with approximately 95 percent confidence. Minimal
cost control equipment and checking procedures are to be employed to
attain this desired precision.
Examining the graph in Figure 21 of cost versus precision, one
observes that A4 is the least costly strategy that meets the required
goal of 2M - 0*12 or M = 0.06 (i.e., an overall error of 61 of S.P.) in
the reported concentration. Similary the combination of Al and A4 meets
the requirement that 3M = 0.12 or M = 0.04 (i.e., an overall error of
4% of S.P.). The assumed values of the standard deviations of the
measured concentrations of suspended particulates for the alternative
courses of action are given in Table 14. The costs for the various alter-
natives are given in Table 6 of Section 3.4 and in Table 14.
Suppose that it is desired that M be less than 0.04 and that the
cost of reporting poor quality data increases rapidly for M greater
than 0.04. This assumption is illustrated by the cost curve given by
the solid line in Figure 21. For any alternative strategy* the cost of
reporting poor quality data is given by the ordinate of this curve
corresponding to the strategy.
106
-------
Table 14: Assumed Standard Deviations and Biases for
Alternative Strategies
1. Flow Rate Check d..
°1
2. Calibration Check d2
•"" *2
3. Elapsed Time Between d_
Sample Collection
and, Analysis o~
Alternative Strategies
AO
0.03
0.02
0
0.03
0.03
0.02
Al
0
0.01
0
0.03
0.03
0.02
A2
0.03
0.01
0
0.03
0.03
0.02
A3
0.01
0.01
0
0.03
0.03
0.02
A4
0.03
0.02
0
0.03
0.01
0.01
A5
0.03
0.02
0
0.03
0
0.01
A1+A4
0
0.01
0
0.03
0.01
0.01
**
***
Bias=T
M
Added Cost ($)/100 Samples
0.041
0.06
0.073
0
0.037
0.04
0.048
33
0.037
0.05
0.062
90
0.037
0.04
0.054
35
0*037
0.04
0.054
25
0.037
0.03
0.048
200
0.033
0.01
0.035
58
Alternative Strategies are given in Table 6, Section 3.4, the c^'s,
1 = 1, 2, and 3, are .assumed values, based on results given in Ref. 1, and
where data are not available, they are engineering judgments.
All of these values are percent error, i.e., 0.03 is equivalent to
0.03 x S.P., etc. for each value given.
***
Bias
107
-------
200
(0
0)
o
o
0)
P-,
w
8
•8
0A5
100
50
Best
Strategies
Cost of Reporting
Poor Quality Data
0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08
M
I o 2
Figure 21: Added Costs Vs.\a + T for Alternative Strategies
108
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4.4 Data Presentation
A reported value whose precision and accuracy (bias) are unknown is
of little, if any, worth. The actual error of a reported value—that is,
the magnitude and sign of its deviation from the true value—is usually
unknown. Limits to this error, however, can usually be inferred, with
some risk of being incorrect, from the precision of the measurement
process by which the reported value was obtained and from reasonable
limits to the possible bias of the measurement process. The bias, or
systematic error, of a measurement process is the magnitude and direc-
tion of its tendency to measure something other than what was intended;
its precision refers to the closeness or dispersion of successive
independent measurements generated by repeated applications of the
process under specified conditions, and its accuracy is determined by
the closeness to the true value characteristic of such measurements.
Precision and accuracy are inherent characteristics of the measure-
ment process employed and not of the particular end result obtained.
From experience with a particular measurement process and knowledge of
its sensitivity to uncontrolled factors, one can often place reasonable
bounds on its likely systematic error (bias). This has been done in the
model for the measured concentration as indicated in Table 14. It is
also necessary to know how well the particular value in hand is likely
to agree with other values that the same measurement process might have
provided in this instance or might yield on measurements of the same mag-
nitude on another occasion. Such information is provided by the estimated
standard deviation of the reported value, which measures (or is an index
of) the characteristic disagreement of repeated determinations of the
same quantity by the same method and thus serves to indicate the precision
(strictly, the imprecision) of the reported value.
A reported result should be qualified by a quasi-absolute type of
statement that places bounds on its systematic error and a separate
statement of its standard deviation, or of an upper bound thereto, when-
ever a reliable determination of such value is available. Otherwise a
computed value of the standard deviation should be given together with
a statement of the number of degrees of freedom on which it is based.
109
-------
As an example, consider strategy AO in Table 14 of Section 4.3.
Here, the assumed standard deviation and bias are; o_ =0.041 * S.P. and
T = 0.06 x S.P._, respectively, where S.P-T is the true concentration of
suspended particulates. The results would be reported as the measured
concentration, S.P. , with the following 2o limits and audit level, e.g.,
m
S.P. - 0.06 x S.P. + 0.082 x S.P.; n=7, N=100,
m — •
110
-------
4.5 Personnel Requirements
Personnel requirements as described here are in terms of the High
Volume Method only. It is realized that these requirements may be only a
minor factor in the overall requirements from a systems point-of-view where
several measurement methods are of concern simultaneously.
A. Training and Experience
1. Director
The director or one of the professional level employees should
have a basic understanding of statistics as used in quality control. He
should be able to perform calculations, such as the mean and standard
deviation, required to define data quality. The importance of and require-
ments for performing independent and random checks as part of the auditing
process must be understood. Three references which treat the above
mentioned topics are listed below:
Probability and Statistics for Engineers, Irvin Miller
and John E. Freund, published by Prentice-Hall, Inc.,
Englewood, N. J., 1965.
Introductory Engineering Statistics, Irwin Guttman and
S. S. Wilks, published by John Wiley and Sons, Inc.,
New York, N. Y., 1965.
The Analysis of Management Decisions, William T. Morris,
published by Richard D. Irwin, Inc. , Homewood, Illinois,
1964.
2. Operator
The High Volume Method is simple at the operational level
requiring no high level skills. A high school graduate with proper
supervision and on-the-job training can become a fully capable operator
within one month or less.
Ill
-------
An effective on-the-job training program could be as follows:
a) Observe experienced operator perform the different
tasks in the measurement process.
b) Study the operational manual of this document and
use it as a guide for performing the operations.
c) Perform operations under the direct supervision
of an experienced operator.
d) -Perform operations independently but with a high
level of quality control checks utilizing the
technique described in the section on operator
proficiency evaluation procedures to encourage
high quality work.
Another alternative would be to have the operator attend an appropriate
basic training course sponsored by EPA.
4.6 Operator Proficiency Evaluation Procedures
One technique which may be useful for early training and qualification
of operators is a system of rating the operators as indicated below.
Various types of violations (e.g., invalid sample resulting from
operator carelessness, failure to maintain records, use of improper equip-
ment, or calculation error) would be assigned a number of demerits
depending upon the relative consequences of the violation. These demerits
could then be summed over a fixed period of time of one week, month, etc.
and a continuous record maintained. The mean and standard deviation of
the number of demerits per week, can be determined for each operator and
a quality control chart provided for maintaining a record of proficiency
of each operator and whether any changes in this level have occurred. In
comparing operators, it is necessary to assign demerits on a per unit
work load basis in order that the inferences drawn from the chart be
consistent. It AaAy on deA-iSiabie. fat the. op&uitoi to be
aitiaAn. Of$ tiuA hohm o^ evaluation. The. &wpoti &kouJid aae
-------
A sample QC chart is given in Figure 22 below. This chart assumes
that the mean and standard deviation of the number of demerits per week,
e.g., are 5 and 1 respectively. After several operators have been evalu-
ated for a few weeks, the limits can be checked to determine if they are
both reasonable and effective in helping to improve or maintain data
quality.
The limits should be based on the operators whose proficiency is
average or slightly better than average. Deviations outside the QC
limits, either above or below, should be considered in evaluating the
operators. Identifying those operators whose proficiency may have
improved is just as important as knowing those operators whose proficiency
may have decreased.
The above procedure may be extended to an entire monitoring network
(system). With appropriate definitions of work load, a continuous record
may be maintained of demerits assigned to the system. This procedure
might serve as an incentive for teamwork, making suggestions for improved
operation procedures, etc.
1234 5 6 7 8 9 10 11 12 13
Time Intervals (Weeks)
Figure 22: Sample QC Chart for Evaluating Operator Proficiency
113
-------
REFERENCES
1. Herbert C. McKee et al., "Collaborative Study of Reference Method for
the Determination of Suspended Particulates in the Atmosphere (High
Volume Method)," Southwest Research Institute, Contract CAP 70-40,
SwRI Project 21-2811, San Antonio, Texas, June 1971.
2. Robert E. Lee, Jr. and Jack Wagman, "A Sampling Anomaly in the
Determination of Atmospheric Sulfate Concentration," American
Industrial Hygiene Association Journal 27, pp. 266-271, May-June 1966.
3. Rober M. Burton et al., "Field Evaluation of the High-Volume Particle
Fractionating Cascade Impactor—A Technique for Respirable Sampling,"
presented at the 65th Annual Meeting of the Air Pollution Control
Association, June 18-22, 1972.
4. Peter K. Mueller et al., "Selection of Filter Media: An Annotated
Outline," presented at the 13th Conference on Methods in Air
Pollution and Industrial Hygiene Studies, University of California,
Berkeley, California, October 30-31, 1972.
5. G. P. Tierney and W. D. Conner, "Hygroscopic Effects on Weight
Determinations of Particulates Collected on Glass-Fiber Filters,"
American Industrial Hygiene Association Journal 28, pp. 363-365,
July-August, 1967.
6. John F. Kowalczyk, "The Effects of Various Pre-Weighing Procedures on
the Reported Weights of Air Pollutants Collected by Filteration,"
presented at "the 60th Annual Meeting of the Air Pollution Control
Association, Cleveland, Ohio, June 11-16, 1967.
7. C. D. Robson and K. E. Foster, "Evaluation of Air Particulate
Sampling Equipment," American Industrial Hygiene Association Journal
2J3, pp. 404-410, 1962.
8. John S. Henderson, "A Continuous-Flow Recorder for the High-Volume
Air Sampler," presented at the 8th Conference on Methods in Air
Pollution and Industrial Hygiene Studies, Oakland, California,
February 6-8, 1967.
9. Walter K. Harrison et al., "Constant Flow Regulators for the High-
Volume Air Sampler," American Industrial Hygiene Association Journal
21., pp. 115-120, 1960.
10. Kendall, M. B., The Advanced Theory of Statistics, Vol. I, p. 148-151,
Charles Griffic & Company, Ltd., 1948.
115
-------
RULES AND REGULATIONS
8191
APPENDIX A
REFERENCE METHOD FOR THE DETERMINATION OF
SUSPENDED PARTICULATES IN THE ATMOSPHERE
(HIGH VOLUME METHOD)
Reproduced from Apperidix B, "National Primary and Secondary
Ambient Air Standards," Federal Register, Vol 36, No. 84, Part II,
Friday, April 30, 1971.
APPENDIX B—RERKENCE MRHOD FOB THE
DXTEBUINATIOH Of SUSPENDS) PARTICULATES
IN THE ATlfOSPHER* (HIGH VOLUME
METHOD)
1. Principle and .Applicability.
1.1 Air la drawn Into a covered bousing
and through a filter by means of a high-flow-
rate blower at a flow rate (1.13 to 1.70 m.V
mln.; 40 to 80 ft.Vmln.) that allows sus-
pended particles having diameters of less
than 100 Mm. (Stokes equivalent diameter)
to pass to the filter surface. (1) Particles
within the size range of 100 to 0.1/i by 14 In.).
S.I.3 Rotameter. Marked In arbitrary
units, frequently 0 to 70, and capable of
being calibrated. Other devices of at least
comparable accuracy may be used.
FEDERAL REGISTER, VOL. 36, NO. 84—FRIDAY, APRIL 30, 1971
A-l
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8192
RULES AND REGULATIONS
8.1.4 Orifice Calibration Unit. Conflating
of a metal tube 7.8-cm. (3 in.) ID and 16.8
cm. (8% in.) long with • «t»ttc pressure tap
S.I cm. (3 in.) from one end. See Figure
B3. The tube end nearest the preaniie tap Is
flanged to about 10.8 cm. (4ft In.) OD with
a male thread of the game alee as tne Intot
end of the high-volume air sampler. A tingle
metal plate 9.3 cm. OH In.) In diameter and
0.24 cm. (Hj in.) thick with a central orifice
3.8 cm. (1ft in.) in diameter IB held In place
at the air inlet end with a female threaded
ring. The other end of the tube IB flanged to
hold a loose female threaded coupling, which
screws onto the Inlet of the sampler. An 18-
hole metal plate, an integral part of the unit.
Is positioned between the orifice and sampler
to simulate the resistance of a clean glass-
fiber Biter. An orifice calibration unit is
shown in Figure B3.
6.1.6 Differential Manometer. Capable of
measuring to at least 40 cm. (16 in.) of
water.
6.1.6 Positioe Displacement titter. Cali-
brated In cubic meters or cubic feet, to be
used as a primary standard.
5.1.7 Barometer. Capable of measuring at-
mospheric pressure to the nearest mm.
6.2 Analysis.
6.2.1 Filter Conditioning Environment.
Balance room or desiccator maintained at
15* to 36*C. and less than 50 percent relative
humidity.
6.2.2 Analytical Balance. Equipped with
a weighing chamber designed to handle un-<
folded 20.3 by 26.4 cm. (8- by 10-ln.) filters
and having a sensitivity of 0.1 mg.
8.2.3 Light Source. Frequently a table of
the type used to view X-ray films.
8.2.4 Numbering Device. Capable of print-
ing identification numbers on the filters.
6. Reagents.
6.1 Filter Media. Glass-fiber filters having
a collection efficiency of at least 09 percent
for particles of 0.3 am. diameter, as measured
by the DOP test, are suitable for the quanti-
tative measurement of concentrations of sus-
pended participates, (5) although some other
medium, such as paper, may be desirable for
some analyses. If a more detailed analysis is
contemplated, care must be exercised to use
filters that contain low background concen-
trations of the pollutant being investigated.
Careful quality control is required to deter-
mine background values of these pollutants.
7. Procedure.
7.1 Sampling.
7.1.1 Filter Preparation. Expose each filter
to the light source and Inspect for pinholee,
particles, or other Imperfections. Filters with
visible Imperfections should not be used. A
small brush Is useful for removing particles.
Equilibrate the filters in the filter condition-
ing environment for 34 hours. Weigh the
niters to the nearest milligram; record tare
weight and filter Identification number. Do
not bend or fold the filter before collection
of the sample.
7.1.2 Sample Collection. Open the shelter,
loosen the wing nuts, and remove the face-
plate from the filter holder. Install a num-
bered, prewelghed, glass-fiber filter In posi-
tion (rough side up), replace the faceplate
without disturbing the niter, and fasten
securely. Undertlghtenlng will allow air leak-
age, overtightenlng will damage the sponge-
rubber faceplate gasket. A very light applica-
tion of talcum powder may be used on the
sponge-rubber faceplate gasket to prevent
the filter from sticking. During Inclement
weather the sampler may be removed to a
protected area for filter change. Close the
roof of the shelter, run the sampler for about
6 minutes, connect the rotameter to the
nipple on the back of the sampler, and read
the rotameter ball with rotameter in a verti-
cal position. Estimate to the nearest whole
number. If the ball is fluctuating rapidly,
tip the rotameter and slowly straighten it
until the ball gives a constant reading. Dis-
connect the rotametcj from the nipple; re-
cord the Initial rotameter trading and the
starting time and date on the filter folder.
(The rotameter should nover be connected
to the sampler except when the flow is being
measured.) Sample for 34 noun from mid-
night to midnight and take a final rotameter
reading. Record the final rotameter reading
and ending time and date on th* filter folder.
Remove the faceplate as described above and
carefully remove the filter from the holder,
touching only the^outer edges. Fold the filter
lengthwise BO that only surfaces with col-
lected partlculates are In contact, and place
In a manlla folder. Record on the folder the
filter number, location, and any other factors,
such as meteorological conditions or razing
of nearby buildings, that might affect the
results. If the sample Is defective, void it at
this time. In order to obtain a valid sample,
the nigh-volume sampler must be operated
with the same rotameter and tubing that
were used during Its calibration.
7.3 Analysis. Equilibrate the exposed fil-
ters for 34 hours in the filter conditioning
environment, then rewelgh. After they are
weighed, the filters may be saved for detailed
chemical analysis.
7.3 Maintenance.
7.3.1 Sampler Motor. Replace brushes
before they are worn to the point where
motor damage can occur.
7.3.3 Faceplate Gasket. Replace when the
margins of samples are no longer sharp. The
gasket may be sealed to the faceplate with
rubber cement or double-sided adhesive tape.
7.3.3 Rotameter. Clean as required, using
alcohol.
8. Calibration.
8.1 Purpose. Since only a small portion
of the total air sampled passes through the
rotameter during measurement, the rotam-
eter must be calibrated against actual air-
flow with the orifice calibration unit. Before
the orifice calibration unit can be used to
calibrate the rotameter, the orifice calibra-
tion unit Itself must be calibrated against
the positive displacement primary standard.
, 8.1.1 Orifice Calibration Unit. Attach the
orifice calibration unit to the intake end
of the positive displacement primary stand-
ard and attach a high-volume motor blower
unit to the exhaust end of the primary
standard. Connect one end of a differential
manometer to the differential pressure tap
of the orifice calibration unit and leave the
other end open to the atmosphere. Operate
the high-volume motor blower unit so that
a series of different, but constant, airflows
(usually six) are obtained for definite time
periods. Record the reading on the differen-
tial manometer at each airflow. The different
constant airflows are obtained by placing a
series of loadplates, one at a time, between
the calibration unit and the primary stand-
ard. Placing the orifice before the inlet re-
duces the pressure at the Inlet of the primary
standard below atmospheric; therefore, a
correction must be made for the Increase in
volume caused by this decreased inlet pres-
sure. Attach one end of a second differential
manameter to an inlet pressure tap of the
primary standard and leave the other open
to the atmosphere. During each of the con-
stant airflow measurements made above,
measure the true inlet pressure of the
primary standard with this second differen-
tial manometer. Measure atmospheric pres-
sure and temperature. Correct the measured
air volume to true air volume as directed In
9.1.1, then obtain true airflow rate, Q, as
directed In 9.1.3. Plot the differential manom-
eter readings of the orifice unit versus Q.
8.1.2 High-Volume Sampler. Assemble a
high-volume sampler with a clean filter In
place and run for at least 6 minutes. Attach
a rotameter, read the ball, adjust so that the
ball reads 66, and seal the adjusting mech-
anism so that it cannot be changed easily.
Shut off motor, remove the filter, and attach
the orifice calibration unit In Ita place. Op-
erate the high-volume sampler at a aeries of
different, but constant, airflows (usually six) .
Record toe reading of the differential ma-
nometer on the orifice calibration unit, and
record the readings of the rotameter at each
flew. Measure atmospheric pressure and tem-
perature. Convert the differential manometer
reading to m.Vmln., Q. then plot rotameter
reading versus Q.
8.1.3 Correction /or Differences in Pressure
or Temperature. See Addendum B.
9. Calculations.
9.1 Calibration of Orifice.
9.1.1 True Air Volume. Calculate the air
volume measured by the positive displace-
ment primary standard.
V. =
Vi = True air volume at atmospheric pres-
— sure, m.*
P. = Barometric pressure, mm. Hg.
Po, = Pressure drop at inlet of primary
standard, mm. Hg.
VM = Volume measured by primary stand-
ard, m.'
9.1.2 Conversion Factors.
Inches Hg. x 26.4 = mm. Hg.
Inohea water x 73.48 x 10-*= inches Hg.
Cubic feet air X 0.0284 = cubic meters air.
9' 1.3 True Airflow Rate.
V.
Q=—
T
Q=Plow rate, m.Vmln.
T=Tune of flow, mm.
9.2 Sample Volume.
9.2.1 Volume Conversion. Convert the Ini-
tial and final rotameter readings to true
airflow rate, Q, using calibration curve of
8.1.2.
9.2.2 Calculate volume of air sampled
V = -
XT
V = Air volume sampled, m.3
Qi = Initial airflow rate, m.Vmln.
Qt = Final airflow rate. m.Vmln.
T= Sampling time, mln.
9.3 Calculate mass concentration of sus-
pended particulates
(W«-WO X10«
. S.P. = -
V
S.P. = Mass concentration of suspended
partlculates, pg/m.*
Wi = Initial weight of filter, g.
W r = Final weight of filter, g.
V= Air volume sampled, m.1
10*= Conversion of g. to n%.
10. References.
(1) Robson, C. D, and Foster, K. E.,
"Evaluation of Air Paniculate Sam-
pling Equipment", Am. Ind. Hyg.
Assoc. J. 24. 404 (1963).
(2) Tlerney, O. P., and Conner, W. D.,
"Hygroscopic Effects on Weight Deter-
minations of Partlculates Collected on
Olass-Plber Filters", Am. Ind. Hyg.
Assoc. J. 28. 863 (1967).
(3) Unpublished data based on a collabora-
tive test Involving 13 participants,
conducted under the direction of the
Methods Standardization Services Sec-
tion of the National Air Pollution Con-
trol Administration. October, 1970.
(4) Harrison, W. K., Nader, J. S., and Fug-
man, F. S., "Constant Flow Regulators
for High-Volume Air Sampler", Am.
tnd. Hyg. Assoc. J. 21, 114-130 (1960).
FEDERAL REGISTER, VOL. 36, NO. 84—FRIDAY, APRIL 30, 1971
A-2
-------
MJUS AND REGULATIONS
8193
(5) P»te. J. B., and Tabor. B. C.. "Analytical
Aspect* of the Use of Olass-mber Fil-
ter* for the Collection and Analysis of
Atmospheric Paniculate Matter". Am.
/tut. Hyf- Atsoc. J. 23. 144-160 (1882).
ADDENDA
A. Alternative equipment.
A modification of the high-volume sampler
Incorporating a method for recording the
actual airflow over the entire sampling-pe-
riod has been described, and Is acceptable
for measuring the concentration of sus-
pended particulars (Henderson. J. S., Eighth
Conference on Methods in Air Pollution and
Industrial Hygiene Studies, 1987, Oakland,
Calif.). This modification consists of an ex-
haust orifice meter assembly connected
through a transducer to a system for con-
tinuously recording airflow on a circular
chart. The volume of air sampled Is cal- .
culated by the following equation:
V = QXT.
Q=Average sampling rate. m.-Vmln.
T=Sampling time, minutes.
The average sampling rate, Q, Is determined
from the recorder chart by estimation if the
flow rate does not vary more than 0.11 m.V
mln. (4 ft.Vmln.) during the sampling pe-
riod. If the flow rate does vary more than
0.11 m.« (4 ft.Vmln.) during the sampling
period, read the flow rate from the chart
at 2-hour Intervals and take the average.
B. Pressure ami Temperature Corrections.
If the pressure or temperature during
high-volume sampler calibration is substan-
tially different from the pressure or tempera-
ture during orifice calibration, a correction
of the flow rate, Q, may be required. If the
pressures dlfler by no more than 16 percent
' and the temperatures differ by no more than
100 percent (°C). the error in the un-
corrected flow-rate will be no more than 16
•percent. If necessary, obtain the corrected
flow rate as directed below. This correction
applies only to orifice meters having a con-
stant orifice coefficient. The coefficient for
the calibrating orifice described In 6.1.4 has
been shown experimentally to be constant
over the normal operating range of the high-
volume sampler (0.6 to 2.2 m.Vmln.; 20 to 78
ft.Vmln.). Calculate corrected flow rate:
^'[TTr-;]"1
Qi=Corrected flow rate, m.Vmln.
Q,=Plow rate during high-volume sampler
calibration (Section 8.1 .2), m.Vmln.
T,=Absolute temperature during orifice
unit .calibration (Section 8.1.1), *K
or -H.
P!=Barometric pressure during orifice unit
calibration (Section 8.1.1), mm. Hg.
T»=Absolute temperature during high-
volume sampler calibration (Section
8.1.3), °K or -R.
Pa=Barometric pressure during high-vol-
ume sampler calibration (Section
8.1.2), mm. Hg.
ADAPTER
MOUNTING MOTOR
PLATE OAIKCT
e Bl. Exploded view ol typical hlfirvvoluflw air Mmpler parts
No. 84—Ft. n 3
FEDERAL UCISTII, VOL. 36, NO. 84—WIOAV, APRIl 30, 1971
A-3
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8194
RULES AND REGULATIONS
Figure B2. Assembled sampler and shelter.
ORIFICE
RESISTANCE PLATES
Figure B3. Orifice calibration unit.
FEOfHAL KGISTft, VOL 36, NO. 64—FRIDAY, APIIL 30, 1971
A-4
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BIBLIOGRAPHIC DATA
SHEET
1. Report No.
EPA-R4-73-028b
3. Recipient's Accession No.
4. Title and Subtitle
GUIDELINES FOR DEVELOPMENT OF A QUALITY ASSURANCE PROGRAM
Reference Method for the Determination of Suspended Particulate
in the Atmosphere (High Volume Method)
5. Report Date
June 1973
6.
7. Author(s)
Franklin Smith and A Carl Nelson, Jr.
8. Performing Organization Kept.
No.
9. Performing Organization Name and Address
Research Triangle Institute
Research Triangle Park, North Carolina
10. Project/Task/Work Unit No.
27709
11. Contract/Grant No.
EPA- Durham
68-02-0598
12. Sponsoring Organization Name and Address
Environmental Protection Agency
National Environmental Research Center
Research Triangle Park, North Carolina 27711
13. Type of Report & Period
Covered interim Contrac
Report - Field document
14.
15. Supplementary Notes
16. Abstracts
Guidelines for quality control of ambient suspended particulate measurements by
the Federal reference method are presented.. These include:
1. Good operating practices
2. Directions on how to assess data and qualify data
3. Directions on how to identify trouble and improve data quality
4. Directions to permit design of auditing activities
5. Procedures which can be used to select action options and relate them
to costs
This document is not a research report. It is designed for use by operating personnel
17. Key Words and Document Analysis. 17a. Descriptors
Quality Assurance
Quality Control
Air Pollution
Quantitative Analysis
Aerosols
17b. Identifiers/Open-Ended Terms
17c. COSAT1 Field/Group
18. Availability Statement
19.. Security Class (This
Report)
UNCLASSIF1
20. Security Class (This
Page
UNCLASSIFIED
21. No. of Pages
130
22. Price
FORM NTIS-3S (REV. 3-72)
USCOMM-DC MOS2-P72
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